Satellite or ground-based measurements for air pollutants (PM2.5, PM10, SO2, NO2, O3) data and their health hazards: which is most accurate and why?

Air pollution is growing at alarming rates on regional and global levels, with significant consequences for human health, ecosystems, and change in climatic conditions. The present 12 weeks (4 October 2021, to 26 December 2021) study revealed the different ambient air quality parameters, i.e., PM2.5, PM10, SO2, NO2, and O3 over four different sampling stations of Delhi-NCR region (Dwarka, Knowledge park III, Sector 125, and Vivek Vihar), India, by using satellite remote sensing data (MERRA-2, OMI, and Aura Satellite) and different ground-based instruments. The ground-based observation revealed the mean concentration of PM2.5 in Dwarka, Knowledge park III, Sector 125, and Vivek Vihar as 279 µg m-3, 274 µg m-3, 294 µg m-3, and 365 µg m-3, respectively. The ground-based instrumental concentration of PM2.5 was greater than that of satellite observations, while as for SO2 and NO2, the mean concentration of satellite-based monitoring was higher as compared to other contaminants. Negative and positive correlations were observed among particulate matter, trace gases, and various meteorological parameters. The wind direction proved to be one of the prominent parameter to alter the variation of these pollutants. The current study provides a perception into an observable behavior of particulate matter, trace gases, their variation with meteorological parameters, their health hazards, and the gap between the measurements of satellite remote sensing and ground-based measurements.

Wildfire-induced pollution and its short-term impact on COVID-19 cases and mortality in California.

Globally, wildfires have seen remarkable increase in duration and size and have become a health hazard. In addition to vegetation and habitat destruction, rapid release of smoke, dust and gaseous pollutants in the atmosphere contributes to its short and long-term detrimental effects. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has emerged as a public health concern worldwide that primarily target lungs and respiratory tract, akin to air pollutants. Studies from our lab and others have demonstrated association between air pollution and COVID-19 infection and mortality rates. However, current knowledge on the impact of wildfire-mediated sudden outburst of air pollutants on COVID-19 is limited. In this study, we examined the association of air pollutants and COVID-19 during wildfires burned during August-October 2020 in California, United States. We observed an increase in the tropospheric pollutants including aerosols (particulate matter [PM]), carbon monoxide (CO) and nitrogen dioxide (NO2) by approximately 150%, 100% and 20%, respectively, in 2020 compared to the 2019. Except ozone (O3), similar proportion of increment was noticed during the peak wildfire period (August 16 - September 15, 2020) in the ground PM2.5, CO, and NO2 levels at Fresno, Los Angeles, Sacramento, San Diego and San Francisco, cities with largest active wildfire area. We identified three different spikes in the concentrations of PM2.5, and CO for the cities examined clearly suggesting wildfire-induced surge in air pollution. Fresno and Sacramento showed increment in the ground PM2.5, CO and NO2 levels, while San Diego recorded highest change rate in NO2 levels. Interestingly, we observed a similar pattern of higher COVID-19 cases and mortalities in the cities with adverse air pollution caused by wildfires. These findings provide a logical rationale to strategize public health policies for future impact of COVID-19 on humans residing in geographic locations susceptible to sudden increase in local air pollution.

Addressing the relevance of COVID-19 pandemic in nature and human socio-economic fate.

COVID-19 or Coronavirus (SARS-COV-2) is a pandemic calamity that has locked people in their own houses. The effect of SARS-COV-2 disease has caused a decrease in the economy as businesses, transportation, aviation, and industries have been halted. Many people have died, and many are trying to survive this pandemic. As we all know, the virus of SARS-COV-2 can be transmitted through physical contact, and the government has taken up specific measures like closing up schools and colleges, closing up malls/markets/public places, and imposing lockdown in cities. It is expected that these measures can result in a decreased infection rate. On the one hand, SARS-COV-2 Has halted economic or developmental growth, but on the other hand, our nature i. e. our earth, is being provided with such conditions that it can restore its losses. Air quality has been improved in the lock down time. The emission level of different gases and particulate matters have slowed down in the Covid period. Water bodies have been clean and more transparent and propagate wildlife and fisheries. Due to the SARS-COV-2 lockdown, businesses and industries have halted, impacting the financial needs of many people around the world. The worry about surviving this pandemic and the financial crisis leads them to mental and emotional distress. This review article summarized the emergence of SARS-COV-2 disease and its role on human physical and psychological health. We also described the positive and negative effects of SARS-COV-2 on climate, environmental, and air quality with upcoming challenges for governments and populations around the world.

Heavy metal concentration and its distribution analysis in urban road dust: A case study from most populated city of Indian state of Uttarakhand.

The present work reports pollution level and spatial distribution of heavy metals (HMs) i.e. Iron (Fe), Manganese (Mn), Zinc (Zn), Copper (Cu), Lead (Pb), Chromium (Cr), Nickel (Ni), and Arsenic (As) in road dust of Dehradun city, Uttarakhand, India. Seventy samples in triplicates were collected from different land-use areas categorized as residential, commercial, national highways, and silent zones. The Concentrations of studied HMs were determined by the acid digestion method followed by inductively coupled plasma-mass spectrometry (ICP-MS). Pearson's significant correlation analysis is used to evaluate the relationship between heavy metal (HM) concentration and principal components analysis (PCA) was used for source identification of HMs in road dust. The average concentration of Mn, Zn, Cu, Pb, and Ni found higher when compared to the Indian soil background values. Among all studied HMs, Pb and Zn were found the most contaminated HMs in road dust. The degree of contamination shows the highest contamination of HMs found in commercial zones followed by National highways. The pollution load index (PLI) was found higher than 1 in all monitored 70 locations, showing the deterioration in the quality of road dust over the Dehradun city due to HMs. The principal component analysis result suggests that PC1 (Fe, Zn, Cu, and Ni) mainly comes from vehicular pollution, including tire wear and brake pad wear particles and corrosion of metallic components. PC2 (Mn and As) primarily comes from fossil fuel burning and pesticides and fertilizers containing Mn and As compounds. PC3 (Pb and Cr) mainly comes into road dust via fuel and lubrication oil residues and chrome-based paints. Spatial distribution maps of the HM concentration reveal that the city's central and eastern zone is the primary hotspot of high HM concentration, which links these zones to high vehicular volume and high population pressure.

Sensitivity of normalized difference vegetation index (NDVI) to land surface temperature, soil moisture and precipitation over district Gautam Buddh Nagar, UP, India.

This study examines the trends in MODIS/TERRA derived Normalized Difference Vegetation Index (NDVI) and its correlation with Land Surface Temperature (LST), Soil Moisture (SM), and precipitation over Gautam Buddh Nagar (India), during the period 2005-2018. The region have a sub-humid and quite moderate climate, scattered into cultivable land, forest and fast growing urbanization zone, making it suitable for monitoring vegetation trends and its accompanying factors. The NDVI-derived vegetation growth patterns over the study region of District Gautam Buddh Nagar, illustrate vigorous seasonal cycles, and interannual variations. The correlation between NDVI, and LST (- 0.45) was observed to be higher than the correlation of NDVI with SM (r = 0.43), and precipitation (r = 0.341), suggesting NDVI as more sensitive to LST as compare to SM, and precipitation, while SM shows the worthy positive correlation (r = 0.63) with the precipitation. On a seasonal basis, NDVI shows high values during winter (0.45 ± 0.02) followed by monsoon (0.44 ± 0.04), post-monsoon (0.41 ± 0.02), and pre-monsoon (0.37 ± 0.04). This study also aims to determine the phase wise status of NDVI and associated parameters.

Black carbon over a high altitude Central Himalayan Glacier: Variability, transport, and radiative impacts.

Ambient equivalent black carbon (BC) measurements spanning from June to October have been carried out over an adjoining location of Satopanth and Bhagirath-Kharak Glaciers (3858m, amsl) of Central Himalaya during the year 2019. Hourly BC varied from 12 ng m-3 to 439 ng m-3 during the entire period of observation. Monthly averaged BC values showed the highest concentration during June (230.96 ± 85.46 ng m-3) and the lowest in August (118.02 ± 71.63 ng m-3). The decrease in BC during monsoon months is attributed to limited long-range transport and rapid wet scavenging processes. Transport model studies indicate a higher retention time of tracer in Uttarakhand, Punjab, Haryana, and adjacent polluted valley regions with increased biomass burning (BB) incidences. The high rate of BC influx during June, September, and October was attributed to transport from the polluted Indo-Gangetic Plain (IGP) region, wildfires, and vehicular emissions in the valley region. Higher equivalent brown carbon (BrC) influx is linked to BB, especially wood-burning, during intense forest fires at slopes of mountains. Data obtained from limited BC observations during the 2011-19 period showed no significant BC influx change during post-monsoon. The strong correlation between BC mass and BB affirms the dominant role of BB in contributing BC to the Glacier region. Increased TOA forcing induced by surface darkening and BC atmospheric radiative heating indicate an additional warming and possible changes of the natural snow cycle over the glacier depending on the characteristics and extent of debris cover.

Strong link between coronavirus count and bad air: a case study of India.

The present study aims to highlight the contrast relationship between COVID-19 (Coronavirus Disease-2019) infections and air pollutants for the Indian region. The COVID-19 data (cumulative, confirmed cases and deaths), air pollutants (PM10, PM2.5, NO2 and SO2) and meteorological data (temperature and relative humidity) were collected from January 2020 to August 2020 for all 28 states and the union territory of India during the pandemic. Now, to understand the relationship between air pollutant concentration, meteorological factor, and COVID-19 cases, the nonparametric Spearman's and Kendall's rank correlation were used. The COVID-19 shows a favourable temperature (0.55-0.79) and humidity (0.14-0.52) over the Indian region. The PM2.5 and PM10 gave a strong and negative correlation with COVID-19 cases in the range of 0.64-0.98. Similarly, the NO2 shows a strong and negative correlation in the range of 0.64-0.98. Before the lockdown, the concentration of pollution parameters is high due to the shallow boundary layer height. But after lockdown, the overall reduction was reported up to 33.67% in air quality index (AQI). The background metrological parameters showed a crucial role in the variation of pollutant parameters (SO2, NO2, PM10 and PM2.5) and the COVID-19 infection with the economic aspects. The European Centre for Medium-Range Weather Forecasts derived monthly average wind speed was also plotted. It can see that January and February of 2020 show the least variation of air mass in the range of 1-2 m/s. The highest wind speed was reported during July and August 2020. India's western and southern parts experienced an air mass in the range of 4-8 m/s. The precipitation/wet deposition of atmospheric aerosols further improves the AQI over India. According to a study, the impact of relative humidity among all other metrological parameters is positively correlated with Cases and death. Outcomes of the proposed work had the aim of supporting national and state governance for healthcare policymakers.

Pandemic induced lockdown as a boon to the Environment: trends in air pollution concentration across India.

The present paper designed to understand the variations in the atmospheric pollutants viz. PM10, PM2.5, SO2, NO2, and CO during the COVID-19 pandemic over eight most polluted Indian cities (Mumbai, Delhi, Bangalore, Hyderabad, Lucknow, Chandigarh, Kolkata, and Ahmedabad). A significant reduction in the PM2.5 (63%), PM10 (56%), NO2 (50%), SO2 (9%), and CO (59%) were observed over Major Dhyan Chand Stadium. At Chhatrapati Shivaji International Airport, a decline of 44% in PM2.5 and 50% in PM10 was seen just a week during the initial phase of the lockdown. Gaseous pollutants (NO2, SO2 & CO) dropped up-to 36, 16, and 41%, respectively. The Air Quality Index (AQI) shows a dramatic change from 7% to 67% during observation at Chandigarh and Ballygunge during the inspection. Whereas, Ahmedabad, Worli, Income Tax Office, Talkatora, Lalbagh, and Ballygaunge have showed a significant change in AQI from 25.76% to 68.55%. However, Zoo Park, CST, Central School, and Victoria show relatively low variation in AQI in the range of 3.0% to 14.50% as compare to 2019 after lockdown. Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) analysis suggested that long range transportation of pollutants were also a part and parcel contributing to changes in AQI which were majorly coming from the regions of Iran, Afghanistan, Saudi Arabia, as well as a regional grant from Indian Gangatic plains and Delhi Non-capital region.

COVID-19 lockdowns reduce the Black carbon and polycyclic aromatic hydrocarbons of the Asian atmosphere: source apportionment and health hazard evaluation.

ABSTRACT: The entire world is affected by Coronavirus disease (COVID-19), which is spreading worldwide in a short time. India is one of the countries which is affected most, therefore, the Government of India has implemented several lockdowns in the entire country from April 25, 2020. We studied air pollutants (i.e., PM2.5, Black Carbon (BC), and Polycyclic Aromatic Hydrocarbons (PAHs) level, and observed significantly sudden reduced. In India, most of the anthropogenic activities completely stopped. Therefore, we studied the levels of BC, PAHs and PM2.5 concentrations, their sources apportion, and health risk assessment during normal days, lockdown (from lockdown 1.0 to lockdown 4.0) and unlock down 1.0 situation at Sakchi, Jamshedpur city. It was observed that lockdowns and unlock down situations BC, PAHs and PM2.5 concentrations were significantly lower than regular days. We applied the advanced air mass back trajectory (AMBT) model to locate airborne particulate matter dispersal from different directions to strengthen the new result. The diagnostic ratio analyses of BC shows that wood burning contribution was too high during the lockdown situations. However, during normal days, the PAHs source profile was dedicated toward biomass, coal burning, and vehicle emission as primary sources of PAHs. During the lockdown period, emission from biomass and coal burning was a significant contributor to PAHs. The summaries of health risk assessment of BC quantified an equal number of passively smoked cigarettes (PSC) for an individual situation was studied. This study focuses on the overall climate impact of pandemic situations.

Black carbon over a central Himalayan Glacier (Satopanth): Pathways and direct radiative impacts.

Continuous measurement of Black Carbon (BC) concentration was carried out during May-October 2018 periods over Satopanth Glacier in the central Himalayas. BC concentrations varied between 28 and 287 ngm-3 on different days during the observational period. High concentration of BC was observed in the month of May (monthly mean of 221 ± 79 ngm-3), and a lower concentration was observed in August (monthly mean of 92 ± 58 ngm-3). Biomass burning was found to contribute up to 58% of BC mass over the region, with lower contribution during June and higher during the month of May. Compensation parameter (K) values were found to vary between -0.005 and 0.005 in different months, asserting the presence of aged BC in June to October months and relatively fresh BC in the month of May. Concentration weighted trajectory (CWT) analysis showed that the air mass from Indo Gangetic Plains (IGP) was responsible for the majority of transported BC in July & August months (up to 65%) and partially in September (up to 40%). However, the transport from Middle East and far north-western regions was found to be the major contributor to BC concentrations in other months. The estimated BC direct radiative forcing was found to induce 4.5 to 7.6 Wm-2 reduction of radiation at the surface (SFC) and the forcing was +2.3 to +3.5 Wm-2 at the Top of the Atmosphere (TOA). The BC induced atmospheric heating rates were found to be up to 0.35 k day-1 over the region. The sensitivity of snow albedo to radiative forcing was studied, and it is found that BC albedo changes tend to decrease albedo with an increase in BC-snow deposition, leading to a decrease in atmospheric absorption.

Temporary reduction in air pollution due to anthropogenic activity switch-off during COVID-19 lockdown in northern parts of India.

Due to fast and deadly spread of corona virus (COVID-19), the Government of India implemented lockdown in the entire country from 25 April 2020. So, we studied the differences in the air quality index (AQI) of Delhi (DTU, Okhla and Patparganj), Haryana (Jind, Palwal and Hisar) and Uttar Pradesh (Agra, Kanpur and Greater Noida) from 17 February 2020 to 4 May 2020. The AQI was calculated by combination of individual sub-indices of seven pollutants, namely PM2.5, PM10, NO2, NH3, SO2, CO and O3, collected from the Central Pollution Control Board website. The AQI has improved by up to 30-46.67% after lockdown. The AQI slope values - 1.87, - 1.70 and - 1.35 were reported for Delhi, - 1.11, - 1.31 and - 1.04 were observed for Haryana and - 1.48, - 1.79 and - 1.78 were found for Uttar Pradesh (UP), which may be attributed to limited access of transportation and industrial facilities due to lockdown. The ozone (O3) concentration was high at Delhi because of lesser greenery as compared to UP and Haryana, which provides higher atmospheric temperature favourable for O3 formation. The air mass back trajectory (AMBT) analysis reveals the contribution of air mass from Europe, Africa and Gulf countries as well as local emissions from Indo-Gangetic Plain, Madhya Pradesh and Maharashtra states of India.

21-Day Lockdown in India Dramatically Reduced Air Pollution Indices in Lucknow and New Delhi, India.

In December 2019, the outbreak of viral disease labeled as Novel Coronavirus started in Wuhan, China, which later came to be known as Covid-19. The disease has spread in almost every part of the world and has been declared a global pandemic in March 2020 by World Health Organization (WHO). The corona virus outbreak has emerged as one of the deadliest pandemics of all time in human history. The ongoing pandemic of COVID-19 has forced several countries of the world to observe complete lockdown forcing people to live in their homes. India also faced the phase of total lockdown for 21 days (in first phase) to avoid the spread of coronavirus to the maximum possible extent. This lockdown impacted the pollution levels of environment and improved air and water quality in the short span owing to very less human activities. The present work scientifically analyzed the available data for primary air pollutants (PM2.5, NO2, SO2 and CO) from two major Indian cities, Lucknow and New Delhi. The analysis was based on air quality data for before lockdown and after lockdown (first phase of 21 days) periods of 21 days each. The results showed significant decline in the studied air pollution indices and demonstrated improvement of air quality in both the cities. The major impact was seen in the levels of PM2.5, NO2 and CO. The levels of SO2 showed less significant decline during the lockdown period. The results are presented with future perspectives to mitigate air pollution in near future by adopting the short and periodical lockdown as a tool.