Evaluation of Nitrogen Oxide Emission Inventories and Trends for On-Road Gasoline and Diesel Vehicles

Intercomparison of Modeled Urban-Scale Vehicle NOx and PM2.5 Emissions-Implications for Equity Assessments

Accurate characterization of emissions is essential for understanding spatiotemporal variations of air pollutants and their societal impacts, including population exposure, health outcomes, and environmental justice implications. Characterizing emissions from the transportation sector is challenging due to uncertainties in emission-producing processes and in fleet composition and activity-factors that lead to differences across modeled vehicle emissions data sets. Here, we compare four data sets─Fuel-Inventory Vehicle Emissions, Neighborhood Emission Mapping Operation, Lake Michigan Air Director Consortium-Northwestern University, and University of Vermont─over the Greater Chicago region at three shared spatial resolutions (1.0, 1.3, and 4 km2). While domain-level data set agreement is strongest at the coarsest resolution, at finer resolutions we find notable inconsistencies, particularly at local scales. At 1 km2, simulated domain total NOx emissions across the four data sets differ up to 82% (∼32-58 k tons/year), while grid cell maximum PM2.5 emissions vary up to 272% (∼1.5-5.5 tons/km2/year). Intercompared emissions data sets share similar inputs; however, divergent outcomes arise from differences in emission factors, simulated vehicle processes, and characterization of traffic data. While domain-level emission burdens among racial/ethnic subgroups are generally ranked similarly across data sets, the magnitude of relative disparities can vary up to 11%-a potentially consequential factor to consider in downstream impact analyses.

Observing Anthropogenic and Biogenic CO2 Emissions in Los Angeles Using a Dense Sensor Network

Urban areas are major contributors to greenhouse gas emissions, necessitating effective monitoring systems to evaluate mitigation strategies. A dense sensor network, such as the Berkeley Environmental Air-quality & CO2 Observation Network (BEACO2N), offers a unique opportunity to monitor urban emissions at high spatial resolution. Here, we describe a simple approach to quantifying urban emissions with sufficient precision to constrain seasonal and annual trends. Measurements from 12 BEACO2N sites in Los Angeles (called the USC Carbon Census) are analyzed within a box model framework. By combining CO2 and CO observations, we partition total CO2 emissions into fossil fuel and biogenic emissions. We infer temporal changes in biogenic emissions that correspond to the MODIS enhanced vegetation index (EVI) and show that net biogenic exchange can consume up to 60% of fossil fuel emissions in the growing season during daytime hours. While we use the first year of observations to describe seasonal variation, we demonstrate the feasibility of this approach to constrain annual and longer trends.

Influence of Oil and Gas End-Use on Summertime Particulate Matter and Ozone Pollution in the Eastern US

The influence of oil and gas end-use activities on ambient air quality is complex and understudied, particularly in regions where intensive end-use activities and large biogenic emissions of isoprene coincide. In these regions, vehicular emissions of nitrogen oxides (NOx≡NO + NO2) modulate the oxidative fate of isoprene, a biogenic precursor of the harmful air pollutants ozone, formaldehyde, and particulate matter (PM2.5). Here, we investigate the direct and indirect influence of the end-use emissions on ambient air quality. To do so, we use the GEOS-Chem model with focus on the eastern United States (US) in summer. Regional mean end-use NOx of 1.4 ppb suppresses isoprene secondary organic aerosol (OA) formation by just 0.02 μg m-3 and enhances abundance of the carcinogen formaldehyde by 0.3 ppb. Formation of other reactive oxygenated volatile organic compounds is also enhanced, contributing to end-use maximum daily mean 8-h ozone (MDA8 O3) of 8 ppb. End-use PM2.5 is mostly (67%) anthropogenic OA, followed by 20% secondary inorganic sulfate, nitrate and ammonium and 11% black carbon. These adverse effects on eastern US summertime air quality suggest potential for severe air quality degradation in regions like the tropics with year-round biogenic emissions, growing oil and gas end-use and limited environmental regulation.

Neighborhood-Level Nitrogen Dioxide Inequalities Contribute to Surface Ozone Variability in Houston, Texas

In Houston, Texas, nitrogen dioxide (NO2) air pollution disproportionately affects Black, Latinx, and Asian communities, and high ozone (O3) days are frequent. There is limited knowledge of how NO2 inequalities vary in urban air quality contexts, in part from the lack of time-varying neighborhood-level NO2 measurements. First, we demonstrate that daily TROPOspheric Monitoring Instrument (TROPOMI) NO2 tropospheric vertical column densities (TVCDs) resolve a major portion of census tract-scale NO2 inequalities in Houston, comparing NO2 inequalities based on TROPOMI TVCDs and spatiotemporally coincident airborne remote sensing (250 m × 560 m) from the NASA TRacking Aerosol Convection ExpeRiment-Air Quality (TRACER-AQ). We further evaluate the application of daily TROPOMI TVCDs to census tract-scale NO2 inequalities (May 2018-November 2022). This includes explaining differences between mean daily NO2 inequalities and those based on TVCDs oversampled to 0.01° × 0.01° and showing daily NO2 column-surface relationships weaken as a function of observation separation distance. Second, census tract-scale NO2 inequalities, city-wide high O3, and mesoscale airflows are found to covary using principal component and cluster analysis. A generalized additive model of O3 mixing ratios versus NO2 inequalities reproduces established nonlinear relationships between O3 production and NO2 concentrations, providing observational evidence that neighborhood-level NO2 inequalities and O3 are coupled. Consequently, emissions controls specifically in Black, Latinx, and Asian communities will have co-benefits, reducing both NO2 disparities and high O3 days city wide.

PM2.5 exposure disparities persist despite strict vehicle emissions controls in California

As policymakers increasingly focus on environmental justice, a key question is whether emissions reductions aimed at addressing air quality or climate change can also ameliorate persistent air pollution exposure disparities. We examine evidence from California's aggressive vehicle emissions control policy from 2000 to 2019. We find a 65% reduction in modeled statewide average exposure to PM2.5 from on-road vehicles, yet for people of color and overburdened community residents, relative exposure disparities increased. Light-duty vehicle emissions are the main driver of the exposure and exposure disparity, although smaller contributions from heavy-duty vehicles especially affect some overburdened groups. Our findings suggest that a continued trend of emissions reductions will likely reduce concentrations and absolute disparity but may not reduce relative disparities without greater attention to the systemic factors leading to this disparity.

Large Decreases in Tailpipe Criteria Pollutant Emissions from the U.S. Light-Duty Vehicle Fleet Expected in 2020-2040

The U.S. EPA MOVES3 model was used to assess the impact of the large-scale introduction of electric vehicles on emissions of criteria pollutants (CO, hydrocarbons [HC], NOx, and particulate matter [PM]) and CO2 from the U.S. light-duty vehicle fleet. Large reductions in emissions of these criteria pollutants occurred in 2000-2020. These trends are expected to continue through 2040 driven by turnover of the conventional fleet with old vehicles being replaced by battery electric vehicles (BEVs) and by new internal combustion engine vehicles (ICEVs) with modern emission control systems. Without the introduction of BEVs, the absolute emissions of CO, NOx, HC, and PM2.5 from the U.S. light-duty vehicle fleet are expected to decrease by approximately 61, 88, 55, and 20% from 2020 to 2040. Introduction of BEVs with market share increasing linearly to 100% in 2040 provides additional benefits, which, combined with ICEV fleet turnover, would lead to decreases of absolute emissions of CO, NOx, HC, and PM2.5 of approximately 77, 94, 71, and 37% from 2020 to 2040. Reductions in CO2 emissions follow a similar pattern. Large decreases in criteria pollutant and CO2 emissions from light duty vehicles lie ahead.

Los Angeles Basin's air quality transformation: a long-term investigation on the impacts of PM regulations on the trends of ultrafine particles and co-pollutants

This study investigates the long-term trends of ambient ultrafine particles (UFPs) and associated airborne pollutants in the Los Angeles Basin from 2007 to 2022, focusing on the indirect effects of regulations on UFP levels. The particle number concentration (PNC) of UFPs was compiled from previous studies in the area, and associated co-pollutant data, including nitrogen oxides (NOx), carbon monoxide (CO), elemental carbon (EC), organic carbon (OC), and ozone (O3), were obtained from the chemical speciation network (CSN) database. Over the study period, a general decrease was noted in the PNC of UFPs, NOx, EC, and OC, except for CO, the concentration trends of which did not exhibit a consistent pattern. UFPs, NOx, EC, and OC were positively correlated, while O3 had a negative correlation, especially with NOx. Our analysis discerned two distinct subperiods in pollutant trends: 2007-2015 and 2016-2022. For example, there was an overall decrease in the PNC of UFPs at an annual rate of -850.09 particles/cm3/year. This rate was more pronounced during the first sub-period (2007-2015) at -1814.9 particles/cm3/year and then slowed to -227.21 particles/cm3/year in the second sub-period (2016-2023). The first sub-period (2007-2015) significantly influenced pollutant level changes, exhibiting more pronounced and statistically significant changes than the second sub-period (2016-2022). Since 2016, almost all primary pollutants have stabilized, indicating a reduced impact of current regulations, and emphasizing the need for stricter standards. In addition, the study included an analysis of Vehicle Miles Traveled (VMT) trends from 2007 to 2022 within the Los Angeles Basin. Despite the general increase in VMT, current regulations and cleaner technologies seem to have successfully mitigated the potential increase in increase in PNC. Overall, while a decline in UFPs and co-pollutant levels was observed, the apparent stabilization of these levels underscores the need for more stringent regulatory measures and advanced emission standards.

Corridor-Level Impacts of Battery-Electric Heavy-Duty Trucks and the Effects of Policy in the United States

Electrifying freight trucks will be key to alleviating air pollution burdens on disadvantaged communities and mitigating climate change. The United States plans to pursue this aim by adding vehicle charging infrastructure along specific freight corridors. This study explores the coevolution of the electricity grid and freight trucking landscape using an integrated assessment framework to identify when each interstate and drayage corridor becomes advantageous to electrify from a climate and human health standpoint. Nearly all corridors achieve greenhouse gas emission reductions if electrified now. Most can reduce health impacts from air pollution if electrified by 2040 although some corridors in the Midwest, South, and Mid-Atlantic regions remain unfavorable to electrify from a human health standpoint, absent policy support. Recent policy, namely, the Inflation Reduction Act, accelerates this timeline to 2030 for most corridors and results in net human health benefits on all corridors by 2050, suggesting that near-term investments in truck electrification, particularly drayage corridors, can meaningfully reduce climate and health burdens.

Improved Spatial Resolution in Modeling of Nitrogen Oxide Concentrations in the Los Angeles Basin

The extent to which emission control technologies and policies have reduced anthropogenic NOx emissions from motor vehicles is large but uncertain. We evaluate a fuel-based emission inventory for southern California during the June 2021 period, coinciding with the Re-Evaluating the Chemistry of Air Pollutants in CAlifornia (RECAP-CA) field campaign. A modified version of the Fuel-based Inventory of Vehicle Emissions (FIVE) is presented, incorporating 1.3 km resolution gridding and a new light-/medium-duty diesel vehicle category. NOx concentrations and weekday-weekend differences were predicted using the WRF-Chem model and evaluated using satellite and aircraft observations. Model performance was similar on weekdays and weekends, indicating appropriate day-of-week scaling of NOx emissions and a reasonable distribution of emissions by sector. Large observed weekend decreases in NOx are mainly due to changes in on-road vehicle emissions. The inventory presented in this study suggests that on-road vehicles were responsible for 55-72% of the NOx emissions in the South Coast Air Basin, compared to the corresponding fraction (43%) in the planning inventory from the South Coast Air Quality Management District. This fuel-based inventory suggests on-road NOx emissions that are 1.5 ± 0.4, 2.8 ± 0.6, and 1.3 ± 0.7 times the reference EMFAC model estimates for on-road gasoline, light- and medium-duty diesel, and heavy-duty diesel, respectively.

Predictability of fossil fuel CO2 from air quality emissions

Quantifying the coevolution of greenhouse gases and air quality pollutants can provide insight into underlying anthropogenic processes enabling predictions of their emission trajectories. Here, we classify the dynamics of historic emissions in terms of a modified Environmental Kuznets Curve (MEKC), which postulates the coevolution of fossil fuel CO₂ (FFCO₂) and NOx emissions as a function of macroeconomic development. The MEKC broadly captures the historic FFCO₂-NO_x dynamical regimes for countries including the US, China, and India as well as IPCC scenarios. Given these dynamics, we find the predictive skill of FFCO2 given NO_x emissions constrained by satellite data is less than 2% error at one-year lags for many countries and less than 10% for 4-year lags. The proposed framework in conjunction with an increasing satellite constellation provides valuable guidance to near-term emission scenario development and evaluation at time-scales relevant to international assessments such as the Global Stocktake.

Rational Regulation of Reducibility and Acid Site on Mn-Fe-BTC to Achieve High Low-Temperature Catalytic Denitration Performance

Selective catalytic reduction with ammonia is the mainstream technology of flue gas denitration (de-NO_x). The reducibility and acid site are two important factors affecting the de-NO_x performance, and effective regulation between them is the key to obtain a highly efficient de-NO_x catalyst. Herein, a series of Mn-Fe-BTC with different ratios of Mn and Fe are synthesized, among which 2Mn-1Fe-BTC with 2:1 molar ratio of Mn and Fe has excellent low-temperature (LT) de-NO_x performance (above 90% NO conversion between 60 and 270 °C) and good tolerance to H₂O and SO₂ poisoning (88% NO conversion at 150 °C with 100 ppm of SO₂ and/or 6% H₂O). It is revealed that the reducibility properties and acid sites of Mn-Fe-BTC can be flexibly tuned by the ratio of Mn and Fe. The difference in electronegativity between Fe and Mn leads to the redistribution of valence electrons, which enables the controllable reducibility of Mn-Fe-BTC. Furthermore, different amounts of Mn and Fe lead to different electron transport, which determines the type and number of acid sites. The synergistic effect of Mn and Fe endows Mn-Fe-BTC with enhanced surface molecular adsorption capacity and enables the catalyst to selectively chemisorb NH₃ and NO at different active sites. This research provides guidance for the flexible regulation of reducibility and acid site of LT de-NO_x catalyst.

Daily Satellite Observations of Nitrogen Dioxide Air Pollution Inequality in New York City, New York and Newark, New Jersey: Evaluation and Application

Urban air pollution disproportionately harms communities of color and low-income communities in the U.S. Intraurban nitrogen dioxide (NO₂) inequalities can be observed from space using the TROPOspheric Monitoring Instrument (TROPOMI). Past research has relied on time-averaged measurements, limiting our understanding of how neighborhood-level NO₂ inequalities co-vary with urban air quality and climate. Here, we use fine-scale (250 m × 250 m) airborne NO₂ remote sensing to demonstrate that daily TROPOMI observations resolve a major portion of census tract-scale NO₂ inequalities in the New York City-Newark urbanized area. Spatiotemporally coincident TROPOMI and airborne inequalities are well correlated (r = 0.82-0.97), with slopes of 0.82-1.05 for relative and 0.76-0.96 for absolute inequalities for different groups. We calculate daily TROPOMI NO₂ inequalities over May 2018-September 2021, reporting disparities of 25-38% with race, ethnicity, and/or household income. Mean daily inequalities agree with results based on TROPOMI measurements oversampled to 0.01° × 0.01° to within associated uncertainties. Individual and mean daily TROPOMI NO₂ inequalities are largely insensitive to pixel size, at least when pixels are smaller than ∼60 km², but are sensitive to low observational coverage. We statistically analyze daily NO₂ inequalities, presenting empirical evidence of the systematic overburdening of communities of color and low-income neighborhoods with polluting sources, regulatory ozone co-benefits, and worsened NO₂ inequalities and cumulative NO₂ and urban heat burdens with climate change.

In-Use Passenger Vessel Emission Rates of Black Carbon and Nitrogen Oxides

This study quantified emission factors of black carbon (BC) and nitrogen oxides (NO_x) from 21 engines on in-use excursion vessels and ferries operating in California's San Francisco Bay, including EPA uncertified and Tier 1-4 engines and across engine operating modes. On average, ∼60 fuel-based emission factors per engine were measured using a novel combination of exhaust plume capture combined with GPS location and speed data that can be more readily deployed than common portable emissions measurement systems. BC and NO_x emission factors (g kg^-1) were lowest and least variable during fast cruising and highest during maneuvering and docked operation. Selective catalytic reduction (SCR) reduced NO_x emissions by ∼80% when functional. However, elevated NO_x emissions that exceeded corresponding exhaust standards were measured on most Tier 3 and Tier 4 engines sampled, which can be attributed to inactive SCR during frequent low engine load operation. In contrast, BC emissions exceeded the PM emission standard for only one engine, and SCR systems employed as a NO_x reduction technology also reduced emitted BC. Using these measured emission factors to compare commuting options, we show that the CO₂-equivalent emissions per passenger-kilometer are comparable when commuting by car and ferry, but BC and NO_x emissions can be several to more than ten times larger when commuting by ferry.

Vehicle Emissions and Urban Air Quality: 60 Years of Progress

The past 60 years have seen large reductions in vehicle emissions of particulate matter (PM), nitrogen oxides (NOx), carbon monoxide (CO), hydrocarbons (HCs), sulfur dioxide (SO2), and lead (Pb). Advanced emission after-treatment technologies have been developed for gasoline and diesel vehicles to meet increasingly stringent regulations, yielding absolute emission reductions from the on-road fleet despite increased vehicle miles traveled. As a result of reduced emissions from vehicles and other sources, the air quality in cities across the U.S. and Europe has improved greatly. Turn-over of the on-road fleet, increasingly stringent emission regulations (such as Tier 3 in the U.S., LEV III in California, Euro 6 in Europe, and upcoming rules in these same regions), and the large-scale introduction of electric vehicles will lead to even lower vehicle emissions and further improvements in air quality. We review historical vehicle emissions and air quality trends and discuss the future outlook.

Utah Wintertime Measurements of Heavy-Duty Vehicle Nitrogen Oxide Emission Factors

There have only been a few wintertime studies of heavy-duty vehicle (HDV) NO_x emissions in the United States, and while they have observed increased emissions, fleet characterization to identify the cause has been lacking. We have collected wintertime measurements of NO_x emission factors from 1591 HDVs at a Utah Port of Entry in December 2020 that includes individual vehicle identification. In general, NO_x emission factors for 2011 and newer chassis model year HDV are significantly higher than those for 2017 spring measurements from California. The newest chassis model year HDV (2017-2021) NO_x emission factors are similar, indicating no significant emission deterioration over the 5 year period, though they are still approximately a factor of 3 higher than the portable emission measurement on-road enforcement standard. We estimate that ambient temperature increases NO_x emissions no more than 25% in the newer HDV, likely through reductions in catalyst efficiencies. NO_x emissions increase to a significantly higher level for the 2011-2013 chassis model year vehicles, where within the uncertainties, they have emissions similar to older precontrol vehicles, indicating that they have lost their NO_x control capabilities within 8 years. MOVES3 modeling of the Utah fleet underpredicted mean NO_x emissions by a factor of 1.8 but the MOVES3 estimate is helped by including a larger fraction of high-emitting glider kit trucks (new chassis with pre-emission control engines) than found in the observations.

An Intelligent Visualisation Tool to Analyse the Sustainability of Road Transportation

Road transport is an integral part of economic activity and is therefore essential for its development. On the downside, it accounts for 30% of the world’s GHG emissions, almost a third of which correspond to the transport of freight in heavy goods vehicles by road. Additionally, means of transport are still evolving technically and are subject to ever more demanding regulations, which aim to reduce their emissions. In order to analyse the sustainability of this activity, this study proposes the application of novel Artificial Intelligence techniques (more specifically, Machine Learning). In this research, the use of Hybrid Unsupervised Exploratory Plots is broadened with new Exploratory Projection Pursuit techniques. These, together with clustering techniques, form an intelligent visualisation tool that allows knowledge to be obtained from a previously unknown dataset. The proposal is tested with a large dataset from the official survey for road transport in Spain, which was conducted over a period of 7 years. The results obtained are interesting and provide encouraging evidence for the use of this tool as a means of intelligent analysis on the subject of developments in the sustainability of road transportation.