Skip to main content
eScholarship
Open Access Publications from the University of California

UC Davis

UC Davis Electronic Theses and Dissertations bannerUC Davis

Trend analysis reveals distinct challenges in NOx emission controls and ozone pollution in California and a megacity in China

Abstract

Nitrogen dioxide (NO2) is a central air pollutant that is a precursor to the secondary pollutants ozone (O3) and particulate matter (PM), which together inflict significant damage to human health, agricultural productivity, biodiversity and impact the Earth’s climate. In California, a strict set of regulations targeting nitrogen oxide emissions, which go beyond national standards, have helped to achieve substantial air quality improvement in past five decades. However, these gains have been stalling suggesting the growing importance of less understood sources. In chapter 1, we present summertime (June–September) spatio-temporal patterns of NO2 concentrations using satellite and ground observations across California during 2009–2020, quantifying the differences in NO2 trends for 5 distinct land cover classes: urban, forests, croplands, scrublands (shrublands, savannas, and grasslands), and barren (minimally vegetated) lands. Over urban environments NO2 columns exhibited continued but weakening downward trends (–3.7 ± 0.3%a–1), which agree fairly well with contemporaneous trends estimated from the surface air quality network (–4.5 ± 0.5%a–1). In rural (non-urban) parts of the state, however, secular trends are insignificant (0.0 to 0.4 ± 0.4%a–1) or in the case of remote forests are on the rise (+4.2 ± 1.2%a–1). Sorting the NO2 satellite data by air temperature and soil moisture reveals relationships that are commensurate with extant parameterizations but do indicate a stronger temperature dependence. We further find that rising temperature and decreasing precipitation in response to climate change is acting to increase soil NOx emissions, explaining about one-third of the observed NO2 rise in non-urban regions across California. These trends, or their absence, can be attributed predominantly to the alarming rise in wildfire frequency, especially since the turn of the 21st century.

Unlike more than 50-years extensive anthropogenic emission reductions in the US, many regions in the East Asia start to implement emission control strategies from the past decade, and the evolution of O3 pollution in these regions follow a distinct track due to its nonlinear responses to precursor emissions. In chapter 2, we identified O3 variations and inferred trends in precursor emissions in a typical megacity (Chengdu) in southwestern China over 2013–2020 based on ambient measurements, emission inventory, and satellite data. Numerical models were used to investigate the changes in meteorological variability and biogenic emissions. Trends of O3 in urban areas show deterioration (+14.0%a–1) between 2013 and 2016 followed by a slight decrease over 2017–2020, while O3 levels in rural areas generally show a downward trend (–2.9%a–1) during 2014–2020. Both emission inventory (–3.7%a–1) and OMI satellite columns (–4.5%a–1) depict strong decline trends in NOx emissions, while satellite HCHO columns exhibit a flattened downward trend of VOC emissions (–1.8%a–1), which caused rural areas shifted from VOCs-limited to transitional or NOx-limited regime since 2016. Considering metropolitan Chengdu remains VOCs-limited regime over time, the existing regulatory framework involving simultaneous NOx and VOCs control would result in evident O3 improvements in the near future. Despite benefits from anthropogenic emission reductions, we demonstrate that meteorological conditions and enhanced biogenic emissions over the warm season could partially or even fully offset effects attributed to emission changes, making the net effects obscure. This chapter informs effective O3 mitigation policies for megacities in East Asia which undergo similar emission pathways in Chengdu.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View