scholarly journals Are contributions of emissions to ozone a matter of scale? – A study using MECO(n) (MESSy v2.50)

2019 ◽  
Author(s):  
Mariano Mertens ◽  
Astrid Kerkweg ◽  
Volker Grewe ◽  
Patrick Jöckel ◽  
Robert Sausen
Keyword(s):  
Source Apportionment ◽  
Emission Inventory ◽  
Climate Model ◽  
Ground Level ◽  
Emission Sources ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Model Resolution ◽  
Ground Level Ozone ◽  
Transport Emissions

Abstract. Anthropogenic and natural emissions influence the tropospheric ozone budget, thereby affecting air-quality and climate. To study the influence of different emission sources on the ozone budget, often source apportionment studies with a tagged tracer approach are performed. Studies investigating air quality issues usually rely on regional models with a high spatial resolution, while studies focusing on climate related questions often use coarsely resolved global models. It is well known that simulated ozone concentrations depend on the resolution of the model and the resolution of the emission inventory. Whether the contributions simulated by source apportionment approaches also depend on the model resolution, however, is still unclear. Therefore, this study is a first attempt to analyse the impact of the model, the model resolution, and the emission inventory resolution on simulated ozone contributions diagnosed with a tagging method. The differences of the ozone contributions caused by these factors are compared with differences which arise due to different emission inventories. To do so we apply the MECO(n) model system which on-line couples a global chemistry-climate model with a regional chemistry-climate model equipped with a tagging scheme for source apportionment. The results of the global model (300 km resolution) are compared with the results of the regional model at 50 km (Europe) and 12 km (Germany) resolution. Averaged over Europe the simulated contributions of land transport emissions to ground-level ozone differ by 10 % at maximum. For other anthropogenic emission sources the differences are in the same order of magnitude, while the contribution of stratospheric ozone to ground level ozone differs by up to 30 % on average. This suggests that ozone contributions of anthropogenic emission sources averaged on continental scale are rather robust with respect to different models, model and emission inventory resolutions. On regional scale, however, we quantified differences of the contribution of land transport emissions to ozone of up to 20 %. Depending on the region the largest differences are either caused by inter model differences, or differences of the anthropogenic emission inventories. Clearly, the results strongly depend on the compared models and emission inventories and cannot necessarily be generalised, however we show how the inclusion of source apportionment methods can help in analysing inter-model differences.

scholarly journals Are contributions of emissions to ozone a matter of scale? – a study using MECO(n) (MESSy v2.50)

2020 ◽  
Vol 13 (1) ◽  
pp. 363-383 ◽  
Author(s):  
Mariano Mertens ◽  
Astrid Kerkweg ◽  
Volker Grewe ◽  
Patrick Jöckel ◽  
Robert Sausen
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Emission Inventory ◽  
Climate Model ◽  
Stratospheric Ozone ◽  
Model Resolution ◽  
Regional Models ◽  
Continental Scale ◽  
The Impact ◽  
Apportionment Methods

Abstract. Anthropogenic and natural emissions influence the tropospheric ozone budget, thereby affecting air quality and climate. To study the influence of different emission sources on the ozone budget, often source apportionment studies with a tagged tracer approach are performed. Studies investigating air quality issues usually rely on regional models with a fine spatial resolution, while studies focusing on climate-related questions often use coarsely resolved global models. It is well known that simulated ozone mixing ratios depend on the resolution of the model and the resolution of the emission inventory. Whether the contributions simulated using source apportionment approaches also depend on the model resolution, however, is still unclear. Therefore, this study attempts for the first time to analyse the impact of the model, the model resolution, and the emission inventory resolution on simulated ozone contributions using a diagnostic tagging method. The differences in the ozone contributions caused by these factors are compared with differences that arise from the usage of different emission inventories. To do so, we apply the MECO(n) (MESSy-fied ECHAM and COSMO models nested n times) model system which couples online a global chemistry-climate model with a regional chemistry-climate model equipped with a tagging scheme for source apportionment. The results of the global model (at 300 km horizontal resolution) are compared with the results of the regional model at 50 km (Europe) and 12 km (Germany) resolutions. Besides model-specific differences and biases that are discussed in detail, our results have important implications for other modelling studies and modellers applying source apportionment methods. First, contributions from anthropogenic emissions averaged over the continental scale are quite robust with respect to the model, model resolution, and emission inventory resolution. Second, differences on the regional scale caused by different models and model resolutions can be quite large, and regional models are indispensable for source apportionment studies on the subcontinental scale. Third, contributions from stratospheric ozone transported to the surface differ strongly between the models, mainly caused by differences in the efficiency of the vertical mixing. As stratospheric ozone plays an important role for ground level ozone, but the models show large differences in the amount of downward transported ozone, source apportionment methods should account for this source explicitly to better understand inter-model differences.

scholarly journals Contribution and uncertainty of sectorial and regional emissions to regional and global PM<sub>2.5</sub> health impacts

2019 ◽  
Vol 19 (7) ◽  
pp. 5165-5186 ◽  
Author(s):  
Monica Crippa ◽  
Greet Janssens-Maenhout ◽  
Diego Guizzardi ◽  
Rita Van Dingenen ◽  
Frank Dentener
Keyword(s):  
Power Generation ◽  
Air Quality ◽  
Human Health ◽  
Emission Inventory ◽  
Health Impacts ◽  
Pollutant Emission ◽  
Emission Sources ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Premature Deaths

Abstract. In this work we couple the HTAP_v2.2 global air pollutant emission inventory with the global source receptor model TM5-FASST to evaluate the relative contributions of the major anthropogenic emission sources (power generation, industry, ground transport, residential, agriculture and international shipping) to air quality and human health in 2010. We focus on particulate matter (PM) concentrations because of the relative importance of PM2.5 emissions in populated areas and the well-documented cumulative negative effects on human health. We estimate that in 2010, depending on the region, annual averaged anthropogenic PM2.5 concentrations varied between ca. 1 and 40 µg m−3, with the highest concentrations observed in China and India, and lower concentrations in Europe and North America. The relative contribution of anthropogenic emission sources to PM2.5 concentrations varies between the regions. European PM pollution is mainly influenced by the agricultural and residential sectors, while the major contributing sectors to PM pollution in Asia and the emerging economies are the power generation, industrial and residential sectors. We also evaluate the emission sectors and emission regions in which pollution reduction measures would lead to the largest improvement on the overall air quality. We show that air quality improvements would require regional policies, in addition to local- and urban-scale measures, due to the transboundary features of PM pollution. We investigate emission inventory uncertainties and their propagation to PM2.5 concentrations, in order to identify the most effective strategies to be implemented at sector and regional level to improve emission inventories, knowledge and air quality modelling. We show that the uncertainty of PM concentrations depends not only on the uncertainty of local emission inventories, but also on that of the surrounding regions. Countries with high emission uncertainties are often impacted by the uncertainty of pollution coming from surrounding regions, highlighting the need for effective efforts in improving emissions not only within a region but also from extra-regional sources. Finally, we propagate emission inventory uncertainty to PM concentrations and health impacts. We estimate 2.1 million premature deaths per year with an uncertainty of more than 1 million premature deaths per year due to the uncertainty associated only with the emissions.

scholarly journals Revisiting the contribution of land transport and shipping emissions to tropospheric ozone

2018 ◽  
Vol 18 (8) ◽  
pp. 5567-5588 ◽  
Author(s):  
Mariano Mertens ◽  
Volker Grewe ◽  
Vanessa S. Rieger ◽  
Patrick Jöckel
Keyword(s):  
Tropospheric Ozone ◽  
North Pacific Ocean ◽  
Ground Level ◽  
Ozone Production ◽  
Perturbation Approach ◽  
Emission Sources ◽  
Ground Level Ozone ◽  
The North ◽  
Transport Emissions ◽  
The North Pacific

Abstract. We quantify the contribution of land transport and shipping emissions to tropospheric ozone for the first time with a chemistry–climate model including an advanced tagging method (also known as source apportionment), which considers not only the emissions of nitrogen oxides (NOx, NO, and NO2), carbon monoxide (CO), and volatile organic compounds (VOC) separately, but also their non-linear interaction in producing ozone. For summer conditions a contribution of land transport emissions to ground-level ozone of up to 18 % in North America and Southern Europe is estimated, which corresponds to 12 and 10 nmol mol−1, respectively. The simulation results indicate a contribution of shipping emissions to ground-level ozone during summer on the order of up to 30 % in the North Pacific Ocean (up to 12 nmol mol−1) and 20 % in the North Atlantic Ocean (12 nmol mol−1). With respect to the contribution to the tropospheric ozone burden, we quantified values of 8 and 6 % for land transport and shipping emissions, respectively. Overall, the emissions from land transport contribute around 20 % to the net ozone production near the source regions, while shipping emissions contribute up to 52 % to the net ozone production in the North Pacific Ocean. To put these estimates in the context of literature values, we review previous studies. Most of them used the perturbation approach, in which the results for two simulations, one with all emissions and one with changed emissions for the source of interest, are compared. For a better comparability with these studies, we also performed additional perturbation simulations, which allow for a consistent comparison of results using the perturbation and the tagging approach. The comparison shows that the results strongly depend on the chosen methodology (tagging or perturbation approach) and on the strength of the perturbation. A more in-depth analysis for the land transport emissions reveals that the two approaches give different results, particularly in regions with large emissions (up to a factor of 4 for Europe). Our estimates of the ozone radiative forcing due to land transport and shipping emissions are, based on the tagging method, 92 and 62 mW m−2, respectively. Compared to our best estimates, previously reported values using the perturbation approach are almost a factor of 2 lower, while previous estimates using NOx-only tagging are almost a factor of 2 larger. Overall our results highlight the importance of differentiating between the perturbation and the tagging approach, as they answer two different questions. In line with previous studies, we argue that only the tagging approach (or source apportionment approaches in general) can estimate the contribution of emissions, which is important to attribute emission sources to climate change and/or extreme ozone events. The perturbation approach, however, is important to investigate the effect of an emission change. To effectively assess mitigation options, both approaches should be combined. This combination allows us to track changes in the ozone production efficiency of emissions from sources which are not mitigated and shows how the ozone share caused by these unmitigated emission sources subsequently increases.

scholarly journals Revisiting the contribution of land transport and shipping emissions to tropospheric ozone

2017 ◽  
Author(s):  
Mariano Mertens ◽  
Volker Grewe ◽  
Vanessa S. Rieger ◽  
Patrick Jöckel
Keyword(s):  
Perturbation Method ◽  
Tropospheric Ozone ◽  
Climate Model ◽  
Ground Level ◽  
Ozone Production ◽  
Perturbation Approach ◽  
Ground Level Ozone ◽  
Depth Analysis ◽  
Northern Pacific ◽  
Transport Emissions

Abstract. We quantify the contribution of land transport and shipping emissions to tropospheric ozone for the first time with a chemistry-climate model including an advanced tagging method, which considers not only the emissions of NOx (NO and NO2), CO or non-methane hydrocarbons (NMHC) separately but the competing effects of all relevant ozone precursors. For summer conditions a contribution of land transport emissions to ground level ozone of up to 18 % in North America and South Europe is estimated, which corresponds to 12 nmol mol−1 and 10 nmol mol−1, respectively. The simulation results indicate a contribution of shipping emissions to ground level ozone during summer in the order of up to 30 % in the Northern Pacific (up to 12 nmol mol−1) and 20 % in the Northern Atlantic (12 nmol mol−1). To put these estimates in the context of literature values, we review previous studies. Most of them used the perturbation approach, in which the results from two simulations, one with all emissions and one with changed emissions for the source of interest, are compared. The comparison shows that the results strongly depend on the chosen methodology (tagging or perturbation method) and on the strength of the perturbation. A more in-depth analysis for the land transport emissions reveals that the two approaches give different results particularly in regions with large emissions (up to a factor of four for Europe). With respect to the contribution of land transport and ship traffic emissions to the tropospheric ozone burden we quantified values of 8 % and 6 % for the land transport and shipping emissions, respectively. Overall, the emissions from land transport contribute to around 20 % of the net ozone production near the source regions, while shipping emissions contribute up to 52 % to the net ozone production in the Northern Pacific. Our estimates of the radiative ozone forcing due to emissions of land transport and shipping emissions are 92 mW m−2 and 62 mW m−2, respectively. Again these results are larger by a factor of 2–3 compared to previous studies using the perturbation approach, but largely agree with previous studies which investigated the difference between the tagging and the perturbation method. Overall our results highlight the importance of differing between the perturbation and the tagging approach, as they answer two different questions. We argue that only the tagging approach can estimate the contribution of emissions, while only the perturbation approach investigates the effect of an emission change. To effectively asses mitigation options both approaches should be combined.

scholarly journals A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): An application of the Community Emissions Data System (CEDS)

2020 ◽  
Author(s):  
Erin E. McDuffie ◽  
Steven J. Smith ◽  
Patrick O'Rourke ◽  
Kushal Tibrewal ◽  
Chandra Venkataraman ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Data System ◽  
Atmospheric Pollutants ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Fuel Type ◽  
Road Transportation ◽  
Activity Data ◽  
Global Emission ◽  
Global Emissions

Abstract. Global anthropogenic emission inventories remain vital for understanding the fate and transport of atmospheric pollution, as well as the resulting impacts on the environment, human health, and society. Rapid changes in today’s society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel-type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx, CO, SO2, NH3, NMVOCs, BC, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture, energy generation, industrial processes, transportation (on-road and non-road), residential, commercial, and other sectors (RCO), waste, solvent use, and international-shipping) and four fuel categories (total coal, solid biofuel, and the sum of liquid fuels and natural gas combustion, plus remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes global gridded (0.5°×0.5°) emission fluxes with monthly time resolution for each compound, sector, and fuel-type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default calibration procedure, and modifications to the final procedures for emissions gridding and aggregation to retain sector and fuel-specific information. Relative to the previous CEDS data released for CMIP6 (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to-date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel-types across multiple source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors, as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), as well as emissions from waste. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture serving as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories, including uncertainties in the underlying activity data and sector- and region-specific emission factors. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS. The CEDSGBD-MAPS emission inventory dataset (both annual country-total and global gridded files) is publicly available and registered under: https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020).

scholarly journals Attributing land transport emissions to ozone and ozone precursors in Europe and Germany

2019 ◽  
Author(s):  
Mariano Mertens ◽  
Astrid Kerkweg ◽  
Volker Grewe ◽  
Patrick Jöckel ◽  
Robert Sausen
Keyword(s):  
Carbon Monoxide ◽  
Nitrogen Oxides ◽  
Tropospheric Ozone ◽  
Seasonal Cycle ◽  
Emission Inventory ◽  
Ground Level ◽  
Global Model ◽  
Ozone Precursors ◽  
Po Valley ◽  
Transport Emissions

Abstract. Land transport is an important emission source of nitrogen oxides, carbon monoxide and volatile organic compounds, which serves as precursors for tropospheric ozone. Besides the direct negative impact of nitrogen oxides, air quality is also affected by these enhanced ozone tropospheric ozone concentrations. As ozone is radiativly active, its increase contributes to climate change. Due to the strong non-linearity of the ozone chemistry, the contribution of land transport emissions to tropospheric ozone cannot be calculated or measured directly, instead atmospheric-chemistry models equipped with specific source apportionment methods (called tagging) are required. In this study we investigate the contributions of land transport emissions to ozone and ozone precursors using the MECO(n) model system, coupling a global and a regional chemistry climate model, which are equipped with a tagging diagnostic. For the first time the effects of long range transport and regional effects of regional emissions are investigated. This is only possible by applying a tagging method simultaneously and consistently on the global and regional scale. We performed two three-year simulations with different anthropogenic emission inventories for Europe by applying our global model with two regional refinements, i.e. a European nest (50 km resolution) in the global model and a German nest (12 km resolution) in the European nest. We find contributions of land transport emissions to reactive nitrogen (NOy) near ground-level in the range of 5 to 10 nmol mol−1, corresponding to 50 to 70 % of the ground level NOy values. The largest contributions are around Paris, Southern England, Moscow, the Po Valley, and Western Germany. Carbon monoxide contributions range from 30 nmol mol−1 to more than 75 nmol mol−1 near emission hot spots such as Paris or Moscow. The contribution of land transport emissions to ozone show a strong seasonal cycle which absolute contributions of 3 nmol mol−1 during winter and 5 to 10 nmol mol−1 during summer. This corresponds to relative contributions of 8 to 10 % during winter and up to 16 % during summer. Those largest values during summer are confined to the Po Valley, while the contribution in Western Europa ranges from 12 to 14 %. The ozone contributions are robust. Only during summer the ozone contributions are slightly influenced by the emission inventory, but these differences are smaller than the range of the seasonal cycle of the contribution. This cycle is caused by a complex interplay of seasonal cycles of other emissions (e.g. biogenic) and seasonal difference of the ozone regimes. This small difference of the ozone contributions due to the emission inventory is remarkable as the precursor concentrations (NOx and CO) are much more affected by the change. In addition, our results suggest that during events with large ozone values the contribution of land transport emissions and biogenic emissions increase strongly. Here, the contribution of land transport emission peak up to 28 %. Hence, land transport is an important contributor to events of large ozone values.

scholarly journals Sectorial and regional uncertainty analysis of the contribution of anthropogenic emissions to regional and global PM<sub>2.5</sub> health impacts

2017 ◽  
Author(s):  
Monica Crippa ◽  
Greet Janssens-Maenhout ◽  
Diego Guizzardi ◽  
Rita Van Dingenen ◽  
Frank Dentener
Keyword(s):  
Power Generation ◽  
Air Quality ◽  
Human Health ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Health Impacts ◽  
Pollutant Emission ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Relative Contribution

Abstract. In this work we couple the HTAPv2.2 global air pollutant emission inventory with the global source receptor model TM5-FASST to evaluate the relative contribution of the major anthropogenic emission sources (power generation, industry, ground transport, residential, agriculture and international shipping) to air quality and human health in 2010. We focus on particulate matter (PM) concentrations because of the relative importance of PM2.5 emissions in populated areas and the proven cumulative negative effects on human health. We estimate that in 2010 regional annual averaged anthropogenic PM2.5 concentrations varied between ca. 1 and 40 μg/m3 depending on the region, with the highest concentrations observed in China and India, and lower concentrations in Europe and North America. The relative contribution of anthropogenic emission source sectors to PM2.5 concentrations varies between the regions. European PM pollution is mainly influenced by the agricultural and residential sectors, while the major contributing sectors to PM pollution in Asia and the emerging economies are the power generation, industrial and residential sectors. We also evaluate the emission sectors and emission regions in which pollution reduction measures would lead to the largest improvement on the overall air quality. We show that in order to improve air quality, regional policies should be implemented (e.g. in Europe) due to the transboundary features of PM pollution. In addition, we investigate emission inventory uncertainties and their propagation to PM2.5 concentrations, in order to identify the most effective strategies to be implemented at sector and regional level to improve emission inventories knowledge and air quality. We show that the uncertainty of PM concentrations depends not only on the uncertainty of local emission inventories but also on that of the surrounding regions. Finally, we propagate emission inventories uncertainty to PM concentrations and health impacts.

scholarly journals Inverse modeling of Texas NO<sub>x</sub> emissions using space-based and ground-based NO<sub>2</sub> observations

2013 ◽  
Vol 13 (21) ◽  
pp. 11005-11018 ◽  
Author(s):  
W. Tang ◽  
D. S. Cohan ◽  
L. N. Lamsal ◽  
X. Xiao ◽  
W. Zhou
Keyword(s):  
Inverse Modeling ◽  
Direct Method ◽  
A Priori ◽  
Model Performance ◽  
Ground Level ◽  
Nox Emissions ◽  
Emission Inventories ◽  
Air Quality Model ◽  
Quality Model ◽  
Ground Level Ozone

Abstract. Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite-observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with decoupled direct method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2-based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3–55% increase in modeled NO2 column densities and 1–7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

scholarly journals Inverse modeling of Texas NO<sub>x</sub> emissions using space-based and ground-based NO<sub>2</sub> observations

2013 ◽  
Vol 13 (7) ◽  
pp. 17479-17517
Author(s):  
W. Tang ◽  
D. Cohan ◽  
L. N. Lamsal ◽  
X. Xiao ◽  
W. Zhou
Keyword(s):  
Inverse Modeling ◽  
Direct Method ◽  
A Priori ◽  
Model Performance ◽  
Ground Level ◽  
Nox Emissions ◽  
Emission Inventories ◽  
Air Quality Model ◽  
Quality Model ◽  
Ground Level Ozone

Abstract. Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3–55% increase in modeled NO2 column densities and 1–7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

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