Formaldehyde column density measurements as a suitable pathway to estimate near-surface ozone tendencies from space

Investigating Changes in Ozone Formation Chemistry during Summertime Pollution Events over the Northeastern United States

Understanding the local-scale spatial and temporal variability of ozone formation is crucial for effective mitigation. We combine tropospheric vertical column densities (VCDTrop) of formaldehyde (HCHO) and nitrogen dioxide (NO2), referred to as HCHO-VCDTrop and NO2-VCDTrop, retrieved from airborne remote sensing and the TROPOspheric Monitoring Instrument (TROPOMI) with ground-based measurements to investigate changes in ozone precursors and the inferred chemical production regime on high-ozone days in May-August 2018 over two Northeast urban domains. Over New York City (NYC) and Baltimore/Washington D.C. (BAL/DC), HCHO-VCDTrop increases across the domain, but higher NO2-VCDTrop occurs mainly in urban centers on ozone exceedance days (when maximum daily 8 h average (MDA8) ozone exceeds 70 ppb at any monitor in the region). The ratio of HCHO-VCDTrop to NO2-VCDTrop, proposed as an indicator of the sensitivity of local surface ozone production rates to its precursors, generally increases on ozone exceedance days, implying a transition toward a more NOx-sensitive ozone production regime that should lead to higher efficacy of NOx controls on the highest ozone days in NYC and BAL/DC. Warmer temperatures and enhanced influence from emissions in the local boundary layer on the high-ozone days are accompanied by slower wind speeds in BAL/DC but stronger, southwesterly winds in NYC.

Atmospheric Formaldehyde Monitored by TROPOMI Satellite Instrument throughout 2020 over São Paulo State, Brazil

We aimed to study the daily formaldehyde (HCHO) columns over urban and forested areas in São Paulo State, Brazil, from rhe TROPOMI spectrometer onboard the Sentinel-5P satellite during 2020. Nineteen specific areas were defined in four regions: 3 areas in each of two preserved Atlantic Forests (PEMD and PETAR), 3 in a sugarcane growing region (NERG) and 10 in the Metropolitan Area of São Paulo (MASP), among which 2 areas are in the Morro Grande reserve, which is a significant remnant of Atlantic Forest outside the densely urbanized area of MASP. An analysis of variance and Tukey’s test showed that the mean annual columns over the Morro Grande reserve (1.69±1.05×10−4 mol/m² and 1.73±1.07×10−4 mol/m²) presented greater statistical similarity with the forest and rural areas of the state (<1.70×10−4 mol/m²) than with MASP (>2.00×10−4 mol/m²), indicating few effects from megacity anthropogenic emissions. Case studies addressing selected days in 2020 showed that fires in and around the state were related to episodes of maximum density of HCHO columns. The results showed significant seasonality, with lower concentrations during summer (wet season) and higher concentrations during winter and spring (dry and transition dry–wet seasons).

Global Surface HCHO Distribution Derived from Satellite Observations with Neural Networks Technique

Formaldehyde (HCHO) is one of the most important carcinogenic air contaminants in outdoor air. However, the lack of monitoring of the global surface concentration of HCHO is currently hindering research on outdoor HCHO pollution. Traditional methods are either restricted to small areas or, for research on a global scale, too data-demanding. To alleviate this issue, we adopted neural networks to estimate the 2019 global surface HCHO concentration with confidence intervals, utilizing HCHO vertical column density data from TROPOMI, and in-situ data from HAPs (harmful air pollutants) monitoring networks and the ATom mission. Our results show that the global surface HCHO average concentration is 2.30 μg/m3. Furthermore, in terms of regions, the concentrations in the Amazon Basin, Northern China, South-east Asia, the Bay of Bengal, and Central and Western Africa are among the highest. The results from our study provide the first dataset on global surface HCHO concentration. In addition, the derived confidence intervals of surface HCHO concentration add an extra layer of confidence to our results. As a pioneering work in adopting confidence interval estimation to AI-driven atmospheric pollutant research and the first global HCHO surface distribution dataset, our paper paves the way for rigorous study of global ambient HCHO health risk and economic loss, thus providing a basis for pollution control policies worldwide.

Identification of long-term evolution of ozone sensitivity to precursors based on two-dimensional mutual verification

Tropospheric ozone pollution has been continuously worsening in China during the past decade. Identification of long-term evolution of ozone sensitivity to precursors is essential to evaluating the impact of emission reduction measures on ozone pollution. Traditional observation-based model and 3-d numerical model are not suitable for analyzing long-term variation of ozone sensitivity to precursors. In this study, by transforming the conventional ozone isopleth plot into a VOCR isopleth plot in the functional space of NO_x and ozone concentrations, we developed a novel approach to identify ozone sensitivity to precursors by simply using long-term monitoring data of ozone, NO_x and temperature. This approach estimated ozone formation regimes (OFR) by ozone sensitivity to NO_x and temperature separately, and the convergence of OFR serves as a way of mutual verification. We found that ozone formation was generally in the VOCR-limited or transitional regime in Shanghai, the largest metropolitan area in China. However, OFR was shifted to NO_x-limited at Pudong station during 2017-19 due much to the stringent NO_x emission control. OFR was also shifted to NO_x-limited along with the increasing temperature. When temperature was over 30 °C, Shanghai was mostly in a NO_x-limited OFR. This highlights that the NO_x emission control measures need to be strengthened to reduce peak ozone levels more efficiently. Jinshan station exhibited a different trend with OFR shifted to VOCR-limited in 2017-19, which proved the effectiveness of VOCs emission control on petrochemical sector. However, OFR was shifted to NO_x-limited when temperature was over 30 °C, suggesting more stringent VOCs emissions control should be targeted on days with higher temperature.

Satellite Formaldehyde to Support Model Evaluation

Formaldehyde (HCHO), a known carcinogen classified as a hazardous pollutant by the United States Environmental Protection Agency (U.S. EPA), is measured through monitoring networks across the U.S. Since these data are limited in spatial and temporal extent, model simulations from the U.S. EPA Community Multiscale Air Quality (CMAQ) model are used to estimate ambient HCHO exposure for the EPA National Air Toxics Assessment (NATA). Here, we employ satellite HCHO retrievals from the Ozone Monitoring Instrument (OMI)-the NASA retrieval developed by the Smithsonian Astrophysical Observatory (SAO), and the European Union Quality Assurance for Essential Climate Variables (QA4ECV) retrieval-to evaluate three CMAQ configurations, spanning the summers of 2011 and 2016, with differing biogenic emissions inputs and chemical mechanisms. These CMAQ configurations capture the general spatial and temporal behavior of both satellite retrievals, but underestimate column HCHO, particularly in the western U.S. In the southeastern U.S., the comparison with OMI HCHO highlights differences in modeled meteorology and biogenic emissions even with differences in satellite retrievals. All CMAQ configurations show low daily correlations with OMI HCHO (r = 0.26 - 0.38), however, we find higher monthly correlations (r = 0.52 - 0.73), and the models correlate best with the OMI-QA4ECV product. Compared to surface observations, we find improved agreement over a 24-hour period compared to afternoon-only, suggesting daily HCHO amounts are captured with more accuracy than afternoon amounts. This work highlights the potential for synergistic improvements in modeling and satellite retrievals to support near-surface HCHO estimates for the NATA and other applications.

Taehwa Research Forest: A receptor site for severe domestic pollution events in Korea during 2016

During the May-June 2016 International Cooperative Air Quality Field Study in Korea (KORUS-AQ), light synoptic meteorological forcing facilitated Seoul metropolitan pollution outflow to reach the remote Taehwa Research Forest (TRF) site and cause regulatory exceedances of ozone on 24 days. Two of these severe pollution events are thoroughly examined. The first, occurring on 17 May 2016, tracks transboundary pollution transport exiting eastern China and the Yellow Sea, traversing the Seoul Metropolitan Area (SMA), and then reaching TRF in the afternoon hours with severely polluted conditions. This case study indicates that although outflow from China and the Yellow Sea were elevated with respect to chemically unperturbed conditions, the regulatory exceedance at TRF was directly linked in time, space, and altitude to urban Seoul emissions. The second case studied, occurring on 09 June 2016, reveals that increased levels of biogenic emissions, in combination with amplified urban emissions, were associated with severe levels of pollutions and a regulatory exceedance at TRF. In summary, domestic emissions may be causing more pollution than by trans-boundary pathways, which have been historically believed to be the major source of air pollution in South Korea. The case studies are assessed with multiple aircraft, model (photochemical and meteorological) simulations, in-situ chemical sampling, and extensive ground-based profiling at TRF. These observations clearly identify TRF and the surrounding rural communities as receptor sites for severe pollution events associated with Seoul outflow, which will result in long-term negative effects to both human health and agriculture in the affected areas.

Mobile Source Contributions to Ambient Ozone and Particulate Matter in 2025

The contribution of precursor emissions from 17 mobile source sectors to ambient ozone and fine particulate matter levels across the U.S. were evaluated, using the CAMx photochemical model, to identify which mobile source sectors are projected to have the largest impacts on air pollution in 2025. Both onroad and nonroad sectors contribute considerably to projected air pollution across much of the country. Summer ozone season ozone contributions between 2 and 5 ppb, which are among the highest levels presented on the maps of mobile source sectors, are largely found in the southeast United States from the onroad sectors, most notably light-duty and heavy-duty vehicles, and along the coastline from the Category 3 (C3) marine sector. Annual average PM2.5 contributions between 0.5 to 0.9 μg/m3, which are among the highest levels presented on the maps of mobile source sectors, are found throughout the Midwest and along portions of the east and west coast from onroad sectors as well as nonroad diesel and rail sectors. Additionally, contributions of precursor emissions to ambient ozone and PM2.5 levels were evaluated to understand the range of impacts from precursors in the various mobile source sectors. For most mobile source sectors, in most locations, NOX emissions contributed more to ozone than VOC emissions, and secondary PM2.5 contributed more to ambient PM2.5 than primary PM2.5. The largest ozone levels on the maps showing contributions from mobile source NOX emissions tended to be between 2 and 5 ppb, while the largest ozone levels on the maps showing contributions from mobile source VOC emissions tended to be between 0.9 and 2 ppb, except for southern California where ozone contributions from VOC emissions from onroad light duty vehicles were between 2 and 5 ppb. The largest contributions to ambient PM2.5 on the maps showing primary and secondary contributions from mobile source sectors tended to be between 0.1 and 0.5 μg/m3. The contribution from primary PM2.5 extended over localized areas (urban-scale) and the contribution from secondary PM2.5 extended over more regional (multi-state) areas.

Characterizing CO and NO y Sources and Relative Ambient Ratios in the Baltimore Area Using Ambient Measurements and Source Attribution Modeling

Modeled source attribution information from the Community Multiscale Air Quality model was coupled with ambient data from the 2011 Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality Baltimore field study. We assess source contributions and evaluate the utility of using aircraft measured CO and NO _y relationships to constrain emission inventories. We derive ambient and modeled ΔCO:ΔNO _y ratios that have previously been interpreted to represent CO:NO _y ratios in emissions from local sources. Modeled and measured ΔCO:ΔNO _y are similar; however, measured ΔCO:ΔNO _y has much more daily variability than modeled values. Sector-based tagging shows that regional transport, on-road gasoline vehicles, and nonroad equipment are the major contributors to modeled CO mixing ratios in the Baltimore area. In addition to those sources, on-road diesel vehicles, soil emissions, and power plants also contribute substantially to modeled NO _y in the area. The sector mix is important because emitted CO:NO _x ratios vary by several orders of magnitude among the emission sources. The model-predicted gasoline/diesel split remains constant across all measurement locations in this study. Comparison of ΔCO:ΔNO _y to emitted CO:NO _y is challenged by ambient and modeled evidence that free tropospheric entrainment, and atmospheric processing elevates ambient ΔCO:ΔNO _y above emitted ratios. Specifically, modeled ΔCO:ΔNO _y from tagged mobile source emissions is enhanced 5-50% above the emitted ratios at times and locations of aircraft measurements. We also find a correlation between ambient formaldehyde concentrations and measured ΔCO:ΔNO _y suggesting that secondary CO formation plays a role in these elevated ratios. This analysis suggests that ambient urban daytime ΔCO:ΔNO _y values are not reflective of emitted ratios from individual sources.

The first evaluation of formaldehyde column observations by improved Pandora spectrometers during the KORUS-AQ field study

The Korea-United States Air Quality Study (KORUS-AQ) conducted during May-June 2016 offered the first opportunity to evaluate direct-sun observations of formaldehyde (HCHO) total column densities with improved Pandora spectrometer instruments. The measurements highlighted in this work were conducted both in the Seoul megacity area at the Olympic Park site (37.5232° N, 27.1260° E; 26 ma.s.l.) and at a nearby rural site downwind of the city at the Mount Taehwa research forest site (37.3123° N, 127.3106° E; 160ma.s.l.). Evaluation of these measurements was made possible by concurrent ground-based in situ observations of HCHO at both sites as well as overflight by the NASA DC-8 research aircraft. The flights provided in situ measurements of HCHO to characterize its vertical distribution in the lower troposphere (0-5km). Diurnal variation in HCHO total column densities followed the same pattern at both sites, with the minimum daily values typically observed between 6:00 and 7:00 local time, gradually increasing to a maximum between 13:00 and 17:00 before decreasing into the evening. Pandora vertical column densities were compared with those derived from the DC-8 HCHO in situ measured profiles augmented with in situ surface concentrations below the lowest altitude of the DC-8 in proximity to the ground sites. A comparison between 49 column densities measured by Pandora vs. aircraft-integrated in situ data showed that Pandora values were larger by 16% with a constant offset of 0.22DU (Dobson units; R 2 = 0.68). Pandora HCHO columns were also compared with columns calculated from the surface in situ measurements over Olympic Park by assuming a well-mixed lower atmosphere up to a ceilometer-measured mixed-layer height (MLH) and various assumptions about the small residual HCHO amounts in the free troposphere up to the tropopause. The best comparison (slope = 1.03±0.03; intercept = 0.29±0.02DU; and R 2 = 0.78±0.02) was achieved assuming equal mixing within ceilometer-measured MLH combined with an exponential profile shape. These results suggest that diurnal changes in HCHO surface concentrations can be reasonably estimated from the Pandora total column and information on the mixed-layer height. More work is needed to understand the bias in the intercept and the slope relative to columns derived from the in situ aircraft and surface measurements.