The coronavirus disease (COVID-19) created enormous pressure across the globe due to an increasing number of COVID-19 infected cases. All the governments’ primary focus is to save humanity from this pandemic problem, and they have lockdown almost the entire nation to stop the spread of infection. This lockdown resulted in a considerable impact on the global as well as a local economy that will take a long time to perform with business as usual scenario. However, improvement in the air quality of the cities across the globe has emerged as a key benefit of this lockdown. Therefore, this study aims to assess the overall impact of social and travel lockdown in five megacities of India; Delhi, Mumbai, Chennai, Kolkata, and Bangalore. The study evaluated the spatiotemporal variations in five criteria pollutants over two time periods, i.e., March–April 2019 and March–April 2020 and 10th–20th March 2020 (before lockdown) and 25th March to 6th April 2020 (during lockdown). The results highlighted a statistically significant decline in all the pollutants in all the megacities except for ozone. It was observed that the concentration of PM2.5, PM10, NO2 and CO declined by ~41% (66–39 µg m–3), ~52% (153–73 µg m–3), ~51% (39–19 µg m–3) and ~28% (0.9–0.65 mg m–3) during the lockdown phase in comparison to the before lockdown in Delhi, respectively. Similar decline in pollutant concentration was observed in other megacities as well. Further, the study conducted an expert survey to identify the possible challenges India might face after lockdown is over. All the experts said that reviving the economy will be a big challenge for the government, and it may result in some tradeoff while managing the air quality in the near future due to scarcity of funds, etc.

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Social and travel lockdown impact considering coronavirus disease (Covid-19) on air quality in megacities of india: Present benefits, future challenges and way forward

https://www.nber.org/system/files/working_papers/w23991/w23991.pdf

Temperature Effects on Productivity and Factor Reallocation: Evidence from a Half Million Chinese Manufacturing Plants

. Reduced visibility is an indicator of poor air quality. Moreover, degradation in visibility can be hazardous to human safety; for example, low visibility can lead to road, rail, sea and air accidents. In this paper, we explore the combined influence of atmospheric aerosol particle and gas characteristics, and meteorology, on long-term visibility. We use visibility data from eight meteorological stations, situated in the UK, which have been running since the 1950s. The site locations include urban, rural and marine environments. Most stations show a long-term trend of increasing visibility, which is indicative of reductions in air pollution, especially in urban areas. Additionally, the visibility at all sites shows a very clear dependence on relative humidity, indicating the importance of aerosol hygroscopicity on the ability of aerosol particles to scatter radiation. The dependence of visibility on other meteorological parameters, such as wind speed and wind direction, is also investigated. Most stations show long-term increases in temperature which can be ascribed to climate change, land-use changes (e.g. urban heat island effects) or a combination of both; the observed effect is greatest in urban areas. The impact of this temperature change upon local relative humidity is discussed. To explain the long-term visibility trends and their dependence on meteorological conditions, the measured data were fitted to a newly developed light-extinction model to generate predictions of historic aerosol and gas scattering and absorbing properties. In general, an excellent fit was achieved between measured and modelled visibility for all eight sites. The model incorporates parameterizations of aerosol hygroscopicity, particle concentration, particle scattering, and particle and gas absorption. This new model should be applicable and is easily transferrable to other data sets worldwide. Hence, historical visibility data can be used to assess trends in aerosol particle properties. This approach may help constrain global model simulations which attempt to generate aerosol fields for time periods when observational data are scarce or non-existent. Both the measured visibility and the modelled aerosol properties reported in this paper highlight the success of the UK's Clean Air Act, which was passed in 1956, in cleaning the atmosphere of visibility-reducing pollutants.

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60 years of UK visibility measurements: impact of meteorology and atmospheric pollutants on visibility

Meteorological parameters play a significant role in affecting ambient air quality of an urban environment. As Dhaka, the capital city of Bangladesh, is one of the air pollution hotspot among the megacities in the world, however the potential meteorological influences on criteria air pollutants for this megacity are remained less studied. The objectives of this research were to examine the relationships between meteorological parameters such as daily mean temperature (o C), relative humidity (%) and rainfall (mm) and, the concentration of criteria air pollutants (SO2, CO, NOx, O3, PM2.5 and PM10) from January, 2013 to December, 2017. This study also focused on the trend analysis of the air pollutants concentration over the period. Spearman correlation was applied to illustrate the relationships between air pollutants concentration and temperature, relative humidity and rainfall.  Multiple linear and non-linear regressions were compared to explore potential role of meteorological parameters on air pollutants' concentrations. Trend analysis resulted that concentration of SO2 is increasing in the air of Dhaka while others are decreasing. Most of the pollutants resulted negative correlation with atmospheric temperature and relative humidity, however, they showed variable response to seasonal variation of meteorological parameters. Regression analysis resulted that both the multiple non-linear and linear model performed similar for predicting concentrations of particulate matters but for gaseous pollutants both model performances were poor. This research is expected to contribute in improving the forecast accuracy of air pollution under variable meteorological parameters considering seasonal fluctuations.

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The relationships between meteorological parameters and air pollutants in an urban environment

Levels of urban pollution can be influenced largely by meteorological conditions and the topography of the area. The impact of the relative humidity (RH) on the daily average PM2.5 concentrations was studied at several sites in a mid-size South American city at a high elevation over the period of nine years. In this work, we show that there is a positive correlation between daily average urban PM2.5 concentrations and the RH in traffic-busy central areas, and a negative correlation in the outskirts of the city in more industrial areas. While in the traffic sites strong events of precipitation (≥9 mm) played a major role in PM2.5 pollution removal, in the city outskirts, the PM2.5 concentrations decreased with increasing RH independently of rain accumulation. Increasing PM2.5 concentrations are to be expected in any highly motorized city where there is high RH and a lack of strong precipitation, especially in rapidly growing and developing countries with high motorization due to poor fuel quality. Finally, two models, based on a logistic regression algorithm, are proposed to describe the effect of rain and RH on PM2.5, when the source of pollution is traffic-based vs. industry-based.

https://www.mdpi.com/2071-1050/10/6/2064/pdf

Contrasted effects of relative humidity and precipitation on urban PM2.5 pollution in high elevation urban areas

The concentration of air pollutants in ambient air is governed by the meteorological parameters such as atmospheric wind speed, wind direction, relative humidity, and temperature. This study analyses the influence of temperature and relative humidity on ambient SO2, NOx, RSPM, and SPM concentrations at North Chennai, a coastal city in India, during monsoon, post-monsoon, summer, and pre-monsoon seasons for 2010-11 using regression analysis. The results of the study show that both SO2 and NOx were negatively correlated in summer ( for SO2 and for NOx) and moderately and positively correlated ( for SO2 and for NOx) during post-monsoon season with temperature. RSPM and SPM had positive correlation with temperature in all the seasons except post-monsoon one. These findings indicate that the influence of temperature on gaseous pollutant (SO2 & NOx) is much more effective in summer than other seasons, due to higher temperature range, but in case of particulate, the correlation was found contradictory. The very weak to moderate correlations existing between the temperature and ambient pollutant concentration during all seasons indicate the influence of inconstant thermal variation in the coastal region. Statistically significant negative correlations were found between humidity and particulates (RSPM and SPM) in all the four seasons, but level of correlation was found moderate only during monsoon ( and ) in comparison with other three seasons and no significant correlation was found between humidity and SO2, NOx in all the seasons. It is suggested from this study that the influence of humidity is effective on subsiding particulates in the coastal region.

/pdf/influence-of-temperature-relative-humidity-and-seasonal-29kdutzmzm.pdf

B. Kumaravel

Papers

Influence of Temperature, Relative Humidity and Seasonal Variability on Ambient Air Quality in a Coastal Urban Area