Inferring the anthropogenic NO&amp;lt;sub&amp;gt;&amp;lt;i&amp;gt;x&amp;lt;/i&amp;gt;&amp;lt;/sub&amp;gt; emission trend over the United States during 2003–2017 from satellite observations: was there a flattening of the emission trend after the Great Recession?

Li, Jianfeng; Wang, Yuhang

doi:10.5194/acp-19-15339-2019

Cited by 18 publications

(28 citation statements)

References 61 publications

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“…Based on calculations by 17 using a regional model, β is estimated to increase by a factor of ~2.2 when decreasing the anthropogenic emission from ~160 • 10 10 molec.cm −2 s −1 to 20 • 10 10 molec.cm −2 s −1 ; this translates into a 22% increase in β for the estimated emission decrease between 2005-2007 and 2015-2017 (factor of 1.7 according to US EPA 18 , in line with recent assessments 17,19,20 ). This change in β is in excellent agreement with our model results (+20%).…”

supporting

confidence: 68%

“…This change in β is in excellent agreement with our model results (+20%). Only a small part of this change is due to chemical feedbacks, as pointed out by 17 . Using MAGRITTE model simulations for the years 2006 and 2016 (with identical meteorological fields and natural emissions for the two years in order to isolate the anthropogenic impact), we calculate that chemical feedbacks can increase β by only about 4-8% at the largest U.S. cities ( Supplementary Fig.…”

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confidence: 97%

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Satellite evidence for changes in the NO2 weekly cycle over large cities

Stavrakou

Müller

Bauwens

et al. 2020

Sci Rep

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Anthropogenic activities, by far the largest source of nox into the atmosphere, induce a weekly cycle of no 2 abundances in cities. Comprehensive analysis of the 2005-2017 OMI NO 2 dataset reveals significant weekly cycles in 115 of the 274 cities considered. These results are corroborated by a full year of highresolution tRopoMi no 2 observations. the oMi dataset permits us to identify trends in the weekly cycle resulting from nox emissions changes. the data show a clear weakening of the weekly cycle over european and U.S. cities, an evolution attributed to the decline in anthropogenic emissions and the resulting growing importance of background no 2 , whereas no 2 lifetime changes also play a minor role. in particular, the Sunday no 2 columns averaged over all U.S. cities are found to increase, relative to the weekly average, from 0.72 during 2005-2007 to 0.88 in 2015-2017. The opposite tendency is recorded in regions undergoing rapid emission growth. Multiyear simulations over the U.S. and the Middle east using the chemistry-transport model MAGRITTEv1.1 succeed in capturing the observed weekly cycles over the largest cities, as well as the observed long-term trends in the weekly cycle. Nitrogen oxides (NOx = NO 2 + NO) play a key role in atmospheric chemistry: they catalyse tropospheric ozone formation, they impact the self-cleaning capacity of the atmosphere, and they are precursors of secondary inorganic aerosol, with consequences for climate and human health 1. Fossil fuel combustion is the dominant source of NOx in the atmosphere, estimated at ~60% of the global total, whereas emissions from vegetation fires, lightning and soils make up the rest 2. Because of their relation to human activities, anthropogenic NOx emissions often display a weekly cycle, with reduced NOx levels in and around cities on rest days. Similar cycles have been also observed for other pollutants, e.g. aerosols 3,4 , and for meteorological parameters such as cloudiness 4,5. The NOx weekly cycle was previously investigated using ground-based, aircraft and satellite measurements 6-8 , whereas spatial patterns observed from satellites were used to study the urban photochemistry with the help of models 9. These studies, however, rely either on relatively short data records of at most several months 8,9 or on satellite data from coarse resolution sounders 6,7. Here we use NO 2 column data from two nadir-viewing satellite sensors, the Ozone Monitoring Instrument (OMI 10) launched in July 2004, and the high-resolution Tropospheric Monitoring Instrument (TROPOMI), single payload of the Sentinel-5 Precursor (S5P) launched in October 2017 11. Both sensors have an equatorial crossing time of ca. 13:40 (local time), and provide daily global coverage at resolutions of 13 × 24 km 2 and 7.2 × 3.5 km 2 (at nadir) for OMI and TROPOMI, respectively. The long data record compiled for this study (2005-2019) and the high resolution of both instruments allows to provide more robust information on the NO 2 weekly cycle over a larger number of cities around ...

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confidence: 68%

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confidence: 97%

Satellite evidence for changes in the NO2 weekly cycle over large cities

Stavrakou

Müller

Bauwens

et al. 2020

Sci Rep

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“…Constraining HCHO has a significant influence on the chemical production of CO and the trend in Inv2 (Zheng et al, 2019). Tropospheric columns of OMI HCHO have been reported to keep increasing over China, likely due to significant increases in NMVOC emissions (Li & Wang, 2019; Shen et al, 2019). This could explain why CO emission estimates continue to decrease in Inv2, while Inv1 flattens out since the optimized emissions are overestimated to compensate for the underestimation of CO photochemical production.…”

Section: Comparison Of Emission Inventories and Inverse Modeling Estimentioning

confidence: 99%

“…They suggest that increases in the relative contribution of non‐anthropogenic background sources of NO x (e.g., lightning and soils) explain the discrepancy between trends in OMI NO 2 and the NEI inventory. Furthermore, several studies have reported that in rural areas, strong nonlinear relationships exist between anthropogenic NO x emissions and satellite NO 2 columns, implying that constraining NO x emissions by NO 2 satellite retrievals might lead to inaccurate estimates (Lamsal et al, 2011; Li & Wang, 2019; Vinken et al, 2014). Laughner and Cohen (2019) reported changes in NO x lifetime for many U.S. cities and suggested that accounting for this change in lifetime more accurately (for example, by using models with higher resolution) should help to improve emission trend estimates.…”

Section: Comparison Of Emission Inventories and Inverse Modeling Estimentioning

confidence: 99%

Intercomparison of Magnitudes and Trends in Anthropogenic Surface Emissions From Bottom‐Up Inventories, Top‐Down Estimates, and Emission Scenarios

et al. 2020

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This study compares recent CO, NOx, NMVOC, SO2, BC, and OC anthropogenic emissions from several state‐of‐the‐art top‐down estimates to global and regional bottom‐up inventories and projections from five Shared Socioeconomic Pathways (SSPs) in several regions. Results show that top‐down emissions derived in several recent studies exhibit similar uncertainty as bottom‐up inventories in some regions for certain species and even less in the case of Chinese CO emissions. In general, the largest discrepancies are found outside of regions such as the United States, Europe, and Japan where the most accurate and detailed information on emissions is available. In some regions such as China, which has recently undergone dynamical economic growth and changes in air quality regulations, the top‐down estimates better capture recent emission trends than global bottom‐up inventories. These results show the potential of top‐down estimates to complement bottom‐up inventories and to aide in the development of emission scenarios, particularly in regions where global inventories lack the necessary up‐to‐date and accurate information regarding regional activity data and emission factors such as Africa and India. Areas of future work aimed at quantifying and reducing uncertainty are also highlighted. A regional comparison of recent CO and NOx trends in the five SSPs indicate that SSP126, a strong pollution control scenario, best represents the trends from the top‐down and regional bottom‐up inventories in the United States, Europe, and China, while SSP460, a low‐pollution control scenario, lies closest to actual trends in West Africa. This analysis can be useful for air quality forecasting and near‐future pollution control/mitigation policy studies.

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“…Some studies inferred NO x (Pison et al, 2007;Tang et al, 2013) and VOC emissions (Koohkan et al, 2013) from surface measurements. Konovalov et al (2006Konovalov et al ( , 2008Konovalov et al ( , 2010, Mijling et al (2012Mijling et al ( , 2013, van der A et al (2008), Lin et al (2012) and Ding et al (2017) have also shown that satellite observations are a suitable source of information to constrain NO x emissions. These regional inversions using satellite observations were often based on Kalman filter (KF) schemes (Mijling et al, 2012(Mijling et al, , 2013van der A et al, 2008;Lin et al, 2012;Ding et al, 2017).…”

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confidence: 99%

Variational regional inverse modeling of reactive species emissions with PYVAR-CHIMERE-v2019

et al. 2021

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Abstract. Up-to-date and accurate emission inventories for air pollutants are essential for understanding their role in the formation of tropospheric ozone and particulate matter at various temporal scales, for anticipating pollution peaks and for identifying the key drivers that could help mitigate their concentrations. This paper describes the Bayesian variational inverse system PYVAR-CHIMERE, which is now adapted to the inversion of reactive species. Complementarily with bottom-up inventories, this system aims at updating and improving the knowledge on the high spatiotemporal variability of emissions of air pollutants and their precursors. The system is designed to use any type of observations, such as satellite observations or surface station measurements. The potential of PYVAR-CHIMERE is illustrated with inversions of both carbon monoxide (CO) and nitrogen oxides (NOx) emissions in Europe, using the MOPITT and OMI satellite observations, respectively. In these cases, local increments on CO emissions can reach more than +50 %, with increases located mainly over central and eastern Europe, except in the south of Poland, and decreases located over Spain and Portugal. The illustrative cases for NOx emissions also lead to large local increments (> 50 %), for example over industrial areas (e.g., over the Po Valley) and over the Netherlands. The good behavior of the inversion is shown through statistics on the concentrations: the mean bias, RMSE, standard deviation, and correlation between the simulated and observed concentrations. For CO, the mean bias is reduced by about 27 % when using the posterior emissions, the RMSE and the standard deviation are reduced by about 50 %, and the correlation is strongly improved (0.74 when using the posterior emissions against 0.02); for NOx, the mean bias is reduced by about 24 % and the RMSE and the standard deviation are reduced by about 7 %, but the correlation is not improved. We reported strong non-linear relationships between NOx emissions and satellite NO2 columns, now requiring a fully comprehensive scientific study.

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Inferring the anthropogenic NO<sub><i>x</i></sub> emission trend over the United States during 2003–2017 from satellite observations: was there a flattening of the emission trend after the Great Recession?

Cited by 18 publications

References 61 publications

Satellite evidence for changes in the NO2 weekly cycle over large cities

Satellite evidence for changes in the NO2 weekly cycle over large cities

Intercomparison of Magnitudes and Trends in Anthropogenic Surface Emissions From Bottom‐Up Inventories, Top‐Down Estimates, and Emission Scenarios

Variational regional inverse modeling of reactive species emissions with PYVAR-CHIMERE-v2019

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