Effects of El Niño on summertime ozone air quality in the eastern United States

Impacts of projected changes in sea surface temperature on ozone pollution in China toward carbon neutrality

The global sea surface temperatures (SSTs) are expected to change diversely in the future under different climate scenarios, which will affect the near-surface ozone (O3) distribution and concentration by influencing meteorological states and large-scale atmospheric circulation. Many countries have planned to reach carbon neutrality by the mid-21st century. In this study, the impacts of global and regional SST changes on near-surface O3 concentrations in China in the middle of the 21st century under the carbon-neutral scenario (Shared Socioeconomic Pathway 1-1.9), compared with the high-emission scenario (Shared Socioeconomic Pathway 5-8.5), and possible physical and chemical mechanisms are investigated using the Community Earth System Model version 1 (CESM1). Under future climate change, the changes in SSTs in the carbon-neutral scenario relative to the high-emission scenario lead to a dipole change in near-surface O3 concentrations in eastern and western China, with a significant decrease of 0.79 ppbv in the eastern China and a significant increase of 1.05 ppbv in the western China. The cooling of North Pacific Ocean under the carbon-neutral scenario causes a decrease in near-surface O3 concentrations by 0.48 ppbv in eastern China due to the weakened chemical production and an increase by 0.74 ppbv in western China attributed to the enhanced O3 transport from Eurasia. Cooling of Southern Hemisphere oceans leads to anomalous upward air motions over eastern China, which weaken the vertical transport of high-elevation O3 to the surface, resulting in a reduction in near-surface O3 concentrations by 0.58 ppbv in eastern China. Our results suggest that future changes in SSTs in the carbon-neutral scenario will positively benefit O3 air quality improvement in the polluted eastern China, with the North Pacific and Southern Hemisphere oceans playing important roles.

Influences of El Niño-Southern Oscillation on summertime ozone pollution over central-eastern China during 1950-2014

Summertime ozone pollution has become increasingly severe over many parts of China in recent years. Due to lack of historical ozone observations, few studies have analyzed the linkage between natural climate variability and ozone levels for a long time series. This study uses the simulation datasets from CMIP6 to explore the effects of El Niño-Southern Oscillation (ENSO) on summertime (June/July/August) surface ozone concentrations in central-eastern China (CEC; 20°N-42°N, 100°E-123°E) during the period of 1950-2014. Our results show that, after excluding the emission-related trend, the detrended summertime daily mean surface ozone concentrations averaged over CEC in El Niño years (30.69 ppb) are higher than those in La Niña events (29.34 ppb). Compared to the summertime mean ozone of 1950-2014 (30.25 ppb), the maximum anomalies in CMIP6 are 2.88 ppb (9.52% higher) and - 5.52 ppb (18.25% lower) in El Niño and La Niña years, respectively. In addition, the summertime MDA8 ozone of CEC is significantly correlated with the central-eastern equatorial Pacific SST (5°N-5°S, 170°W-120°W) (R = 0.29, P-value = 0.02). Such ozone increases/declines in El Niño/La Niña years are also found in satellite observations of OMI ozone. The results show that the ENSO affects the large-scale circulations over central-eastern China, which regulate the regional atmospheric stability and meteorological conditions (including horizontal wind fields, geopotential height, vertical velocity, surface air temperature, and precipitation) to influence the efficiency of ozone photochemical formation and transport. Our study makes better estimation and attribution of future surface ozone pollution in China.

Satellite-Based Long-Term Spatiotemporal Patterns of Surface Ozone Concentrations in China: 2005-2019

BACKGROUND

Although short-term ozone (O3) exposure has been associated with a series of adverse health outcomes, research on the health effects of chronic O3 exposure is still limited, especially in developing countries because of the lack of long-term exposure estimates.

OBJECTIVES

The present study aimed to estimate the spatiotemporal distribution of monthly mean daily maximum 8-h average O3 concentrations in China from 2005 to 2019 at a 0.05° spatial resolution.

METHODS

We developed a machine learning model with a satellite-derived boundary-layer O3 column, O3 precursors, meteorological conditions, land-use information, and proxies of anthropogenic emissions as predictors.

RESULTS

The random, spatial, and temporal cross-validation R2 of our model were 0.87, 0.86, and 0.76, respectively. Model-predicted spatial distribution of ground-level O3 concentrations showed significant differences across seasons. The highest summer peak of O3 occurred in the North China Plain, whereas southern regions were the most polluted in winter. Most large urban centers showed elevated O3 levels, but their surrounding suburban areas may have even higher O3 concentrations owing to nitrogen oxides titration. The annual trend of O3 concentrations fluctuated over 2005-2013, but a significant nationwide increase was observed afterward.

DISCUSSION

The present model had enhanced performance in predicting ground-level O3 concentrations in China. This national data set of O3 concentrations would facilitate epidemiological studies to investigate the long-term health effect of O3 in China. Our results also highlight the importance of controlling O3 in China's next round of the Air Pollution Prevention and Control Action Plan. https://doi.org/10.1289/EHP9406.