Detectability assessment of a satellite sensor for lower tropospheric ozone responses to its precursors emission changes in East Asian summer

Abstract

Satellite sensors are powerful tools to monitor the spatiotemporal variations of air pollutants in large scales, but it has been challenging to detect surface O3 due to the presence of abundant stratospheric and upper tropospheric O3. East Asia is one of the most polluted regions in the world, but anthropogenic emissions such as NOx and SO2 began to decrease in 2010s. This trend was well observed by satellites, but the spatiotemporal impacts of these emission trends on O3 have not been well understood. Recent advancement in a retrieval method for the Ozone Monitoring Instrument (OMI) sensor enabled detection of lower tropospheric O3 and its legitimacy has been validated. In this study, we investigated the statistical significance for the OMI sensor to detect the lower tropospheric O3 responses to the future emission reduction of the O3 precursor gases over East Asia in summer, by utilizing a regional chemistry model. The emission reduction of 10, 25, 50, and 90% resulted in 4.4, 11, 23, and 53% decrease of the areal and monthly mean daytime simulated satellite-detectable O3 (ΔO3), respectively. The fractions of significant areas are 55, 84, 93, and 96% at a one-sided 95% confidence interval. Because of the recent advancement of satellite sensor technologies (e.g., TROPOMI), study on tropospheric photochemistry will be rapidly advanced in the near future. The current study proved the usefulness of such satellite analyses on the lower tropospheric O3 and its perturbations due to the precursor gas emission controls.

Quantifying the Importance of Ultraviolet Radiation and Non-linear Chemistry on Surface Ozone Prediction

“…Long term average concentrations of PM 2.5 (atmospheric fine particulate matter with aerodynamic diameter less than or equal to 2.5m) in China has been observed at extremely high levels over a considerable amount of time over the last two decades, attracting widespread attention due to its harmful impacts on visibility, human health (mental and physical health), traffic safety, construction, economy , nature, and its interaction with climate (Liang et al, 2016). Previous studies have pointed out that coal combustion, motor vehicle emissions and industrial sources are major PM 2.5 sources in China, while domestic fuel burning, biomass burning, other anthropogenic emissions sources, as well as dust also contribute to PM 2.5 concentration in China as well (Cohen & Wang, 2014;Huo et al, 2011;Karagulian et al, 2015;Wang, Cohen, et al, 2021;Zhang et al, 2007). PM 2.5 comprises of inorganic sources such as sulfate, nitrate, and mineral dust, and organic sources such as organic carbon and black carbon (BC), with the portion of these components varying in degree based on the day of the year, source time, geographic region, and local meteorology, among other factors (Deng et al, 2021;Ding et al, 2016;Wang, Wang, et al, 2021).…”

“…Some instruments, such as the Nimbus Total Ozone Mapping Spectrometer (TOMS), the Aura Ozone Monitoring Instrument (Huang et al), and Global Ozone Monitoring Experiment (GOME), etc., can derive ozone amounts and its vertical profiles in the stratosphere, while in general tropospheric ozone detection is less sensitive (Bak et al, 2012;Liu et al, 2004;Martin, 2008;Miyazaki et al, 2019), due to the fact that the majority of the vertically integrated O 3 column is found in the stratosphere. At the present time, the best remote sensing can generally do for tropospheric ozone is to make observations of the lower troposphere (not only confined to the surface or the boundary layer) over highly polluted regions, in which case there still remains a large bias (of or greater than 10%) with respect to measurements (Liu et al, 2005;Kajino et al, 2019). There are also point-measurements made by upward looking O 3 LIDAR, but these results are highly limited in space and also tend to also be error prone (Steinbrecht et al, 2009;.…”

Ozone Continues to Increase in East Asia Despite Decreasing NO2: Causes and Abatements

“…Space-borne tropospheric O 3 regime identification has been carried out over large spatial areas; however, the ability to infer surface O 3 levels from these studies has been limited by the uncertainties in O 3 precursors from tropospheric column integration quantities that are based on precursor distribution probabilities [36,37]. However, with the help of sophisticated satellite retrieval algorithms, it has recently become possible to extract lower free tropospheric O 3 precursors from satellite signals [38][39][40][41][42], enabling large-scale spatiotemporal analysis of lower tropospheric O 3 concentrations.…”

Comparison of three aerosol representations of NHM-Chem (v1.0) for the simulations of air quality and climate-relevant variables

“…S1-1 in the Supplement. The offline coupled version has been used for various purposes, such as the simulation of dust vortices in the Taklimakan Desert (Yumimoto et al, 2019), the simulation of the dispersion and deposition of radionuclides due to the Fukushima nuclear accident (Kajino et al, 2019b(Kajino et al, , 2021Sekiyama and Kajino, 2020), simulation of lower-tropospheric ozone in East Asia (Kajino et al, 2019c), and the simulation of transition metals in East Asia (Kajino et al, 2020). Other meteorological models, such as the Weather Research and Forecast model (WRF; Skamarock et al, 2008), ASUCA (JMA, 2014;Aranami et al, 2015), and Scalable Computing for Advanced Library and Environment (SCALE; Nishizawa et al, 2015, can be used for offline coupled simulations (Fig.…”