Estimation of Water Demand in Iran Based on SARIMA Models

The generation of synthetic, residential water demands that can reproduce essential statistical features of historical residential water consumption is essential for planning, design, and operation of water resource systems. Most residential water consumption series are seasonal and nonstationary. We employ the seasonal autoregressive integrated moving average (SARIMA) model. We fit this model to monthly residential water consumption in Iran from May 2001 to March 2010. We find that a three-parameter log-logistic distribution fits the model residuals adequately. We forecast values for 1 year ahead using the fitted SARIMA model.     

Health risk assessment of mercury and arsenic associated with consumption of fish from the Persian Gulf

Concentrations of mercury and arsenic in fish from the Persian Gulf were determined by graphite furnace atomic absorption spectrometry. Concentrations of the metals in muscle samples were 0.049–0.402 μg g^?1 for mercury and 0.168–0.479 μg g^?1 for arsenic, with means of 0.133 and 0.312 μg g^?1, respectively. The maximum daily consumption rate (grams per day) and meal consumption limit (meals per month) was calculated to estimate health risks associated with fish consumption. According to the results, the maximum allowable consumption rate varies between 8–56 and 15–96 g/day base on mercury and arsenic content, respectively. The results of this study indicate that the concentration of mercury and arsenic is well below the maximum permissible levels for mercury (0.5 μg g^?1) and arsenic (6 μg g^?1) according to international standards.     

Indoor exposure to respirable particulate matter and particulate-phase PAHs in rural homes in North India

In order to evaluate the exposure of the northern India rural population to polyaromatic hydrocarbon (PAH) inhalation, indoor pollution was assessed by collecting and analyzing the respirable particulate matter PM_2.5 and PM₁₀ in several homes of the village Bhithauli near Lucknow, UP. The home selection was determined by a survey. Given the nature of biomass used for cooking, homes were divided into two groups, one using all kinds of biomass and the second type using plant materials only. Indoor mean concentrations of PM_2.5 and associated PAHs during cooking ranged from 1.19 ± 0.29 to 2.38 ± 0.35 and 6.21 ± 1.54 to 12.43 ± 1.15 μg/m³, respectively. Similarly, PM₁₀ and total PAHs were in the range of 3.95 ± 1.21 to 8.81 ± 0.78 and 7.75 ± 1.42 to 15.77 ± 1.05 μg/m³, respectively. The pollutant levels during cooking were significantly higher compared to the noncooking period. The study confirmed that indoor pollution depends on the kind of biomass fuel used for cooking.     

Investigating the impacts of treated effluent discharge on coastal water health (Visakhapatnam,SW coast of Bay of Bengal,India)

The present study investigated the impacts of treated effluent discharge on physicochemical and biological properties of coastal waters from three pharmaceuticals situated along the coast of Visakhapatnam (SW Bay of Bengal). Seawater samples were collected (during the months of December 2013, March 2014 and April 2014) from different sampling locations (Chippada (CHP), Tikkavanipalem (TKP) and Nakkapalli (NKP)) at 0- and 30-m depths within 2-km radius (0.5 km = inner, 1 km = middle and 2 km?=?outer sampling circles) from the marine outfall points. Physicochemical and biological parameters, which differed significantly within the stations, were likely to be influenced by strong seasonality rather than local discharge. Dissolved oxygen variability was tightly coupled with both physical and biological processes. Phytoplankton cell density and total chlorophyll (TChla) concentrations were significantly correlated with dissolved inorganic nutrient concentrations. CHP (December) represented a diatom bloom condition where the highest concentrations of diatom cells, total chlorophyll (TChla), dissolved oxygen coupled with lower zooplankton abundance and low nutrient levels were noticed. The centric diatom, Chaetoceros sp. (>?50%) dominated the phytoplankton community. TKP (March) represented a post-diatom bloom phase with the dominance of Pseudo-nitzschia seriata; zooplankton abundance and nutrient concentrations were minimum. Conversely, NKP (April) represented a warm well-stratified heterotrophic period with maximum zooplankton and minimum phytoplankton density. Dinoflagellate abundance increased at this station. Relatively higher water temperature, salinity, inorganic nutrients coupled with very low concentrations of dissolved oxygen, TChla and pH were observed at this station. Copepods dominated the zooplankton communities in all stations and showed their highest abundance in the innermost sampling circles. Treated effluent discharge did not seem to have any significant impact at these discharge points.     

Land surface temperature estimating in urbanized landscapes using artificial neural networks

Scenario-based land surface temperature (LST) modeling is a powerful tool for adopting proper urban land use planning policies. In this study, using greater Isfahan as a case study, the artificial neural network (ANN) algorithm was utilized to explore the non-linear relationships between urban LST and green cover spatial patterns derived from Landsat 8 OLI imagery. The model was calibrated using two sets of variables: Normalized Difference Built Index (NDBI) and Normalized Difference Vegetation Index (NDVI). Furthermore, Compact Development Scenario (CDS) and Green Development Scenario (GDS) were defined. The results showed that GDS is more successful in mitigating urban LST (mean LST?=?40.93) compared to CDS (mean LST?=?44.88). In addition, urban LST retrieved from the CDS was more accurate in terms of ANOVA significance (sig?=?0.043) than the GDS (sig?=?0.010). The findings of this study suggest that developing green spaces is a key strategy to combat against the risk of LST concerns in urban areas.     

Potentially toxic elements in urban soils: source apportionment and contamination assessment

Soils play a vital role in the quality of the urban environment and the health of its residents. City soils and street dusts accumulate various contaminants and particularly potentially toxic elements (PTEs) from a variety of human activities. This study investigates the current condition of elemental concentration in the urban soils of Hamedan, the largest and the fastest-growing city in western Iran. Thirty-four composite soil samples were collected from 0 to 10 cm topsoil of various land uses in Hamedan city and were analyzed for total concentration of 63 elements by ICP-MS. The possible sources of elemental loadings were verified using multivariate statistical methods (principal component analysis and cluster analysis) and geochemical indices. The spatial variability of the main PTEs was mapped using geographic information system (GIS) technique. The results revealed a concentration for As, Co, Cr, Mn, Mo, Ni, and V in the soil samples comparable to the background values as well as a range of associations among these elements in a single component suggesting geogenic sources related to geological and pedogenic processes, while the soils mostly presented a moderate to considerable enrichment/contamination of Cd, Zn, Pb, and Sb and moderate enrichment/contamination of Cu, Zn, and Mo. It was found that anthropogenic factors, vehicular traffic in particular, control the concentration of a spectrum of elements that are typical of human activities, i.e., Cd, Cu, Hg, Pb, Sb, and Zn. Lead and Sb were both the most enriched elements in soils with no correlation with land use highlighting general urban emissions over time and the impact of transport networks directly on soil quality. The highest concentrations of As were recorded in the southern part of the city reflecting the influence of metamorphic rocks. The effect of the geological substrate on the Co and Ni contents was confirmed by their maximum concentrations in the city’s marginal areas. However, high spatial variability of urban elements’ contents displayed the contribution of various human activities. In particular, the increased concentration of Cd, Sb, and Pb was found to be consistent with the areas where vehicular traffic is heaviest.