Deep learning-based downscaling of tropospheric nitrogen dioxide using ground-level and satellite observations

Air quality is one of the major issues within an urban area that affect people's living environment and health conditions. Existing observations are not adequate to provide a spatiotemporally comprehensive air quality information for vulnerable populations to plan ahead. Launched in 2017, TROPOspheric Monitoring Instrument (TROPOMI) provides a high spatial resolution (~5 km) tropospheric air quality measurement that captures the spatial variability of air pollution, but still limited by its daily overpass in the temporal dimension and relatively short historical records. Integrating with the hourly available AirNOW observations by ground-level discrete stations, we proposed and compared two deep learning methods that learn the relationship between the ground-level nitrogen dioxide (NO₂) observation from AirNOW and the tropospheric NO₂ column density from TROPOMI to downscale the daily NO₂ to an hourly resolution. The input predictors include the locations of AirNOW stations, AirNOW NO₂ observations, boundary layer height, other meteorological status, elevation, major roads, and power plants. The learned relationship can be used to produce NO₂ emission estimates at the sub-urban scale on an hourly basis. The two methods include 1) an integrated method between inverse weighted distance and a feed forward neural network (IDW + DNN), and 2) a deep matrix network (DMN) that maps the discrete AirNOW observations directly to the distribution of TROPOMI observations. We further compared the accuracies of both models using different configurations of input predictors and validated their average Root Mean Squared Error (RMSE), average Mean Absolute Error (MAE) and the spatial distribution of errors. Results show that DMN generates more reliable NO₂ estimates and captures a better spatial distribution of NO₂ concentrations than the IDW + DNN model.

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.

Comparison and Validation of TROPOMI and OMI NO2 Observations over China

The new-generation sensor TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel 5 precursor (S5P) satellite is promising for monitoring air pollutants with greater spatial resolution, especially for China, which suffers from severe pollution. As tropospheric NO2 vertical column densities (VCDs) from TROPOMI have become available since February 2018, this study presents the comparisons of NO2 data measured by TROPOMI and its predecessor Ozone Monitoring Instrument (OMI) over China, together with validation against ground Multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements. At the nationwide scale, we used two different filters performed for the TROPOMI data (named TROPOMI50 and TROPOMI75), and the TROPOMI50 yielded larger values than TROPOMI75. The TROPOMI NO2 datasets from different filters show consistent spatial patterns with OMI, and the correlation coefficient values were both above 0.93. However, linear regression indicates that NO2 loadings in TROPOMI is about 2/3 to 4/5 of those in OMI, which is presumably due to a different cloud mask and uncertainties of air mass factors. The absolute difference is prominent over the high pollution areas such as Jing-Jin-Ji region and during winter and autumn, exceeding 0.6 × 1016 molecules cm−2 (molec cm−2). However, the NO2 concentrations retrieved from TROPOMI50 in the southern China may be somewhat higher than OMI. When it comes to the local-scale Jing-Jin-Ji hotspot, the analysis focuses on a comparison to TROPOMI75. TROPOMI manifests high quality and exhibits a significantly better performance of representing spatial variability. In contrast, OMI shows fewer effective pixels and does a poor job of capturing local details due to its row anomaly and low resolution. The absolute difference between two datasets shows the same seasonal behavior with NO2 variation, which is most striking in the winter (0.31 × 1016 molec cm−2) and is lowest in the summer (0.05 × 1016 molec cm−2). Furthermore, the ground MAX-DOAS instrument in Xianghe station, the representative site in Jing-Jin-Ji, is used to assess the skill of satellite retrievals. It turns out that both OMI and TROPOMI underestimate the observations, ranging from 30% to 50%, with OMI being less biased. In spite of the negative drift, the temporal structures of changes derived from OMI and TROPOMI closely match the ground-based records, since the correlation coefficients are above 0.8 and 0.95 for daily and monthly scales, respectively. Overall, TROPOMI NO2 retrievals are better suited for applications in China as well as the Jing-Jin-Ji hotspot due to its higher spatial resolution, although some improvements are also needed in the near future.

The Spatial–Temporal Variation of Tropospheric NO2 over China during 2005 to 2018

In recent years, new and strict air quality regulations have been implemented in China. Therefore, it is of great significance to evaluate the current air pollution situation and effectiveness of actions. In this study, Ozone Monitoring Instrument (OMI) satellite data were used to detect the spatiotemporal characteristics of tropospheric NO2 columns over China from 2005 to 2018, including spatial distribution, seasonal cycles and long-term trends. The averaged NO2 pollution is higher in southeastern China and lower in the northwest, which are well delineated by the Heihe–Tengchong line. Furthermore, the NO2 loadings are highest in the North China Plain, with vertical column density (VCD) exceeding 13 × 1015 molec cm−2. Regarding the seasonal cycle, the NO2 loadings in eastern China is highest in winter and lowest in summer, while the western region shows the opposite feature. The amplitude of annual range increase gradually from the south to the north. If the entire period of 2005–2018 is taken into account, China has experienced little change in NO2. In fact, however, there appears to be significant trends of an increase followed by a downward tendency, with the turning point in the year 2012. In the former episode of 2005–2012, increasing trends overwhelm nearly the whole nation, especially in the Jing–Jin–Tang region, Shandong Province, and Northern Henan and Southern Hebei combined regions, where the rising rates were as high as 1.0–1.8 × 1015 molec cm−2 year−1. In contrast, the latter episode of 2013–2018 features remarkable declines in NO2 columns over China. Particularly, the regions where the decreased degree was remarkable in 2013–2018 were consistent with the regions where the upward trend was obvious in 2005–2012. Overall, this upward–downward pattern is true for most parts of China. However, some of the largest metropolises, such as Beijing, Shanghai and Guangzhou, witnessed a continuous decrease in the NO2 amounts, indicating earlier and more stringent measures adopted in these areas. Finally, it can be concluded that China’s recent efforts to cut NO2 pollution are successful, especially in mega cities.

Long-Term Trends Worldwide in Ambient NO2 Concentrations Inferred from Satellite Observations

BACKGROUND

Air pollution is associated with morbidity and premature mortality. Satellite remote sensing provides globally consistent decadal-scale observations of ambient nitrogen dioxide (NO2) pollution.

OBJECTIVE

We determined global population-weighted annual mean NO2 concentrations from 1996 through 2012.

METHODS

We used observations of NO2 tropospheric column densities from three satellite instruments in combination with chemical transport modeling to produce a global 17-year record of ground-level NO2 at 0.1° × 0.1° resolution. We calculated linear trends in population-weighted annual mean NO2 (PWMNO2) concentrations in different regions around the world.

RESULTS

We found that PWMNO2 in high-income North America (Canada and the United States) decreased more steeply than in any other region, having declined at a rate of -4.7%/year [95% confidence interval (CI): -5.3, -4.1]. PWMNO2 decreased in western Europe at a rate of -2.5%/year (95% CI: -3.0, -2.1). The highest PWMNO2 occurred in high-income Asia Pacific (predominantly Japan and South Korea) in 1996, with a subsequent decrease of -2.1%/year (95% CI: -2.7, -1.5). In contrast, PWMNO2 almost tripled in East Asia (China, North Korea, and Taiwan) at a rate of 6.7%/year (95% CI: 6.0, 7.3). The satellite-derived estimates of trends in ground-level NO2 were consistent with regional trends inferred from data obtained from ground-station monitoring networks in North America (within 0.7%/year) and Europe (within 0.3%/year). Our rankings of regional average NO2 and long-term trends differed from the satellite-derived estimates of fine particulate matter reported elsewhere, demonstrating the utility of both indicators to describe changing pollutant mixtures.

CONCLUSIONS

Long-term trends in satellite-derived ambient NO2 provide new information about changing global exposure to ambient air pollution. Our estimates are publicly available at http://fizz.phys.dal.ca/~atmos/martin/?page_id=232.

Global inorganic nitrogen dry deposition inferred from ground- and space-based measurements

Atmospheric nitrogen (N) dry deposition is an important component in total N deposition. However, uncertainty exists in the assessment of global dry deposition. Here, we develop empirical models for estimating ground N concentrations using NO₂ satellite measurements from the Ozone Monitoring Instrument (OMI) and ground measurements from 555 monitoring sites. Global patterns and trends in the fluxes of NO₂, HNO₃, NH₄⁺, and NO₃⁻ were assessed for 2005–2014. Moreover, we estimated global NH₃ dry deposition directly using data from 267 monitoring sites. Our results showed that East Asia, the United States, and Europe were important regions of N deposition, and the total annual amount of global inorganic N deposition was 34.26 Tg N. The dry deposition fluxes were low in Africa and South America, but because of their large area, the total amounts in these regions were comparable to those in Europe and North America. In the past decade, the western United States and Eurasia, particularly eastern China, experienced the largest increases in dry deposition, whereas the eastern United States, Western Europe, and Japan experienced clear decreases through control of NO_x and NH₃ emissions. These findings provide a scientific background for policy-makers and future research into global changes.

High-resolution satellite-based analysis of ground-level PM2.5 for the city of Montreal

Satellite remote sensing offers the opportunity to determine the spatial distribution of aerosol properties and could fill the gap of ground-level observations. Various algorithms have recently been developed in order to retrieve the aerosol optical depth (AOD) at continental scales. However, they are, to some extent, subject to coarse spatial resolutions which are not appropriate for intraurban scales as usually needed in health studies. This paper presents an improved AOD retrieval algorithm for satellite instrument MODIS at 1-km resolution for intraurban scales. The MODIS-retrieved AODs are used to derive the ground-level PM2.5 concentrations using the aerosol vertical profiles and local scale factors obtained from the GEOS-Chem model simulation. The developed method has been applied to retrieve the AODs and to evaluate the ground-level PM2.5 over the city of Montreal, Canada for 2009 on daily, monthly and annual scales. The daily and monthly results are compared with the monitoring values with correlations R(2) ranging from 0.86 to 0.93. Especially, the annual mean PM2.5 concentrations are in good agreement with the measurement values at all monitoring stations (r=0.96, slope=1.0132 ± 0.0025, intercept=0.5739 ± 0.0013). This illustrates that the developed AOD retrieval algorithm can be used to retrieve AODs at a higher spatial resolution than previous studies to further derive the regional full coverage PM2.5 results at finer spatial and temporal scales. The study results are useful in health risk assessment across this region.

Satellite observations of NO2 trend over Romania

Satellite-based measurements of atmospheric trace gases loading give a realistic image of atmospheric pollution at global, regional, and urban level. The aim of this paper is to investigate the trend of atmospheric NO2 content over Romania for the period 1996-2010 for several regions which are generally characterized by different pollutant loadings, resulting from GOME-1, SCIAMACHY, OMI, and GOME-2 instruments. Satellite results are then compared with ground-based in situ measurements made in industrial and relatively clean areas of one major city in Romania. This twofold approach will help in estimating whether the trend of NO2 obtained by means of data satellite retrievals can be connected with the evolution of national industry and transportation.

Remote sensing of particulate pollution from space: have we reached the promised land?

The recent literature on satellite remote sensing of air quality is reviewed. 2009 is the 50th anniversary of the first satellite atmospheric observations. For the first 40 of those years, atmospheric composition measurements, meteorology, and atmospheric structure and dynamics dominated the missions launched. Since 1995, 42 instruments relevant to air quality measurements have been put into orbit. Trace gases such as ozone, nitric oxide, nitrogen dioxide, water, oxygen/tetraoxygen, bromine oxide, sulfur dioxide, formaldehyde, glyoxal, chlorine dioxide, chlorine monoxide, and nitrate radical have been measured in the stratosphere and troposphere in column measurements. Aerosol optical depth (AOD) is a focus of this review and a significant body of literature exists that shows that ground-level fine particulate matter (PM2.5) can be estimated from columnar AOD. Precision of the measurement of AOD is +/-20% and the prediction of PM2.5 from AOD is order +/-30% in the most careful studies. The air quality needs that can use such predictions are examined. Satellite measurements are important to event detection, transport and model prediction, and emission estimation. It is suggested that ground-based measurements, models, and satellite measurements should be viewed as a system, each component of which is necessary to better understand air quality.

Satellite derived trends in NO2 over the major global hotspot regions during the past decade and their inter-comparison

We assessed satellite derived tropospheric NO(2) distribution on a global scale and identified the major NO(2) hotspot regions. Combined GOME and SCIAMACHY measurements for the period 1996-2006 have been used to compute the trends over these regions. Our analysis shows that tropospheric NO(2) column amounts have increased over the newly and rapidly developing regions like China (11+/-2.6%/year), south Asia (1.76+/-1.1%/year), Middle East (2.3+/-1%/year) and South Africa (2.4+/-2.2%/year). Tropospheric NO(2) column amounts show some decrease over the eastern US (-2+/-1.5%/year) and Europe (0.9+/-2.1%/year). We found that although tropospheric NO(2) column amounts decreased over the major developed regions in the past decade, the present tropospheric NO(2) column amounts over these regions are still significantly higher than those observed over newly and rapidly developing regions (except China). Tropospheric NO(2) column amounts show some decrease over South America and Central Africa, which are major biomass burning regions in the Southern Hemisphere.