Application of Earth observations and chemical transport modelling to investigate air quality and health from the city to the global scale

Abstract

Ambient air pollution is responsible for 4-9 million premature deaths worldwide each year. Routine ground-based monitoring of air quality in cities is sparse and expensive and only includes a handful of pollutants. Most health risk assessment models are derived with limited health outcomes and cover a narrow range (2.4-35 µg m$^{-3}$) of fine particulate (PM$_{2.5}$) concentrations. Satellites provide daily global coverage of a dynamic range of pollutants for more than a decade and there are updated health risk assessment models that account for the increasing number of health outcomes that have been associated with air pollution and that cover a wider exposure range than previous models. In this work, the skill of satellite observations at reproducing variability in surface air quality in the UK and Indian cities was assessed. Temporal consistency (R>0.5) occurred between space-based and surface observations of nitrogen dioxide (NO$_2$) and ammonia (NH$_2$), whereas measurements of aerosol optical depth (AOD) have weak month-to-month variability (R<0.4) with surface PM$_{2.5}$, but do replicate long term trends in PM$_{2.5}$. This provided the confidence to use satellite observations to determine recent (2000s 2010s) long-term trends in NO$_2$, NH$_3$, formaldehyde (HCHO) as a marker for reactive non-methane volatile organic compounds (NMVOCs), and AOD as a marker for PM$_{2.5}$ in London and Birmingham in the UK, and Delhi and Kanpur in India. Trends in most pollutants declined in UK cities because of successful control on vehicular emissions but increased in Indian cities despite recent pollution control measures. These validated satellite observations were then used to quantify long-term trends in air quality over 46 tropical cities which are growing at an unprecedented pace (1-10 % a$^{-1}$) and that lack routine, reliable and accessible ground-based air quality measurements. Most pollutants in almost all tropical cities increased, driven almost exclusively by increase in anthropogenic activity rather than traditional biomass burning. Population exposure to hazardous pollutants PM$_{2.5}$ and NO$_2$ increased by up to 23 % a$^{-1}$ for NO$_2$ and 18 % a$^{-1}$ for PM$_{2.5}$ due to the combined increase in emerging anthropogenic air pollution and population. This suggests an impending health crisis that demands further analysis to determine the increase in health burden from increased exposure to these hazardous pollutants. This was followed by examining the health burden from exposure to PM$_{2.5}$ produced exclusively from fossil fuel combustion, a dominant and controllable anthropogenic source of PM$_{2.5}$. The health burden was estimated using the chemical transport model GEOS-Chem, validated with satellite and surface observations, and a recent meta-analysis that accounted for a wider exposure range than previous approaches. 10.2 million adult premature deaths were estimated to be from fossil fuel related PM$_{2.5}$ in 2012 with 62 % of these in China and India. These estimates are more than double than those obtained from the Global Burden of Disease and other studies because of the updated health risk assessment model and a finer spatial resolution chemical transport model. These estimates decline to 8.7 million in 2018 due to substantial decline in fossil fuel emissions in China, demonstrating the efficacy of air quality policies that target fossil fuel sources. Fossil fuel combustion can be more readily controlled than other primary and secondary sources of PM$_{2.5}$ and transitioning towards cleaner sources of energy can mitigate these premature deaths. These results highlight the immediate health crisis due to ongoing reliance on fossil fuels to complement the longer term and potentially more severe effects these will have on climate. The thesis demonstrates the application of satellite observations, ground-based measurements, chemical transport models, emission inventories and health risk assessment models and statistical techniques to determine trends and drivers of these trends in air quality in cities and estimate the health burden at different spatial scales. This is crucial information that policymakers and stakeholders require to make informed decisions and develop prescient policies