Air pollution exposures in early life and brain development in children (ABC): protocol for a pregnancy cohort study.

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.

Integrated hepatic transcriptomics and metabolomics identify Pck1 as a key factor in the broad dysregulation induced by vehicle pollutants.

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.

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 (, particulate matter with aerodynamic diameter ). Toxicological research suggests that these pathways might be important processes by which impacts health, but there are relatively few epidemiological studies due to a lack of a national monitoring network.

Objectives: We used new spatiotemporal exposure models to examine associations of both 1-y and 1-month average concentrations with markers of inflammation and coagulation.

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.

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 (PM) 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 [NO]) 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.

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.

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.

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.

Indoor Air Quality Intervention in Schools: Effectiveness of a Portable HEPA Filter Deployment in Five Schools Impacted by Roadway and Aircraft Pollution Sources.

The Healthy Air, Healthy Schools Study was established to better understand the impact of ultrafine particles (UFPs) on indoor air quality in communities surrounding Seattle-Tacoma (Sea-Tac) International Airport. The study team took multipollutant measurements of indoor and outdoor air pollution at five participating school locations to estimate infiltration indoors. The schools participating in this project were located within a 7-mile radius of Sea-Tac International Airport and within 0.

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.

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 (NO), fine particulate matter (PM), and carbon dioxide (CO) at 309 roadside sites within a large, 1200 land km (463 mi) area representative of the cohort.

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).

Publicly available low-cost sensor measurements for PM exposure modeling: Guidance for monitor deployment and data selection.

High-resolution, high-quality exposure modeling is critical for assessing the health effects of ambient PM in epidemiological studies. Using sparse regulatory PM measurements as principal model inputs may result in two issues in exposure prediction: (1) they may affect the models' accuracy in predicting PM spatial distribution; (2) the internal validation based on these measurements may not reliably reflect the model performance at locations of interest (e.g.

Deployment, Calibration, and Cross-Validation of Low-Cost Electrochemical Sensors for Carbon Monoxide, Nitrogen Oxides, and Ozone for an Epidemiological Study.

We designed and built a network of monitors for ambient air pollution equipped with low-cost gas sensors to be used to supplement regulatory agency monitoring for exposure assessment within a large epidemiological study. This paper describes the development of a series of hourly and daily field calibration models for Alphasense sensors for carbon monoxide (CO; CO-B4), nitric oxide (NO; NO-B4), nitrogen dioxide (NO; NO2-B43F), and oxidizing gases (OX-B431)-which refers to ozone (O) and NO. The monitor network was deployed in the Puget Sound region of Washington, USA, from May 2017 to March 2019.

Association between Airport-Related Ultrafine Particles and Risk of Malignant Brain Cancer: A Multiethnic Cohort Study.

Ultrafine particles (UFP; diameter less than or equal to 100 nm) may reach the brain via systemic circulation or the olfactory tract and have been implicated in the risk of brain tumors. The effects of airport-related UFP on the risk of brain tumors are not known. Here we determined the association between airport-related UFP and risk of incident malignant brain cancer ( = 155) and meningioma ( = 420) diagnosed during 16.

Improving Air Pollution Predictions of Long-Term Exposure Using Short-Term Mobile and Stationary Monitoring in Two US Metropolitan Regions.

Mobile monitoring is increasingly employed to measure fine spatial-scale variation in air pollutant concentrations. However, mobile measurement campaigns are typically conducted over periods much shorter than the decadal periods used for modeling chronic exposure for use in air pollution epidemiology. Using the regions of Los Angeles and Baltimore and the time period from 2005 to 2014 as our modeling domain, we investigate whether including mobile or stationary passive sampling device (PSD) monitoring data collected over a single 2-week period in one or two seasons using a unified spatio-temporal air pollution model can improve model performance in predicting NO and NO concentrations throughout the 9-year study period beyond what is possible using only routine monitoring data.

Distinct Ultrafine Particle Profiles Associated with Aircraft and Roadway Traffic.

The Mobile ObserVations of Ultrafine Particles study was a two-year project to analyze potential air quality impacts of ultrafine particles (UFPs) from aircraft traffic for communities near an international airport. The study assessed UFP concentrations within 10 miles of the airport in the directions of aircraft flight. Over the course of four seasons, this study conducted a mobile sampling scheme to collect time-resolved measures of UFP, CO, and black carbon (BC) concentrations, as well as UFP size distributions.

Predicting PM in Well-Mixed Indoor Air for a Large Office Building Using Regression and Artificial Neural Network Models.

Although the exposure to PM has serious health implications, indoor PM monitoring is not a widely applied practice. Regulations on the indoor PM level and measurement schemes are not well established. Compared to other indoor settings, PM prediction models for large office buildings are particularly lacking.

Probabilistic predictive principal component analysis for spatially misaligned and high-dimensional air pollution data with missing observations.

Accurate predictions of pollutant concentrations at new locations are often of interest in air pollution studies on fine particulate matters (PM), in which data is usually not measured at all study locations. PM is also a mixture of many different chemical components. Principal component analysis (PCA) can be incorporated to obtain lower-dimensional representative scores of such multi-pollutant data.