A real-time assessment of hazardous atmospheric pollutants across cities in China and India.

China and India are two of the fastest-growing developing economies covering about 35 % of the world's population. Due to the extensive prevalence of air pollution across cities in China and India, contemporary assessment of atmospheric pollution through real-time and remote sensing observations is inadequate. The study aims to determine the spatial distribution and temporal variation of hazardous atmospheric pollutants across cities in China (Shanghai, Nanjing, Jinan, Zhengzhou and Beijing) and India (Kolkata, Asansol, Patna, Kanpur and Delhi). Ground observation data on CO, O3, PM2.5, PM10, NO2 and SO2 along with remote sensing data on AOD, CO, O3, BC, NO2, SO2 and dust surface mass concentrations are used to assess atmospheric pollution. This study examines daily, zonal and longitudinal pollutant distributions using Sentinel-5 P data and surface mass concentrations over the vertical column evaluated from NASA satellite data. The Mann-Kendall test and relative change methods have been implemented to assess pollutant trends while Sen's Slope identifies the magnitude of change. The similarity test and data validation methods including NRMSE, PC and MBias have been employed to ensure consistency in analysing annual trends for each air pollutant in the datasets. Additionally, multiple correlation matrix analysis has been used to examine the associations among different pollutants from both datasets based on their annual averages. Remote sensing data reveals that eastern China and north-eastern India have the highest aerosol, BC, CO, NO2 and SO2 while western China and southern India lowest. Dust peaks in the west while O3 levels are highest in the northern part of China and India. Ground observation data indicates that Chinese cities have higher annual mean SO2 and O3 concentrations with yearly declines in PM2.5, PM10, NO2, SO2 and CO notably SO2. Indian cities witnessed overall increases in PM2.5, PM10, NO2 and SO2 from 2012 to 2019 with a slight decline in 2020 followed by a resurgence in 2023. The findings provide insights for implementing regional policy measures to reduce air pollution based on changes in pollutant behaviour. The study suggests that addressing atmospheric pollutants, particularly NO2, CO, PM2.5, PM10, and SO2 requires a comprehensive environmental policy framework involving central and state governments and enforcing stringent environmental protection laws.

Optimization and establishment of laboratory rearing conditions for Cimex lectularius L. against variable temperature and relative humidity.

Emerging infestations of bed bugs are affecting normal human lifestyle globally. This study has been designed to optimize the rearing conditions for Cimex lectularius L. (Hemiptera), to support the scientific research on them. Bed bugs have been projected onto three different temperature (20 °C, 25 °C, and 30 °C) and relative humidity (50%, 70%, and 90%) conditions to check their overall growth and survival rate. Adult mortality, weight loss, egg laying, percentage hatching, hatching initiation and completion, nymph mortality, and molting have been evaluated to optimize the best conditions. The temperature at 25 °C with 90% RH showed minimum mortality for adults (female 13.33 ± 3.33% and male 6.67 ± 3.33%) and nymphs (13.33 ± 3.33%), while maximum egg laying (40.33 ± 1.86), with highest percentage hatching (98.23 ± 0.58%). At 30 °C with 90% RH, hatching initiation and completion (5.19 ± 0.12 days and 7.23 ± 0.16 days) as well as molting initiation and completion (3.73 ± 0.12 days and 7.00 ± 0.24 days) were found to be fastest. Thus, it can be concluded that 25 °C with 90% RH is ideal for rearing of adults and 30 °C with 90% RH is appropriate for rapid growth of nymphs.

COVID-19's lockdown effect on air quality in Indian cities using air quality zonal modeling.

The complete lockdown due to COVID-19 pandemic has contributed to the improvement of air quality across the countries particularly in developing countries including India. This study aims to assess the air quality by monitoring major atmospheric pollutants such as AOD, CO, PM2.5, NO2, O3 and SO2 in 15 major cities of India using Air Quality Zonal Modeling. The study is based on two different data sources; (a) grid data (MODIS- Terra, MERRA-2, OMI and AIRS, Global Modeling and Assimilation Office, NASA) and (b) ground monitoring station data provided by Central Pollution Control Board (CPCB) / State Pollution Control Board (SPCB). The remotely sensed data demonstrated that the concentration of PM2.5 has declined by 14%, about 30% of NO2 in million-plus cities, 2.06% CO, SO2 within the range of 5 to 60%, whereas the concentration of O3 has increased by 1 to 3% in majority of cities compared with pre lockdown. On the other hand, CPCB/SPCB data showed more than 40% decrease in PM2.5 and 47% decrease in PM10 in north Indian cities, more than 35% decrease in NO2 in metropolitan cities, more than 85% decrease in SO2 in Chennai and Nagpur and more than 17% increase in O3 in five cities amid 43 days pandemic lockdown. The restrictions of anthropogenic activities have substantial effect on the emission of primary atmospheric pollutants.