Modeling Ozone in the Eastern U.S. using a Fuel-Based Mobile Source Emissions Inventory

Abstract

Recent studies suggest overestimates in current U.S. emission inventories of nitrogen oxides (NO = NO + NO). Here, we expand a previously developed fuel-based inventory of motor-vehicle emissions (FIVE) to the continental U.S. for the year 2013, and evaluate our estimates of mobile source emissions with the U.S. Environmental Protection Agency's National Emissions Inventory (NEI) interpolated to 2013. We find that mobile source emissions of NO and carbon monoxide (CO) in the NEI are higher than FIVE by 28% and 90%, respectively. Using a chemical transport model, we model mobile source emissions from FIVE, and find consistent levels of urban NO and CO as measured during the Southeast Nexus (SENEX) Study in 2013. Lastly, we assess the sensitivity of ozone (O) over the Eastern U.S. to uncertainties in mobile source NO emissions and biogenic volatile organic compound (VOC) emissions. The ground-level O is sensitive to reductions in mobile source NO emissions, most notably in the Southeastern U.S. and during O exceedance events, under the revised standard proposed in 2015 (>70 ppb, 8 h maximum). This suggests that decreasing mobile source NO emissions could help in meeting more stringent O standards in the future.

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?

“…The agreement of decreasing trends among the datasets is just as good for the post-2011 period as the pre-2011 period. This result differs from Miyazaki et al (2017) and Jiang et al (2018), who suggested no significant decreasing trend for OMI TVCD data and inversed NO x emissions after 2010. The disagreement can be explained by the results of Fig.…”

“…The continuous decrease in anthropogenic NO x emissions was consistent with the ongoing reduction in vehicle emissions (McDonald et al, 2018). On the other hand, Miyazaki et al (2017) and Jiang et al (2018) found that the US NO x emissions derived from satellite NO 2 TVCDs, including OMI (the Ozone Monitoring Instrument), SCIA-MACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartography), and GOME-2A (Global Ozone Monitoring Experiment 2 onboard METOP-A), were almost flat from 2010-2015 and suggested that the decrease in NO x emissions was only significant before 2010, which was completely different from the bottom-up and fuel-based emission estimates.…”

“…The much slower satellite TVCD trends for regions with low NO x emissions was previously discussed by Zhang et al (2018). In addition, Miyazaki et al (2017) and Jiang et al (2018) conducted NO x emission inversions by using the Model for Interdisciplinary Research on Climate (MIROC)-Chem with a coarse resolution of 2.8 • × 2.8 • , which was insufficient to separate urban and rural regions and might distort predicted NO 2 TVCDs and inversed NO x emissions due to nonlinear effects (Valin et al, 2011;Yu et al, 2016), which is another possible reason for their finding of flattening NO x emission trends after 2010.…”

“…The overall reduction (about 30 %-50 %) of anthropogenic NO x emissions from the mid-2000s to the 2010s was corroborated by observed decreases in vehicle NO x emission factors, NO 2 surface concentrations, nitrate wet deposition flux (Fig. S1 in the Supplement), and NO 2 tropospheric vertical column densities (TVCDs) (Bishop and Stedman, 2015;Georgoulias et al, 2019;Li et al, 2018;McDonald et al, 2018;Miyazaki et al, 2017;Russell et al, 2012;Tong et al, 2015). How-ever, the detailed NO x emission changes after the Great Recession (from December 2007 to June 2009) are highly uncertain.…”

“…Since the area of low anthropogenic NO x emission regions is larger than high anthropogenic NO x emission regions (Table 2), the arithmetic averaging will lead to a large weighting of rural observations, which do not reflect anthropogenic NO x emission changes. Miyazaki et al (2017) and Jiang et al (2018) included all regions in their analyses, but we exclude rural regions. Figure S9 shows the seasonal variations if the TVCDs over rural regions are included; the result shows a much lower decreasing rate of TVCDs over the CONUS.…”