Formaldehyde (HCHO) As a Hazardous Air Pollutant: Mapping Surface Air Concentrations from Satellite and Inferring Cancer Risks in the United States.

Formaldehyde (HCHO) is the most important carcinogen in outdoor air among the 187 hazardous air pollutants (HAPs) identified by the U.S. Environmental Protection Agency (EPA), not including ozone and particulate matter. However, surface observations of HCHO are sparse and the EPA monitoring network could be prone to positive interferences. Here we use 2005-2016 summertime HCHO column data from the OMI satellite instrument, validated with high-quality aircraft data and oversampled on a 5 × 5 km2 grid, to map surface air HCHO concentrations across the contiguous U.S. OMI-derived summertime HCHO values are converted to annual averages using the GEOS-Chem chemical transport model. Results are in good agreement with high-quality summertime observations from urban sites (-2% bias, r = 0.95) but a factor of 1.9 lower than annual means from the EPA network. We thus estimate that up to 6600-12 500 people in the U.S. will develop cancer over their lifetimes by exposure to outdoor HCHO. The main HCHO source in the U.S. is atmospheric oxidation of biogenic isoprene, but the corresponding HCHO yield decreases as the concentration of nitrogen oxides (NOx ≡ NO + NO2) decreases. A GEOS-Chem sensitivity simulation indicates that HCHO levels would decrease by 20-30% in the absence of U.S. anthropogenic NOx emissions. Thus, NOx emission controls to improve ozone air quality have a significant cobenefit in reducing HCHO-related cancer risks.

Formaldehyde columns from the Ozone Monitoring Instrument: Urban versus background levels and evaluation using aircraft data and a global model.

[1] We combine aircraft measurements (Second Texas Air Quality Study, Megacity Initiative: Local and Global Research Observations, Intercontinental Chemical Transport Experiment: Phase B) over the United States, Mexico, and the Pacific with a 3-D model (GEOS-Chem) to evaluate formaldehyde column (ΩHCHO) retrievals from the Ozone Monitoring Instrument (OMI) and assess the information they provide on HCHO across local to regional scales and urban to background regimes. OMI ΩHCHO correlates well with columns derived from aircraft measurements and GEOS-Chem (R = 0.80). For the full data ensemble, OMI's mean bias is -3% relative to aircraft-derived ΩHCHO (-17% where ΩHCHO > 5 × 1015 molecules cm-2) and -8% relative to GEOS-Chem, within expected uncertainty for the retrieval. Some negative bias is expected for the satellite and model, given the plume sampling of many flights and averaging over the satellite and model footprints. Major axis regression for OMI versus aircraft and model columns yields slopes (95% confidence intervals) of 0.80 (0.62-1.03) and 0.98 (0.73-1.35), respectively, with no significant intercept. Aircraft measurements indicate that the normalized vertical HCHO distribution, required by the satellite retrieval, is well captured by GEOS-Chem, except near Mexico City. Using measured HCHO profiles in the retrieval algorithm does not improve satellite-aircraft agreement, suggesting that use of a global model to specify shape factors does not substantially degrade retrievals over polluted areas. While the OMI measurements show that biogenic volatile organic compounds dominate intra-annual and regional ΩHCHO variability across the United States, smaller anthropogenic ΩHCHO gradients are detectable at finer spatial scales (∼20-200 km) near many urban areas.

Unraveling pathways of elevated ozone induced by the 2020 lockdown in Europe by an observationally constrained regional model using TROPOMI.

Questions about how emissions are changing during the COVID-19 lockdown periods cannot be answered by observations of atmospheric trace gas concentrations alone, in part due to simultaneous changes in atmospheric transport, emissions, dynamics, photochemistry, and chemical feedback. A chemical transport model simulation benefiting from a multi-species inversion framework using well-characterized observations should differentiate those influences enabling to closely examine changes in emissions. Accordingly, we jointly constrain NO x and VOC emissions using well-characterized TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO2 columns during the months of March, April, and May 2020 (lockdown) and 2019 (baseline). We observe a noticeable decline in the magnitude of NO x emissions in March 2020 (14 %-31 %) in several major cities including Paris, London, Madrid, and Milan, expanding further to Rome, Brussels, Frankfurt, Warsaw, Belgrade, Kyiv, and Moscow (34 %-51 %) in April. However, NO x emissions remain at somewhat similar values or even higher in some portions of the UK, Poland, and Moscow in March 2020 compared to the baseline, possibly due to the timeline of restrictions. Comparisons against surface monitoring stations indicate that the constrained model underrepresents the reduction in surface NO2. This underrepresentation correlates with the TROPOMI frequency impacted by cloudiness. During the month of April, when ample TROPOMI samples are present, the surface NO2 reductions occurring in polluted areas are described fairly well by the model (model: -21 ± 17 %, observation: -29 ± 21 %). The observational constraint on VOC emissions is found to be generally weak except for lower latitudes. Results support an increase in surface ozone during the lockdown. In April, the constrained model features a reasonable agreement with maximum daily 8 h average (MDA8) ozone changes observed at the surface (r = 0.43), specifically over central Europe where ozone enhancements prevail (model: +3.73 ± 3.94 %, + 1.79 ppbv, observation: +7.35 ± 11.27 %, +3.76 ppbv). The model suggests that physical processes (dry deposition, advection, and diffusion) decrease MDA8 surface ozone in the same month on average by -4.83 ppbv, while ozone production rates dampened by largely negative J NO 2 [ NO 2 ] - k NO + O 3 [ NO ] [ O 3 ] become less negative, leading ozone to increase by +5.89 ppbv. Experiments involving fixed anthropogenic emissions suggest that meteorology contributes to 42 % enhancement in MDA8 surface ozone over the same region with the remaining part (58 %) coming from changes in anthropogenic emissions. Results illustrate the capability of satellite data of major ozone precursors to help atmospheric models capture ozone changes induced by abrupt emission anomalies.

Quantifying the Impact of Excess Moisture From Transpiration From Crops on an Extreme Heat Wave Event in the Midwestern U.S.: A Top-Down Constraint From Moderate Resolution Imaging Spectroradiometer Water Vapor Retrieval.

The primary focus of this study is to understand the contribution from excess moisture from crop transpiration to the severity of a heat wave episode that hit the Midwestern U.S. from 16 to 20 July 2011. To elucidate this, we first provide an optimal estimate of the transpiration water vapor flux using satellite total column water vapor retrievals whose accuracy and precision are characterized using independent observations. The posterior transpiration flux is estimated using a local ensemble transform Kalman filter that employs a mesoscale weather model as the forward model. The new estimation suggests that the prior values of transpiration flux from crops are biased high by 15%. We further use the constrained flux to examine the sensitivity of meteorology to the contributions from crops. Over the agricultural areas during daytime, elevated moisture (up to 40%) from crops not only increases humidity (thus the heat index) but also provides a positive radiative forcing by increasing downward longwave radiation (13 ± 4 W m-2) that results in even higher surface air temperature (+0.4 °C). Consequently, we find that the elevated moisture generally provides positive feedback to aggravate the heat wave, with daytime enhancements of heat index by as large as 3.3 ± 0.8 °C. Due to a strong diurnal cycle in the transpiration, the feedback tends to be stronger in the afternoon (up to 5 °C) and weaker at night. Results offer a potential basis for designing mitigation strategies for the effect of transpiration from agriculture in the future, in addition to improving the estimation of canopy transpiration.

Evaluating a Space-Based Indicator of Surface Ozone-NO x -VOC Sensitivity Over Midlatitude Source Regions and Application to Decadal Trends.

Determining effective strategies for mitigating surface ozone (O3) pollution requires knowledge of the relative ambient concentrations of its precursors, NO x , and VOCs. The space-based tropospheric column ratio of formaldehyde to NO2 (FNR) has been used as an indicator to identify NO x -limited versus NO x -saturated O3 formation regimes. Quantitative use of this indicator ratio is subject to three major uncertainties: (1) the split between NO x -limited and NO x -saturated conditions may shift in space and time, (2) the ratio of the vertically integrated column may not represent the near-surface environment, and (3) satellite products contain errors. We use the GEOS-Chem global chemical transport model to evaluate the quantitative utility of FNR observed from the Ozone Monitoring Instrument over three northern midlatitude source regions. We find that FNR in the model surface layer is a robust predictor of the simulated near-surface O3 production regime. Extending this surface-based predictor to a column-based FNR requires accounting for differences in the HCHO and NO2 vertical profiles. We compare four combinations of two OMI HCHO and NO2 retrievals with modeled FNR. The spatial and temporal correlations between the modeled and satellite-derived FNR vary with the choice of NO2 product, while the mean offset depends on the choice of HCHO product. Space-based FNR indicates that the spring transition to NO x -limited regimes has shifted at least a month earlier over major cities (e.g., New York, London, and Seoul) between 2005 and 2015. This increase in NO x sensitivity implies that NO x emission controls will improve O3 air quality more now than it would have a decade ago.

Observing atmospheric formaldehyde (HCHO) from space: validation and intercomparison of six retrievals from four satellites (OMI, GOME2A, GOME2B, OMPS) with SEAC4RS aircraft observations over the Southeast US.

Formaldehyde (HCHO) column data from satellites are widely used as a proxy for emissions of volatile organic compounds (VOCs) but validation of the data has been extremely limited. Here we use highly accurate HCHO aircraft observations from the NASA SEAC4RS campaign over the Southeast US in August-September 2013 to validate and intercompare six retrievals of HCHO columns from four different satellite instruments (OMI, GOME2A, GOME2B and OMPS) and three different research groups. The GEOS-Chem chemical transport model is used as a common intercomparison platform. All retrievals feature a HCHO maximum over Arkansas and Louisiana, consistent with the aircraft observations and reflecting high emissions of biogenic isoprene. The retrievals are also interconsistent in their spatial variability over the Southeast US (r=0.4-0.8 on a 0.5°×0.5° grid) and in their day-to-day variability (r=0.5-0.8). However, all retrievals are biased low in the mean by 20-51%, which would lead to corresponding bias in estimates of isoprene emissions from the satellite data. The smallest bias is for OMI-BIRA, which has high corrected slant columns relative to the other retrievals and low scattering weights in its air mass factor (AMF) calculation. OMI-BIRA has systematic error in its assumed vertical HCHO shape profiles for the AMF calculation and correcting this would eliminate its bias relative to the SEAC4RS data. Our results support the use of satellite HCHO data as a quantitative proxy for isoprene emission after correction of the low mean bias. There is no evident pattern in the bias, suggesting that a uniform correction factor may be applied to the data until better understanding is achieved.

Validation of OMI HCHO data and its analysis over Asia.

OMI HCHO is validated over the continental US (CONUS), and used to analyze regional sources in Northeast Asia (NA) and Southeast Asia (SA). OMI HCHO Version 2.0 data show unrealistic trends, which prompted the production of a corrected OMI HCHO data set. EOF and SVD are utilized to compare the spatial and temporal variability between OMI HCHO against GOME and SCIAMACHY, and against GEOS-Chem. CONUS HCHO chemistry is well studied; its concentrations are greatest in the southeastern US with annual cycle maximums corresponding to the summer vegetation. The corrected OMI HCHO agrees with this understanding as well as with the other sensors measurements and has no unrealistic trends. In NA the annual cycle is super-posed by extremely large concentrations in polluted mega-cities. The other sensors generally agree with NA's OMI HCHO regional distribution, but megacity signal is not seen in GEOS-Chem. Our study supports the findings proposed by others that the emission inventory used in GEOS-Chem significantly underestimates anthropogenic influence on HCHO emission over megacities. The persistent mega-city signal is also present in SA. In SA the spatial and temporal patterns of OMI HCHO show a maximum in the dry season. The patterns are in remarkably good agreement with fire counts, which illustrates that the variability of HCHO over SA is strongly influenced by biomass burning. The corrected OMI HCHO data has realistic trends, conforms to well-known sources over CONUS, and has shown a stationary large concentration over polluted Asian mega-cities, and a widespread biomass burning in SA.

Interpreting satellite column observations of formaldehyde over tropical South America.

Space-borne column measurements of formaldehyde (HCHO), a high-yield oxidation product of volatile organic compounds (VOCs), represent important constraints for quantifying net regional fluxes of VOCs. Here, we interpret observed distributions of HCHO columns from the Global Ozone Monitoring Experiment (GOME) over tropical South America during 1997-2001. We present the first comparison of year-long in situ isoprene concentrations and fire-free GOME HCHO columns over a tropical ecosystem. GOME HCHO columns and in situ isoprene concentrations are elevated in the wet and dry seasons, with the highest values in the dry season. Previous analysis of the in situ data highlighted the possible role of drought in determining the elevated concentrations during the dry season, inferring the potential of HCHO columns to provide regional-scale constraints for estimating the role of drought on isoprene emissions. The agreement between the observed annual cycles of GOME HCHO columns and Along-Track Scanning Radiometer firecount data over the Amazon basin (correlations typically greater than 0.75 for a particular year) illustrates the potential of HCHO column to provide quantitative information about biomass burning emissions.

Tropospheric ozone profiles from a ground-based ultraviolet spectrometer: a new retrieval method.

We present, to the best of our knowledge, a new method to retrieve tropospheric ozone (O3) profiles from ground-based ultraviolet spectroscopic measurements. This method utilizes radiance spectra in the Huggins bands (i.e., 300-340 nm) measured at three off-axis angles (e.g., 45 degrees, 75 degrees, and 85 degrees) normalized to direct-Sun irradiances or zenith-sky radiances with the total column O3 derived from direct-Sun or zenith-sky measurements as a constraint. The vertical resolution of the retrieved O3 values ranges from approximately 3 km near the surface to approximately 12 km at 20 km altitude. This method can be used to measure diurnal variation of tropospheric O3 profiles and is complementary to the Umkehr method that mainly measures ozone profiles in the stratosphere.

Undersampling correction for array detector-based satellite spectrometers.

Array detector-based instruments are now fundamental to measurements of ozone and other atmospheric trace gases from space in the ultraviolet, visible, and infrared. The present generation of such instruments suffers, to a greater or lesser degree, from undersampling of the spectra, leading to difficulties in the analysis of atmospheric radiances. We provide extended analysis of the undersampling suffered by modern satellite spectrometers, which include the Global Ozone Monitoring Experiment, Scanning Imaging Absorption Spectrometer for Atmospheric Chartography, Ozone Monitoring Instrument, and Ozone Mapping and Profiler Suite. The analysis includes basic undersampling, the effects of binning into separate detector pixels, and the application of high-resolution Fraunhofer spectral data to correct for undersampling in many useful cases.

Global partitioning of NOx sources using satellite observations: relative roles of fossil fuel combustion, biomass burning and soil emissions.

We use space-based observations of NO2 columns from the Global Ozone Monitoring Experiment (GOME) to derive monthly top-down NOx emissions for 2000 via inverse modeling with the GEOS-CHEM chemical transport model. Top-down NOx sources are partitioned among fuel combustion (fossil fuel and biofuel), biomass burning and soils by exploiting the spatio-temporal distribution of remotely sensed fires and a priori information on the location of regions dominated by fuel combustion. The top-down inventory is combined with an a priori inventory to obtain an optimized a posteriori estimate of the relative roles of NOx sources. The resulting a posteriori fuel combustion inventory (25.6 TgN year(-1)) agrees closely with the a priori (25.4 TgN year(-1)), and errors are reduced by a factor of 2, from +/- 80% to +/- 40%. Regionally, the largest differences are found over Japan and South Africa, where a posteriori estimates are 25% larger than a priori. A posteriori fuel combustion emissions are aseasonal, with the exception of East Asia and Europe where winter emissions are 30-40% larger relative to summer emissions, consistent with increased energy use during winter for heating. Global a posteriori biomass burning emissions in 2000 resulted in 5.8 TgN (compared to 5.9 TgN year(-1) in the a priori), with Africa accounting for half of this total. A posteriori biomass burning emissions over Southeast Asia/India are decreased by 46% relative to a priori; but over North equatorial Africa they are increased by 50%. A posteriori estimates of soil emissions (8.9 TgN year(-1)) are 68% larger than a priori (5.3 TgN year(-1)). The a posteriori inventory displays the largest soil emissions over tropical savanna/woodland ecosystems (Africa), as well as over agricultural regions in the western U.S. (Great Plains), southern Europe (Spain, Greece, Turkey), and Asia (North China Plain and North India), consistent with field measurements. Emissions over these regions are highest during summer at mid-latitudes and during the rainy season in the Tropics. We estimate that 2.5-4.5 TgN year(-1) are emitted from N-fertilized soils, at the upper end of previous estimates. Soil and biomass burning emissions account for 22% and 14% of global surface NOx emissions, respectively. We infer a significant role for soil NOx emissions at northern mid-latitudes during summer, where they account for nearly half that of the fuel combustion source, a doubling relative to the a priori. The contribution of soil emissions to background ozone is thus likely to be underestimated by the current generation of chemical transport models.

Mapping tropospheric ozone profiles from an airborne ultraviolet-visible spectrometer.

We present a novel technique for retrieving ozone (O3) profiles and especially tropospheric O3 from airborne UV/visible spectrometer measurements. This technique utilizes radiance spectra from one down-looking and two up-looking (85 degrees and 75 degrees) directions, taking advantage of the O3 absorption structure in the Huggins (300-340-nm) and Chappuis (530-650-nm) bands. This technique is especially sensitive to tropospheric O3 below and < or =8 km above the aircraft with a vertical resolution of 2-6 km and is sensitive to lower and middle stratospheric O3 with a vertical resolution of 8-15 km. It can measure tropospheric O3 at spatial resolutions of 2 km x 2 km or higher and is therefore well suited for regional air-quality studies and validation of satellite measurements.