Assessing the air quality, public health, and equity implications of an Advanced Clean Trucks policy for Illinois

Abstract

Policies designed to reduce transportation emissions are known to be co-beneficial due to reductions in planet-warming greenhouse gases like carbon dioxide (CO₂) and health-harmful air pollutants, such as nitrogen dioxide (NO₂). The growing recognition of persistent racial and ethnic disparities in air pollution exposure and associated health impacts has increased demand for policy interventions aimed at systematically reducing such inequities. Here, we use a regulatory-grade air quality model focused on the Chicago region to find that medium- and heavy-duty vehicle (MHDV) tailpipe emissions account for ~22% of the area’s ambient NO₂ concentrations. Exposure to MHDV-tailpipe NO₂ in our domain is associated with 1330 (95% confidence interval (CI): 330, 2000) annual premature deaths and 1580 (95% CI: −310, 3870) new cases of pediatric asthma, disproportionately affecting census tracts with higher percentages of residents of color. Given the inequitable impacts of MHDV NO₂ exposure, we also use our model to assess the air quality, health, and equity outcomes if a policy scenario based on California’s Advanced Clean Trucks (ACT) regulation were instantaneously adopted in Illinois. We find that ACT adoption would lead to ~48% of on-road MHDVs having zero tailpipe emissions by 2050; an instantaneous transition to this policy would reduce annual mean population-weighted NO₂ concentrations by 0.98 ppb (parts per billion) (−8.4%), resulting in reductions of 500 (95% CI: −120, −750) premature deaths and 600 (95% CI: 120, −1440) fewer new pediatric asthma cases annually – with the largest health benefits observed in neighborhoods with higher percentages of residents of color. Our study highlights the benefits of implementing policy interventions focused on zero-emission MHDVs to address air pollution exposure and health impact disparities.

Graphical abstract

Keywords

zero-emission vehicles / transportation / air pollution / public health / environmental justice

1 Introduction

The disproportionate impacts of traffic-related air pollution on historically marginalized U.S. population subgroups underscores the potential for policy interventions that target transport emissions to advance environmental justice objectives and enhance public health outcomes (Chambliss et al., 2021; Demetillo et al., 2021; Kerr et al., 2021). Nearly a quarter of the U.S. population resides within 500 m of high-volume roadways, with people of color disproportionately exposed to traffic (Antonczak et al., 2023). Within the U.S., the on-road transportation sector contributes ~29% of both the nation’s greenhouse gas and nitrogen oxide emissions. Nitrogen oxide emissions (NO_x; NO₂ + NO) include primary health-harmful pollutants like NO₂ and precursors that contribute to the formation of secondary health-harmful pollutants, such as tropospheric ozone (O₃) and fine particulate matter (PM_2.5). Despite comprising less than 10% of on-road vehicles (Environmental Defense Fund, 2021), medium- and heavy-duty vehicles (MHDVs) contribute ~23% and 31% of on-road greenhouse gas and NO_x emissions, respectively (US Environmental Protection Agency, 2017, 2021a).

Exposure to traffic-related primary and secondary pollutants is associated with a myriad of substantial negative health outcomes (HEI, 2022). Exposure to traffic-related NO₂ has been implicated in pediatric asthma incidence (Khreis et al., 2017), with global NO₂ pollution estimated to contribute to 1.85 million new pediatric asthma cases annually (Anenberg et al., 2022). Ethnic and racial disparities are evident in the distribution of NO₂ pollution concentrations, with people of color experiencing concentrations 15%−50% higher than the U.S. average (Kerr et al., 2023). Additionally, there is growing confidence in the linkages between NO₂ exposure and premature mortality (Huangfu and Atkinson, 2020; HEI, 2022). As a result of this growing confidence, researchers have recently estimated annual U.S. NO₂-attributable premature mortality to be ~170850 premature deaths per year (Camilleri et al., 2023a). Given that NO₂ exposure is disproportionately higher among marginalized populations, premature mortality attributable to NO₂ exposure has also been found to be elevated among population subgroups. For example, Camilleri et al. (2023a) found that NO₂-attributable mortality rates among the U.S. Black population were 47% higher than the continental U.S. average. Premature deaths have also been linked to traffic-related O₃ and PM_2.5 exposure (Davidson et al., 2020), with 43% of these deaths attributed to on-road diesel vehicle emissions (Anenberg et al., 2019). Given emerging confidence in the health-harming impacts of traffic-related NO₂ and the well-established health-harmful linkage to O₃, here we evaluate how a policy intervention aimed at transitioning MHDVs to zero-emission vehicles alters NO₂ and O₃ concentrations, and assess the population exposure, health outcomes, and associated environmental equity implications.

Previously adopted air quality remediation interven-tions range from emissions testing (CARB, 2021) to emission control technology mandates (U.S. Environmental Protection Agency, 2021a) to incentives promoting electric passenger car and truck adoption (The White House, 2023). While these efforts have contributed to an overall improvement in U.S. air quality, relative racial and ethnic disparities in exposure and health outcomes persist, and in some cases, have increased. For example, from 2010 to 2019, relative racial disparities in PM_2.5-attributable mortality and NO₂-attributable pediatric asthma have grown in the U.S. (Polonik et al., 2023; Kerr et al., 2024b). This growing recognition of persistent relative racial disparities has increased demand for policy interventions aimed at systematically reducing inequities (Wang et al., 2023). Among these, Polonik et al. (2023) suggested that policy interventions focused on the transportation sector had the greatest potential to reverse disparities in exposure. However, a recent California-focused study found that while aggressive vehicle emission control policies had reduced average statewide exposures to PM_2.5, relative exposure disparities for people of color had increased (Koolik et al., 2024). Koolik et al. concluded that reducing the inequitable relative exposure to vehicle emissions ultimately requires policies addressing the disproportionate geographical distribution of emissions in overburdened communities. These findings underscore that broad, sector-wide emission reductions alone are insufficient to address inequities in transportation-related pollution. Instead, targeted policies (e.g., low emission zones, incentives for heavy-duty electrification, etc.) that prioritize emission reductions in historically over-burdened communities are more effective in mitigating racial disparities (Camilleri et al. 2023b; Polonik et al., 2023).

Calls for policies that target unjust exposure and health disparities are often led by community members and non-profit organizations that represent residents who are most impacted by exposure and health injustices. In the state of Illinois, the Neighbors for an Equitable Transition to Zero-Emissions (NET-Z) coalition have worked to reduce diesel pollution in communities across the state and have recently advocated for the state to implement an Advanced Clean Trucks (ACT) policy. This policy, initially implemented in California, would require manufacturers to gradually increase the proportion of zero-emission MHDVs sold in Illinois. Because this policy targets MHDVs, which predominantly operate along major roadways, it could offer a potential solution to reducing observed disparities in traffic-related air pollution exposure. As a result, this study was designed to simulate the potential benefits of Illinois adopting an ACT policy while also demonstrating the effectiveness of collaboration between scientists and local advocacy groups, such that the collaboratively agreed-upon experimental design aligned scientific research objectives with the questions and priorities of community members, for greater policy impact.

To assess the efficacy of policy interventions in reducing air pollution exposure and associated health injustices, pollutants must be accurately characterized at spatial resolutions that facilitate differential exposure and susceptibility estimates among population subgroups. This is particularly true in urban settings where pollutant gradients can be steep (Levy et al., 2014; Apte et al., 2017; Montgomery et al., 2023a), marginalized populations are prevalent, and geographic segregation due to systemically racist policies persists (e.g., redlining, chronic disinvestment) (Mohegh et al., 2021; Lane et al., 2022). Prior research has demonstrated that impact- and equity-focused assessments should resolve pollutants at ∼1 km or finer scales, due to an underestimation of impacts when assessments are conducted at a coarser resolution (Mohegh et al., 2021; Clark et al., 2022). Similarly, using coarse resolution (e.g., county- or state-level) baseline disease rates in health impact assessments can substantially underestimate true health impacts when compared with estimates that use health and demographic data at finer spatial scales (e.g., census tract-level) (Southerland et al., 2021; deSouza et al., 2024).

Advances in computational power and the availability of high-resolution emission data sets have enabled the use of Chemical Transport Models (CTMs) for assessments of air pollution exposure (Zhang et al., 2014) and remediation strategies at enhanced resolutions (Liang et al., 2019; Schnell et al., 2019). For our purposes, a high-resolution CTM refers to a model capable of resolving pollutant concentrations at spatial scales of ~1 km or finer, as models with this level of resolution are effective in capturing air pollution disparities. Recent studies have highlighted the effectiveness of using high-resolution CTMs to simulate electric vehicle adoption, focusing their analyses on the associated impacts on air quality (e.g., Li et al., 2016) and health (e.g., Pan et al., 2019; Gai et al., 2020; Mousavinezhad et al., 2024). However, only a few have leveraged their high-resolution CTM simulations to assess the overall equity implications (e.g., Camilleri et al., 2023b; Visa et al., 2023). Unlike prior studies, which often rely on arbitrary or generalized zero-emission vehicle adoption rates to estimate impacts, this study simulates a targeted zero-emission vehicle adoption policy designed with community-aligned real-world policy goals. This approach provides a more actionable and policy-relevant framework for evaluating impacts on exposure, health, and equity in Illinois, enhancing its utility for understanding policy outcomes and supporting policy advocacy.

In consultation with NET-Z coalition members, we designed a study that uses a regulatory-grade CTM to quantify the air quality and health impacts of MHDV emissions. Here, regulatory-grade CTM refers to the WRF-CMAQ model used by the U.S. EPA to support environmental policy decisions. This model is designed to meet rigorous scientific and regulatory standards, ensuring state-of-the-science simulations of air quality and pollutant dispersion. We then assess the effectiveness of an ACT policy scenario to reduce MHDV-related pollutant concentrations and health impacts in the Greater Chicago region. Projected MHDV sales and fleet turnover were modeled through 2050, assuming ACT implementation starts in 2027 and zero-emission vehicle energy demands would be met by renewable sources. Census-tract health and demographic data are then used to estimate the potential health benefits of the ACT as well as constrain equity outcomes. Our analysis is centered on the Greater Chicago region (Cook, DuPage, Kane, Kendall, Lake, McHenry, Will Counties), which is recognized as a substantial freight hub, attracting 53% of Illinois’ MHDV vehicle miles traveled (Eyth et al., 2022). This region is home to a diverse population of 8.5 million residents, representing approximately 68.5% of Illinois’ total population (Manson et al., 2023). Our results provide critical information for policymakers, environmental advocates, and public health practitioners striving to address the disproportionate burden of transportation-related air pollution on marginalized communities.

2 Methods

The below-described methodology grew out of a dialog between NET-Z coalition members and academic researchers at Northwestern University that was facilitated by the Environmental Defense Fund (EDF). The Northwestern Researchers had recently published a manuscript detailing the Air quality, health and equity implications of electrifying heavy-duty vehicles (Camilleri et al., 2023b). EDF thought the results of the paper and its press release (PR) could be helpful to share with local environmental justice groups participating in the NET-Z coalition. EDF staff helped organize a virtual Zoom-based briefing for NET-Z members from Northwestern researchers on the Camilleri et al. findings and subsequent additional analyses, and assisted with the preparation of an approachable 2-page briefing document that was distributed to the coalition’s members, including representatives from the Respiratory Health Association (RHA), Warehouse Workers for Justice (WWJ), and Little Village Environmental Justice Organization (LVEJO). During the briefing, and in a subsequent follow-up Zoom meeting, NET-Z members provided feedback on the published Northwestern study. Specifically, the coalition members criticized Camilleri et al. (2023b) for 1) its use of an arbitrary electric vehicle adoption policy as opposed to one of the policies they were lobbying state legislatures to adopt (e.g., ACT) and 2) its use of CTM simulations that underpredict pollutant concentrations on the south-west side of Chicago based on the lived experience of residents. As a result of these criticisms and conversations, the following experiment was co-designed by NET-Z, EDF, and the Northwestern researchers.

Our study domain encompasses the Chicago metropolitan area and its surrounding collar counties (Fig.1), including Cook, DuPage, Kane, Kendall, Lake, McHenry, and Will Counties, which we henceforth refer to as the Greater Chicago region. The Chicago Metropolitan Agency for Planning (CMAP) estimates that in the Greater Chicago region, nearly 1 in 7 vehicles on urban interstates are trucks and that ~25% of all freight trains and 50% of intermodal trains in the U.S. pass through the area (CMAP, 2017). This substantial truck and rail activity underscores the region’s role as a critical freight hub, which is further evidenced by its high concentration of freight establishments per capita (Cidell, 2010), such as warehouses, which can experience up to 30,000 truck trips daily (CMAP, 2017). Truck traffic associated with the movement of freight has disproportionate impacts, as warehousing in Illinois is 195% more likely to be situated in Hispanic or Latino neighborhoods (Environmental Defense Fund, 2024). Consequently, truck traffic in this region has sparked concerns raised by Chicago-based community groups (e.g., LVEJO, WWJ), particularly regarding its disproportionate impact on local environmental justice communities (WWJ, 2023; Lippert, 2024). In 2023, the deployment of 35 truck-counting cameras throughout Chicago revealed that communities along I-55, southwest of downtown, frequently experience thousands of truck passages daily in predominantly non-white neighborhoods (Center for Neighborhood Technology, 2024). With over half of the state’s population residing within the Greater Chicago region, this area offers a crucial opportunity to understand how targeted MHDV policy interventions can effectively address urban air pollution and current environmental justice issues.

Fig.1 The study domain encompasses the Chicago metropolitan area and its surrounding collar counties, including Cook (location of Chicago, IL), DuPage, Kane, Kendall, Lake, McHenry, and Will Counties.

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2.1 Air quality modeling

To quantify the impact of MHDV emissions and assess the policy benefits and tradeoffs of an ACT policy adoption scenario in Illinois, we simulate changes in air pollutants as a result of two zero-emission MDHV adoption scenarios using the two-way coupled Community Multi-scale Air Quality (CMAQ, v5.2 (Byun and Schere, 2006)) and Weather Research and Forecasting (WRF, v3.8 (Skamarock et al., 2008)) modeling platform (WRF-CMAQ (Wong et al., 2012)). Using a nested modeling framework, within our innermost high-resolution domain we simulate air pollutant concentrations at a 1.3 km² horizontal spatial resolution over a midwestern domain centered on southern Lake Michigan, encompassing the Greater Chicago region. Due to computational expense, meteorological conditions were simulated for one month within each meteorological season, specifically August and October 2018, and January and April 2019. Our meteorological modeling framework and evaluation are outlined in detail in Montgomery et al. (2023b). Monthly simulations for baseline (i.e., simulations where the magnitude of vehicle emissions are not modified) and zero-emission MHDV adoption scenarios were then averaged to approximate annualized mean conditions, aligned with methods employed by previous research (Peng et al., 2021; Torbatian et al., 2024).

Simulated emissions are developed using the EPA’s Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system, version 2016 V2 (Eyth et al., 2022). This emission data set is developed using the EPA’s Motor Vehicle Emission Simulator (MOVES) version 3 and the 2017 NEI (version 2016fj), which is projected back one year. The SMOKE modeling platform incorporates MOVES to generate hourly, gridded, and meteorologically informed emissions through the combination of county-specific emission factors with traffic activity data (e.g., vehicle miles traveled, hours of idling activity, etc.), meteorological data (e.g., ambient temperature and humidity from WRF-CMAQ), and other ancillary data, such as speed distributions (Eyth et al., 2022). This modeling framework simulates vehicle processes such as running exhaust, start exhaust, brake wear, tire wear, evaporative emissions, crankcase exhaust, refueling vapor emissions, extended idle exhaust from long-haul combination trucks (i.e., hotelling), and the recent addition of off-network idling (ONI) exhaust (U.S. Environmental Protection Agency, 2021b; Eyth et al., 2022). The recent addition of ONI is meant to account for emissions resulting from vehicles idling off roadways for less than one hour, such as vehicles idling in driveways, pick-up lines, or during loading and unloading of freight. In MOVES vehicle emission processes are categorized into six groups: rate-per-distance, rate-per-vehicle, rate-per-profile, rate-per-hour, rate-per-hour-oni, and rate-per-start, taking into consideration vehicle fleet characteristics such as vehicle make, model, and age, road type, and fuel properties (Eyth et al., 2022).

County-level emissions are spatially distributed to uniform grids using spatial surrogates, which quantify the proportion of a geographic attribute within a grid cell relative to the corresponding attribute’s areal extent across a given county. Highly resolved spatial surrogates used to spatially distribute emissions were developed by the Lake Michigan Air Directors Consortium (LADCO, 2022). The default spatial surrogate used to distribute ONI emissions in SMOKE is based on the National Land Cover Database’s medium and high development intensity classification, which includes areas with a mix of constructed materials and vegetation, or highly developed areas where large numbers of people reside or work. This spatial distribution reasonably represents ONI activity for light-duty vehicle types but does not adequately capture the localized idling activity of MHDVs, which often idle at warehouses, distribution centers, ports, railyards, intermodal facilities, and feeder roads. Recent satellite observations have detected elevated levels of NO₂ pollution downwind of areas with dense warehousing, a feature that is not currently captured by the U.S. EPA’s emission inventory (Goldberg et al., 2024; Kerr et al., 2024a). Therefore, as a first step to augment the spatial distribution of MHDV emissions, three-fourths of ONI emissions from specific MHDVs (i.e., single-unit short- and long-haul trucks, and combination short- and long-haul trucks) are allocated to warehouse locations utilizing data from the Commercial Real Estate Market Analytics (CoStar). Within the SMOKE modeling platform, emissions from on-road, point, and area sources are generated, whereas biogenic emissions, lightning emissions, and windblown dust are calculated within CMAQ.

Baseline simulations were evaluated following the EPA recommendations (Dennis et al., 2010), using an operational evaluation by comparing hourly model performance with EPA surface observations. Within the model domain, baseline WRF-CMAQ simulations of average hourly NO₂ and O₃ are well correlated with EPA surface observations (r > 0.6), with an average normalized mean bias (NMB) of −6.79% and 32.13%, respectively (Appendix A1). While there are no set benchmarks for photochemical modeling in the U.S., our model performance of NMB and Pearson correlation coefficients (r) are aligned with other previously published Midwestern-focused WRF-CMAQ modeling studies (Bickford et al., 2014; Montgomery et al., 2023b).

To assess the overall impact of MHDV emissions on air quality, we design one scenario that eliminates all MHDV tailpipe emissions from the existing on-road MHDV fleet within the regulatory-grade model (Tab.1). We define MHDVs as the Federal Highway Administration’s Highway Performance Monitoring System (HPMS) vehicle Class 2b and higher. Given our modeling framework, the HPMS MHDV classifications do not directly map to MOVES vehicle classifications. Therefore, HPMS MHDV classification were aligned with MOVES definitions by incorporating the regulatory class coverage adjustments from MOVES, which provided national estimates of the composition of MOVES vehicle types when converting from the HPMS classifications (U.S. Environmental Protection Agency, 2021b). For example, for MOVES’s vehicle class “Light Commercial Truck,” only 24.74% falls under the MHDV classification (i.e., Class 2b and higher). Therefore, we modified MOVES emission factor tables to reflect zero tailpipe emissions for 24.7% of the MOVES Light Commercial Truck vehicle class. Emission factors for brake and tire wear processes were not modified. We assessed the difference in annualized population-weighted mean pollutant concentrations between our simulation in which all tailpipe emissions from MHDVs are removed and the baseline, attributing the difference in air pollution concentrations to MHDV-related traffic activity. Annualized concentrations were calculated by averaging results from the four simulated months—August and October 2018, and January and April 2019—representing one month from each meteorological season.

Tab.1 Sensitivity simulations comparing baseline, 100% MHDV scenario, and ACT adoption in Illinois, highlighting modifications to emissions and spatial distribution of off-network idling (ONI) emissions

Item	Scenario
	Baseline	100% MHDV	ACT Adoption in IL
Emission changes	No modifications	100% of tailpipe emissions from MHDVs removed	Tailpipe emission reductions per class: Class 2b&3: 46.5% Buses: 65% Vocational: 62% Tractor-trailers: 35%
Spatial distribution of ONI emissions	75% of ONI MHDV emissions assigned to grid cells containing warehouses	Same as baseline	Same as baseline

For our ACT policy adoption scenario, we simulated an instantaneous transition to zero tailpipe emission MHDVs in proportions aligned with the expected percentage of on-road zero-emission MHDVs in 2050 if Illinois adopted an ACT policy effective in model year 2027 (Tab.1). Illinois-specific fleet turnover starting with model year 2027 was calculated following the methodology of Robo et al. (2022), in which future fleet turnover is estimated based on historical average turnover rates and projected sales of MHDVs through 2050. Using this approach, we estimated the percentage of on-road zero-emission MHDVs in 2050 to be 46% of Class 2b vehicles, 47% of Class 3 vehicles, 65% of buses, 62% of vocational vehicles (such as refuse trucks, motor homes, and single-unit trucks), and 35% of tractor-trailers (Fig.2(a)). MOVES regulatory class coverage adjustments do not differentiate between Class 2b and Class 3. Consequently, we adjusted emission reductions from these two classes by averaging their corresponding projected fleet turnover, resulting in a reduction of 46.5%. By 2050, the largest number of zero-emission MHDVs in the Greater Chicago region will be Class 2b/3 vehicles, totaling over 108000 vehicles, followed by vocational vehicles which will number over 76000 vehicles (Fig.2(b)). We modified MOVES emission factor tables, scaling reductions based on the zero-emission MHDV projections and the regulatory class coverage adjustments, assuming current vehicle demographics and technology. Given ongoing efforts to decarbonize the electricity grid, the supplemental energy required for zero-emission vehicles in this policy scenario is presumed to originate from renewable sources. We posit that this assumption is reasonable given that in 2021, Illinois signed the Climate and Equitable Jobs Act which targets a transition to 100% renewable energy by 2050 (Climate and Equitable Jobs Act, 2021). While not all energy production occurs in Illinois, previous EV adoption analyses revealed only marginal effects when additional electricity generation unit emissions are accounted for within the CTM domain (Visa et al., 2023)

Fig.2 (a) Estimated percent of on-road zero-emission MHDVs and (b) total number of on-road zero-emission MHDVs in the Greater Chicago region as a result of modeled Advanced Clean Trucks policy adoption in Illinois beginning with model year 2027 and projected through 2050. The legend includes examples of vehicles within each class.

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2.2 Health impact analyses

Using differences in census tract-level air pollutant concentrations between CTM sensitivity simulations and the baseline ($\mathrm{\Delta }x)$, we assessed the potential health benefits/tradeoffs of the MHDV transitions described above. Specifically, we estimate the NO₂ and O₃ attributable premature mortality and NO₂ attributable pediatric asthma incidence using Eqs. (1) and (2):

(1)${\mathrm{A}\mathrm{F}}_{\mathrm{c}\mathrm{t}}=1-{\mathrm{e}}^{(-\beta {\mathrm{\Delta }x}_{\mathrm{c}\mathrm{t}})},$

(2)${\mathrm{M}\mathrm{o}\mathrm{r}\mathrm{t}}_{\mathrm{c}\mathrm{t}}={\mathrm{B}\mathrm{M}\mathrm{R}}_{\mathrm{c}\mathrm{t}}\times {\mathrm{P}\mathrm{O}\mathrm{P}}_{\mathrm{c}\mathrm{t}}\times {\mathrm{A}\mathrm{F}}_{\mathrm{c}\mathrm{t}}.$

We first estimated the fraction of the underlying health outcome attributable to air pollution exposure, i.e., the attributable fraction (AF), following Eq. (1). Census tract-level air pollution concentrations were determined by calculating the area average of the intersection between grid cell-level simulated pollutant concentrations and census tract polygons using the GeoPandas package (Jordahl et al., 2021). β coefficients for each pollutant and health outcome were derived from relative risks (RRs) calculated in previous peer-reviewed epidemiological studies. We estimated the annual premature all-cause mortality associated with long-term exposure to NO₂ for people over 30 years using a relative risk (RR) of 1.04 (95% CI 1.01–1.06) per 10 μg/m³ converted to ppb (parts per billion) equivalent (HEI, 2022) and a RR of 1.02 (95% CI 1.01–1.04) (Turner et al., 2016) per 10 ppb was used to estimate the all-cause mortality associated with long-term exposure to daily maximum 8-h running mean O₃ (MDA8 O₃). Lastly, NO₂-attributable pediatric asthma incidence (new cases annually) was estimated using an HEI-derived RR of 1.05 (95% CI 0.99–1.12) per 10 μg/m³ (HEI, 2022) for children under the age of 18.

For each census tract, the annual all-cause air pollution attributable deaths were then calculated by multiplying the census-tract level AF from Eq. (1) by the baseline mortality rate (BMR) or asthma incidence and the population (POP) within each census tract (ct; Eq. (2)). We leverage high-resolution all-cause BMRs at the census tract level, stratified by 5-year age groups and derived from USALEEP abridged life tables with modifications for broader use in national health benefits analyses (Raich et al., 2020). BMRs represent the time period 2010–2015. Census-tract level demographic data of race and ethnicity was collected from the U.S. Census Bureau 2015–2019 American Community Survey (ACS; accessed by the National Historical Geographic Information System) (Manson et al., 2023). Given the lack of high-resolution asthma incidence rates, here we used annual state-level asthma incidence rates for 2019, stratified by 5-year age group from the Global Burden Disease Study from 2019 (Murray et al., 2020). Given the underlying differences in methodologies used to derive the different RRs, such as adjusting for confounding factors, we report air pollution attributable health impacts for each pollutant separately.

3 Results

3.1 Impact of zero-emission MHDV adoption policy on NO₂

To assess the impacts of zero-emission MHDV adoption scenarios in Illinois, we simulate (i) baseline conditions, (ii) instantaneous elimination of all MHDV tailpipe emissions, and (iii) instantaneous transition to the proportion of zero tailpipe emission MHDVs that could be achieved by 2050 with adoption of an ACT new vehicle sales targets starting in model year 2027 (see Section 2). In the baseline simulations, annual population-weighted mean NO₂ concentrations are 11.7 ppb, with concentrations exceeding 25 ppb within the urban core of Chicago, near airports (i.e., O’Hare International and Chicago Midway), and along interstate highways that feed into the city (Fig.3(a)). Outside of Cook County, home of Chicago, simulated NO₂ concentrations are generally less than 8 ppb, with the exception of city centers and primary trucking routes, e.g., I-294, I-80, and I-55. We compare our baseline results to those of Montgomery et al. (2023b), as both studies utilize the same meteorological inputs and modeling framework, with the primary methodological difference, the emission modeling platforms used. We find that locations of elevated NO₂ concentrations in the baseline simulation are similar to those found in Montgomery et al. (2023b). However hot spots near airports were not found in Montgomery et al. (2023b) and are here attributable to the newer emission modeling platform, i.e., SMOKE version 2016V2, which treats airport emissions as two-dimensional pollution sources rather than distributing these emissions vertically along the glide path (Eyth et al., 2022).

Fig.3 WRF-CMAQ simulated change in annualized mean (August and October 2018, January and April 2019) NO2 concentrations for (a) baseline, (b) NO2 reduction when MHDV emissions are eliminated (100% zero-emission MHDV scenario minus baseline), (c) NO2 reduction under an Illinois Advanced Clean Trucks (ACT) policy scenario (ACT minus baseline), and (d) percent of MHDV attributable NO2 reduced by an ACT policy scenario within Illinois over the Greater Chicago region (Cook, DuPage, Kane, Kendall, Lake, McHenry, and Will Counties).

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To determine where MHDV emissions most impact the Greater Chicago region, we remove MHDV tailpipe emissions from the baseline scenario. We find that in the Greater Chicago region, MHDV emissions contribute to ~22.2% (2.59 ppb) of the domain’s annual population-weighted mean NO₂ concentrations, with localized MHDV NO₂ contributions reaching 10.13 ppb (Fig.3(b)). MHDV pollution is simulated to be most concentrated along primary roadways near downtown Chicago and in the collar counties of Lake and Will. Localized hotspots of MHDV pollution off roadways are particularly notable in central DuPage and Will counties. These hotspots are attributed to truck stops and rest areas where long-haul combination trucks idle extensively during mandated rest periods. MHDV pollution concentrations decrease away from the urban core of Chicago, with local minimum contributions reaching 0.46 ppb in more rural portions of McHenry County.

In our ACT policy simulations, we estimate that ~48% of on-road MHDVs in Illinois will have transitioned to zero-emission vehicles by 2050 (Fig.2). This shift to zero-emission MHDVs would result in reductions of 0.98 ppb (−8.4%) for annual population-weighted mean NO₂ concentrations, with a local maximum decrease of 3.33 ppb from the baseline simulation (Fig.3(c)). The largest decreases in NO₂ concentrations are observed along primary roadways, particularly north of downtown Chicago, where MHDV-attributable pollution is highest. The smallest reductions in MHDV pollution occur within the collar counties, with a localized minimum reduction of 0.19 ppb. Overall, the ACT policy scenario leads to localized reductions in MHDV-related NO₂ pollution ranging from 31% to 42% across the Greater Chicago region (Fig.3(d)). The largest relative percentage reductions occur predominantly away from major roadways, while the lowest percentage changes are observed along primary roadways in Cook, Lake, and Will counties. This pattern occurs because computing relative percentage changes from small absolute concentrations yields larger percentage changes. Truck stops are also identified as regions where the percentage reduction of MHDV-related pollution is ~30%.

3.2 Impact of zero-emission MHDV adoption policy on O₃

The annual population-weighted mean concentration of MDA8 O₃ is 44.32 ppb in the baseline scenario. The highest MDA8 O₃ concentrations occur within Chicago’s collar counties, reaching up to 49.32 ppb (Fig.4(a)). Conversely, the lowest concentrations are observed along primary roadways and within the urban core, with a localized minimum of 20.74 ppb near O’Hare International and Midway Airports. Spatially, MDA8 O₃ concentrations exhibit a clear gradient, transitioning from lower levels in densely populated urban areas to higher levels in the collar counties – highlighting the influence of local emission sources and atmospheric conditions on O₃ formation.

Fig.4 WRF-CMAQ simulated change in annualized mean (August and October 2018, January and April 2019) MDA8 O3 concentrations for (a) baseline, (b) difference in MDA8 O3 between 100% zero-emission MHDV scenario and baseline (100% zero-emission MHDV - baseline), (c) difference in MDA8 O3 between Illinois Advanced Clean Trucks policy scenario and baseline (ACT - baseline) over the Greater Chicago region (Cook, DuPage, Kane, Kendall, Lake, McHenry, and Will Counties).

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When MHDV tailpipe emissions are removed, we find increases in MDA8 O₃ concentrations, particularly along major road networks (Fig.4(b)). This phenomenon is primarily due to the reduction of NO_x titration, a process in which NO reacts with hydroxyl radicals or O₃ itself to decrease O₃ concentrations (Isaksen et al., 2009). Without MHDV-related NO_x emissions, less O₃ is destroyed through this reaction. The annual population-weighted mean concentration of MDA8 O₃ is estimated to be 0.83 ppb (1.86%) higher when MHDV tailpipe NO_x emissions are removed, with a maximum simulated local increase of 4.23 ppb. MDA8 O₃ increases from MHDV emissions reductions occur predominantly along interstates and highways, a pattern that is the spatial inverse of where MHDV NO₂ pollution is highest. Rural portions of McHenry County see decreases in MDA8 O₃, while suburban counties of Lake, Kendall, Will, and Kane exhibit regions that experience minimal change in MDA8 O₃ exposure when MHDV emissions are removed.

Similar results are found when simulating ACT policy adoption, albeit to a lesser extent, with rural regions (e.g., McHenry, Kendall, and Kane Counties) experiencing slight decreases (up to −0.08 ppb) or no change in MDA8 O₃ concentrations (Fig.4(c)). Increases in annual population-weighted mean MDA8 O₃ for the domain were 0.35 ppb, an increase of 0.78% from the baseline simulation, with localized maximum increases up to 1.48 ppb. This observed increase in MDA8 O₃ is consistent with findings from electric vehicle adoption studies, which have also reported increases in ozone concentrations over primary roadways in the Greater Chicago region (Camilleri et al., 2023b; Visa et al., 2023; Mousavinezhad et al., 2024) and beyond (Pan et al., 2019; Peters et al., 2020; Skipper et al., 2023), as well as with earlier work focused on the weekend effect, wherein less weekend traffic in urban environments leads to higher weekend O₃ concentrations than observed on weekdays (Wolff et al., 2013) .

Tropospheric ozone production is influenced by the balance between NO_x and volatile organic compounds (VOCs), with the VOC-NO_x ratio serving as an indicator of whether ozone formation is driven primarily by the availability of VOCs or NO_x. On average for the U.S., the transition from a VOC-limited to a NO_x-limited regime occurs at a VOC:NO_x ratio of ~9.2 (Ashok and Barrett, 2016), but can differ regionally depending on meteorology, emission sources, and VOC constituents (Seinfeld and Pandis, 2016). However, researchers focused on urban environments found that this transition occurs at a ratio of ~6.7 in the Chicago region (Ashok and Barrett, 2016). In our baseline scenario, the annualized mean VOC:NO_x ratio for the Greater Chicago region is 4.75, with localized ratios ranging from 0.83 to 8.55 (Fig.5(a)). The lowest VOC:NO_x ratios (VOC:NO_x < 4) are simulated within urban areas (e.g., Cook, DuPage Counties) where O₃ concentrations are lowest (Fig.4), indicating VOC-limited regimes. A transition toward NO_x-limited regimes (VOC:NO_x > 7) is simulated as one moves from urban centers to more rural areas where O₃ concentrations are highest (e.g., northwestern portion of McHenry County, southern portions of Will County). Variations in January, April, and October VOC:NO_x ratio within the Greater Chicago region, with monthly means ranging from 3.94 to 4.25, exhibit a spatial pattern consistent with annualized averages (Appendix A3). However, in August, the mean VOC:NO_x ratio across the study domain increases to 7.15, indicative of a potential shift toward a transitional state between VOC- and NO_x-limited regimes in some areas of the Greater Chicago region.

Fig.5 WRF-CMAQ simulated annualized mean (August and October 2018, January and April 2019) volatile organic compounds (VOC) to NOx ratios for (a) baseline, (b) 100% zero-emission MHDV scenario and, (c) an Illinois Advance Clean Trucks policy scenario over the Greater Chicago region (Cook, DuPage, Kane, Kendall, Lake, McHenry, and Will Counties).

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When all MHDV tailpipe emissions are removed, the Greater Chicago region domain annual mean VOC:NO_x ratios increase to 6.28 and localized ratios reach 10.64 in the collar counties (Fig.5(b)). However, despite the increase in VOC:NO_x ratios across the study domain, parts of the city of Chicago – particularly along primary roadways – are still VOC-limited (VOC:NO_x < 4). When simulating the ACT policy adoption scenario, the annual mean VOC:NO_x ratio for the Greater Chicago region is higher than the baseline domain mean but lower than the ratios when all MHDV emissions are removed (5.21), with isolated areas reaching 9.28 (Fig.5(c)). In August, mean VOC:NO_x ratios increase to 7.98 within the study domain, indicating a transitional regime that may contribute to the observed smaller extent of MDA8 O₃ increases during the summer month. This finding underscores the potential of zero-emission MHDV adoption strategies to facilitate O₃ reductions, as evidenced by the increase in annualized average VOC:NO_x ratios in both sensitivity simulations. However, it also highlights that isolated MHDV-specific policy interventions are insufficient to shift the O₃ regime to be NO_x-limited within the entire Greater Chicago region. Therefore, additional measures, such as VOC emission controls or additional vehicle sector emission reductions are necessary to achieve a full transition to a NO_x-limited regime within the Greater Chicago region.

3.3 Zero-emission MHDV adoption policy on health and equity outcomes

Next, we examine the health and equity implications of MHDV-related pollution across the Greater Chicago region at the census-tract scale. This assessment involves evaluating the change in simulated criteria air pollutants alongside USALEEP all-cause mortality rates for each census tract across the domain. Here, we find MHDVs contribute to ~1330 (95% confidence interval (CI: 330, 2000) premature deaths per year and 1580 (CI: 310, 3870) new cases of pediatric asthma due to NO₂ exposure within the region. Due to MHDVs contributions to reduced MDA8 O₃ concentrations, we estimate that 110 (CI: 50, 210) premature deaths per year are avoided by MHDV emissions within the study domain.

Within the study domain, we integrate our findings of simulated air pollution and health outcomes with census tract demographic composition to evaluate the equity impacts of MHDV emissions. The demographic composition of the Greater Chicago region includes residents that are 51% white, 17% Black, 23% Hispanic or Latino, and 7% Asian (Appendix A4). When examining the total impacts of MHDVs within the Greater Chicago region, people of color bear a disproportionate burden, as census tracts with the highest MHDV pollution exposure (i.e., 10th decile) consist of 45% Black, 33% white, 13% Hispanic or Latino, and 7% Asian populations. Within these census tracts, MHDV-related pollution contributes up to 4.16 ppb of NO₂. Census tracts with the largest MHDV-related NO₂ health impacts experience premature death rates of up to 49 deaths annually per 100000 residents. In contrast, census tracts with the lowest MHDV exposure, predominantly composed of white residents, exhibit marginal rates of NO₂-related health impacts, with fewer than 1 premature death annually per 100000 residents from MHDV-related pollutants.

In estimating the health benefits of an ACT policy implementation scenario for Illinois, our analysis indicates that the Greater Chicago region would experience a reduction of 500 premature deaths per year (CI: −120, −750), primarily attributed to decreases in NO₂, representing a reduction of 37.6% in MHDV-related NO₂ mortality (Tab.2). All census tracts within the area experience decreases in attributable mortality rates, with rates of up to 71 deaths per year per 100000 people avoided in census tracts with the largest reductions in NO₂ exposure (Appendix A2). Additionally, reductions in NO₂ would lead to a decrease in pediatric asthma cases across the Greater Chicago region, amounting to 600 (CI: 120, −1440) new cases prevented annually, representing a 38.0% reduction in new pediatric cases attributable to MHDV-related pollution. The increase in MDA8 O₃ would result in an increase of 40 (CI: 22, 90) deaths per year, with individual census tracts seeing up to 7 additional deaths per 100000 people each year.

Tab.2 Attributable annual premature deaths (per 100,000 for 30 years and older) from exposure to NO2 and MDA8 O3 concentrations and new cases of pediatric asthma due to NO2 exposure from (first row) MHDV-attributable pollutant concentrations, (second row) reductions in MHDV pollution concentrations as a result of an Illinois ACT policy adoption scenario, (third row) percent change in MHDV health impacts from ACT policy adoption scenario compared to baseline over the Greater Chicago region (Cook, DuPage, Kane, Kendall, Lake, McHenry, and Will Counties)

Items	Attributable mortality NO2	Attributable mortality MDA8 O3	Pediatric asthma (New Cases)
MHDVs total contribution	1330 (CI: 330, 2000)	−110 (CI: −50, −210)	1580 (CI: 3870, 310)
ACT policy reductions	−500 (CI: −120, −750)	+40 (CI: 22, 90)	−600 (CI: 120, −1440)
Percent reduction	−37.6%	+36.3%	−38.0%

Under an ACT policy adoption scenario, the most substantial NO₂ reductions, i.e., reductions larger than 1.5 ppb, are primarily observed in census tracts composed of a higher percentage of residents of color (Fig.6(a)). When considering the 10th decile, which identifies communities simulated to have the largest reductions in MHDV-related pollution exposure, non-white residents collectively make up over 50% of the decile. However, when examining variations in MDA8 O₃, minimal change in concentrations occurs within regions predominantly inhabited by white residents, whereas the most substantial disbenefits are observed in areas with demographic compositions exceeding 60% nonwhite in the 10th decile (Fig.5(b)). Census tracts that experience the largest reductions in NO₂ (top decile) are estimated to have reductions in NO₂-attributable mortality of up to 18 premature deaths per year per 100000 people annually, with nonwhite residents experiencing the largest benefits (Fig.5(c)). For example, the residents of census tracts with the largest NO₂-associated reductions in mortality are 48% Black, 12% Hispanic or Latino, 7% Asian and 31% white. Larger health benefits for Black residents are, in part, attributed to higher baseline mortality rates among this demographic group (Camilleri et al., 2023b).

Fig.6 Deciles of (a, b) change in NO2 and MDA8 O3 concentrations between an ACT policy scenario and baseline and (c, d) change in NO2 and MDA8 O3 attributable mortality rates stratified by race and ethnic composition over the Greater Chicago region.

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4 Discussion

Utilizing a high-resolution regulatory-grade CTM, this study characterizes the air pollution, health, and equity disbenefits of current MHDV tailpipe emissions and evaluates the efficacy of an ACT policy to ameliorate these negative outcomes in the Greater Chicago region. Our findings highlight the substantial impact MHDV emissions have on local air pollution and public health, particularly for neighborhoods with a higher percentage of nonwhite residents. Given this context, we find that the implementation of an ACT policy in Illinois offers promise for mitigating some of the adverse effects of MHDV pollution, with the largest localized reductions of MHDV-related NO₂ pollution simulated in census tracts composed of a higher percentage of residents of color. The health and equity benefits of reduced MHDV-related NO₂ pollution are slightly offset by associated marginal increases in MDA8 O₃ concentrations that disproportionately impact non-white residents, with the highest increased O₃ concentrations observed along primary roadways. However, even in the areas where O₃ would be increased, health benefits from reduced NO₂ outweigh the disbenefits associated with increased O₃ exposure.

We find that our instantaneous ACT policy adoption scenario would reduce localized NO₂ concentrations up to 42% within our study domain, with overall population-weighted mean NO₂ decreasing ~8%. This decrease is notable given epidemiological advances that have strengthened the evidence linking NO₂ exposure to premature mortality. In 2020 Huangfu and Atkinson indicated “moderate confidence” in the linkage of NO₂ exposure with premature mortality. In 2021 the World Health Organization cited new epidemiological evidence in revising its NO₂ air quality guidelines to be more stringent (10 µg/m³ ≈ 5.3 ppb annual average) (World Health Organization, 2021). Most recently, a systematic review and meta-analysis conducted by the Health Effects Institute (HEI) in 2022 found “high confidence” in NO₂ attributable mortality. Using relative risk derived from the 2022 HEI systematic review and meta-analysis, NO₂-attributable mortality in the U.S. was estimated at nearly 171,000 premature deaths annually, with the Chicago region experiencing mortality rates 1.3 times higher than the CONUS average (Camilleri et al., 2023a). NO₂ has also been found to exacerbate asthma in children due to its potential to cause airway inflammation and oxidative stress (Achakulwisut et al., 2019). These findings detail the growing epidemiological confidence in the health harmful effects of NO₂ exposure sit in contrast with the U.S. annual primary and secondary NO₂ standards (53 ppb), which have not changed since 1971, and the 1-h standard of 100 ppb, which was last updated in 2010 (U.S. Environmental Protection Agency, 2018). In addition, NO_x emissions are a public health concern due to their role as precursors to tropospheric O₃ and fine particulate matter, both of which are contributors to air pollution-related morbidities and mortality. Given the context of these studies and the large contribution of NO_x emissions from the transportation sector in the U.S., our results underscore the importance of targeted policies, such as the ACT, to reduce NO₂ concentrations.

Our results suggest that the adoption of an ACT policy would lead to a reduction in NO₂ concentrations but would concurrently result in marginally increased MDA8 O₃ concentrations across most of the Greater Chicago region. This observation is consistent with previous studies that simulate zero-emission vehicle adoption, indicating that when traffic-related NO_x pollution decreases, there is the possibility of a subsequent increase in MDA8 O₃ concentrations due to the role NO plays in suppressing the formation and survival of O₃ in VOC-limited environments. For example, Visa et al. (2023) simulated the electrification of 30% of all transportation modes (motorcycles, primarily gasoline-fueled passenger light-duty cars and trucks, and primarily heavy-duty diesel-fueled refuse trucks, motorhomes, commercial short- and long-haul trucks, and intercity, transit, and school buses) in the Chicago region and found increases in MDA8 O₃ exceedance days in urban regions. Even studies that simulate a full conversion of on-road vehicles to zero-emission fleets, as well as consider changes in future fleet composition and traffic volumes, find an increase in simulated MDA8 O₃ concentrations of up to 1.09 ppb (Mousavinezhad et al., 2024). This highlights the potential necessity of considering supplementary policy measures at the city level to limit VOC emissions (Wang et al., 2024), in addition to efforts aimed at reducing traffic-related pollution.

Our ACT scenario results suggest that the implementation of an ACT policy has the potential to not only enhance air quality but also yield ancillary benefits by reducing adverse health outcomes and mitigating socioeconomic impacts. We find that an ACT policy adoption in the Greater Chicago region would reduce MHDV-related NO₂ adverse health outcomes by ~38%. Indeed, despite the potential increase in O₃ concentrations in urban areas (e.g., Cook County, along primary roadways), the health benefits stemming from reductions in NO₂ outweigh the adverse effects associated with additional O₃. Moreover, we utilize the 2017 estimated value of a statistical life, which is 9.6 million U.S. dollar (Viscusi and Masterman, 2017), to estimate that a decrease in MHDV-related NO₂ mortality would result in an annual decrease of 4.8 billion U.S. dollar in health damages within the Greater Chicago region. An ACT policy would also lead to an annual decrease of 3.9 million tons of CO₂ emissions in the Greater Chicago region. Using a social cost of carbon, set at 185 US dollar per metric ton of CO₂ to account for the socioeconomic impacts of greenhouse gas emissions (Rennert et al., 2022), this reduction would result in an annual benefit of 731 million U.S. dollar. This finding highlights that economic benefits derived from improved air quality can outweigh the economic benefits from reductions in greenhouse gas emissions, consistent with previous literature (Shindell et al., 2021).

Our study examines the racial and ethnic composition of air pollutant exposure and associated health outcomes, and suggests that neighborhoods with higher percentages of residents of color stand to experience the greatest health benefits from an ACT policy adoption. Previous literature has identified persistent equity gaps associated with zero-emission passenger vehicle adoption, noting that the benefits are more likely to be realized by non-disadvantaged communities (Yu et al., 2023). This is attributed to the ability of residents in these areas to afford zero-emission vehicles, coupled with the greater likelihood of charging stations located within more affluent neighborhoods (Hsu and Fingerman, 2021). Our MHDV-focused results suggest a different equity outcome. We find that implementing policies aimed at transitioning MHDVs to zero-emission vehicles in the Greater Chicago region presents a more equitable approach since a majority of non-white and low-income populations reside near major roadways where MHDVs are prevalent. Our findings underscore the potential advantages of targeted zero-emission vehicle adoption policies. However, it is necessary to acknowledge that our study does not address the equity outcomes associated with all aspects of zero-emission vehicles. A comprehensive cradle-to-grave life cycle assessment of zero-emission MHDVs is needed to provide additional insights into the full spectrum of benefits and tradeoffs associated with zero-emission vehicle transition policies (Das et al., 2023). Furthermore, our analysis only considers the Greater Chicago region, but research has demonstrated that zero-emission vehicle adoption benefits and trade-offs vary by region (He et al., 2016; Pan et al., 2019; Peters et al., 2020; Schnell et al., 2021; Skipper et al., 2023; Mousavinezhad et al., 2024). However, given the substantial impact of transportation-related pollutants and the increasing relative ethnic and racial disparities in pollution-attributable health burdens observed in recent years, policy interventions explicitly aimed at reducing inequalities in pollution exposure are needed. Our simulation of an ACT policy scenario demonstrates how targeting MHDVs for transition to zero-emission vehicles contributes to lessening the inequitable health burden experienced by predominantly non-white communities.

A prior study that examined the implications of an instantaneous transition to 30% electric heavy-duty vehicles focused on the same region reported population-weighted reductions of 0.5 ppb of NO₂ (~6%) and an increase in MDA8 O₃ of up to ~1.5 ppb in the urban core of Chicago (Camilleri et al., 2023b). In comparison, our analysis of an ACT policy scenario simulates a similar magnitude increase in MDA8 O₃ but a larger magnitude decrease in population-weighted NO₂ concentrations (−0.98 ppb, or ~8%). Given that our ACT policy simulation transitions ~48% of MHDVs to zero-emission vehicles, compared to the 30% transition of only HDVs in Camilleri et al., we would anticipate more substantial NO₂ reductions in the ACT simulation. However, additional differences between these two studies likely arise due to different emission modeling platforms (i.e., SMOKE 2016V2 platform and 2016Beta platform), as the 2016Beta platform has higher emission rates for heavy-duty diesel vehicles (US Environmental Protection Agency, 2021b; Lang et al., 2025). Although the findings are closely aligned, discrepancies underscore the importance of considering specific emission modeling platforms when evaluating the air quality impacts of transitioning to zero-emission vehicles.

While our analysis showcases the value of both community-engaged and policy-relevant science, sub-stantial work remains. The EPA’s finalization of the Clean Truck Plan in 2022, which targets substantial reductions in NO_x emissions from heavy-duty vehicles starting with model year 2027 (US Environmental Protection Agency, 2021a), highlights the importance of incorporating the most up-to-date policies into future zero-emission vehicle assessment frameworks. We also note that our study is based on current vehicle fleet characteristics and future changes in fleet makeup may further contribute to reductions in traffic-related pollution. Therefore, future analyses should account for projected fleet traffic volumes and changes in fleet composition. Moreover, research has identified heightened and disproportionate pollution impacts near inter-regional freight facilities (Thind et al., 2023; Goldberg et al., 2024; Kerr et al., 2024a), emphasizing the need to explore policy-based solutions tailored to address the localized effects of medium- and heavy-duty vehicle activity.

5 Conclusions

This study demonstrates that neighborhood-scale CTMs can be leveraged to evaluate the impacts of policy interventions on racial and ethnic disparities in traffic-related air pollution, with community feedback playing a pivotal role in enhancing the scope and application of the research. As local community groups advocate for the urgent need to tackle issues of environmental injustice, our findings offer insights into the potential of policy measures, such as an ACT policy, to improve air quality and reduce health inequities, particularly in marginalized communities. Future research and policy development are essential to attain equitable outcomes across all populations, necessitating interdisciplinary collaboration and community participation to shape effective and equitable strategies aimed at mitigating environmental burdens from the transportation sector.

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Acknowledgments

Research reported in this publication was supported by an U.S. National Science Foundation CAREER: CAS-Climate-2239834 award to D.E.H. and an Environmental Defense Fund (EDF) grant to D.E.H.. We acknowledge the valuable contributions of NET-Z coalition members, including representatives from the Respiratory Health Association, Warehouse Workers for Justice, and the Little Village Environmental Justice Organization, as well as additional support from EDF staff members Ellen Robo, Alex Franco, and Tammy Thompson, all of whom provided essential input to this research beyond the contributions of the listed co-authors. EDF acknowledges support for this research from the Robertson Foundation and Signe Ostby and Scott Cook, Valhalla Foundation.

Competing interests

The authors declare that they have no competing interests.

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