Tracer-based characterization of source variations of ambient isoprene mixing ratios in a hillocky megacity, India, influenced by the local meteorology.

The ambient biogenic volatile organic compounds (BVOCs), mainly isoprene, are potentially involved in the formation of secondary pollutants, hence, they are significant in terms of air quality and climate. Although the largest sources of BVOCs are tropical regions, the measurements of isoprene in the Indian subcontinent are limited. We conducted the measurements of isoprene, benzene, and toluene at an urban site in a hillocky megacity of India using a high-sensitivity proton transfer reaction quadrupole mass spectrometer (PTR-QMS). The mixing ratios of isoprene were compared with those of aromatic compounds like benzene and toluene, which represent typical anthropogenic VOCs. Isoprene and isoprene/benzene (>5 ppbv ppbv-1) showed higher levels in the pre-monsoon months, most likely due to large emissions by urban vegetation during physiological activities in plants which was enhanced by the high ambient temperatures and solar radiation. While Benzene and toluene showed higher mixing ratios during winter, which were due to shallower boundary layer depths and transport of air masses from polluted Indo-Gangetic Plain during this season. The mixing ratios of VOCs show significant diurnal variation as a result of their different origins and the role of different meteorological parameters. The robust emission ratios of isoprene/benzene obtained from nighttime data were used to separate the non-anthropogenic and anthropogenic isoprene emissions. ∼30% enhancement observed in non-anthropogenic emissions to isoprene from winter to pre-monsoon season when temperatures and solar radiation were stronger, although traffic in the city. Isoprene/benzene ratio at lower temperatures (<25 °C) and solar radiation (<100 W m-2) was predominantly controlled by anthropogenic sources. Overall, toluene and isoprene are the most frequent species in terms of having the highest ozone-forming potential (OFP) values but biogenic isoprene became more important to ozone formation during the afternoon hours in the pre-monsoon months with high air temperatures (>25 °C).

Disparity in ozone trends under COVID-19 lockdown in a closely located coastal and hillocky metropolis of India.

The outbreak of COVID-19, a global health challenge faced by countries worldwide, led to a lockdown in India, thereby bringing down the emissions of various air pollutants. Here, we discuss the behaviour of surface ozone (O3) concentrations and its precursors, oxides of nitrogen (NOx), carbon monoxide (CO), and volatile organic compounds (VOC) at two Indian megacities namely Mumbai and Pune, closely located yet vastly differing in meteorology due to their locations. Although levels of CO, NO2, and VOC declined sharply after the lockdown in both cities, with NO2 showing the highest reduction, ozone concentration in Pune remained unaffected, whereas Mumbai exhibited a mixed trend, touching even a maximum in between the lockdown. On a diurnal scale, the magnitude of O3 levels during the lockdown period is higher at almost all hours in Mumbai, and in Pune, it is almost identical except during night hours when it is marginally higher in the lockdown period as compared to the normal period. On a whole, the pollution levels were brought down significantly which can be used as a benchmark in the future for the implementation of policies related to air quality management and emission control in Indian megacities by the policymakers. These results also can pave a way for the scientific community for local air quality modelling.

Is Meteorology a Factor to COVID-19 Spread in a Tropical Climate?

It was speculated that fewer COVID-19 infections may emerge in tropical countries due to their hot climate, but India emerged as one of the leading hotspot. There is no concrete answer on the influence of meteorological parameters on COVID-19 even after more than a year of outbreak. The present study examines the impacts of Meteorological parameters during the summer and monsoon season of 2020, in different Indian mega cities having distinct climate and geography. The results indicate the sign of association, but it varies from one climatic zone to another. The principal component analysis revealed that humidity is strongly correlated with COVID-19 infections in hillocky city Pune (R = 0.70), dry Delhi (R = 0.50) and coastal Mumbai (R = 0.46), but comparatively weak correlation is found in arid climatic city of Ahmedabad. As against the expectations, no discernible correlation is found with temperature in any of the cities. As the virus in 2020 in India largely travelled with droplets, the association with absolute humidity in the dry regions has serious implications. Clarity in understanding the impact of seasonality will greatly help epidemiological research and in making strategies to control the pandemic in India and other tropical countries around the world.

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions.

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015-2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO2 + O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.

On processes controlling fine particulate matters in four Indian megacities.

The data of most toxic particulate pollutants (PM2.5 and PM10) obtained from a dense SAFAR observational network in four Indian mega cities (Delhi, Mumbai, Pune and Ahmedabad) located in North-West part of India, not very far from each other, have been presented in this work. In spite of similar kind of sources of anthropogenic local emissions, each city has its unique air pollution footprints. The paper addresses the role of geographical location based prevailing meteorology in determining the variability of particulate matter in different seasons and processes responsible for the same. We hereby demonstrate that although Delhi has the highest level of particulate matters, the percentage share of PM2.5 in PM10 is highest for Mumbai (60%) as compared to 50% of Delhi. The pollutant levels of Delhi, Mumbai and Pune show strong seasonal variability whereas Ahmedabad does not show any significant variation for summer to winter. We have further discussed that the landlocked geography of Delhi and coastal location of Mumbai often play a dominant role in the distribution of air pollutants. Hence, the mitigation options require specific consideration of integrated approach for each city.