Accelerated penetration of on-road electric vehicles offers regional and community-scale air quality benefits; however, such benefits have not been previously quantified regarding environmental justice communities near major roads. This study evaluated six 2040 electric vehicle scenarios and quantified concentration reductions of nitrogen dioxide and fine particulate matter (diameter less than 2.5 µm) for southern California environmental justice communities near Interstate 710. Findings showed that aggressive electric vehicle penetration (85% electric vehicle share) reduced nitrogen dioxide and fine particulate matter concentrations more in communities with more people of color (1.9 ppb and 1.1 μg m⁻³) than in communities with more White residents (1.6 ppb and 0.94 μg m⁻³). Aggressive electric vehicle penetration reduced pollution exposure disparity by 30% for nitrogen dioxide and 14% for fine particulate matter. Disparity reductions were also found based on educational attainment. Results suggest policies that encourage accelerated electric vehicle penetration will address inequalities in air pollution and help achieve environmental justice.

We examined two near-road monitoring sites where the daily PM_2.5 readings were among the highest of any near-road monitoring location in the U.S. during 2014–2016: Denver, Colorado, in February 2014 and Indianapolis, Indiana, in November 2016. At the Denver site, which had the highest measured U.S. near-road 24-hr PM_2.5 concentrations in 2014, concentrations exceeded the daily National Ambient Air Quality Standards (NAAQS) on three days during one week in 2014; the Indianapolis site had the second-highest number of daily exceedances of any near-road site in 2016 and the highest 3-year average PM_2.5 of any near-road site during 2014–2016. Both sites had hourly pollutant, meteorological, and traffic data available, making them ideal for case studies. For both locations, we compared air pollution observations at the near-road site to observations at other sites in the urban area to calculate the near-road PM_2.5 “increment” and evaluated the effects of changes in meteorology and traffic. The Denver near-road site consistently had the highest PM_2.5 values in the Denver area, and was typically highest when winds were near-downwind, rather than directly downwind, to the freeway. Complex Denver site conditions (near-road buildings and roadway alignment) likely contributed to higher PM_2.5 concentrations. The increment at Indianapolis was also highest under near-downwind, rather than directly downwind, conditions. At both sites, while the near-road site often had higher PM_2.5 concentrations than nearby sites, there was no clear correlation between traffic conditions (vehicle speed, fleet mix) and the high PM_2.5 concentrations.

This article presents a new analysis approach to design and evaluate motor vehicle inspection and maintenance (I/M) programs. The new approach, called I/M-Design, uses real-world data to provide two resources not previously available: (1) a transparent framework to quantitatively illustrate the range of emission reductions available from I/M, and (2) a sensitivity analysis tool to evaluate how key variables affect I/M performance. In addition, the approach satisfies a policy-making information need—how to convey, in a logical and straightforward manner, the expected benefits from I/M without relying on modeling tools inaccessible to those outside the air quality field. The material presented in this article illustrates the new approach by estimating hydrocarbon (HC) emission reduction benefits available from enhanced I/M in southern California’s South Coast Air Basin. I/M-Design estimates that enhanced I/M results in a 14–28% reduction in light-duty motor vehicle HC exhaust emissions; this estimate compares well to other California I/M program evaluations. Even more importantly, I/M-Design sensitivity analyses illustrate how I/M programs that implement stringent failure thresholds, motivate pre-test repair work, and improve repair effectiveness can provide emission reductions that substantially exceed the performance of existing programs.

Control of CO is one of the great air-quality management success stories of the past 20 years. This paper evaluates whether past progress will continue into the future and whether changes in microscale CO concentrations are comparable to reductions observed at the regional scale. Neighborhood and microscale CO concentrations were evaluated at six northern and southern California monitoring sites. The study also included a review of CO emission, concentration, and exposure trends and on-road motor vehicle-based CO emission control programs for California and the United States. Consistent with California and national trends, CO concentrations declined at each of the six study locations from 1988 through 1998. Microscale concentrations declined at the same rate as did neighborhood-scale concentrations. Rollback analyses demonstrated that microscale concentrations will continue to decline through at least 2010-2020. Within a few years, microscale violations of the CO National Ambient Air Quality Standards (NAAQS) will be unlikely in California except under extraordinary circumstances.

This study used a new emissions modeling tool, CT-EMFAC, to assess the sensitivity of mobile source air toxic (MSAT) emissions to changes in traffic volumes, speeds, and fleet composition. In addition, the choice of the speed calculation method, which is usually part of a postprocessing technique, was analyzed. The investigation employed a hypothetical 6.7-mi freeway segment located in southern California; activity data were derived from comparable real-world information obtained from the California Department of Transportation. Results show that emissions more than doubled in 2004 and increased by a factor of two to four in 2030 when traffic volumes increased 30% above base case conditions. The nonlinear shift in emissions was a function of decreased travel speeds and increased grams per mile emission rates that accompanied increased traffic volumes. Fleet composition (the proportion of trucks) was also shown to affect MSAT emissions, especially for diesel particulate matter and aldehydes. Under some scenarios, the choice of the speed calculation method had a greater effect on MSAT emissions than 26 years of fleet turnover. The analysis also showed that the type of speed calculation method used could result in large variations in MSAT emissions. Application of one speed calculation method resulted in calculated congested freeway speeds that did not fall below 10 mph. The speed calculation method chosen was highly influential in the 2030 case study when forecasted volumes reached levels at which speeds approached the 10 mph minimum allowed by the speed calculation method; this probably underpredicted emissions.