The implementation of data reconciliation for evaluating a full-scale petrochemical wastewater treatment plant

Data reconciliation and mass balance analysis were conducted for the first time to improve the data obtained from a petrochemical wastewater treatment plant (WWTP), and the results were applied to evaluate the performance of the plant. Daily average values for 209 days from the inlet and outlet of the plant obtained from WWTP documentation center along with the results of four sampling runs in this work were used for data reconciliation and performance evaluation of the plant. Results showed that standard deviation and relative errors in the balanced data of each measurement decreased, especially for the process wastewater from 24.5 to 8.6 % for flow and 24.5 to 1.5 % for chemical oxygen demand (COD). The errors of measured data were −137 m³/day (−4.41 %) and 281 kg/day (7.92 %) for flow and COD, respectively. According to the balanced data, the removal rates of COD and 5-day biological oxygen demand (BOD₅) through the aeration unit were equal to 37 and 46 %, respectively. In addition, the COD and BOD₅ concentrations were reduced by about 61.9 % (2137 kg/day) and 78.1 % (1976 kg/day), respectively, prior to the biological process. At the same time, the removal rates of benzene, toluene, and styrene were 56, 38, and 69 %, respectively. The results revealed that about 40 % of influent benzene (75.5 kg/day) is emitted to the ambient air at the overhead of the equalization basin. It can be concluded that the volatilization of organic compounds is the basic mechanism for the removal of volatile organic compounds (VOCs) and it corresponds to the main part of total COD removal from the WWTP.

     

Estimating and mapping forest biomass using regression models and Spot-6 images (case study: Hyrcanian forests of north of Iran)

Hyrcanian forests of North of Iran are of great importance in terms of various economic and environmental aspects. In this study, Spot-6 satellite images and regression models were applied to estimate above-ground biomass in these forests. This research was carried out in six compartments in three climatic (semi-arid to humid) types and two altitude classes. In the first step, ground sampling methods at the compartment level were used to estimate aboveground biomass (Mg/ha). Then, by reviewing the results of other studies, the most appropriate vegetation indices were selected. In this study, three indices of NDVI, RVI, and TVI were calculated. We investigated the relationship between the vegetation indices and aboveground biomass measured at sample-plot level. Based on the results, the relationship between aboveground biomass values and vegetation indices was a linear regression with the highest level of significance for NDVI in all compartments. Since at the compartment level the correlation coefficient between NDVI and aboveground biomass was the highest, NDVI was used for mapping aboveground biomass. According to the results of this study, biomass values were highly different in various climatic and altitudinal classes with the highest biomass value observed in humid climate and high-altitude class.     

Effects of cimetidine and N-acetylcysteine on paraquat-induced acute lung injury in rats: a preliminary study

Abstract

Lung injury in rats challenged with paraquat at 20?mg kg^?1 body weight was histopathologically evident by inflammation, hemorrhage, and vascular congestion. Increased levels of reactive oxygen species and lipid peroxidation, decreased glutathione content, and lower tissue antioxidant capacity was found. The effects of N-acetylcysteine and cimetidine, a well-known potent inhibitor for organic cation transport, were examined. Lung injury was attenuated by N-acetylcysteine but not by cimetidine. The findings are consistent with the assumption that beneficial effects of N-acetylcysteine administration in paraquat-challenged animals might be linked to its ability for preserving the cellular redox environment and preventing oxidative stress, while cimetidine might even hasten paraquat-induced lung injury. On the other hand, the effects of cimetidine on paraquat-induced lung injury underline the importance of future studies on the role of transporters in this complication.     

Groundwater depth and elevation interpolation by kriging methods in Mohr Basin of Fars province in Iran

Prediction of groundwater depth and elevation is important in quantitative water management especially in arid areas. There are several basins in southwest of Iran, in Zagross Mountain, in which the water wells are distributed along a narrow elliptic ring band around the region. To find the most applicable interpolation method, both of the groundwater depth and elevation are predicted by different kriging methods. It is found that the groundwater elevation and depth can be predicted by different methods. Furthermore, it is found that the methods in which the trend is eliminated predicted the groundwater elevation and depth in central part of the region is with less standard error. Furthermore, the methods with no trend elimination, predicted the groundwater depths with less error near the water wells. Dividing the area to hydro-geologically homogeneous sub-areas improved the interpolation precision.     

A stochastic conflict resolution model for trading pollutant discharge permits in river systems

This paper presents an efficient methodology for developing pollutant discharge permit trading in river systems considering the conflict of interests of involving decision-makers and the stakeholders. In this methodology, a trade-off curve between objectives is developed using a powerful and recently developed multi-objective genetic algorithm technique known as the Nondominated Sorting Genetic Algorithm-II (NSGA-II). The best non-dominated solution on the trade-off curve is defined using the Young conflict resolution theory, which considers the utility functions of decision makers and stakeholders of the system. These utility functions are related to the total treatment cost and a fuzzy risk of violating the water quality standards. The fuzzy risk is evaluated using the Monte Carlo analysis. Finally, an optimization model provides the trading discharge permit policies. The practical utility of the proposed methodology in decision-making is illustrated through a realistic example of the Zarjub River in the northern part of Iran.     

Examining Relationships Between Socioeconomic Factors and Landscape Metrics in the Southern Basin of the Caspian Sea

Socioeconomic forces are not only among the main drivers of landscape dynamics; they are also influenced by landscape patterns. Landscape structure and functions are closely related to natural and social factors. The objective of this study was to investigate the relationships among some human-related factors and landscape ecological metrics as landscape pattern indicators and to identify suitable metrics for modeling these relationships. To this goal, landscape ecological metrics were calculated for each of the 32 counties of Mazandaran and Guilan provinces located in the southern basin of the Caspian Sea using land use/cover maps in class level. Stream network metrics were calculated using a digital elevation model, road density metrics were calculated using map of main roads separately, and significant metrics were selected according to results of correlation tests and factor analysis. The correlations between these metrics and socioeconomic factors were tested, and their relationships were modeled with multiple linear regressions. Significant relationships were found among socioeconomic factors and landscape ecological metrics, and land use/cover data are applicable for modeling socioeconomic factors, especially demographic and employment structure factors. Among the landscape metrics applied in this study, road density, mean patch size, mean nearest neighbor distance, and percentage of a land use/cover class in landscape were important metrics for predicting socioeconomic factors. Our findings indicated that road density metric and percentages of urban class are useful for predicting urban socioeconomic factors and percentage of agriculture and forest classes in the landscape are suitable metrics for predicting rural socioeconomic factors.     

Contamination by organochlorine compounds in the edible tissue of four sturgeon species from the Caspian Sea (Iran)

This study focused on accumulation of organochlorine compounds (OCs), including dichloro-diphenyl-trichloroethanes (DDTs), hexachlorobenzene (HCB), hexachlorocyclohexanes (HCHs), and polychlorinated biphenyls (PCBs) accumulation in the muscle of four sturgeon (Persian sturgeon, Acipenser persicus; Stellate sturgeon, Acipenser stellatus; Ship sturgeon, Acipenser nudiventris and Beluga sturgeon, Huso huso) from the southern Caspian Sea. The DDT group was prominent in all of the sturgeon muscle tested constituting almost half or more of the total organochlorine content. Contaminant concentration generally followed this order: DDTs>PCBs>HCHs>HCB. The OCs concentrations in Beluga sturgeon (H. huso) were the highest and over four times higher than in the next highest species (A. nudiventris). From an ecotoxicological point of view, the concentrations of OCs in experimental fishes do not reflect a comparatively clean and pollution-free environment; however, results from this study shown that the inflow of organic pollutants into the Caspian Sea has been reduced when compared with prior studies. Levels of measured OCs in sturgeon were relatively low, but the level of some OCs in some of the specimens tested exceeded the guidelines for food; therefore, the maximum allowable daily consumption rate for sturgeon from this watershed may be limited by DDTs and PCBs content for high risk populations.