فصلنامه محیط شناسی
سال چهل و نهم شماره 1 (پیاپی 105، بهار 1402)

The purpose of this research is to determine the toxicity of chemical components in PM2.5 particles and its production sources with the help of linear multivariate regression models between 2014 and 2015 at the Sharif University station. Based on the chemical analysis of the samples and the use of the oxidation capacity of suspended particles as an indicator of particle toxicity (ROS), it is possible to determine the toxicity of particles, their chemical compositions and provide resources. The amount of toxicity received in the cold seasons of the year was 1.5-3 times higher than in the hot seasons of the year, and due to the concentration of light vehicles in the cold seasons, the possibility between this source and the toxicity of particles is strengthened. The results of Pearson's correlation analysis showed that chemical components of human origin antimony, cadmium, nickel and arsenic had the highest correlation with toxicity index. This result is also consistent with Spearman's rank correlation analysis. Also, by examining the relationship between toxicity and resource contribution, the monthly contribution of MENA to gasoline vehicles and fuel oil is explained with both types of toxicity indices. By performing multivariate linear regression between toxicity and related chemical elements as well as two related sources, according to the obtained results, the contribution of gasoline vehicles in causing particle toxicity in the survey valley is equal to 83% on average.

In this research, the effect of the effective parameters in the iwan on the cooling performance of summer rooms in the residential structures of Yazd city was evaluated. The aim of the current research is to provide an optimal model for increasing sustainable development for contemporary housing in a hot and dry climate. Therefore, in the beginning, in order to investigate the effect of the effective parameters on the iwan, field studies and typology of the house plans of Yazd were studied, and in the next step, the base models were simulated in the Ecotect software and for data analysis, the EnergyPlus software was used. Then, the criteria and sub-criteria of the optimal iwan model were ranked after determining the weight of parameters affecting iwan and prioritizing them using the analytical hierarchy process (AHP) in Super Decisions. The results showed that the main criteria were ranked in the following order: changing the height of iwan, the effect of the main zone, determining the optimal weight of length, height, and depth parameters on iwan, and determining the optimal dimensions of iwan in (summer rooms). The positive effect of the iwan itself shows the advantage of using this idea in sustainable housing designs and suitable for hot and dry climate

Human activities have increasingly threatened biodiversity and habitat services. With the intensification of fragmented habitats has affected their quality. In this regard, it is necessary to know the spatial pattern of habitat hotspots because it, in turn, causes environmental sustainability. In present research, habitat quality modeled in arid ecosystems of South Khorasan province using InVEST software based on human threats, impact, distance, relative sensitivity to threats, and accessibility of habitat sources. Then spatial data mining of hotspots was analyzed using Gettis-Ord Gi, Moran and natural breaks methods. Also, the accuracy assessment of habitat hotspots extraction, through the ROC index, indicated accuracy more than 80% in the mentioned data mining methods, but the Gettis-Ord Gi index had the highest accuracy (94.5%). The results of the spatial statistics of habitat hotspots overlapping with the protected areas of the province showed that Kamarsorkh Protected area contains the most (91.33%) and the Estand No-hunt area has the least (0.54%) habitat hotspots. Also, some areas of habitat hotspots were identified in free lands (9.34%). Therefore, the current protected areas do not cover a significant percentage of the hotspots in the free lands, so in sustainable conservation planning, the proposed methodology in research can apply to change and revise the borders of the protected areas.

The performance of the Fe3O4- CeO2- NH2/ chitosan/ Polyvinyl alcohol nano hybrid synthesized by casting method was investigated for the adsorption of Cu (II) and Ni (II) cations from water system. The synthesized nano hybrid adsorbents were characterized by FESEM, BET and FTIR analyses. The effect of single and binary oxides content, Fe3O4-CeO2-NH2 content, pH, initial cation concentration, contact time and temperature on the adsorption capacity was evaluated in a batch system. The results showed that the adsorption capacity significantly increased after modification of adsorbent with Fe3O4- CeO2- NH2 nanoparticles. The kinetic and equilibrium data were accurately evaluated by the double- exponential and Redlich- Peterson models, respectively. The maximum adsorption capacity of nano hybrid adsorbent was estimated to be 246.9 and 88.6 mg / g at 45 º C for Cu (II) and Ni (II) cations, respectively. Thermodynamic investigation indicated an endothermic and spontaneous adsorption for both metal cations; and adsorption was favored at higher temperature. The synthesized nano hybrid can be easily regenerated after five cycles of adsorption- desorption. 

The road transportation has become one of the major metal contamination sources that could impact on roadside soils. Therefore, this study was conducted to evaluate the toxicity and related health implications of roadside contaminated soils with Zn, Pb, Cd, and Cr in city of Hamedan, west of Iran. In so doing, a total of 63 surface soil samples were collected along 700 m of a 9 km segment of the three major highways (i.e. Goltepeh (G), Razen (R) and Kermanshah (K)) in Hamedan Province. After acid digestion of samples, the element contents were determined using inductively coupled plasma optical emission spectroscopy (ICP-OES). The computed values of the Nemrow integrated pollution index (NIPI) showed that the pollution of all the analyzed elements in the highways with higher traffic volume (i.e. R and K) could be classified as "severe", indicating that effect of human activities, especially with the traffic origin. Also, based on the mean values of the toxic risk index (TRI) of the elements, the soil samples could be classified as 'non-toxicity'. Besides, the non-carcinogenic risk index (HI) values of the tested elements suggested that the HI could be classified as 'low risk' for both children and adults. Moreover, the carcinogenic risk (CR) of Cr was at a tolerable level for both children and adults, while Pb and Cd have been shown no significant carcinogenic risk. In conclusion, it is suggested that contaminated soil analyses be included in future studies in order to maintain environmental and human health.

The aim of this research is investigate quality of underground and Surface water of the Dez Dam lake. Existence of two oil fields (Qala Nar and Balaroud), upstream of Dez Dam and their inclined slope towards Dez Dam Lake, Will affected the release of oil pollutants through underground water to the Dez Dam. Risk assessment development has been done using EPA method. The samples of underground water and Dez dam reservoir were analyzed by gas chromatograph to determine the amount of total petroleum hydrocarbons. The new risk assessment equation (HRA) formulated by considering the importance factor. Analytical Hierarchy Process (AHP) used to evaluate the degree of health importance of petroleum hydrocarbons in the range of C10, C20, C30 in underground water and Dez Dam and the probable risk to human health was calculated according to the EPA standard and the new method for carcinogenic and non-carcinogenic risk. According to the EPA, the results of this research do not include cancer slope (CSF), as a result, there is no risk of carcinogenesis in the existing samples but they have a non-carcinogenic. C10 and C22 hydrocarbons entered the dam from underground water, C10 in the EPA method with a rate of 1.94 and in the new method (HRA) 1.13 has the highest probability of non-carcinogenic risk. Results obtained from the EPA equation and the new HRA formula in this research showed that the total petroleum hydrocarbons entered the underground water and dam lake and have a high probability of non-carcinogenic risk.

Predicting the effect of climate change on native ecosystems is one of the longstanding goals of ecologists and is essential for their conservation and management. Species distribution models (SDMs) are the most widely used tools to predict the effects of climate change on the geographical range of plants. In this study, two regression techniques (GLM and MARS) and two machine learning techniques (ANN and RF), along with environmental factors were used to predict the distribution of Onobrychis cornuta L. The species response to future climate (2050-2070) was investigated under optimistic (SSP1-2.6), pessimistic (SSP3-7.0) and very pessimistic (SSP5-8.5) emission scenarios of the IPSL-CM6A-LR climatic model from CMIP6 models. Based on results, the ensemble model and then MARS presented the most accurate prediction. ANN had the lowest prediction accuracy with a significant difference from other models (p<0.05). The sensitivity analysis revealed altitude (24.64%), maximum temperature of the warmest month (20.31%), temperature seasonality (16.57%) and diurnal range of mean temperature (16%) as the most effective variables on the distribution. According to the ensemble model, the suitable habitat occupies about 27% of the area, but its distribution will be decrease under the future climate. The SSP5-8.5 scenario will have the greatest impact on the displacement of the species distribution range. The resulting prediction maps provide valuable information for conservation strategies, including identifying suitable places for its reintroduction and cultivation in the framework of rangeland management plans.