Interpreting changes in anthropogenic emissions underlying abrupt changes in observed air quality using surface and satellite observations and a chemical transport model

Lu, Gongda (2022). Interpreting changes in anthropogenic emissions underlying abrupt changes in observed air quality using surface and satellite observations and a chemical transport model. University of Birmingham. Ph.D.

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Abstract

Effective air quality policy is hindered by inaccurate estimates of precursor emissions, unvalidated, sparse or absent monitoring networks, and uncertain formation pathways of air pollution. Of particular concern are regions with severe air pollution, such as northern China and, large cities in South and Southeast Asia, and large cities in the world with high anthropogenic emissions. This work makes use of field campaign measurements, reference network measurements, satellite observations and a chemical transport model (CTM) to address these knowledge gaps in these regions.
In the Beijing-Tianjin-Hebei region (BTH) in northern China, the Chinese government implemented strict emission control measures in autumn-winter 2017/2018 to address fine particulate matter (PM2.5) pollution. PM2.5 reduction targets were met, so these controls are now adopted in other parts of China, even though the relative role of emission controls and meteorology was not assessed. Surface observations of air quality from monitoring networks (validated against field campaign measurements) and the GEOS-Chem CTM were used after addressing large biases in the regional bottom-up anthropogenic emission inventory for China. According to the model, emission controls accounted for less than half (at most 43%) the decline in total PM2.5 while most (57%) was due to interannual variability in meteorology. Specifically, a deeper planetary boundary layer, stronger winds, and lower relative humidity during the emission control period. Emission controls alone would not achieve the PM2.5 reduction targets of 15-25% in this region.
Cities in South and Southeast Asia are developing rapidly, but routine, up-to-date and publicly available inventories of emissions are lacking for this region. Nitrogen oxides (NOx) emissions in cities are important precursors to health-hazardous PM2.5 and tropospheric ozone (O3) where it is a greenhouse gas. NOx lifetimes and emissions over 10 large cities in South and Southeast Asia in 2019 were obtained by applying an exponentially modified Gaussian (EMG) approach with a wind rotation technique to the nitrogen dioxide (NO2) tropospheric vertical column densities (VCDs) from the high spatial resolution TROPOspheric Monitoring Instrument (TROPOMI). Annual averaged NOx emissions range from < 50 mol s-1 for Karachi, Ahmedabad, Mumbai, Lahore and Chennai, 50-100 mol s-1 for Manila and Jakarta, and > 100 mol s-1 for Delhi, Dhaka and Singapore. This is comparable to the range of emissions estimates for polluted cities in China. Bottom-up NOx emissions from a widely used publicly available global inventory exceed the top-down estimates for most cities. The discrepancy is >100% for Chennai, Singapore and Jakarta. It was only possible to estimate top-down monthly NOx estimates for 3 cities, due to issues with the line density fitting parameters at these fine temporal scales. These ranged from 63 to 148 mol s-1 for Singapore (annual mean 114 mol s-1), 44 to 109 mol s-1 for Jakarta (68 mol s-1), and 26 to 67 mol s-1 for Manila (53 mol s-1). Month-to-month variability is absent in the bottom-up emission estimates. The discrepancies identified in this work need to be resolved to ensure the development of effective policies.
Abrupt changes in air quality during COVID-19 lockdowns presented an opportunity to investigate changes in observed PM2.5, NOx and O3 pollution due to interventions. Surface observations of air quality in 11 cities worldwide were analysed. Observed NO2 decreased substantially at urban background and roadside sites in all the cities, by 10-60% at urban background sites, and by 29 53% at roadside sites. In contrast, observed O3 increased in all cities after the lockdowns, by 16-167% at urban background sites and by 20-156% at roadside sites. The percentage changes in observed PM2.5 are -39 to 153% at urban background sites, -41 to 108% at roadside sites, and -34 to 165% at rural sites. But by comparing observations in 2020 to those in 2016-2019 during the equivalent periods, results here demonstrated that the observations of air quality alone cannot represent the changes in emissions due to COVID-19 lockdowns as the impact of meteorology should be considered.
Findings in this thesis demonstrate the application of observations from multiple platforms, innovative analytical techniques, and an advanced chemical transport model to abrupt changes in air quality in time and space to better understand air pollution precursor emissions and formation pathways and to interpret the relative contribution from changes in emissions and meteorology. Such information is vital for developing well-informed environmental policies.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):