Ozone Monitoring Instrument NO2 Columns Research Articles

Long-term variations of ground-level NO2 concentrations along coastal areas in China

The long-term trends of the ground-level NO2 concentrations over coastal areas in China were analysed from 2007 to 2019 in this study, based on the measurements from Ozone Monitoring Instrument (OMI) and the simulations from the Model for Ozone and Related Chemical Tracers (MOZART)-4. Multiple Gaussian functions were used to simulate the atmospheric profiles of NO2 concentrations from the MOZART-4, and the ratio of the ground-level concentrations to the columns estimated from this Gaussian function was used to convert the OMI NO2 columns to that at the ground level. The estimation results showed that the ground-level NO2 concentrations were well consistent with those of ground measurements in 2017 (the correlation coefficients ranging from 0.84 to 0.87 in the four seasons). The NO2 concentrations presented an increasing rate of 0.6 μg/m3/yr during 2007–2011 and then a decreasing rate of 0.5 μg/m3/yr until 2019. Most areas in the China Sea suffered from the maximum NO2 concentrations during 2011–2013. The temporal variations of NO2 over coastal lands were consistent with those over the ocean during 2007–2016, but they presented different after the implementation of coastal emission control area (ECA) policies in 2016. The ECA policies significantly decreased the NO2 concentrations in the Yangtze River Delta (the YRD) and the Bohai Rim, and they inhibited the increase of NO2 in the Pearl River Delta (the PRD). These results might be helpful in understanding the current situation of ground-level NO2 pollution over oceans and coastal land in China and provide guidance for further development of ECA policies.

European NO<sub><i>x</i></sub> emissions in WRF-Chem derived from OMI: impacts on summertime surface ozone

Abstract. Ozone (O3) is a secondary air pollutant that negatively affects human and ecosystem health. Ozone simulations with regional air quality models suffer from unexplained biases over Europe, and uncertainties in the emissions of ozone precursor group nitrogen oxides (NOx=NO+NO2) contribute to these biases. The goal of this study is to use NO2 column observations from the Ozone Monitoring Instrument (OMI) satellite sensor to infer top-down NOx emissions in the regional Weather Research and Forecasting model with coupled chemistry (WRF-Chem) and to evaluate the impact on simulated surface O3 with in situ observations. We first perform a simulation for July 2015 over Europe and evaluate its performance against in situ observations from the AirBase network. The spatial distribution of mean ozone concentrations is reproduced satisfactorily. However, the simulated maximum daily 8 h ozone concentration (MDA8 O3) is underestimated (mean bias error of −14.2 µg m−3), and its spread is too low. We subsequently derive satellite-constrained surface NOx emissions using a mass balance approach based on the relative difference between OMI and WRF-Chem NO2 columns. The method accounts for feedbacks through OH, NO2's dominant daytime oxidant. Our optimized European NOx emissions amount to 0.50 Tg N (for July 2015), which is 0.18 Tg N higher than the bottom-up emissions (which lacked agricultural soil NOx emissions). Much of the increases occur across Europe, in regions where agricultural soil NOx emissions dominate. Our best estimate of soil NOx emissions in July 2015 is 0.1 Tg N, much higher than the bottom-up 0.02 Tg N natural soil NOx emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN). A simulation with satellite-updated NOx emissions reduces the systematic bias between WRF-Chem and OMI NO2 (slope =0.98, r2=0.84) and reduces the low bias against independent surface NO2 measurements by 1.1 µg m−3 (−56 %). Following these NOx emission changes, daytime ozone is strongly affected, since NOx emission changes particularly affect daytime ozone formation. Monthly averaged simulated daytime ozone increases by 6.0 µg m−3, and increases of >10 µg m−3 are seen in regions with large emission increases. With respect to the initial simulation, MDA8 O3 has an improved spatial distribution, expressed by an increase in r2 from 0.40 to 0.53, and a decrease of the mean bias by 7.4 µg m−3 (48 %). Overall, our results highlight the dependence of surface ozone on its precursor NOx and demonstrate that simulations of surface ozone benefit from constraining surface NOx emissions by satellite NO2 column observations.

Long-term (2005–2015) trends analysis of OMI retrieved NO2 columns in Taiwan

In this study, the monthly data retrieved from the Ozone Monitoring Instrument (OMI) have been used to estimate long-term trends of NO2 (2005–2015) in the entire Taiwan as well as in five representative city areas of Taiwan. The long-term NO2 data have been used for trend analysis and evaluated to find the extent of the effects of NOx emission reduction and related environmental regulations on the NO2 trend. Desirable policies and strategies for further reducing NOx emission have been also discussed. The corresponding reductions are 15–37% for the five city areas and 24% for the entire Taiwan over the 10-yr span. Clearly, the governmental policies/measures enacted during this 10-yr period are responsible for the reduction of tropospheric NO2 column values. The OMI NO2 column values of four cities (i.e., Taipei, Taichung, Kaohsiung, and Douliu) are relatively highly correlated (r = 0.70–0.95), indicating the cities have similar emission sources. Furthermore, the correlations between observed OMI NO2 columns and their emission NOx are all significant in the three metropolitan cities and the entire Taiwan (r = 0.66–0.89). The correlation of OMI-based NO2 VCDs and ground-based NO2 levels is high in Kaohsiung (r = 0.82) and moderate in Taipei and Taichung (r = 0.60 and 0.59, respectively). The satellite retrieved OMI NO2 data clearly indicate their usefulness in evaluating decreasing trend of the NO2, a precursor gas of PM2.5 during the 10-yr span for the entire region of Taiwan and for the selected five cities.

Emissions of nitrogen oxides from US urban areas: estimation from Ozone Monitoring Instrument retrievals for 2005–2014

Abstract. Satellite remote sensing of tropospheric nitrogen dioxide (NO2) can provide valuable information for estimating surface nitrogen oxides (NOx) emissions. Using an exponentially modified Gaussian (EMG) method and taking into account the effect of wind on observed NO2 distributions, we estimate 3-year moving-average emissions of summertime NOx from 35 US (United States) urban areas directly from NO2 retrievals of the Ozone Monitoring Instrument (OMI) during 2005–2014. Following conclusions of previous studies that the EMG method provides robust and accurate emission estimates under strong-wind conditions, we derive top-down NOx emissions from each urban area by applying the EMG method to OMI data with wind speeds greater than 3–5 m s−1. Meanwhile, we find that OMI NO2 observations under weak-wind conditions (i.e., < 3 m s−1) are qualitatively better correlated to the surface NOx source strength in comparison to all-wind OMI maps; therefore, we use them to calculate the satellite-observed NO2 burdens of urban areas and compare with NOx emission estimates. The EMG results show that OMI-derived NOx emissions are highly correlated (R > 0.93) with weak-wind OMI NO2 burdens as well as with bottom-up NOx emission estimates over 35 urban areas, implying a linear response of the OMI observations to surface emissions under weak-wind conditions. The simultaneous EMG-obtained effective NO2 lifetimes (~ 3.5 ± 1.3 h), however, are biased low in comparison to the summertime NO2 chemical lifetimes. In general, isolated urban areas with NOx emission intensities greater than ~ 2 Mg h−1 produce statistically significant weak-wind signals in 3-year average OMI data. From 2005 to 2014, we estimate that total OMI-derived NOx emissions over all selected US urban areas decreased by 49 %, consistent with reductions of 43, 47, 49, and 44 % in the total bottom-up NOx emissions, the sum of weak-wind OMI NO2 columns, the total weak-wind OMI NO2 burdens, and the averaged NO2 concentrations, respectively, reflecting the success of NOx control programs for both mobile sources and power plants. The decrease rates of these NOx-related quantities are found to be faster (i.e., −6.8 to −9.3 % yr−1) before 2010 and slower (i.e., −3.4 to −4.9 % yr−1) after 2010. For individual urban areas, we calculate the R values of pair-wise trends among the OMI-derived and bottom-up NOx emissions, the weak-wind OMI NO2 burdens, and ground-based NO2 measurements, and high correlations are found for all urban areas (median R= 0.8), particularly large ones (R up to 0.97). The results of the current work indicate that using the EMG method and considering the wind effect, the OMI data allow for the estimation of NOx emissions from urban areas and the direct constraint of emission trends with reasonable accuracy.

Assessment of the magnitude and recent trends in satellite-derived ground-level nitrogen dioxide over North America

We estimate ground-level nitrogen dioxide (NO2) concentrations from the OMI (Ozone Monitoring Instrument) over North America for the period 2005–2012. A chemical transport model (GEOS-Chem) is used to account for effects of the NO2 profile on the column retrieval, and to relate OMI NO2 columns to ground-level concentrations. The magnitude of the period-mean OMI-derived NO2 concentrations is evaluated versus in situ measurements from air quality networks yielding a significant spatial correlation (r = 0.81) but OMI-derived values are lower with a slope of 0.4. Comparison of the in situ concentrations versus spatially resolved concentrations estimated from land use regression models reveals that this difference partially arises from representativeness difference due to preferential placement of in situ monitors at locations with enhanced NO2, coupled with the OMI horizontal resolution. In situ observations provide information about local concentrations while OMI offers area-averaged information. The remaining difference is less readily explained and appears to include a combination of the effects of local unresolved geophysical processes affecting both the NO2 retrieval and the vertical profile used to relate the column to ground level. We also evaluate trends over North America from OMI and in situ measurements for the period of 2005–2012. OMI derived ground-level NO2 well reproduces the spatial pattern of the in situ trends (r = 0.77) and the slope of 0.4 versus the trend from in situ monitors is consistent with the slope versus mean concentrations. Absolute regional trends inferred from in situ measurements alone may overestimate area average changes. Nonetheless coincidently sampled ground-level NO2 concentrations from OMI and in situ measurements for 2005–2012 exhibit similar relative decreases over Eastern (−6.5 ± 2.0%/yr, −7.1 ± 1.3%/yr), Western (−4.5 ± 1.1%/yr, −6.5 ± 0.7%/yr) and Central (−3.3 ± 2.3%/yr, −4.1 ± 0.8%/yr) North America.

Evaluating NOx emission inventories for regulatory air quality modeling using satellite and air quality model data

The purpose of this study was to assess the accuracy of NOx emissions in the Texas Commission on Environmental Quality's (TCEQ) State Implementation Plan (SIP) modeling inventories of the southeastern U.S. We used retrieved satellite tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI) together with NO2 columns from the Comprehensive Air Quality Model with Extensions (CAMx) to make top–down NOx emissions estimates using the mass balance method. Two different top–down NOx emissions estimates were developed using the KNMI DOMINO v2.0 and NASA SP2 retrievals of OMI NO2 columns. Differences in the top–down NOx emissions estimates made with these two operational products derived from the same OMI radiance data were sufficiently large that they could not be used to constrain the TCEQ NOx emissions in the southeast. The fact that the two available operational NO2 column retrievals give such different top–down NOx emissions results is important because these retrievals are increasingly being used to diagnose air quality problems and to inform efforts to solve them. These results reflect the fact that NO2 column retrievals are a blend of measurements and modeled data and should be used with caution in analyses that will inform policy development. This study illustrates both benefits and challenges of using satellite NO2 data for air quality management applications. Comparison with OMI NO2 columns pointed the way toward improvements in the CAMx simulation of the upper troposphere, but further refinement of both regional air quality models and the NO2 column retrievals is needed before the mass balance and other emission inversion methods can be used to successfully constrain NOx emission inventories used in U.S. regulatory modeling.

Changes in nitrogen oxides emissions in California during 2005–2010 indicated from top‐down and bottom‐up emission estimates

AbstractIn California, emission control strategies have been implemented to reduce air pollutants. Here we estimate the changes in nitrogen oxides (NOx = NO + NO2) emissions in 2005–2010 using a state‐of‐the‐art four‐dimensional variational approach. We separately and jointly assimilate surface NO2 concentrations and tropospheric NO2 columns observed by Ozone Monitoring Instrument (OMI) into the regional‐scale Sulfur Transport and dEposition Model (STEM) chemical transport model on a 12 × 12 km2 horizontal resolution grid in May 2010. The assimilation generates grid‐scale top‐down emission estimates, and the updated chemistry fields are evaluated with independent aircraft measurements during the NOAA California Nexus (CalNex) field experiment. The emission estimates constrained only by NO2 columns, only by surface NO2, and by both indicate statewide reductions of 26%, 29%, and 30% from ~0.3 Tg N/yr in the base year of 2005, respectively. The spatial distributions of the emission changes differ in these cases, which can be attributed to many factors including the differences in the observation sampling strategies and their uncertainties, as well as those in the sensitivities of column and surface NO2 with respect to NOx emissions. The updates in California's NOx emissions reduced the mean error in modeled surface ozone in the Western U.S., even though the uncertainties in some urban areas increased due to their NOx‐saturated chemical regime. The statewide reductions in NOx emissions indicated from our observationally constrained emission estimates are also reflected in several independently developed inventories: ~30% in the California Air Resources Board bottom‐up inventory, ~4% in the 2008 National Emission Inventory, and ~20% in the annual mean top‐down estimates by Lamsal et al. using the global Goddard Earth Observing System (GEOS)‐Chem model and OMI NO2 columns. Despite the grid‐scale differences among all top‐down and bottom‐up inventories, they all indicate stronger emission reductions in the urban regions. This study shows the potential of using space‐/ground‐based monitoring data and advanced data assimilation approach to timely and independently update NOx emission estimates on a monthly scale and at a fine grid resolution. The well‐evaluated results here suggest that these approaches can be applied more broadly.

Worldwide biogenic soil NO<sub>x</sub> emissions inferred from OMI NO<sub>2</sub> observations

Abstract. Biogenic NOx emissions from soils are a large natural source with substantial uncertainties in global bottom-up estimates (ranging from 4 to 15 Tg N yr−1). We reduce this range in emission estimates, and present a top-down soil NOx emission inventory for 2005 based on retrieved tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). We use a state-of-science soil NOx emission inventory (Hudman et al., 2012) as a priori in the GEOS-Chem chemistry transport model to identify 11 regions where tropospheric NO2 columns are dominated by soil NOx emissions. Strong correlations between soil NOx emissions and simulated NO2 columns indicate that spatial patterns in simulated NO2 columns in these regions indeed reflect the underlying soil NOx emissions. Subsequently, we use a mass-balance approach to constrain emissions for these 11 regions on all major continents using OMI observed and GEOS-Chem simulated tropospheric NO2 columns. We find that responses of simulated NO2 columns to changing NOx emissions are suppressed over low NOx regions, and account for these non-linearities in our inversion approach. In general, our approach suggests that emissions need to be increased in most regions. Our OMI top-down soil NOx inventory amounts to 10.0 Tg N for 2005 when only constraining the 11 regions, and 12.9 Tg N when extrapolating the constraints globally. Substantial regional differences exist (ranging from −40% to +90%), and globally our top-down inventory is 4–35% higher than the GEOS-Chem a priori (9.6 Tg N yr−1). We evaluate NO2 concentrations simulated with our new OMI top-down inventory against surface NO2 measurements from monitoring stations in Africa, the USA and Europe. Although this comparison is complicated by several factors, we find an encouraging improved agreement when using the OMI top-down inventory compared to using the a priori inventory. To our knowledge, this study provides, for the first time, specific constraints on soil NOx emissions on all major continents using OMI NO2 columns. Our results rule out the low end of reported soil NOx emission estimates, and suggest that global emissions are most likely around 12.9 ± 3.9 Tg N yr−1.

Scaling Relationship for NO2Pollution and Urban Population Size: A Satellite Perspective

Concern is growing about the effects of urbanization on air pollution and health. Nitrogen dioxide (NO2) released primarily from combustion processes, such as traffic, is a short-lived atmospheric pollutant that serves as an air-quality indicator and is itself a health concern. We derive a global distribution of ground-level NO2 concentrations from tropospheric NO2 columns retrieved from the Ozone Monitoring Instrument (OMI). Local scaling factors from a three-dimensional chemistry-transport model (GEOS-Chem) are used to relate the OMI NO2 columns to ground-level concentrations. The OMI-derived surface NO2 data are significantly correlated (r = 0.69) with in situ surface measurements. We examine how the OMI-derived ground-level NO2 concentrations, OMI NO2 columns, and bottom-up NOx emission inventories relate to urban population. Emission hot spots, such as power plants, are excluded to focus on urban relationships. The correlation of surface NO2 with population is significant for the three countries and one continent examined here: United States (r = 0.71), Europe (r = 0.67), China (r = 0.69), and India (r = 0.59). Urban NO2 pollution, like other urban properties, is a power law scaling function of the population size: NO2 concentration increases proportional to population raised to an exponent. The value of the exponent varies by region from 0.36 for India to 0.66 for China, reflecting regional differences in industrial development and per capita emissions. It has been generally established that energy efficiency increases and, therefore, per capita NOx emissions decrease with urban population; here, we show how outdoor ambient NO2 concentrations depend upon urban population in different global regions.

Indirect validation of tropospheric nitrogen dioxide retrieved from the OMI satellite instrument: Insight into the seasonal variation of nitrogen oxides at northern midlatitudes

We examine the seasonal variation in lower tropospheric nitrogen oxides (NOx = NO + NO2) at northern midlatitudes by evaluating tropospheric NO2 columns observed from the Ozone Monitoring Instrument (OMI) satellite instrument with surface NO2 measurements (SouthEastern Aerosol Research and Characterization and Air Quality System) and current bottom‐up NOx emission inventories, using a global model of tropospheric chemistry (GEOS‐Chem). The standard (SP) and DOMINO (DP) tropospheric NO2 column products from OMI exhibit broadly similar spatial and seasonal variation, but differ substantially over continental source regions. A comparison of the two OMI tropospheric NO2 products with in situ surface NO2 concentrations and bottom‐up NOx emissions over the southeast United States indicates that annual mean NO2 columns from the DP are biased high by 21%–33% and those from the SP are biased high by 27%–43%. The bias in SP columns is highly seasonal, 67%–74% in summer compared with −6% to −1% in winter. Similar seasonal differences exist between top‐down and bottom‐up NOx emission inventories over North America, Europe, and East Asia. The air mass factor largely explains the observed seasonal difference between the DP and SP, and in turn the seasonal SP bias. We develop a third product (DP_GC) using averaging kernel information from the DP and NO2 vertical profiles from GEOS‐Chem. This product reduces to 5%–21% the annual mean bias over the southeast United States. We use the seasonal variation in the DP_GC to estimate the seasonal variation in the lifetime of lower tropospheric NOx against oxidation to HNO3 over the eastern United States. The effective NOx lifetime at OMI overpass time (early afternoon) ranges from 7.6 h in summer to 17.8 h in winter, consistent within 3 h of the simulated lifetime. GEOS‐Chem calculations reveal that the seasonal variation in OMI NO2 columns largely reflects gas‐phase oxidation of NO2 in summer with an increasing role for heterogenous chemistry in winter.

Validation of Ozone Monitoring Instrument NO2 measurements using ground based NO2 measurements at Zvenigorod, Russia

We present the results of comparison between Ozone Monitoring Instrument (OMI) data of NO2 measurements (Collection 3) onboard the NASA EOS-Aura satellite and correlative ground-based twilight measurements at Zvenigorod station in Russia in 2004–2008. Compared quantities are unpolluted column and tropospheric column amounts of NO2 which are standard products of OMI measurements. The NO2 columns observed by our ground-based instrument have been interpolated to the time of OMI measurements using a one-dimensional photochemical model. According to our comparison, the OMI unpolluted NO2 columns underestimate ground-based measurements by (0.084 ± 0.025) × 1015 molecules/cm2, or (3.2 ± 0.9)%. The correlation coefficient between the OMI and ground-based unpolluted NO2 columns is 0.92. The tropospheric NO2 columns derived from OMI measurements are on average by (1.8 ± 0.5) × 1015 cm−2, or approximately 40%, less than those derived from ground-based measurements. The correlation coefficient between these data is about 0.3. Reasons for this discrepancy are discussed.

NO2columns in the western United States observed from space and simulated by a regional chemistry model and their implications for NOxemissions

There are many isolated sources of NOxemissions across the western United States, including electrical power generation plants and urban areas. In this manuscript, two satellite instruments measuring NO2vertical columns over these sources and an atmospheric chemical‐transport model are used to evaluate bottom‐up NOxemission inventories, model assumptions, and satellite retrieval algorithms. We carried out simulations with the Weather Research and Forecasting‐Chemistry (WRF‐Chem) model for the western U.S. domain during the summer of 2005 using measured power plant NOxemissions. Model NO2vertical columns are compared with a retrieval of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite instrument data by the University of Bremen and retrievals of the Ozone Monitoring Instrument (OMI) data by the U.S. National Aeronautics and Space Administration (NASA) and a modified version of the NASA OMI retrieval produced by the University of Bremen. For areas dominated by power plant NOxemissions, the model NO2columns serve as a comparison standard for satellite retrievals because emissions are continuously monitored at all large U.S. power plants. An extensive series of sensitivity tests of the assumptions in both the satellite retrievals and the model are carried out over the Four Corners and San Juan power plants, two adjacent facilities in the northwest corner of New Mexico that together represent the largest NOxpoint source in the United States. Overall, the SCIAMACHY and OMI NO2columns over western U.S. power plants agree well with model NO2columns, with differences between the two being within the variability of the model and satellite. In contrast to regions dominated by power plant emissions, model NO2columns over large urban areas along the U.S. west coast are approximately twice as large as satellite NO2columns from SCIAMACHY and OMI retrievals. The discrepancies in urban areas are beyond the sensitivity ranges in the model simulations and satellite observations, implying overestimates of these cities' bottom‐up NOxemissions, which are dominated by motor vehicles. Taking the uncertainties in the satellite retrievals into account, our study demonstrates that the tropospheric columns of NO2retrieved from space‐based observations of backscattered solar electromagnetic radiation can be used to evaluate and improve bottom‐up emission inventories.