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In this paper, we analyzed two decadal long term (2003–2022) data of AOD and cloud parameters to understand the spatial and temporal variations in aerosol radiative characteristics over a highly polluted urbanized region of Northern India. The aerosol and cloud data were derived at spectral wavelength of 550 nm from the MODIS based Terra/Aqua satellites. Detailed AOD quantitative analysis considering monthly, seasonal and interannual changes was investigated in relation to cloud characteristics and zonal synoptic climatic disturbances. HYSPLIT back trajectory 5-day analysis was made to know the pathways of air masses ending at Delhi region of India. Moreover, we applied Student's t-test to mean Terra AOD and cloud properties to examine and further validate the relationship of aerosol-cloud interaction over the urban tropical Delhi zone close to Himalaya range of Northern India. Results indicated that AODs were found to be increased significantly (> 68%) during the 20 years period of 2003–2022, which might be accounted to continuously increased aerosol pollution in atmosphere. On an annual basis, mean Terra AOD exhibited an increasing trend of ~ 0.0009 per year, whereas seasonal mean AOD was observed to be maximum for winter (~ 0.96) and minimum for summer (~ 0.55), respectively. The correlation coefficient was highest (+ 0.73) between AOD and precipitable water vapor, whereas lowest (− 0.46) between AOD and cloud top pressure (CTP). The findings of AOD and cloud parameters have been compared with the earlier findings made on different Indian cities. [ABSTRACT FROM AUTHOR]

To monitor the spread of the novel coronavirus (COVID-19), India, during the last week of March 2020, imposed national restrictions on the movement of its citizens (lockdown). Although India's economy was shut down due to restrictions, the nation observed a sharp decline in particulate matter (PM) concentrations. In recent years, Delhi has experienced rapid economic growth, leading to pollution, especially in urban and industrial areas. In this paper, we explored the linkages between air quality and the nationwide lockdown of the city of Delhi using a geographic information system (GIS)-based approach. Data from 37 stations were monitored from 12 March, 2020 to 2 April, 2020 and it was found that the Air Quality Index for the city was almost reduced by 37% and 46% concerning PM2.5 and PM10, respectively. The study highlights that, in regular conditions, the atmosphere's natural healing rate against anthropogenic activities is lower, as indicated by a higher AQI. However, during the lockdown, this sudden cessation of anthropogenic activities leads to a period in which the natural healing rate is greater than the induced disturbances, resulting in a lower AQI, and thus proving that this pandemic has given a small window for the environment to breathe and helped the districts of Delhi to recover from serious issues related to bad air quality. If such healing windows are incorporated into policy and decision-making, these can prove to be effective measures for controlling air pollution in heavily polluted regions of the World. [ABSTRACT FROM AUTHOR]

To reduce the pollution from the atmosphere or polluted cities like the capital city Delhi of India, use of artificial rain is a solution. In this paper, we have proposed and analyzed a nonlinear mathematical model to reduce the pollution level by rain making. In the proposed model five variables are considered, namely; (i) number density of water vapor, (ii) number density of cloud drops, (iii) number density of raindrops, (iv) cumulative concentration of aerosols, and (v) concentration of pollutant particles suspended in the region of consideration. The effect of environmental fluctuations has been studied with the help of Lyapunov functionals. The model is analyzed in the presence of white noise and proved that if rain persists, the pollutants can be totally washed out. It has been observed that the environmental disturbances are not much favorable in such experiments as the presence of environmental disturbance may destabilize the system. It is found that to remove pollutants completely, it is necessary to prevent the formation of pollutants. The simulation is performed to support the analytical findings. [ABSTRACT FROM AUTHOR]

We use a state-of-the-art regional chemistry transport model (WRF-Chem v4.2.1) to simulate particulate air pollution over northern India during September–November 2016. This period includes a severe air pollution episode marked by exceedingly high levels of hourly PM 2.5 (particulate matter having an aerodynamic diameter ≤ 2.5 µ m) during 30 October to 7 November, particularly over the wider Indo-Gangetic Plain (IGP). We provide a comprehensive evaluation of simulated seasonal meteorology (nudged by ERA5 reanalysis products) and aerosol chemistry (PM 2.5 and its black carbon (BC) component) using a range of ground-based, satellite and reanalysis products, with a focus on the November 2016 haze episode. We find the daily and diurnal features in simulated surface temperature show the best agreement followed by relative humidity, with the largest discrepancies being an overestimate of night-time wind speeds (up to 1.5 m s -1) confirmed by both ground and radiosonde observations. Upper-air meteorology comparisons with radiosonde observations show excellent model skill in reproducing the vertical temperature gradient (r>0.9). We evaluate modelled PM 2.5 at 20 observation sites across the IGP including eight in Delhi and compare simulated aerosol optical depth (AOD) with data from four AERONET sites. We also compare our model aerosol results with MERRA-2 reanalysis aerosol fields and MODIS satellite AOD. We find that the model captures many features of the observed aerosol distributions but tends to overestimate PM 2.5 during September (by a factor of 2) due to too much dust, and underestimate peak PM 2.5 during the severe episode. Delhi experiences some of the highest daily mean PM 2.5 concentrations within the study region, with dominant components nitrate (∼25 %), dust (∼25 %), secondary organic aerosols (∼20 %) and ammonium (∼10 %). Modelled PM 2.5 and BC spatially correlate well with MERRA-2 products across the whole domain. High AOD at 550nm across the IGP is also well predicted by the model relative to MODIS satellite (r≥0.8) and ground-based AERONET observations (r≥0.7), except during September. Overall, the model realistically captures the seasonal and spatial variations of meteorology and ambient pollution over northern India. However, the observed underestimations in pollutant concentrations likely come from a combination of underestimated emissions, too much night-time dispersion, and some missing or poorly represented aerosol chemistry processes. Nevertheless, we find the model is sufficiently accurate to be a useful tool for exploring the sources and processes that control PM 2.5 levels during severe pollution episodes. [ABSTRACT FROM AUTHOR]

The enormity of air pollution has always been a matter of concern due to rapid development and urbanization over a long period. The increasing level of pollutants in ambient air in 2016-2017 has deteriorated the air quality of Delhi at an alarming rate. This brought us to focus our study on air quality in Delhi region. The prediction of future air quality has been carried out by analyzing the pollutants using data analysis techniques. In our previous study, we had analyzed the data from 2011-2015. Detailed analysis from 2009-2017 of air pollutants has been proposed in this extended paper along with the critical observation of 2016-2017 air pollutants trend in Delhi. Descriptive analysis and predictive analysis have been used to study the trends of various air pollutants like sulphur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), suspended particulate matter (PM), ozone (O 3 ) carbon monoxide (CO), benzene, and forecast the future trend. We have observed through data analytics techniques that SO 2 is likely to increase by 1.24ug/m 3 , NO 2 is likely to increase by 16.77ug/m 3 , O3 is likely to increase by 6.11 mg/m 3 , benzene is likely to reduce by 1.33 mg/m 3 and NO 2 is predicted to reduce by 0.169 mg/m 3 in the coming years. [ABSTRACT FROM AUTHOR]

The alarming rate of depleting limited natural resources is forcing inhabitants of the earth to find solution to the issue on a war footing. From Rio Summit to Rio+20 Summit to other brain storming sessions at regional and local level, stakeholders are striving hard to find a solution to the ecological imbalances and ways to restore environmental degradation. Are efforts at the macro-level being percolated to the bottom of the pyramid? It is essential to identify micro-level behavioural insights including psychological and socio-cultural factors that form the fabric of any society. This study aims to capture individual consciousness in accepting such practices that lead to sustainability. The paper discusses responses of the people in the city of Delhi to the strategies adopted for regulating environmental pollution due to vehicle movements. A survey was conducted on residents of Delhi to share their opinion on Odd Even Scheme, a road rationing initiated by the Government of Delhi to bring down armingly hazardous levels of pollutional. Data were evaluated with statistical techniques. The responses were mixed and indicated that constant motivation and reinforcement were needed to bring effectiveness. However the level of social engagement due to the scheme was commendable. [ABSTRACT FROM AUTHOR]

The present study investigates the reduction in nitrogen dioxide (NO2) levels using satellite-based (Sentinel-5P TROPOMI) and ground-based (Central Pollution Control Board) observations of 2020. The lockdown duration, monthly, seasonal and annual changes in NO2 were assessed comparing the similar time period in 2019. The study also examines the role of atmospheric parameters like wind speed, air temperature, relative humidity, solar radiation and atmospheric pressure in altering the monthly and annual values of the pollutant. It was ascertained that there was a mean reduction of ~ 61% (~ 66.5%), ~ 58% (~ 51%) in daily mean NO2 pollution during lockdown phase 1 when compared with similar period of 2019 and pre-lockdown phase in 2020 from ground-based (satellite-based) measurements. April month with ~ 57% (~ 57%), summer season with ~ 48% (~ 32%) decline and an annual reduction of ~ 20% (~ 18%) in tropospheric NO2 values were observed (p < 0.001) compared to similar time periods of 2019. It was assessed that the meteorological parameters remained almost similar during various parts of the year in 2019 and 2020, indicating a negligent role in reducing the values of atmospheric pollution, particularly NO2 in the study area. It was concluded that the halt in anthropogenic activities and associated factors was mainly responsible for the reduced values in the Delhi conglomerate. Similar work can be proposed for other pollutants to holistically describe the pollution scenario as an aftermath of COVID-19-induced lockdown. [ABSTRACT FROM AUTHOR]

Open-burning of municipal solid waste (MSW) is a major source of PM emissions in developing world cities, but few studies have characterized this phenomenon at the city and intracity (neighborhood) scale relevant to human health impacts. This paper develops a consistent field method for measuring the spatial frequency of the incidence of MSW-burning and presents results in three neighborhoods of varying socioeconomic status (SES) in Delhi, India, observed in winter and summer over 2 years. Daily MSW-burning incidents ranged from 24 to 130/km²-day during winter and 5-87/km²-day during summer, with the highest intensity in low SES neighborhoods. Distinct seasonal and diurnal patterns are observed. The daily mass of MSW-burned was also estimated at 90-1170 kg/km²-day and 13-1100 kg/km²-day in highest to low SES neighborhoods, in winter and summer, respectively. The scaled-up estimate of total MSW-burned for Delhi city ranged from 190 to 246 tons/day, about 2%-3% of total generated MSW; morning-burning contributed >65% of the total. MSW composition varied systematically across neighborhoods and season. Agra had much higher MSW-burning (39-202 incidents/km²-day; 672-3485 kg/km²-day) in the summer. The field method thus captures differences in MSW-burning across cities, neighborhoods, diurnally and seasonally, important for more fine grained air pollution modeling, and for tracking/monitoring policy effectiveness on-ground. [ABSTRACT FROM AUTHOR]

Although lockdown of the industrial and transport sector and stay at home advisories to counter the COVID-19 pandemic have shown that the air quality has improved during this time, very little is known about the role of ambient air pollutants and meteorology in facilitating its transmission. This paper presents the findings from a study that was conducted to evaluate whether air quality index (AQI), three primary pollutants (PM 2.5 , PM 10 and CO), Ground level ozone (O 3) and three meteorological variables (temperature, relative humidity, wind speed) have promoted the COVID-19 transmission in five megacities of India. The results show significant correlation of PM 2.5 , PM 10 , CO, O 3 concentrations, AQI and meteorological parameters with the confirmed cases and deaths during the lockdown period. Among the meteorological variables considered, temperature strongly correlated with the COVID-19 cases and deaths during the lockdown (r = 0.54 ; 0.25) and unlock period (r = 0.66 ; 0.25). Among the pollutants, ozone, and among the meteorological variables, temperature, explained the highest variability, up to 34% and 30% respectively, for COVID-19 confirmed cases and deaths. AQI was not a significant parameter for explaining the variations in confirmed and death cases. WS and RH could explain 10–11% and 4–6% variations of COVID-19 cases. A GLM model could explain 74% and 35% variability for confirmed cases and deaths during the lockdown and 66% and 19% variability during the unlock period. The results suggest that meteorological parameters may have promoted the COVID-19 incidences, especially the confirmed cases. Our findings may encourage future studies to explore more about the role of ambient air pollutants and meteorology on transmission of COVID-19 and similar infectious diseases. [Display omitted] • During lockdown for COVID-19, air quality improved in five megacities of India. • PM 2.5 , PM 10 , CO concentration across the megacities reduced during the lockdown. • Delhi and Kolkata experienced rise in O 3 concentration during lockdown. • PM 2.5 , PM 10 , CO, O 3 , AQI and T correlated with COVID-19 confirmed cases and deaths. • Temperature explained up to 30% variability for COVID-19 cases during the lockdown. [ABSTRACT FROM AUTHOR]

The article focuses on the air pollution problem of Delhi, India, including air pollution (re)distribution inside and outside the city and policies enacted by the local government to address the issue. Topics discussed include data used to assess coverage of air pollution in the Indian city, the use of conditional autoregressive modelling to examine the impact of Land-Use and Land-Cover (LULC) types and findings that revealed small changes to LULC.