Quantifying the contributions of road and air traffic to ambient ultrafine particles in two urban communities.

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.

Modified FOLFOX6 plus bevacizumab with and without nivolumab for first-line treatment of metastatic colorectal cancer: phase 2 results from the CheckMate 9X8 randomized clinical trial.

BACKGROUND: Standard first-line therapies for metastatic colorectal cancer (mCRC) include fluoropyrimidine-containing regimens with oxaliplatin and/or irinotecan and a biologic agent. Immunotherapy may enhance antitumor activity in combination with standard therapies in patients with mCRC. Here, we present phase 2 results of nivolumab plus standard-of-care therapy (SOC; 5-fluorouracil/leucovorin/oxaliplatin/bevacizumab) versus SOC in the first-line treatment of patients with mCRC (CheckMate 9X8). METHODS: CheckMate 9X8 was a multicenter, open-label, randomized, phase 2/3 trial. Eligible patients were at least 18 years of age with unresectable mCRC and no prior chemotherapy for metastatic disease. Patients were randomized 2:1 to receive nivolumab 240 mg plus SOC or SOC alone every 2 weeks. The primary endpoint was progression-free survival (PFS) by blinded independent central review (BICR) per Response Evaluation Criteria in Solid Tumors V.1.1. Secondary endpoints included PFS by investigator assessment; objective response rate (ORR), disease control rate, duration of response, and time to response, all by BICR and investigator assessments; overall survival; and safety. Preplanned exploratory biomarker analyses were also performed. RESULTS: From February 2018 through April 2019, 310 patients were enrolled, of which 195 patients were randomized to nivolumab plus SOC (n=127) or SOC (n=68). At 21.5-month minimum follow-up, PFS with nivolumab plus SOC versus SOC did not meet the prespecified threshold for statistical significance; median PFS by BICR was 11.9 months in both arms (HR, 0.81 (95% CI, 0.53 to 1.23); p=0.30). Higher PFS rates after 12 months (18 months: 28% vs 9%), higher ORR (60% vs 46%), and durable responses (median 12.9 vs 9.3 months) were observed with nivolumab plus SOC versus SOC. Grade 3-4 treatment-related adverse events were reported in 75% versus 48% of patients; no new safety signals were identified. CONCLUSIONS: The CheckMate 9X8 trial investigating first-line nivolumab plus SOC versus SOC in patients with mCRC did not meet its primary endpoint of PFS by BICR. Nivolumab plus SOC showed numerically higher PFS rates after 12 months, a higher response rate, and more durable responses compared with SOC alone, with acceptable safety. Further investigation to identify subgroups of patients with mCRC that may benefit from nivolumab plus SOC versus SOC in the first-line setting is warranted. TRIAL REGISTRATION NUMBER: NCT03414983.

Association between Airport Ultrafine Particles and Lung Cancer Risk: The Multiethnic Cohort Study.

BACKGROUND: 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.

Coarse Particulate Matter and Markers of Inflammation and Coagulation in the Multi-Ethnic Study of Atherosclerosis (MESA) Population: A Repeat Measures Analysis.

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.

Traffic-related air pollution and dementia incidence in the Adult Changes in Thought Study.

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.

Impact of pancreas transplantation alone on kidney function: A multicenter clinical cohort study.

Pancreas transplantation alone (PTA) is a ß cell replacement option for selected patients with type 1 diabetes mellitus; concerns have been raised regarding deterioration in kidney function (KF) after PTA. This retrospective multicenter study assessed actual impact of transplantation and immunosuppression on KF in PTA recipients at three Transplant Centers. The primary composite endpoint 10 years after PTA was >50% eGFR decline, eGFR < 30 mL/min/1.73 m2 , and/or receiving a kidney transplant (KT). Overall, 822 PTA recipients met eligibility. Median baseline and 10-year eGFR (mL/min/1.73 m2 ) were 76.3 (58.1-100.8) and 51.3 (35.3-65.9), respectively. Primary composite endpoint occurred in 98 patients (53.5%) with 45 experiencing a >50% decrease in eGFR by 10 years post-transplant, 38 eGFR < 30 mL/min/1.73 m2 and 49 requiring KT. KF declined most significantly within 6 months post-PTA, more often in females and patients with better preserved GFR up to 5 years with 11.6% kidney failure at 10 years. Patient survival and death-censored graft survival were both 68% at 10 years with overall graft thrombosis rate 8%. KF declined initially after PTA but stabilized with further slow progression. In conclusion, prospective intervention studies are needed to test renal sparing interventions while gathering more granular data.

Brentuximab vedotin with dacarbazine or nivolumab as frontline cHL therapy for older patients ineligible for chemotherapy.

ABSTRACT: Older patients with advanced-stage classical Hodgkin lymphoma (cHL) have inferior outcomes compared with younger patients, potentially due to comorbidities and frailty. This noncomparative phase 2 study enrolled patients aged ≥60 years with cHL unfit for conventional chemotherapy to receive frontline brentuximab vedotin (BV; 1.8 mg/kg) with dacarbazine (DTIC; 375 mg/m2) (part B) or nivolumab (part D; 3 mg/kg). In parts B and D, 50% and 38% of patients, respectively, had ≥3 general comorbidities or ≥1 significant comorbidity. Of the 22 patients treated with BV-DTIC, 95% achieved objective response, and 64% achieved complete response (CR). With a median follow-up of 63.6 months, median duration of response (mDOR) was 46.0 months. Median progression-free survival (mPFS) was 47.2 months; median overall survival (mOS) was not reached. Of 21 patients treated with BV-nivolumab, 86% achieved objective response, and 67% achieved CR. With 51.6 months of median follow-up, mDOR, mPFS, and mOS were not reached. Ten patients (45%) with BV-DTIC and 16 patients (76%) with BV-nivolumab experienced grade ≥3 treatment-emergent adverse events; sensory peripheral neuropathy (PN; 27%) and neutropenia (9%) were most common with BV-DTIC, and increased lipase (24%), motor PN (19%), and sensory PN (19%) were most common with BV-nivolumab. Despite high median age, inclusion of patients aged ≤88 years, and frailty, these results demonstrate safety and promising durable efficacy of BV-DTIC and BV-nivolumab combinations as frontline treatment, suggesting potential alternatives for older patients with cHL unfit for initial conventional chemotherapy. This trial was registered at www.clinicaltrials.gov as #NCT01716806.

Blood Pressure Effect of Traffic-Related Air Pollution : A Crossover Trial of In-Vehicle Filtration.

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 µm wider (CI, -1.5 to 6.8 µm). 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.

Particulate matter, traffic-related air pollutants, and circulating C-reactive protein levels: The Multiethnic Cohort Study.

Inhaled particles and gases can harm health by promoting chronic inflammation in the body. Few studies have investigated the relationship between outdoor air pollution and inflammation by race and ethnicity, socioeconomic status, and lifestyle risk factors. We examined associations of particulate matter (PM) and other markers of traffic-related air pollution with circulating levels of C-reactive protein (CRP), a biomarker of systemic inflammation. CRP was measured from blood samples obtained in 1994-2016 from 7,860 California residents participating in the Multiethnic Cohort (MEC) Study. Exposure to PM (aerodynamic diameter ≤2.5 µm [PM2.5], ≤10 µm [PM10], and between 2.5 and 10 µm [PM10-2.5]), nitrogen oxides (NOx, including nitrogen dioxide [NO2]), carbon monoxide (CO), ground-level ozone (O3), and benzene averaged over one or twelve months before blood draw were estimated based on participants' addresses. Percent change in geometric mean CRP levels and 95% confidence intervals (CI) per standard concentration increase of each pollutant were estimated using multivariable generalized linear regression. Among 4,305 females (55%) and 3,555 males (45%) (mean age 68.1 [SD 7.5] years at blood draw), CRP levels increased with 12-month exposure to PM10 (11.0%, 95% CI: 4.2%, 18.2% per 10 µg/m3), PM10-2.5 (12.4%, 95% CI: 1.4%, 24.5% per 10 µg/m3), NOx (10.4%, 95% CI: 2.2%, 19.2% per 50 ppb), and benzene (2.9%, 95% CI: 1.1%, 4.6% per 1 ppb). In subgroup analyses, these associations were observed in Latino participants, those who lived in low socioeconomic neighborhoods, overweight or obese participants, and never or former smokers. No consistent patterns were found for 1-month pollutant exposures. This investigation identified associations of primarily traffic-related air pollutants, including PM, NOx, and benzene, with CRP in a multiethnic population. The diversity of the MEC across demographic, socioeconomic, and lifestyle factors allowed us to explore the generalizability of the effects of air pollution on inflammation across subgroups.

Characterizing Ultrafine Particle Mobile Monitoring Data for Epidemiology.

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.

Assessing the effectiveness of portable HEPA air cleaners for reducing particulate matter exposure in King County, Washington homeless shelters: Implications for community congregate settings.

Over four thousand portable air cleaners (PACs) with high-efficiency particulate air (HEPA) filters were distributed by Public Health - Seattle & King County to homeless shelters during the COVID-19 pandemic. This study aimed to evaluate the real-world effectiveness of these HEPA PACs in reducing indoor particles and understand the factors that affect their use in homeless shelters. Four rooms across three homeless shelters with varying geographic locations and operating conditions were enrolled in this study. At each shelter, multiple PACs were deployed based on the room volume and PAC's clean air delivery rate rating. The energy consumption of these PACs was measured using energy data loggers at 1-min intervals to allow tracking of their use and fan speed for three two-week sampling rounds, separated by single-week gaps, between February and April 2022. Total optical particle number concentration (OPNC) was measured at 2-min intervals at multiple indoor locations and an outdoor ambient location. The empirical indoor and outdoor total OPNC were compared for each site. Additionally, linear mixed-effects regression models (LMERs) were used to assess the relationship between PAC use time and indoor/outdoor total OPNC ratios (I/OOPNC). Based on the LMER models, a 10 % increase in the hourly, daily, and total time PACs were used significantly reduced I/OOPNC by 0.034 [95 % CI: 0.028, 0.040; p < 0.001], 0.051 [95 % CI: 0.020, 0.078; p < 0.001], and 0.252 [95 % CI: 0.150, 0.328; p < 0.001], respectively, indicating that keeping PACs on resulted in significantly lower I/OOPNC. The survey suggested that keeping PACs on and running was the main challenge when operating them in shelters. These findings suggested that HEPA PACs were an effective short-term strategy to reduce indoor particle levels in community congregate living settings during non-wildfire seasons and the need for formulating practical guidance for using them in such an environment.

Race-free estimated glomerular filtration rate equation in kidney transplant recipients: development and validation study.

OBJECTIVE: To compare the performance of a newly developed race-free kidney recipient specific glomerular filtration rate (GFR) equation with the three current main equations for measuring GFR in kidney transplant recipients. DESIGN: Development and validation study SETTING: 17 cohorts in Europe, the United States, and Australia (14 transplant centres, three clinical trials). PARTICIPANTS: 15 489 adults (3622 in development cohort (Necker, Saint Louis, and Toulouse hospitals, France), 11 867 in multiple external validation cohorts) who received kidney transplants between 1 January 2000 and 1 January 2021. MAIN OUTCOME MEASURE: The main outcome measure was GFR, measured according to local practice. Performance of the GFR equations was assessed using P30 (proportion of estimated GFR (eGFR) within 30% of measured GFR (mGFR)) and correct classification (agreement between eGFR and mGFR according to GFR stages). The race-free equation, based on creatinine level, age, and sex, was developed using additive and multiplicative linear regressions, and its performance was compared with the three current main GFR equations: Modification of Diet in Renal Disease (MDRD) equation, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation, and race-free CKD-EPI 2021 equation. RESULTS: The study included 15 489 participants, with 50 464 mGFR and eGFR values. The mean GFR was 53.18 mL/min/1.73m2 (SD 17.23) in the development cohort and 55.90 mL/min/1.73m2 (19.69) in the external validation cohorts. Among the current GFR equations, the race-free CKD-EPI 2021 equation showed the lowest performance compared with the MDRD and CKD-EPI 2009 equations. When race was included in the kidney recipient specific GFR equation, performance did not increase. The race-free kidney recipient specific GFR equation showed significantly improved performance compared with the race-free CKD-EPI 2021 equation and performed well in the external validation cohorts (P30 ranging from 73.0% to 91.3%). The race-free kidney recipient specific GFR equation performed well in several subpopulations of kidney transplant recipients stratified by race (P30 73.0-91.3%), sex (72.7-91.4%), age (70.3-92.0%), body mass index (64.5-100%), donor type (58.5-92.9%), donor age (68.3-94.3%), treatment (78.5-85.2%), creatinine level (72.8-91.3%), GFR measurement method (73.0-91.3%), and timing of GFR measurement post-transplant (72.9-95.5%). An online application was developed that estimates GFR based on recipient's creatinine level, age, and sex (https://transplant-prediction-system.shinyapps.io/eGFR_equation_KTX/). CONCLUSION: A new race-free kidney recipient specific GFR equation was developed and validated using multiple, large, international cohorts of kidney transplant recipients. The equation showed high accuracy and outperformed the race-free CKD-EPI 2021 equation that was developed in individuals with native kidneys. TRIAL REGISTRATION: ClinicalTrials.gov NCT05229939.

Exposure assessment for air pollution epidemiology: A scoping review of emerging monitoring platforms and designs.

BACKGROUND: Both exposure monitoring and exposure prediction have played key roles in assessing individual-level long-term exposure to air pollutants and their associations with human health. While there have been notable advances in exposure prediction methods, improvements in monitoring designs are also necessary, particularly given new monitoring paradigms leveraging low-cost sensors and mobile platforms. OBJECTIVES: We aim to provide a conceptual summary of novel monitoring designs for air pollution cohort studies that leverage new paradigms and technologies, to investigate their characteristics in real-world examples, and to offer practical guidance to future studies. METHODS: We propose a conceptual summary that focuses on two overarching types of monitoring designs, mobile and non-mobile, as well as their subtypes. We define mobile designs as monitoring from a moving platform, and non-mobile designs as stationary monitoring from permanent or temporary locations. We only consider non-mobile studies with cost-effective sampling devices. Then we discuss similarities and differences across previous studies with respect to spatial and temporal representation, data comparability between design classes, and the data leveraged for model development. Finally, we provide specific suggestions for future monitoring designs. RESULTS: Most mobile and non-mobile monitoring studies selected monitoring sites based on land use instead of residential locations, and deployed monitors over limited time periods. Some studies applied multiple design and/or sub-design classes to the same area, time period, or instrumentation, to allow comparison. Even fewer studies leveraged monitoring data from different designs to improve exposure assessment by capitalizing on different strengths. In order to maximize the benefit of new monitoring technologies, future studies should adopt monitoring designs that prioritize residence-based site selection with comprehensive temporal coverage and leverage data from different designs for model development in the presence of good data compatibility. DISCUSSION: Our conceptual overview provides practical guidance on novel exposure assessment monitoring for epidemiological applications.

Design and evaluation of short-term monitoring campaigns for long-term air pollution exposure assessment.

BACKGROUND: Short-term mobile monitoring campaigns to estimate long-term air pollution levels are becoming increasingly common. Still, many campaigns have not conducted temporally-balanced sampling, and few have looked at the implications of such study designs for epidemiologic exposure assessment. OBJECTIVE: We carried out a simulation study using fixed-site air quality monitors to better understand how different short-term monitoring designs impact the resulting exposure surfaces. METHODS: We used Monte Carlo resampling to simulate three archetypal short-term monitoring sampling designs using oxides of nitrogen (NOx) monitoring data from 69 regulatory sites in California: a year-around Balanced Design that sampled during all seasons of the year, days of the week, and all or various hours of the day; a temporally reduced Rush Hours Design; and a temporally reduced Business Hours Design. We evaluated the performance of each design's land use regression prediction model. RESULTS: The Balanced Design consistently yielded the most accurate annual averages; while the reduced Rush Hours and Business Hours Designs generally produced more biased results. SIGNIFICANCE: A temporally-balanced sampling design is crucial for short-term campaigns such as mobile monitoring aiming to assess long-term exposure in epidemiologic cohorts. IMPACT STATEMENT: Short-term monitoring campaigns to assess long-term air pollution trends are increasingly common, though they rarely conduct temporally balanced sampling. We show that this approach produces biased annual average exposure estimates that can be improved by collecting temporally-balanced samples.

Impact of Mobile Monitoring Network Design on Air Pollution Exposure Assessment Models.

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.

Evaluation of the effects of elevated CO2 concentrations on the growth of cassava storage roots by destructive harvests and ground penetrating radar scanning approaches.

Cassava (Manihot esculenta Crantz) production will need to be improved to meet future food demands in Sub-Saharan Africa. The selection of high-yielding cassava cultivars requires a better understanding of storage root development. Additionally, since future production will happen under increasing atmospheric CO2 concentrations ([CO2 ]), cultivar selection should include responsiveness to elevated [CO2 ]. Five farmer-preferred African cassava cultivars were grown for three and a half months in a Free Air CO2 Enrichment experiment in central Illinois. Compared to ambient [CO2 ] (~400 ppm), cassava storage roots grown under elevated [CO2 ] (~600 ppm) had a higher biomass with some cultivars having lower storage root water content. The elevated [CO2 ] stimulation in storage root biomass ranged from 33% to 86% across the five cultivars tested documenting the importance of this trait in developing new cultivars. In addition to the destructive harvests to obtain storage root parameters, we explored ground penetrating radar as a nondestructive method to determine storage root growth across the growing season.

Within-City Variation in Ambient Carbon Monoxide Concentrations: Leveraging Low-Cost Monitors in a Spatiotemporal Modeling Framework.

BACKGROUND: Based on human and animal experimental studies, exposure to ambient carbon monoxide (CO) may be associated with cardiovascular disease outcomes, but epidemiological evidence of this link is limited. The number and distribution of ground-level regulatory agency monitors are insufficient to characterize fine-scale variations in CO concentrations. OBJECTIVES: To develop a daily, high-resolution ambient CO exposure prediction model at the city scale. METHODS: We developed a CO prediction model in Baltimore, Maryland, based on a spatiotemporal statistical algorithm with regulatory agency monitoring data and measurements from calibrated low-cost gas monitors. We also evaluated the contribution of three novel parameters to model performance: high-resolution meteorological data, satellite remote sensing data, and copollutant (PM2.5, NO2, and NOx) concentrations. RESULTS: The CO model had spatial cross-validation (CV) R2 and root-mean-square error (RMSE) of 0.70 and 0.02 parts per million (ppm), respectively; the model had temporal CV R2 and RMSE of 0.61 and 0.04 ppm, respectively. The predictions revealed spatially resolved CO hot spots associated with population, traffic, and other nonroad emission sources (e.g., railroads and airport), as well as sharp concentration decreases within short distances from primary roads. DISCUSSION: The three novel parameters did not substantially improve model performance, suggesting that, on its own, our spatiotemporal modeling framework based on geographic features was reliable and robust. As low-cost air monitors become increasingly available, this approach to CO concentration modeling can be generalized to resource-restricted environments to facilitate comprehensive epidemiological research. https://doi.org/10.1289/EHP10889.

Characterization of Annual Average Traffic-Related Air Pollution Concentrations in the Greater Seattle Area from a Year-Long Mobile Monitoring Campaign.

Growing evidence links traffic-related air pollution (TRAP) to adverse health effects. We designed an innovative and extensive mobile monitoring campaign to characterize TRAP exposure levels for the Adult Changes in Thought (ACT) study, a Seattle-based cohort. The campaign measured particle number concentration (PNC) to capture ultrafine particles (UFP), black carbon (BC), nitrogen dioxide (NO2), fine particulate matter (PM2.5), and carbon dioxide (CO2) at 309 roadside sites within a large, 1200 land km2 (463 mi2) area representative of the cohort. We collected about 29 two-minute measurements at each site during all seasons, days of the week, and most times of the day over a 1-year period. Validation showed good agreement between our BC, NO2, and PM2.5 measurements and monitoring agency sites (R2 = 0.68-0.73). Universal kriging-partial least squares models of annual average pollutant concentrations had cross-validated mean square error-based R2 (and root mean square error) values of 0.77 (1177 pt/cm3) for PNC, 0.60 (102 ng/m3) for BC, 0.77 (1.3 ppb) for NO2, 0.70 (0.3 µg/m3) for PM2.5, and 0.51 (4.2 ppm) for CO2. Overall, we found that the design of this extensive campaign captured the spatial pollutant variations well and these were explained by sensible land use features, including those related to traffic.

Traffic-related Air Pollution and Lung Cancer Incidence: The California Multiethnic Cohort Study.

Rationale: Although the contribution of air pollution to lung cancer risk is well characterized, few studies have been conducted in racially, ethnically, and socioeconomically diverse populations. Objectives: To examine the association between traffic-related air pollution and risk of lung cancer in a racially, ethnically, and socioeconomically diverse cohort. Methods: Among 97,288 California participants of the Multiethnic Cohort Study, we used Cox proportional hazards regression to examine associations between time-varying traffic-related air pollutants (gaseous and particulate matter pollutants and regional benzene) and lung cancer risk (n = 2,796 cases; average follow-up = 17 yr), adjusting for demographics, lifetime smoking, occupation, neighborhood socioeconomic status (nSES), and lifestyle factors. Subgroup analyses were conducted for race, ethnicity, nSES, and other factors. Measurements and Main Results: Among all participants, lung cancer risk was positively associated with nitrogen oxide (hazard ratio [HR], 1.15 per 50 ppb; 95% confidence interval [CI], 0.99-1.33), nitrogen dioxide (HR, 1.12 per 20 ppb; 95% CI, 0.95-1.32), fine particulate matter with aerodynamic diameter <2.5 µm (HR, 1.20 per 10 µg/m3; 95% CI, 1.01-1.43), carbon monoxide (HR, 1.29 per 1,000 ppb; 95% CI, 0.99-1.67), and regional benzene (HR, 1.17 per 1 ppb; 95% CI, 1.02-1.34) exposures. These patterns of associations were driven by associations among African American and Latino American groups. There was no formal evidence for heterogeneity of effects by nSES (P heterogeneity > 0.21), although participants residing in low-SES neighborhoods had increased lung cancer risk associated with nitrogen oxides, and no association was observed among those in high-SES neighborhoods. Conclusions: These findings in a large multiethnic population reflect an association between lung cancer and the mixture of traffic-related air pollution and not a particular individual pollutant. They are consistent with the adverse effects of air pollution that have been described in less racially, ethnically, and socioeconomically diverse populations. Our results also suggest an increased risk of lung cancer among those residing in low-SES neighborhoods.

Aircraft noise and vehicle traffic-related air pollution interact to affect preterm birth risk in Los Angeles, California.

INTRODUCTION: Air pollution has been linked to preterm birth (PTB) while findings for noise exposure have been mixed. Few studies - none considering airports - have investigated combined exposures. We explore the relationship between joint exposure to airport-related noise, airport ultrafine particles (UFP), and vehicle traffic-related air pollution (TRAP) on risk of PTB near Los Angeles International Airport (LAX). METHODS: We used comprehensive birth data for mothers living ≤15 km from LAX from 2008 to 2016 (n = 174,186) Noise data were generated by monitor-validated models. NO2 was used as a TRAP proxy, estimated with a seasonally-adjusted, validated land-use regression model. We estimated the effects of exposure to airport-related noise and TRAP on PTB employing logistic regression models that adjusted for known maternal risk factors for PTB as well as aircraft-origin UFP and neighborhood characteristics. RESULTS: The adjusted odds ratio (aOR) for PTB from high noise exposure (i.e. > 65 dB) was 1.10 (95% CI: 1.01-1.19). Relative to the first quartile, the aORs for PTB in the second, third, and fourth TRAP quartiles were 1.10 (95% CI: 1.05-1.16), 1.11 (95% CI: 1.05-1.16), and 1.15 (95% CI: 1.10-1.22), respectively. When stratifying by increasing TRAP quartiles, the aORs for PTB with high airport-related noise were 1.04 (95% CI: 0.91-1.18), 1.02 (95% CI: 0.88-1.19), 1.24 (95% CI: 1.03-1.48), and 1.44 (95% CI: 1.08-1.91) (p-interaction = 0.06). CONCLUSION: Our results suggest a potential synergism between airport-related noise and TRAP exposures on increasing the risk of PTB in this metropolitan area.