Health Risk Appraisal Associated with Air Quality over Coal-Fired Thermal Power Plants and Coalmine Complex Belts of Urban-Rural Agglomeration in the Eastern Coastal State of Odisha, India

Manufacturing and mining sectors are serious pollution sources and risk factors that threaten air quality and human health. We analyzed pollutants at two study sites (Talcher and Brajrajnagar) in Odisha, an area exposed to industrial emissions, in the pre-COVID-19 year (2019) and consecutive pandemic years, including lockdowns (2020 and 2021). We observed that the annual data for pollutant concentration increased at Talcher: PM2.5 (7-10%), CO (29-35%), NO2 and NOx (8-57% at Talcher and 14-19% at Brajrajnagar);while there was slight to substantial increase in PM10 (up to 11%) and a significant increase in O3 (41-88%) at both sites. At Brajrajnagar, there was a decrease in PM2.5 (up to 15%) and CO (around half of pre-lockdown), and a decrease in SO2 concentration was observed (30-86%) at both sites. Substantial premature mortality was recorded, which can be attributed to PM2.5 (16-26%), PM10 (31-43%), NO2 (15-21%), SO2 (4-7%), and O3 (3-6%). This premature mortality caused an economic loss between 86-36 million USD to society. We found that although lockdown periods mitigated the losses, the balance of rest of the year was worse than in 2019. These findings are benchmarks to manage air quality over Asia's largest coalmine fields and similar landscapes.

Establishing a link between fine particulate matter (PM2.5) zones and COVID -19 over India based on anthropogenic emission sources and air quality data.

The spread of coronavirus disease of 2019 (COVID-19) pandemic around the globe is affecting people. The majority of Indian urban complexes are reeling under high emissions of deadly fine particulate matter PM2.5 and resulting in poor air quality. These fine particles penetrate deep into the body and fuel inflammation in the lungs and respiratory tract, leading to the risk of having cardiovascular and respiratory problems, including a weak immune system. In the present study, we report the first national-scale study over India, which establishes a strong relationship between the PM2.5 emission load and COVID-19 infections and resulting deaths. We find a significant correlation (R2 = 0.66 & 0.60) between the states as well as districts having varied levels of PM2.5 emissions with corresponding COVID-19 positive cases respectively, and R2 = 0.61 between wavering air quality on a longer time scale and the number of COVID-19 related deaths till 5 November 2020. This study provides practical evidence that cities having pollution hotspot where fossil fuel emissions are dominating are highly susceptible to COVID-19 cases.

On modelling growing menace of household emissions under COVID-19 in Indian metros.

While local anthropogenic emission sources contribute largely to deteriorate metro air quality, long range transport can also play a significant role in influencing levels of pollutants, particularly carbon monoxide (CO) that has a relatively long life span. A nationwide lockdown of two months imposed across India amid COVID-19 led to a dramatic decline in major sources of emissions except for household, mainly from cooking. This initially led to declined levels of CO in two of the largest megacities of India, Delhi and Mumbai under stable weather conditions, followed by a distinctly different variability under the influence of prevailing mesoscale circulation. We hereby trace the sources of CO from local emissions to transport pathways and interpret the observed variability in CO using the interactive WRF-Chem model and back trajectory analysis. For this purpose, COVID-19 emission inventory of CO has been estimated. Model results indicate a significant contribution from externally generated CO in Delhi from surrounding regions and an unusual peak on 17th May amid lockdown due to long range transport from the source region of biofuel emissions in central India. However, the oceanic winds played a larger role in keeping CO levels in check in a coastal megacity Mumbai which otherwise has high CO emissions from household sources due to a larger share of urban slums. Keeping track of evolving carbon-intensive pathways can help inform government responses to the COVID-19 pandemic to prioritize controls of emissions sources.

Significant change in air quality parameters during the year 2020 over 1st smart city of India: Bhubaneswar.

Prevention of Coronavirus results in lockdown in India from 24 March 2020 to 31 May 2020. Eastern India, which is having a dense cluster of coal-fired power plants and home to many mines, mineral industries, has not shutdown power plants and coal mines during this lockdown period, though other industrial and vehicular emissions were almost zero. The present study attempts to find the change in various atmospheric pollutants during this lockdown period over an eastern tropical Indian station-Bhubaneswar, which is the first smart city proposed in smart city mission of Government of India. The study analyses hourly concentrations of PM2.5, PM10, NO X , O3, and CO for March-May 2019 and 2020. The study shows a significant increase (rather than decrease) in PM2.5 and PM10, increase in O3 and a decrease in CO and NO X during the lockdown period. Results are advocating the impact of transported pollution over the study area for maintaining the PM2.5 and PM10 values even during the lockdown situation.

Spatial and temporal variations of air pollution over 41 cities of India during the COVID-19 lockdown period.

In this study, we characterize the impacts of COVID-19 on air pollution using NO2 and Aerosol Optical Depth (AOD) from TROPOMI and MODIS satellite datasets for 41 cities in India. Specifically, our results suggested a 13% NO2 reduction during the lockdown (March 25-May 3rd, 2020) compared to the pre-lockdown (January 1st-March 24th, 2020) period. Also, a 19% reduction in NO2 was observed during the 2020-lockdown as compared to the same period during 2019. The top cities where NO2 reduction occurred were New Delhi (61.74%), Delhi (60.37%), Bangalore (48.25%), Ahmedabad (46.20%), Nagpur (46.13%), Gandhinagar (45.64) and Mumbai (43.08%) with less reduction in coastal cities. The temporal analysis revealed a progressive decrease in NO2 for all seven cities during the 2020 lockdown period. Results also suggested spatial differences, i.e., as the distance from the city center increased, the NO2 levels decreased exponentially. In contrast, to the decreased NO2 observed for most of the cities, we observed an increase in NO2 for cities in Northeast India during the 2020 lockdown period and attribute it to vegetation fires. The NO2 temporal patterns matched the AOD signal; however, the correlations were poor. Overall, our results highlight COVID-19 impacts on NO2, and the results can inform pollution mitigation efforts across different cities of India.