[1] Simultaneous measurements of near-surface ozone, NO x (NO + NO 2 ), and meteorological parameters were carried out at the tropical coastal location of Trivandrum (8.55°N, 77°E) in India from November 2007 to May 2009. The data have been used to investigate the diurnal and seasonal patterns of ozone and its precursor, NO x , and also the interdependence of these two chemical species. The diurnal pattern is found to be closely associated with the mesoscale circulation (sea breeze and land breeze) and the availability of NO x . The daytime peak in ozone extends until the onset of land breeze, which brings in NO x for titration of ozone. Near-surface ozone concentration reaches peak values during the postmonsoon or winter months and shows minima during the summer or monsoon season. The high ozone concentration during winter is due to the presence of northeasterly winds that transport precursor gases to the site. The daytime concentration of ozone is found to be directly linked to the nighttime level of NO x . The present analysis reveals that one molecule of NO x or NO 2 is responsible for the formation of about seven to nine molecules of ozone. A study of satellite-derived tropospheric ozone and total ozone has shown that tropospheric ozone contributes 8%-15% of total ozone over this site and near-surface ozone contributes 34%-83% of tropospheric ozone. The seasonal pattern of tropospheric column ozone is similar to that of tropospheric NO 2 .Citation: David, L. M., and P. R. Nair (2011), Diurnal and seasonal variability of surface ozone and NO x at a tropical coastal site: Association with mesoscale and synoptic meteorological conditions,

Tropospheric aerosol optical depth (AOD) over India was simulated by Goddard Earth Observing System (GEOS)‐Chem, a global 3‐D chemical‐transport model, using SMOG (Speciated Multi‐pOllutant Generator from Indian Institute of Technology Bombay) and GEOS‐Chem (GC) (current inventories used in the GEOS‐Chem model) inventories for 2012. The simulated AODs were ~80% (SMOG) and 60% (GC) of those measured by the satellites (Moderate Resolution Imaging Spectroradiometer and Multi‐angle Imaging SpectroRadiometer). There is no strong seasonal variation in AOD over India. The peak AOD values are observed/simulated during summer. The simulated AOD using SMOG inventory has particulate black and organic carbon AOD higher by a factor ~5 and 3, respectively, compared to GC inventory. The model underpredicted coarse‐mode AOD but agreed for fine‐mode AOD with Aerosol Robotic Network data. It captured dust only over Western India, which is a desert, and not elsewhere, probably due to inaccurate dust transport and/or noninclusion of other dust sources. The calculated AOD, after dust correction, showed the general features in its observed spatial variation. Highest AOD values were observed over the Indo‐Gangetic Plain followed by Central and Southern India with lowest values in Northern India. Transport of aerosols from Indo‐Gangetic Plain and Central India into Eastern India, where emissions are low, is significant. The major contributors to total AOD over India are inorganic aerosol (41–64%), organic carbon (14–26%), and dust (7–32%). AOD over most regions of India is a factor of 5 or higher than over the United States.

The annual premature mortality in India attributed to exposure to ambient particulate matter (PM 2.5 ) exceeds 1 million (Cohen et al., 2017(Cohen et al., , https://doi.org/10.1016. Studies have estimated sector-specific premature mortality from ambient PM 2.5 exposure in India and shown residential energy use is the dominant contributing sector. In this study, we estimate the contribution of PM 2.5 and premature mortality from six regions of India in 2012 using the global chemical-transport model. We calculate how premature mortality in India is determined by the transport of pollution from different regions. Of the estimated 1.1 million annual premature deaths from PM 2.5 in India, about~60% was from anthropogenic pollutants emitted from within the region in which premature mortality occurred,~19% was from transport of anthropogenic pollutants between different regions within India,~16% was due to anthropogenic pollutants emitted outside of India, and~4% was associated with natural PM 2.5 sources. The emissions from Indo Gangetic Plain contributed to~46% of total premature mortality over India, followed by Southern India (13%). Indo Gangetic Plain also contributed (~8%) to the most premature mortalities in other regions of India through transport. More than 50% of the premature mortality in Northern, Eastern, Western, and Central India was due to transport of PM 2.5 from regions outside of these individual regions. Our results indicate that reduction in anthropogenic emissions over India, as well as its neighboring regions, will be required to reduce the health impact of ambient PM 2.5 in India.

Urban outdoor air pollution in the developing world, mostly due to particulate matter with diameters smaller than 2.5 µm (PM2.5), has been highlighted in recent years. It leads to millions of premature deaths. Outdoor air pollution has also been viewed mostly as an urban problem. We use satellite-derived demarcations to parse India’s population into urban and nonurban regions, which agrees with the census data. We also use the satellite-derived surface PM2.5 levels to calculate the health impacts in the urban and nonurban regions. We show that outdoor air pollution is just as severe in nonurban regions as in the urban regions of India, with implications to monitoring, regulations, health, and policy.

[1] Studies on the solar eclipse-induced changes in near-surface ozone and its precursors NO x and CO were carried out at two nearby tropical coastal locations, Thumba (very close to the sea) and the Centre for Earth Science Studies (CESS), which is 4.5 km off the Thumba coast and with varying topography, during the annular eclipse of 15 January 2010. The surface ozone decreased by 12 and 13 ppb (35% and 52%) over Thumba and CESS, with the time lag of 40 min and 25 min from the maximum phase of eclipse, respectively, and at CESS, post-eclipse recovery was faster compared to Thumba. No pronounced change was observed in NO x , but CO showed an enhancement toward the ending phase of the eclipse. The diurnal patterns of ozone and their differences at the two sites were strongly dependent on local meteorology, in particular, the mesoscale dynamics and topography. While the temperature decreased by 1.2°C at Thumba, the decrease was almost double ($2.1°C) at CESS. The early fall in temperature caused the early setting in of land-breeze (post-eclipse effect), which in turn triggered an early evening decrease in near-surface ozone compared to the control conditions. The present study points to the role of mesoscale meteorology/dynamics in controlling the evolution of solar eclipse-induced changes in ozone in a relatively clean environment. The chemical box model simulations reproduced these broad features: a percentage decrease and the time lag in surface ozone. The observation of total column ozone showed a decrease and fluctuations, after the eclipse maximum.

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