Anthropogenic Pollution (Anthropog. pollut) – ISSN 2588-4646 is a peer-reviewed journal intended to publish original research papers in all main branches of environmental pollution research. Journal DOI: 10.57647/AP Journal Abbreviation: Anthropog pollut Journal Title Acronym: AP Journal Owner: Islamic Azad University Publisher: Islamic Azad University, Co-publishing: OICC Press, UK The Journal is being published biannual (2 issues per year). This peer-reviewed Journal covered in the Islamic Azad University according to certificate number 95/s/87/96789 on 10th of February 2017 in collaboration with the Association for Environmental Education and Sustainable Development as a Scientific Research Journal. Publication: Accepted papers will be added immediately to the “current” volume’s Table of Contents after the immediate peer-review process.
Studying the Effects of Irrigation Levels, Mycorrhizal Fungi and Azsperilum Bacteria on Environmental Traits and Physiological Performance of Agricultural Products
Environmental pollution is one of the fundamental challenges of today's world that has significant impacts on agriculture and food security. The use of water resource management methods and biofertilizers as strategies to reduce the effects of environmental stresses is of interest to researchers. Facilitating the use of water resources in agriculture is one of the key strategies in improving crop yield and maintaining environmental quality. This study aimed to investigate the effects of different irrigation levels and the use of biofertilizers such as Azospirillum lipoferum and mycorrhizal fungi on environmental traits and quantitative and qualitative performance of barley cultivars. This study was conducted during two crop years (2018-2019) in a farm located at kilometer 4 of the Ardabil-Khalkhal road as a factorial experiment in a randomized complete block design with three replications. The main objective of this study was to reduce the negative effects of water stresses on the yield and yield components of barley cultivars using biofertilizers. The results showed that under normal irrigation conditions, Kavir cultivar showed the highest grain yield with 7755.5 kg/ha, while Valfajr cultivar showed the lowest yield with 5650 kg/ha. Under water stress conditions (irrigation only up to 50% of the spike stage), Nosrat cultivar showed the best yield with 6209.4 kg/ha, while Kavir cultivar showed the lowest yield with 4167.7 kg. The results showed that Nosrat cultivar has the highest stress tolerance, while Valfajr cultivar showed the lowest stress tolerance. In the second year, the application of Azospirillum growth-promoting bacteria and mycorrhizal fungi increased grain yield by 2.02, 2.38 and 3.31 percent, respectively, compared to the control group (without the application of mycorrhizal and bacteria). Full irrigation during the plant growth period increased grain yield by 4.43 and 10.04 percent compared to the limited irrigation and rainfed treatments. Principal component analysis showed that the first three components with eigenvalues higher than one explained 99.6% of the total variation in physiological traits. This first component included traits such as plant height, peduncle length, number of grains per spike, and grain weight per spike, which had a positive effect on grain yield. Therefore, the Valfajr cultivar is recommended due to its ability to increase grain yield.
Copyright (c) 2025 Shahryar Olumi Somarin, Jalil Ajali, Ali Faramarzi, Mehrdad Abdi, Naser Nazari (Author) https://creativecommons.org/licenses/by/4.0
Health Risk Assessment and Source Identification of Potentially Toxic Elements Contamination in the Soils of Agricultural Lands in Shazand Region, Markazi Province, Iran
This study was carried out to evaluate the health risk assessment and the sources of metals (Lead, Cadmium, Arsenic, Nickel, Zinc and Copper) in agricultural soils in Shazand region, Iran. The data was collected from 90 surface soil samples (0-5 cm). US EPA methodology was used for risk assessment and epidemiological study-based risk assessment. Moreover, the sources of these toxic elements using Principal Component Analysis (PCA) were investigated. The results showed that the mean concentrations of Pb, Cd, Ni, Zn, and as of 90 topsoil samples exceeded the average world soils values, except for Cu. Multivariate statistical analysis showed that Pb and Zn originated from common anthropogenic sources related to industrialization, whereas Cu and Ni are probably associated with geological sources. The total non-cancer risk values for adults and children were 0.72 and 7.95, respectively, and the total carcinogenic risks were 8.46E-05 and 2.69E-04, respectively. The non-carcinogenic risk for children was above the threshold level, but low for adults. The total potential carcinogenic health risks for children exceeded the threshold of 1E-04 indicating a high carcinogenic risk for them, whereas the risk for adults was considered acceptable. Furthermore, As was the primary hazardous metal to human health, followed by Cd and Ni. These findings can assist governmental agencies in implementing targeted control strategies to prevent the contamination of toxic elements.
Copyright (c) 2025 Shahrzad Oskouei, Hamid Toranjzar, Abbas Ahmadi, Amir Hossein Baghaie, Javad Varvani (Author) https://creativecommons.org/licenses/by/4.0
Urban Street Dust as a Mirror of Industrial Identity: A Comparative Analysis of Metal Pollution Profiles and Health Risks) Caseud Study: Borujerd City, Iran)
Urban street dust serves as a critical reservoir for toxic potentially toxic elements, posing significant environmental and public health risks—particularly in industrializing regions of the Global South. While numerous studies have assessed metal pollution in individual cities, a crossregional synthesis linking contamination profiles to socio-industrial contexts remains lacking. To address this gap, we conducted a systematic review and comparative meta-analysis of peerreviewed studies (2015–2025) from urban centers across Iran and South Asia, integrating new empirical data from Borujerd City, Iran—a representative case of small industrial cities in semiarid zones. Our analysis reveals a striking regional divergence: Iranian cities consistently exhibit arsenic (As)-dominated pollution, with hazard quotients (HQ) for children reaching 17.05 in Borujerd, far exceeding safe thresholds. In contrast, South Asian cities (e.g., Gazipur, Bangladesh) show rising contamination from technology-critical elements (Bi, Ga, In) linked to e-waste and electric mobility. Source apportionment across the region identifies industrial gas emissions (29.6% in Borujerd) and traffic-related activities as dominant contributors, though their chemical fingerprints differ markedly. While carcinogenic risks remain below the U.S. EPA threshold (10⁻⁶), non-carcinogenic risks, especially from As-demand urgent intervention. We propose a dual-track policy framework: (i) strict emission controls on As-laden industrial gases in Iran, and (ii) e-waste recycling regulations to curb emerging metal leakage in South Asia. This study provides a scalable model for context-sensitive urban dust management that balances industrial development with public health protection.
Copyright (c) 2025 Parvin Goudarzi Yaghoubi, Javad Varvani, Bahman Shams Esfandabad, Hamid Torangzar, Abbas Ahmadi (Author) https://creativecommons.org/licenses/by/4.0
The Role of Building Information Modeling (BIM) in Reducing the Environmental Impacts of the Construction Industry
The aim of this study is to examine the status and implementation of Building Information Modeling (BIM) in Iran using the SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis model. BIM represents the fastest-growing concept in construction management and plays a significant role in reducing the negative environmental impacts associated with the construction industry. Accordingly, this research addresses two central questions: How can a meaningful connection be found between BIM performance and environmental process improvement? How can a SWOT framework be used to turn weaknesses into strengths and threats into opportunities? Additionally, this study explores the environmental impacts of BIM, highlighting its potential to contribute meaningfully to energy conservation, reduction of greenhouse gas emissions, and waste management in the construction sector. The research methodology employed is analytical-descriptive, relying on library research and document analysis, with SWOT matrix analysis as the primary tool. SWOT provides a simple yet powerful framework to assess an organization's internal resources and limitations, market opportunities, and external threats. This analysis facilitated the identification of strengths, weaknesses, opportunities, and threats associated with BIM implementation in the Iranian context. Based on the SWOT analysis, the level of BIM adoption in Iran was evaluated, and its internal (S, W) and external (O, T) factors were identified. The results show that the Probability of Strategic Success (PSS) score is 0.552, which is supported by 4 strategies, namely conservative, defensive, aggressive, and competitive: high cost of BIM implementation in engineering firms is linked with the environmental benefits of contributing to architectural design standards, suggesting that greater attention be paid to sustainability in future designs (Conservative strategy), Lack of improvement in waste management correlates with the increasing volume of construction debris in the environment (Defensive strategy), Implementation of BIM in Iran can reduce material waste, enhance project quality, and automate drawing production, thereby motivating students in the construction field (Aggressive strategy), Reduction of construction costs through BIM technology can incentivize contractors and stakeholders to adopt the system more widely (Aggressive strategy).
Copyright (c) 2025 Hassan Feridonzadeh, Ramin Shahabi Jou, Hesam Feridonzadeh (Author) https://creativecommons.org/licenses/by/4.0
Nanoplastics as Epigenetic Disruptors: A Biochemical Review of Environmental Pollutants and Gene Regulation
Nanoplastics (NPLs), emerging environmental contaminants, have been found to perturb cellular homeostasis through biochemical and epigenetic mechanisms. Due to their small size and high surface reactivity, NPLs can pierce biological systems where they induce oxidative stress, inflammation, and endocrine disruption. Recent studies propose that NPLs have the ability to alter DNA methylation patterns, histone changes, and non-coding RNA expression, leading to persistent alterations in gene regulation. Such epigenetic changes correlate with the development of cancer, neurological diseases, and metabolic disorders with possible heritable effects crosswise through generations. In spite of rising evidence, considerable deficiencies remain in current research, especially regarding human epidemiological experiments and standardized detection assays. Lack of longitudinal experiments with accredited biomarkers limits our data about chronic exposure as well as transgenerational impacts. Multi-omics approaches, such as transcriptomics, proteomics, and metabolomics, hold viable methodologies to establish molecular pathways induced by NPLs. Integration of biochemical data with environmental toxicity is critical to enable accurate risk assessment as well as policy construction. Our review highlights an imperative for interdisciplinary collaboration to address the complex health and environmental implications of nanoplastics. Improvement of detection technologies, standardizing exposure protocols, and incorporating epigenetic endpoints into regulatory protocols are critical steps to reduce NPLs' molecular legacy.
Copyright (c) 2025 Tahereh Navaei Diva, Ali Taleshtabar Dolaty (Author) https://creativecommons.org/licenses/by/4.0
Investigating the Efficiency of Combination of Ozone Based Advanced Oxidation Process and Nanobubbles in Removing the Chemical Oxygen Demand (COD) from Zar Grain Refinery Industrial Wastewater
This study was designed to evaluate the efficiency of a combined Advanced Oxidation Process (AOP) and Ozone Nanobubbles (NB) for treating industrial wastewater from the Zar Grain Refinery. To this end, the optimal concentrations of three oxidizing agents including ozone (O3), hydrogen peroxide (H2O2), and iron chloride (FeCl3) were initially determined using Response Surface Methodology (RSM) and Central Composite Design (CCD). In each experiment, wastewater samples from the Zar Grain Refinery were treated under consistent conditions with varying concentrations of the oxidizing compounds. Then, through multi-objective optimization, an optimal value of O3, H2O2, and FeCl3 was calculated to achieve maximum wastewater treatment efficiency. The results indicated that O3 had the most significant impact on reducing wastewater COD rates, showing approximately a 75% increase in COD removal efficiency. Regression models revealed that the interactive and non-linear effects of the oxidizing agents on COD reduction were significant. Based on these findings, it can be concluded that the combined AOPs would demonstrate high efficiency in removing COD from Zar Grain Refinery industrial wastewater. Finally, in addition to investigating the efficiency of the AOP process in treating wastewater from other industries, it is recommended that further studies be conducted to optimize other operational parameters influencing the wastewater treatment process, such as reaction time and temperature.
Copyright (c) 2025 Saeed Malek Mohammadi, Soheil Sobhanardakani, Ahmadreza Yari, Bahareh Lorestani, Mehrdad Cheraghi (Author) https://creativecommons.org/licenses/by/4.0
Designing an Implementation Model for Realizing Environmental Policies Based on Sustainable Development in Iran through the Application of Knowledge Management
This study was conducted with the aim of designing an implementation model based on the application of knowledge management to improve the implementation of environmental policies in government institutions of the country. The present study is considered to be applied in terms of purpose and strategic in terms of approach. The research population consisted of 50 experts, managers, and specialists from government organizations active in the field of the environment who were selected purposefully. The data collection tool was a researcher-made questionnaire based on a five-point Likert scale that was designed with a focus on three dimensions of knowledge management (acquiring, sharing, and evaluating knowledge) and five key factors of policy implementation (organizational structure, resources, communications, executives' orientation, and organizational culture). Descriptive statistics, exploratory factor analysis (EFA) and Pearson correlation test were used to analyze the data using SPSS software. Also, to strengthen the analysis, the country's upstream environmental documents were also examined using qualitative analysis. The first component, which includes the resources and orientation of the implementers, had the highest explanatory power among the identified components with an eigenvalue of 3.377 and a share of 22.514% of the total variance. After that, the organizational culture component with an eigenvalue of 2.629 and a share of 17.527% is located, which indicates the importance of the values, beliefs, and norms governing the organization in accepting and implementing environmental policies. The final designed model consists of three layers, which are: the central layer: implementation of environmental policies; the middle layer: four rearranged executive components; and the outer layer: three dimensions of knowledge management. By providing a systematic, localized, and data-driven approach, this model has the ability to explain inter-organizational interactions, evaluate organizational learning, and policy coherence in the executive structure of the Islamic Republic of Iran government, and is considered a scientific response to the challenge of the lack of an effective executive model in this area.
Copyright (c) 2025 Shahram Shiranzaei, Hooman Bahmanpour, Seyed Mahdi Alvani (Author) https://creativecommons.org/licenses/by/4.0
Evaluation of Phthalate Concentration in Landfill Leachate in the West of Guilan Province, Iran
Landfill leachate contains pollutants, including phthalates, which pose significant risks to the environment and human health. This study aimed to investigate the phthalates concentration in landfill leachate from three cities in western Guilan: Astara, Talesh, and Anzali. Samples were collected from three designated stations during both the rainy and dry seasons. Physicochemical parameters such as pH, electrical conductivity (EC), organic matter content, and phthalate concentrations were measured using the standard extraction method EPA Method 8061A, with gas chromatography-mass spectrometry (GC-MS). The results revealed that the average total phthalate concentration in landfill leachate across the three cities was 455.46 ppb, with significant seasonal variation between the rainy and dry seasons (P < 0.05). Astara exhibited the highest phthalate concentration, measuring 239.50 ppb. Throughout both seasons, bis (2ethylhexyl) phthalate (BEHP) accounted for the most significant proportion, comprising 73.2% of total phthalates, followed by dioctyl phthalate (DOP) at 13%, dimethyl phthalate (DMP) at 6.4%, and isobutyl phthalate (IBP) at 5.5%. Diethyl phthalate (DEP), dibutyl phthalate (DBP), and benzyl butyl phthalate (BBP) were less prevalent, representing 1.1%, 0.5%, and 0.2%, respectively. Health risk assessments indicated that the contamination factor (CFi) was highest at the Talesh station (80.30), followed by Anzali (45.52) and Astara (10.69). Similarly, the Pollution Load Index (PLI) was greatest at Talesh (32.32), followed by Astara (20.24) and Anzali (11.32). These findings underscore the critical need for continuous monitoring and effective management of landfill leachate, as well as further investigation into the health and environmental impacts of phthalate contamination.
Copyright (c) 2025 Somayeh Nemati Gaskaminjan, Fatemeh Shariati, Mohsen Mohammadi Galangash, Leila Ooshaksaraei (Author) https://creativecommons.org/licenses/by/4.0
Responsible Citizen Behavior Modeling in Urban Waste Management
Identifying factors affecting citizens' responsible behavior in the field of waste generation can provide insights for urban planners for policymaking and improving waste management practices. The aim of the present study is to identify the factors affecting citizens' responsible behavior in waste management. This study is exploratory in purpose and applied-developmental in nature. The study site in this research was the city of Arak in Markazi Province. In the qualitative section, related studies were reviewed using MAXQDA software, and the model's factors and items were identified and categorized. These factors were then evaluated through content validity and reliability testing using the Kappa coefficient. In the quantitative section, the designed model was validated using expert opinions and a Likert-scale questionnaire. Smart PLS software was used for data analysis. The study's findings identified seven components and twenty-three items, including economic and financial motivations, culture and media, social, legal, infrastructure, environmental and waste literacy, and individual and psychological characteristics, as influential factors in responsible waste management behavior. The Kappa coefficient, with a value of 0.95, confirmed the model's reliability. Additionally, the quantitative findings showed that the factor loadings obtained for all components were evaluated as acceptable or excellent. The highest Q² value belonged to the environmental literacy construct, indicating the model's predictive power for responsible waste management behavior through this construct. The obtained P values for all paths confirmed the model's hypotheses, and the structural fit of the model was also validated. Therefore, the critical necessity of developing environmental literacy and waste management to minimize waste, through green consumption, waste prevention, and recycling, is clearly emphasized.
Copyright (c) 2025 Mohammadali Nejat, Saeed Motahari, Azita Behbahani, Mahdieh Rezaei (Author) https://creativecommons.org/licenses/by/4.0
Optimizing Anaerobic Biological Treatment of Industrial Acidic Wastewater Using Sulfate-Reducing Bacteria
This study focused on the anaerobic biological treatment of acidic wastewater from polymer plants utilizing sulfuric acid, specifically employing sulfate-reducing bacteria (SRB). Quantitative analyses were conducted to evaluate the effects of key parameters, including temperature, pH, and pollutant concentration. A series of twelve experiments was performed at two temperature levels (25°C and 60°C), two pH levels (7.5 and 8.5), and three sulfate ion concentrations (50, 200, and 450 mg/L SO₄²⁻). Results demonstrated that increasing the temperature from 25 °C to 60 °C at an initial sulfate concentration of 50 mg/L and pH 7.5 improved treatment efficiency by 17.6%. Overall treatment efficiencies varied between 45.3% and 49.9% across different concentrations. Additionally, raising the pH from 7.5 to 8.5 at both temperatures resulted in an approximate 16.4% increase in treatment performance. The data also revealed a linear correlation between temperature and sulfate ion concentration and a second order correlation between pH and sulfate ion concentration. These findings underscore the significant influence of temperature and pH on the anaerobic biological treatment of sulfate ions in industrial wastewater, highlighting the necessity of controlling these parameters to optimize purification outcomes.
Copyright (c) 2025 Nafiseh Panahi Osalou, Lobat Taghavi, Amir Hessam Hasani, Mohsen Dehghani Ghanatghestani (Author) https://creativecommons.org/licenses/by/4.0
Enhancing Soil Remediation: Integrated Mycobacterium and Barley (Hordeum Vulgare) Systems for Petroleum Hydrocarbons and Heavy Metals Restoration in Soils Near Shiraz Oil Refinery
Industrial activities, particularly oil refining, release significant pollutants like TPH, PAHs, and heavy metals into the environment, necessitating sustainable remediation strategies. Therefore, in this study we evaluated the synergistic potential of bioremediation using Mycobacterium and phytoremediation with barley to remediate contaminated soils in Shiraz oil refinery, Iran. 36 soil samples were analyzed to isolate bioremediating mycobacteria using turbidometric, chromatographic, biochemical, and molecular assays. Greenhouse experiments used soil spiked with PAHs (100–200 mg/kg)and heavy metals (As, Hg, Cd, Pb, Cr; 3–400 mg/kg) at low, medium, and high levels. Five phytoremediation(P),bioremediation(B), combined treatments include phytoremediation control, and bioremediation(MB), and sterile control, were assessed over 90 days, analyzing soil properties, contaminant levels, plant growth, TF, and BAF.13 Mycobacterium isolates (36.11%)representing nine species were identified. Key species such as M. gilvum and M. smegmatis achieved >60% degradation of both PAHs and heavy metals, while M. austroafricanum and M. vaccae showed superior PAH degradation (65–80%),with M. vaccae also achieving 75% heavy metal reduction. The MB treatment significantly outperformed the others, achieving 78–86% PAH degradation and 58–68% heavy metal removal (p< 0.001). Soil quality indicators improved notably: microbial biomass increased by 35%, pH rose from 5.8 to 6.8, organic matter increased from 2.0% to3.5%, and EC decreased from 1.5 to 1.0 dS/m. Barley biomass increased by 25%(roots)and 20% (shoots), with TF and BAF values ranging from 0.25 0.55. This study demonstrates that integrated bioremediation using barley and Mycobacteria offers a sustainable strategy for restoring petroleum and heavy metal contaminated soils in industrial areas.
Copyright (c) 2025 Maryam Aghakhani, Seyed Ali Abtahi, Davood Azadi, Mojtaba Jafarinia (Author) https://creativecommons.org/licenses/by/4.0
Traffic Air Pollution and Respiratory Health: A Route Based Exposure-Symptom Study among Urban Taxi Drivers in Isfahan, Iran
Taxi drivers constitute one of the most at-risk subpopulations for road traffic air pollution within urban settings. In the polluted city of Isfahan, Central Iran, a cohort of 349 middle-aged male taxi drivers who were specifically exposed to road pollution was selected. Data collection involved assessing four respiratory symptoms (RSs)- coughing, dyspnea, wheezing, and chest tightness- using a 5-point Likert and a series of independent variables associated with the increase or abatement of air pollution along the routes that each driver took regularly during his working hours. A Generalized Additive Model (0.372 < R2 < 0.576) was applied to determine the prevalence of RSs in relation to a small subset of independent variables identified using a Varimax-rotated PCA analysis. According to the findings, increasing roadside greenery, as measured through a Sentinel-2 NDVI layer, decreases the prevalence of RSs. Conversely, an increase in the number of bus stations, the mean average travel time spent by the taxi drivers on the road between two destinations, and the mean annual concentration of PM2.5 along the routes (with an average of 23.99 ± 6.00 µg/m³) exhibited a positive association with the onset of RSs. This research underscored the susceptibility of taxi drivers to road traffic air pollution while highlighting the alleviating role of road greenery in influencing the respiratory health of Isfahan taxi drivers.
Copyright (c) 2025 Samaneh Mohammadsoleimani, Mozhgan Ahmadi Nadoushan (Author) https://creativecommons.org/licenses/by/4.0
Assessment of the Environmental Impacts of Landslides on Groundwater Resources Using Geoelectrical Surveys and Dipole-Dipole Arrays
The present study aimed to assess the geological impacts of landslides on groundwater resources along the Shemshak-Dizin road, Iran, using the geoelectric geophysical method based on a dipole-dipole array. Thus, five geoelectric acquisition profiles were designed and implemented to identify the landslide geometry and assess its impacts on the regional groundwater system. The results of reverse modeling showed the clear boundary of the landslide layers and the areas with high humidity, as well as the lithological facies and the local water infiltration through fractures downstream of the landslide. The comparative results of the quantity of groundwater at present with those of the previous year show that the groundwater level in this area has decreased by an average of 14 meters compared to 2010. In addition, due to the destruction of vegetation, the penetration of surface water caused by rainfall into the soil has decreased, which has had a negative impact on the occurrence of landslides. The results showed that the penetration of water caused by rainfall in the study area in 2010 was about 64 percent, which decreased in 2023 owing to the destruction of vegetation and reached about 55 percent. Factors such as slope, altitude, rainfall, distance to fault, and land use were effective in the occurrence of landslides in the study area. On the other hand, the regional groundwater had no direct or positive impact on landslides. However, landslides in the area had caused the groundwater level to drop. Destruction of vegetation was one of the factors affecting this phenomenon.
Copyright (c) 2025 Pejman Aramfar, Arezou Dorostian, Soheila Bouzari, Elham Boostan (Author) https://creativecommons.org/licenses/by/4.0
Enhancing Resilience in Drinking Water Wells: An Optimal Model for Quality Protection Zone Determination (A Case Study of Maragheh City)
In this paper, the water quality characteristics of water wells in Maragheh city were investigated with the aim of determining the resilience status and health risk using the MODFLOW groundwater flow numerical model. Data analysis was improved using the Groundwater Modeling System (GMS) software and acceptable results were obtained by comparing with the methods. Key criteria, such as storage capacity, hydraulic conductivity and specific performance, were accurately determined in 54 separate clusters of drinking water wells. The model was fully calibrated and covered sustainability scenarios for a 22-year period (2001-2023). Based on this approach, a comparative assessment of well quality areas was performed and compared using different analytical methods. Considering the groundwater pollution risk index from 1 to 100, lower values indicate a reduced risk of pollution and, as a result, greater resilience. Therefore, by qualitative zoning of the aquifer around the wells, the pollution risk index was determined and based on that, the level of resilience was determined. The findings showed that about 70% of the well water in the study area had a high pollution risk index (1-20), indicating high resilience, 10% had a medium resilience index (21-40), 10% had a low resilience index (41-60), and 10% had a very low resilience index (>60). Among the new findings of this study are the multifaceted effects of variables such as geographical extent, hydraulic characteristics of the aquifer, and contaminant compositions, indicating the inherent vulnerability of wells and the need to review water resources management.
Copyright (c) 2025 Maghsoud Amirpoor, Hossein Yousefi, Nasser Ebadati, Seyyed Hossein Hashemi (Author) https://creativecommons.org/licenses/by/4.0
Dye Remediation from Water using Hematite Nanoparticles through performance of Response surface methodology (RSM), Photo Catalytic degradation and Equilibrium Adsorption Studies
Various industries like textile, paint, plastic manufacturing industry discharge harmful dye effluents in clean water reservoirs. Thus the water containing such dyes is unfit for aquatic life as well as humans. This work aimed to investigate the application of Dalbergia Sissoo (DS) sawdust and Acacia nilotica (AN) wood biomass modified Fe2O3 nanoparticles as effective adsorbents in order to take out methylene blue from contaminated water. The morphological studies of plant biomass showed that the surface was uneven having pores of different sizes hence allowing dye adsorption. The bands of various functional groups for example, hydroxyl, carbonyl, and C-H were found in spectra which were responsible for the stabilization of synthesized nanoparticles. Various analytical parameters such as contact time, methylene blue (MB) dye concentration, temperature, weight of adsorbate and photocatalytic degradation on the adsorption was studied. Maximum adsorption capacity qe (5.887 mg g-1) was obtained at the optimized settings. Dye remediation with ANFeNP was expanded up to 96% dye concentration was changed from 20mg/L to 100mg/L. The results best fitted Freundlich isotherm which proposed multi-layered adsorption occurred on adsorbent’s surface. The contact time parameter study revealed maximum dye removal of 97% at 105 minutes. Kinetic studies exhibited that process of adsorption obeys PSO and IPD models, which indicated that chemisorption was followed suggesting the diffusion of adsorbate in inner layers of adsorbent’s surface. With change in adsorbent’s dose from 0.1g to 0.5g, percentage removal was increased up to 96%. The photocatalytic activity of adsorbent at 120 minutes showed dye removal with a percentage of 97. The investigational data accurately fitted to Langmuir and Freundlich isotherms. Thermodynamic calculations indicated feasible adsorption which is also automatic and heat-absorbing. Statistical optimization studies were done using Response Surface methodology (RSM). The value of predicted and adjusted R2 indicates excellent relationship between predicted and experimental responses. Response surface methodology and central composite design were also applied to experimental data to predict the effect of multiple parameters revealing good correspondence between these parameters revealing good correspondence between these parameters.
Copyright (c) 2025 Tunzeel Iqbal, Haleema Bibi, Somyah Aziz (Author) https://creativecommons.org/licenses/by/4.0
Investigation of the Extra-Organizational Collaborations in Reduction Environmental Pollutions of Tourism Development on Qeshm Island Using Network Analysis Approach
The environment is the central core of the natural tourism industry; therefore, tourism development directly depends on the environment health. This means that institutional reforms and intra-organizational decisions related to tourism management cannot be considered as an independent and separate issue from environmental management. This research examines the level of cooperation and participation of Qeshm Island’s residents with environmental decisions and actions of government organizations to achieve an efficient model for the successful implementation of environmental decisions which guarantee tourism sustainable development on Qeshm Island. For this purpose, various types of public communication and island tourism activists (governors of rural districts, council members, local people, and other individuals) with government organizations were examined regarding their environmental approaches affecting tourism on Qeshm Island through selecting environmental pollution criteria as one of the determinant limitations in the tourism development on Qeshm Island and applying a network analysis approach. At first, 50 questionnaires were completed and data were analyzed by using the Ucinet and Netdraw software to analyze these variables through the snowball sampling method and visiting the organizations and departments which affect impact the tourism industry and also the organizations and departments related to environmental management and protection on Qeshm Island. Regarding the level of referring to government organizations, the results showed that governors of rural districts and local people with a degree centrality of 33 and intermediate centrality of 460/ 663 and 575/979, respectively, have the most referral to government organizations. Through the cooperation network, the local people with a degree centrality of 38 and intermediate centrality of 456/500 and council members with a degree centrality of 36 and betweenness centrality of 460/ 663 are the most cooperators in carrying out the activities related to environmental pollution reduction on Qeshm Island. The degree centrality of 42 and the betweenness centrality of 249/398 for the council members showed that they have the highest level of trust in government organizations. Generally, among all the variables, governors of rural districts, council members, and local people have the most relevant activities, cooperation, and trust for environmental pollution reduction related to government organizations on this island, respectively. Therefore, it can be concluded that environmental challenges such as environmental pollution will be reduced by optimizing this network and increasing social capital among this group.
Copyright (c) 2025 Ardeshir Shayesteh, Mohsen Dehghani Ghanatghestani, Mehdi Jabbarzadeh, Hananeh Mohammadi Kangarani, Lobat Taghavi (Author) https://creativecommons.org/licenses/by/4.0
Groundwater Quality Assessment and Refining Vulnerability Index through Machine Learning and Pollution Index Integration: A Case Study of the Koohpayeh Plain in Central Iran.
Groundwater contamination is a critical issue, especially in arid regions where it serves as the main water supply. This study emphasizes the importance of integrating traditional methods with machine learning techniques to enhance groundwater vulnerability assessments in the Koohpayeh aquifer, central Iran. Groundwater quality was assessed using the Pollution Index of Groundwater (PIG) and Water Quality Index (WQI). WQI values ranged from less than 15 to 55, indicating poor water quality, particularly in central and southeastern regions, due to contaminants from agriculture and urban activities. The PIG index revealed severe pollution in 45% of the area, showing a strong correlation between high PIG and low WQI values. Machine learning methods, including Random Forest (RF), Gradient Boosting (GB), and Support Vector Regression (SVR), were used to refine the DRASTIC model. RF emerged as the most effective model, achieving an MSE of 0.05 and an R² of 0.89, outperforming GB, which had a slightly higher R² of 0.91 but a greater MSE of 0.08. A strong correlation between nitrate levels and the optimized vulnerability indices validated the improved DRASTIC model’s accuracy. The enhanced DRASTIC model provides a more reliable tool for identifying high-risk areas and developing targeted groundwater management strategies. This study underscores the value of combining traditional assessments with machine learning to improve groundwater quality monitoring and protect public health. These findings can support decision-makers in prioritizing pollution control strategies, optimizing groundwater monitoring programs, and designing sustainable management plans in vulnerable arid and semi-arid regions.
Copyright (c) 2025 Navideh Najafpour, Shahrokh Soltaninia (Author) https://creativecommons.org/licenses/by/4.0
Evaluation of criteria affecting pollution reduction and sustainable management of water resources using the Flood Hazard Zoning approach (A case study: Goharrood River, Iran)
The present study aimed to evaluate the criteria affecting sustainable water resources management in the Goharrood River Basin (Rasht City, Gilan Province, Northern Iran) through the Flood Hazard Zoning approach to identify major flood occurrence centers and optimal flood dam location. Criteria and sub-criteria were identified using a Hierarchical Structure and prioritized based on Pairwise Comparison, Analytic Hierarchy Process (AHP) and Expert Opinions. Zoning was also done through Geographic Information System (GIS). The results showed that economic (weight value (WV) = 0.608) and technical (WV = 0.229) criteria were in first and second priority, followed by environmental and social criteria with weight values ​​of 0.112 and 0.051, respectively. Moreover, the sub-criteria of cultivation pattern (WV=0.539), welfare level (WV=0.536), demand rate (WV=0.583) and water conservation (WV=0.521) were preferred in the management of Goharrood river water resources. Based on the findings, the eastern part of the river basin had a higher potential for flooding. Therefore, three main centers were identified as important locations for the construction of flood barriers. Construction of flood dams can control future floods and prevent environmental pollution and reduction in the quality of surface and groundwater in the study area.
Copyright (c) 2025 Zahra Pourdasht, Mohammad Ebrahim Ramazani, Fariborz Ahmadzadeh Kaleybar, Omid Rafieiyan, Arezoo Nejaei (Author) https://creativecommons.org/licenses/by/4.0
Reduction of the Effects of Pollution Caused by Toxins through Essential Oil Extraction of Lavender and Rosemary Plants on Potato Aphid (Macrosiphum euphorbiae)
Prolonged and excessive use of synthetic pesticides has led to pest resistance and contamination of soil, water, and air, threatening vital environmental resources. Plant-derived pesticides offer a sustainable, eco-friendly alternative, potentially improving agricultural productivity, food security, and consumer health. We evaluated the insecticidal efficacy of lavender (Lavandula angustifolia) and rosemary (Rosmarinus officinalis) essential oils (EOs) against potato aphids (Macrosiphum euphorbiae). EOs were extracted via hydrodistillation and tested in a completely randomized design with four replicates at 25°C and 65 ± 5% relative humidity, assessing mortality 24 hours post-treatment. Probit analysis using Minitab software (version 17) determined LC50 and LC90 values of 8,417 ppm and 47,774 ppm for lavender EO, and 10,315 ppm and 49,905 ppm for rosemary EO, respectively. Field comparisons of lavender EO at 8,417 ppm (LC50) with imidacloprid at 1 g/L (diluted 1:1000) showed imidacloprid efficacy of 91.4–98.3% and lavender EO efficacy of 41.6–47.8%. These results confirm the significant insecticidal potential of EOs, positioning them as viable alternatives to chemical insecticides for future pest management programs
Copyright (c) 2025 Abutaleb Ghaffari, Lobat Taghavi, Aref Marouf, Parviz Moradi (Author) https://creativecommons.org/licenses/by/4.0
Ecological Risk Assessment of Potentially Toxic Metals in Water and Sediments of Urban River Ecosystems (Case Study: Zarjub River and Gohar Rood in Rasht, Iran)
The Zarjub River and Gohar Rood represent serious pollution concerns among urban rivers in northern Iran, as they discharge into the international Anzali Lagoon. This study aimed to evaluate the concentration of potentially heavy metals (PTMs) in the water and sediments of these two rivers. To this end, water and sediment samples were taken from 10 sampling stations along the two rivers, and then physicochemical factors and concentration of PTMs were measured; moreover, environmental indices were calculated. Results showed that the water pH, DO, and TDS were 6.7, 4.9, and 316.5, respectively. In addition, the concentration of Fe, Pb, Al, Hg, and Cd in water samples were 0.166, 0.1, 0.1, 1, and 0, and their concentration in sediment samples was equal to 41686.1, 70.031, 12721.9, 0.1, and 0.1, respectively. The geo-accumulation index (Igeo), enrichment factor (EF), contamination factor (CF), ecological risk index (ERI), and potential ecological risk (PER) were also calculated for the water and sediment samples. The measurement of PTMs and the above-mentioned indices demonstrated that the water of the studied rivers does not contain high levels of heavy metals, whereas their sediments contain high levels of PTMs. The study findings suggested that these two urban rivers are not in a hazardous state in terms of PTMs; however, it is necessary to further manage and control the entry of urban wastewater into these two rivers.
Copyright (c) 2025 Ali Maghsoudi Shaghaghi, Mohammad Dehdar Dargahi, Mohammadreza Rahimibashar, Mahsa Hakimi Abed, Bahram Ahmadi (Author) https://creativecommons.org/licenses/by/4.0
Determining the standard requirements for sustainable conservation of Iran's industrial architectural heritage with an emphasis on controlling the mutual effects of architecture and the environment on each other
This article examines the standard requirements for the protection of Iran's industrial architectural heritage and emphasizes the importance of controlling the interactions between architecture and the environment. Industrial heritage, which includes buildings and facilities related to the industrial era, is a valuable part of the country's cultural history. However, the lack of specific principles and regulations for the protection of these sites has led to serious damage and destruction of both the heritage and the surrounding environment. The research method of this study is applied in purpose and descriptive-analytical in nature. A questionnaire was designed and distributed among 384 architects who are members of the Tehran Engineering System Organization, followed by statistical analysis. Additionally, existing data and documents regarding industrial heritage and global experiences in this field were reviewed and analyzed. Furthermore, the challenges and obstacles in protecting this heritage have been thoroughly examined. The main innovation of this research lies in identifying the need to formulate new principles and regulations for the protection of industrial architectural heritage. Based on the results obtained, it is suggested that a legal and standard framework for managing and protecting these sites be established. This framework could include strategies for coordination between architecture and the environment to prevent the destruction and damage to industrial buildings and the environment. The findings of this research could assist policymakers, architects, and urban managers in taking effective actions for the preservation and maintenance of industrial heritage by better understanding the interactions between architecture and the environment. Ultimately, this article emphasizes the importance of creating a comprehensive and integrated approach to protect industrial architectural heritage and their environments, aiming to raise public awareness in this area.
Sustainable architecture and environment
Restoration and revitalization of Iran's industrial heritage
Copyright (c) 2025 Payvand Amir Borbor, Afshin Ghorbani Param (Author) https://creativecommons.org/licenses/by/4.0
Sustainable Water Treatment Solutions: Enhancing Efficiency with Tube Settlers to Address Water Scarcity
Water scarcity has emerged as a pressing global challenge, exacerbated by factors such as climate change, population growth, and industrialization (United Nations, 2023). One such promising technology is the integration of tube settlers into existing water treatment frameworks. Tube settlers are gravity-assisted sedimentation devices that enhance the efficiency of the clarification process by promoting the aggregation and settling of suspended solids (AWWA, 2011). The application of tube settler technology has significantly advanced water treatment by reducing detention time and enhancing sedimentation through high-rate sedimentation principles. This study evaluates the impact of integrating innovative tube settlers into the sedimentation processes of water treatment plants. A comparative analysis was conducted to compare conventional accelerator clarifiers with enhanced clarifiers equipped with tube settlers. Tube settler groups, inclined at a 60° angle and measuring 90 cm in lengthir, were used to facilitate the flow of screened raw water. Key parameters including the number of backwashes per day, energy consumption, and removal efficiencies of Al³⁺, Fe³⁺, turbidity, total suspended solids (TSS), and biological agents (diatoms, nematodes, rotifers, protozoa, and algae) were assessed. The study highlighted significant reductions in treatment costs, with a 25% decrease in electricity consumption and improved contaminant removal. Clarifiers equipped with tube settlers demonstrated significantly higher removal efficiencies for all parameters measured, with average removal rates of 74% for Al³⁺, 60% for Fe³⁺, 77% for total suspended solids (TSS), and 92% for algae. These findings confirm that integrating tube settlers greatly enhances the efficiency of water treatment processes. It is recommended that designers of water treatment plants include tube settlers in the initial design phase, and prioritize re-engineering efforts to ensure optimal operation.
Copyright (c) 2025 Mohsen Memarzadeh, Mozhgan Ahmadi Nadoushan, Payam Najafi, Mehran Hoodaji (Author) https://creativecommons.org/licenses/by/4.0
Comparing Random Forest and Regression Models for Dust Storm Assessment in Kermanshah Province, Iran
Identifying dust sources is essential for effective management. This study employs remote sensing and machine learning techniques, specifically Random Forest Model (RFM) and Multiple Linear Regression (MLR), to identify dust production areas in Kermanshah province from 2000 to 2020. The results indicate that the Random Forest Model (RFM) outperforms Multiple Linear Regression (MLR). Specifically, the accuracy of the RFM, with a correlation coefficient of 0.900, is significantly higher than that of the MLR, which has a correlation coefficient of 0.840. Furthermore, the Root Mean Square Error (RMSE) for the RFM was 5.59, whereas for the MLR it was 7.05, confirming the superiority of the RFM’s accuracy. Key factors influencing dust production include elevation, erosion, soil moisture, land cover, geology, daytime land surface temperature, and NDVI. The western and southwestern regions have been identified as hotspots for dust production. These findings can assist policymakers in effectively allocating resources and managing dust-related issues. Hazard zoning maps will facilitate the identification of areas requiring immediate intervention.
Copyright (c) 2025 Mehranoosh Gholipour, Maryam Kiani Sadr, Bahareh Lorestani, Mehrdad Cheraghi, Soheil Sobhanardakani (Author) https://creativecommons.org/licenses/by/4.0
Pollution-Driven Morphological Adaptations in Scorpions: Insights from Human-Dominated Landscapes
Pollution from human activities, such as industrialization and agriculture, has profound impacts on ecosystems and their inhabitants. This study investigates how environmental pollution influences morphological adaptations in scorpions, using them as bioindicators to assess ecological changes in human-dominated landscapes. Scorpions (Androctonus crassicauda; Buthidae family) were collected from regions in Isfahan Province, Iran, representing gradients of agricultural, urbanized, and industrialized areas. Morphological traits were measured and analyzed using multivariate statistical methods. Results revealed that over 70% of the variance in morphological traits was explained by a size gradient, with industrial pollution significantly associated with increased morphological variability (β= 0.176, t= 2.019, p= 0.030). In contrast, agricultural activities were linked to reduced morphological diversity (β= -0.09, t= -2.739, p= 0.007). These findings suggest that industrial pollution enhances morphological variability, likely through phenotypic plasticity in response to diverse stressors, while agricultural practices limit it, possibly due to environmental homogenization and pesticide pressures.
Copyright (c) 2025 Yalda Montaser, Atefeh Chamani, Rouhullah Dehghani, Hedieh jafari (Author) https://creativecommons.org/licenses/by/4.0
A proxy-based restriction scoring approach using soil physico-chemical properties to assess potentially toxic element risk in agroecosystems
Agricultural intensification, particularly in developing countries, has led to widespread soil pollution and potentially toxic element (PTE) contamination due to excessive use of synthetic fertilizers and pesticides. This study assesses the spatial variability of HM contamination risks in the Mehrgard Catchment (1275.59 km²), Isfahan Province, using soil physico-chemical properties as proxies. Soil samples from 134 locations revealed significant heterogeneity in organic carbon (OC, 0.5–6.9%), alkaline phosphatase activity (ALP, 0.59–15.67 µmol/g/l), and texture (sand 54.9–78.8%). Principal component analysis (PCA) identified three components explaining ~80% of the variance, emphasizing the dominant roles of OC, ALP, and texture in regulating PTE dynamics. OC and nutrient-related parameters were key to PTE retention, while sandy soils and carbonate content increased contamination risks. A restriction score (RS, ranging from -1.132 to 0.676) was calculated for each location using PCA-derived weights and adjusted soil properties. Hotspot analysis (Getis-Ord Gi*) identified northern areas as high-risk zones (49 locations across three clusters), where soil properties elevated PTE accumulation risks. The findings advocate for site-specific strategies, such as organic amendments for sandy soils and precision irrigation for carbonate-rich areas, to mitigate PTE contamination, highlighting the inadequacy of uniform agricultural practices for sustainable land use.
Copyright (c) 2025 Seyed Mohsen Ghoreishi, Elham Chavoshi, Sattar Chavoshi Borujeni (Author) https://creativecommons.org/licenses/by/4.0
Enhanced Monitoring of Air Pollution in Asalouyeh, Iran Using Sentinel-5 Satellite Imagery and Google Earth Engine
Asalouyeh, a rapidly industrializing port city in Iran, faces significant environmental challenges due to air pollution resulting from extensive industrial activities. This study employs Sentinel-5 satellite data and the Google Earth Engine (GEE) platform to assess the spatial and temporal distribution of key air pollutants, including nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), and aerosols, over the period from 2019 to 2023. By leveraging the advanced capabilities of remote sensing and cloud-based geospatial analysis, we processed satellite imagery to monitor atmospheric pollution levels and identify pollution hotspots. The findings indicate a notable increase in pollutant concentrations, particularly NO₂, CO, and SO₂. NO₂ levels increased from a range of 0.0022–0.0071 µmol/m² in 2019 to 0.0025–0.0099 µmol/m² in 2023, while CO concentrations rose from 0.63–0.88 ppm in 2019 to 0.58–0.86 ppm in 2023. Similarly, SO₂ concentrations increased significantly, from 0.008–0.04 ppm in 2019 to 0.01–0.06 ppm in 2023. Aerosol Optical Depth (AOD) values also showed an upward trend, reaching a peak of -0.034 to 0.8 in 2023 compared to -0.81 to 0.016 in 2019. The results demonstrate a clear correlation between increasing pollution levels and industrial expansion in Asalouyeh, with the highest concentrations observed near petrochemical complexes and transportation corridors. The identified pollution hotspots provide critical insights for policymakers, enabling targeted interventions such as emission control regulations, improved industrial waste management, and enhanced monitoring infrastructure. By integrating Sentinel-5 data with GEE’s cloud-based processing capabilities, this study establishes a scalable and cost-effective framework for continuous air quality assessment in industrial zones, addressing the limitations of traditional ground-based monitoring. These findings contribute to a growing body of research on industrial air pollution in the Persian Gulf region, emphasizing the urgent need for stringent environmental policies and sustainable industrial practices to mitigate pollution-related health risks.
Copyright (c) 2025 Hossein Torabi, Zahra Abedi, Barat Mojaradi, Zahra Azizi (Author) https://creativecommons.org/licenses/by/4.0
Assessment and prioritization of different land use effect on surface soils contamination with some trace elements in Rey City, Tehran Province, Iran
Assessment of different land use effects on surface soil contamination is necessary for sustainable management of urban-industrial ecosystem.for this purpose in Rey city of Tehran province ,soil sampling was conducted across industrial and other land-use areas, collecting 52 composite surface samples (0–20 cm depth) to assess trace metal contamination. Samples were analyzed for metals (As, Cd, Pb, Zn, Cu, Ni) using atomic absorption spectrophotometry (AAS) and inductively coupled plasma (ICP-OES). Physical and chemical properties (texture, pH, organic matter, calcium carbonate) were measured via standardized methods.Pollution levels were evaluated using indices like the geoaccumulation index (Igeo), contamination factor (CF), Nemerow pollution index (NIPI), and potential ecological risk index (PERI), which incorporated toxicity factors and background values. Spatial hot/cold spots of contamination were identified via Getis-Ord analysis, highlighting clusters of high/low metal concentrations. These methods aimed to distinguish natural versus anthropogenic contamination and assess ecological risks. The study emphasized integrating geochemical, statistical, and spatial tools to map pollution patterns and prioritize mitigation efforts in Rey City’s industrially impacted soils. The Getis-Ord analysis revealed minimal pollution for Al (12% cold spots), localized As (<5%) and Cd hot spots, and elevated contamination for Cu (13%), Hg (>50% in west/north), and Mn. Mercury and manganese exhibited the most widespread pollution, highlighting critical environmental risks in Ray City, while aluminum showed negligible contamination. The results provide valuable guidance for policymakers, urban planners, and environmental managers to design targeted remediation efforts and preventive measures to reduce soil pollution risks.
Copyright (c) 2025 Laleh Ghiasi, Javad Varvani, Hamid Toranjzar, Abbas Ahmadi, Amir Hossein Baghaie (Author) https://creativecommons.org/licenses/by/4.0
Identifying the causes of floods and assessing the resulting environmental damage to provide a flood compensation model
Natural disasters can cause significant environmental damage and pollution, including floods that cause significant loss of life and environmental damage. Hence, modeling the compensation of such losses and utilizing specific strategies such as flood insurance can be considered effective solutions for compensation. Accordingly, the present study attempted to first identify flood damages using the Delphi method. Then, the identified criteria were prioritized through Analytic Hierarchy Process (AHP). Finally, the data were analyzed to provide a flood insurance and compensation model using national and international insurance laws and regulations. The results showed that, among the main criteria of flood damage, financial, human, and environmental losses were ranked most important with relative weights of 0.217, 0.191, and 0.178, respectively, and social damages were ranked least important with a weight of 0.108. Moreover, the most important sub-criteria, in order of priority, were building destruction (0.115), loss of life (0.110), and water pollution (0.084). To conclude, understanding the legal challenges associated with compensation is crucial in developing effective flood insurance plans. The legal challenges of natural catastrophe compensation involve a complex interplay of liability laws, both civil and criminal, insurance mechanisms, and the broader socio-economic impacts on affected communities. The distinctive and innovative proposal of providing a flood insurance plan with independent legal, technical, and structural frameworks and indicators based on the environmental insurance development approach is a suitable model for flood compensation. Developing a flood insurance scheme that effectively compensates for natural disaster losses requires addressing numerous legal challenges, including establishing a clear regulatory framework, managing flood risks, designing equitable compensation mechanisms, determining the roles of the public and private sectors, ensuring coordination across jurisdictions, and adapting to the impacts of climate change
Copyright (c) 2025 Mohammad Zahednia, Shirin Shirazian, Mohammad Reza Miri Lavasani, Hanie Nekoomaram, Mansour Pournouri (Author) https://creativecommons.org/licenses/by/4.0
Evaluation of temporal and spatial changes of irrigation water quality classes in Qazvin Plain, Iran, using machine learning models
The present study aimed to determine the quality and quantity of groundwater resources for agricultural purposes in the Qazvin Plain (northwest of Iran) using the spatial and temporal distribution maps of agricultural water quality classes prepared by machine learning models during three study periods of spring 2012, 2016, and 2020. Modeling was performed based on geological maps, annual precipitation maps and 12 hydrogeochemical parameters measured for 63 piezometric wells. Appropriate hydrochemical parameters were selected for each statistical period to model agricultural water quality using the machine learning models of Random Forest (RF), Boosted Regression Tree (BRT) and Multinomial Logistic Regression (MnLR). The results introduced the best models to be RF in 2012 (kappa coefficient (κ)=0.54, overall accuracy (OA)= 69%) and MnLR in 2016 and 2020 (κ= 0.83 and 0.75; OA=88 and 84%), respectively. The percentage of area for C4-S3 class (very high salinity with high sodium) increased from 5% in 2011 to 23.9% in 2019. Giving the increased precipitation in 2019, the agricultural water quality class in the southern region changed from C4-S3 in 2015 to C4-S2 (very high salinity with medium sodium) in 2019. Additionally, the simulated maps showed an elevation in the percentage of C4-S3 class area from 2012 to 2020 in the central part of the region where agricultural lands are concentrated. Our findings revealed the trend of adverse changes in water quality at different regions of Qazvin Plain during the years of study, highlighting the need to make purposeful management decisions. And The study utilized both advanced machine learning algorithms and traditional classification methods, including the Wilcox diagram, to assess agricultural water quality based on twelve physicochemical parameters. And The 12 parameters used in the study were selected based on data availability and relevance to agricultural water quality standards. Due to inconsistent data across years, variables such as nitrate and organic matter were excluded.
Copyright (c) 2025 Leila Davoodi Memar Otagvar, Ebrahim Fataei, Babak Naeimi, Mehdi Tajiabadi (Author) https://creativecommons.org/licenses/by/4.0
Evaluating the impact of source separation on the quality of biodegradable municipal waste (A case study: District 8 of Karaj city, Iran)
The present study was conducted to determine the effects of source separation training for municipal solid waste on the quality of compostable organic waste at District 8 of Karaj Municipality, Iran. This was an experimental study, the tools of which were sampling and conducting experiments. The research data were collected using cluster sampling. To determine the chemical properties of wet waste, samples were taken from 480 households in 7 neighborhoods of District 8 of Karaj Municipality, followed by laboratory analysis. To measure the quality of compostable organic materials, first, waste from the studied households was received once without providing training and subjected to physical analysis (separation of wet and dry materials). Once again, after providing training, the waste of the studied households was collected separately, wet and dry, from the doorsteps of the homes. From the total wet waste samples taken from each neighborhood, after complete mixing, one sample was taken for chemical analysis and transported to the laboratory. The measured parameters included total nitrate, organic carbon, electrical conductivity (EC), pH, calcium, cadmium, copper, iron, potassium, magnesium, phosphorus and lead. A t-test was used to obtain the difference between the physical and chemical properties of the wet waste before and after source separation training to households. Data were analyzed using SPSS27 software. Based on the results, there was a statistically significant difference between the values of EC, pH, cadmium, and iron at the level of 5%, as well as between the parameters of copper, potassium, magnesium, and phosphorus at the level of 1%, in the pre- and post-training stages. The EC value in the pre-training phase was 9914 μs/cm, which decreased to 7350 μs/cm after training. Calcium levels were 19,674 and 30,898 mg/kg, potassium levels were 24,006 and 18,225 mg/kg, phosphorus levels were 1987 and 3019 mg/kg, and the iron levels were 1804 and 466 before and after training, respectively. The concentration of magnesium in compostable organic waste increased significantly in the post-training phase compared to the pre-training phase. The findings of this study revealed the effectiveness of source separation of municipal solid waste in maintaining the amounts of elements present in compostable organic materials at appropriate levels.
Copyright (c) 2025 Marjan Potki, Ebrahim Fataei, Ali Akbar Imani, Marjaneh Kharrat Sadeghi (Author) https://creativecommons.org/licenses/by/4.0