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The contamination of inorganic elements in soil is a serious environmental problem,. The aim of the present study is to investigate concentrations of 19 elements in order to access the extent of their contaminations in the surface soil of hydroelectric catchments, Uttarakhand, India. For analysis, 168 soil samples were divided into eight groups according to altitudes. In soil samples, the concentration levels of Cr and Cu were found more than their background and threshold limit. Moreover, the evaluation of geochemical index (Igeo), enrichment factor (EF), and contamination factor (CF) suggests that soil samples were reasonably contaminated and highly enriched in Rb. The pollution load index (PLI) and degree of contamination (Cd) revealed that the presence of contaminations (PLI: 1.44; Cd: 44.94) in the study site might be a possible health risk for local residents. However, the calculation pollution ecological risk index (PERI) suggests low ecological risk (PERI: 77.61) of these elements. The clustering of sampling groups contained two clusters: the first cluster comprised F1 and F4 while the second cluster consists of the rest of the sampling group. Multivariate statistical analysis revealed that the variation in concentrations of the elements might be a result of agricultural activities and pedological processes. [ABSTRACT FROM PUBLISHER]

Climate changes are likely to be significantly affected by reservoirs/lakes due to emission of greenhouse gas (GHG), change in the magnitude and seasonality of river runoffs and severe extreme events. In this study, a coupled GHG Risk Assessment Tool (GRAT) and Soil Water Assessment Tool (SWAT) are used to predict the GHG risk of Koteshwar reservoirs located in Uttarakhand, India. Before running the GRAT model, SWAT model was used to simulate the runoffs (one of the major input of GRAT). The model was calibrated (2004–09) and validated (2010–13) at Uttarkashi station using monthly discharge data. The model performance was checked by R2, NSE, RSR, and p-value as 0.785, 0.60, 0.63, and 0.04, respectively, during calibration and 0.790, 0.66, 0.57, and 0.06 during validation and shows satisfactory model performance on monthly time step. Further, GRAT model is also applied and the results show that Koteshwar reservoir is found to be under high risk of CO2(CO2> 645 mg m−2d−1) and medium risk of CH4(CH4< 45 mg m−2d−1) till 2023. Subsequently, the GHG risk is minimized after passage of time over 100 years. These models may be used by the policy-makers to know the potential of GHG and its vulnerability to the reservoirs after the impoundment. [ABSTRACT FROM PUBLISHER]

Soil organic carbon (SOC) is the largest active terrestrial carbon reservoir, which behaves both as a sink and source for atmospheric carbon. The same is maximum in the forest soil ofAbies pindrow(128 t ha−1) and minimum inPinus roxburghii(69 t ha−1). The mitigation potential is also found to be maximum in Alpine forest soil (i.e., 1.84) inAbies pindrowand minimum in the chir (i.e., 1.00) inP. Roxburghii. This indicates that alpine forest soil can hold nearly two times more SOC than chir and hence it behaves as a CO2sink. The overall average content of SOC and carbon dioxide equivalent under all land use was estimated at 91.29 t ha−1and 334.11 t ha−1, respectively. The objective of this study is to estimate the spatial variability of SOC stocks in the catchment of both the Tehri and Koteshwar hydroelectric reservoir using field investigations, laboratory measurements, and geostatistical methods. The study provides an estimation for the amount of carbon reaching to the reservoir through various sources, where it undergoes aerobic and anaerobic degradation, thereby releasing green house gases (GHGs) to the atmosphere. The information provided in this article will be useful for policy-makers and environmentalists for undertaking appropriate conservation plans to mitigate GHGs. [ABSTRACT FROM AUTHOR]

The hydropower reservoirs, considered as a green source of energy, are now found to emit significant quantities of greenhouse gas (GHG) to the atmosphere. This article attempts to predict the vulnerability of Tehri reservoir, India to GHG emissions using the GHG risk assessment tool (GRAT). The GRAT is verified with experimental GHG fluxes. The annual mean CO2fluxes from diffusion, bubbling, and degassing were 425.93 ± 122.50, 4.81 ± 1.33, and 7.01 ± 2.77 mg m−2d−1, whereas CH4fluxes were 23.11 ± 7.08, 4.79 ± 1.08, and 7.41 ± 4.50 mg m−2d−1, respectively, during 2011–12. The model found that Tehri reservoir emitted higher CO2and CH4(i.e., 790 mg m−2d−1and 64 mg m−2d−1, respectively) in 2011, which came within vulnerability range causing more climate change impact. By the year 2015, it would scale down to medium risks necessitating no further assessment of GHG. Significant difference between predicted and experimental GHG emission are assessed, which may be due to insufficient data, spatial and temporal variations, decomposition of flooded biomass, limitation of GRAT model, and inadequate methodology. The study reveals that GHG emission from Tehri reservoir is less than predicted by the GRAT. [ABSTRACT FROM PUBLISHER]

This study estimates the cancer and non-cancer health risk among the roadside vendors in Delhi, the capital city of India. Air samples of selected NMHCs and their derivatives were collected from four different sites (one traffic intersection, one industrial, and two residential) in Delhi and were analyzed on Gas Chromatograph (GC) to obtain their atmospheric concentrations. At each site, a survey among the roadside vendors was also conducted to obtain information about their bodyweight and exposure to outdoor ambient air. The study reveals that hazard quotient of 1,3-butadiene is greater than one at all the sites, with its maximum value occurring at the industrial site. The major contributors to the workplace cancer risk (WCR) are found to be 1,3-butadiene and chloroform. The overall WCR is observed to be the highest (9.4 × 10−4) at the traffic intersection site, followed by the industrial site (7.0 × 10−4). Cancer incidence data and the population data are also used to estimate the growth of cancer risk in Delhi from 2009 to 2016. Comparison of the WCR values of the four sites with the cancer risk estimated from the cancer incidence data shows that NMHCs and their derivatives are significant contributors to the overall cancer risk in Delhi. Our results suggest that NMHCs and their derivatives need to be given due consideration in the National Cancer Control Programme of India. [ABSTRACT FROM AUTHOR]