نشریه محیط زیست طبیعی
سال هفتاد و ششم شماره 2 (تابستان 1402)

Today, one of the most important challenges in wastewater treatment is the destruction of organic pollutants, especially antibiotics. This research investigated the efficiency of the photocatalytic process in removing the antibiotic amoxicillin from the water environment using SiO2@TiO2 nanocomposite. The desired nanocomposite has been synthesized using sol-gel method and characterized by XRD, FTIR and TEM techniques. To improve the performance of the fabricated nanocomposite, parameters such as pH, contact time, nanocomposite concentration, and drug concentration were studied and optimized using the response surface method and the Central Composite Design model. Characterization of nanocomposite with XRD showed the formation of crystalline phases and anatase structure. The formation of SiO2@TiO2 nanocomposite with Ti-O-Si bond was confirmed in FT-IR spectrum. Also, the TEM image showed that the particles have a spherical and uniform structure. The results of photocatalytic optimization experiments showed that the highest degradation efficiency (98.7%) of amoxicillin under pH:3, amoxicillin initial concentration: 10 mg/L, nanocomposite concentration: 2 g/L, contact time: 10 minutes, which is very close to the efficiency of predicted removal under optimal conditions in the BBD model (100%). Due to the high degradation efficiency and high production of free radicals, the synthetic photocatalyst has a high ability to degrade pharmaceutical pollutants, especially antibiotics, which develops its future applications for the degradation of organic pollutants with a similar chemical structure.

Globally, freshwater is unevenly distributed, both in space and time. Increasing human exploitation increase the pressure on water as a resource for human well-being. For this reason, in order to compensate for the lack of water, human beings are thinking about inter-basin water transfer. One of the water transfer plans that is being implemented is the water transfer plan from the headwaters of Halil River to Kerman. Considering the importance of this issue, the purpose of the present study is to investigate the attitude of the farmers of Jiroft Plain towards this plan. In this study, 150 farmers of Jiroft Plain were randomly selected and interviewed in the spring of 1401. To evaluate the factors affecting the attitude of farmers, variables such as 1) communication with local groups, 2) trust in government organizations, 3) non-participation in government programs, 4) lack of assistance to farmers from the government, 5) impact on agriculture and the environment, 6) turning the Jiroft plain into a desert, 7) cooperation between governmental and non-governmental organizations as an independent variable and agree or disagree with the water transfer plan was considered dependent variables. Finally, a logistic regression test was used for analysis. The results showed that people who believe that participation in government programs is wrong, the government will not help the farmers after the water transfer plan, the farmers will be severely affected and the Jiroft Plain will turn into a desert. Some people are against the water transfer plan.

Human-induced land use land cover changes have resulted in adverse impacts on the environment at various spatial and temporal scales. Land surface temperature (LST) is an important indicator associated with strong spatio-temporal variability in complex Earth Patterns. Remote sensing is the primary source for various types of thematic data critical to land analysis, including land use data and land surface temperature changes. In this study, first, to analyze the spatial-temporal land surface temperature changes, LST maps were prepared using Radiative Transfer Equation, Single Channel Algorithm, Split Window Algorithm and Two Mono Window Algorithm. Then the performance of Land Surface Temperature (LST) retrieval methods was evaluated. Land use and land cover maps were prepared to investigate the contribution and role of each land use class on the changes of the LST.  Also, the effects Normalized Difference Vegetation Index, Normalized Difference Built-up Index and elevation on LST variability were investigated. There was a positive correlation of LST with Normalized Difference Built-up Index and a negative correlation with Normalized Difference Vegetation Index and elevation for all years. Spatio-temporal analysis shows a 6.64°C increase in LST from 1989 to 2021. The results clearly showed the moderating role of vegetation, regardless of its type, on LST. The findings of the present study serve as basic information for future studies to investigate the impact of different policies on LULC change in the region. Also, the obtained results reveal the importance of studying and examining the mentioned changes in order to achieve sustainable development.

Ecosystem is a platform for economic and social development and in fact a support for sustainable production in any society, so that its exploitation is essential and unavoidable. One of the important subdivisions of ecosystems is pastures. The management and development of tourism in pastures can reduce the pressure on the rangeland by creating and improving the livelihood of the beneficiaries. Based on this, the purpose of this research is to formulate a solution to achieve sustainability in the pastures of Derkash village, Maneh and Samalghan counties, Razavi Khorasan province. First, by filling out the letter and interviewing the local stakeholders (135 of the tourist areas), the requirements for the formulation of direct standards were converted using the simple random sampling method in collecting people. In the next stage, the questionnaire was completed and in the form of a SWOT questionnaire, it was placed at the disposal of 45 experts and experts related to the exploitation of pastures, so that coefficients and scoring can be done by them. SWOT analysis was used to formulate strategies for achieving sustainable tourism, and finally the extracted strategies were prioritized by the QSPM matrix. The results showed that the cases of "advertising to attract tourists and registration of accommodation in online sites for booking, implementation of the standards considered by tourists (especially parking), creation of handicraft markets and village products (such as honey) to create supplementary income for interest vector and cultural and social education of the residents of some villages to accept and attract tourists are the first to fourth priorities in order to achieve sustainable tourism in the pastures of the studied area.

The increase in population and the development of urban and industrial infrastructure have caused an increase in atmospheric pollutants and numerous environmental problems. The aim of this study was to find the origin and measure the health risk index of heavy metals (Cadmium and Lead) in the dust falling from the buildings of science and research unit. For this purpose, the sampling of atmospheric particles (dust) from the interior spaces of the buildings was done in 20 points by passive method. The obtained concentrations of the studied metals were used to calculate various health risk indices, enrichment index, land accumulation index, ecological risk index, carcinogenic risk index and HI risk index. The average concentration of studied metals in different stations for cadmium and lead metals was evaluated as 5.4081±0.85 and 170.9257±71.9418 mg/kg, respectively. There was a statistical difference between the average concentration of metals in such a way that this noticeable difference was observed with lead metal (P<0.05) and cadmium metal (P<0.05). The enrichment factor showed a significant difference between lead (P<0.05) and cadmium (P<0.05). There was a difference between cadmium (P<0.05) and lead (P< 0.05) accumulation index. Ecological risk index was evaluated low in all stations except stations 8 and 18. Daily chronic absorption from the gastrointestinal tract for lead metal was calculated at the highest level. The non-carcinogenicity index of the gastrointestinal tract for lead metal was evaluated as high. The respiratory tract also showed a very low risk. In general, the results showed that the studied area has heavy metal pollution, which has the capacity of carcinogenic and non-carcinogenic risk for sensitive groups of the society.

Today, the rapid development of industries and the use of hundreds of new chemical compounds in them have led to the creation of huge amounts of industrial wastewater, the discharge of which into the environment, especially watercourses, has caused severe pollution. The discharge of colored wastewater into natural ecosystems has created serious risks such as carcinogenesis, mutagenicity, etc. for aquatic life due to adverse functions. Meanwhile, Reactive Black 5 has many industrial applications, especially in the textile industry worldwide. Fe (VI) was synthesized electrochemically using iron and steel electrodes in potassium hydroxide solution at 65 ° C and then used to remove the reactive Black 5 in the batch removal system. In this study, the surface response method (RSM), the effect of various parameters including initial color pH, Fe (VI) dose and time and then the central composite design (CCD) were used to find the best removal conditions. The optimal values for the three variables of pH, Fe (VI) dose and time were obtained 4.5, 24.5 mg and 25 minutes, respectively. In the present study, by increasing the Fe (VI) dose and after 25 minutes from the start of the reaction, the removal efficiency increased, if the removal was better in acidic conditions than in alkaline conditions. Also, under the optimal conditions of Fe (VI) solution, it was able to remove 97% of reactive black 5. Finally, under the same conditions, real wastewater was also worked on and the removal rate was 95%. The findings of this study showed that Fe (VI) can be used as a suitable, inexpensive and high-performance oxidizing agent in the removal of reactive Black 5 from textile industry effluents.

The country's pastures are one of the main sources of production and provide an important part of the fodder needed by livestock. This issue is very important in the Zagros region. Therefore, the main goal of this research is to investigate the effective factors on the participation of users in rangeland projects in Lorestan province. The collection of data and information in this research was done through a questionnaire (130 questionnaires from the operators of Borujerd city). The results of the logit model showed that the variables of education, second job, the cost of animal fodder, grazing license and the degree of dependence on pastures have a negative and significant relationship with participation in grazing projects, as well as the variables of membership in a cooperative, annual income, ownership, compliance with the pasture law, attendance at The experts' classes and the level of trust in the executors of the plan show a positive and meaningful relationship. The highest elasticity values ​​and the estimated final effect are respectively related to the variables of dependence and participation in classes, so that with an increase of one percent in dependence and one unit in participation in classes, the probability of participating in projects decreases by 3.455 percent and 0.764 units will increase. McFadden's coefficient of determination is 50%, which shows that the explanatory variables of the model have explained the changes of the dependent variable well. Also, Amare Madala and Estrella confirm this. The percentage of correct prediction also shows that 86% of the respondents correctly answered the willingness to participate according to the information. Therefore, it is suggested that due to the limited budget of the organizations, priority should be given to increase the participation of users through the media and form educational classes to increase their awareness and knowledge regarding the necessity of implementing rangeland projects. At the same time, the issue of planning based on land development and grazing plans and drafting new laws should also be on the agenda.

Effective management of human-wildlife conflicts requires an understanding of risk perception, peoples’ responses to conflicts, as well as the impact of socio-economic and cultural factors on people's attitudes. We designed a questionnaire form to investigate the effect of each factor on human-brown bear conflicts in the areas with a high risk of conflict in Kamfiruz (Marvdasht county, Fars), during the peak conflict period (July to September), and evaluate the contribution of the effective strategies in mitigating conflicts. We used logistic regression to evaluate the factors affecting people's attitudes and also network analysis to survey the role of each factor in human-bear conflict and the importance of effective strategies in reducing conflict. The results showed that, according to the respondent's point of view, habitat loss and scarcity of natural prey, persecuting brown bears, and lack of sufficient knowledge about the species have the most centrality in the network. Also, among the suggested solutions by the respondent's, visual or auditory deterrents, trained dogs, compensation payments, insuring, and increasing natural prey’s population had the most centrality in the network, respectively. The results of the logistic regression showed that people who feel more eager when they see or think about bears have a more positive attitude toward the species. Also, people who like brown bears have a more positive attitude towards them. On the other hand, people who have a higher level of conflict with the species have a negative attitude towards it. According to the results, considering factors influencing natives' attitudes and engaging people in collaborative conservation programs have an important role in identifying effective and applicable solutions to mitigate human-brown bear conflicts.

A relatively accurate prediction of the concentration of pollutants and environmental variables, short-term and long-term, is an important step in reducing the damage caused by poor air quality. In this study, first by spatiotemporal analysis and then, using prediction techniques, to predict the concentration of fine atmospheric particles (PM2.5), temperature and vegetation cover index (NDVI) on the trend of PM2.5 in a period of 5 years (2017-2022) was discussed at the level of Iran. The data of PM2.5 concentration, temperature and vegetation index were extracted based on MERRA-2, FLDAS and MODIS satellite models. In the five-year study period, a somewhat downward trend was observed for the air concentration of PM2.5. The results showed the lowest annual average concentration of fine atmospheric particles in 2019 and 2020. Also, a strong correlation between PM2.5 concentration and temperature was obtained. The highest average concentration of PM2.5 occurred in the northwest, west, and southwest of Iran. In the next step, in order to predict the future concentration of PM2.5 air particles, temperature and vegetation index, the Exponential Smoothing approach was used in the Python statistical library (Statsmodels) to model monthly time series. Evaluation of the models with two criteria of root mean square error (RMSE) and coefficient of determination (R2) was done to minimize the estimation error and find the most suitable model among the eleven predicted models. The results show that double exponential smoothing models are more suitable for predicting PM2.5 concentration and triple exponential smoothing models with Holt-Winter trend are more suitable for predicting temperature and NDVI data. This study can help public and private institutions to better understand economic, health and environmental condition affected by air pollution effects by predicting the period when air pollution levels may be particularly high.

The dynamic link between economic growth and environmental quality has drawn the attention of numerous scholars to the problem of clean production and sustainable development. In light of this backdrop, the aim of this study is to provide a framework for discovering a good understanding of economic policies in connection to sustainable environments by looking at the mediating role of financial development. In this regard, the System Generalized Method of Moment (SYS-GMM) estimator is used to investigate the role of financial development in the effect of economic growth on six environmental indicators for selected 30 Organization for Economic Cooperation and Development (OECD) countries from 2000 to 2019. The results showed that along with the effect of economic growth on each of the environmental indicators, including ecological footprint, adjusted net savings, pressure on nature, and environmental performance, financial development weakens this effect. Meanwhile, no significant relationship has been observed regarding the indicators of environmental sustainability and environmental vulnerability. In other words, the negative impact of economic growth on environmental quality is not independent of financial development; so that with the gradual improvement of financial development, economic growth will have a less negative impact on the quality of the environment. Moreover, regarding each of the environmental indicators, energy consumption has a positive effect on environmental degradation. However, trade openness and financial development have positive influences on environmental quality. Given the critical role of financial development in mitigating the detrimental effects of economic growth on the quality of the environment, governments are urged to boost the financial development sector in their macroeconomic policies.

The development and expansion of industrial and agricultural centers has caused an increase in industrial and agricultural wastewaters and their entry into the environment, which will cause widespread damage. The aim of this research is to investigate the effects of heavy metal toxicity on blood parameters, biochemical parameters and liver enzymes of desert scraper (Capoeta fusca). The acute toxicity of studied heavy metals was estimated according to the OECD method. Samples in 5 groups of 20 pieces (one control group) were exposed to the sublethal concentration of different heavy metals and after the end of 28 days, the blood serum of the fishes was collected and its biochemical parameters and liver enzymes were measured by autoanalyzer. The average lethal concentration of cadmium, chromium, cobalt and copper in 96 hours for the studied species is 37.14, 292.49, 106.95 and 10.73 mg/L, respectively. The number of erythrocytes (× 106 mm3) in the blood of fishes exposed to cadmium, chromium, cobalt and copper was 3.4 ± 0.17, 4.5 ± 0.22, 2.9 ± 0.14, and 3.6 ± 0.18, respectively. The number of erythrocytes of fish exposed to cadmium, cobalt and copper is significantly (p < 0.05) lower than the control group (4.8 ± 0.24). The main damages to erythrocytes exposed to cadmium, chromium, cobalt and copper include vacuolation and deformation of erythrocytes. Glucose and cholesterol levels of fish exposed to cadmium, chromium, cobalt and copper metals are significantly (P<0.05) higher than the control group, and triglyceride, protein and albumin levels are decreased compared to the control group. The level of liver enzymes alkaline phosphatase (ALP), aspartate aminotransferase (AST) and alanine aminotransferase (ALT) in fish exposed to cadmium, chromium, cobalt and copper was significantly (P< 0.05) higher than the control group after 28 days. Therefore, the exposure of the studied species to different heavy metals causes changes in the level of biochemical parameters and liver enzymes In addition, biochemical parameters and liver enzymes can be used as appropriate biomarkers for fish health and for monitoring the quality of aquatic environments.