Opencast mining causes significant environmental concern due to acid mine drainage (AMD) caused by the oxidation of pyrites and other sulfur-bearing minerals. The present study intends to determine the seasonal variability of AMD in the affected area of the Ledo opencast mining, the cytotoxicity of the AMD, and the AMD remediation process. The physicochemical properties of the collected samples were analyzed by using laboratory-based methods and sophisticated instrumental tools. The cytotoxicity study of AMD water was performed by using different cell lines such as normal rat muscle and human carcinoma cells. The study demonstrates that the mine water samples have high conductivity (1.30-2.49 ms cm-1) with high total dissolved solids (1068-1339 ppm) which can change the ionic composition of water. The concentration level of trace elements are also found to be higher than the permissible limit during monsoon season. A simple laboratory-based remediation process of AMD has been carried out in the current study by using size segregated pulverized limestone and the process reveals the decrease in elemental concentrations of AMD water. This study will be useful to develop a remediation technique to minimize the concentration levels of hazardous elements and ions in the AMD water.

The Carbonaceous Aerosol Emissions, Source Apportionment and Climate Impacts (COALESCE) is a multi‐institutional Indian network project to better understand carbonaceous aerosol induced air quality and climate effects. This study presents time synchronized measurements of surface PM_2.5 concentrations made during 2019 at 11 COALESCE sites across India. The network median PM_2.5 concentration was 42 μg m⁻³ with the highest median value at Rohtak (99 μg m⁻³) and the lowest median value at Mysuru (26 μg m⁻³). The influence of six meteorological parameters on PM_2.5 were evaluated. Causality analysis suggested that temperature, surface pressure, and relative humidity were the most important factors influencing fine PM mass, on an annual as well as seasonal scale. Further, a multivariable linear regression model showed that, on an annual basis, meteorology could explain 16%–41% of PM_2.5 variability across the network. Concentration Weighted Trajectories (CWT) together with the results of causality analysis revealed common regional sources affecting PM_2.5 concentrations at multiple regional sites. Further, CWT source locations for all sites across the network correlated with the SMoG‐India emissions inventory at the 95th percentile confidence. Finally, CWT maps in conjunction with emissions inventory were used to obtain quantitative estimates of anthropogenic primary PM_2.5 sectoral shares from a mass‐meteorology‐emissions reconciliation, for all 11 pan‐India network sites. These estimates can help guide immediate source reduction and mitigation actions at the national level.

Energy conservation in brick production is crucial to achieving net-zero carbon emissions from the building sector, especially in countries with major expansions in the built environment. However, widely disparate energy consumption estimates impede benchmarking its importance relative to the steel and cement industries. Here we modelled Indian brick production and its regional energy consumption by combining a nationwide questionnaire survey on feedstock, process variables and practices with remote sensing data on kiln enumeration. We found a large underreporting in current official estimates of energy consumption, with actual energy consumption comparable to that in the steel and cement industries in the country. With a total estimated production of 233 ± 15 billion bricks per year, the brick industry consumes 990 ± 125 PJ yr⁻¹ of energy, 35 ± 6 Mt yr⁻¹ coal and 25 ± 6 Mt yr⁻¹ biomass. The main drivers of energy consumption for brick production are the kiln technology, the production capacity and the fuel mix used. The results suggest that improving operating practices would be a first step in making brick production more energy efficient.

Diesel engine railway traffic causes atmosphere pollution due to the exhaust emission which may be harmful to the passengers as well as workers. In this study, the air quality and PM₁₀ concentrations were evaluated around a railway station in Northeast India where trains are operated with diesel engines. The gaseous pollutant (e.g. SO₂, NO₂, and NH₃) was collected and measured by using ultraviolet–visible spectroscopy. The advanced level characterizations of the PM10 samples were carried out by using ion chromatography, Fourier-transform infrared, X-ray diffraction, inductively coupled plasma optical emission spectrometry , X-ray photoelectron spectroscopy, field-emission scanning electron microscopy with energy-dispersive spectroscopy, and high-resolution transmission electron microscopy with energy-dispersive spectroscopy techniques to know their possible environmental contaminants. High-performance liquid chromatography technique was used to determine the concentration of polycyclic aromatic hydrocarbons to estimate the possible atmospheric pollution level caused by the rail traffic in the enclosure. The average PM₁₀ concentration was found to be 262.11 µg m⁻³ (maximum 24 hour) which indicates poor air quality (AQI category) around the rail traffic. The statistical and air mass trajectory analysis was also done to know their mutual correlation and source apportionment. This study will modify traditional studies where only models are used to simulate the origins.