Constraining East Asia ammonia emissions through satellite observations and iterative Finite Difference Mass Balance (iFDMB) and investigating its impact on inorganic fine particulate matter.

Uncertainty in ammonia (NH) emissions causes the inaccuracy of fine particulate matter simulations, which is associated with human health. To address this uncertainty, in this work, we employ the iterative finite difference mass balance (iFDMB) technique to revise NH emissions over East Asia using the Cross-track Infrared Sounder (CRIS) satellite for July, August, and September 2019. Compared to the emissions, the revised NH emissions show an increase in China, particularly in the North China Plain (NCP) region, corresponding to agricultural land use in July, August, and September and a decrease in South Korea in September.

Large eddy simulation of sneeze plumes and particles in a poorly ventilated outdoor air condition: A case study of the University of Houston main campus.

Since the outbreak of the COVID-19 pandemic, many previous studies using computational fluid dynamics (CFD) have focused on the dynamics of air masses, which are believed to be the carriers of respiratory diseases, in enclosed indoor environments. Although outdoor air may seem to provide smaller exposure risks, it may not necessarily offer adequate ventilation that varies with different micro-climate settings. To comprehensively assess the fluid dynamics in outdoor environments and the efficiency of outdoor ventilation, we simulated the outdoor transmission of a sneeze plume in "hot spots" or areas in which the air is not quickly ventilated.

Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter.

From hourly ozone observations obtained from three regions⸻Houston, Dallas, and West Texas⸻we investigated the contributions of meteorology to changes in surface daily maximum 8-h average (MDA8) ozone from 2000 to 2019. We applied a deep convolutional neural network and Shapely additive explanation (SHAP) to examine the complex underlying nonlinearity between variations of surface ozone and meteorological factors. Results of the models showed that between 2000 and 2019, specific humidity (38% and 27%) and temperature (28% and 37%) contributed the most to ozone formation over the Houston and Dallas metropolitan areas, respectively.

The sensitivities of ozone and PM concentrations to the satellite-derived leaf area index over East Asia and its neighboring seas in the WRF-CMAQ modeling system.

Vegetation plays an important role as both a sink of air pollutants via dry deposition and a source of biogenic VOC (BVOC) emissions which often provide the precursors of air pollutants. To identify the vegetation-driven offset between the deposition and formation of air pollutants, this study examines the responses of ozone and PM concentrations to changes in the leaf area index (LAI) over East Asia and its neighboring seas, using up-to-date satellite-derived LAI and green vegetation fraction (GVF) products. Two LAI scenarios that examine (1) table-prescribed LAI and GVF from 1992 to 1993 AVHRR and 2001 MODIS products and (2) reprocessed 2019 MODIS LAI and 2019 VIIRS GVF products were used in WRF-CMAQ modeling to simulate ozone and PM concentrations for June 2019.

Changes in the ozone chemical regime over the contiguous United States inferred by the inversion of NO and VOC emissions using satellite observation.

To investigate changes in the ozone (O) chemical production regime over the contiguous United States (CONUS) with accurate knowledge of concentrations of its precursors, we applied an inverse modeling technique with Ozone Monitoring Instrument (OMI) tropospheric nitrogen dioxide (NO) and total formaldehyde (HCHO) retrieval products in the summers of 2011, 2014, and 2017, years in which United States National Emission Inventory were based. The inclusion of dynamic chemical lateral boundary conditions and lightning-induced nitric oxide emissions significantly account for the contribution of background sources in the free troposphere. Satellite-constrained nitrogen oxide (NO) and non-methane volatile organic compounds (NMVOCs) emissions mitigate the discrepancy between satellite and modeled columns: the inversion suggested 2.