Growing evidence links air pollution to colorectal cancer (CRC) incidence. We examined this association within the large Multiethnic Cohort Study (MEC). Geocoded residential addresses for 98,675 California MEC participants were appended to ambient air pollution measures of PM2.5 (particulate matter [PM] with an aerodynamic diameter <2.5 μm), PM10 (PM < 10 μm), nitrogen dioxide (NO2), nitrogen oxides (NOx), carbon monoxide (CO), and ozone (O3), generated from enrollment (1993-1996) to December 31, 2018. Multivariable-adjusted Cox proportional hazards models evaluated associations of time-varying air pollutants with CRC incidence (n = 3217 cases). We assessed heterogeneity in associations by demographics, tumor stage, and anatomical subsite. CRC incidence increased with PM2.5 exposure (per 10 μg/m3; hazard ratio [HR] = 1.13, 95% confidence interval [CI] = 0.96-1.33), mainly among female (HR = 1.29, 95% CI = 1.03-1.62) but not among male participants (Pheterogeneity = 0.08). CRC incidence also increased with NOx exposure among female (HR = 1.22, 95% CI = 1.01-1.48) but not male participants (Pheterogeneity = 0.07). Increased incidence associated with PM2.5 (HR = 1.36, 95% CI = 1.05-1.76), NO2 (per 20 parts per billion [ppb]; HR = 1.32, 95% CI = 1.05-1.68) and CO (per 1000 ppb; HR = 1.36, 95% CI = 1.01-1.84) exposures were observed for left colon and rectal cancers combined, but not right colon cancers (Pheterogeneity by site = 0.08, 0.06 and 0.13, respectively). Associations of PM2.5 and NO2 with rectal cancer incidence differed by population group (Pheterogeneity = 0.04 and 0.03, respectively), and was mostly driven by positive associations among Latino participants. In summary, increasing PM2.5, NO2, NOx, and CO exposures were suggestively associated with increased CRC incidence, particularly among female and Latino participants and for left colon and rectal cancers.

Early life exposure to air pollution is associated with adverse health outcomes in children however few studies have investigated children's air pollution exposures in urban settings in sub-Saharan Africa (SSA). We measured fine particulate matter (PM2.5) and carbon monoxide (CO) in homes of infants in Nairobi, Kenya and conducted exploratory analysis of exposure factors. Questionnaires captured household characteristics and self-reported air pollution exposures. Indoor and outdoor 24-hour (24 h) concentrations were measured inside and 1 m outside the house. PM2.5 was sampled using standard gravimetric procedures; CO was measured with direct-reading electrochemical sensors. Forty-eight homes were sampled at median infant age 11.5 months (range 0.8-26.2 months). During sampling, 66.7%, 18.8%, 10.4% and 10.4% of mothers, respectively, reported using liquefied petroleum gas (LPG), ethanol, electricity, and kerosene for cooking. Median indoor and outdoor 24 h PM2.5 concentrations (n = 39) were 39.9 ug/m3 (range, 12.8-519.6 ug/m3) and 23.3 ug/m3 (range, 2.6-68.2 ug/m3), respectively. Most PM2.5 concentrations (97% of indoor; 79% of outdoor) exceeded the World Health Organization (WHO) 24 h air quality guideline (AQG) of 15 ug/m3. Median indoor (n = 47) and outdoor (n = 41) 24 h mean CO concentrations were 0.7 ppm (range, 0-33.9 ppm) and 0.0 ppm (range, 0-1.0 ppm), respectively. Mean indoor CO concentrations exceeded the WHO 24 h AQG of 6.2 ppm in 9% of homes. Despite frequent use of cooking fuels considered to be clean such as LPG and ethanol, PM2.5 and CO levels in infant homes in urban SSA often exceeded the WHO AQGs. Expanded studies of children's air pollution exposures in urban SSA are needed to build awareness and inform policy.

Dimension reduction is often the first step in statistical modeling or prediction of multivariate spatial data. However, most existing dimension reduction techniques do not account for the spatial correlation between observations and do not take the downstream modeling task into consideration when finding the lower-dimensional representation. We formalize the closeness of approximation to the original data and the utility of lower-dimensional scores for downstream modeling as two complementary, sometimes conflicting, metrics for dimension reduction. We illustrate how existing methodologies fall into this framework and propose a flexible dimension reduction algorithm that achieves the optimal trade-off. We derive a computationally simple form for our algorithm and illustrate its performance through simulation studies, as well as two applications in air pollution modeling and spatial transcriptomics.

Introduction Air pollution is linked with poor neurodevelopment in high-income countries. Comparable data are scant for low-income countries, where exposures are higher. Longitudinal pregnancy cohort studies are optimal for individual exposure assessment during critical windows of brain development and examination of neurodevelopment. This study aims to determine the association between prenatal ambient air pollutant exposure and neurodevelopment in children aged 12, 24 and 36 months through a collaborative, capacity-enriching research partnership.Methods and analysis This observational cohort study is based in Nairobi, Kenya. Eligibility criteria are singleton pregnancy, no severe pregnancy complications and maternal age 18 to 40 years. At entry, mothers (n=400) are administered surveys to characterise air pollution exposures reflecting household features and occupational activities and provide blood (for lead analysis) and urine specimens (for polycyclic aromatic hydrocarbon (PAH) metabolites). Mothers attend up to two additional antenatal study visits, with urine collection, and infants are followed through age 36 months for annual neurodevelopment and caregiving behaviour assessment, and child urine and blood collection. Primary outcomes are child motor skills, language and cognition at 12, 24 and 36 months, and executive function at 36 months. The primary exposure is urinary PAH metabolite concentrations. Additional exposure assessment in a subset of the cohort includes residential indoor and outdoor air monitoring for fine particulate matter (PM2.5), carbon monoxide (CO), ultrafine particles (UFP) and black carbon (BC).Ethics and dissemination This study was approved by the Kenyatta National Hospital - University of Nairobi Ethics and Research Committee, and the University of Washington Human Subjects Division. Results are shared at annual workshops.

Supplementary Table 3 shows an analysis of the association between Airport-Related UFP and Lung Cancer Risk by Smoking Status and Histology among California MEC Participants between 1993-2013.

Traffic-related activities are widely acknowledged as a primary source of urban ambient ultrafine particles (UFPs). However, a notable gap exists in quantifying the contributions of road and air traffic to size-resolved and total UFPs in urban areas. This study aims to delineate and quantify the traffic's contributions to size-resolved and total UFPs in two urban communities. To achieve this, stationary sampling was conducted at near-road and near-airport communities in Seattle, Washington State, to monitor UFP number concentrations during 2018-2020. Comprehensive correlation analyses among all variables were performed. Furthermore, a fully adjusted generalized additive model, incorporating meteorological factors, was developed to quantify the contributions of road and air traffic to size-resolved and total UFPs. The study found that vehicle emissions accounted for 29% of total UFPs at the near-road site and 13% at the near-airport site. Aircraft emissions contributed 14% of total UFPs at the near-airport site. Notably, aircraft predominantly emitted UFP sizes below 20 nm, while vehicles mainly emitted UFP sizes below 50 nm. These findings reveal the variability in road and air traffic contributions to UFPs in distinct areas. Our study emphasizes the pivotal role of traffic layout in shaping urban UFP exposure.

BACKGROUND:While epidemiologic evidence links higher levels of exposure to fine particulate matter (PM2.5) to decreased cognitive function, fewer studies have investigated links with traffic-related air pollution (TRAP), and none have examined ultrafine particles (UFP, ≤100 nm) and late-life dementia incidence. OBJECTIVE:To evaluate associations between TRAP exposures (UFP, black carbon [BC], and nitrogen dioxide [NO2]) and late-life dementia incidence. METHODS:We ascertained dementia incidence in the Seattle-based Adult Changes in Thought (ACT) prospective cohort study (beginning in 1994) and assessed ten-year average TRAP exposures for each participant based on prediction models derived from an extensive mobile monitoring campaign. We applied Cox proportional hazards models to investigate TRAP exposure and dementia incidence using age as the time axis and further adjusting for sex, self-reported race, calendar year, education, socioeconomic status, PM2.5, and APOE genotype. We ran sensitivity analyses where we did not adjust for PM2.5 and other sensitivity and secondary analyses where we adjusted for multiple pollutants, applied alternative exposure models (including total and size-specific UFP), modified the adjustment covariates, used calendar year as the time axis, assessed different exposure periods, dementia subtypes, and others. RESULTS:We identified 1,041 incident all-cause dementia cases in 4,283 participants over 37,102 person-years of follow-up. We did not find evidence of a greater hazard of late-life dementia incidence with elevated levels of long-term TRAP exposures. The estimated hazard ratio of all-cause dementia was 0.98 (95 % CI: 0.92-1.05) for every 2000 pt/cm3 increment in UFP, 0.95 (0.89-1.01) for every 100 ng/m3 increment in BC, and 0.96 (0.91-1.02) for every 2 ppb increment in NO2. These findings were consistent across sensitivity and secondary analyses. DISCUSSION:We did not find evidence of a greater hazard of late-life dementia risk with elevated long-term TRAP exposures in this population-based prospective cohort study.

Supplementary Table 1 shows an overview of the study characteristics of California Multiethnic Cohort (MEC) Participants at Baseline by Race and Ethnicity between 1993-1996.

BACKGROUND:In contrast to fine particles, less is known of the inflammatory and coagulation impacts of coarse particulate matter (PM10-2.5, particulate matter with aerodynamic diameter ≤10μm and>2.5μm). Toxicological research suggests that these pathways might be important processes by which PM10-2.5 impacts health, but there are relatively few epidemiological studies due to a lack of a national PM10-2.5 monitoring network. OBJECTIVES:We used new spatiotemporal exposure models to examine associations of both 1-y and 1-month average PM10-2.5 concentrations with markers of inflammation and coagulation. METHODS:We leveraged data from 7,071 Multi-Ethnic Study of Atherosclerosis and ancillary study participants 45-84 y of age who had repeated plasma measures of inflammatory and coagulation biomarkers. We estimated PM10-2.5 at participant addresses 1 y and 1 month before each of up to four exams (2000-2012) using spatiotemporal models that incorporated satellite, regulatory monitoring, and local geographic data and accounted for spatial correlation. We used random effects models to estimate associations with interleukin-6 (IL-6), C-reactive protein (CRP), fibrinogen, and D-dimer, controlling for potential confounders. RESULTS:Increases in PM10-2.5 were not associated with greater levels of inflammation or coagulation. A 10-μg/m3 increase in annual average PM10-2.5 was associated with a 2.5% decrease in CRP [95% confidence interval (CI): -5.5, 0.6]. We saw no association between annual average PM10-2.5 and the other markers (IL-6: -0.7%, 95% CI: -2.6, 1.2; fibrinogen: -0.3%, 95% CI: -0.9, 0.3; D-dimer: -0.2%, 95% CI: -2.6, 2.4). Associations consistently showed that a 10-μg/m3 increase in 1-month average PM10-2.5 was associated with reduced inflammation and coagulation, though none were distinguishable from no association (IL-6: -1.2%, 95% CI: -3.0 , 0.5; CRP: -2.5%, 95% CI: -5.3, 0.4; fibrinogen: -0.4%, 95% CI: -1.0, 0.1; D-dimer: -2.0%, 95% CI: -4.3, 0.3). DISCUSSION:We found no evidence that PM10-2.5 is associated with higher inflammation or coagulation levels. More research is needed to determine whether the inflammation and coagulation pathways are as important in explaining observed PM10-2.5 health impacts in humans as they have been shown to be in toxicology studies or whether PM10-2.5 might impact human health through alternative biological mechanisms. https://doi.org/10.1289/EHP12972.

PURPOSE Recent studies suggested fine particulate matter (PM 2.5 ) exposure increases the risk of breast cancer, but evidence among racially and ethnically diverse populations remains sparse. MATERIALS AND METHODS Among 58,358 California female participants of the Multiethnic Cohort (MEC) Study followed for an average of 19.3 years (1993-2018), we used Cox proportional hazards regression to examine associations of time-varying PM with invasive breast cancer risk (n = 3,524 cases; 70% African American and Latino females), adjusting for sociodemographics and lifestyle factors. Subgroup analyses were conducted for race and ethnicity, hormone receptor status, and breast cancer risk factors. RESULTS Satellite-based PM 2.5 was associated with a statistically significant increased incidence of breast cancer (hazard ratio [HR] per 10 μg/m 3 , 1.28 [95% CI, 1.08 to 1.51]). We found no evidence of heterogeneity in associations by race and ethnicity and hormone receptor status. Family history of breast cancer showed evidence of heterogeneity in PM 2.5 -associations ( P heterogeneity = .046). In a meta-analysis of the MEC and 10 other prospective cohorts, breast cancer incidence increased in association with exposure to PM 2.5 (HR per 10 μg/m 3 increase, 1.05 [95% CI, 1.00 to 1.10]; P = .064). CONCLUSION Findings from this large multiethnic cohort with long-term air pollutant exposure and published prospective cohort studies support PM 2.5 as a risk factor for breast cancer. As about half of breast cancer cannot be explained by established breast cancer risk factors and incidence is continuing to increase, particularly in low- and middle-income countries, our results highlight that breast cancer prevention should include not only individual-level behavior-centered approaches but also population-wide policies and regulations to curb PM 2.5 exposure.

Supplementary Table 5 shows an analysis of the association between Airport-Related UFP and Lung Cancer Risk Overall by Histology and Time Period among California MEC participants between 1993-2013.

Supplementary Table 2 shows an analysis of the association between Airport-Related UFP and Squamous Cell Carcinoma Risk by Smoking Status among California MEC participants between 1993-2013.

Abstract Background: Growing evidence suggests that air pollution may be a risk factor for colorectal cancer (CRC). We examined the association between ambient particulate matter (PM) exposure and CRC risk within the Multiethnic Cohort Study (MEC), representing the first study to include a large sample of racial and ethnic minoritized populations. Methods: The MEC is a prospective study that recruited, from 1993 through 1996, men and women ages 45-75 years largely from five racial and ethnic groups (African American, Japanese American, Latino, Native Hawaiian, and Non-Hispanic White) living in Hawai‘i and California. This study included 98,675 California MEC participants, residing predominately in Los Angeles County. Satellite-based PM2.5 (PM with an aerodynamic diameter <2.5μm) exposures were estimated from a published spatiotemporal model. Kriging interpolation was used to estimate PM10 (PM <10μm) exposures using routine air monitoring data from the US Environmental Protection Agency. Time-varying PM exposures were assessed from time of recruitment through 12/31/2018. Incident invasive CRC cases were identified via linkage with the California Cancer Registry (n=3,217). Cox proportional hazards models were used to examine the association between PM and CRC risk using age as the time metric, with strata defined by age at cohort entry and race and ethnicity, and adjusting for demographic and lifestyle factors. Heterogeneity of the PM-CRC association was assessed by sex, race and ethnicity, and CRC subsite (right colon, left colon, rectum). Results: Risk of CRC increased with PM2.5 (per 10μg/m3 hazard ratio [HR] 1.13, 95% confidence interval [CI] 0.96-1.33) with a larger HR observed among females (HR 1.29, 95% CI 1.03-1.62) than males (HR 0.96, 95% CI 0.76-1.22) (Pheterogeneity=0.24). CRC risk was positively associated with PM2.5 across race and ethnicity (except for African American participants) with the largest HR observed among Latino participants (HR 1.47, 95% CI 1.03-2.08) (Pheterogeneity=0.20). There was no statistically significant heterogeneity of PM2.5 effect by tumor subsite (Pheterogeneity=0.07); although larger HRs were seen for left colon (HR 1.52, 95% CI 1.08- 2.14) and rectal cancers (HR 1.54, 95% CI 1.05-2.25) than right colon cancers (HR 1.09, 95% CI 0.88-1.35). PM10 was not associated with CRC risk (per 10 μg/m3; HR 1.02, 95% CI 0.93-1.22) with no evidence of heterogeneity in associations by sex or race and ethnicity (respective Pheterogeneity 0.75, 0.44). Although HRs for PM10 appeared to differ by CRC subsite (Pheterogeneity=0.03), the 95% CI of these HRs included the null (right HR 0.95, 95% CI 0.84-1.06; left HR 1.13, 95% CI 0.95-1.35; rectal HR 1.18, 95% CI 0.97-1.43). Conclusions: Preliminary findings suggest that PM2.5 exposure is associated with CRC risk with larger associations in females and, possibly, for left colon and rectal cancer. Additional studies are needed to confirm these findings and evaluate the potential biological pathways underlying these associations. Citation Format: Ugonna Ihenacho, Chiuchen Tseng, Jun Wu, Scott Fruin, Timothy V. Larson, Salma Shariff-Marco, Loïc Le Marchand, Daniel O. Stram, Lynne R. Wilkens, Christopher A. Haiman, Beate Ritz, Iona Cheng, Anna H. Wu. Association between ambient particulate matter and colorectal cancer incidence: The Multiethnic Cohort Study [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A048.

AbstractBackground: Ultrafine particles (UFP) are unregulated air pollutants abundant in aviation exhaust. Emerging evidence suggests that UFPs may impact lung health due to their high surface area-to-mass ratio and deep penetration into airways. This study aimed to assess long-term exposure to airport-related UFPs and lung cancer incidence in a multiethnic population in Los Angeles County. Methods: Within the California Multiethnic Cohort, we examined the association between long-term exposure to airport-related UFPs and lung cancer incidence. Multivariable Cox proportional hazards regression models were used to estimate the effect of UFP exposure on lung cancer incidence. Subgroup analyses by demographics, histology and smoking status were conducted. Results: Airport-related UFP exposure was not associated with lung cancer risk [per one IGR HR, 1.01; 95% confidence interval (CI), 0.97–1.05] overall and across race/ethnicity. A suggestive positive association was observed between a one IQR increase in UFP exposure and lung squamous cell carcinoma (SCC) risk (HR, 1.08; 95% CI, 1.00–1.17) with a Phet for histology = 0.05. Positive associations were observed in 5-year lag analysis for SCC (HR, 1.12; 95% CI, CI, 1.02–1.22) and large cell carcinoma risk (HR, 1.23; 95% CI, 1.01–1.49) with a Phet for histology = 0.01. Conclusions: This large prospective cohort analysis suggests a potential association between airport-related UFP exposure and specific lung histologies. The findings align with research indicating that UFPs found in aviation exhaust may induce inflammatory and oxidative injury leading to SCC. Impact: These results highlight the potential role of airport-related UFP exposure in the development of lung SCC.

BACKGROUND:Exposure to air pollution is associated with worldwide morbidity and mortality. Diesel exhaust (DE) emissions are important contributors which induce vascular inflammation and metabolic disturbances by unknown mechanisms. We aimed to determine molecular pathways activated by DE in the liver that could be responsible for its cardiometabolic toxicity. METHODS:Apolipoprotein E knockout (ApoE KO) mice were exposed to DE or filtered air (FA) for two weeks, or DE for two weeks followed by FA for 1 week. Expression microarrays and global metabolomics assessment were performed in the liver. An integrated transcriptomic and metabolomic analytical strategy was employed to dissect critical pathways and identify candidate genes that could dissect DE-induced pathogenesis. HepG2 cells were treated with an organic extract of DE particles (DEP) vs. vehicle control to test candidate genes. RESULTS:DE exposure for 2 weeks dysregulated 658 liver genes overrepresented in whole cell metabolic pathways, especially including lipid and carbohydrate metabolism, and the respiratory electron transport pathway. DE exposure significantly dysregulated 118 metabolites, resulting in increased levels of triglycerides and fatty acids due to mitochondrial dysfunction as well as increased levels of glucose and oligosaccharides. Consistently, DEP treatment of HepG2 cells led to increased gluconeogenesis and glycogenolysis indicating the ability of the in-vitro approach to model effects induced by DE in vivo. As an example, while gene network analysis of DE livers identified phosphoenolpyruvate carboxykinase 1 (Pck1) as a key driver gene of DE response, DEP treatment of HepG2 cells resulted in increased mRNA expression of Pck1 and glucose production, the latter replicated in mouse primary hepatocytes. Importantly, Pck1 inhibitor mercaptopicolinic acid suppressed DE-induced glucose production in HepG2 cells indicating that DE-induced elevation of hepatic glucose was due in part to upregulation of Pck1 and increased gluconeogenesis. CONCLUSIONS:Short-term exposure to DE induced widespread alterations in metabolic pathways in the liver of ApoE KO mice, especially involving carbohydrate and lipid metabolism, together with mitochondrial dysfunction. Pck1 was identified as a key driver gene regulating increased glucose production by activation of the gluconeogenesis pathway.

Supplementary Table 4 shows an analysis of co-pollutants (NO2, PM10, PM2.5) and UFP Associations by Lung Cancer Histologies among California MEC Participants from 1993-2013.

Short-term mobile monitoring campaigns are increasingly used to assess long-term air pollution exposure in epidemiology. Little is known about how monitoring network design features, including the number of stops and sampling temporality, impacts exposure assessment models. We address this gap by leveraging an extensive mobile monitoring campaign conducted in the greater Seattle area over the course of a year during all days of the week and most hours. The campaign measured total particle number concentration (PNC; sheds light on ultrafine particulate (UFP) number concentration), black carbon (BC), nitrogen dioxide (NO2), fine particulate matter (PM2.5), and carbon dioxide (CO2). In Monte Carlo sampling of 7327 total stops (278 sites × 26 visits each), we restricted the number of sites and visits used to estimate annual averages. Predictions from the all-data campaign performed well, with cross-validated R2s of 0.51-0.77. We found similar model performances (85% of the all-data campaign R2) with ∼1000 to 3000 randomly selected stops for NO2, PNC, and BC, and ∼4000 to 5000 stops for PM2.5 and CO2. Campaigns with additional temporal restrictions (e.g., business hours, rush hours, weekdays, or fewer seasons) had reduced model performances and different spatial surfaces. Mobile monitoring campaigns wanting to assess long-term exposure should carefully consider their monitoring designs.

Background: Ambient air pollution, including traffic-related air pollution (TRAP), increases cardiovascular disease risk, possibly through vascular alterations. Limited information exists about in-vehicle TRAP exposure and vascular changes.Objective: To determine via particle filtration the effect of on-roadway TRAP exposure on blood pressure and retinal vasculature.Design: Randomized crossover trial. (ClinicalTrials.gov: NCT05454930)Setting: In-vehicle scripted commutes driven through traffic in Seattle, Washington, during 2014 to 2016.Participants: Normotensive persons aged 22 to 45 years (n = 16).Intervention: On 2 days, on-road air was entrained into the vehicle. On another day, the vehicle was equipped with high-efficiency particulate air (HEPA) filtration. Participants were blinded to the exposure and were randomly assigned to the sequence.Measurements: Fourteen 3-minute periods of blood pressure were recorded before, during, and up to 24 hours after a drive. Image-based central retinal arteriolar equivalents (CRAEs) were measured before and after. Brachial artery diameter and gene expression were also measured and will be reported separately.Results: Mean age was 29.7 years, predrive systolic blood pressure was 122.7 mm Hg, predrive diastolic blood pressure was 70.8 mm Hg, and drive duration was 122.3 minutes (IQR, 4 minutes). Filtration reduced particle count by 86%. Among persons with complete data (n = 13), at 1 hour, mean diastolic blood pressure, adjusted for predrive levels, order, and carryover, was 4.7 mm Hg higher (95% CI, 0.9 to 8.4 mm Hg) for unfiltered drives compared with filtered drives, and mean adjusted systolic blood pressure was 4.5 mm Hg higher (CI, -1.2 to 10.2 mm Hg). At 24 hours, adjusted mean diastolic blood pressure (unfiltered) was 3.8 mm Hg higher (CI, 0.02 to 7.5 mm Hg) and adjusted mean systolic blood pressure was 1.1 mm Hg higher (CI, -4.6 to 6.8 mm Hg). Adjusted mean CRAE (unfiltered) was 2.7 mu m wider (CI, -1.5 to 6.8 mu m).Limitations: Imprecise estimates due to small sample size; seasonal imbalance by exposure order.Conclusion: Filtration of TRAP may mitigate its adverse effects on blood pressure rapidly and at 24 hours. Validation is required in larger samples and different settings.Primary Funding Source: U.S. Environmental Protection Agency and National Institutes of Health.

Mobile monitoring is increasingly used to assess exposure to traffic-related air pollutants (TRAPs), including ultrafine particles (UFPs). Due to the rapid spatial decrease in the concentration of UFPs and other TRAPs with distance from roadways, mobile measurements may be non-representative of residential exposures, which are commonly used for epidemiologic studies. Our goal was to develop, apply, and test one possible approach for using mobile measurements in exposure assessment for epidemiology. We used an absolute principal component score model to adjust the contribution of on-road sources in mobile measurements to provide exposure predictions representative of cohort locations. We then compared UFP predictions at residential locations from mobile on-road plume-adjusted versus stationary measurements to understand the contribution of mobile measurements and characterize their differences. We found that predictions from mobile measurements are more representative of cohort locations after down-weighting the contribution of localized on-road plumes. Further, predictions at cohort locations derived from mobile measurements incorporate more spatial variation compared to those from short-term stationary data. Sensitivity analyses suggest that this additional spatial information captures features in the exposure surface not identified from the stationary data alone. We recommend the correction of mobile measurements to create exposure predictions representative of residential exposure for epidemiology.