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We use a 3-D regional atmospheric chemistry transport model (WRF-Chem) to examine ozone dry deposition in East Asia, which is an important but uncertain research area because of insufficient observation and numerical studies focusing on East Asia. Here we compare two widely used dry deposition parameterization schemes, the Wesely and M3DRY schemes, which are used in the WRF-Chem and Community Multiscale Air Quality (CMAQ) models, respectively. Simulated ozone dry deposition velocities with the two schemes under identical meteorological conditions show considerable differences (a factor of 2) owing to surface resistance parameterization discrepancies. Resulting ozone concentrations differ by up to 10 ppbv for a monthly mean in May when the peak ozone typically occurs in East Asia. An evaluation of the simulated dry deposition velocities shows that the Wesely scheme calculates values with more pronounced diurnal variation than the M3DRY and results in a good agreement with the observations. However, we find significant changes in simulated ozone concentrations using the Wesely scheme but with different surface type data sets, indicating the high sensitivity of ozone deposition calculations to the input data. The need is high for observations to constrain the dry deposition parameterization and its input data to improve the use of air quality models for East Asia.

Recent studies have shown that methane emissions are underestimated by inventories in many US urban areas. This has important implications for climate change mitigation policy at the city, state, and national levels. Uncertainty in both the spatial distribution and sectoral allocation of urban emissions can limit the ability of policy makers to develop appropriately focused emission reduction strategies. Top-down emission estimates based on atmospheric greenhouse gas measurements can help to improve inventories and inform policy decisions. This study presents a new high-resolution (0.02 × 0.02°) methane emission inventory for New York City and its surrounding area, constructed using the latest activity data, emission factors, and spatial proxies. The new high-resolution inventory estimates of methane emissions for the New York-Newark urban area are 1.3 times larger than those for the gridded Environmental Protection Agency inventory. We used aircraft mole fraction measurements from nine research flights to optimize the high-resolution inventory emissions within a Bayesian inversion. These sectorally optimized emissions show that the high-resolution inventory still significantly underestimates methane emissions within the New York-Newark urban area, primarily because it underestimates emissions from thermogenic sources (by a factor of 2.3). This suggests that there remains a gap in our process-based understanding of urban methane emissions.

Wildfire is a major disturbance agent in Arctic boreal and tundra ecosystems that emits large quantities of atmospheric pollutants, including PM 2.5 . Under the substantial Arctic warming which is two to three times of global average, wildfire regimes in the high northern latitude regions are expected to intensify. This imposes a considerable threat to the health of the people residing in the Arctic regions. Alaska, as the northernmost state of the US, has a sizable rural population whose access to healthcare is greatly limited by a lack of transportation and telecommunication infrastructure and low accessibility. Unfortunately, there are only a few air quality monitoring stations across the state of Alaska, and the air quality of most remote Alaskan communities is not being systematically monitored, which hinders our understanding of the relationship between wildfire emissions and human health within these communities. Models simulating the dispersion of pollutants emitted by wildfires can be extremely valuable for providing spatially comprehensive air quality estimates in areas such as Alaska where the monitoring station network is sparse. In this study, we established a methodological framework that is based on an integration of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, the Wildland Fire Emissions Inventory System (WFEIS), and the Arctic-Boreal Vulnerability Experiment (ABoVE) Wildfire Date of Burning (WDoB) dataset, an Arctic-oriented fire product. Through our framework, daily gridded surface-level PM 2.5 concentrations for the entire state of Alaska between 2001 and 2015 for which wildfires are responsible can be estimated. This product reveals the spatio-temporal patterns of the impacts of wildfires on the regional air quality in Alaska, which, in turn, offers a direct line of evidence indicating that wildfire is the dominant driver of PM 2.5 concentrations over Alaska during the fire season. Additionally, it provides critical data inputs for research on understanding how wildfires affect human health which creates the basis for the development of effective and efficient mitigation efforts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Nitrogen dioxide (NO 2 ) pollution remains a serious global problem, particularly near highly populated urbanized coasts that face increasing challenges with climate change. Yet, the combined impact of urban emissions, pollution transport, and complex meteorology on the spatiotemporal dynamics of NO 2 along heterogeneous urban coastlines remains poorly characterized. Here, we integrated measurements from different platforms - boats, ground-based networks, aircraft, and satellites - to characterize total column NO 2 (TCNO 2 ) dynamics across the land-water continuum in the New York metropolitan area, the most populous area in the United States that often experiences the highest national NO 2 levels. Measurements were conducted during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS), with a main goal to extend surface measurements beyond the coastline - where ground-based air-quality monitoring networks abruptly stop - and over the aquatic environment where peaks in air pollution often occur. Satellite TCNO 2 from TROPOMI correlated strongly with Pandora surface measurements (r = 0.87, N = 100) both over land and water. Yet, TROPOMI overall underestimated TCNO 2 (MPD = -12%) and missed peaks in NO 2 pollution caused by rush hour emissions or pollution accumulation during sea breezes. Aircraft retrievals were in excellent agreement with Pandora (r = 0.95, MPD = -0.3%, N = 108). Stronger agreement was found between TROPOMI, aircraft, and Pandora over land, while over water satellite, and to a lesser extent aircraft, retrievals underestimated TCNO 2 particularly in the highly dynamic New York Harbor environment. Combined with model simulations, our shipborne measurements uniquely captured rapid transitions and fine-scale features in NO 2 behavior across the New York City - Long Island Sound land-water continuum, driven by the complex interplay of human activity, chemistry, and local scale meteorology. These novel datasets provide critical information for improving satellite retrievals, enhancing air quality models, and informing management decisions, with important implications for the health of diverse communities and vulnerable ecosystems along this complex urban coastline., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

NASA's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011-2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea-United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO 2 ), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO 2 measurements were made, including in situ concentrations and column amounts of NO 2 using ground- and aircraft-based instruments, while NO 2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO 2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO 2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO 2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO 2 values are about a factor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori profiles) but mostly to OMI's large footprint (> 312 km 2 )., Competing Interests: Competing interests. The authors declare that they have no conflict of interest.

Using the Community Multiscale Air Quality (CMAQ) model and the Benefits Mapping and Analysis Program - Community Edition (BenMAP-CE) tool, we estimate the benefits of anthropogenic emission reductions between 2002 and 2011 in the Eastern United States (US) with respect to surface ozone concentrations and ozone-related health and economic impacts, during a month of extreme heat, July 2011. Based on CMAQ simulations using emissions appropriate for 2002 and 2011, we estimate that emission reductions since 2002 likely prevented 10- 15 ozone exceedance days (using the 2011 maximum 8-hr average ozone standard of 75 ppbv) throughout the Ohio River Valley and 5- 10 ozone exceedance days throughout the Washington, DC - Baltimore, MD metropolitan area during this extremely hot month. CMAQ results were fed into the BenMAP-CE tool to determine the health and health-related economic benefits of anthropogenic emission reductions between 2002 and 2011. We estimate that the concomitant health benefits from the ozone reductions were significant for this anomalous month: 160-800 mortalities (95% confidence interval (CI): 70-1,010) were avoided in July 2011 in the Eastern U.S, saving an estimated $1.3-$6.6 billion (CI: $174 million-$15.5 billion). Additionally, we estimate that emission reductions resulted in 950 (CI: 90-2,350) less hospital admissions from respiratory symptoms, 370 (CI: 180-580) less hospital admissions for pneumonia, 570 (CI: 0-1650) less Emergency Room (ER) visits from asthma symptoms, 922,020 (CI: 469,960-1,370,050) less minor restricted activity days (MRADs), and 430,240 (CI: -280,350-963,190) less symptoms of asthma exacerbation during July 2011. Implications : We estimate the benefits of air pollution emission reductions on surface ozone concentrations and ozone-related impacts on human health and the economy between 2002 and 2011 during an extremely hot month, July 2011, in the eastern United States (US) using the CMAQ and BenMAP-CE models. Results suggest that, during July 2011, emission reductions prevented 10-15 ozone exceedance days in the Ohio River Valley and 5-10 ozone exceedance days in the Mid Atlantic; saved 160-800 lives in the Eastern US, saving $1.3 - $6.5 billion; and resulted in 950 less hospital admissions for respiratory symptoms, 370 less hospital admissions for pneumonia, 570 less Emergency Room visits for asthma symptoms, 922,020 less minor restricted activity days, and 430,240 less symptoms of asthma exacerbation.

Surface ozone (O 3 ) was analyzed to investigate the role of the bay breeze on air quality at two locations in Edgewood, Maryland (lat: 39.4°, lon: -76.3°) for the month of July 2011. Measurements were taken as part of the first year of NASA's "Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality" (DISCOVER-AQ) Earth Venture campaign and as part of NASA's Geostationary for Coastal and Air Pollution Events Chesapeake Bay Oceanographic campaign with DISCOVER-AQ (Geo-CAPE CBODAQ). Geo-CAPE CBODAQ complements DISCOVER-AQ by providing ship-based observations over the Chesapeake Bay. A major goal of DISCOVER-AQ is determining the relative roles of sources, photochemistry and local meteorology during air quality events in the Mid-Atlantic region of the U.S. Surface characteristics, transport and vertical structures of O 3 during bay breezes were identified using in-situ surface, balloon and aircraft data, along with remote sensing equipment. Localized late day peaks in O 3 were observed during bay breeze days, maximizing an average of 3 h later compared to days without bay breezes. Of the 10 days of July 2011 that violated the U.S. Environmental Protection Agency (EPA) 8 h O 3 standard of 75 parts per billion by volume (ppbv) at Edgewood, eight exhibited evidence of a bay breeze circulation. The results indicate that while bay breezes and the processes associated with them are not necessary to cause exceedances in this area, bay breezes exacerbate poor air quality that sustains into the late evening hours at Edgewood. The vertical and horizontal distributions of O 3 from the coastal Edgewood area to the bay also show large gradients that are often determined by boundary layer stability. Thus, developing air quality models that can sufficiently resolve these dynamics and associated chemistry, along with more consistent monitoring of O 3 and meteorology on and along the complex coastline of Chesapeake Bay must be a high priority.