انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Investigation of water hardness removal efficiency using kaolinite modified with sodium dodecylbenzene sulfonate بررسی راندمان حذف سختی آب با استفاده ازکائولینیت اصلاح شده با سدیم دودسیل بنزن سولفونات 10511 10522 230563 10.22034/jess.2024.467067.2270 FA مریم آهنکوب گروه زمین شناسی، دانشگاه پیام نور، ایران 0000-0002-9941-7927 گشتاسب مردانی مرکز سلولی ملکولی،پژوهشکده پایه سلامت،دانشگاه علوم پزشکی شهرکرد،شهرکرد، ایران Journal Article 2024 07 09 This study investigates and compares the use of raw kaolinite and kaolinite modified with sodium benzene dodecyl sulfonate in removing water hardness. To prepare modified kaolinite, first wash raw kaolinite three times with distilled water to remove surface contaminants and then dry it in a ceramic pot for 5 hours at 100 °C and 2 grams of kaolinite are extracted. Weigh on a precision balance and add 200 ml of sodium dodecyl benzene sulfonate solution with a concentration of 4 mmol/L and stir by magnetic stirrer for 90 minutes to absorb sodium dodecyl benzene sulfonate by calcium phosphate. The kaolinite precipitate is obtained and the supernatant is discarded. The precipitate is dried in an oven and the bonding between kaolinite and sodium dodecyl benzene sulfonate is examined by titration with sodium hydroxide, and finally the resulting particles are examined by XRD. Then, synthetic solutions of calcium carbonate and magnesium carbonate will be prepared as hard water samples at concentrations of 100, 200 and 500 mg/L and with a volume of 500 mL in three 1-L reactors, followed by raw and modified kaolinite adsorbents. was used to determine the removal rate of these carbonates. . The results obtained indicate the removal of water hardness (calcium carbonate and magnesium carbonate) at concentrations of 100, 200 and 500 by both raw kaolin and kaolin dodecyl benzene sulfonate at concentrations of 0.3, 1 and 2 mg per liter. The dodecyl benzene sulfanate type has the highest hardness absorption. Introduction Water hardness and water-soluble solids lead to corrosion or sedimentation in water distribution pipes, which in addition to creating heavy economic costs leads to numerous health problems and user dissatisfaction and water wastage. Studies also show that water hardness affects cardiovascular mortality, growth retardation, reproductive failure and other health problems. Among the types of clay soils, kaolin has a high potential in removing pollutants from the aquatic environment. Kaolinite is the most important mineral component of kaolin, which has received great attention as an adsorbent due to its high adsorption capacity, large specific surface area and good physical and chemical stability. will bring. Several studies have been conducted on the removal of water hardness by natural kaolinite or kaolinite modified with hydrochloric acid and sodium, but no study has been conducted on the removal of water hardness by kaolinite modified with sodium benzene dodecyl sulfonate. This is therefore addressed in this study. Materials and methods First, the modified kaolinite was prepared with the help of sodium dodecylbenzene sulfonate and raw kaolinite, and then a solution consisting of calcium carbonate and magnesium carbonate in a volume of 500 mL with three concentrations of 100, 200 and 500 mg/liter was prepared in three volumes of 1 liter. Then, raw and modified kaolinite with 3 different doses will be added to the solution and stirred at 150 rpm. Every 15 minutes, 20 ml of sample will be taken from the solution and the hardness of calcium and magnesium will be examined by titration. became. Finally, the results were analyzed. Results and discussion Initially, kaolinite modified with sodium dodecylbenzene sulfonate was prepared. Then, synthetic solutions of calcium carbonate and magnesium carbonate were prepared as hard water samples. In the third step, the titration of the solutions was carried out, and then. Calcium and magnesium hardness measurements were performed. To determine the calcium removal rate, a synthetic calcium carbonate solution was first prepared as a hard water sample containing calcium carbonate and magnesium carbonate with concentrations of 100, 200 and 500 mg/L and a volume of 500 mL in three 1-L reactors. The dose of sodium dodecyl benzene sulfonate-modified absorbent is 30 mg, 1 g and 2 g. All the above steps were performed on magnesium and calcium 100, 200, 500 samples in order to compare the absorption rate of calcium ions by the two types of kaolinite. Conclusion Based on the results of the analyzes obtained from the laboratory samples of the removal of water hardness (calcium carbonate and magnesium) by raw kaolin and kaolin dodecyl benzene sulfonate, it can be acknowledged that both kaolin show very good performance in hardness removal and between the two kaolin Kaolin of the dodecylbenzene type shows a much higher efficiency in removing both magnesium and calcium hardness. This removal is much higher at high kaolin concentrations. Thus, at a concentration of 1 mg per liter of kaolin, the hardness removal rate is higher than at a concentration of 0.3 mg per liter and hardness removal at a concentration of 2 mg per liter is higher than the other two concentrations. Karlsson Faudot, É. 2021.Investigation of sustainable methods to reduce water hardness in drinking water treatment plants. Kusrini, E. et al. 2020. Application of activated Na-zeolite a as a water softening agent to remove Ca۲+ and Mg۲+ ions from water. AIP Conference Proceedings. Mafi, A. Khayati, G. 2021. Evaluation of Water Softening with the Removal of Calcium Ion by Ion Flotation Approach. Korean Chemical Engineering Research. Vol. 59. P.24-219. Nasrollahi, Y., et al. 2019. Investigation of Water Hardness Reduction (Ca+ Mg) using Strong Cationic Resins. Iranian Journal of Soil and Water Research. .Vol. 50. P. 50-1341. Ni, X. et al. 2021.The adsorptive behaviour of kaolinite to sodium dodecyl benzene sulphonate and the structural variation of kaolinite. Scientific Reports. Vol. 11. P.1-9. Okpong, E. et al. 2020. Synthesis of Zeolite A from Aloji Kaolin to Investigate Its Performance in Hard Water Softening. Ronny, R. et al.2019. Banana Stem Charcoal as Adsorbents Reduce Water Hardness Levels. International Journal of Environment, Engineering and Education. Vol.1. P.1-6. Shahmirzadi, M.A.A, et al., 2018.. Significance, evolution and recent advances in adsorption technology, materials and processes for desalination, water softening and salt removal. Journal of environmental management. Vol 324. P. 44-215. Tang ,C., et al. 2021. Evaluation and comparison of centralized drinking water softening technologies: Effects on water quality indicators. Water Research. Vol. 203.P.117-439. Wahyuni, N. et al. 2021. Characterization of Hydrochloric Acid Activated Natural Kaolin and its application as adsorbent for Mg۲+. Journal of Physics: Conference Series. Wickramasuriya, A. Chandima Wickramasinghe Arachchige, R. Kottegoda, I. 2021. Characterization and Modification of Clay for Removal of Drinking Water Hardness. Mater Sci Res India. Vol. 318.P. 18-31. Zhao, L. et al. 2020. Adsorption of Cu (II) by phosphogypsum modified with sodium dodecyl benzene sulfonate. Journal of hazardous materials. Vol. 387. P. 121-808. در این مطالعه به بررسی و مقایسه استفاده از کائولینیت خام و کائولینیت اصلاح شده با سدیم بنزن دودسیل سولفونات در حذف سختی آب پرداخته شده است. برای تهیه کائولینیت اصلاح شده ، ابتدا کائولینیت خام را ۳ بار با آب مقطر شست و شو داده تا آلودگی های سطحی از بین برود و سپس درون یک بوته سرامیکی به مدت ۵ ساعت با دمای ۱۰۰ درجه سانتی گراد درون آون خشک میکنیم و ۲ گرم ازکائولینیت را برروی یک ترازوی دقیق وزن کرده و به آن ۲۰۰ میلی لیتر محلول سدیم دودسیل بنزن سولفونات با غلظت ۴ میلی مول در لیتراضافه کرده وتوسط همزن مغناطیسی به مدت ۹۰ دقیقه همزده میشود تا سدیم دودسیل بنزن سولفونات توسط کائولینیت جذب شود.سپس محلول را سانتریفیوژکرده تا رسوب کائولینیت حاصل شود و سوپرناتانت آن را دورمیریزیم. رسوب را درون آون خشک میکنیم و بررسی برقراری پیوند و اتصال بین کائولینیت و سدیم دودسیل بنزن سولفونات را از طریق تیتراسیون به کمک سدیم هیدروکسید انجام میدهیم و در نهایت ذرات حاصله توسط XRD بررسی شد. سپس محلول های سنتتیک کربنات کلسیم کربنات و منیزیم به عنوان نمونه آب سخت در غلظت های ۱۰۰, ۲۰۰ و ۵۰۰ میلی گرم بر لیتر و با حجم ۵۰۰ میلی لیتردر سه راکتور ۱لیتری تهیه شد و پس از ان از جاذب های کائولینیت خام و اصلاح شده برای تعین میزان حذف این کربناتها استفاده شد. . نتایج بدست آمده دال بر حذف سختی آب (کربنات کلسیم و کربنات منیزیم ) در غلظت 100، 200 و 500 توسط هر دو نوع کائولن خام و کائولن دودسیل بنزن سولفانات در غلظت‌های 3/0 ، 1 و 2 میلیگرم برلیتر می‌باشدکه در بین این دو کائولن تیپ دودسیل بنزن سولفانات دارای بیشترین جذب سختی را نشان می‌دهد.

https://www.jess.ir/article_230563_77679e27a590f67cf1758a97904ee92e.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Process and Economic Evaluation of Biomass Gasification for Syngas Production: Effective Parameters and Sensitivity Analysis ارزیابی فرایندی و اقتصادی فرایند گازی‌سازی باگاس برای تولید گاز سنتز: بررسی پارامترهای مؤثر و آنالیز حساسیت 10523 10533 230598 10.22034/jess.2025.520091.2371 FA مهدی صدیقی دانشیار، گروه مهندسی شیمی، دانشگاه قم، قم، ایران 0000-0003-2681-1357 کوشا امامی فارغ التحصیل کارشناسی ارشد مهندسی سیستم های انرژی، دانشکده فنی مهندسی، دانشگاه قم 0000-0003-2681-1357 Journal Article 2025 04 29 Population expansion and improvement in society drive a continuously rising need for energy. Depletion of finite fossil fuels and mounting pollution leading to global warming exacerbates damage to the environment. Under these circumstances, biomass gasification has been recognized globally as a promising technique. Syngas, being a product of gasification, consists of hydrogen, methane, carbon monoxide, and carbon dioxide. The subject of this paper is steam gasification with bagasse, a waste product of sugarcane production, as a feedstock. The simulation was carried out using Aspen Plus software by implementing the Boston-Mathias alpha function and Peng-Robinson cubic equation of state. The primary aim of this research paper is to gain the highest lower heating value (LHV) of syngas. Utilization of a carbon dioxide capture solvent in an absorption tower is proposed in this paper by adopting the steam gasification process. These processes aim at improving output properties and minimizing environmental impacts of energy generation. Sensitivity was done to ascertain crucial parameters like the gasifier's temperature and pressure and mass flow rate of steam into the reactor. Targets are to increase LHV of syngas and improve cold gas efficiency. With proper planning and accurate analysis, the LHV of syngas increased by 30.7% and cold gas efficiency by 36.1% compared to earlier research. Also, 95% of carbon dioxide released was captured and sequestered with this method. This study presented the prospects for biomass gasification as an alternative green energy option, preventing limitations of resources and environmental degradation. With optimization of the operating parameters, there were great improvements in syngas and process efficiency. Carbon dioxide capture additionally reduced environmental loads, resulting in cleaner energy systems. These developments served to illustrate the demand for advanced technologies in meeting increasing energy demands while mitigating the effects of climate change. EXTENDED ABSTRACT An extended abstract is a more detailed version of a regular abstract. It provides a comprehensive summary of a research paper, thesis, or presentation — often used in academic conferences and journals to give readers enough information to understand the scope and significance of the work without reading the full document. Structure : Includes the following sections: Introduction / Background : Explains the problem, context, and motivation. Objectives / Research Questions : What the study aims to achieve. Methodology : Brief description of methods, tools, or experimental setup. Results / Findings : Summary of key outcomes or discoveries. Discussion / Implications : Interpretation of results and their importance. Conclusion : Final thoughts and potential future work. The final results is based on the following: Research background and problem statement Theoretical framework or model developed Experimental design or simulation methodology Data analysis techniques Key results and performance indicators Practical or theoretical contributions Limitations and future research directions Introduction The extraction of energy resources using fossil fuels has caused several adverse impacts on the environment, such as pollution and global warming. Carbon-neutral and readily available forms of energy, including biomass derived from industrial and agricultural waste, can solve the above issue. Biomass materials, such as sugar cane, offer additional value due to their lower lignin content, higher glucose levels, and suitability for syngas production via gasification. The process of gasification, modeled using the Aspen Plus software, converts carbon-rich raw materials at elevated temperatures into syngas. Prior research works have acknowledged the role of gasification in improving energy efficiency and mitigating environmental issues. This research optimizes bagasse gasification operational parameters to offer better syngas quality while reducing emissions, and also assesses the economic considerations of the process, proving that bagasse gasification can be an effective renewable energy source. Materials and methods A sensitivity analysis of the gasification process was conducted with respect to the four key components of syngas—namely, hydrogen, methane, carbon monoxide, and carbon dioxide—and three key parameters that dictate reactor performance: temperature, pressure, and inlet steam flow rate. Initially, the optimization of these parameters was carried out to maximize the production of syngas, while at the same time minimizing associated production costs. Finally, the economic viability of the process at the established optimum points was examined to ensure that both technical efficacy and affordability were achieved within the scope of the study. Results and discussion In this study, a sensitivity analysis of the gasification process was conducted, focusing on the four primary syngas constituents (hydrogen, methane, carbon monoxide, and carbon dioxide) and three most significant parameters (temperature, pressure, and steam flow rate). Hydrogen and carbon monoxide yields were optimized at 850°C in the temperature optimization. Any increase above this temperature subjects the reactor to clogging via sintering reactions. At pressure optimization, 1 bar was found to be the optimum; higher pressure reduced cold gas efficiency and enhanced the formation of carbon dioxide and methane as by-products. The steam flow rate was optimized at 3500 kg/h, balancing reduced hydrogen formation with negligible carbon dioxide production, with little impact on cold gas efficiency. These results maximize gasification efficiency while minimizing cost repercussions. Conclusion In this study, the results showed that pre-drying bagasse prior to use significantly improved reactor efficiency and reduced fuel consumption by eliminating moisture content and therby preventing a rise in combustion temperature in the reactor. Additionally, the hydrogenation tower of sulfur recovers sulfur (91 kg/hr) and boosts the production of hydrogen (from 140 to 190 kg/hr) via the desulfurization of syngas and suppression of undesired side reactions. Sensitivity analyses identified the optimum bagasse and inlet steam flow rates at 15,000 kg/hr and 3,500 kg/hr, respectively, which maximize high-quality syngas production. The gasifier reactor is operated at 850°C and 1 bar with no appreciable tar and heavy hydrocarbon formation. Under these parameters, the reactor produces 1,176 kg/hr of hydrogen, 88 kg/hr methane, 12,952 kg/hr carbon monoxide, and 841 kg/hr carbon dioxide. Two significant parameters, cold gas efficiency, and LHV of syngas were contrasted. Results, as against those established by Motaz et al. [22], present improved cold gas efficiency by 30% and LHV of 4.66 MJ/kg syngas. Also, the design of a carbon capture tower re-captures 95% of the carbon dioxide produced, and this reduces the environmental impact of the process significantly. Removal of impu- red compounds also increases the LHV of the syngas to 1.77 MJ/kg. با افزایش جمعیت و پیشرفت بشر، نیاز به انرژی پیوسته درحال‌رشد است. مصرف سوخت‌های فسیلی، علاوه بر محدودیت منابعشان، یکی از عوامل اصلی تولید آلاینده‌های زیست‌محیطی و گرمایش تدریجی زمین به شمار می‌رود. در این میان، گازی‌سازی زیست‌توده در سطح جهان به‌عنوان فرایندی با آینده‌ای روشن مطرح شده است. محصول این فرایند، گاز سنتز نام دارد که ترکیبی از هیدروژن، متان، کربن مونوکسید و کربن‌دی‌اکسید است. در این پژوهش باگاس که ضایعات کشاورزی صنعت تولید شکر از نیشکر است، به‌عنوان خوراک فرایند گازی‌سازی در نظر گرفته شده است. این فرایند در نرم‌افزار اسپن پلاس با استفاده از معادله حالت مکعبی پنگ رابینسون با تابع آلفای بوستون - ماتیاس شبیه‌سازی شد. هدف اصلی این پژوهش بیشینه‌کردن حداقل ارزش حرارتی گاز سنتز است. در این مقاله به‌کارگیری بخار آب به‌عنوان عامل گازی ساز و استفاده از برج جاذب کربن برای جذب دی‌اکسیدکربن تولیدی طراحی شد تا کیفیت تولید افزایش و اثرات زیست‌محیطی کاهش پیدا کنند. پارامترهای تعیین‌کننده بر اساس تحلیل حساسیت، شامل دمای رآکتور گازی ساز، فشار رآکتور گازی ساز، و دبی جرمی بخار ورودی به رآکتور گازی ساز تعیین شده است. هدف از این فرایند، افزایش حداقل ارزش حرارتی و راندمان گاز سرد است. با انجام طراحی و تحلیل‌های دقیق، حداقل ارزش حرارتی گاز سنتز تولیدی به میزان 7/30% و راندمان گاز سرد به میزان 1/36% نسبت به مطالعات قبلی افزایش یافته است. در این فرایند، 95% کربن دی‌اکسید تولیدی جذب و ذخیره‌سازی می‌شود.

https://www.jess.ir/article_230598_91cdae6cf5ce5d387a964fea1d12e139.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Prediction of Bed load Transport Rate into Lateral Intakes in Bend Channels Using Hybrid Machine Learning and Discrete Phase Numerical Modeling پیش بینی نرخ انتقال بار بستر ورودی به آبگیرهای جانبی واقع در کانال های قوسی با استفاده از ترکیب مدل های یادگیری ماشین و مدل عددی فاز گسسته 10534 10548 230603 10.22034/jess.2025.523286.2375 FA حسین منتصری دانشکده مهندسی، گروه مهندسی عمران، دانشگاه یاسوج 0000-0001-5117-0462 حمید نجاتی دانشکده مهندسی، دانشگاه یاسوج 0009-0009-6270-7603 Journal Article 2025 05 13 Subsequently, the calibrated numerical model was implemented for lateral intake at 31 positions of the external bend from the section of 10 to 140 degrees of the bend with 5-degree intervals and with 5 diversion angles of 10, 30, 50, 70, and 90 degrees and three intake discharge ratios of 20%, 30%, and 40%, and the percentage of sediment diverted to the lateral intake was determined for each model. The results were used as necessary data for training and validation of various neural network models. Next, by extracting the results, using 70% of the data, a meta-model was trained using the multi-layer artificial neural network (MLP), radial basis function network (RBF), generalized regression neural network (GRNN), and support vector regression (SVR) models, and its accuracy was evaluated using a part of the data that was not used in the training phase. The accuracy of the results of the aforementioned model in terms of the error index of the mean absolute magnitude of the relative error in the validation period (3.6%) indicates the better ability of the SVR neural network model in predicting the amount of sediment input to the lateral intakes. Materials and methods - Laboratory and numerical model In the present study, first, using a discrete phase numerical model, the sediment transport phenomenon in a 180-degree curved channel with a lateral intake was simulated, and the sediment transport mechanism and the amount of sediment entering the intake under different hydraulic conditions were investigated (Tavakoli et al., 2019). To verify the numerical model, the results of the laboratory study by Montaseri (2008) were used. This model includes a U-shaped channel with an average radius of 2.6 m and a width of 0.6 m. - Artificial Neural Network Models Artificial neural networks, inspired by the human body's neural network, are composed of components called neurons and include the following: - Multilayer Neural Network (MLP) model - Radial Basis Function (RBF) networks - Generalized Regression Neural Network (GRNN) - Support Vector Regression (SVR) Results and discussion The analysis of different artificial neural network models in predicting the amount of sediment entering the lateral catchment in a U-shaped arched channel reveals that the support vector regression (SVR) model achieved the highest correlation coefficient (R² = 0.982) between observed and predicted data. The radial basis function (RBF) model followed closely with an R² value of 0.98, while the multilayer perceptron (MLP) and general regression neural network (GRNN) models exhibited R² values of 0.976 and 0.949, respectively. Conclusion In this study, based on the data obtained from the calibrated numerical model, a metamodel was used in different neural network models to predict the amount of sediment entering the lateral intakes in the U-shaped arched channel, and different architectures of neural network models were examined. The results show that the best multilayer neural network architecture with two hidden layers and 5 neurons in the first hidden layer and 5 neurons in the second hidden layer was obtained. The best RBF neural network architecture was obtained with a Spread value of 0.25. The best GRNN neural network architecture was obtained with a Spread value of 5. The results show that the SVR model has the maximum correlation coefficient (R2) with the observational data. Therefore, it is recommended to use the support vector regression model to predict the sediment entering the lateral intakes. In this study, a predictive metamodel based on the Fluent numerical model and various artificial neural network models is presented to estimate the amount of sediment diverted to lateral catchments located in river bends based on input data including the catchment location, catchment deviation angle, and percentage of inflow. In the first step, using the discrete phase two-phase model in Fluent, the sediment transport phenomenon was simulated in a 180-degree curved channel with a lateral catchment located at a position of 115 degrees from the outer bend and with a deviation angle of 45 degrees, and the results were calibrated with laboratory data. Subsequently, the calibrated numerical model was implemented at 31 positions of the outer bend from a section of 10 to 140 degrees of the bend with 5-degree intervals and with 5 intake angles of 10, 30, 50, 70, and 90 degrees and three intake discharges of 20%, 30%, and 40%, and the percentage of sediment diverted to the lateral catchment was determined for each model. The results were used as necessary data for training and validation of various neural network models. Next, by extracting the results, using 70% of the data, a meta-model was trained using the models of multilayer artificial neural network (MLP), radial branch neural network (RBF), generalized regression neural network (GRNN), and support vector regression (SVR), and its accuracy was evaluated using a part of the data that was not used in the training phase. The accuracy of the results of the aforementioned model in terms of the error index of the mean absolute magnitude of the relative error in the validation period (3.6%) indicates the better ability of the SVR neural network model in predicting the sediment input to the lateral catchment. In this study, a predictive metamodel based on the Fluent numerical model and various artificial neural network models is presented to estimate the amount of sediment diverted to lateral catchments located in river bends based on input data including the catchment location, catchment deviation angle, and percentage of inflow. In the first step, using the discrete phase two-phase model in Fluent, the sediment transport phenomenon was simulated in a 180-degree curved channel with a lateral catchment located at a position of 115 degrees from the outer bend and with a deviation angle of 45 degrees, and the results were calibrated with laboratory data. Subsequently, the calibrated numerical model was implemented at 31 positions of the outer bend from a section of 10 to 140 degrees of the bend with 5-degree intervals and with 5 intake angles of 10, 30, 50, 70, and 90 degrees and three intake discharges of 20%, 30%, and 40%, and the percentage of sediment diverted to the lateral catchment was determined for each model. The results were used as necessary data for training and validation of various neural network models. Next, by extracting the results, using 70% of the data, a meta-model was trained using the models of multilayer artificial neural network (MLP), radial branch neural network (RBF), generalized regression neural network (GRNN), and support vector regression (SVR), and its accuracy was evaluated using a part of the data that was not used in the training phase. The accuracy of the results of the aforementioned model in terms of the error index of the mean absolute magnitude of the relative error in the validation period (3.6%) indicates the better ability of the SVR neural network model in predicting the sediment input to the lateral catchment. این پژوهش به توسعه یک فرامدل ترکیبی پیشرفته می‌پردازد که مدل‌سازی عددی دوفازی را با الگوریتم‌های یادگیری ماشین تلفیق می‌کند تا نرخ رسوب انحرافی به آبگیرهای جانبی در قوس رودخانه‌ها را با دقت بالا پیش‌بینی نماید. مطالعه حاضر با در نظر گرفتن سه پارامتر کلیدی موقعیت آبگیر در طول قوس خارجی (10-140 درجه)، زاویه انحراف آبگیر (10-90 درجه) و درصد دبی آبگیری (40-20%)، یک چارچوب تحلیلی جامع را ارائه می دهد. ابتدا، با استفاده از مدل دوفازی فاز گسسته در نرم افزار Fluent، شبیه سازی پدیده انتقال رسوب در یک کانال قوسی 180 درجه با آبگیر جانبی که در موقعیت 115 درجه از قوس خارجی و با زاویه انحراف 45 درجه قرار دارد، صورت پذیرفته و نتایج حاصل با داده های آزمایشگاهی کالیبره گردیده است. در ادامه، در 31 موقعیت از قوس خارجی از مقطع 10 تا 140 درجه از قوس با فواصل 5 درجه و با 5 زاویه آبگیری 10، 30، 50، 70 و 90 درجه و سه دبی آبگیری 20%، 30% و 40% مدل عددی کالیبره شده، اجرا گردیده است و درصد رسوب انحرافی به آبگیر جانبی برای هر مدل تعیین گردید. نتایج حاصل به عنوان داده های لازم برای آموزش و صحت سنجی مدل های مختلف شبکه عصبی به کار برده شد. در ادامه با استفاده از 70 درصد داده های حاصل، یک فرامدل با استفاده از مدل‌های شبکه عصبی مصنوعی چند لایه (MLP)، شبکه عصبی شعاعی (RBF)، شبکه عصبی رگرسیون عمومی (GRNN) و رگرسیون بردار پشتیبان (SVR) آموزش داده شده و صحت آن توسط بخشی از داده‌هایی که در مرحله آموزش از آنها استفاده نشده، مورد ارزیابی قرار گرفت. دقت نتایج حاصل از مدل های مذکور بر اساس معیار ضریب همبستگی، نشان‌دهنده توانایی بهتر مدل شبکه عصبی SVR در پیش بینی مقادیر رسوب ورودی به آبگیر جانبی نسبت به سایر مدل ها می باشد.

https://www.jess.ir/article_230603_14a44184e153225aac09c814509d1426.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Analysis of the Phenomenon of Woody Plant Encroachment in the Context of Social-Ecological System Change تحلیل پدیده گسترش و غالبیت گیاهان چوبی در زمینه تغییر نظام اجتماعی - اکولوژیکی اکوسیستم 10549 10559 230611 10.22034/jess.2024.467516.2272 FA الهام قهساره اردستانی استادیار، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد 0000-0002-4740-7698 شهرام منصوری دانشجوی دکتری، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد حجت الله خدری غریبوند استادیار، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد 0000-0002-6673-8345 محسن بهمنی دانشیار، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد Journal Article 2024 07 13 The phenomenon of woody plant encroachment (WPE), which is characterized by the proliferation of woody vegetation in non-forested biomes such as grasslands, is a less well-known but equally important global trend. Grasslands cover more than 31% of the Earth's surface and are a significant part of global livestock production. To better understand and manage this phenomenon, it is essential to identify key drivers, feedbacks, and thresholds within a social-ecological system change framework. This study reviews recent and authoritative scientific articles related to woody plant expansion and dominance to explore the perspective of system change in social-ecological systems. The social-ecological system dynamics of both grass and woody plant communities are governed by competitive feedback loops (ecological and social processes) that work simultaneously to determine the vegetation cover. Identifying pivotal points in the form of feedback loops and direct and indirect local and global drivers is a key strength of the comprehensive social-ecological system change framework for effective management of grassland systems. Efficient management requires finding points in the system where changes will have the greatest benefit, which necessitates a better understanding of interactions between ecological and social systems. Future studies can address this. Introduction The process of deforestation, which is dominated by clearing of woody plants caused by natural and unnatural factors, has intensified. The phenomenon of woody plant encroachment (WPE), which is characterized by the proliferation of woody vegetation in non-forested biomes such as grasslands, is a less well-known but equally important global trend. Grasslands cover more than 31% of the Earth's surface and are a significant part of global livestock production. However, evidence suggests that these regions have been experiencing WPE over the past two centuries. Grasslands alternate between plant communities of grasses and woody plants. This shift in plant community structure, known as the phenomenon of WPE, has impacted ecosystem services globally. This phenomenon often occurs unexpectedly and is difficult to reverse. It requires a new framework to understand this phenomenon, one that recognizes WPE as a social-ecological system. Ecological components interact with social components through the provision of ecosystem services. Human decisions influence the receipt or non-receipt of key and valuable ecosystem services. To better understand and manage this phenomenon, it is essential to identify key drivers, feedbacks, and thresholds within a social-ecological system change framework. Materials and methods This study reviews recent and authoritative scientific articles related to woody plant expansion and dominance to explore the perspective of system change in social-ecological systems. Results and discussion The social-ecological system dynamics of both grass and woody plant communities are governed by competitive feedback loops (ecological and social processes) that work simultaneously to determine the vegetation cover. The feedback loops include balancing and reinforcing loops. The set of feedback loops that dominate the system at a given time determines the current system state. In grassland systems, the fire feedback loop is dominant. In contrast, woody plant systems are influenced by two reinforcing feedback loops: the climate-establishment feedback loop, which is prevalent in dry grasslands, and the fire-suppression feedback loop, which is likely to occur in wet grasslands. Fire suppression feedback is directly influenced by fire policies, which are related to regional population growth and urbanization. The drivers of woody plant expansion and dominance can be categorized into internal (plant density, grasshoppers, leaf-eaters, and soil moisture) and external (population growth and urbanization, land use changes, organizational arrangements, and global CO2 concentration) factors. These drivers play different roles in initiating, starting, and sustaining WPE, which is crucial for understanding and managing this phenomenon. The WPE is considered a structural change in social-ecological systems, focusing on the interactions between fundamental feedback processes, particularly the interactions between social and ecological processes. The analysis of existing studies indicates that humans have a local and global impact on grasslands and that this increasing shift from grass to woody plant communities may be largely related to population growth. Given the current preferences and consumption technologies, population growth is associated with increased demand for livestock production as a food source and increased CO2 emissions through various human activities. Additionally, there is a direct correlation between human population growth and fire suppression. All these factors have a greater impact on grassland systems, increasing the likelihood of WPE. Conclusion Identifying pivotal points in the form of feedback loops and direct and indirect local and global drivers is a key strength of the comprehensive social-ecological system change framework for effective management of grassland systems. Efficient management requires finding points in the system where changes will have the greatest benefit, which necessitates a better understanding of interactions between ecological and social systems. Future studies can address this. Introduction The process of deforestation, which is dominated by clearing of woody plants caused by natural and unnatural factors, has intensified. The phenomenon of woody plant encroachment (WPE), which is characterized by the proliferation of woody vegetation in non-forested biomes such as grasslands, is a less well-known but equally important global trend. Grasslands cover more than 31% of the Earth's surface and are a significant part of global livestock production. However, evidence suggests that these regions have been experiencing WPE over the past two centuries. Grasslands alternate between plant communities of grasses and woody plants. This shift in plant community structure, known as the phenomenon of WPE, has impacted ecosystem services globally. This phenomenon often occurs unexpectedly and is difficult to reverse. It requires a new framework to understand this phenomenon, one that recognizes WPE as a social-ecological system. Ecological components interact with social components through the provision of ecosystem services. Human decisions influence the receipt or non-receipt of key and valuable ecosystem services. To better understand and manage this phenomenon, it is essential to identify key drivers, feedbacks, and thresholds within a social-ecological system change framework. Materials and methods This study reviews recent and authoritative scientific articles related to woody plant expansion and dominance to explore the perspective of system change in social-ecological systems. Results and discussion The social-ecological system dynamics of both grass and woody plant communities are governed by competitive feedback loops (ecological and social processes) that work simultaneously to determine the vegetation cover. The feedback loops include balancing and reinforcing loops. The set of feedback loops that dominate the system at a given time determines the current system state. In grassland systems, the fire feedback loop is dominant. In contrast, woody plant systems are influenced by two reinforcing feedback loops: the climate-establishment feedback loop, which is prevalent in dry grasslands, and the fire-suppression feedback loop, which is likely to occur in wet grasslands. Fire suppression feedback is directly influenced by fire policies, which are related to regional population growth and urbanization. The drivers of woody plant expansion and dominance can be categorized into internal (plant density, grasshoppers, leaf-eaters, and soil moisture) and external (population growth and urbanization, land use changes, organizational arrangements, and global CO2 concentration) factors. These drivers play different roles in initiating, starting, and sustaining WPE, which is crucial for understanding and managing this phenomenon. The WPE is considered a structural change in social-ecological systems, focusing on the interactions between fundamental feedback processes, particularly the interactions between social and ecological processes. The analysis of existing studies indicates that humans have a local and global impact on grasslands and that this increasing shift from grass to woody plant communities may be largely related to population growth. Given the current preferences and consumption technologies, population growth is associated with increased demand for livestock production as a food source and increased CO2 emissions through various human activities. Additionally, there is a direct correlation between human population growth and fire suppression. All these factors have a greater impact on grassland systems, increasing the likelihood of WPE. Conclusion Identifying pivotal points in the form of feedback loops and direct and indirect local and global drivers is a key strength of the comprehensive social-ecological system change framework for effective management of grassland systems. Efficient management requires finding points in the system where changes will have the greatest benefit, which necessitates a better understanding of interactions between ecological and social systems. Future studies can address this. روند جنگل‌زدایی که پاکسازی گیاهان چوبی ناشی از عوامل طبیعی و غیرطبیعی در آن غالب است، شدت گرفته است. در صورتی که یک روند جهانی کمتر شناخته شده و به همان اندازه مهم، گسترش و چیرگی گیاهان چوبی (بوته‌ای، درختچه‌ای و درختی) در بیوم‌های غیرجنگلی از جمله علفزارها در حال وقوع است و ممکن است منجر به افزایش ترسیب کربن شود. علفزارها بیش از 31 درصد از سطح کره زمین و بخش عمده دامپروری جهان را به خود اختصاص می‌دهند. به منظور فهم و مدیریت بهتر این پدیده درک محرک‌های کلیدی، بازخوردها و آستانه‌ها در چارچوب تحلیل تغییر نظام اجتماعی-اکولوژیکی ضروری است. در نهایت این مطالعه با دیدگاه سیستم‌های اجتماعی-اکولوژیکی به راهبردهای مدیریتی مرتبط با آن اشاره می‌کند. این مطالعه با مرور مقالات علمی معتبر و جدید مرتبط به گسترش و چیرگی گیاهان چوبی به بررسی دیدگاه تغییر نظام در سیستم اجتماعی – اکولوژیکی می‌پردازد. پویایی سیستم اجتماعی - اکولوژیکی هر یک از این دو نظام گیاهان علفی و چوبی تحت غالبیت حلقه‌های بازخورد رقابتی (فرآیندهای اکولوژیکی و فرآیندهای اجتماعی) قرار دارند که به طور همزمان کار می‌کنند و نظام پوشش گیاهی را تعیین می‌کنند. امکان شناسایی نقاط اهرمی در قالب حلقه‌های بازخورد و محرک‌های مستقیم محلی و غیرمستقیم جهانی به روشی یکپارچه در یک تحلیل واحد نقطه قوت کلیدی چارچوب پایگاه داده تغییر نظام اجتماعی- اکولوژیکی اکوسیستم برای مدیریت موثر سیستم‌های علفزار است. در این راستا، مدیریت کارآمد نیاز به یافتن نقاطی در سیستم برای مداخله دارد جایی که تغییر در سیستم بیشترین سود را به همراه دارد که این امر نیاز به درک بهتری از تعاملات بین سیستم‌های اجتماعی و اکولوژیکی دارد که مطالعات آتی می‌توانند به این امر بپردازند.

https://www.jess.ir/article_230611_31325c934b12b1f010ba8a4583f4f03b.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 The long-term effects of different agricultural management practices on selected soil chemical properties تأثیر طولانی‌مدت مدیریت‌های مختلف کشاورزی بر برخی ویژگی‌های شیمیایی خاک 10560 10574 230845 10.22034/jess.2025.524920.2377 FA محمود ارژنگ نیا دانش‌آموخته کارشناسی ارشد علوم خاک، دانشکده کشاورزی، دانشگاه جیرفت، جیرفت، ایران. 0009-0006-4665-1038 قباد جلالی استادیار گروه علوم خاک، دانشکده کشاورزی، دانشگاه جیرفت، جیرفت، ایران 0009-0006-4665-1038 جواد زمانی استادیار گروه علوم خاک، دانشکده کشاورزی، دانشگاه جیرفت، جیرفت، ایران 0000-0002-9877-560X فریده عباس زاده افشار استادیار گروه علوم خاک، دانشکده کشاورزی، دانشگاه جیرفت، جیرفت، ایران 0000-0003-3448-1853 Journal Article 2025 05 20 Introduction Human interventions, particularly land-use changes and agricultural management practices, exert a profound and lasting influence on soil quality indicators. Numerous studies have demonstrated that such interventions can significantly alter soil physical and chemical properties. Practices like excessive application of chemical fertilizers often degrade soil quality, while appropriate management techniques such as conservation tillage, crop residue retention, and the use of organic or manure-based fertilizers can help maintain or even improve soil health. A thorough review of the global literature reveals that the effects of land-use change on soil characteristics are highly dependent on ecosystem type and climate conditions. For instance, findings from temperate and tropical humid ecosystems differ markedly from those observed in arid and semi-arid climates. Meta-analyses have shown that land-use change often has a more pronounced and enduring impact on soil organic carbon (SOC) than climatic variation alone, with reported declines in SOC reaching up to 30% in some cases. The conversion of natural ecosystems such as primary forests or grasslands into agricultural lands has also been associated with significant reductions in SOC, cation exchange capacity (CEC), and increases in soil salinity (EC). However, these impacts vary based on land-use history, soil type, and management intensity. While long-term land-use changes can lead to either beneficial or adverse outcomes, most evidence suggests that, in the absence of sustainable management, converting natural land to intensive agriculture typically accelerates soil degradation processes, including nutrient depletion, erosion, and reduced water-holding capacity. On the other hand, implementing sustainable agricultural practices may enhance certain soil quality indicators particularly when organic inputs are emphasized. These findings underscore the need for region-specific assessments, as generalizations from one ecological zone may not be valid in another. In this context, the Jiroft Plain an agriculturally vital region in southern Iran with a dry to semi-arid climate has received limited research attention regarding the impacts of land-use change on soil quality. Given its strategic importance in national food production, this study aims to investigate the long-term effects of different land-use types on key soil chemical properties in the Jiroft region, with the goal of informing sustainable soil and land management strategies. Materials and methods Geologically, the Jiroft Plain is situated within the Central Iranian sedimentary basin and is delineated from the Kavir Basin by the Jebalbarez mountain range, which trends northwest to southeast. Additionally, it forms part of the Bazzman-Sahand volcanic belt. The study area is geographically positioned at 28°35′14″N latitude and 57°48′14″E longitude. Within the Jiroft Plain, three agricultural zones characterized by distinct land-use types were selected: rangeland (non-cultivated land adjacent to agricultural areas), arable land (cultivated under an annual potato-onion rotation), orchards (citrus), and greenhouse cultivation (greenhouse cucumber). The selection of these sites was guided by two primary criteria: long-term land-use stability (no changes over several years) and a minimum of 20 years of continuous cultivation following the specified cropping system. For each land-use category, three composite soil samples were collected, each comprising ten subsamples taken from a standard soil depth. The analyses included determination of soil clay content via the hydrometer method, organic carbon content by the Walkley-Black method, soil pH in saturated paste, electrical conductivity in saturated extract, available phosphorus using the Olsen method, exchangeable potassium by the one-normal ammonium acetate method, and cation exchange capacity (CEC) through ammonium acetate and sodium acetate extractions. Sodium concentration in the saturated paste extract was measured using flame photometry, while calcium and magnesium concentrations were quantified by atomic absorption spectroscopy. Subsequently, the Sodium Adsorption Ratio (SAR) was calculated based on these measurements. Results and discussion The analysis of variance results demonstrated that land-use type exerted a statistically significant effect (at the 1% probability level) on all examined soil properties. Comparative analysis of mean pH values revealed that soils under arable and orchard land uses exhibited higher pH levels than those under greenhouse cultivation across all three study regions. Additionally, the comparison of mean values indicated that agricultural management practices, particularly greenhouse cultivation and the cultivation of onions and potatoes, significantly increased soil salinity compared to uncultivated lands in all regions. Furthermore, although soils under agricultural land uses displayed higher Sodium Adsorption Ratio (SAR) values than uncultivated soils across all study sites, this increase did not reach statistical significance. Organic carbon content varied substantially among the land uses, ranging from 0.06% to 1.34%, with the highest concentration observed in orchard soils within region 2 and the lowest in uncultivated soils in region 3. Cation exchange capacity (CEC) under different land uses ranged from 3.86 to 12.40 cmol(+) kg⁻¹, with orchard lands in region 2 exhibiting the highest values, while the lowest CEC was recorded in uncultivated soils in region 1. The studied land uses also had a significant positive impact on soil phosphorus and potassium contents. The elevated concentrations of these nutrients in greenhouse soils were primarily attributed to the intensive application of chemical fertilizers containing phosphorus and potassium, in contrast to the control (uncultivated) soils. Given phosphorus’s relative immobility in soil, it tends to accumulate rather than leach, especially under excessive fertilizer application aimed at increasing crop yield. The reduced phosphorus levels observed in uncultivated lands were attributed to the absence of fertilizer inputs. Notably, phosphorus toxicity has recently emerged as a challenge in certain greenhouses within the Jiroft region, imposing additional costs on farmers for soil remediation. Conclusion Land use and land management practices, particularly over the long term, lead to significant changes in soil properties. Addressing this issue across various regions of the country is essential to prevent uncontrolled soil degradation. Generally, natural land uses, due to the absence of soil disturbance, contribute more effectively to soil conservation compared to other land-use types. Although converting land to agricultural use may enhance certain soil characteristics such as organic matter content, cation exchange capacity, and even soil salinity this improvement does not necessarily imply the absence of soil degradation associated with such changes. The application of fertilizers, especially chemical fertilizers, in agricultural lands can lead to the accumulation of elements like phosphorus in the soil, necessitating careful monitoring. To safeguard soil health, appropriate land management practices must be adopted in the region’s agricultural lands. Furthermore, sustainable soil management in regional agriculture requires regular assessment of soil properties ideally at intervals of a few years to effectively evaluate the impacts of land-use changes. کیفیت خاک تحت تأثیر عوامل ذاتی مانند ماده مادری و شرایط اقلیمی قرار دارد، اما عوامل اکتسابی از جمله شیوه‌های مدیریت خاک و تغییرات کاربری اراضی نیز نقش مهمی در تعیین آن ایفا می‌کنند. بنابراین، شناخت دقیق تأثیرات این عوامل و تعامل بین آن‌ها برای دستیابی به مدیریت پایدار خاک ضروری است. پژوهش حاضر با هدف بررسی اثرات بلندمدت انواع مدیریت کشاورزی بر ویژگی‌های خاک در دشت جیرفت انجام گرفت. چهار نوع کاربری شامل اراضی کشت‌نشده (شاهد)، اراضی زراعی با تناوب کشت سیب‌زمینی و پیاز، اراضی باغی مرکبات و اراضی گلخانه‌ای انتخاب شدند. نمونه‌برداری از خاک سطحی در سه منطقه مختلف و با سه تکرار انجام شد. پارامترهای pH، هدایت الکتریکی (EC)، نسبت جذب سدیم (SAR)، کربن آلی، ظرفیت تبادل کاتیونی (CEC) و میزان فسفر و پتاسیم قابل جذب اندازه‌گیری گردید. نتایج نشان داد که روش‌های مختلف مدیریت کشاورزی تأثیر قابل توجهی بر ویژگی‌های خاک دارند. بیشترین مقدار pH در اراضی زراعی و باغی و کمترین در اراضی گلخانه‌ای مشاهده شد. همچنین، اراضی گلخانه‌ای و زراعی باعث افزایش معنادار هدایت الکتریکی خاک شدند که این موضوع بیانگر افزایش شوری و اثرات منفی احتمالی فعالیت‌های کشاورزی است. در مقابل، میزان کربن آلی در اراضی باغی و تا حدی در اراضی گلخانه‌ای نسبت به اراضی کشت‌نشده بالاتر بود. ظرفیت تبادل کاتیونی در اراضی باغی به طور معناداری بیشتر از سایر کاربری‌ها، به ویژه اراضی شاهد، بود که این پارامتر همبستگی مثبت و معناداری با درصد رس و ماده آلی خاک داشت. همچنین، فسفر و پتاسیم قابل جذب در خاک اراضی گلخانه‌ای و زراعی افزایش چشمگیری داشت که احتمالاً ناشی از مصرف بیشتر کودهای شیمیایی است. در مجموع، یافته‌ها نشان می‌دهد که تغییر کاربری اراضی و شیوه‌های مدیریت کشاورزی نقش مهمی در تغییر ویژگی‌های خاک دارند؛ بنابراین، پایش مستمر این پارامترها برای حفظ پایداری تولید کشاورزی امری حیاتی است.

https://www.jess.ir/article_230845_8d440770d379046d8437fccd8c76fa77.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Study on adsorption performance of different adsorbents in CO2/N2 separation مقایسه جذب سطحی تعادلی جاذب‌های مختلف در جداسازی /N2 CO2 10575 10582 230921 10.22034/jess.2025.496880.2382 FA بهنام رضازاده دانشجوی دکتری مهندسی شیمی، دانشکده مهندسی شیمی، دانشگاه صنعتی سهند 0009-0007-8764-5336 امین علمداری استادیار مهندسی شیمی، دانشکده فنی، دانشگاه ارومیه Journal Article 2025 06 04 Comparison of Equilibrium Adsorption of Different Adsorbents in the Separation of Carbon Dioxide from Nitrogen Behnam Rezazadeh1, Amin alamdari2* 1- Ph. D. Student of Chemical Engineering, Faculty of chemical Engineering, sahand University of Technology, Tabriz, Iran 2- Assistant Professor, Faculty of Engineering, Department of Chemical Engineering, Urmia University, Urmia, Iran *Corresponding Author Email: a.alamdari@urmia.ac.ir Abstract There are various adsorbents for the separation of nitrogen and carbon dioxide gases with different adsorption capacity and selectivity. A comprehensive comparison should be made between different adsorbents to select the appropriate adsorbent for a desired process. In this paper, the equilibrium adsorption value and selectivity of different adsorbents have been investigated using the Ideal Adsorption Solution Theory (IAST) to determine the appropriate adsorbent for the separation of nitrogen and carbon dioxide gases. The (IAST) model has been used to compare adsorbents at different pressures (1 to 100 kPa) and in a 50-50 percent composition to compare adsorbents in different gas percentage compositions (0.9-0.1) at a total pressure of 100 kPa. The results showed that the activated carbon/zeolite adsorbent has the highest selectivity at a temperature of 298 K and the KIT-6 adsorbent has the highest total adsorption. The studies showed that the Zeolite 13X adsorbent has lower selectivity and adsorption capacity than other adsorbents. Finally, a new trade-off diagram was prepared based on the adsorption rate versus selectivity of different adsorbents to guide researchers for use in industrial applications. Keywords Adsorption, Nitrogen, Carbon oxide, Ideal Adsorption Solution Theory (IAST) EXTENDED ABSTRACT Introduction CO2 emission from fossil fuel combustion is considered as one of the main issues of environmental problems and global warming has actuated the researches on CO2 separation from flue gas. However, various methods have been used to removing CO2 from natural gas and flue gas, among which the adsorption is considered as a more cost-effective technical solution, along with low energy consumption, simple design, environmental efficient method. On the other hand, there is no simple comparison between the performances of the adsorbents. In this regard, a method it can be used to select an appropriate adsorbent with high selectivity, coupled with the effect of operating conditions on performance, the ideal adsorption solution theory (IAST). Theory (IAST) is one of the most reliable methods for predicting adsorption equilibrium of gas mixtures, which is often used to predict the equilibrium of mixture of gas mixture and only uses pure component adsorption. for CO2/N2 separation, various adsorbents were reported .In this research, CO2/N2 adsorbents were compared with the calculations of two - component mixture adsorption by use (IAST) under pressure of 1-100 kpa .At the end, a new commercial design of the adsorption values as a simple guide for researchers for industrial applications for the selection of high-performance adsorbents for the separation of CO2/N2 has been prepared. Theory and modeling: IAST method This method is one of the most widely used models to predict the balance in multicomponent mixtures. the advantages of this method are high speed, simple calculations, thermodynamic stability, and the ability to use all existing equilibrium isotherms. This theory assumes that the adsorbed mixture is an ideal solution, where there is no interaction between the components present in the adsorption phase. This theory is based on thermodynamic solutions which is independent of the real adsorption model. Different versions of this theory have been proposed that are continued by prausnitz that are extended for fast systems and other versions such as vermeilen have been developed by Luan which can be used to improve the speed of calculations in this research, by using ideal adsorption solution and related MATLAB program, two - component mixture adsorption modelling was investigated. Variations in selectivity versus pressure changes as well as the difference between the adsorbents in the selectivity and the total uptake for different adsorbents were introduced. For the two-component adsorption calculations, the adsorption data of pure component is required. Results and discussion By changing the operating pressure in the range of 1-100 kPa for the gas mixture (50 - 50) CO2/N2, different adsorbents were investigated. The results show that by increasing the pressure on the adsorbent type, the amount of carbon dioxide adsorbed increases with further increase or is not significantly changed. Also, it is shown that the effect of increasing pressure leads to an increase in adsorption rate. Also, for the activated carbon - AQSOA FAM Z02 - KIT‑6 adsorbent, a very little change in the adsorption rate is created. Also, by increasing the selectivity of MIL 100 (Fe) - Activated carbon/zeolit, as expected, we see more selectivity at low temperatures the selectivity of adsorbent is more than other adsorbents. In this adsorbent, the adsorbent has a selectivity at 303 K and the adsorbent KIT‑6 has the maximum total uptake. On the other hand, MOF-505@GO adsorbent has less selectivity and less adsorption capacity than other adsorbents. However, the choice of the adsorbent should be based on economic calculations. Conclusion The performance of different adsorbents was investigated for CO2/N2 separation using the idea of al adsorption solution. Among all the adsorbents MIL-100(Fe) and Activated carbon/zeolite and activated/zeolite adsorbents have selectivity to CO2/N2, respectively. Among the selected adsorbents, the highest CO2 adsorption belongs to KIT‑6 the obtained diagram of CO2 adsorption in the presence of CO2 selectivity for different adsorbents is prepared which is a suitable guide for selecting appropriate adsorbent for industrial applications of these adsorbents. Abstract There are various adsorbents for the separation of nitrogen and carbon dioxide gases with different adsorption capacity and selectivity. A comprehensive comparison should be made between different adsorbents to select the appropriate adsorbent for a desired process. In this paper, the equilibrium adsorption value and selectivity of different adsorbents have been investigated using the Ideal Adsorption Solution Theory (IAST) to determine the appropriate adsorbent for the separation of nitrogen and carbon dioxide gases. The (IAST) model has been used to compare adsorbents at different pressures (1 to 100 kPa) and in a 50-50 percent composition to compare adsorbents in different gas percentage compositions (0.9-0.1) at a total pressure of 100 kPa. The results showed that the activated carbon/zeolite adsorbent has the highest selectivity at a temperature of 298 K and the KIT-6 adsorbent has the highest total adsorption. The studies showed that the Zeolite 13X adsorbent has lower selectivity and adsorption capacity than other adsorbents. Finally, a new trade-off diagram was prepared based on the adsorption rate versus selectivity of different adsorbents to guide researchers for use in industrial applications. جاذب‌های مختلفی برای جداسازی گازهای نیتروژن و دی اکسید کربن با ظرفیت جذب و انتخاب‌پذیری متفاوت وجود دارند. بین جاذب‌های مختلف، باید مقایسه جامعی جهت انتخاب جاذب مناسب برای یک فرایند مطلوب صورت گیرد. در این مقاله، مقدار جذب تعادلی و انتخاب‌پذیری جاذب‌های مختلف با استفاده از تئوری محلول جذب ایده‌آل (IAST) برای تعیین جاذب‌ مناسب برای جداسازی گازهای نیتروژن و دی اکسید کربن بررسی شده است. مدل (IAST) برای مقایسه جاذب‌ها در فشارهای مختلف (1 تا 100 کیلو پاسکال) و در ترکیب درصد 50-50 جهت مقایسه جاذب‌ها در ترکیب درصدهای مختلف گاز (9/0- 1/0) در فشار کل100 کیلو پاسکال استفاده شده است. نتایج نشان داد، جاذب کربن فعال/زئولیت در دمای 298 کلوین بیشترین میزان انتخاب‌پذیری و جاذب KIT-6 بیشترین میزان جذب کل را دارد. بررسی‌ها نشان داد، جاذب Zeolite 13X انتخاب‌پذیری و ظرفیت جذب کمتری نسبت به دیگر جاذب‌ها دارد. در انتها نمودار جدیدtrade - off ، بر اساس میزان جذب در برابر انتخاب‌پذیری جاذب‌های مختلف جهت راهنمایی محقیق برای استفاده درکاربردهای صنعتی تهیه شد.

https://www.jess.ir/article_230921_a836b4ecce2b0ef86c5112499a40798b.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Management and Applications of Artificial Intelligence for Environmental Pollution Control at Steel Industry مدیریت و کاربرد های هوش مصنوعی جهت کنترل آلودگی های محیط زیست در صنعت فولاد 10583 10594 230922 10.22034/jess.2025.532225.2386 FA محمد حسین صیادی استاد تمام گروه محیط‌زیست، دانشگاه شهید باهنر کرمان 0000-0002-7128-9919 زهرا سیمایی دانشجوی کارشناسی گروه محیط‌زیست، ، دانشگاه شهید باهنر کرمان سارا امامی استاد مدعو گروه محیط‌زیست، دانشگاه شهید باهنر کرمان 0009-0007-1424-9551 Journal Article 2025 07 02 EXTENDED ABSTRACT The steel industry, as one of the fundamental pillars of the global economy, faces numerous challenges, including environmental pollution, especially air pollution. This industry contributes significantly to greenhouse gas emissions and air and water pollution. Recent research shows that the use of new technologies, especially artificial intelligence, can help improve environmental conditions and reduce pollution. The aim of this study is to investigate the application of artificial intelligence in reducing air pollution and improving sustainability in the steel industry. This research seeks to identify opportunities in this field and provide suggestions for investment and improving environmental conditions. This study is a descriptive analytical and library type that used the scientific databases Google Scholar and Scopus to collect articles related to artificial intelligence, the steel industry, and environmental pollution. In total, 90 articles were selected and reviewed as primary sources. The results show that artificial intelligence can help optimize production processes, predict maintenance, and quality control in the steel industry. This technology helps reduce the negative impacts of the steel industry on the environment, especially air pollution, by identifying sources of pollution and predicting trends. Steel companies also use artificial intelligence to optimize processes and reduce environmental pollution, especially air pollution and waste. The use of modern technologies and artificial intelligence also improves product quality, reduces environmental pollution, and reduces costs; therefore, investing in this area can help improve environmental conditions and increase efficiency in the steel industry, leading to a reduction in air pollution. The steel industry, as one of the fundamental pillars of the global economy, faces numerous challenges, including environmental pollution, especially air pollution. This industry contributes significantly to greenhouse gas emissions and air and water pollution. Recent research shows that the use of new technologies, especially artificial intelligence, can help improve environmental conditions and reduce pollution. The aim of this study is to investigate the application of artificial intelligence in reducing air pollution and improving sustainability in the steel industry. This research seeks to identify opportunities in this field and provide suggestions for investment and improving environmental conditions. This study is a descriptive analytical and library type that used the scientific databases Google Scholar and Scopus to collect articles related to artificial intelligence, the steel industry, and environmental pollution. In total, 90 articles were selected and reviewed as primary sources. The results show that artificial intelligence can help optimize production processes, predict maintenance, and quality control in the steel industry. This technology helps reduce the negative impacts of the steel industry on the environment, especially air pollution, by identifying sources of pollution and predicting trends. Steel companies also use artificial intelligence to optimize processes and reduce environmental pollution, especially air pollution and waste. The use of modern technologies and artificial intelligence also improves product quality, reduces environmental pollution, and reduces costs; therefore, investing in this area can help improve environmental conditions and increase efficiency in the steel industry, leading to a reduction in air pollution. Introduction Given the challenges and opportunities in the steel industry, this study seeks to identify effective solutions to reduce the negative impacts of steel production on the environment. It also examines how to invest in new technologies and improve data infrastructure to contribute to sustainable development and reduce air pollution. The use of artificial intelligence as a key tool in strategic management and process optimization can lead to improved environmental conditions and increased quality of life in communities related to the steel industry. The purpose of this study is to investigate the application of artificial intelligence in reducing air pollution and improving sustainability in the steel industry. Materials and methods This is a descriptive library and analytical study that was used to collect articles related to artificial intelligence, the steel industry, and environmental pollution from scientific databases such as Google Scholar and Scopus. The selected articles included research and review articles published between 2020 and 2025. Of the initial 500 articles, 100 articles were removed due to irrelevance to the topic, 200 articles due to low quality, and 50 articles due to lack of access to the full text. Finally, 90 articles of suitable quality were selected for the final analysis. These articles were divided into three main categories: applications of artificial intelligence in steel production (45 articles), quality control and process improvement (30 articles), and environmental pollution (15 articles), which examined the modeling and reduction of environmental pollution in the steel industry. Results and discussion The steel industry has significant environmental impacts, including air, water, and soil pollution. Steelmaking furnaces, especially blast furnaces and electric arc furnaces, are major sources of greenhouse gas emissions and other pollutants. These furnaces produce carbon dioxide, carbon monoxide, and nitrogen oxides, which contribute to climate change and health problems. In addition, industrial wastewater containing toxic chemicals and heavy metals can contaminate groundwater and soil resources, posing a threat to public health. Artificial intelligence, as a new tool, can play a significant role in reducing these negative impacts. Using advanced algorithms and big data analytics, artificial intelligence can help optimize production processes, predict maintenance, and control quality. This technology identifies sources of pollution, predicts trends, and optimizes processes, which in turn leads to reduced waste and improved environmental performance. Companies like ArcelorMittal and Tata Steel are using AI to optimize processes, predict equipment replacement times, and control emissions. These measures help reduce energy consumption and improve product quality. For example, ArcelorMittal uses machine learning algorithms to analyze dust data and determine the optimal time to collect it. In addition, the use of modern wastewater treatment technologies and environmental management systems can help reduce pollution and improve environmental conditions. AI can also help raise awareness among workers and managers about complying with environmental standards. Overall, AI, as a powerful tool in the steel industry, can help reduce pollution and waste and help companies improve their environmental performance. This approach not only helps protect the environment, but can also lead to increased productivity and reduced costs. Conclusion This article examines the application of artificial intelligence in the steel industry and its impact on reducing environmental pollution. Artificial intelligence helps optimize production processes by identifying and managing sources of pollution. Using machine learning algorithms and sensors, industries can analyze and monitor data related to pollutant emissions. These measures not only help reduce air pollution and improve public health, but also increase the competitiveness and efficiency of the steel industry in the global market. Investment in artificial intelligence technologies can be a successful model for other industries. صنعت فولاد به‌عنوان یکی از ارکان اساسی اقتصاد جهانی، با چالش‌های متعددی از جمله آلودگی محیط‌زیست و به‌ویژه آلودگی هوا روبرو است. این صنعت سهم قابل‌توجهی در انتشار گازهای گلخانه‌ای و آلودگی‌های هوا و آب دارد. تحقیقات اخیر نشان می‌دهد که با به‌کارگیری فناوری‌های نوین، به‌ویژه هوش مصنوعی، می‌توان به بهبود شرایط محیطی و کاهش آلودگی کمک کرد. هدف این مطالعه بررسی کاربرد هوش مصنوعی در کاهش آلودگی هوا و بهبود پایداری در صنعت فولاد است. این تحقیق به دنبال شناسایی فرصت‌های موجود در این زمینه و ارائه پیشنهاداتی برای سرمایه‌گذاری و بهبود شرایط محیط زیستی است. این مطالعه از نوع تحلیلی توصیفی و کتابخانه‌ای است که از پایگاه‌ داده علمی ساینس دایرکت برای جمع‌آوری مقالات مرتبط باهوش مصنوعی، صنعت فولاد و آلودگی محیط زیستی استفاده شده است. در مجموع، 550 مقاله به‌عنوان منابع اصلی انتخاب و بررسی شدند. نتایج نشان می‌دهد که هوش مصنوعی می‌تواند به بهینه‌سازی فرایندهای تولید، پیش‌بینی نگهداری و کنترل کیفیت در صنعت فولاد کمک کند. این فناوری با شناسایی منابع آلودگی و پیش‌بینی روندها، به کاهش تأثیرات منفی صنعت فولاد بر محیط‌زیست، به‌ویژه آلودگی هوا، کمک می‌کند. همچنین، شرکت‌های فولادی از هوش مصنوعی برای بهینه‌سازی فرایندها و کاهش آلودگی‌های محیط زیستی خصوصاً آلودگی هوا و پسماند استفاده می‌کنند. استفاده از فناوری‌های نوین و هوش مصنوعی بهبود کیفیت محصولات، کاهش آلودگی محیط زیستی و کاهش هزینه‌ها را نیز به همراه دارد؛ بنابراین، سرمایه‌گذاری در این حوزه می‌تواند به بهبود شرایط محیط زیستی و افزایش کارایی در صنعت فولاد کمک کند و به کاهش آلودگی هوا منجر شود.

https://www.jess.ir/article_230922_fac76d398571af15ca74cad029b71e65.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Measurement of Climate Change Composite Index in Iran’s Provinces محاسبه شاخص ترکیبی تغییر اقلیم در استان‌های ایران 10595 10615 230927 10.22034/jess.2025.539114.2391 FA مهدیس متقیان فرد دانشکده اقتصاد و مدیریت دانشگاه سمنان. سمنان. ایران 0000-0003-0240-4650 مجید مداح گروه آموزشی اقتصاد، دانشکده اقتصاد، مدیریت و علوم اداری دانشگاه سمنان 0000-0003-2697-9547 محمد رحیمی گروه آموزشی بیابان‌زدایی،دانشکده کویرشناسی، دانشگاه سمنان 0000-0001-6405-8488 Journal Article 2025 08 06 Abstract: Climate Change is one of the most important environmental phenomenon in the current century. Located in an arid and semi-arid region of the world, Iran has already faced a water crisis and increasing temperatures, so the country is vulnerable to the climate change impacts. Due to the development of climate change studies and it’s impacts on different aspects of human’s life especially the economic sector, it appears that the lack of an indicator reflecting the state of climate change is felt in this context. While in the field, most of studies focus on analyzing the effects of climate change on the economy using only temperature and precipitation variables, however this multidimensional phenomenon is more than merely daily temperature and precipitation changes. Due to the complex nature of climate change, the study introduces and develops a composite index for climate change in provinces of Iran for 33 years (1991-2023) and examines it’s trends. The study applies Principal Component Analysis (PCA) method for weighing based on 25 climate change indices from World Meteorological Organization. The results show that in the most provinces the composite index deteriorated over the study period and this situation is more concerning in arid and semi-arid provinces like Fars. It is worth pointing out that this composite index can be useful for interdisciplinary studies and policy making specially in agricultural sector studies which is the most susceptible economic sector. Extended Abstract: Introduction: Iran is located in the Middle East, an arid and semi-arid region in the world. It has already faced a water crisis and increasing temperatures, so the country is unsafe from climate change and its impacts. While in the field of environmental and climate change studies, most of them focus on analyzing the effects of climate change on the economy using only two variables (temperature and precipitation), this study aims to take into account a wide range of climate change variables by using core indices of climate change in order to provide a more comprehensive and precise description of the situation. Due to the development of composite indicators in economics studies, the study introduces and develops a composite index for climate change trends in provinces of Iran for 33 years. This composite index can simplify the complexity of this phenomenon, and then we can more easily analyze, compare, and track the trend of this multi-dimensional concept. It is noteworthy to mention that this composite index can be useful for studies and policy making in an agricultural sector which is the most vulnerable economic sector. Methodology: The study estimated a composite climate change index for 23 provinces in Iran by using proper methods and 25 climate change core indices from 1991 to 2023. This comprehensive study covers a broad geographic region of the country. Since all indices do not have negative impacts as they increase, the study classifies indices into two groups. The first group contains 16 indices, and their increase is expected to be harmful and negatively impact the social and economic sectors. On the other hand, the second group contains 9 indices, and their increase is expected to be welcome and have positive impacts. Weighing is the most crucial step in the composite index process. There are different methods to assign weight to the indicators; each has advantages and disadvantages. Meanwhile, principal components analysis (PCA) is one of the most used methods, and it will also be applied in this study. This method is commonly employed, especially when a linear relationship between variables is assumed. It is selected in this study because principal component analysis (PCA) serves as an effective tool to reveal patterns of similarity and difference within the data. Once those patterns are identified, PCA facilitates to reduce the number of dimensions without losing important information in the original data. Discussion: As demonstrated both indices had unpleasant trends, especially in the last 20 years. This trend is worse in provinces located in arid and semi-arid regions of the country, but as we have seen in the results, all provinces will face the challenges of climate change, and none of them is safe. For index 1, high values and increasing trends are expected to be harmful. Province like Fars have more critical situations, which is expected to worsen without proper action. Index 2 will negatively affect different sectors of the country as it declines. Provinces in arid regions are on the frontline of the impacts of the changes in the second index. Bushehr has a critical condition from the perspective of the second index. However, this province has a share of more than 5 percent of Iran's GDP. This trend can decrease the province's GDP. It is worth mentioning that the indices' deterioration can negatively impact economic-social sectors. Conclusion: Creating a composite climate change index is crucial for decision-making and policy-making processes to consider environmental aspects. Instead of dealing with numerous individual indicators, policymakers will have a composite index that covers all dimensions of climate change, allowing them to address every aspect of this issue. This will help not to eliminate any dimensions of climate change phenomenon. Similar to other applied indices such as the Climate Vulnerability Index (CVI), which is widely used by many countries to analyze vulnerability at the regional level, this index offers a robust framework for evaluation. Built upon a comprehensive set of standardized ETCCDI climate indices and employing a two-dimensional approach that categorizes indicators into favorable and unfavorable components, the proposed index can function on a level comparable to or even exceeding that of traditional vulnerability indices, which often focus solely on socio-economic variables. Due to its emphasis on key standard climatic variables, this index enables long-term trend analysis across different geographic scales and can be integrated with social and economic indicators. While the findings highlight the worsening of climatic conditions across most provinces, it is essential to distinguish between the study’s comprehensive analytical approach and the descriptive reporting of index values. The primary aim of this research is to establish a coherent, integrated framework for analyzing climate change at the national level. This purpose extends beyond regional assessments of index fluctuations and can serve as a basis for interdisciplinary applications in economic, social, and policy-making domains. تغییر اقلیم یکی از پدیده‌های محیط زیستی مهم در قرن حاضر است. ایران با واقع‌شدن در منطقه خشک و نیمه‌خشک جهان با افزایش دما و بحران آب روبه‌رو بوده که این مسئله باعث می‌شود تا کشور نسبت به اثرات تغییر اقلیم آسیب‌پذیر باشد. باتوجه‌به گسترش مطالعات مربوط به تغییر اقلیم و اثرات آن بر ابعاد متفاوت زندگی بشر خصوصاً بخش اقتصادی آن، به نظر می‌رسد جای یک شاخص نشان‌دهنده وضعیت تغییر اقلیم در مطالعات خالی است. در بیشتر مطالعات انجام شده برای بررسی پیامدهای این پدیده بر اقتصاد، در بیشتر مواقع تنها از متغیرهای دما و بارش استفاده می‌شود؛ اما این پدیده چندبعدی چیزی فراتر از تنها به‌سادگی تغییرات دما و بارش روزانه است. این مطالعه با توجه به ماهیت پیچیده تغییر اقلیم، یک شاخص ترکیبی از آن را در سطح استان‌های ایران در دوره زمانی 33ساله (1370-1402) معرفی و استخراج کرده و روند آن را مورد تحلیل و بررسی قرار می‌دهد. در این راستا از روش وزن‌دهی تحلیل مؤلفه‌های اصلی (PCA) بر مبنای 25 متغیر اصلی تغییر اقلیم که توسط سازمان هواشناسی جهانی معرفی شده، استفاده شده است. نتایج نشان می‌دهد که روند تغییر اقلیم در بیشتر استان‌های کشور در دوره تحت بررسی بدتر شده که این وضعیت در استان‌های مناطق خشک و نیمه‌خشک از جمله فارس جدی‌تر است. لازم به ذکر است این شاخص ترکیبی می‌تواند به سیاست‌گذاری و پژوهش‌های بین‌رشته‌ای خصوصاً مطالعات بخش کشاورزی که آسیب‌پذیرترین بخش‌ اقتصادی نسبت به تغییر اقلیم است، کمک قابل‌توجهی کند.

https://www.jess.ir/article_230927_41c31e5fd8102081f5067a185ec1f064.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Smartening the agricultural water distribution structure based on social participation in rice farming هوشمند سازی ساختار توزیع آب زراعی بر پایه مشارکت اجتماعی در کشاورزی برنج 10616 10630 231011 10.22034/jess.2025.540244.2392 FA افسانه برنجکار گورابی دانش آموخته دکتری تخصصی، جغرافیا و برنامه ریزی روستایی، علوم و تحقیقات تهران، تهران،ایران 0009-0006-0419-1838 اسماعیل کدیور خواه چماچائی دانش آموخته دکتری تخصصی، جغرافیا و برنامه ریزی روستایی، دانشگاه آزاد اسالمی واحد رشت، رشت ، ایران Journal Article 2025 08 09 Given the water crisis and challenges of water resource management in agriculture, especially in rice cultivation, which requires high water requirements, designing smart water distribution systems with farmers' participation can help optimize water consumption, reduce conflicts, and increase productivity. This research seeks to investigate technological solutions to improve the water distribution system with a focus on stakeholder participation in the two northern provinces of the country. The study area examined in this research is the plain areas suitable for rice cultivation in the two northern provinces of Guilan and Mazandaran, which are considered the main rice producing areas in the country with a total of 452,960 hectares of cultivated area, and the share of water consumed in the two provinces of Guilan and Mazandaran is 47% of the country's total share. This research is applied in terms of purpose and descriptive-analytical in terms of method, with a combined approach (qualitative-quantitative). The target population includes rice farmers, local irrigators, and water distribution system officials in the provinces of Guilan and Mazandaran who irrigate their fields using traditional methods and local irrigation. Focusing on the smartization of agricultural water distribution and relying on the social participation of rice farmers, this article seeks to identify the challenges in the water distribution system and examine the role of smart technologies such as IoT, remote sensing, and automated water management systems. The findings show that agricultural water management in these areas is mainly based on traditional methods, and modern technologies are used only at limited levels and in research farms to monitor rice fields. The results of the study indicate that the use of smart irrigation technologies by farmers can help in optimal water management in the study area and, while preventing its waste, lead to a balanced consumption of pesticides and fertilizers in accordance with the actual needs of the farms. In addition to the productivity of rice fields, this approach plays an effective role in preserving the environment. Water stress is a common and growing global challenge, as increasing uncertainty in weather due to climate change affects water availability in many regions and disrupts livelihoods and environmental functions, especially those related to agriculture and food security.Water resource management has always been one of the challenges that farmers have faced for centuries, and they have tried to address this challenge by forming network structures to irrigate their fields. In our country, water resource constraints have always been an issue that farmers face.). Since rice agriculture is a major consumer of water resources, it requires efficient management systems, and traditional water distribution can lead to resource waste and social conflicts among rice producers. Therefore, integrating indigenous knowledge and community participation with modern technologies (such as smart water monitoring systems) can help improve water distribution efficiency and rice cultivation sustainability. Smart irrigation based on the Internet of Things (IoT) leads to greater crop development, effective water management, and remote access compared to conventional irrigation systems. The strategy, which aims to provide remote access to the system and ensure that farmers have continuous information and control over their fields throughout the year. Materials and methods This research is applied in terms of purpose and descriptive-analytical in terms of method, conducted with a mixed (qualitative-quantitative) approach. The study population includes rice farmers, local irrigators, and water distribution system officials in the provinces of Guilan and Mazandaran who irrigate their fields using traditional methods and local irrigation. In this research, which aims to investigate the smartization of rice field irrigation methods and social participation of agricultural users, the data collection methods used are reviewing documents, articles, and reports related to smart water management and social participation, and semi-structured interviews, discussions with stakeholders (farmers, irrigation managers, technical experts) to identify challenges and solutions. Results and discussion In the participatory method where irrigation of farms has been based on traditional methods, artificial intelligence has come to the aid of farmers and, as an executive arm, can carry out the process of farm operations and management in a shorter time and with greater accuracy. In this way, local irrigators who have the role of distributing and managing water in farms can make real-time decisions in water management and distribution by taking advantage of artificial intelligence. Smart panels installed in rice fields can provide accurate information about the level of need of rice fields to irrigators to guide them in making appropriate decisions and take real-time, effective and appropriate actions according to the needs of each farm. However, the important point is the infrastructure part in making farms smart. With the entry of governing institutions in order to inform traditional irrigators of the role of making rice fields smart in facilitating irrigation matters and reducing waste of resources, which is in the interest of rice farmers, and also taking macro-policies in paying low-interest and long-term facilities in order to make farms smart, they can have a revolution in the field of agricultural water management. Conclusion The use of modern irrigation systems using smart technologies is a revolution in irrigation and rice production. The two provinces of Guilan and Mazandaran, as the two rice producing hubs of the country, are also facing limited access to water resources during the rice growing seasons, like other provinces, and traditional irrigation structures no longer meet this need to improve the production process and increase productivity. There is a need for technology as an effective and technical arm to help traditional irrigators to make optimal use of limited water resources using modern tools and techniques. In the study conducted in the two provinces under study, irrigation methods are carried out traditionally and with the social participation of the farmers themselves, and the use of artificial intelligence and modern technologies is limited to research studies that use smart devices installed in rice fields using existing sensors to assess soil moisture levels, water needs, etc., and irrigation is carried out in proportion to the information obtained from these devices. The social participation of farmers, which plays a central role in smart irrigation of rice fields, is not limited to the acceptance of technology, but also includes active cooperation, collective management, and building trust among stakeholders. باتوجه به بحران آب و چالش‌های مدیریت منابع آبی درکشاورزی، به‌ویژه درکشت برنج که نیاز آبی بالایی دارد، طراحی سیستم‌های هوشمند توزیع آب با مشارکت کشاورزان می‌تواند به بهینه‌سازی مصرف آب، کاهش تعارضات و افزایش بهره‌وری کمک کند. این پژوهش به دنبال بررسی راهکارهای فناورانه برای بهبود نظام توزیع آب با محوریت مشارکت ذینفعان در دو استان شمالی کشور است. محدوده مطالعاتی مورد بررسی در این پژوهش مناطق جلگه ای و مستعد کشت برنج در دو استان شمالی گیلان و مازندران است که در مجموع با 96/452 هزار هکتار سطح زیر کشت به عنوان اصلی‌ترین مناطق تولید کننده برنج در کشور محسوب می‌شوند و سهم آب مصرفی دو استان گیلان مازندران 47 درصد سهم کل کشور است. این پژوهش از نظر هدف، کاربردی و از نظر روش، توصیفی-تحلیلی است که با رویکرد ترکیبی (کیفی-کمی) است. جامعه هدف شامل کشاورزان برنج‌کار، آبیاران محلی و مسئولان نظام توزیع آب در استان‌های گیلان و مازندران است که مزارع خود را با استفاده از روش های سنتی و آبیارهای محلی آبیاری می کنند. مقاله حاضر با تمرکز بر هوشمندسازی توزیع آب زراعی و با تکیه بر مشارکت اجتماعی کشاورزان برنج‌کاران، درصدد شناسایی چالش‌های موجود در سیستم توزیع آب و بررسی نقش فناوری‌های هوشمند‌ مانند IoT، سنجش از دور و سیستم‌های مدیریت خودکار آب است. یافته‌ها نشان می‌دهد که مدیریت آب زراعی در این مناطق عمدتاً بر روش‌های سنتی استوار است و فناوری‌های نوین تنها در سطوح محدود و مزارع تحقیقاتی برای پایش مزارع برنج به کار گرفته می‌شوند. نتایج پژوهش حاکی از آن است که به‌کارگیری فناوری‌های هوشمند آبیاری توسط کشاورزان می‌تواند به مدیریت بهینه آب، در محدوده مطالعاتی کمک کند و ضمن جلوگیری از هدر رفت آن به مصرف متعادل سموم و کودها متناسب با نیاز واقعی مزارع بینجامد. این رویکرد علاوه بر بهره‌وری مزارع برنج نقش مؤثری در حفظ محیط‌زیست دارد .

https://www.jess.ir/article_231011_f1d561867eaea8a7086277adb096e25f.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Suitable plants as a second crop after Rice in the Paddy Fields of Guilan Province گیاهان مناسب به عنوان کشت دوم پس از برنج در شالیزارهای استان گیلان 10631 10643 231013 10.22034/jess.2025.540405.2393 FA روح اله یوسفی استادیار پژوهشی، موسسه تحقیقات برنج کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، رشت، ایران. 0000-0001-5437-9333 Journal Article 2025 08 10 ABSTRACT The development of double cropping after rice harvesting is considered a fundamental strategy to enhance production and income for farmers while maintaining rice production sustainability in Guilan province. Despite the vital importance of this type of cultivation in paddy fields, a vast area of these lands remains uncultivated due to various agricultural, economic, and social reasons. In order to identify profitable species of forage crops (including fodder beet, triticale, and clover) and oilseed species (including canola and camelina) for double cropping after rice, and to evaluate their effects on profitability, yield, and interference with the rice cropping calendar, an experiment was conducted in a randomized complete block design with three replications at the Soil and Water Research Station of the Rice Research Institute of Iran. Based on the results of this research, the yields of canola and camelina were approximately the same. Fresh and dry clover had different yields, and the aerial organ and root yields of fodder beet also showed different values. Fresh and dry triticale also had different yields, respectively. Economic analysis showed that the cultivation of canola, camelina, and fodder beet is not economically viable, while clover cultivation is only profitable when sold fresh. Based on the results of this research, triticale, with the least interference in the rice cropping calendar, has good yield and profitability and is recommended as a suitable option for double cropping after rice in the region. Introduction Given the increasing population and limited land resources, enhancing productivity per unit area is an unavoidable necessity. Double cropping serves as a strategy to boost productivity, positively impacting rural household economies and enabling optimal land utilization. However, due to agronomic, economic, and social factors, a significant portion of these lands remains uncultivated after the rice harvest. Selecting the appropriate crop and using optimized cultivation techniques are crucial for the success of double cropping. Effective marketing and economic profitability are also important for expanding the cultivated area of these products. Given the diverse conditions, region-specific research is needed to optimize crop rotation strategies in rice-based systems. This study aims to identify profitable forage and oilseed crops for second cropping after rice in the paddy fields of Gilan Province, thereby promoting optimal resource utilization and enhancing the economic and environmental sustainability of these regions Materials and methods To investigate the effects of crop rotation canola, camelina, clover, fodder beet, and triticale on profitability, yield, and compatibility with the rice cropping calendar, an experiment was conducted in during the 2019-2020 growing season at the Soil and Water Rice Research Station in Rasht.Each experimental plot for canola, camelina, triticale, and clover was planted in 20 rows, spaced 25 cm apart and 10 meters long. Each experimental plot for forage beet was planted in ten rows, spaced 50 cm apart and 10 meters long. All seeds were manually sown on ridges created with a furrower. Canola, camelina, forage beet, and clover were planted in the second half of October, and triticale was planted in mid-November. The spacing between treatments was one meter, and between replications was two meters. After the rice harvest, in order to prepare the land for planting the desired forage and oilseed crops, tillage operations were performed in two stages, perpendicular to each other, with a rotary plow at a depth of 10-15 cm. To improve drainage, prevent seed suffocation in waterlogged conditions, and prevent stem rot, furrows and ridges were created with a furrower. Before the experiment, soil samples were taken from the field at a depth of 0-30 cm, and the physical and chemical properties of the soil were determined. The required fertilizer for each crop was applied in different stages based on the technical recommendations of the soil and water department researchers at the Rice Research Institute. Due to sufficient rainfall during the plant growth season, no irrigation was performed, and the cultivation was rainfed. Clover was harvested at the beginning of flowering, which coincided with the milk stage of grain development in triticale. To determine the fresh forage yield per unit area, the marginal rows and half a meter from the top and bottom of each plot were removed as border effects, and the plots were harvested and immediately weighed. To measure dry forage yield, one kilogram of fresh forage was randomly selected from each treatment, and the samples were dried in an oven at 75 degrees Celsius for 48 hours and weighed. Forage yield was determined based on 15% moisture content. Statistical analysis of the data was performed using Excel software with simple and combined statistical analyses. Mean comparisons were performed using the LSD test at a 5% probability level. Finally, economic evaluation, including the determination of net annual benefits and benefit-cost ratio, was carried out by considering the costs of planting, maintenance, harvesting, and silage making, in order to select the best treatments. Results and discussion Variance analysis showed that the type of forage crop had a highly significant effect (P < 0.01) on fresh forage yield, dry forage yield, and plant height. This indicates significant differences in these traits among the different types of forage crops studied. In other words, the selection of forage crop type significantly affects yield and plant height. However, the effect of forage crop type on the ratio of dry to fresh forage yield was not statistically significant (P > 0.05). This suggests that the different types of forage crops studied do not differ significantly in the amount of dry matter present in the fresh forage. Mean comparisons showed that triticale, with a fresh forage yield of 3460.7 g/m² and a dry forage yield of 395.85 g/m², significantly outperformed the other crops studied. Berseem clover, with a fresh forage yield of 1491 g/m² and a dry forage yield of 185.78 g/m², ranked next, which was significantly higher than forage canola, fodder beet, and camelina. Triticale also had the tallest plant height at 115.66 cm. Economic analysis showed that cultivating triticale, berseem clover, and fodder beet in Guilan province resulted in positive net annual benefits and a benefit-cost ratio greater than one, indicating the profitability of these crops in the region. Among the crops studied, berseem clover had the highest economic return, with a benefit-cost ratio of 4.67 and a net annual benefit of 165,034,310 Rials. The development of forage crop cultivation, particularly legumes, plays a significant role in providing forage, reducing erosion, improving soil texture, utilizing low-yielding areas, and ultimately, promoting sustainable agriculture. Based on the results of the economic analysis, cultivating canola and camelina is not cost-effective in the conditions of Guilan province. In contrast, clover, triticale, and fodder beet can be recommended as a second crop after rice in the paddy fields of this province due to their suitable yield and profitability. Conclusion Triticale and clover, due to their suitable forage yield, adaptability to regional conditions, and high potential for producing quality forage, can be considered appropriate options for second cropping in the paddy lands of Guilan Province.Nevertheless, the development of second cropping in these lands also faces challenges such as drainage issues, a lack of suitable machinery, and inadequate markets. توسعه کشت دوم پس از برداشت برنج، به عنوان یکی از راهکارهای اساسی افزایش تولید و درآمد کشاورزان و حفظ پایداری تولید برنج در استان گیلان مطرح است. با وجود اهمیت حیاتی این نوع کشت در اراضی شالیزاری، سطح وسیعی از این اراضی به دلایل متعدد زراعی، اقتصادی و اجتماعی، همچنان به صورت نکاشت باقی می‌ماند. به‌منظور شناسایی گونه‌های سودآور گیاهان علوفه‌ای (شامل چغندر علوفه‌ای، تریتیکاله و شبدر) و دانه‌های روغنی (شامل کلزا و کاملینا) برای کشت دوم پس از برنج و ارزیابی اثرات آن‌ها بر سودآوری، عملکرد و تداخل با تقویم زراعی برنج، آزمایشی در قالب طرح بلوک‌های کامل تصادفی با سه تکرار در پایگاه تحقیقات شالیزاری خاک و آب موسسه تحقیقات برنج کشور به اجرا درآمد. نتایج این تحقیق نشان داد که عملکرد کلزا و کاملینا تقریباً یکسان بوده است. شبدر تر و خشک، عملکرد متفاوتی داشتند و عملکرد اندام هوایی و ریشه چغندر علوفه‌ای نیز مقادیر مختلفی را نشان داد. همچنین، عملکرد تریتیکاله تر و خشک نیز به ترتیب عملکرد متفاوتی داشتند. تجزیه‌ و تحلیل اقتصادی نشان داد کشت کلزا، کاملینا و چغندر علوفه‌ای از نظر اقتصادی مقرون‌به‌صرفه نیست. کشت شبدر تنها در صورت فروش به‌صورت تازه (تر) سودآور است. بر اساس نتایج این تحقیق، تریتیکاله با کمترین تداخل در تقویم زراعی برنج، عملکرد و سودآوری مطلوبی دارد و به‌عنوان گزینه‌ای مناسب برای کشت دوم پس از برنج در منطقه قابل‌توصیه است.

https://www.jess.ir/article_231013_f59261960d3bb9ed4bc8d560fc3c5754.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Synthesis of Zeolite nanocomposite/ Carbon Nanotubes (CNTs) for phosphate removal from aqueous solution سنتز نانو کامپوزیت زئولیت/نانو لوله های کربنی (CNTs) به منظور حذف فسفات از محلول آبی 10644 10659 231117 10.22034/jess.2025.537298.2388 FA ملیکا نور گروه منابع طبیعی و محیط زیست واحد علوم و تحقیقات ، دانشگاه آزاد اسلامی تهران،ایران 0009-0003-5791-7776 لعبت تقوی گروه منابع طبیعی و محیط زیست- واحد علوم و تحقیقات- دانشگاه آزاد اسلامی- تهران 0000-0002-4973-318X ایوب رضایی پژوهشکده سلامت،دانشگاه علوم پزشکی کرمانشاه،کرمانشاه،ایران 0000-0002-9109-3948 Journal Article 2025 07 30 Instructions people, animals and plants with good and healthy growing. But when too much of it—especially as phosphate—gets into rivers, lakes or groundwater, it’s bad news. Stuff like farm fertilizers, city runoff, and factory waste dumps phosphate into water, causing something called eutrophication. That’s when the algae and the plankton go hog wild, make the water gross, smelly, and cloudy, suck up all the oxygen—and mess things up for fish and other aquatic critters. Even a tiny bit, like 100 micrograms per liter, can kind of set this in motion, so it's a problem everywhere, from big lakes to small streams. This mess comes from two places: us adding too much phosphorus to water and old phosphorus stuck in lake or river bottoms sneaking back out over time. So, we got to find smart ways to clean it up and stop it from coming back. There are a bunch of methods—like reverse osmosis, ion exchange, chemical tricks, electric treatments, or using bacteria and plants—but I think adsorption is the way to go. It’s like using a sponge that soaks up phosphate and holds onto it. It’s cheap, works really well, doesn’t leave junk behind, and you can tweak it to fit different types of water or pollution levels. People are now hyped about super tiny materials called Nano adsorbents. They’re so small they’ve got tons of surface area to grab pollutants. Two cool ones are zeolites and carbon nanotubes (CNTs). Zeolites are like tiny cages that trap ions and help reactions go faster. CNTs are strong, bendy, and have some neat electrical and chemical properties. By mixing them, we made a special hybrid material called a nanocomposite to clean phosphate from water in a more efficient and targeted way. In this study, we tested how good it is by playing around with things like water acidity, how much material we used, how long it sat in the solution, and how much phosphate was present in the water samples. Materials and Methods To make our nanocomposite, we took 20 grams of zeolite and mixed it with just 0.03 grams of CNTs. We tossed them in a clean container, stirred them up for 30 minutes with a magnetic stirrer, then spun it in a centrifuge for 10 minutes to separate the solid part from the liquid. We dried the solid in an oven at 80°C for a whole day, then baked it at 600°C in a furnace for 3 hours to make it sturdy and enhance its structure. This process helped embed the CNTs into the zeolite network. For the actual tests, we made water samples with phosphate concentrations ranging from 10 to 50 mg/L in 100 mL of distilled water. We adjusted the water’s pH from 2 to 11 using sodium hydroxide or hydrochloric acid. We also tried different contact times (from 10 to 120 minutes) and different dosages of the material (from 0.01 to 0.05 grams) to figure out what setup gave the best phosphate removal results. These variables—pH, time, material amount, and phosphate level—all affect how well the material grabs phosphate, how much it can hold onto, and whether you can use it again for multiple rounds. We checked out: How it grabs phosphate: We tested two main models—Langmuir (where phosphate sticks in a single layer) and Freundlich (where it can form multilayers). How fast it works: We looked at pseudo-first-order (based on free sites) and pseudo-second-order (based on chemical bonding) kinetic models. We used a number called R² (correlation coefficient) to see which model fit the data better. Energy side of things: We calculated Gibbs free energy to figure out if the process happens spontaneously or not. We used materials like sodium hydrogen phosphate for the phosphate solution, nitric acid to clean CNTs, and sodium hydroxide for pH adjustment. Equipment included a super accurate digital scale, magnetic stirrer, centrifuge, furnace, shaker, oven, and lab tools like FTIR, FESEM, XRD, and BET to check out the material’s chemistry, surface, crystal structure, and surface area. We ran each test at least three times to make sure our data was reliable. Results and Discussion Our zeolite/CNT nanocomposite was awesome at cleaning phosphate! Here’s the scoop: FTIR tests showed a strong signal at 1643.02 cm⁻¹ with 135.54% absorption, meaning the surface had active sites perfect for grabbing phosphate ions. FESEM and XRD showed it has a smooth, crystalline structure with lots of mesopores—tiny holes that help trap phosphate really well. BET analysis confirmed the surface area was big, which means more places to hold pollutants. It worked best at pH 7 (which is like normal drinking water) after 60 minutes of contact time, removing 91% of the phosphate. When we added more phosphate (10 to 50 mg/L), the percentage of removal dipped slightly, but the total amount removed increased, which is a good sign. The process followed Langmuir and pseudo-second-order models closely, with an R² of 0.987, showing these models are spot-on. It still worked great even after three cycles of reuse, which makes it really promising for real-world applications where cost and durability matter. Our results line up with other scientific studies but stand out for a few reasons. Some researchers using modified materials only reached 39% phosphate removal, while our composite hit 91%. Another group got 91% too, but only under acidic conditions—ours worked great at neutral pH, which is easier to maintain and safer. Similar performance was seen with iron-CNT composites and hybrid materials like MOF/CNT or magnetic graphene oxide, but our focus on phosphate specifically gave it an edge. We didn’t study biosensors or multiple pollutants—just laser-focused on getting phosphate out, and it paid off. Conclusion Our zeolite/CNT nanocomposite is a total champ at cleaning phosphate from water. It worked best at pH 7 after 60 minutes, removing 91% of phosphate. Even at higher phosphate concentrations, it held strong. All tests—from FTIR and FESEM to BET and XRD—proved it’s got an excellent structure full of functional groups and pores. The Langmuir and pseudo-second-order models explained its behavior perfectly, and it stayed effective even after being reused three times. That’s a win for sustainability. This material could seriously help fix phosphate pollution in real settings. It’s cheap, strong, works under normal conditions, and doesn’t need fancy chemicals or extreme pH. The next thing to do is to scale it up — try it in larger water treatment systems like in municipalities or industry, perhaps even see how it does with other pollutants as well. It’s a move forward in the battle for cleaner water and a healthier environment. فسفر از عناصر ضروری برای رشد گیاهان و جانوران به‌شمار می‌رود، اما ورود بیش از حد آن از طریق فاضلاب و کودهای شیمیایی به منابع آبی منجر به آلودگی زیست ‌محیطی می‌گردد. این پژوهش با هدف بررسی کارایی نانوکامپوزیت زئولیت/نانولوله‌کربنی(CNT) در حذف یون فسفات از محلول‌های آبی و تحلیل ساختار و عملکرد آن تحت شرایط مختلف انجام شد. نانوکامپوزیت مورد نظر به روش سنتز شیمیایی تهیه و با استفاده از آنالیزهای FTIR، FESEM، XRD و BET مشخصه‌یابی گردید. نتایج آزمون XRD ساختار بلوری نانوکامپوزیت را تأیید کرد و طیف FTIR بیشترین جذب را در عدد موجی 02/1643 cm⁻¹ نسبت داد. آزمون BET سطح ویژه بالا و حضور مزوحفره ها را نشان داد و تصاویر FESEM نمایانگر مورفولوژی یکنواخت بودند. فرایند حذف فسفات در شرایط مختلفی از جمله pH، زمان تماس، دوز جاذب و غلظت فسفات بررسی شد. شرایط بهینه برای جذب فسفات در pH برابر 7 و زمان تماس 60 دقیقه با بازده حذف 91% به‌دست آمد. با افزایش غلظت اولیه فسفات، ظرفیت جذب افزایش و درصد حذف 48/78درصدکاهش یافت. مدل سینتیکی شبه‌مرتبه دوم و ایزوترم لانگمویر با ضریب تعیین (R²=0.987) بهترین تطابق را با داده‌های تجربی داشتند. نتایج بررسی ترمودینامیکی نشان داد که فرآیند جذب در دماهای مختلف از کارایی مناسبی برخوردار است. همچنین، نانوکامپوزیت پس از سه مرحله بازیافت، همچنان ظرفیت جذب قابل توجهی 50/24 mg/g و درصد حذف 68/81% را حفظ کرد. این یافته‌ها نشان‌دهنده پتانسیل بالای نانوکامپوزیت زئولیت/CNT در تصفیه آب و کاهش آلاینده‌های زیست‌محیطی هستند.

https://www.jess.ir/article_231117_45f2980c5e2041ed391298baceea70e6.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Bibliometric Analysis of the Global Sustainable Buildings Trend (2020–2025): Focusing on Integrating Smart Technologies in Energy Management, Improving Quality of Life, and Reducing Environmental Impacts تحلیل کتاب سنجی روند جهانی ساختمان‌های پایدار (2020–2025): با تمرکز بر ادغام فناوری‌های هوشمند در مدیریت انرژی، بهبود کیفیت زندگی و کاهش اثرات زیست‌محیطی 10660 10675 231123 10.22034/jess.2025.544659.2400 FA امیرحسین شیردل گروه معماری، دانشکده معماری و شهرسازی، دانشگاه شهید بهشتی، تهران، ایران. 0009-0006-2297-502X Journal Article 2025 09 02 ABSTRACT: The rapid growth of urbanization, climate change, and constraints on energy resources have underscored, more than ever, the necessity of developing buildings with optimized energy consumption, environmental resilience, and the integration of smart technologies. Despite remarkable progress in artificial intelligence, the Internet of Things, and Building Information Modeling, significant challenges remain in the practical integration of these technologies, the evaluation of their actual performance, and their social acceptance.This study was conducted with the aim of performing a bibliometric analysis of global research trends in sustainable, smart, and low carbon emission buildings over the period 2020–2025, in order to identify growth patterns, research fronts, and scientific linkages among authors and research institutions. The need for this research lies in the fact that identifying scientific streams and existing gaps enables more effective direction for future investigations and supportive policymaking.Data were extracted from the Lens.org database and analyzed using VOSviewer software (version 1.6.20) to conduct keyword co-occurrence, citation, and bibliographic coupling analyses. The findings revealed that, following continuous growth up to 2022, the field of sustainable and smart buildings has entered a phase of thematic reconfiguration, in which innovative digital technologies, intelligent energy management, enhancement of quality of life, and mitigation of environmental impacts have become central areas of focus. Network analysis indicated the presence of clusters encompassing energy management and smart systems, performance optimization and simulation, integration of renewable energy, climate-responsive design, artificial intelligence applications, smart cities, and life-cycle assessment. Furthermore, gaps were observed in the full integration of technologies, economic evaluation, and social acceptance. The results suggest that the future of this field will be grounded in the convergence of technology, policy, and the social sciences, and that by developing dynamic assessment frameworks, the path toward achieving self-sufficient, resilient, and climate adaptive buildings can be accelerated, ultimately contributing to a sustainable environment. EXTENDED ABSTRACT Introduction The building sector, as a pivotal component of the built environment, constitutes not merely a collection of physical structures but a complex socio-technical system that mediates the interaction between human activity and the natural environment. This sector plays a decisive role in meeting diverse functional, operational, and comfort needs while simultaneously exerting significant influence on global energy consumption patterns, natural resource utilization, urban environmental quality, and the trajectory of socio-economic development (Soltani, 2016; Mahdinejad & Asadpour, 2019; Asadpour et al., 2024a, 2024b; Shirdel et al., 2025a, 2025b). In contemporary urban contexts, rapid urbanization, unprecedented population growth, and evolving lifestyle patterns have collectively intensified the demand for heterogeneous building typologies and functional spaces. These pressures manifest as heightened demands on infrastructure systems, substantial increases in energy use, accelerated rates of resource extraction, and expanded pollutant emissions across local, regional, and global scales. The environmental consequences of these trends are profound. Increased emissions accelerate climate change dynamics, resource depletion undermines planetary boundaries, and habitat disruption contributes to biodiversity loss and ecosystem fragmentation (Beladi & Yunusa‑Kaltungo, 2025; Asadpour & Habibi, 2015). Empirical evidence increasingly demonstrates that conventional planning and construction paradigms—rooted in linear resource flows and static performance assumptions—are insufficient to address these interlinked challenges (Asadpour et al., 2016). Against this backdrop, the integration of smart technologies emerges as a transformative strategy. Automated energy management systems enable dynamic optimization of energy flows, environmental sensors facilitate real-time monitoring of air quality and thermal comfort, and advanced analytics derived from consumption data inform predictive maintenance, behavioral feedback, and demand-response mechanisms (González‑Briones et al., 2018). The convergence of these tools not only offers measurable pathways for reducing greenhouse gas emissions but also advances occupant well-being through enhanced comfort, health, and user autonomy. This technological potential aligns closely with the operational and design imperatives of sustainable and net-zero energy buildings, architectural typologies that reconcile human comfort with environmental stewardship. Such buildings embody an integrative approach—balancing energy efficiency, renewable energy uptake, resource circularity, and social responsibility—thus contributing directly to the broader objectives of sustainable urban development (Dwaikat & Ali, 2016). Materials and methods This study conducts a scientometric analysis of global research on sustainable buildings, emphasizing the integration of smart technologies for energy management, quality of life improvement, and environmental impact reduction. Recognizing net‑zero and energy‑positive buildings as pivotal in addressing climate change, it maps scientific developments from 1950 to 2025. A total of 1,570 English‑language publications (2020–2025) in the field of architecture—comprising research articles, reviews, and conference papers—were retrieved from the Lens.org database. Themes included smart design, energy optimization, intelligent management systems, indoor environmental quality, and carbon reduction. Manual data cleaning ensured accuracy and consistency. Using VOSviewer (v.1.6.20), the study generated knowledge maps, identified collaboration networks, and analyzed keyword co‑occurrences and co‑citation patterns. Results reveal key emerging topics, core technologies, and geographic and institutional linkages shaping the field, offering insights to advance scientific cooperation and practical strategies for sustainable, technology‑integrated building design. Results and discussion The scientometric analysis of publications between 2020 and 2026 reveals a clear growth–decline pattern. Scientific production began moderately in 2020, increased substantially in 2021, and peaked in 2022 with over 420 documents. The subsequent drop in 2023 to about 270 outputs was followed by a slight recovery in 2024, while 2025–2026 show reduced figures—likely due to incomplete database indexing. Throughout this period, journal articles remained dominant, conference papers held a notable secondary share, and preprints contributed modestly during peak years. Source analysis shows Sustainability, Energies, and Buildings as the top three journals, jointly capturing the highest visibility and output share. Other outlets displayed more specialized and dispersed publication patterns. Authorship network mapping identified 75 prolific researchers within a highly interconnected cluster, reflecting intensive collaboration and thematic alignment. Citation and bibliographic coupling mapping revealed major clusters around smart energy management, building performance optimization, renewable integration, and climate‑responsive design, with bridging themes in AI applications, life‑cycle assessment, and urban smart policy. High‑impact articles act as central hubs, linking technical, environmental, and policy domains. The dense connectivity and interdisciplinary integration observed suggest that smart, sustainable building research has reached a state of scientific maturity, with strong collaborative frameworks. Identified clusters and network structures highlight targeted pathways for innovation, bridge knowledge gaps, and support policy and practical strategies for advancing energy efficiency, environmental performance, and quality of life in the built environment. Conclusion The field of sustainable and smart buildings has rapidly advanced alongside AI, IoT, and renewable energy, forming a new paradigm in architecture and urbanism. Bibliometric findings show global expansion in scope and conceptual overlap, with research centered on smart energy management, quality of life, and environmental impact reduction. Key gaps remain in large‑scale integration of BIM, IoT, and AI, economic policies, user acceptance, resilience to climate extremes, and comprehensive performance evaluation. Future research priorities include AI‑driven energy optimization, green finance models, user–building interaction studies, resilient self‑sufficient design, continuous performance monitoring, cross‑cultural best‑practice transfer, and circular‑economy material lifecycle strategies. رشد پرشتاب شهرنشینی، تغییرات اقلیمی و محدودیت منابع انرژی، ضرورت توسعه ساختمان‌هایی با مصرف بهینه انرژی، تاب‌آوری محیطی و بهره‌گیری از فناوری‌های هوشمند را بیش از پیش آشکار کرده است. با وجود پیشرفت‌های چشمگیر در حوزه‌های هوش مصنوعی، اینترنت اشیاء و مدل‌سازی اطلاعات ساختمان، همچنان چالش‌هایی جدی در یکپارچه‌سازی عملی این فناوری‌ها، ارزیابی عملکرد واقعی و پذیرش اجتماعی آن‌ها باقی مانده است. این پژوهش با هدف تحلیل کتاب‌سنجی روند جهانی تحقیقات در زمینه ساختمان‌های پایدار، هوشمند و کم‌اثر از نظر انتشار کربن، در بازه زمانی 2020 تا 2025 انجام شد تا الگوهای رشد، محورهای پژوهشی و پیوندهای علمی بین نویسندگان و مراکز تحقیقاتی شناسایی شود. ضرورت انجام این مطالعه در آن است که شناسایی جریان‌های علمی و خلأهای موجود، امکان جهت‌دهی کارآمدتر به تحقیقات آتی و سیاست‌گذاری‌های حمایتی را فراهم می‌آورد. داده‌ها از پایگاهLens.org استخراج و با استفاده از نرم‌افزار VOSviewer (نسخه 1.6.20)، تحلیل‌های هم‌وقوعی کلیدواژه‌ها، استنادی و هم‌پیوندی کتابشناختی انجام گرفت. نتایج نشان داد که پس از رشد مداوم تا سال 2022، حوزه ساختمان‌های پایدار و هوشمند وارد مرحله‌ای از بازتنظیم موضوعی شده است که در آن فناوری‌های دیجیتال نوآورانه، مدیریت هوشمند انرژی، ارتقای کیفیت زندگی و کاهش اثرات زیست‌محیطی به محورهای اصلی توجه بدل گشته‌اند. تحلیل شبکه‌ها بیانگر خوشه‌هایی شامل مدیریت انرژی و سیستم‌های هوشمند، بهینه‌سازی و شبیه‌سازی عملکرد، ادغام انرژی‌های تجدیدپذیر، طراحی اقلیمی، کاربرد هوش مصنوعی، شهر هوشمند و ارزیابی چرخه عمر است. همچنین شکاف‌هایی در یکپارچه‌سازی کامل فناوری‌ها، ارزیابی اقتصادی و پذیرش اجتماعی مشاهده شد. یافته‌ها نشان می‌دهد آینده این حوزه بر همگرایی میان فناوری، سیاست‌گذاری و علوم انسانی استوار خواهد بود و با توسعه چارچوب‌های ارزیابی پویا، می‌توان مسیر دستیابی به ساختمان‌هایی خودکفا، تاب‌آور و سازگار با اقلیم را تسریع کرد و به محیط زیستی پایدار دست یافت.

https://www.jess.ir/article_231123_ef68a45ae6bcdf2b57303dfa052c1777.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Spatial Analysis of More-Than-Three-Decade Green Infrastructure Change Using Landscape Ecology Approach in Borujerd City تحلیل فضایی بیش از سه دهه تغییرات زیرساخت‌های سبز با استفاده از رویکرد اکولوژی سیمای سرزمین در شهر بروجرد 10676 10689 231276 10.22034/jess.2025.544552.2402 FA ایمان سعیدی گروه علوم و مهندسی محیط زیست، دانشکده منابع طبیعی و محیط زیست، دانشگاه ملایر 0000-0001-8749-3829 حسن دارابی گروه مهندسی طراحی محیط زیست، دانشکده محیط زیست، دانشگاه تهران، تهران 0000-0002-9353-4639 Journal Article 2025 09 04 1. Introduction Green Infrastructure (GI) is a foundational network of natural and semi-natural elements crucial for delivering ecosystem services, enhancing biodiversity, and improving urban well-being. In semi-arid and arid regions like Iran, GI faces a paradoxical threat: its necessity is greatest due to harsh climatic conditions, yet its viability is most compromised by rapid, unplanned urban expansion and intense water stress. While the dynamics of GI are well-studied in temperate climates, a significant research gap exists regarding its long-term spatiotemporal changes and ecological consequences in water-scarce urban settings. This study addresses this critical gap by conducting a systematic, metric-based analysis of GI transformations in Borujerd, Iran, a representative mid-sized city in the semi-arid Zagros region. Over a 35-year period (1990–2025), this research moves beyond simple land cover change detection to quantify the qualitative degradation and fragmentation of the urban ecological matrix, providing insights critical for sustainable urban planning in arid environments. 2. Methodology The study employed a robust multi-temporal remote sensing and spatial analysis framework. The study area encompassed Borujerd city and its ecologically connected peripheral villages to capture the complete urban-rural ecosystem. The methodology was structured in three primary phases: 2.1. Data Acquisition and Pre-processing: Four Landsat satellite images (Landsat 5/TM for 1990 and 2000; Landsat 8/OLI for 2018; Landsat 9/OLI-2 for 2025) were acquired for the summer season. All images were pre-processed in TerrSet (v18.31) to Level 2 Surface Reflectance, with additional atmospheric correction using the Dark Object Subtraction (DOS) algorithm and geometric standardization to ensure cross-sensor comparability. 2.2. Land Cover Classification and Accuracy Assessment: Land cover was classified into three primary classes: (1) Built-up areas (urban fabric, infrastructure), (2) Green Infrastructure (parks, gardens, farms, natural vegetation), and (3) Barren land (bare soil, desertified areas). A supervised classification was performed using the Maximum Likelihood Classifier (MLC) algorithm. Accuracy was rigorously assessed using independent ground control points, resulting in high accuracy levels (Overall Accuracy >90%, Kappa Coefficient >0.82 for all years), meeting international standards for landscape studies. 2.3. Landscape Metric Analysis: The classified maps were exported to Fragstats (v4.2) to calculate 10 key landscape metrics at both the class and landscape levels. These metrics were selected to capture different dimensions of landscape change: Quantitative/Area Metrics: Class Area (CA), Percentage of Landscape (PLAND). Structural/Configuration Metrics: Number of Patches (NP), Largest Patch Index (LPI), Edge Density (ED), Landscape Shape Index (LSI), Effective Mesh Size (MESH). Functional/Pattern Metrics: Contagion (CONTAG), Shannon's Diversity Index (SHDI), Shannon's Evenness Index (SHEI). This multi-metric approach allowed for a comprehensive assessment of fragmentation, connectivity, and spatial heterogeneity. 3. Results and Discussion The results reveal a dramatic transformation of Borujerd's landscape, characterized by extensive urbanization and the severe fragmentation of its green spaces. 3.1. Land Cover Change: Built-up areas expanded explosively by 128% (from 1,206.54 ha in 1990 to 2,748.6 ha in 2025), primarily at the expense of barren land, which decreased by 25%. The GI area showed a fluctuating trend, decreasing from 4,296.6 ha in 1990 to a low of 3,849.84 ha in 2000, before a partial recovery to 4,388.94 ha by 2025. This late recovery is likely due to afforestation efforts or agricultural expansion but masks a more profound qualitative degradation. 3.2. Green Infrastructure Fragmentation: Despite the net recovery in area by 2025, the landscape metrics revealed severe structural fragmentation: The Number of Patches (NP) for GI increased by 74% (from 651 to 1132), indicating that once-continuous green areas were subdivided into smaller, isolated pieces. The Largest Patch Index (LPI) decreased by 17%, signifying the loss of core habitat areas essential for supporting biodiversity. Edge Density (ED) increased, indicating more complex and irregular boundaries between green patches and urban areas, increasing edge effects. Effective Mesh Size (MESH) nearly halved, demonstrating a significant increase in the isolation of GI patches and a collapse of ecological connectivity. 3.3. Overall Landscape Degradation: At the landscape level, connectivity (CONTAG) decreased significantly from 84.48 to 73.9, indicating a breakdown in the spatial cohesion of the entire landscape. Increased diversity (SHDI) and evenness (SHEI) reflected a more heterogeneous and intermixed landscape, which in this context is a negative consequence of fragmentation and urban sprawl rather than increased ecological richness. 3.4. Discussion of Implications: The findings align with global studies on urban ecological fragmentation but highlight acute challenges specific to semi-arid regions. The intense fragmentation increases water stress, as smaller, isolated green patches have higher edge-to-area ratios, leading to greater evapotranspiration and increased irrigation demands—a critical issue in water-scarce Iran. This creates a negative feedback loop where maintaining ecological aesthetics exacerbates water resource depletion. The drivers of this change are linked to rapid population growth, rural-urban migration, and municipal policies that prioritized industrial and commercial development over ecological conservation, leading to low-density, sprawling expansion (confirmed by the rising LSI of built-up areas). The study underscores that in arid environments, the spatial configuration of GI is a more critical determinant of its sustainability and ecological functionality than its total area alone. 4. Conclusion and Policy Recommendations This study concludes that rapid urbanization has driven the severe fragmentation of GI in Borujerd, significantly reducing ecological connectivity and functionality despite a recent increase in green space area. The quantitative and qualitative metrics provided a much more nuanced understanding than area change alone could offer. The findings necessitate a paradigm shift in urban planning for semi-arid Iranian cities. Key policy recommendations include: 1. Adopting a Hierarchical GI Network: Planning should focus on creating a connected network of core habitats (protecting large existing patches), linear corridors (along rivers, roads), and small integrated green spaces in dense urban fabrics. 2. Water-Sensitive Design: Mandating the use of native, drought-resistant plant species to reduce irrigation needs and integrating blue-green infrastructure for rainwater harvesting and stormwater management. 3. Adaptive Zoning and Governance: Implementing adaptive zoning codes that limit impervious surfaces and promote infill development over urban sprawl. Establishing interdisciplinary "green councils" to unify urban planning, water management, and environmental agencies. 4. Strategic Conservation: Prioritizing the conservation of remaining barren lands not as vacant lots, but as crucial areas for groundwater recharge and future green space expansion. This research establishes landscape metrics as vital diagnostic tools for arid cities navigating planetary boundaries. Future studies should integrate hyperspectral imagery to distinguish native from non-native vegetation and employ hydrological models to quantify the water trade-offs associated with different GI planning scenarios. زیرساخت‌های سبز، بخش تفکیک ناپذیر عرصه های شهری است که وظیفه ارائه خدمات اکوسیستمی را برعهده دارد. برهمین اساس نیز بر کیفیت زندگی شهری اثرگذار است. اما به دلیل رشد سرسام آور شهری این زیرساخت ها به صورت مداوم در معرض تهدید و در نتیجه کاهش چشمگیری ساختاری و عملکردی قرار دارند. این موضوع در مناطق نیمه‌خشک و خشک، به‌ویژه در شرایط تنش آبی، نیازمند بررسی عمیق‌تری است. بر همین اساس هدف این مطالعه بررسی نظام‌مند، مبتنی بر معیار و با صراحت زمانی برای آشکار کردن روندها تغییر زیرساخت های سبز شهری به‌کارگیری معیارهای بوم‌شناسی سیمای سرزمین است. به این منظور تجزیه و تحلیل مکانی-زمانی پویایی زیرساخت‌های سبز (GI) در بروجرد، ایران (1990-2025) با استفاده از تصاویر لندست، صورت گرفته است. در ابتدا، اقدم به طبقه بندی پوشش زمین به مناطق ساخته شده، زیرساخت‌های سبز و زمین‌های بایر شد سپس روند تغییرات زیرساخت‌های سبز با استفاده از 10 متریک اکولوژی سیمای سرزمین تحلیل شد. نتایج نشان می‌دهد شهرنشینی سریع (گسترش 128٪) باعث گسستگی شدید زیرساخت سبز شده است. معیارهای کلیدی - تراکم لکه (NP ↑)، تراکم لبه (ED ↑) و شاخص بزرگترین لکه (LPI ↓) نشان دهنده تجزیه زیستگاه، علیرغم بهبود نسبی زیرساخت سبز تا سال 2025 هستند، اتصال سیمای سرزمین (CONTAG) به طور قابل توجهی کاهش یافته است.. این روند دال برتشدید تنش آبی در نواحی خشک و نیمه‌خشک است. چراکه زیرساخت‌های سبز گسسته نیاز به آبیاری بیشتری دارد. از صحت ، Fragstats و TerrSet کمی‌سازی قوی (OA >90٪، Kappa >0،82) ارائه دادندکه زیرساخت‌های آبی-سبز یکپارچه و شبکه‌های اکولوژیکی سلسله مراتبی نیازمند مدیریتی متناسب برای پیشگیری از تداوم روند گسستگی و افزایش تاب‌آوری در شهرهای کم آب ایران است. .

https://www.jess.ir/article_231276_f6c5fe9e207a16fb771e2231a9f30851.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Comparing and Investigating the Effects of Income Inequality on Air Pollution; Case Study: Selected Member Countries of the Shanghai Cooperation Organization مقایسه و بررسی اثرات نابرابری درآمد بر آلودگی هوا؛ مطالعه موردی: کشورهای عضو سازمان همکاری شانگهای 10690 10704 231696 10.22034/jess.2025.548118.2409 FA حمیدرضا ایزدی دانشیار گروه اقتصاد، دانشکده مدیریت و علوم انسانی، دانشگاه دریانوردی و علوم دریایی چابهار، چابهار، ایران 0000-0003-2297-6429 الما گمشادزهی کارشناس ارشد اقتصاد محیط زیست، دانشکده مدیریت و علوم انسانی، دانشگاه دریانوردی و علوم دریایی چابهار، چابهار، ایران 0000-0003-2297-6429 Journal Article 2025 09 22 Environmental challenges, notably air pollution and climate change, have increasingly attracted scholarly and policy attention in recent years. Among the contributing factors, income inequality may affect pollution levels by altering consumption patterns and shaping societal demand for environmental quality. This study investigates the impact of income inequality on air pollution in member countries of the Shanghai Cooperation Organisation, employing the Panel Autoregressive Distributed Lag (ARDL) approach across the period 2000–2022. The results reveal that rising income inequality exerts a statistically significant positive effect on carbon dioxide emissions, suggesting that unequal income distribution contributes to environmental degradation. Moreover, the findings underscore the mitigating roles of renewable energy consumption, gross domestic product, and education levels in reducing environmental pollutants. These insights offer valuable guidance for policymakers seeking to address income inequality while advancing air quality and environmental sustainability. Introduction Income distribution has long been debated in economic policy discussions. While the focus of developing economies often centers on growth, advanced economies emphasize equitable income distribution to improve social welfare. Air pollution, particularly carbon dioxide emissions, is a critical environmental issue affecting health and economic stability. The Kuznets Environmental Curve suggests a nonlinear relationship where pollution initially rises with economic growth but later declines as economies adopt sustainable practices. This study investigates whether income inequality influences air pollution patterns in SCO countries, considering economic structure, policy interventions, and environmental regulations. In recent decades, the accelerating pace of industrialization and urbanization has intensified environmental challenges, particularly air pollution, which poses severe risks to public health and ecological sustainability. At the same time, income inequality has emerged as a critical socio-economic issue that not only affects social welfare but may also influence environmental quality through consumption behavior, energy demand, and political economy mechanisms. Although a growing body of literature has examined the inequality–environment nexus at the national level, limited attention has been paid to its implications within the framework of regional economic organizations, where member states share common interests and cooperative policies. Against this backdrop, the present study investigates the impact of income inequality on air pollution in the Shanghai Cooperation Organization (SCO) member countries over the period 2000–2022, providing novel insights into the interaction between socio-economic disparities and environmental degradation in a multilateral context. Materials and methods This research employs Panel ARDL modelling to analyze the relationship between income inequality (Gini coefficient) and air pollution (CO₂ emissions) in selected SCO member states from 2000 to 2022. Additional variables include GDP per capita, urban population growth, literacy rates, and renewable energy consumption. The dataset was obtained from the World Bank and other official sources. Unit root tests were conducted to confirm stationarity, followed by cointegration analysis to assess long-term relationships. The model estimates both short-run and long-run effects to provide a comprehensive understanding of policy implications. The study employs a Panel Autoregressive Distributed Lag (Panel ARDL) approach, which allows for the estimation of both short-run and long-run relationships among the variables while accommodating mixed orders of integration. The analysis covers 11 SCO member states, namely Russia, China, India, Iran, Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, Pakistan, Belarus, and Mongolia. The dependent variable is carbon dioxide (CO₂) emissions, used as a proxy for air pollution. The primary explanatory variable is the Gini coefficient as a measure of income inequality, while control variables include GDP per capita, renewable energy consumption, urbanization rate, and literacy rate. Diagnostic tests such as cross-sectional dependence, Chow, Hausman, and Pedroni co-integration tests, as well as an error correction mechanism (ECM), were conducted to validate the robustness of the results. Results and discussion Findings confirm that income inequality negatively impacts air quality. Higher inequality correlates with increased CO₂ emissions, reinforcing the view that unequal economic structures contribute to environmental degradation. Countries with lower inequality demonstrate better pollution control due to broader access to cleaner technologies and stronger environmental governance. The results also show that increasing renewable energy consumption and GDP per capita significantly reduce pollution levels. Educational attainment plays a supportive role by fostering environmental awareness. These findings highlight the necessity of inclusive growth policies and clean energy investments to curb pollution. Empirical results reveal several important outcomes: - Income inequality exerts a negative and statistically significant effect on environmental quality, implying that greater disparities in income distribution lead to higher CO₂ emissions and worsened air pollution. - Renewable energy consumption and educational attainment significantly reduce CO₂ emissions in the long run, underscoring their role in fostering sustainable development. - The effect of GDP per capita follows the Environmental Kuznets Curve (EKC) hypothesis, suggesting that economic growth initially intensifies air pollution but subsequently contributes to environmental improvement once a certain income threshold is surpassed. - Urbanization is positively associated with CO₂ emissions, reflecting the environmental pressures of rapid population growth in urban areas. - The error correction term of -0.25 indicates a relatively fast speed of adjustment, with approximately 25% of short-run disequilibrium corrected annually toward long-run equilibrium. Conclusion This study underscores the critical intersection of economic inequality and environmental sustainability. Addressing income disparities through progressive taxation and redistributive policies can play a vital role in mitigating pollution. Furthermore, expanding renewable energy infrastructure and integrating environmental education into policy frameworks are essential strategies for long-term improvement. SCO member nations can leverage collaborative policymaking to balance economic growth with ecological responsibility. The findings confirm that income inequality is a significant determinant of environmental degradation in SCO member countries. Reducing inequality not only enhances social cohesion but also contributes to mitigating air pollution and improving environmental quality. Furthermore, investments in renewable energy, educational expansion, and sustainable economic growth represent effective pathways for reducing carbon emissions. From a policy perspective, SCO member states should prioritize: 1. Redistributive fiscal reforms—including progressive taxation and targeted social spending—to reduce inequality and strengthen environmental outcomes. 2. Environmental taxation and incentives—imposing levies on highly polluting industries and reallocating revenues toward renewable energy projects and clean technologies. 3. Support for low-income households—through subsidies and access to energy-efficient housing and infrastructure, reducing their reliance on polluting energy sources. 4. Regional cooperation—formulating harmonized environmental policies and promoting the exchange of green technologies among SCO members. 5. Educational initiatives—raising awareness of environmental issues and fostering eco-friendly consumption and production practices. در سال‌های اخیر، چالش‌های زیست‌محیطی از جمله آلودگی هوا و تغییرات اقلیمی، توجه فزاینده‌ای را از سوی سیاست‌گذاران و پژوهشگران به خود جلب کرده‌اند. یکی از عوامل کلیدی در این زمینه، نابرابری درآمدی است که می‌تواند از طریق تغییر در الگوهای مصرف و تقاضای اجتماعی برای کیفیت محیط‌زیست، بر شدت آلودگی تأثیر بگذارد. این مطالعه با بهره‌گیری از روش پانل ARDL، به بررسی تأثیر نابرابری درآمدی بر آلودگی هوا در کشورهای عضو سازمان همکاری شانگهای طی دوره زمانی ۲۰۰۰ تا ۲۰۲۲ می‌پردازد. نتایج نشان می‌دهد که افزایش نابرابری درآمدی در این کشورها اثر مثبت و معناداری بر انتشار دی‌اکسید کربن دارد؛ به‌گونه‌ای که توزیع نابرابر درآمد می‌تواند منجر به کاهش کیفیت محیط‌زیست و تشدید مسائل مربوط به آلودگی هوا شود. افزون بر این، یافته‌های پژوهش نقش مؤثر مصرف انرژی‌های تجدیدپذیر، تولید ناخالص داخلی و سطح آموزش را در کاهش آلاینده‌های زیست‌محیطی برجسته می‌سازد. این بینش‌ها می‌توانند به سیاست‌گذاران در طراحی راهبردهای مؤثر برای مدیریت نابرابری درآمدی و کاهش آلودگی هوا یاری رسانند.

https://www.jess.ir/article_231696_826731472a553ec15186482ca5152cec.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Survey of distance indices to estimate the spatial distribution pattern of Ephedra major and Hymenocrater calycinus medicinal species in southwest rangelands of Bojnord بررسی شاخص‌های فاصله‌ای برآورد الگوی پراکنش مکانی گونه‌های دارویی Ephedra major و Hymenocrater calycinus در مراتع جنوب غرب بجنورد 10705 10718 234928 10.22034/jess.2025.547738.2407 FA علی محمد اسعدی ﮔﺮوه مهندسی طبیعت، دانشکده کشاورزی ﺷﯿﺮوان ،دانشگاه بجنورد، اﯾﺮان، Journal Article 2025 09 18 ABSTRACT Ephedra major and Hymenocrater calycinus are among the bushy and shrub plants resisting to drought conditions. These species have a very important role in soil protection, medicinal and forage value in arid areas. This research was conducted in order to investigate the distance indices to determine the species spatial distribution pattern of Ephedra major and Hymenocrater calycinus in the southwest rangelands of Bojnord. Vegetation sampling was done by systematic-random method, therefore, 5 transects of 100 meters were determined in each working unit. To collect information from the habitat, the nearest species and nearest neighbor distance method was used. Evaluation was done by using distance indices of Eberhart, Hinez, Pielou, T-square, Hopkins, Holgate and Johnson and Zimmer. The findings showed that most of the investigated indices accepted the clumped distribution pattern, so it can be said that the spatial distribution pattern of Ephedra major and Hymenocrater calycinus is clumped. Results showed the uniform pattern of Holgate and Pielou indices for Ephedra major species and Hopkins, Holgate and Pielou indices for Hymenocrater calycinus species. In general, the use of plant distribution patterns plays a significant role in choosing the appropriate sampling method, ecological interpretations and providing management approaches. Key words: Ephedra major, Distribution pattern, Distance indices, Hymenocrater calycinus, Rangelands. EXTENDED ABSTRACT Introduction Ephedra major is dioecious and evergreen bushy and shrubs growing to 20-200 cm tall; woody stems well developed, erect or mostly procumbent, thick; herbaceous branchlets are slender, striate, smooth, bluish-green or grayish-green, 1-1.5 mm in diameter, internodes short, 1-3 cm × 1-1.5 mm, finely furrowed. Leaves are opposite, leathery, greenish or brownish, 1.5-3 mm, connate for ca. 3/4 their length, free part bluntly triangular. Female cones usually opposite at nodes, shortly pedunculate, elongate-ovoid or ovoid at maturity, 8-10 × 4-5 mm; bracts in 3 pairs, apical pair connate for ca. 2/3 their length, red and fleshy at maturity; integument tube to 2 mm, straight or slightly curved, slightly exerted. Seeds usually 1, elongate-ovoid, 5-7 × 2.5-3 mm and male cones are sessile, subglobose, 4-5 mm long. Ephedra has long been used as a medicinal plant to reduce fever, initiate perspiration, manage asthma, and treat coughing. Hymenocrater calycinus (Boiss.) Benth. is one of medicinal herbs in Lamiaceae family of Iran and it is growing natural habitats in the north east of Iran. In traditional medicine, this plant use for diuretic, flu treatment, antifungal, antibacterial and antioxidant. Knowledge of the spatial distribution pattern of plant communities is essential for understanding many questions in ecology and management of natural ecosystems. Ephedra major and Hymenocrater calycinus are among plants resistant to drought conditions and play a very important role in soil protection, medicinal and fodder value in dry areas. This survey was conducted in order to investigate the distance indices to determine the distribution pattern of Ephedra major and Hymenocrater calycinus species in the mountainous shrub rangelands in the southwest of Bojnord with an area of about 9300 hectares. Materials and Methods Vegetation sampling was done by systematic-random method, therefore, 5 transects of 100 meters were determined in each work unit (north and south slopes). To collect data from the site, the nearest species and nearest neighbor distance method was used. Evaluation was done using Eberhart, Hinez, Pielou, T-square, Hopkins, Holgate and Johnson and Zimmer distance indices. Results and Discussion The findings showed that among the distance indices, Eberhart, Hopkins, Johnson and Zimmer, T-square and Hinez indices with values of 2.205, 0.53, 6.178, 0.653 and 2.603 respectively for Ephedra major species and Eberhart, Johnson and Zimmer, T-square and Hinez indices with the values of 1.687, 4.632, 0.547 and 1.643, respectively, for Hymenocrater calycinus species, the pattern of distribution in the studied habitat is clumped. The results showed that the indices of Holgate and Pillow with the values of -0.473 and 0.374 respectively and Hopkins, Holgate and Pillow with the values of 0.43, -0.485 and 0.798 respectively for Ephedra major and Hymenocrater calycinus species showed a uniform distribution pattern. Because most of the examined indicators accepted the clumped pattern, therefore, for the management plans of the region using these plants, the clumped pattern must be considered. Generaly, the use of spatial patterns of plants in providing management solutions can contain an important point for those involved in the executive departments of natural ecosystems renovation that successful plans for the renovation and improvement of rangelands follow the natural patterns which are usually clustereds. Conclusion In conclusion in the investigate, the results showed that most of the surveyed indicators accepted the clumped distribution pattern, so it can be said that the spatial distribution pattern of Ephedra major and Hymenocrater calycinus is clumped in the survey sites. Based on the findings obtained from the study of other researchers, the clumped type is the most commonly observed plants spatial pattern in natural ecosystems. Spatial patterns of plants play a significant role in recognizing and solving ecological problems and introducing management strategies. Distribution patterns are of great importance in studying the formation of plant communities, and the results of the estimation of plant factors may be affected by the distribution pattern. By studying the distribution pattern in plant communities, one can gain a lot of knowledge about the uniformity and non-uniformity of the habitat, the type of reproduction and reproduction, biodiversity, plant spread, competition, and better protection of ecosystems. The distribution pattern of plant species also affects the sampling method and certainly the number of samples required. It should be noted that the type of dominant plant species in each habitat and the specific conditions of the plants under study, plants with different densities and with different distribution patterns can result in different findings, therefore, choosing a suitable index for evaluating the plants of the habitat is of great importance and should be given priority. The findings of this study can contain an important point for stakeholders and managers of executive departments for the restoration of natural ecosystems, which is emphasized by this study. Successful plans for the restoration and improvement of natural resources follow natural patterns that are usually cumulative. افدرا و گل اروانه از جمله گیاهان درختچه ای و بوته ای مقاوم به شرایط خشکی هستند. این گونه ها نقش بسیار مهمی در حفاظت خاک، ارزش دارویی و علوفه ای در نواحی خشک ایفا می نمایند. این تحقیق به منظور بررسی شاخص های فاصله ای تعیین الگوی پراکنش گونه ای افدرا و گل اروانه در مراتع جنوب غرب بجنورد انجام شد. نمونه برداری پوشش گیاهی به روش سیستماتیک- تصادفی انجام شد، از این رو در هر واحد کاری 5 ترانسکت 100 متری مشخص شد. با استفاده از شاخص های فاصله ای ابرهارت، هینز، پیلو، مربع T، هاپکینز، هولگیت و جانسون و زیمر ارزیابی انجام شد. یافته ها نشان داد که غالب شاخص ها مورد بررسی الگوی پراکنش کپه ای را پذیرفتند، بنابراین می توان گفت که الگوی پراکنش مکانی افدرا و گل اروانه به صورت کپه ای است. نتایج نشان داد که شاخص های هولگیت و پیلو برای گونه افدرا و هاپکینز، هولگیت و پیلو برای گونه گل اروانه الگوی پراکنش مکانی را به صورت یکنواخت معرفی نمودند. به طور‌کلی، کاربرد الگوهای مکانی گیاهان در ارایه راهکارهای مدیریتی می‌تواند حاوی نکته‌ای مهم برای دست‌اندرکاران بخش‌های اجرایی احیای زیست‌بوم‌های طبیعی باشد که طرح‌های موفق احیا و اصلاح مراتع از الگوهای طبیعی که معمولا کپه‌ای است پیروی نمایند.

https://www.jess.ir/article_234928_027206f22522b9ead68adc7f8547ff6e.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Removal of Pollutant Phenanthrene from Soil Washing Wastewater Using Mathematical Model حذف آلاینده فنانترن از پساب حاصل از خاکشوئی با استفاده از مدل ریاضی 10719 10733 235583 10.22034/jess.2025.547785.2408 FA ملیکا علی شیرازی دانشکده محیط زیست پردیس بین المللی کیش دانشگاه تهران 0000-0003-3272-6992 سعید گیتی پور دانشکده محیط زیست دانشگاه تهران 0000-0002-0694-7110 مجید بغدادی داشکده محیط زیست دانشگاه تهران 0000-0001-9816-764X Journal Article 2025 09 25 Polycyclic aromatic hydrocarbons (PAHs) are among the most persistent and hazardous organic pollutants found in natural ecosystems, and phenanthrene, a three-ring PAH, has received particular attention because of its toxicity, environmental persistence, and ability to accumulate in soil and aquatic environments. The contamination of wastewater with phenanthrene is largely the result of incomplete combustion of fossil fuels, leakage from petroleum refining processes, and a range of industrial and urban activities. Once released, phenanthrene exhibits strong hydrophobicity and chemical stability, characteristics that make it difficult to degrade naturally and that promote its long-term accumulation in sediments, soils, and aquatic environments. Numerous studies have shown that phenanthrene is both carcinogenic and mutagenic, while also contributing to cardiovascular disease, reproductive disorders, and developmental abnormalities in humans and other organisms. Its ability to bioaccumulate and biomagnify through food chains, coupled with its persistence in the environment, makes phenanthrene a serious ecological and public health hazard. For this reason, the development and implementation of effective treatment methods for wastewater contaminated with phenanthrene is an urgent priority in environmental engineering and pollution management. The selection of an optimal remediation strategy for phenanthrene-contaminated wastewater is a complex task because it requires balancing multiple and often conflicting factors. Technical effectiveness alone is not sufficient; a treatment method must also be economically feasible, technologically accessible, and compatible with existing social and regulatory conditions. This challenge is particularly acute in developing countries such as Iran, where financial resources are limited, advanced remediation technologies are not always accessible, and institutional frameworks for environmental management may lack consistency. Therefore, decision-making in this context must account for not only pollutant removal efficiency but also broader considerations such as cost of implementation, availability of suitable technologies, time required for treatment, and the potential to recover or reuse pollutants in order to offset remediation costs. In this study, a hybrid multi-criteria decision-making (MCDM) model was employed to address these challenges and to identify the most suitable method for treating wastewater contaminated with phenanthrene. The research combined the fuzzy analytic hierarchy process (FAHP) with the fuzzy VIKOR (FVIKOR) model to evaluate alternative remediation techniques under uncertainty and with multiple decision criteria. This integrated approach was designed to reduce subjectivity in expert judgments, handle conflicting criteria, and provide a transparent framework for ranking options. The evaluation criteria were first identified through a comprehensive review of the literature and by consulting experts in petroleum pollution management and environmental remediation. Four main indicators were selected: cost, technology availability, pollutant recovery potential, and time. Expert opinions gathered through structured questionnaires were analyzed using FAHP to assign weights to these indicators. The results revealed that cost was the most influential factor, accounting for 46% of the decision-making weight, followed by technology availability with 39%, pollutant recovery potential with 9%, and time with only 6%. These findings reflect the reality that in developing regions, economic feasibility and accessibility of technologies dominate environmental decision-making, often outweighing other considerations such as pollutant recovery or treatment speed. Five remediation methods were shortlisted for evaluation: reverse osmosis membrane treatment, potassium salt-assisted membrane treatment, chemical oxidation, photocatalytic oxidation, and biological degradation using microorganisms. Each method was assessed using FVIKOR, which calculates three parameters—S (group utility, reflecting the overall performance of an option across criteria), R (individual regret, reflecting the worst performance across criteria), and Q (the compromise solution index that combines S and R into a single ranking measure). The results demonstrated clear differences in the performance of these methods. The reverse osmosis membrane technique achieved the best overall ranking with values of R = 0.205, S = 0.274, and Q = 0.002. The potassium salt membrane technique followed closely, with R = 0.214, S = 0.271, and Q = 0.005. Chemical oxidation ranked third with R = 0.207, S = 0.331, and Q = 0.028, while biological degradation and photocatalytic oxidation were less favorable, with higher costs, longer treatment times, or limited technological feasibility leading to R, S, and Q values that placed them at the bottom of the ranking. The dominance of membrane-based technologies in this analysis highlights their effectiveness and adaptability for treating phenanthrene-contaminated wastewater. Reverse osmosis is widely recognized for its ability to remove a broad range of organic and inorganic pollutants with high efficiency and reliability. Its relatively short treatment time and compatibility with different wastewater compositions make it particularly suitable for urgent remediation needs. The potassium salt membrane method, while slightly less efficient than reverse osmosis in the model, remains attractive because of its lower operational costs, its ability to recover pollutants during the treatment process, and its strong compatibility with local conditions. Chemical oxidation methods, although capable of degrading phenanthrene, are less practical in the Iranian context due to the high costs of chemicals, risks of secondary pollution, and complex operational requirements. Biological degradation, though environmentally sustainable and theoretically appealing, is constrained by slow treatment times and sensitivity to environmental conditions, which reduces its feasibility for large-scale applications. Photocatalytic oxidation, despite its promise in laboratory settings, suffers from high costs and scalability issues, making it less suitable for immediate implementation in resource-limited settings. The results of this study have broader implications for environmental policy and management. The high weighting of cost and technology availability suggests that without investment in infrastructure and technology transfer, even highly effective remediation methods may remain impractical in many developing countries. This underscores the importance of policies that reduce the financial barriers to advanced remediation technologies, such as subsidies, international cooperation, or technology-sharing agreements. Furthermore, the incorporation of pollutant recovery into the decision-making model points to the potential benefits of integrating circular economy principles into wastewater management. By designing treatment methods that not only remove but also recover valuable by-products, countries can offset some of the costs associated with remediation, making advanced technologies more economically viable. This approach could also create new opportunities for resource efficiency and sustainability, turning waste into a potential source of value rather than solely a liability. Another key contribution of this study is the demonstration of the value of hybrid MCDM approaches in environmental engineering. Traditional decision-making models often struggle with uncertainty and subjectivity, particularly when expert opinions differ or when data is incomplete. By applying FAHP to weight the criteria and FVIKOR to rank the alternatives, this study was able to incorporate fuzzy logic and triangular fuzzy sets to manage uncertainty more effectively. The integration of expert knowledge with quantitative modeling enhanced the robustness and credibility of the findings, offering a replicable framework for future studies in other contexts or with other pollutants. Moreover, the transparency of the model provides a structured basis for dialogue among stakeholders, facilitating consensus-building and more informed decision-making in environmental management. In conclusion, this study identified reverse osmosis membrane treatment and potassium salt-assisted membrane treatment as the most suitable technologies for the remediation of wastewater contaminated with phenanthrene under the specific economic, technological, and social conditions of Iran. These findings are not only supported by the mathematical modeling but also consistent with experimental evidence reported in the literature, which confirms the high efficiency of membrane technologies in removing PAHs from wastewater. More broadly, the research underscores the need to approach environmental remediation holistically, balancing technical efficiency with cost-effectiveness, technological feasibility, and opportunities for pollutant recovery. For policy-makers, engineers, and industry stakeholders, the results highlight the importance of investing in accessible and affordable remediation technologies, particularly in developing countries where constraints are most acute. For researchers, the study provides a methodological framework that can be applied to other pollutants and contexts, helping to bridge the gap between theoretical solutions and practical implementation. Ultimately, the integration of advanced decision-making tools with practical environmental engineering offers a pathway toward more sustainable and effective management of persistent pollutants such as phenanthrene, supporting both environmental protection and public health in the face of growing industrial challenges. امروزه آلودگی خاک و پساب به هیدروکربن‌های آروماتیک چندحلقه‌ای، به‌ویژه فنانترن، به‌عنوان یکی از چالش‌های جدی زیست‌محیطی مطرح است که پیامدهای قابل توجهی بر سلامت انسان و سایر موجودات زنده دارد. بنابراین، انتخاب و به‌کارگیری روش‌های کارآمد برای پالایش پساب آلوده به این ترکیبات از اهمیت ویژه‌ای برخوردار است. فرآیند گزینش یک تکنیک مناسب برای پاکسازی، تحت تأثیر عوامل مختلفی از جمله شرایط جغرافیایی، محدودیت‌های اقتصادی و اجتماعی و همچنین دسترسی به فناوری قرار دارد؛ به همین دلیل، تصمیم‌گیری در این زمینه می‌تواند پیچیده و چالش‌برانگیز باشد. در این پژوهش، برای شناسایی و اولویت‌بندی بهترین گزینه‌های پالایش پساب آلوده به فنانترن، از رویکرد تصمیم‌گیری چندمعیاره و مدل تحلیل سلسله‌مراتبی فازی (FAHP) استفاده گردید. در این چارچوب، شاخص‌های کلیدی با بهره‌گیری از منابع علمی معتبر و مشورت با متخصصان حوزه پاکسازی زیست‌محیطی تعیین و سپس وزن‌دهی شدند. نتایج حاصل نشان داد که هزینه با سهم 46 درصد، در دسترس بودن فناوری با 39 درصد، قابلیت بازیابی آلاینده با 9 درصد و زمان با 6 درصد به‌عنوان مهم‌ترین معیارهای تصمیم‌گیری معرفی شدند. همچنین به کمک مدل ویکور فازی (FVIKOR)، گزینه‌های مختلف پالایش مورد ارزیابی قرار گرفتند که در نهایت، روش غشایی (اسمز معکوس) با مقادیر R=0.205، S=0.274،Q=0.002 و سپس روش غشایی مبتنی بر نمک پتاسیم با مقادیر R=0.214، S=0.271،Q=0.005 به‌عنوان کارآمدترین گزینه‌ها شناسایی شدند .افزون بر این، نتایج به‌دست‌آمده نشان می‌دهد که روش‌های غشایی نه تنها به دلیل کارایی بالا، بلکه به سبب قابلیت انطباق با شرایط عملیاتی متنوع، می‌توانند به‌عنوان گزینه‌ای پایدار برای مدیریت پساب‌های آلوده به فنانترن مطرح شوند. این یافته‌ها اهمیت توجه به پارامترهای اقتصادی و دسترسی به فناوری را در طراحی و اجرای پروژه‌های پالایش نشان می‌دهد و می‌تواند به سیاست‌گذاران و مهندسان محیط زیست در انتخاب راهبردهای بهینه کمک شایانی نماید.

https://www.jess.ir/article_235583_e2f328efb6808cdafa53dd40c1ebb060.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Investigating the Environmental Impact of ICT Imports, Differentiated by Global North and South Regions, on Iran's Steel Industry بررسی اثرات زیست محیطی واردات کالاهای ICT از کشورهای توسعه یافته و در حال توسعه بر بخش آهن و فولاد در ایران 10734 10754 235600 10.22034/jess.2025.550377.2410 FA مهدی نجاتی دانشیار، گروه آموزشی علوم اقتصادی، دانشکده مدیریت و اقتصاد، دانشگاه شهید باهنر کرمان 0000-0003-4103-869X مریم حاجی پور اپورواری دانشجوی دکتری، گروه آموزشی علوم اقتصادی، دانشکده مدیریت و اقتصاد، دانشگاه شهید باهنر کرمان 0009-0009-4234-5684 سید عبدالمجید جلائی اسفندآبادی استاد، گروه آموزشی علوم اقتصادی، دانشکده مدیریت و اقتصاد، دانشگاه شهید باهنر کرمان 0000-0001-8154-9123 مجتبی بهمنی دانشیار، گروه آموزشی علوم اقتصادی، دانشکده مدیریت و اقتصاد، دانشگاه شهید باهنر کرمان 0000-0003-0257-5775 Journal Article 2025 10 01 Achieving sustainable development necessitates leveraging existing potentials and utilizing international opportunities to foster desirable economic growth while adhering to appropriate environmental standards. The development of energy-intensive industries, particularly the iron and steel sector, can accelerate economic growth but may entail adverse environmental impacts, thereby undermining the trajectory of sustainable development. As one of the international opportunities, importing high-technology goods, such as information and communication technology (ICT) products, and integrating them into production processes can drive economic growth. Furthermore, if ICT imports are accompanied by technological spillovers, they may contribute to cleaner production technologies in energy-intensive industries like iron and steel. It is noteworthy that the level of development of the exporting countries and their capacity to absorb and apply foreign technology in the importing country are critical factors influencing the extent of productivity spillovers. In this study, a multi-regional general equilibrium model is employed to investigate the effects of ICT imports on environmental variables and the iron and steel sector. To this end, the world’s countries are aggregated into three regions: Iran (the ICT importer), developed countries, and developing countries (the ICT-exporting regions). The results indicate that, in addition to increased production and exports, energy demand, carbon emissions, and energy intensity in the iron and steel sector rise, while carbon dioxide intensity decreases. Moreover, if the source region is developing countries, ICT imports from both developed and developing regions render the production techniques in the iron and steel sector more polluting. A key finding is that technological spillovers from imports originating in developing countries lead to a deterioration in both technique and composition effects in the iron and steel sector, resulting in higher carbon emissions. Conversely, when imports originate from developed countries, technological spillovers improve the technique and composition of production at the macro level, reducing output in the iron and steel sector and shifting production techniques toward cleaner inputs. Based on these findings, it is recommended that, if environmental considerations are prioritized, importing ICT from developed countries should be emphasized. Efforts should focus on removing tariff and non-tariff barriers to imports from developed regions to facilitate this process. Introduction Global warming has prompted nations worldwide to seek effective strategies to mitigate its impacts. To this end, annual global conferences, known as the Conference of the Parties (COP), are convened with the primary objective of reducing greenhouse gas emissions. Carbon dioxide (CO₂) constitutes the largest share of greenhouse gases, primarily emitted through the consumption of fossil fuels across various economic sectors. Energy-intensive industries, particularly the iron and steel sector, are among the most significant contributors to carbon emissions. As a country with substantial energy reserves and a prominent iron and steel industry, Iran plays a critical role in global carbon emissions. Several factors can contribute to mitigating the adverse environmental impacts of this sector, with the adoption of information and communication technology (ICT) goods and their associated technologies in production processes being a key determinant in reducing carbon emissions. For countries lacking the capacity to produce high-technology ICT goods domestically, access to these technologies can be achieved through imports or foreign direct investment (FDI). The technological sophistication of ICT goods varies across countries. For instance, ICT imports from developed nations typically embody higher technological advancements compared to those from developing countries. Moreover, the environmental cleanliness of these technologies may differ, leading to varying environmental impacts in the importing countries. Additionally, imports may generate spillover effects, such as technology transfer, the extent of which depends on the recipient country's capacity to absorb foreign technology. This study employs a multi-regional computable general equilibrium (CGE) model to investigate the impact of ICT imports on a range of variables within the iron and steel sector. The analysis evaluates how the integration of ICT goods influences carbon emissions, energy consumption, and related intensities, considering both direct effects and potential technological spillovers. Materials and methods In this study, a multi-regional general equilibrium model is employed to investigate the effects of ICT imports on environmental variables and the iron and steel sector. To this end, the world’s countries are aggregated into three regions: Iran (the ICT importer), developed countries, and developing countries (the ICT-exporting regions). Results and discussion The results indicate that, in addition to increased production and exports, energy demand, carbon emissions, and energy intensity in the iron and steel sector rise, while carbon dioxide intensity decreases. Moreover, if the source region is developing countries, ICT imports from both developed and developing regions render the production techniques in the iron and steel sector more polluting. A key finding is that technological spillovers from imports originating in developing countries lead to a deterioration in both technique and composition effects in the iron and steel sector, resulting in higher carbon emissions. Conversely, when imports originate from developed countries, technological spillovers improve the technique and composition of production at the macro level, reducing output in the iron and steel sector and shifting production techniques toward cleaner inputs. Conclusion Based on the findings, the following policy recommendations are proposed to promote technological advancement and environmental sustainability in Iran’s iron and steel sector. First, to accelerate technological progress, it is imperative to address barriers to importing information and communication technology (ICT) goods, particularly from developed countries. Second, enhancing technology absorption capacities—such as human capital, institutional quality, and research and development (R&D) capabilities—will facilitate greater technological spillovers, thereby strengthening Iran’s technological base. Third, if policymakers aim to align with global environmental objectives, prioritizing ICT imports from developed countries is advisable due to their higher technological sophistication and cleaner production standards. Imports from developed nations are likely to yield greater environmental and technological benefits. However, if the objective is to expand iron and steel production while adhering to environmental standards, efforts should focus on removing both tariff and non-tariff barriers to ICT imports from both developed and developing countries. In this study, a multi-regional general equilibrium model is employed to investigate the effects of ICT imports on environmental variables and the iron and steel sector. To this end, the world’s countries are aggregated into three regions: Iran (the ICT importer), developed countries, and developing countries (the ICT-exporting regions). The results indicate that, in addition to increased production and exports, energy demand, carbon emissions, and energy intensity in the iron and steel sector rise, while carbon dioxide intensity decreases. Moreover, if the source region is developing countries, ICT imports from both developed and developing regions render the production techniques in the iron and steel sector more polluting. A key finding is that technological spillovers from imports originating in developing countries lead to a deterioration in both technique and composition effects in the iron and steel sector, resulting in higher carbon emissions. Conversely, when imports originate from developed countries, technological spillovers improve the technique and composition of production at the macro level, reducing output in the iron and steel sector and shifting production techniques toward cleaner inputs. Based on these findings, it is recommended that, if environmental considerations are prioritized, importing ICT from developed countries should be emphasized. Efforts should focus on removing tariff and non-tariff barriers to imports from developed regions to facilitate this process. استفاده از فناوریهای نوین در فرایند تولید کالاهای انرژی‌بر مانند آهن و فولاد، علاوه‌براینکه تولید کالاها را بهبود می‌بخشد، می‌تواند اثرات زیست محیطی را تشدید نموده و یا کاهش دهد. یکی از روشهای دستیابی به فناوری های پیشرفته، واردات فناوری اطلاعات و ارتباطات(ICT) است. چنانچه واردات ICT همراه با سرریز تکنولوژی باشد ممکن است به پاک‌تر شدن تکنولوژی تولید آهن و فولاد کمک نماید. در این تحقیق با بکارگیری یک مدل تعادل عمومی چندمنطقه‌ای به بررسی اثرات واردات کالاهای ICT بر بخش آهن و فولاد پرداخته شده‌است. نتایج نشان می‌دهد که واردات ICT از کشورهای درحال‌توسعه (جنوب) اگر بدون سرریز بهره‌وری باشد، انتشار کربن و مصرف انرژی را افزایش و شدت کربن و انرژی را کاهش خواهد داد و اگر واردات همراه با اثرات سرریز باشد، شدت کربن و شدت انرژی را کاهش خواهدداد. واردات ICT از کشورهای توسعه‌یافته (شمال) منجر به کاهش انتشار کربن و مصرف انرژی و همچنین افزایش شدت کربن و شدت انرژی در بلندمدت شده‌است که نشان دهنده کاهش تولید در این بخش می‌باشد. علاوه‌براین نتایج نشان می‌دهد که، هرچه قابلیت جذب تکنولوژی در ایران بهبودیابد، شدت کربن و شدت انرژی به میزان قابل ملاحظه‌ای کاهش خواهد یافت. به طوریکه این کاهش شدیدتر خواهد بود اگر واردات از شمال باشد. براین اساس، برای ارتقای کیفیت محیط زیست، افزایش واردات ICT بخصوص از شمال و بهبود عوامل دخیل در قابلیت جذب تکنولوژی در کشور ایران، پیشنهاد می گردد.

https://www.jess.ir/article_235600_edfab73cf297ccba4445360dc0cdc91a.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Urban Development Strategies to Improve the Resilience and Ecological Efficiency of Urban Services in Tehran Abstract راهبردهای توسعه شهری جهت بهبود تاب‌آوری و بازده اکولوژیک خدمات شهری تهران 10755 10769 236885 10.22034/jess.2025.556123.2422 FA محمد جواد امیری پردیس بین المللی ارس، دانشگاه تهران 0000-0003-1748-9036 شادی مالکی پردیس بین المللی ارس، دانشگاه تهران 0009-0001-6204-5082 اسماعیل صالحی پردیس بین المللی ارس، دانشگاه تهران 0000-0002-1627-6277 Journal Article 2025 11 03 The primary goal of this research is to analyze the ecological resilience and efficiency of urban services within Tehran’s neighborhoods. The study aims to identify the key factors influencing ecological resilience in Tehran's urban areas and the critical variables that affect the performance of urban services in these neighborhoods. Additionally, this research proposes a conceptual framework that links the ecological resilience of urban neighborhoods with the effectiveness of urban services. It explores the relationship between these two variables and provides strategies for urban environmental planning and management. The study is specifically focused on District 4 of Tehran, located in the northeastern part of the city, which is also the easternmost district. Ecological resilience, a core concept in urban environmental management, refers to the ability of urban systems to absorb environmental shocks, adapt to changes, and recover from disruptions. This study examines ecological resilience using several key variables, including biodiversity, the ability of urban environments to filter and absorb pollution, resilience to climate change, and the sustainable management of natural resources. These factors are essential for the long-term sustainability of urban areas, as they directly influence the effectiveness and functionality of urban services. Strengthening ecological resilience ensures that urban systems can continue to provide vital services even under environmental stress. On the other hand, the productivity of urban services refers to how efficiently and effectively urban services, such as public transportation, waste management, water and electricity supply, and healthcare, are delivered to residents. The productivity of urban services is evaluated based on several factors, including accessibility, service quality, cost-effectiveness, and citizen satisfaction. These indicators help to measure how well services meet the needs of the population, their capacity to function effectively, and how responsive they are to the demands of a growing urban population. The research reveals a significant connection between ecological resilience and urban service productivity. In neighborhoods where ecological resilience is stronger, urban services are typically more efficient and reliable. This connection highlights the importance of strengthening ecological resilience to improve urban service delivery. The findings suggest that enhancing ecological resilience can simultaneously improve the efficiency and sustainability of urban services, leading to a more resilient and well-functioning urban environment. Thus, urban development strategies should aim to enhance both ecological resilience and service productivity simultaneously to achieve sustainable urban growth. One of the key conclusions of this study is the need for integrated urban planning strategies that address both ecological resilience and urban service efficiency. Urban planners and policymakers must adopt approaches that recognize the interconnectedness of these two factors, rather than treating them as separate issues. Strategies that integrate modern technologies for efficient resource management, the promotion of sustainable public transportation, and active community participation in urban planning are essential for improving both ecological resilience and the efficiency of urban services. These integrated strategies are critical for ensuring that cities not only endure environmental disruptions but also thrive in the face of these challenges, securing long-term urban sustainability. The study also identifies areas in Tehran where improvements are needed. In neighborhoods with lower levels of ecological resilience, the performance of urban services is often significantly compromised. These neighborhoods struggle to maintain adequate services due to environmental challenges, which in turn affects the quality of life for residents. This underscores the importance of developing tailored solutions that address both ecological resilience and urban service efficiency. By improving both factors, urban managers can create an environment that is more resilient and capable of delivering better services to residents. Several urban planning strategies are recommended based on the findings of this study. These strategies include developing sustainable infrastructure that minimizes environmental impact, adopting renewable energy sources to reduce dependency on fossil fuels, improving public transportation systems to decrease pollution and congestion, and implementing waste management policies that prioritize recycling and resource recovery. These strategies aim to foster an urban environment that is both ecologically resilient and capable of providing high-quality services to residents, ensuring the overall sustainability of urban life. In conclusion, this research highlights the importance of a comprehensive urban planning approach that integrates both ecological resilience and the efficiency of urban services. The findings of the study demonstrate how these two factors are interdependent and how improving one can lead to positive changes in the other. By enhancing ecological resilience, cities can ensure that urban services are more effective and sustainable, ultimately improving the quality of life for residents. Urban planning strategies that recognize the interconnectedness of these two elements are essential for shaping cities that are resilient to environmental challenges and capable of meeting the needs of their growing populations. Furthermore, community engagement plays a crucial role in the success of urban sustainability initiatives. When local residents are actively involved in decision-making processes, they develop a sense of ownership and responsibility toward the ecological health of their neighborhoods. This engagement leads to more effective implementation of sustainable practices and higher satisfaction with urban services. By fostering community involvement, urban areas can become more resilient, and urban services can be better aligned with the needs and expectations of the population. As urbanization accelerates globally, the importance of integrating ecological resilience with the productivity of urban services becomes increasingly evident. The future of cities depends on creating environments where ecological and human service systems are enhanced in parallel. By adopting strategies that address both resilience and service productivity, cities can meet the growing demands of their populations while ensuring that they are sustainable, livable, and resilient in the face of climate change and environmental degradation. Urban planners must work toward fostering cities that are not only capable of adapting to changing conditions but also provide the essential services that enhance the quality of life for residents, now and in the future. As urbanization accelerates globally, the importance of integrating ecological resilience with the productivity of urban services becomes increasingly evident. The future of cities depends on creating environments where ecological and human service systems are enhanced in parallel. By adopting strategies that address both resilience and service productivity, cities can meet the growing demands of their populations while ensuring that they are sustainable, livable, and resilient in the face of climate change and environmental degradation. Urban planners must work toward fostering cities that are not only capable of adapting to changing conditions but also provide the essential services that enhance the quality of life for residents, now and in the future. The integration of these strategies will be pivotal in ensuring urban areas can sustain development while preserving the ecological balance needed for future generations. Furthermore, the role of innovative technology and policy frameworks cannot be overlooked in supporting the implementation of these sustainable solutions. هدف از انجام این پژوهش تحلیل تاب‌آوری و بهره‌وری اکولوژیک خدمات شهری در محلات تهران است. اهداف این تحقیق عبارتند از تعیین متغیرهای تاب‌آوری اکولوژیکی محلات شهری در تهران، تعیین متغیرهای بهره‌وری خدمات شهری محلات شهر تهران، ارائه مدل مفهومی تاب‌آوری اکولوژیکی محلات شهری و بهره‌وری خدمات شهری محلات، تعیین رابطه میان متغیرهای تاب‌آوری اکولوژیکی محلات شهری و متغیرهای بهره‌وری خدمات شهری محلات و ارائه راهبردهای برنامه‌‌ریزی و مدیریت محیط زیست شهری. محدوده مورد مطالعه منطقه 4 تهران است که در شمال شرقی تهران قرار دارد و شرقی‌ترین محله تهران است. تحلیل رابطه میان متغیرهای تاب‌آوری اکولوژیکی محلات شهری و بهره‌وری خدمات شهری نشان می‌دهد که این دو مجموعه متغیر به طور قابل توجهی به هم مرتبط هستند و تقویت یکی می‌تواند بهبود دیگری را نیز به دنبال داشته باشد. در نهایت مبتنی بر یافته‌های پژوهش، چند راهبرد برنامه‌ریزی شهری برای ارتقای تاب‌آوری و بهره‌وری اکولوژیک خدمات شهری پیشنهاد می‌شود.

https://www.jess.ir/article_236885_5fe679f0ebab5bb48efeeb654764cb0d.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Analyzing the Effect of the Resource Curse on the Happiness Kuznets Curve in Developing Countries تحلیل اثر نفرین منابع طبیعی بر منحنی کوزنتس شادی کشورهای در حال توسعه 10770 10785 237496 10.22034/jess.2025.551463.2412 FA امیررضا خلیلی دانشجوی کارشناسی ارشد اقتصاد انرژی، دانشکده مدیریت و اقتصاد، دانشگاه شهید باهنر کرمان، ایران 0009-0000-4971-079X مهدی نجاتی دانشیار، گروه اقتصاد، مدیریت و اقتصاد، شهید باهنر کرمان، ایران. 0000-0003-4103-869X Journal Article 2025 10 06 Happiness is a subjective feeling that has been regarded as one of the fundamental goals of human life since the time of Aristotle. Since sustainable happiness and sustainable development are considered two sides of the same coin, if an increase in happiness is assumed to depend on economic growth and natural resources are considered key factors in this process, it can be argued that achieving happiness is closely linked to economic growth and the effective utilization of natural resources. Accordingly, the present study examines the relationship between the resource curse and economic growth within the framework of the Happiness Kuznets Curve in 66 developing countries. To analyze this relationship, both the random effects model and threshold regression method were employed. The results of the random effects model indicate that economic growth has a positive and significant effect on happiness, while its square has a negative and significant coefficient, reflecting a nonlinear relationship between income and happiness. Subsequently, by determining a threshold for the share of natural resource rents in GDP, countries were divided into two groups. The findings show that in the first regime, natural resources have a positive and significant effect on happiness, but after exceeding the threshold, this effect becomes negative and significant. This reversal indicates the occurrence of the resource curse, which can reduce happiness through channels such as corruption, weakened governance, and inequality. Consequently, the policy recommendation of this study, which may be relevant for the countries under investigation, is to diversify the economy, improve governance, and pay special attention to the human development index and its relationship with quality of life in order to enhance happiness. Introduction Happiness is a mental and emotional feeling that has always been a fundamental goal for humans. According to existing studies, individuals with higher levels of happiness tend to have greater productivity, job performance, success, and health. Accordingly, happiness plays a crucial role not only in shaping personality but also in maintaining mental well-being and coping with the challenges of contemporary life. Given that promoting mental health has become a major social priority, and that mental health is a key component of human capital influencing economic growth through various channels, attention to this issue is increasingly necessary. Moreover, the role of gross domestic product in human well-being and the direct positive relationship between happiness and income indicate that economic growth and increased national income can enhance people’s satisfaction and happiness. The importance of this issue has reached a level where many countries today integrate sustainable happiness with sustainable development, viewing it as a gateway to achieving sustainability and even as a measure for assessing the level of development. Therefore, high income and economic development are considered among the main factors contributing to happiness in societies. This perspective also has deep roots in the history of economic thought. Since the emergence of economics as a discipline by Adam Smith, economic theories have been grounded in the concept of happiness, as he argued that higher income leads to greater satisfaction and well-being. From this viewpoint, if happiness is regarded as an outcome of economic growth, and economic growth is dependent on a country’s resources and productive capacities, it follows that many factors influencing happiness are rooted in economic growth. While numerous factors affect economic growth, energy and natural resources play an undeniable role. However, many resource-rich countries have fallen into what is known as the “resource curse.” Due to overreliance on natural resources, these countries often experience low economic growth, which can adversely affect their citizens’ well-being and happiness. Therefore, examining happiness in countries with abundant natural resources becomes particularly important. Materials and methods This study aims to examine the factors influencing happiness in a dynamic manner, using available data for 66 developing countries over the period 2010-20221, employing the generalized method of moments (GMM) with fixed effects as well as threshold regression. In this study, the fixed-effects GMM model is applied to control for country-specific characteristics and the endogeneity among variables. Since happiness is influenced by dynamic factors such as per capita income, unemployment, and corruption control, using the GMM model allows for a more precise causal analysis and prevents bias in the estimates. In contrast, the threshold model is employed to analyze the nonlinear effect of natural resources on happiness. The research hypothesis is based on the existence of a critical level of resource rents, beyond which the effect of natural resources shifts from positive to negative. The threshold model enables countries to be divided into two regimes according to their dependence on natural resources, allowing the distinct effects in each regime to be analyzed. This approach is particularly suitable for empirically testing the “resource curse” hypothesis. Therefore, the combination of these two models allows, on the one hand, controlling for data dynamics and cross-country heterogeneity, and on the other hand, accurately examining the nonlinear and threshold effects of natural resources on the formation of happiness. Results and discussion Based on the results of the random-effects model, the per capita GDP variable has a positive and significant impact on the happiness index. This finding indicates that, at the baseline level, economic growth contributes to an improvement in happiness in developing countries. However, the squared term of per capita GDP shows a negative and significant coefficient (-0.107), reflecting a nonlinear relationship between income and happiness. In other words, these results suggest the presence of a Kuznets curve for happiness in the countries under study. This inverted U-shaped relationship, as illustrated in the figure below, indicates that beyond a certain income level, further increases in income may be associated with a decline in subjective well-being and happiness. The results also show that the unemployment rate has a negative and significant effect on happiness (coefficient = -0.019), which aligns with economic theory and previous studies. This implies that unemployment, due to its adverse impact on happiness, can have substantial psychological and social consequences, ultimately reducing overall well-being. Contrary to expectations, life expectancy exhibits a negative and significant coefficient (-0.692), which may be due to interactions with other variables such as income or health quality. On the other hand, consistent with expectations, the corruption control variable (LCOR) has a positive and significant effect on happiness (coefficient = 0.095), indicating that improvements in institutional quality and reductions in corruption generally enhance social trust and life satisfaction. In the second part of the empirical analysis, a threshold test was conducted for the natural resource rent variable. The estimated threshold value is 6.92% of natural resource rents relative to GDP. This suggests that in countries where the share of natural resource rents is below this threshold, the utilization of natural resources through income growth, job creation, or infrastructure development can positively contribute to happiness. However, when natural resource rents exceed this critical level, their impact on happiness turns negative, reflecting the adverse effects of overreliance on natural resources on both mental and social well-being. Accordingly, this threshold can serve as a warning indicator for policymakers in resource-rich countries, representing a critical limit for economic and social policy planning. The threshold model results for the natural resource income variable (LRE) further indicate a dual relationship between natural resources and happiness levels. When the share of natural resource rents is below the 6.92% threshold, the variable has a positive and significant effect on happiness, highlighting the constructive role of natural resources during early stages of development, particularly through public revenue generation, infrastructure improvement, and economic welfare enhancement. Once this threshold is exceeded, the coefficient of natural resources becomes negative and significant, suggesting that overreliance on natural resource income can reduce happiness levels. This shift in effect provides clear evidence of the resource curse phenomenon, which may undermine mental well-being through channels such as increased corruption, weakened governance, reduced economic diversification, and heightened social inequality. Therefore, the 6.92% threshold should be carefully considered as a critical economic and social limit in natural resource policy-making. Conclusion Overall, the results obtained from the estimation of the empirical models including the GMM fixed-effects regression and threshold analysis provide strong evidence of the complexity and multidimensionality of the relationship between economic variables and happiness levels in developing countries. The findings of this study not only confirm the existence of the happiness Kuznets curve but also highlight the significant effects of factors such as unemployment, corruption control, and natural resource utilization. In particular, the threshold model results indicate that the impact of natural resources on happiness depends on the level of resource exploitation, and beyond a specific critical threshold, this effect may become negative. Accordingly, economic growth alone cannot ensure a sustainable increase in happiness unless it is accompanied by good governance, appropriate redistribution policies, and economic diversification. شادی، احساسی ذهنی است که از دوران ارسطو تاکنون به‌عنوان یکی از اهداف اساسی زندگی انسان مطرح بوده است. از آنجا که شادی پایدار و توسعه پایدار دو روی یک سکه تلقی می‌شوند، اگر افزایش شادی را در گرو رشد اقتصادی بدانیم و منابع طبیعی را از عوامل کلیدی این روند در نظر بگیریم، می‌توان گفت دستیابی به شادی با رشد اقتصادی و بهره‌برداری مؤثر از منابع طبیعی در ارتباطی تنگاتنگ قرار دارد. بر این اساس، پژوهش حاضر به بررسی رابطه میان نفرین منابع طبیعی و رشد اقتصادی در چارچوب منحنی کوزنتس شادی در ۶۶ کشور در حال توسعه می‌پردازد. برای تحلیل این رابطه، از دو روش مدل اثرات تصادفی و رگرسیون آستانه‌ای بهره گرفته شده است. نتایج مدل اثرات تصادفی نشان می‌دهد که رشد اقتصادی اثری مثبت و معنادار بر شادی دارد، اما مجذور آن دارای ضریب منفی و معنادار است که بیانگر رابطه‌ای غیرخطی میان درآمد و شادی است. در ادامه، با تعیین آستانه‌ای برای سهم رانت منابع طبیعی از GDP، کشورها به دو گروه تقسیم شدند. یافته‌های این قسمت نشان می‌دهد در رژیم اول، منابع طبیعی اثری مثبت و معنادار بر شادی داشته، اما پس از عبور از آستانه، این اثر منفی و معنادار می‌شود. این تغییر جهت، بیانگر بروز پدیده نفرین منابع است که می‌تواند از مسیرهایی چون فساد، تضعیف حکمرانی و نابرابری، شادی را کاهش دهد. در نتیجه توصیه سیاستی‌ مطالعه حاضر که می‌تواند مورد توجه کشورهای مورد بررسی واقع شود، تنوع‌بخشی به اقتصاد، بهبود حکمرانی و توجه ویژه به شاخص توسعه انسانی و ارتباط آن با کیفیت زندگی جهت ارتقای شادی می‌باشد.

https://www.jess.ir/article_237496_97ac96f135d06f46c3905d3af3284360.pdf

انتشارات "فن پایا" مطالعات علوم محیط زیست 2588-6851 10 3 2025 09 23 Modelling the summer and winter variations of water chemical parameters in the Gheshlaqh, Gaveroud, and Sirvan rivers مدل‌سازی تغییرات تابستانه و زمستانه پارامترهای شیمیایی آب در رودخانه‌های قشلاق، گاوه‌رود و سیروان 10786 10797 237675 10.22034/jess.2025.550964.2411 FA بهزاد رهنما گروه اکولوژی، پژوهشکده اکولوژی دریای خزر، مؤسسه تحقیقات علوم شیلاتی کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، ساری، ایران 0000-0001-6646-9766 مهدی خوشناموند گروه اکولوژی، پژوهشکده اکولوژی دریای خزر، مؤسسه تحقیقات علوم شیلاتی کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، ساری، ایران 0000-0002-2037-8073 حسن نصراله زاده ساروی گروه اکولوژی، پژوهشکده اکولوژی دریای خزر، مؤسسه تحقیقات علوم شیلاتی کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، ساری، ایران 0000-0003-1362-1036 عبدالعظیم فاضل مرکز تحقیقات ذخایر آبزیان آب‌های داخلی، مؤسسه تحقیقات علوم شیلاتی کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، گرگان، ایران. عیسی حاجی راد کوچک گروه اکولوژی، پژوهشکده اکولوژی دریای خزر، مؤسسه تحقیقات علوم شیلاتی کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، ساری، ایران 0000-0002-2037-8073 طاهره اسکندری گروه اکولوژی، پژوهشکده اکولوژی دریای خزر، مؤسسه تحقیقات علوم شیلاتی کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، ساری، ایران 0000-0002-2261-2409 حوریه یونسی پور گروه اکولوژی، پژوهشکده اکولوژی دریای خزر، مؤسسه تحقیقات علوم شیلاتی کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، ساری، ایران 0000-0002-7026-2407 Journal Article 2025 10 03 Abstract The quality of river water is influenced by a combination of natural and human factors, and its spatial and seasonal variations can have significant impacts on the health of aquatic ecosystems and human uses. The present study aimed to investigate and compare the summer and winter variations of chemical parameters of water, including nitrate (NO3-), phosphate (PO43-), bicarbonate (HCO3-), sulfate (SO42-), ammonium (NH4+), silica (SiO2), sodium (Na+), potassium (K+), and total dissolved solids (TDS) in the Gheshlaqh, Gaveroud, and Sirvan rivers in Kurdistan Province. Sampling was conducted at six stations during two seasons (summer and winter) of 2024, and the data were modelled using the Inverse Distance Weighting (IDW) interpolation method in the GIS environment. The results showed that in summer, due to reduced flow discharge and increased pollutant inputs, the concentrations of most parameters increased, while in winter, dilution effects caused by precipitation and runoff led to their relative decrease. Downstream of the Sanandaj wastewater treatment plant (station 3) had the highest concentrations of nitrate, phosphate, ammonium, sodium, and potassium in both seasons, indicating the dominant role of point sources in determining water quality. The Gaveroud branch acted as a diluting flow, resulting in a relative reduction in pollutant concentrations when merging with the main river. The variation patterns of bicarbonate and silica were mainly controlled by geological characteristics and hydrological conditions. The assessment of TDS indicated that high values, especially in summer, could pose a serious threat to the quality of water for agricultural and drinking purposes. Overall, the findings demonstrated that improving the efficiency of the wastewater treatment plant and land-use management in the watershed could serve as key strategies for enhancing the sustainability of water resources in the region. Abstract The quality of river water is influenced by a combination of natural and human factors, and its spatial and seasonal variations can have significant impacts on the health of aquatic ecosystems and human uses. The present study aimed to investigate and compare the summer and winter variations of chemical parameters of water, including nitrate (NO3-), phosphate (PO43-), bicarbonate (HCO3-), sulfate (SO42-), ammonium (NH4+), silica (SiO2), sodium (Na+), potassium (K+), and total dissolved solids (TDS) in the Gheshlaqh, Gaveroud, and Sirvan rivers in Kurdistan Province. Sampling was conducted at six stations during two seasons (summer and winter) of 2024, and the data were modelled using the Inverse Distance Weighting (IDW) interpolation method in the GIS environment. The results showed that in summer, due to reduced flow discharge and increased pollutant inputs, the concentrations of most parameters increased, while in winter, dilution effects caused by precipitation and runoff led to their relative decrease. Downstream of the Sanandaj wastewater treatment plant (station 3) had the highest concentrations of nitrate, phosphate, ammonium, sodium, and potassium in both seasons, indicating the dominant role of point sources in determining water quality. The Gaveroud branch acted as a diluting flow, resulting in a relative reduction in pollutant concentrations when merging with the main river. The variation patterns of bicarbonate and silica were mainly controlled by geological characteristics and hydrological conditions. The assessment of TDS indicated that high values, especially in summer, could pose a serious threat to the quality of water for agricultural and drinking purposes. Overall, the findings demonstrated that improving the efficiency of the wastewater treatment plant and land-use management in the watershed could serve as key strategies for enhancing the sustainability of water resources in the region. Abstract The quality of river water is influenced by a combination of natural and human factors, and its spatial and seasonal variations can have significant impacts on the health of aquatic ecosystems and human uses. The present study aimed to investigate and compare the summer and winter variations of chemical parameters of water, including nitrate (NO3-), phosphate (PO43-), bicarbonate (HCO3-), sulfate (SO42-), ammonium (NH4+), silica (SiO2), sodium (Na+), potassium (K+), and total dissolved solids (TDS) in the Gheshlaqh, Gaveroud, and Sirvan rivers in Kurdistan Province. Sampling was conducted at six stations during two seasons (summer and winter) of 2024, and the data were modelled using the Inverse Distance Weighting (IDW) interpolation method in the GIS environment. The results showed that in summer, due to reduced flow discharge and increased pollutant inputs, the concentrations of most parameters increased, while in winter, dilution effects caused by precipitation and runoff led to their relative decrease. Downstream of the Sanandaj wastewater treatment plant (station 3) had the highest concentrations of nitrate, phosphate, ammonium, sodium, and potassium in both seasons, indicating the dominant role of point sources in determining water quality. The Gaveroud branch acted as a diluting flow, resulting in a relative reduction in pollutant concentrations when merging with the main river. The variation patterns of bicarbonate and silica were mainly controlled by geological characteristics and hydrological conditions. The assessment of TDS indicated that high values, especially in summer, could pose a serious threat to the quality of water for agricultural and drinking purposes. Overall, the findings demonstrated that improving the efficiency of the wastewater treatment plant and land-use management in the watershed could serve as key strategies for enhancing the sustainability of water resources in the region. Abstract The quality of river water is influenced by a combination of natural and human factors, and its spatial and seasonal variations can have significant impacts on the health of aquatic ecosystems and human uses. The present study aimed to investigate and compare the summer and winter variations of chemical parameters of water, including nitrate (NO3-), phosphate (PO43-), bicarbonate (HCO3-), sulfate (SO42-), ammonium (NH4+), silica (SiO2), sodium (Na+), potassium (K+), and total dissolved solids (TDS) in the Gheshlaqh, Gaveroud, and Sirvan rivers in Kurdistan Province. Sampling was conducted at six stations during two seasons (summer and winter) of 2024, and the data were modelled using the Inverse Distance Weighting (IDW) interpolation method in the GIS environment. The results showed that in summer, due to reduced flow discharge and increased pollutant inputs, the concentrations of most parameters increased, while in winter, dilution effects caused by precipitation and runoff led to their relative decrease. Downstream of the Sanandaj wastewater treatment plant (station 3) had the highest concentrations of nitrate, phosphate, ammonium, sodium, and potassium in both seasons, indicating the dominant role of point sources in determining water quality. The Gaveroud branch acted as a diluting flow, resulting in a relative reduction in pollutant concentrations when merging with the main river. The variation patterns of bicarbonate and silica were mainly controlled by geological characteristics and hydrological conditions. The assessment of TDS indicated that high values, especially in summer, could pose a serious threat to the quality of water for agricultural and drinking purposes. Overall, the findings demonstrated that improving the efficiency of the wastewater treatment plant and land-use management in the watershed could serve as key strategies for enhancing the sustainability of water resources in the region. کیفیت آب رودخانه‌ها تحت تأثیر ترکیبی از عوامل طبیعی و انسانی قرار دارد و تغییرات مکانی و فصلی آن می‌تواند پیامدهای مهمی بر سلامت اکوسیستم‌های آبی و مصارف انسانی داشته باشد. پژوهش حاضر با هدف بررسی و مقایسه تغییرات تابستانه و زمستانه پارامترهای شیمیایی آب شامل نیترات (NO3-)، فسفات (PO43-)، بی‌کربنات (HCO3-)، سولفات (SO42-)، آمونیوم (NH4+)، سیلیس (SiO2)، سدیم (Na+)، پتاسیم (K+) و کل مواد محلول (TDS) در رودخانه‌های قشلاق، گاوه‌رود و سیروان در استان کردستان انجام شد. نمونه‌برداری در شش ایستگاه طی دو فصل (تابستان و زمستان) سال 1403 صورت گرفت و داده‌ها با استفاده از روش درون‌یابی فاصله معکوس (Inverse Distance Weighting; IDW) در محیط GIS مدل سازی شدند. نتایج نشان داد که در فصل تابستان به دلیل کاهش دبی جریان و افزایش ورودی آلاینده‌ها، غلظت بیشتر پارامترها افزایش یافت؛ در حالی که در زمستان اثر رقیق‌سازی ناشی از بارش‌ها و رواناب موجب کاهش نسبی آن‌ها شد. پایین‌دست تصفیه‌خانه فاضلاب سنندج (ایستگاه سوم) بیشترین غلظت نیترات، فسفات، آمونیوم، سدیم و پتاسیم را در هر دو فصل داشت که بیانگر نقش غالب منابع نقطه‌ای در تعیین کیفیت آب است. شاخه گاوه‌رود به‌عنوان جریان رقیق‌کننده موجب کاهش نسبی غلظت آلاینده‌ها در ترکیب با جریان اصلی شد. الگوی تغییرات بی‌کربنات و سیلیس بیشتر تحت کنترل ویژگی‌های زمین‌شناسی و شرایط هیدرولوژیکی قرار داشت. بررسی TDS نشان داد که مقادیر بالا به‌ویژه در تابستان می‌تواند تهدیدی جدی برای کیفیت آب کشاورزی و شرب محسوب شود. به‌طور کلی، یافته‌ها نشان دادند که ارتقای کارایی تصفیه‌خانه فاضلاب و مدیریت کاربری اراضی در حوضه آبریز می‌تواند راهکاری کلیدی برای بهبود پایداری کیفی منابع آب منطقه باشد.

https://www.jess.ir/article_237675_5c97e000b9c6ea64fdac4539d8bd6cc0.pdf