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At least 343 records · Page 19

Washington Health & Air Quality: Quantifying Air Quality Parameters and Validating Air Pollution Sources Impacting the Health of Puget Sound Residents Through the Use of NASA and ESA Remote Sensing Data

In the Puget Sound region of Washington, high levels of air pollutants put residents’ health at risk by increasing their likelihood of developing critical respiratory conditions. This project used remotely-sensed data to investigate aerosol optical depth (AOD) from NASA satellite sensors including the Terra and Aqua MODerate resolution Imaging Spectroradiometer (MODIS) and European Space Agency Copernicus Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI). The team visualized the most recent data in Google Earth Engine (GEE) API to display air pollution trends from Northern California to British Columbia, which will support the Puget Sound Clean Air Agency’s (PSCAA) decision-making processes. The team performed linear regressions using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to form a relationship between ground-level microscopic particles (PM2.5) and AOD in the Puget Sound region, validating the relationship using concentration readings taken from Environmental Protection Agency (EPA) air quality monitors. The team utilized estimated PM2.5 and other satellite data to produce a web-based tool and to evaluate the effectiveness of using such a tool for near real-time air quality monitoring within a particular region. The team found that the tool provides useful supplementary data that fills in the gaps of the PSCAA’s air monitoring network.

Health & Air Quality↗

Causes of Model Biases in Simulating Inorganic Aerosol Composition During KORUS-AQ and Implications for the Estimate of Transboundary Pollution

East Asia is a region of increasing economic growth which has led to severe PM2.5 pollution in urban areas. The joint NASA-NIER Korea-United States Air Quality (KORUS-AQ) field campaign in May-June 2016 provided an extensive dataset of ground, airborne, and remote sensing observations to test model simulations of PM2.5 pollution transport and potential control measures. During KORUS-AQ, a period of haze was observed in which PM2.5 rapidly increased to the highest levels observed during the campaign. This increase is associated with increasing inorganic aerosol. While a portion of this increase is due to long-range transport, there is observational evidence that aerosol formation from local precursors was also enhanced. This suggests that domestic policy measures could have a greater than expected influence on controlling PM2.5. However, models have difficulty reproducing PM2.5 levels, particularly the composition of secondary inorganic aerosol. Models generally underestimate sulfate and overestimate nitrate and fail to represent the peak levels of PM2.5 during haze events. These biases have been chiefly attributed to errors in chemical mechanisms and model meteorology, not issues with underlying emissions inventories. Here, we use observations from KORUS-AQ interpreted by the GEOS-Chem chemical transport model to improve the model’s ability to reproduce secondary inorganic aerosol concentrations during the campaign and explore mechanisms to improve model biases during the haze event. We assess the fraction of inorganic aerosol from the improved model simulation that results from transboundary transport during KORUS-AQ and test the model sensitivity to potential emission reduction measures that could improve air quality in Seoul during different meteorological periods including haze episodes.

Katie Travis↗

Assessment of Natural and Anthropogenic Aerosol Air Pollution In the Middle East Using MERRA-2, CAMS Data Assimilation Products, and High-Resolution WRF-Chem Model Simulations

Modern-Era Retrospective analysis for Research and Applications v.2 (MERRA-2), Copernicus Atmosphere Monitoring Service Operational Analysis (CAMS-OA), and a high-resolution regional Weather Research and Forecasting model coupled with chemistry (WRF-Chem) were used to evaluate natural and anthropogenic particulate matter (PM) air pollution in the Middle East (ME) during 2015–2016. Two Moderate Resolution Imaging Spectrometer (MODIS) retrievals – combined product Deep Blue and Deep Target (MODIS-DB&DT) and Multi-Angle Implementation of Atmospheric Correction (MAIAC) – and Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) observations as well as in situ PM measurements for 2016 were used for validation of the WRF-Chem output and both assimilation products. MERRA-2 and CAMS-OA assimilate AOD observations. WRF-Chem is a free-running model, but dust emission in WRF-Chem is tuned to fit AOD and aerosol volume size distributions obtained from AERONET. MERRA-2 was used to construct WRF-Chem initial and boundary conditions both for meteorology and chemical and aerosol species. SO2 emissions in WRF-Chem are based on the novel OMI-HTAP SO2 emission dataset. The correlation with the AERONET AOD is highest for MERRA-2 (0.72–0.91), MAIAC (0.63–0.96), and CAMSOA (0.65–0.87), followed by MODIS-DB&DT (0.56–0.84) and WRF-Chem (0.43–0.85). However, CAMS-OA has a relatively high positive mean bias with respect to AERONET AOD. The spatial distributions of seasonally averaged AODs from WRF-Chem, assimilation products, and MAIAC are well correlated with MODIS-DB&DT AOD product. MAIAC has the highest correlation (R = 0.8), followed by MERRA-2 (R = 0.66), CAMS-OA (R = 0.65), and WRF-Chem (R = 0.61). WRF-Chem, MERRA-2, and MAIAC underestimate and CAMS-OA overestimates MODIS-DB&DT AOD. The simulated and observed PM concentrations might differ by a factor of 2 because it is more challenging for the model and the assimilation products to reproduce PM concentration measured within the city. Although aerosol fields in WRF-Chem and assimilation products are entirely consistent, WRF-Chem is preferable for analysis of regional air quality over the ME due to its higher spatial resolution and better SO2 emissions. The WRF-Chem’s PM background concentrations exceed the World Health Organization (WHO) guidelines over the entire ME. Mineral dust is the major contributor to PM (≈ 75%–95%) compared to other aerosol types. Near and downwind from the SO2 emission sources, non-dust aerosols (primarily sulfate) contribute up to 30% to PM(sub 2.5). The contribution of sea salt to PM in coastal regions can reach 5%. The contributions of organic matter, black carbon and organic carbon to PM over the Middle East are insignificant. In the major cities over the Arabian Peninsula, the 90th percentile of PM(sub 10) and PM(sub 2.5) (particles with diameters less than 10 and 2.5 μm, respectively) daily mean surface concentrations exceed the corresponding Kingdom of Saudi Arabia air quality limits. The contribution of the non-dust component to PM(sub 2.5) is < 25%, which limits the emission control effect on air quality. The mitigation of the dust effect on air quality requires the development of environment-based approaches like growing tree belts around the cities and enhancing in-city vegetation cover. The WRF-Chem configuration presented in this study could be a prototype of a future air quality forecast system that warns the population against air pollution hazards.

Alexander Ukhov↗

Asthma and Particulate Matter Pollution: Insights from Health Survey and Air Quality Monitoring in the Buzzard Point, Washington, DC Neighborhood

Air pollution, climate change, and other environmental factors contribute to increasing asthma in manycities, including Washington, DC. This work provides a case study of how community input, neighborhood-level health surveys, and air quality monitoring can inform the understanding of asthma and air pollution.A partnership between residents, concerned citizens, scientists, and educators has been working for envi-ronmental health in a DC neighborhood located on a major roadway, next to concrete batch plants andclose to several construction projects. A 2016 Community Health and Safety Study by the DC Departmentof Health, Office of Health Equity, recognized this particular neighborhood as more vulnerable to healthimpacts from recent construction in the area, compared with the surrounding areas, due to lower averageincome and higher percentage of seniors and children. This work presents neighborhood health surveysand air quality monitoring data at a more granular, local level than available from DC governmentagencies. The health surveys documented residents’ experiences around air pollution, asthma,and other health concerns. A key finding was evidence that asthma might be undercounted in thisneighborhood; among residents who did not indicate a diagnosis of asthma, many discussed havingsymptoms that could reflect asthma. Air quality monitoring (particulate matter [PM]) did not indicate thatfederal air quality standards have been violated. Real-time PM data, however,illustrated how current PMstandards, such as 1- and 24-hour averages, may fail to capture shorter duration high PM events that areconsistent with resident concerns.

Shizuka Hsieh↗

Delaware Basin Health and Air Quality: Spatiotemporal Analysis of Air Pollutants Collected from Ground and Space Instruments Around the Guadalupe Mountains and Carlsbad Caverns National Parks

Nitrogen dioxide (NO2) is a precursor for secondary air pollutants, which are associated with decreased visibility, and decreased ecosystem and respiratory health. NO2 is a growing threat to national parks within the Delaware Basin where nearby oil and gas activity contributes to deteriorating park conditions, implying adverse effects on the local tourism economy and public health. To demonstrate spatial and temporal patterns of air pollution in the parks, we examined average monthly, seasonal, and annual tropospheric column concentrations of NO2 in Carlsbad Caverns (CAVE) and Guadalupe Mountain (GUMO) National Parks. We used both the NASA Ozone Monitoring Instrument (OMI) and the European Space Agency (ESA) Tropospheric Monitoring Instrument (TROPOMI) to map NO2 tropospheric column densities. Using ground-based emissions values from the Environmental Protection Agency National Emissions Inventory (NEI) for two nearby natural gas processing plants (Indian Basin Gas Plant, South Carlsbad Plant), we extrapolated monthly trends from these point sources and compared seasonal emissions levels with the measurements recorded by OMI and TROPOMI. The NEI data show an 8% increase in flaring from 2013–2021. OMI measured a 38.3% NO2 increase over the Delaware Basin, 15.29% increase over CAVE, and 4.26% decrease over GUMO from 2011–2018. TROPOMI measured a -1% NO2 change over the Delaware Basin, 3% over CAVE, and 7% over GUMO from 2018–2020. The analysis indicates a positive correlation between emissions from fossil fuel exploration and NO2 concentrations above CAVE and GUMO. This information will inform National Park Service air quality monitoring and policy efforts to ensure compliance with the Clean Air Act.

Sean Cusick↗

Enabling Analysis of Air Quality Data From Tropospheric Emissions: Monitoring of POllution (Tempo) Via Cloud-Based Tools

Launched in April 2023, the Tropospheric Emissions: Monitoring of POllution (TEMPO) instrument provides high-resolution measurements of key atmospheric pollutants, such as ozone, nitrogen dioxide, and formaldehyde. Maximizing the use and utility of this new source of air quality information requires streamlining data access for a wide variety of research, public health, and other interested users. These varied applications often require the data to be structured in different ways, e.g., specific formats, array shapes, or file sizes. To enable access to TEMPO data in different forms, the NASA Atmospheric Science Data Center (ASDC), as part of the NASA Earth Science Data and Information System (ESDIS), provides a variety of cloud-based data transformation and GIS visualization tools. This presentation demonstrates methods of accessing and working with TEMPO data through these services, while highlighting aspects of the software and algorithmic workflows that perform the necessary data transformations. Examples include data subsetting, concatenation, and visualizations accessible via Jupyter notebooks and GIS software.

Daniel Kaufman↗

Environmental exposure to industrial air pollution is associated with decreased male fertility

Objective: To understand how chronic exposure to industrial air pollution is associated with male fertility through semen parameters. Design: Retrospective cohort study. Subjects: Men in the Subfertility, Health and Assisted Reproduction cohort who underwent a semen analysis 2005-2017 with ≥1 measured semen parameter (N=21,563). Intervention(s): Residential histories for each man were constructed using locations from administrative records linked through the Utah Population Database. Industrial facilities with air emissions of nine endocrine disrupting compound chemical classes were identified from the Environmental Protection Agency Risk-Screening Environmental Indicators microdata. Chemical levels were linked with residential histories for the 5 years prior to each semen analysis. Main Outcome Measures: Semen analyses were classified as azoospermic or oligozoospermic (< 15 M/mL) using World Health Organization cutoffs for concentration. Bulk semen parameters such as concentration, total count, ejaculate volume, total motility, total motile count, and total progressive motile count were also measured. Multivariable regression models with robust standard errors were used to associate exposure quartiles for each of the nine chemical classes with each semen parameter, adjusting for age, race, and ethnicity, as well as neighborhood socioeconomic disadvantage. Results: After adjustment for demographic covariates, several chemical classes were associated with azoospermia and decreased total motility and volume. For exposure in the 4th relative to 1st quartile, significant associations were observed for acrylonitrile (β total motility = -0.87 pp), aromatic hydrocarbons (odds ratio [OR]azoospermia = 1.53; β volume = -0.14 mL), dioxins (OR azoospermia = 1.31; β volume = -0.09 mL; β total motility = -2.65 pp), heavy metals (β total motility = -2.78pp), organic solvents (OR azoospermia = 1.75; β volume = -0.10 mL), organochlorines (OR azoospermia = 2.09; β volume = -0.12 mL), phthalates (OR azoospermia = 1.44; β volume = -0.09 mL; β total motility = -1.21 pp), and silver particles (OR azoospermia = 1.64; β volume = -0.11 mL). All semen parameters significantly decreased with increasing socioeconomic disadvantage. Men who lived in the most disadvantaged areas had concentration, volume, and total motility of 6.70 M/mL, 0.13 mL, and 1.79 pp lower, respectively. Count, motile count, and total progressive motile count all decreased by 30–34 M.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Bayesian modeling of traffic-related air pollutants: A case study of urban transportation and air quality dynamics in Columbia, South Carolina

Traffic emissions significantly impact near-road air quality and public health. This research applies a Bayesian modeling framework to investigate these impacts using high-resolution traffic and air pollutant data from an urban corridor in Columbia, South Carolina. Despite a data collection period truncated by the COVID-19 lockdown, the Bayesian approach successfully identified significant predictors and quantified model uncertainty. Employing Bayesian Model Selection and Averaging enhanced prediction accuracy and evaluated model uncertainty. Findings indicate that higher temperatures and increased moisture levels elevate particulate matter (PM 1.0 , PM 2.5 , PM 10 ) concentrations, while traffic speed significantly affects nitrogen dioxide (NO 2 ) levels. Specifically, higher average traffic speeds (indicative of smoother flow) correspond to lower NO 2 concentrations, suggesting that less congested conditions reduce NO 2 emissions. This study highlights the robustness of Bayesian methods for generating reliable air quality insights even under data-constrained conditions. The findings underscore the importance of traffic flow management (e.g., reducing congestion) for mitigating near-road NO 2 exposure and provide a basis for developing targeted public health strategies.

54 ENVIRONMENTAL SCIENCES↗

Unique impacts of strong and westward-extended western Pacific subtropical high on ozone pollution over eastern China

As a subtropical anticyclonic high-pressure system that typically forms over the northwestern Pacific Ocean in summer, the Western Pacific subtropical high (WPSH) affects meteorological conditions and ozone pollution in China. The relationship between maximum daily 8-h average ozone (MDA8 O 3 ) concentrations and the extremely strong and westward-extended WPSH occurred in 2022 is investigated using observations, reanalysis data and GEOS-Chem model simulations. The intensity of WPSH has a significant positive correlation with MDA8 O3 over southern China during July-August in 2022, with a correlation coefficient of +0.44, but the correlation is negative (–0.40) in northern China. During the strong WPSH days, MDA8 O 3 increased by 16.5µgm -3 (16.4% relative to July-August average) over southern China and decreased by 19.0µgm -3 (14.5%) in northern China compared to the weak WPSH days. The unique dipole pattern in the relationship between ozone levels and the WPSH in 2022 exhibited a contrast to that during 2015–2021. The difference is primarily due to the extremely strong WPSH intensity and its unusual westward expansion in 2022. In this case, an anomalous anticyclone at 500 hPa dominates over southern China, which creates conditions conducive for ozone formation and accumulation. The anticyclone weakened horizontal winds and reduced the dispersion of ozone, alongside a high temperature and low relative humidity, which favored the chemical production of ozone. In contrast, abnormal northerly winds enhanced ozone diffusion in northern China and the low temperature reduced ozone chemical production. Here, this study reveals the mechanism for the significant impact of strong and westward-extended WPSH on ozone concentrations over China, emphasizing the role of the WPSH location in modulating meteorology and ozone levels.

54 ENVIRONMENTAL SCIENCES↗

Composition, Emissions, and Air Quality Impacts of Hazardous Air Pollutants in Unburned Natural Gas from Residential Stoves in California

The presence of hazardous air pollutants (HAPs) entrained in end-use natural gas (NG) is an understudied source of human health risks. We performed trace gas analyses on 185 unburned NG samples collected from 159 unique residential NG stoves across seven geographic regions in California. Our analyses commonly detected 12 HAPs with significant variability across region and gas utility. Mean regional benzene, toluene, ethylbenzene, and total xylenes (BTEX) concentrations in end-use NG ranged from 1.6–25 ppmv–benzene alone was detected in 99% of samples, and mean concentrations ranged from 0.7–12 ppmv (max: 66 ppmv). By applying previously reported NG and methane emission rates throughout California’s transmission, storage, and distribution systems, we estimated statewide benzene emissions of 4,200 (95% CI: 1,800–9,700) kg yr –1 that are currently not included in any statewide inventories–equal to the annual benzene emissions from nearly 60,000 light-duty gasoline vehicles. Additionally, we found that NG leakage from stoves and ovens while not in use can result in indoor benzene concentrations that can exceed the California Office of Environmental Health Hazard Assessment 8-h Reference Exposure Level of 0.94 ppbv–benzene concentrations comparable to environmental tobacco smoke. This study supports the need to further improve our understanding of leaked downstream NG as a source of health risk.

42 ENGINEERING↗

Biochemical Conversion of Herbaceous Biomass to Renewable Diesel: Net Greenhouse Gas and Air Pollutant Trade-offs

This study examines greenhouse gas (GHG) and criteria air pollutant (CAP) emissions trade-offs for renewable diesel across 12 scenarios, involving different biochemical conversion designs, biorefinery scales, and feedstocks. A conventional design uses lignin for on-site heat and power, which exports excess power to the grid. An alternative design exports lignin pellets, offsetting other pellet production methods but requiring grid electricity to meet biorefinery power demands. Net emissions were quantified in Iowa and Georgia, selected considering feedstock availability, coproduct displacement, and regional power grids, assuming grid-exported power avoids coal or low-carbon electricity. Results for the conventional design remained consistent across the electricity displacement scenarios. When comparing lignin utilization strategies, pelletizing lignin reduces sulfur dioxide, carbon monoxide, nitrogen oxides, and volatile organic compounds (net emissions –0.66 mg MJ –1 , 25 mg MJ –1 , 25 mg MJ –1 , 7.8 mg MJ –1 , respectively). However, lignin pelletization increases net particulate matter (fine and coarse) and ammonia (net emissions of 4.7 mg MJ –1 , 13 mg MJ –1 , and 0.26 mg MJ –1 , respectively), alongside indirect GHG emissions due to grid electricity dependence. Additionally, processing 2000 tonnes corn stover daily minimizes emissions for both designs. Only lignin pelletization with renewable electricity and additional particulate matter and ammonia controls reduces all CAP and GHG emissions simultaneously.

09 BIOMASS FUELS↗

Regime-Dependence of Nocturnal Nitrate Formation via N 2 O 5 Hydrolysis and Its Implication for Mitigating Nitrate Pollution

The heterogeneous hydrolysis of dinitrogen pentoxide (N 2 O 5 ) is an important pathway in nitrate formation; however, its formation rate and relative contribution to total particulate nitrate (pNO 3 - ) are highly variable. Here we report that nocturnal pNO 3 - formation via N 2 O 5 hydrolysis is dependent on the regime defined by the ratio of NO 2 to O 3 . Nocturnal pNO 3 - formation via N 2 O 5 hydrolysis is suppressed in an O 3 -limited regime but enhanced in a NO 2 -limited regime. The results have crucial implications for effective control of nitrate pollution in the future. An exclusive decrease in NO 2 will decrease nocturnal pNO 3 - formation in a NO 2 -limited regime but may be less effective or even increase nocturnal pNO 3 - formation in an O 3 -limited regime.

54 ENVIRONMENTAL SCIENCES↗

COVID-19 pandemic reveals persistent disparities in nitrogen dioxide pollution

We leverage the unparalleled changes in human activity during COVID-19 and the unmatched capabilities of the TROPOspheric Monitoring Instrument to understand how lockdowns impact ambient nitrogen dioxide (NO 2 ) pollution disparities in the United States. The least White communities experienced the largest NO 2 reductions during lockdowns; however, disparities between the least and most White communities are so large that the least White communities still faced higher NO 2 levels during lockdowns than the most White communities experienced prior to lockdowns, despite a ~50% reduction in passenger vehicle traffic. Similar findings hold for ethnic, income, and educational attainment population subgroups. Future strategies to reduce NO 2 disparities will need to target emissions from heavy-duty vehicles.

TROPOMI↗

Association of particulate air pollution and acute mortality: involvement of ultrafine particles?

Recent epidemiological studies show an association between particulate air pollution and acute mortality and morbidity down to ambient particle concentrations below 100 micrograms/m3. Whether this association also implies a causality between acute health effects and particle exposure at these low levels is unclear at this time; no mechanism is known that would explain such dramatic effects of low ambient particle concentrations. Based on results of our past and most recent inhalation studies with ultrafine particles in rats, we propose that such particles, that is, particles below approximately 50 nm in diameter, may contribute to the observed increased mortality and morbidity In the past we demonstrated that inhalation of highly insoluble particles of low intrinsic toxicity, such as TiO2, results in significantly increased pulmonary inflammatory responses when their size is in the ultrafine particle range, approximately 20 nm in diameter. However, these effects were not of an acute nature and occurred only after prolonged inhalation exposure of the aggregated ultrafine particles at concentrations in the milligrams per cubic meter range. In contrast, in the course of our most recent studies with thermodegradation products of polytetrafluoroethylene (PTFE) we found that freshly generated PTFE fumes containing singlet ultrafine particles (median diameter 26 nm) were highly toxic to rats at inhaled concentrations of 0.7-1.0 x 10(6) particles/cm3, resulting in acute hemorrhagic pulmonary inflammation and death after 10-30 min of exposure. We also found that work performance of the rats in a running wheel was severely affected by PTFE fume exposure. These results confirm reports from other laboratories of the highly toxic nature of PTFE fumes, which cannot be attributed to gas-phase components of these fumes such as HF, carbonylfluoride, or perfluoroisobutylene, or to reactive radicals. The calculated mass concentration of the inhaled ultrafine PTFE particles in our studies was less than 60 micrograms/m3, a very low value to cause mortality in healthy rats. Aging of the fumes with concomitant aggregation of the ultrafine particles significantly decreases their toxicity. Since ultrafine particles are always present in the urban atmosphere, we suggest that they play a role in causing acute lung injury in sensitive parts of the population.

NASA Discipline Environmental Health↗

Wildfire Emissions and Their Interaction with Urban and Rural Pollution: Data and Simulations

In recent years NASA has conducted a series of airborne campaigns (e. g. SEAC4RS*, ARCTAS, INTEX-A/B) over North America using an instrumented DC-8 aircraft equipped to measure a very large number of gaseous and aerosol constituents including several unique tracers. In these campaigns wild fires were extensively sampled near source as well as downwind after aging. The data provided detailed information on the composition and chemistry of fire emissions under a variety of atmospheric conditions as well as their interactions with rural and urban air pollution. Major fires studied including the California Rim fire in 2013 (SEAC4RS), the 2008 California wildfires (ARCTAS), and the Alaskan fires downwind over eastern US (INTEX-A). Although some fire plumes contained virtually no O3 enhancement, others showed significant ozone formation. Over Los Angeles, the highest O3 mixing ratios were observed in fire influenced urban air masses. Attempts to simulate these interactions using state of the art models were only minimally successful and indicated several shortcomings in simulating fire emission influences on urban smog formation. A variety of secondary oxidation products (e. g. O3, PAN, HCHO) were substantially underestimated. We will discuss the data collected in fire influenced air masses and their potential air quality implications.

FIre Emissions↗

Evaluating a Priori Ozone Profile Information Used in TEMPO (Tropospheric Emissions: Monitoring of Pollution) Tropospheric Ozone Retrievals

A primary objective for TOLNet is the evaluation and validation of space-based tropospheric O3 retrievals from future systems such as the Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite. This study is designed to evaluate the tropopause-based O3 climatology (TB-Clim) dataset which will be used as the a priori profile information in TEMPO O3 retrievals. This study also evaluates model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time (NRT) data assimilation model products (NASA Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS-5) Forward Processing (FP) and Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2)) and full chemical transport model (CTM), GEOS-Chem, simulations. The TB-Clim dataset and model products are evaluated with surface (0-2 km) and tropospheric (0-10 km) TOLNet observations to demonstrate the accuracy of the suggested a priori dataset and information which could potentially be used in TEMPO O3 algorithms. This study also presents the impact of individual a priori profile sources on the accuracy of theoretical TEMPO O3 retrievals in the troposphere and at the surface. Preliminary results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles observed by TOLNet, model-simulated profiles from a full CTM (GEOS-Chem is used as a proxy for CTM O3 predictions) resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly (diurnal cycle evaluation) and daily-averaged (daily variability evaluation) TOLNet observations. Furthermore, it was determined that when large daily-averaged surface O3 mixing ratios are observed (65 ppb), which are important for air quality purposes, TEMPO retrieval values at the surface display higher correlations and less bias when applying CTM a priori profile information compared to all other data products. The primary reason for this is that CTM predictions better capture the spatio-temporal variability of the vertical profiles of observed tropospheric O3 compared to the TB-Clim dataset and other NRT data assimilation models evaluated during this study.

Pollution↗

Improved Rice Residue Burning Emissions Estimates: Accounting for Practice-Specific Emission Factors in Air Pollution Assessments of Vietnam

In Southeast Asia and Vietnam, rice residues are routinely burned after the harvest to prepare fields for the next season. Specific to Vietnam, the two prevalent burning practices include: a). piling the residues after hand harvesting; b). burning the residues without piling, after machine harvesting. In this study, we synthesized field and laboratory studies from the literature on rice residue burning emission factors for Particulate Matter less than 2.5 microns (PM2.5). We found significant differences in the resulting burning-practice specific emission factors, with 16.9 grams per square kilogram (plus or minus 6.9) for pile burning and 8.8 grams per square kilogram (plus or minus 3.5) for non-pile burning. We calculated burning practice specific emissions based on rice area data, region-specific fuel-loading factors, combined emission factors, and estimates of burning from the literature. Our results for year 2015 estimate 180 gigagrams of PM2.5 result from the pile burning method and 130 gigagrams result from non-pile burning method, with the most-likely current emission scenario of 150 gigagrams PM2.5 emissions for Vietnam. For comparison purposes, we calculated emissions using generalized agricultural emission factors employed in global biomass burning studies. These results estimate 80 gigagrams PM2.5, which is only 44 percent of the pile burning-based estimates, suggesting underestimation in previous studies. We compare our emissions to an existing all-combustion sources inventory, results show emissions account for 14-18 percent of Vietnam's total PM2.5 depending on burning practice. Within the highly-urbanized and cloud-covered Hanoi Capital region (HCR), we use rice area from Sentinel-1A to derive spatially-explicit emissions and indirectly estimate residue burning dates. Results from HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) back-trajectory analysis stratified by season show autumn has most emission trajectories originating in the North, while spring has most originating in the South, suggesting the latter may have bigger impact on air quality. From these results, we highlight locations where emission mitigation efforts could be focused and suggest measures for pollutant mitigation. Our study demonstrates the need to account for emissions variation due to different burning practices.

Air Pollution↗