It is important to have reliable information on various natural and anthropogenic factors responsible for influencing and shaping stream water quality parameters as long as water resource conservation and management planning are concerned from the local to global scale. Daunting environmental pressures at multiple scales makes this necessity more pronounced owing to the special role of stream ecosystems in providing regional services. Understanding how coupled effect of natural and anthropogenic factors controls stream water quality parameters and how the relationships change over space and time will help policy makers and resource managers to target appropriate scales at watershed level for the quality management of stream waters. This paper sums up the information on various natural and anthropocentric factors as major determinants responsible for conditioning and shaping stream water quality parameters and their simultaneous influence on biota and its use.

No abstract

No abstract

A novel temperature stable alkaline protease yielding bacteria was isolated from the soils of Dachigam National Park, which is known to be inhabited by a wide variety of endemic plant and animal species of Western Himalaya. This high-potential protease producing isolate was characterized and identified as Bacillus amyloliquefaciens strain HM48 by morphological, Gram’s staining and biochemical techniques followed by molecular characterization using 16S rRNA approach. The extracellular protease of B. amyloliquefaciens HM48 was purified by precipitating with ammonium sulfate (80%), followed by dialysis and Gel filtration chromatography increasing its purity by 5.8-fold. The SDS–PAGE analysis of the purified enzyme confirmed a molecular weight of about ≈25 kDa. The enzyme displayed exceptional activity in a broad temperature range (10–90 °C) at pH 8.0, retaining its maximum at 70 °C, being the highest reported for this proteolytic Bacillus sp., with KM and Vmax of 11.71 mg/mL and 357.14 µmol/mL/min, respectively. The enzyme exhibited remarkable activity and stability against various metal ions, surfactants, oxidizing agent (H2O2), organic solvents and displayed outstanding compatibility with widely used detergents. This protease showed effective wash performance by exemplifying complete blood and egg-yolk stains removal at 70 °C and efficiently disintegrated chicken feathers making it of vital importance for laundry purpose and waste management. For functional analysis, protease gene amplification of strain HM48 yielded a nucleotide sequence of about 700 bp, which, when checked against the available sequences in NCBI, displayed similarity with subtilisin-like serine protease of B. amyloliquefaciens. The structure of this protease and its highest-priority substrate β-casein was generated through protein modeling. These protein models were validated through futuristic algorithms following which protein–protein (protease from HM48 and β-casein) docking was performed. The interaction profile of these proteins in the docked state with each other was also generated, shedding light on their finer details. Such attributes make this thermally stable protease novel and suitable for high-temperature industrial and environmental applications.

No abstract

No abstract

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.Plain Language Summary Surface PM 2.5 mass causal associations with annual and seasonal meteorology during 2019 across 11 pan-India COALESCE network locations were examined. Temperature, surface pressure and relative humidity were the most influential factors on fine PM mass concentrations. However, across the country only 16%-41% of fine PM variability was explained by meteorology on an annual basis. A fusion of trajectory ensemble methods with national emissions inventory was used for apportioning anthropogenic primary PM 2.5 at all 11 locations. Mass-meteorology-emissions associations helped identify priority sectors for source control across the country.

No abstract