COVID-19 perturbation on US air quality and human health impact assessment.

The COVID-19 stay-at-home orders issued in the United States caused significant reductions in traffic and economic activities. To understand the pandemic's perturbations on US emissions and impacts on urban air quality, we developed near-real-time bottom-up emission inventories based on publicly available energy and economic datasets, simulated the emission changes in a chemical transport model, and evaluated air quality impacts against various observations. The COVID-19 pandemic affected US emissions across broad-based energy and economic sectors and the impacts persisted to 2021. Compared with 2019 business-as-usual emission scenario, COVID-19 perturbations resulted in annual decreases of 10-15% in emissions of ozone (O3) and fine particle (PM2.5) gas-phase precursors, which are about two to four times larger than long-term annual trends during 2010-2019. While significant COVID-induced reductions in transportation and industrial activities, particularly in April-June 2020, resulted in overall national decreases in air pollutants, meteorological variability across the nation led to local increases or decreases of air pollutants, and mixed air quality changes across the United States between 2019 and 2020. Over a full year (April 2020 to March 2021), COVID-induced emission reductions led to 3-4% decreases in national population-weighted annual fourth maximum of daily maximum 8-h average O3 and annual PM2.5. Assuming these emission reductions could be maintained in the future, the result would be a 4-5% decrease in premature mortality attributable to ambient air pollution, suggesting that continued efforts to mitigate gaseous pollutants from anthropogenic sources can further protect human health from air pollution in the future.

An Inversion Framework for Optimizing Non-Methane VOC Emissions Using Remote Sensing and Airborne Observations in Northeast Asia During the KORUS-AQ Field Campaign.

We aim to reduce uncertainties in CH2O and other volatile organic carbon (VOC) emissions through assimilation of remote sensing data. We first update a three-dimensional (3D) chemical transport model, GEOS-Chem with the KORUSv5 anthropogenic emission inventory and inclusion of chemistry for aromatics and C2H4, leading to modest improvements in simulation of CH2O (normalized mean bias (NMB): -0.57 to -0.51) and O3 (NMB: -0.25 to -0.19) compared against DC-8 aircraft measurements during KORUS-AQ; the mixing ratio of most VOC species are still underestimated. We next constrain VOC emissions using CH2O observations from two satellites (OMI and OMPS) and the DC-8 aircraft during KORUS-AQ. To utilize data from multiple platforms in a consistent manner, we develop a two-step Hybrid Iterative Finite Difference Mass Balance and four-dimensional variational inversion system (Hybrid IFDMB-4DVar). The total VOC emissions throughout the domain increase by 47%. The a posteriori simulation reduces the low biases of simulated CH2O (NMB: -0.51 to -0.15), O3 (NMB: -0.19 to -0.06), and VOCs. Alterations to the VOC speciation from the 4D-Var inversion include increases of biogenic isoprene emissions in Korea and anthropogenic emissions in Eastern China. We find that the IFDMB method alone is adequate for reducing the low biases of VOCs in general; however, 4D-Var provides additional refinement of high-resolution emissions and their speciation. Defining reasonable emission errors and choosing optimal regularization parameters are crucial parts of the inversion system. Our new hybrid inversion framework can be applied for future air quality campaigns, maximizing the value of integrating measurements from current and upcoming geostationary satellite instruments.

Water vapor satellite products in the European Arctic: An inter-comparison against GNSS data.

The European Arctic is a region of high interest for climate change. Water vapor plays a fundamental role in global warming; therefore, high-quality water vapor monitoring is essential for assimilation in forecast simulations. The seven analyzed instruments on-board satellite platforms are: Atmospheric Infrared Sounder (AIRS), Global Ozone Monitoring Instrument 2 (GOME-2), Moderate-Resolution Imaging Spectroradiometer (MODIS), Ozone Monitoring Instrument (OMI), SCanning Imaging Absorption Spectrometer for Atmospheric Carthography (SCIAMACHY) and Polarization and Directionality of the Earth's Reflectances (POLDER). The GNSS data from Ny-Ålesund are matched to satellite observations of IWV in a 30-min temporal window, and 100-km radius. Then, statistics and the distribution of satellite-ground differences under different conditions are studied. The correlation coefficient (R2) with ground-based measurements is about 0.7 for all products except OMI (R2=0.5), and MODIS NIR and POLDER (R2=0.3). OMI shows high bias and variability compared to the rest of products. RMSE values are of the order of 3 mm for all satellites, except OMI (7 mm) and POLDER (5 mm). Bias (MBE) is negligible for AIRS, close to +1.6 mm for GOME-2 and MODIS IR, +0.8 mm for MODIS NIR, +5.9 mm for OMI, -2.7 mm for POLDER and -1.2 mm for SCIAMCHY. All satellite products tend to overestimate small IWV values and underestimate large IWV values. Variability also increases with IWV. An underestimation of the satellite products and an increase on the variability is generally observed for large Solar Zenith Angle (SZA) values. Under cloudy conditions, underestimation and variability are increased. Seasonal behavior is driven by the typical cloud cover (CC), SZA, and IWV values. In summer, it is typical to find conditions with large IWV, small SZA and large CC values. Therefore, in summer months satellite products are more biased (either positively or negatively) and with more variability, but in relative terms they are less biased and exhibit less variability.

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.

Mapping hydroxyl variability throughout the global remote troposphere via synthesis of airborne and satellite formaldehyde observations.

The hydroxyl radical (OH) fuels tropospheric ozone production and governs the lifetime of methane and many other gases. Existing methods to quantify global OH are limited to annual and global-to-hemispheric averages. Finer resolution is essential for isolating model deficiencies and building process-level understanding. In situ observations from the Atmospheric Tomography (ATom) mission demonstrate that remote tropospheric OH is tightly coupled to the production and loss of formaldehyde (HCHO), a major hydrocarbon oxidation product. Synthesis of this relationship with satellite-based HCHO retrievals and model-derived HCHO loss frequencies yields a map of total-column OH abundance throughout the remote troposphere (up to 70% of tropospheric mass) over the first two ATom missions (August 2016 and February 2017). This dataset offers unique insights on near-global oxidizing capacity. OH exhibits significant seasonality within individual hemispheres, but the domain mean concentration is nearly identical for both seasons (1.03 ± 0.25 × 106 cm-3), and the biseasonal average North/South Hemisphere ratio is 0.89 ± 0.06, consistent with a balance of OH sources and sinks across the remote troposphere. Regional phenomena are also highlighted, such as a 10-fold OH depression in the Tropical West Pacific and enhancements in the East Pacific and South Atlantic. This method is complementary to budget-based global OH constraints and can help elucidate the spatial and temporal variability of OH production and methane loss.

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.

Validation of integrated water vapor from OMI satellite instrument against reference GPS data at the Iberian Peninsula.

This paper shows the validation of integrated water vapor (IWV) measurements retrieved from the Ozone Monitoring Instrument (OMI), using as reference nine ground-based GPS stations in the Iberian Peninsula. The study period covers from 2007 to 2009. The influence of two factors, - solar zenith angle (SZA) and IWV -, on OMI-GPS differences was studied in detail, as well as the seasonal dependence. The pseudomedian of the relative differences is -1 ± 1% and the inter-quartile range (IQR) is 41%. Linear regressions calculated over each station show an acceptable agreement (R2 up to 0.77). The OMI-GPS differences display a clear dependence on IWV values. Hence, OMI substantially overestimates the lower IWV data recorded by GPS (∼ 40%), while underestimates the higher IWV reference values (∼ 20%). In connection to this IWV dependence, the relative differences also show an evident SZA dependence when the whole range of IWV values are analyzed (OMI overestimates for high SZA values while underestimates for low values). Finally, the seasonal variation of the OMI-GPS differences is also associated with the strong IWV dependence found in this validation exercise.

Spatiotemporal structure of a laser beam over 144 km in a Canary Islands experiment.

We analyzed the observations of scintillations in a laser beam (532 nm, ~200 mW power) traveling along a 144 km path at an altitude of 2.2-2.4 km above sea level, just above the atmospheric boundary layer, between the islands of La Palma and Tenerife. The observations were performed during nighttime on 18 July 2011, by means of a telescope with an aperture diameter of 1 m. Strong scintillations were observed. The estimates of spatial spectra and correlation functions indicated that the observed intensity fields possess, statistically, a locally isotropic structure, which agrees with the idea of a locally isotropic turbulence. The estimates of spatial autospectra and autocorrelation functions of the intensity field indicated that the characteristic scale of the internal structure of the observed clusters is 6.5-8 mm, while the characteristic size of the clusters is 4-5 cm. The major contribution to the observed scintillations comes from the inhomogeneities of the intensity field with scales from 1-2 cm up to 10-12 cm. The analysis of the cross-spectra indicated that the hypothesis of frozen turbulence introduced by Taylor can be used for the description of spatiotemporal structure of intensity fluctuations of laser beams traveling through long paths in the atmosphere.