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Climate change influences the agricultural sector by reducing available water resources, thereby influencing income, consumer and producer surplus, and crop prices. So, it is necessary to have a comprehensive integrated method to measure the effects of these changes on natural resources and social conditions. The present study aims to use the positive mathematical programming method to discover the trend and conditions of groundwater resources, agricultural water use, food security, and economic welfare of the agricultural sector in Iran. To this end, data for the period 2000–2015 was used under four different scenarios of normal climate change, climate change, climate variability, and concurrent climate change The results showed that the mean agricultural water use will amount to 35,103.6, 26,533.8, 35,216, and 26,510.7 million m3 and the mean decline in the reserves of aquifers will amount to 4422.22, 11,165.6, 4438.25, and 11,267.4 million m3 under the scenarios, respectively. With respect to food security, the net farm revenue will be 314,560, 248,753, 315,427, and 248,574 billion IRR, respectively. The mean crop price per ton will reach 905.3, 1141.8, 904, and 1142.8 million IRR, respectively. The mean consumer surplus will be 172,107.7, 166,450, 172,024, and 166,403 billion IRR and the mean producer surplus will be 419,959.2, 395,380, 419,751, and 395,204 billion IRR, respectively. Based on the results, to reduce the adverse impacts of climate change on different studied aspects, it is necessary to change policymaking in the water and agricultural sectors, especially regarding the shift from traditional agricultural water allocation to its market-based allocation and to change planting pattern.
相似文献The purpose of this study is to investigate the customer-based brand equity (CBBE) of green brands and their impact on green purchase consumption with the moderating effect of religious commitment. Data were gathered from 315 consumers in three large cities in Pakistan and further analysed by partial least square. The results of this study revealed that there is a significant positive nexus between CBBE and green purchase consumption. Additionally, results showed the evidence of religious commitment moderating the relationship between CBBE and green purchase consumption. The findings are helpful to the greening companies, suggesting that they should focus on every component of brand performance in order to achieve the higher ranked performance that ultimately initiates green purchase and repurchase consumption. This research addresses the attitude behaviour gap in green purchase consumption by incorporating the contingent impact of religious commitment.
相似文献Release of harmful organic intermediates or byproducts during the manufacture of petrochemical compounds is a serious problem in petrochemical plants. In this work, polysulfone membranes blended with GO/TiO2 nanocomposite were synthesized by phase inversion method and coated with a polyamide layer formed by interfacial polymerization to prepare a thin-film composite (TFC) sample. Analysis and characterization of the sample were carried out by XRD, FE-SEM, BET, FTIR/ATR, AFM, TGA, and zeta potential. Results indicated that incorporation of GO/TiO2 into the membrane structure enhanced porosity, surface roughness, and macrovoid formation along the cross-section of the sublayer and permeability of the membrane. The TFC membranes were applied to remove mononitrotoluene (MNT) and dinitrotoluene (DNT) as the basic intermediates of toluene diisocyanate (TDI). The membranes demonstrated high efficiency (>?90%) for the removal of MNT and DNT according to the charge exclusion mechanism and Donnan effect. Application of the TFC membrane for treatment of wastewater in the TDI plant showed that the removal of pollutants is variable in the range of 45–65% and 53–69% for the membrane with the highest flux and highest rejection in different transmembrane pressure, respectively.
相似文献Mapping spatial distribution of climatological parameters with a good degree of accuracy is crucial in environmental modeling and planning. Nowadays, there are various models to estimate and predict spatial variables in an area but some such as cokriging and geographically weighted regression (GWR) have got more attention from experts in this field. The objectives of this study are to evaluate and compare GWR with ordinary cokriging (OCK) techniques for estimating the mean annual air temperature (MAT) of Iran using European Centre for Medium-Range Weather Forecasts (ECMWF) data and auxiliary variables (e.g., longitude, latitude and altitude). The MAT-gridded data for Iran was collected in pixels during the time interval of 1987–2015 from the ERA-Interim re-analysis version of ECMWF. Validation results indicate that cokriging model with latitude and altitude for estimating MAT has the lowest MAE (0.0155), MBE (0.00085), RMSE (0.0251), and the highest NS (0.9999) in relation to other cokriging methods. On the other hand, GWR with altitude has better results than those of GWR with other auxiliary variables because of its MAE (0.1271), MBE (0.0124), RMSE (0.1760), and NS (0.9969). By comparing two mentioned methods, cokriging with latitude and altitude has provided the best performance in relation to GWR for prediction of MAT in Iran. To obtain accurate estimation of the spatial distribution of MAT, local residuals were analyzed. Results concluded that residuals of the OCK model have high spatial adaptations between the observed and predicted MAT data compared to the GWR model. Hence, OCK was a relatively optimum method for the estimation of MAT compared with GWR.
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