Ambient exposure to fine particulate matter with oxidative potential affects oxidative stress biomarkers in pregnancy.

Prenatal exposures to ambient particulate matter (PM2.5) from traffic may generate oxidative stress, and thus contribute to adverse birth outcomes. We investigated whether PM2.5 constituents from brake and tire wear affect levels of oxidative stress biomarkers (malondialdehyde (MDA), 8-hydroxy-2'-deoxyguanosine (8-OHdG)) using urine samples collected up to three times during pregnancy in 156 women recruited from antenatal clinics at the University of California Los Angeles. Land use regression models with co-kriging were employed to estimate average residential outdoor concentrations of black carbon (BC), PM2.5 mass, PM2.5 metal components, and three PM2.5 oxidative potential metrics during the 4-weeks prior to urine sample collection. 8-OHdG concentrations in mid-pregnancy increased by 24.8% (95% CI: 9.0, 42.8) and 14.3% (95% CI: 0.4%, 30.0%) per interquartile range (IQR) increase in PM2.5 mass and BC, respectively. The brake wear marker (barium) and the oxidative potential metrics were associated with increased MDA concentration in the 1st sample collected (10-17 gestational week), but 95% CIs included the null. Traffic-related air pollution contributed in early to mid-pregnancy to oxidative stress generation previously linked to adverse birth outcomes.

Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position.

Oxidative potential (OP) has been proposed as a possible integrated metric for particles smaller than 2.5 µm in diameter (PM2.5) to evaluate adverse health outcomes associated with particulate air pollution exposure. Here, we investigate how OP depends on sources and chemical composition and how OP varies by land use type and neighborhood socioeconomic position in the Los Angeles area. We measured OH formation (OPOH), dithiothreitol loss (OPDTT), black carbon, and 52 metals and elements for 54 total PM2.5 samples collected in September 2019 and February 2020. The Positive Matrix Factorization source apportionment model identified four sources contributing to volume-normalized OPOH: vehicular exhaust, brake and tire wear, soil and road dust, and mixed secondary and marine. Exhaust emissions contributed 42% of OPOH, followed by 21% from brake and tire wear. Similar results were observed for the OPDTT source apportionment. Furthermore, by linking measured PM2.5 and OP with census tract level socioeconomic and health outcome data provided by CalEnviroScreen, we found that the most disadvantaged neighborhoods were exposed to both the most toxic particles and the highest particle concentrations. OPOH exhibited the largest inverse social gradients, followed by OPDTT and PM2.5 mass. Finally, OPOH was the metric most strongly correlated with adverse health outcome indicators.

A Review of Road Traffic-Derived Non-Exhaust Particles: Emissions, Physicochemical Characteristics, Health Risks, and Mitigation Measures.

Implementation of regulatory standards has reduced exhaust emissions of particulate matter from road traffic substantially in the developed world. However, nonexhaust particle emissions arising from the wear of brakes, tires, and the road surface, together with the resuspension of road dust, are unregulated and exceed exhaust emissions in many jurisdictions. While knowledge of the sources of nonexhaust particles is fairly good, source-specific measurements of airborne concentrations are few, and studies of the toxicology and epidemiology do not give a clear picture of the health risk posed. This paper reviews the current state of knowledge, with a strong focus on health-related research, highlighting areas where further research is an essential prerequisite for developing focused policy responses to nonexhaust particles.

Fine Particulate Matter Metal Composition, Oxidative Potential, and Adverse Birth Outcomes in Los Angeles.

BACKGROUND: Although many studies have linked prenatal exposure to PM2.5 to adverse birth outcomes, little is known about the effects of exposure to specific constituents of PM2.5 or mechanisms that contribute to these outcomes. OBJECTIVES: Our objective was to investigate effects of oxidative potential and PM2.5 metal components from non-exhaust traffic emissions, such as brake and tire wear, on the risk of preterm birth (PTB) and term low birth weight (TLBW). METHODS: For a birth cohort of 285,614 singletons born in Los Angeles County, California, in the period 2017-2019, we estimated speciated PM2.5 exposures modeled from land use regression with cokriging, including brake and tire wear related metals (barium and zinc), black carbon, and three markers of oxidative potential (OP), including modeled reactive oxygen species based on measured iron and copper (ROS), OH formation (OPOH), and dithiothreitol (DTT) loss (OPDTT). Using logistic regression, we estimated odds ratios (OR) and 95% confidence intervals (CI) for PTB and TLBW with speciated PM2.5 exposures and PM2.5 mass as continuous variables scaled by their interquartile range (IQR). RESULTS: For both metals and oxidative potential metrics, we estimated increased risks for PTB (ORs ranging from 1.01 to 1.03) and TLBW (ORs ranging from 1.02 to 1.05) per IQR exposure increment that were robust to adjustment for PM2.5 mass. Associations for PM2.5 mass, black carbon, metal components, and oxidative potential (especially ROS and OPOH) with adverse birth outcomes were stronger in Hispanic, Black, and mixed-race or Native American women. DISCUSSION: Our results indicate that exposure to PM2.5 metals from brake and tire wear and particle components that contribute to oxidative potential were associated with an increased risk of PTB and TLBW in Los Angeles County, particularly among Hispanic, Black, and mixed-race or Native American women. Thus, reduction of PM2.5 mass only may not be sufficient to protect the most vulnerable pregnant women and children from adverse effects due to traffic source exposures. https://doi.org/10.1289/EHP12196.

Elemental composition of fine and coarse particles across the greater Los Angeles area: Spatial variation and contributing sources.

The inorganic components of particulate matter (PM), especially transition metals, have been shown to contribute to PM toxicity. In this study, the spatial distribution of PM elements and their potential sources in the Greater Los Angeles area were studied. The mass concentration and detailed elemental composition of fine (PM2.5) and coarse (PM2.5-10) particles were assessed at 46 locations, including urban traffic, urban community, urban background, and desert locations. Crustal enrichment factors (EFs), roadside enrichments (REs), and bivariate correlation analysis revealed that Ba, Cr, Cu, Mo, Pd, Sb, Zn, and Zr were associated with traffic emissions in both PM2.5 and PM2.5-10, while Fe, Li, Mn, and Ti were affected by traffic emissions mostly in PM2.5. The concentrations of Ba, Cu, Mo, Sb, Zr (brake wear tracers), Pd (tailpipe tracer), and Zn (associated with tire wear) were higher at urban traffic sites than urban background locations by factors of 2.6-4.6. Both PM2.5 and PM2.5-10 elements showed large spatial variations, indicating the presence of diverse emission sources across sampling locations. Principal component analysis extracted four source factors that explained 88% of the variance in the PM2.5 elemental concentrations, and three sources that explained 86% of the variance in the PM2.5-10 elemental concentrations. Based on multiple linear regression analysis, the contribution of traffic emissions (27%) to PM2.5 was found to be higher than mineral dust (23%), marine aerosol (18%), and industrial emissions (8%). On the other hand, mineral dust was the dominant source of PM2.5-10 with 45% contribution, followed by marine aerosol (22%), and traffic emissions (19%). This study provides novel insight into the spatial variation of traffic-related elements in a large metropolitan area.

Co-kriging with a low-cost sensor network to estimate spatial variation of brake and tire-wear metals and oxidative stress potential in Southern California.

Due to regulations and technological advancements reducing tailpipe emissions, an increasing proportion of emissions arise from brake and tire wear particulate matter (PM). PM from these non-tailpipe sources contains heavy metals capable of generating oxidative stress in the lung. Although important, these particles remain understudied because the high cost of actively collecting filter samples. Improvements in electrical engineering, internet connectivity, and an increased public concern over air pollution have led to a proliferation of dense low-cost air sensor networks such as the PurpleAir monitors, which primarily measure unspeciated fine particulate matter (PM2.5). In this study, we model the concentrations of Ba, Zn, black carbon, reactive oxygen species concentration in the epithelial lining fluid, dithiothreitol (DTT) loss, and OH formation. We use a co-kriging approach, incorporating data from the PurpleAir network as a secondary predictor variable and a land-use regression (LUR) as an external drift. For most pollutant species, co-kriging models produced more accurate predictions than an LUR model, which did not incorporate data from the PurpleAir monitors. This finding suggests that low-cost sensors can enhance predictions of pollutants that are costly to measure extensively in the field.

Experimental study of a string-based counterflow wet electrostatic precipitator for collection of fine and ultrafine particles.

Wet electrostatic precipitators (WESP) have been widely studied for collecting fine and ultrafine particles, such as diesel particulate matter (DPM), which have deleterious effects on human health. Here, we report an experimental and numerical simulation study on a novel string-based two-stage WESP. Our new design incorporates grounded vertically aligned polymer strings, along which thin films of water flow down. The water beads, generated by intrinsic flow instability, travel down the strings and collect charged particles in the counterflowing gas stream. We performed experiments using two different geometric configurations of WESP: rectangular and cylindrical. We examined the effects of the WESP electrode bias voltage, air stream velocity, and water flow rate on the number-based fractional collection efficiency for particles of diameters ranging from 10 nm to 2.5 µm. The collection efficiency improves with increasing bias voltages or decreasing airflow rates. At liquid-to-gas (L/G) as low as approximately 0.0066, our design delivers a collection efficiency over 70% even for fine and ultrafine particles. The rectangular and cylindrical configurations exhibit similar collection efficiencies under nominally identical experimental conditions. We also compare the water-to-air mass flow rate ratio, air flow rate per unit collector volume, and collection efficiency of our string-based design with those of previously reported WESPs. The present work demonstrates a promising design for a highly efficient, compact, and scalable two-stage WESPs with minimal water consumption.Implications: Wet Electrostatic Precipitators (WESPs) are highly effective for collecting fine particles in exhaust air streams from various sources such as diesel engines, power plants, and oil refineries. However, their large-scale adoption has been limited by high water usage and reduced collection efficiencies for ultrafine particles. We perform experimental and numerical investigation to characterize the collection efficiency and water flow rate-dependence of a new design of WESP. The string-based counterflow WESP reported in this study offers number-based collection efficiencies >70% at air flow rates per collector volume as high as 4.36 (m3/s)/m3 for particles of diameters ranging from 10 nm - 2.5 µm, while significantly reducing water usage. Our work provides a basis for the design of more compact and water-efficient WESPs.