arXiv subjects

Hong Liao

Publications and source records attributed to Hong Liao.

4 recordsLinked to original sources

arXiv2025

Zeeman: A Deep Learning Regional Atmospheric Chemistry Transport Model

Atmospheric chemistry encapsulates the emission of various pollutants, the complex chemistry reactions, and the meteorology dominant transport, which form a dynamic system that governs air quality. While deep learning (DL) models have shown promise in capturing intricate patterns for forecasting individual atmospheric component - such as PM2.5 and ozone - the critical interactions among multiple pollutants and the combined influence of emissions and meteorology are often overlook. This study introduces an advanced DL-based atmospheric chemistry transport model Zeeman for multi-component atmospheric chemistry simulation. Leveraging an attention mechanism, our model effectively captures the nuanced relationships among these constituents. Performance metrics demonstrate that our approach rivals numerical models, offering an efficient solution for atmospheric chemistry. In the future, this model could be further integrated with data assimilation techniques to facilitate efficient and accurate atmospheric emission estimation and concentration forecast.

physics.ao-ph↗

arXiv2025

High-resolution geostationary satellite observations of free tropospheric NO2 over North America: implications for lightning emissions

Free tropospheric (FT) nitrogen dioxide (NO2) plays a critical role in atmospheric oxidant chemistry as a source of tropospheric ozone and of the hydroxyl radical (OH). It also contributes significantly to satellite-observed tropospheric NO2 columns, and must be subtracted when using these columns to quantify surface emissions of nitrogen oxide radicals (NOx = NO + NO2). But large uncertainties remain in the sources and chemistry of FT NO2 because observations are sparse. Here, we construct a new cloud-sliced FT NO2 (700-300 hPa) product from the TEMPO geostationary satellite instrument over North America. This product provides higher data density and quality than previous products from low Earth orbit (LEO) instruments, with the first observation of the FT NO2 diurnal cycle across seasons. Combined with coincident observations from the Geostationary Lightning Mapper (GLM), the TEMPO data demonstrate the dominance of lightning as a source of FT NO2 in non-winter seasons. Comparison of TEMPO FT NO2 data with the GEOS-CF atmospheric chemistry model shows overall consistent magnitudes, seasonality, and diurnal variation, with a midday minimum in non-winter seasons from photochemical loss. However, there are major discrepancies that we attribute to GEOS-CF's use of a standard cloud-top-height (CTH)-based scheme for the lightning NOx source. We find this scheme greatly underestimates offshore lighting flash density and misrepresents the diurnal cycle of lightning over land. Our FT NO2 product provides a unique resource for improving the lightning NOx parameterization in atmospheric models and the ability to use NO2 observations from space to quantify surface NOx emissions.

physics.ao-ph↗

arXiv2022

Large discrepancy between observations and simulations: Implications for urban air quality in China

Chemical transport models (CTMs) have been widely used to provide instructions for the control of ozone (O3) pollution. However, we find large discrepancies between observation- and model-based urban O3 chemical regimes: volatile organic compound (VOC)-limited regimes over N. China and weak nitrogen oxides (NOx)-limited regimes over S. China in observations, in contrast to simulations with widespread distributions of strong NOx-limited regimes. The conflicting O3 evolutions are caused by underestimated urban NOx concentrations and the possible overestimation of biogenic VOC emissions. Reductions in NOx emissions, in response to regulations, have thus led to an unintended deterioration of O3 pollution over N. China provinces, for example, an increase in surface O3 by approximately 7 ppb over the Sichuan Basin (SCB) in 2014-2020. The NOx-induced urban O3 changes resulted in an increase in premature mortality by approximately 3000 cases in 2015-2020.

physics.ao-ph↗

arXiv2022

Coarse particulate matter air quality in East Asia: implications for fine particulate nitrate

Coarse particulate matter (PM) is a serious air pollution problem in East Asia. Analysis of air quality network observations in the North China Plain and the Seoul Metropolitan Area shows that it is mainly anthropogenic and has decreased by 21% over 2015-2019. This anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate (PM2.5) nitrate, a major contributor to PM2.5 pollution. Including it in the GEOS-Chem model decreases simulated PM2.5 nitrate to improve agreement with observations. Decreasing anthropogenic coarse PM over 2015-2019 directly increases PM2.5 nitrate in summer, offsetting the effect of other emission controls, while in winter it increases the sensitivity of PM2.5 nitrate to ammonia and sulfur dioxide emissions. Our work implies the need for stronger ammonia and nitrogen oxides emission controls to improve PM2.5 air quality as coarse PM continues to decrease.

physics.ao-ph↗