Assimilative capacity approach for air pollution control in automotive engines through magnetic field-assisted combustion of hydrocarbons

Environmental Science and Pollution Research - Deterioration of air quality through the combustion of hydrocarbon fuels has been one of the global transboundary problems put before the research...     

Landslide probability mapping by considering fuzzy numerical risk factor (FNRF) and landscape change for road corridor of Uttarakhand,India

Landslide poses severe threats to the natural landscape of the Lesser Himalayas and the lives and economy of the communities residing in that mountainous topography. This study aims to investigate whether the landscape change has any impact on landslide occurrences in the Kalsi-Chakrata road corridor by detailed investigation through correlation of the landslide susceptibility zones and the landscape change, and finally to demarcate the hotspot villages where influence of landscape on landslide occurrence may be more in future. The rational of this work is to delineate the areas with higher landslide susceptibility using the ensemble model of GIS-based multi-criteria decision making through fuzzy landslide numerical risk factor model along the Kalsi-Chakrata road corridor of Uttarakhand where no previous detailed investigation was carried out applying any contemporary statistical techniques. The approach includes the correlation of the landslide conditioning factors in the study area with the changes in land use and land cover (LULC) over the past decade to understand whether frequent landslides have any link with the physical and hydro-meteorological or, infrastructure, and socioeconomic activities. It was performed through LULC change detection and landslide susceptibility mapping (LSM), and spatial overlay analysis to establish statistical correlation between the said parameters. The LULC change detection was performed using the object-oriented classification of satellite images acquired in 2010 and 2019. The inventory of the past landslides was formed by visual interpretation of high-resolution satellite images supported by an intensive field survey of each landslide area. To assess the landslide susceptibility zones for 2010 and 2019 scenarios, the geo-environmental or conditioning factors such as slope, rainfall, lithology, normalized differential vegetation index (NDVI), proximity to road and land use and land cover (LULC) were considered, and the fuzzy LNRF technique was applied. The results indicated that the LULC in the study area was primarily transformed from forest cover and sparse vegetation to open areas and arable land, which is increased by 6.7% in a decade. The increase in built-up areas and agricultural land by 2.3% indicates increasing human interference that is continuously transforming the natural landscape. The landslide susceptibility map of 2019 shows that about 25% of the total area falls under high and very high susceptibility classes. The result shows that 80% of the high landslide susceptible class is contained by LULC classes of open areas, scrubland, and sparse vegetation, which point out the profound impact of landscape change that aggravate landslide occurrence in that area. The result acclaims that specific LULC classes, such as open areas, barren-rocky lands, are more prone to landslides in this Lesser Himalayan road corridor, and the LULC-LSM correlation can be instrumental for landslide probability assessment concerning the changing landscape. The fuzzy LNRF model applied has 89.6% prediction accuracy at 95% confidence level which is highly satisfactory. The present study of the connection of LULC change with the landslide probability and identification of the most fragile landscape at the village level has been instrumental in delineation of landslide susceptible areas, and such studies may help the decision-makers adopt appropriate mitigation measures in those villages where the landscape changes have mainly resulted in increased landslide occurrences and formulate strategic plans to promote ecologically sustainable development of the mountainous communities in India's Lesser Himalayas.

     

Insights into hazardous solid waste generation during COVID-19 pandemic and sustainable management approaches for developing countries

Journal of Material Cycles and Waste Management - The recent emergence of the COVID-19 pandemic has contributed to the drastic production and use of healthcare and personal protective equipment,...     

A GFP-based bacterial biosensor with chromosomally integrated sensing cassette for quantitative detection of Hg(II) in environment

A mercury biosensor was constructed by integrating biosensor genetic elements into E. coli JM109 chromosome in a single copy number, using the attP/attB recombination mechanism of λphage. The genetic elements used include a regulatory protein gene (merR) along with operator/promoter (O/P) derived from the mercury resistance operon from pDU1358 plasmid of Serratia marcescens. The expression of reporter gene gfp is also controlled by merR/O/P. Integration of the construct into the chromosome was done to increase the stability and precision of the biosensor. This biosensor could detect Hg(II) ions in the concentration range of 100-1700 nmol/L, and manifest the result as the expression of GFP. The GFP expression was significantly different (P ≤ 0.05) for each concentration of inducing Hg(II) ions in the detection range, which reduces the chances of misinterpretation of results. A model using regression method was also derived for the quantification of the concentration of Hg(II) in water samples.     

The Adaptive Capacity Wheel: a method to assess the inherent characteristics of institutions to enable the adaptive capacity of society

Climate change potentially brings continuous and unpredictable changes in weather patterns. Consequently, it calls for institutions that promote the adaptive capacity of society and allow society to modify its institutions at a rate commensurate with the rate of environmental change. Institutions, traditionally conservative and reactive, will now have to support social actors to proactively respond through planned processes and deliberate steps, but also through cherishing and encouraging spontaneous and autonomous change, as well as allowing for institutional redesign. This paper addresses the question: How can the inherent characteristics of institutions to stimulate the capacity of society to adapt to climate change from local through to national level be assessed? On the basis of a literature review and several brainstorm sessions, this paper presents six dimensions: Variety, learning capacity, room for autonomous change, leadership, availability of resources and fair governance. These dimensions and their 22 criteria form the Adaptive Capacity Wheel. This wheel can help academics and social actors to assess if institutions stimulate the adaptive capacity of society to respond to climate change; and to focus on whether and how institutions need to be redesigned. This paper also briefly demonstrates the application of this Adaptive Capacity Wheel to different institutions.     

An assessment of carbon stock for various land use system in Aravally mountains, Western India

Reducing carbon emissions from deforestation and degradation in developing countries is of the central importance in efforts to combat climate change. A study was conducted to measure carbon stocks in various land-use systems including forms and reliably estimates the impact of land use on carbon (C) stocks in the forest of Rajasthan, western India (23°3′–30°12′N longitude and 69°30′–78°17′E). 22.8% of India is forested and 0.04% is the deforestation rate of India. In Indian forest sector of western India of Aravally mountain range covered large area of deciduous forest and it’s very helpful in carbon sequestration at global level. The carbon stocks of forest, plantation (reforestation) and agricultural land in aboveground, soil organic and fine root within forest were estimated through field data collection. Results revealed that the amount of total carbon stock of forests (533.64?±?37.54 Mg·ha^?1, simplified expression of Mg (carbon) ·ha^?1) was significantly greater (P?<?0.05) than the plantation (324.37?±?15.0 Mg·ha^?1) and the agricultural land (120.50?±?2.17 Mg·ha^?1). Soil organic carbon in the forests (172.84?±?3.78 Mg·ha^?1) was also significantly greater (P?<?0.05) than the plantation (153.20?±?7.48 Mg·ha^?1) and the agricultural land (108.71?±?1.68 Mg·ha^?1). The differences in carbon stocks across land-use types are the primary consequence of variations in the vegetation biomass and the soil organic matter. Fine root carbon was a small fraction of carbon stocks in all land-use types. Most of the soil organic carbon and fine root carbon content was found in the upper 30-cm layer and decreased with soil depth. The aboveground carbon (ABGC): soil organic carbon (SOC): fine root carbon ratios (FRC), was 8:4:1, 4:5:1, and 3:37:1 for the forest, plantation and agricultural land, respectively. These results indicate that a relatively large proportion of the C loss is due to forest conversion to agricultural land.     

Simulating impacts,potential adaptation and vulnerability of maize to climate change in India

Climate change associated global warming, rise in carbon dioxide concentration and uncertainties in precipitation has profound implications on Indian agriculture. Maize (Zea mays L.), the third most important cereal crop in India, has a major role to play in country’s food security. Thus, it is important to analyze the consequence of climate change on maize productivity in major maize producing regions in India and elucidate potential adaptive strategy to minimize the adverse effects. Calibrated and validated InfoCrop-MAIZE model was used for analyzing the impacts of increase in temperature, carbon dioxide (CO₂) and change in rainfall apart from HadCM3 A2a scenario for 2020, 2050 and 2080. The main insights from the analysis are threefold. First, maize yields in monsoon are projected to be adversely affected due to rise in atmospheric temperature; but increased rainfall can partly offset those loses. During winter, maize grain yield is projected to reduced with increase in temperature in two of the regions (Mid Indo-Gangetic Plains or MIGP, and Southern Plateau or SP), but in the Upper Indo-Gangetic Plain (UIGP), where relatively low temperatures prevail during winter, yield increased up to a 2.7°C rise in temperature. Variation in rainfall may not have a major impact on winter yields, as the crop is already well irrigated. Secondly, the spatio-temporal variations in projected changes in temperature and rainfall are likely to lead to differential impacts in the different regions. In particular, monsoon yield is reduced most in SP (up to 35%), winter yield is reduced most in MIGP (up to 55%), while UIGP yields are relatively unaffected. Third, developing new cultivars with growth pattern in changed climate scenarios similar to that of current varieties in present conditions could be an advantageous adaptation strategy for minimizing the vulnerability of maize production in India.     

Informal e-waste recycling: environmental risk assessment of heavy metal contamination in Mandoli industrial area,Delhi, India

Nowadays, e-waste is a major source of environmental problems and opportunities due to presence of hazardous elements and precious metals. This study was aimed to evaluate the pollution risk of heavy metal contamination by informal recycling of e-waste. Environmental risk assessment was determined using multivariate statistical analysis, index of geoaccumulation, enrichment factor, contamination factor, degree of contamination and pollution load index by analysing heavy metals in surface soils, plants and groundwater samples collected from and around informal recycling workshops in Mandoli industrial area, Delhi, India. Concentrations of heavy metals like As (17.08 mg/kg), Cd (1.29 mg/kg), Cu (115.50 mg/kg), Pb (2,645.31 mg/kg), Se (12.67 mg/kg) and Zn (776.84 mg/kg) were higher in surface soils of e-waste recycling areas compared to those in reference site. Level exceeded the values suggested by the US Environmental Protection Agency (EPA). High accumulations of heavy metals were also observed in the native plant samples (Cynodon dactylon) of e-waste recycling areas. The groundwater samples collected form recycling area had high heavy metal concentrations as compared to permissible limit of Indian Standards and maximum allowable limit of WHO guidelines for drinking water. Multivariate analysis and risk assessment studies based on total metal content explains the clear-cut differences among sampling sites and a strong evidence of heavy metal pollution because of informal recycling of e-waste. This study put forward that prolonged informal recycling of e-waste may accumulate high concentration of heavy metals in surface soils, plants and groundwater, which will be a matter of concern for both environmental and occupational hazards. This warrants an immediate need of remedial measures to reduce the heavy metal contamination of e-waste recycling sites.     

Solubilization of municipal sewage waste activated sludge by novel lytic bacterial strains

Extracellular polymeric substances (EPS) are an extracellular matrix found in sludge which plays a crucial role in flocculation by interacting with the organic solids. Therefore, to enhance pretreatment of sludge, EPS have to be removed. In this study, EPS were removed with a chemical extractant, NaOH, to enhance the bacterial pretreatment. A lysozyme secreting bacterial consortium was isolated from the waste activated sludge (WAS). The result of density gradient gel electrophoresis (DGGE) analysis revealed that the isolated consortium consists of two strains. The two novel strains isolated were named as Jerish03 (NCBI accession number KC597266) and Jerish 04 (NCBI accession number KC597267) and they belong to the genus Bacillus. Pretreatment with these novel strains enhances the efficiency of the aerobic digestion of sludge. Sludge treated with the lysozyme secreting bacterial consortium produced 29 % and 28.5 % increase in suspended solids (SS) reduction and chemical oxygen demand (COD) removal compared to the raw activated sludge (without pretreatment) during aerobic digestion. It is specified that these two novel strains had a high potential to enhance WAS degradation efficiency in aerobic digestion.     

Green algae of the genus Spirogyra: A potential absorbent for heavy metal from coal mine water

Algae have considerable capability for absorbing heavy metals from wastewaters and are considered an effective treatment technology. Heavy metal absorption from coal mine water from the Bhowra Abandoned mine (open cast mine) and the Sudamdih Shaft mine (underground mine waters), both located in Dhanbad, India, by cells of Spirogyra was studied at different dilutions (100 percent, 80 percent, 60 percent, 40 percent, and 20 percent). In the present study, the following 18 metals were selected for analysis: aluminium (Al), arsenic (As), silver (Ag), barium (Ba), beryllium (Be), bismuth (Bi), cadmium (Cd), cobalt (Co), chromium (Cr), cesium (Cs), copper (Cu), iron (Fe), gallium (Ga), indium (In), potassium (K), manganese (Mn), nickel (Ni), and vanadium (V). Accordingly, Al and K were found to be higher in concentration with respect to selected metals for both mine waters. The biosorption study revealed that higher amounts of Al, Bi, Co, Cs, Fe, Ga, Mn, Ni, and V were absorbed by algal biomass at 100 percent concentration from both mine waters. The maximum uptake of Cu, As, and Cd was measured at 60 percent, 40 percent, and 20 percent, respectively, for the Bhowra Abandoned mine water. The biosorption equilibrium study revealed that Ag, Al, Ba, Be, Bi, Co, Cr, Cs, Fe, Ga, In, K, Mn, Ni, and V were maximally absorbed by algal biomass at 100 percent concentration from Bhowra mine water, while the maximum uptake by the algal biomass measured for the Sudamidh coal mine water was for Al, As, Bi, Cu, Fe, and Mn at 100 percent concentration. The different physicochemical characteristics of mine water and drinking water standards was also studied. Accordingly, total dissolved solid and chemical oxygen demand concentrations exceeded the drinking water standards for water samples collected from both mines.