A multi-criteria GIS-based model for wind farm site selection with the least impact on environmental pollution using the OWA-ANP method

Environmental Science and Pollution Research - Wind energy is considered one of the most efficient and cost-effective ways to generate electricity, since it has a low environmental impact. So, it...     

The detection of SARS-CoV-2 RNA in indoor air of dental clinics during the COVID-19 pandemic

Environmental Science and Pollution Research - In the indoor environment of dental clinics, dental personnel and patients are exposed to a risk of infection because of the transmission of...     

CLIMATE CHANGE IMPACTS ON NEW YORK CITY'S WATER SUPPLY SYSTEM1

ABSTRACT: It has been well established that the greenhouse gas loading of the atmosphere has been increasing since the mid 19th century. Consequently, shifts in the earth's radiative balance are expected with accompanying alterations to the earth's climate. With these anticipated, and perhaps already observable, changes in both global and regional climate, managers of regional water resources seek insight to the possible impacts climate change may have on their present and future water supplies. The types and degrees of impacts that climate change may have on New York City's water supply system were assessed in a study of a watershed at Allaben, New York. Hypothetical scenarios of future climate and climate change projections from three General Circulation Models (GCMs) were used in conjunction with the WatBal hydrological model and the Palmer Drought Severity Index (PDSI) to ascertain how runoff and soil moisture from this watershed may change in a warmer climate. For the worst case predictions, the results indicate that within the century of the 2000s, the watershed's air temperature may increase up to about 11°F, while its precipitation and runoff may decrease by about 13 and 30 percent, respectively. If this watershed is typical of the others within the New York City water supply system, the system's managers should consider implementing mitigation and adaptation strategies in preparation for the worst of these possible future conditions.     

Multi-objective conflict resolution optimization model for reservoir’s selective depth water withdrawal considering water quality

Environmental Science and Pollution Research - This paper develops a multi-objective conflict resolution simulation-optimization model based on a leader-follower game to resolve conflicts between...     

Sustainable EOQ and EPQ models for a two-echelon multi-product supply chain with return policy

Environment, Development and Sustainability - In this work, a new model is developed to determine optimum sustainable economic order quantity (EOQ) and economic production quantity (EPQ) values for...     

High-risk behaviors while driving: A population-based study from Iran

Objective: Traffic injuries are becoming one of the most important challenges of public health systems. Because these injuries are mostly preventable, the aim of this study is to evaluate the four main high-risk behaviors while driving.

Methods: This cross-sectional study was conducted on a random sample from the population of Mashhad, Iran, in 2014. A checklist and a previously validated questionnaire for the transtheoretical stages of change model (TTM) were used for data collection. Statistical analyses were performed using SPSS 11.5 software with P <.05 statistically significant.

Results: Totally 431 individuals were included with a mean age of 30 ± 11.3 years. Forty-three percent (183) were male. The TTM model revealed that participants were mostly in pre-actional phases regarding not using a cell phone while driving (80%), fastening the driver's seat belt (66%), front seat belt (68%), and rear seat belt (85%) The penalty was a protective factor only for using cellphone (odd ratio [OR] = 0.82, 95% confidence interval [CI], 0.68–0.98). Lower education (OR = 0.12, 95% CI, 0.01–0.94) and male gender (OR = 0.35, 95% CI, 0.14–0.83) were indicative of lower rates of fastening the front and rear seat belts.

Conclusion: The stages of change model among study participants is a proper reflection of the effectiveness of the current policies. More serious actions regarding these high-risk behaviors should be considered in legislation.     

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.