Long-term source apportionment of PM2.5 across the contiguous United States (2000-2019) using a multilinear engine model.

Identifying PM2.5 sources is crucial for effective air quality management and public health. This research used the Multilinear Engine (ME-2) model to analyze PM2.5 from 515 EPA Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE) sites across the U.S. from 2000 to 2019. The U.S. was divided into nine regions for detailed analysis. A total of seven source types (tracers) were resolved across the country: (1) Soil/Dust (Si, Al, Ca and Fe); (2) Vehicle emissions (EC, OC, Cu and Zn); (3) Biomass/wood burning (K); (4) Heavy oil/coal combustion (Ni, V, Cl and As); (5) Secondary sulfate (SO42-); (6) Secondary nitrate (NO3-) and (7) Sea salt (Mg, Na, Cl and SO42-). Furthermore, we extracted and calculated secondary organic aerosols (SOA) based on the secondary sulfate and nitrate factors. Notably, significant reductions in secondary sulfate, nitrate, and heavy oil/coal combustion emissions reflect recent cuts in fossil-fueled power sector emissions. A decline in SOA suggests effective mitigation of their formation conditions or precursors. Despite these improvements, vehicle emissions and biomass burning show no significant decrease, highlighting the need for focused control on these persistent pollution sources for future air quality management.

Elemental Characterization of Ambient Particulate Matter for a Globally Distributed Monitoring Network: Methodology and Implications.

Global ground-level measurements of elements in ambient particulate matter (PM) can provide valuable information to understand the distribution of dust and trace elements, assess health impacts, and investigate emission sources. We use X-ray fluorescence spectroscopy to characterize the elemental composition of PM samples collected from 27 globally distributed sites in the Surface PARTiculate mAtter Network (SPARTAN) over 2019-2023. Consistent protocols are applied to collect all samples and analyze them at one central laboratory, which facilitates comparison across different sites. Multiple quality assurance measures are performed, including applying reference materials that resemble typical PM samples, acceptance testing, and routine quality control. Method detection limits and uncertainties are estimated. Concentrations of dust and trace element oxides (TEO) are determined from the elemental dataset. In addition to sites in arid regions, a moderately high mean dust concentration (6 µg/m3) in PM2.5 is also found in Dhaka (Bangladesh) along with a high average TEO level (6 µg/m3). High carcinogenic risk (>1 cancer case per 100000 adults) from airborne arsenic is observed in Dhaka (Bangladesh), Kanpur (India), and Hanoi (Vietnam). Industries of informal lead-acid battery and e-waste recycling as well as coal-fired brick kilns likely contribute to the elevated trace element concentrations found in Dhaka.

Improvement of Surface PM2.5 Diurnal Variation Simulations in East Africa for the MAIA Satellite Mission.

The Multi-Angle Imager for Aerosols (MAIA), supported by NASA and the Italian Space Agency, is planned for launch into space in 2025. As part of its mission goal, outputs from a chemical transport model, the Unified Inputs for Weather Research and Forecasting Model coupled with Chemistry (UI-WRF-Chem), will be used together with satellite data and surface observations for estimating surface PM2.5. Here, we develop a method to improve UI-WRF-Chem with surface observations at the U.S. embassy in Ethiopia, one of MAIA's primary target areas in east Africa. The method inversely models the diurnal profile and amount of anthropogenic aerosol and trace gas emissions. Low-cost PurpleAir sensor data are used for validation after applying calibration functions obtained from the collocated data at the embassy. With the emission updates in UI-WRF-Chem, independent validation for February 2022 at several different PurpleAir sites shows an increase in the linear correlation coefficients from 0.1-0.7 to 0.6-0.9 between observations and simulations of the diurnal variation of surface PM2.5. Furthermore, even by using the emissions optimized for February 2021, the UI-WRF-Chem forecast for March 2022 is also improved. Annual update of monthly emissions via inverse modeling has the potential and is needed to improve MAIA's estimate of surface PM2.5.

Outdoor Ultrafine Particulate Matter and Risk of Lung Cancer in Southern California.

Rationale: Particulate matter ⩽2.5 µm in aerodynamic diameter (PM2.5) is an established cause of lung cancer, but the association with ultrafine particulate matter (UFP; aerodynamic diameter < 0.1 µm) is unclear. Objectives: To investigate the association between UFP and lung cancer overall and by histologic subtype. Methods: The Los Angeles Ultrafines Study includes 45,012 participants aged ⩾50 years in southern California at enrollment (1995-1996) followed through 2017 for incident lung cancer (n = 1,770). We estimated historical residential ambient UFP number concentrations via land use regression and back extrapolation using PM2.5. In Cox proportional hazards models adjusted for smoking and other confounders, we estimated associations between 10-year lagged UFP (per 10,000 particles/cm3 and quartiles) and lung cancer overall and by major histologic subtype (adenocarcinoma, squamous cell carcinoma, and small cell carcinoma). We also evaluated relationships by smoking status, birth cohort, and historical duration at the residence. Measurements and Main Results: UFP was modestly associated with lung cancer risk overall (hazard ratio [HR], 1.03 [95% confidence interval (CI), 0.99-1.08]). For adenocarcinoma, we observed a positive trend among men; risk was increased in the highest exposure quartile versus the lowest (HR, 1.39 [95% CI, 1.05-1.85]; P for trend = 0.01) and was also increased in continuous models (HR per 10,000 particles/cm3, 1.09 [95% CI, 1.00-1.18]), but no increased risk was apparent among women (P for interaction = 0.03). Adenocarcinoma risk was elevated among men born between 1925 and 1930 (HR, 1.13 [95% CI, 1.02-1.26] per 10,000) but not for other birth cohorts, and was suggestive for men with ⩾10 years of residential duration (HR, 1.11 [95% CI, 0.98-1.26]). We found no consistent associations for women or other histologic subtypes. Conclusions: UFP exposure was modestly associated with lung cancer overall, with stronger associations observed for adenocarcinoma of the lung.

Two-year-long high-time-resolution apportionment of primary and secondary carbonaceous aerosols in the Los Angeles Basin using an advanced total carbon-black carbon (TC-BC(λ)) method.

In recent years, carbonaceous aerosols (CA) have been recognized as a significant contributor to the concentration of particles smaller than 2.5 µm (i.e., PM2.5), with a negative impact on public health and Earth's radiative balance. In this study, we present a method for CA apportionment based on high-time-resolution measurements of total carbon (TC), black carbon (BC), and spectral dependence of absorption coefficient using a recently developed Carbonaceous Aerosol Speciation System (CASS). Two-year-long CA measurements at two different locations within California's Los Angeles Basin are presented. CA was apportioned based on its optical absorption properties, organic or elemental carbon composition, and primary or secondary origin. We found that the secondary organic aerosols (SOA), on average, represent >50 % of CA in the study area, presumably resulting from the oxidation of anthropogenic and biogenic volatile organic components. Remarkable peaks of SOA in summer afternoons were observed, with a fractional contribution of up to 90 %. On the other hand, the peak of primary emitted CA, consisting of BC and primary organic aerosol (POA), contributed >80 % to the CA during morning rush hours on winter working days. The light absorption of BC dominated over the brown carbon (BrC), which contributed to 20 % and 10 % of optical absorption at the lower wavelength of 370 nm during winter nights and summer afternoons, respectively. The highest contribution of BrC, up to 50 %, was observed during the wildfire periods. Although the uncertainty levels can be high for some CA components (such as split between primary emitted and secondary formed BrC during winter nights), further research focused on the optical properties of CA at different locations may help to better constrain the parameters used in CA apportionment studies. We believe that the CASS system combined with the apportionment method presented in this study can offer simplified and cost-effective insights into the composition of carbonaceous aerosols.

Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change.

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.

Land use regression models for ultrafine particles, fine particles, and black carbon in Southern California.

Exposure models are needed to evaluate health effects of long-term exposure to ambient ultrafine particles (UFP; <0.1 µm) and to disentangle their association from other pollutants, particularly PM2.5 (<2.5 µm). We developed land use regression (LUR) models to support UFP exposure assessment in the Los Angeles Ultrafines Study, a cohort in Southern California. We conducted a short-term measurement campaign in Los Angeles and parts of Riverside and Orange counties to measure UFP, PM2.5, and black carbon (BC), collecting three 30-minute average measurements at 215 sites across three seasons. We averaged concentrations for each site and evaluated geographic predictors including traffic intensity, distance to airports, land use, and population and building density by supervised stepwise selection to develop models. UFP and PM2.5 measurements (r = 0.001) and predictions (r = 0.05) were uncorrelated at the sites. UFP model explained variance was robust (R2 = 0.66) and 10-fold cross-validation indicated good performance (R2 = 0.59). Explained variation was moderate for PM2.5 (R2 = 0.47) and BC (R2 = 0.38). In the cohort, we predicted a 2.3-fold exposure contrast from the 5th to 95th percentiles for all three pollutants. The correlation between modeled UFP and PM2.5 at cohort residences was weak (r = 0.28), although higher than between measured levels. LUR models, particularly for UFP, were successfully developed and predicted reasonable exposure contrasts.

Impact of emissions from the Ports of Los Angeles and Long Beach on the oxidative potential of ambient PM0.25 measured across the Los Angeles County.

In this study, weekly samples of ambient PM0.25 (particulate matter with an aerodynamic diameter <0.25 µm) were collected in three contrasting locations, including central Los Angeles (USC), north Long Beach (NLB), and the Port of Long Beach (PRT), during June and July of 2017 to evaluate the chemical composition of ambient PM0.25 and identify the sources that contribute to the oxidative potential of ambient PM0.25 in these locations. Special focus was given in exploring the impact of emissions from the Ports of Los Angeles and Long Beach on the oxidative potential of ambient PM0.25 measured across these sites. The oxidative potential of the collected samples was quantified by means of an in vitro cell-based alveolar macrophage (AM) assay. We used multiple linear regression (MLR) analysis to link individual measured species, used as source markers, to the oxidative potential of the ambient PM0.25 across the monitoring sites. Results from the MLR analysis indicated that vehicular emissions and secondary organic aerosols (SOA) were the major contributors to the oxidative potential of ambient PM0.25 across the three sites, with corresponding contributions of 40 ±â€¯2% and 39 ±â€¯3%, respectively. Emissions of PM0.25 related to port activities, including emissions from ships, locomotives, and heavy-duty vehicles (HDVs) operating at the port, accounted for 16 ±â€¯3% of the overall oxidative potential of the ambient PM0.25 samples. The concentrations of the marker species at the three different sites suggested that the contributions of port-related emissions to the oxidative potential of PM0.25 decreased from the port area to central Los Angeles, underscoring the greater impact of these emissions on the PM0.25 toxicity in the communities near the Ports of Los Angeles and Long Beach, whereas we observed larger impact of SOA formation and vehicular emissions on the oxidative potential of ambient PM0.25 in the receptor sites located further inland.

Spatio-temporal trends and source apportionment of fossil fuel and biomass burning black carbon (BC) in the Los Angeles Basin.

In this study, we evaluated the spatial and temporal trends of black carbon (BC) in the Los Angeles Basin between 2012-2013 and 2016-2017. BC concentrations were measured in seven wavelengths using Aethalometers (AE33) at four sites, including central Los Angeles (CELA), Anaheim, Fontana, and Riverside. Sources of BC were quantified using the equivalent black carbon (EBC) model. Results indicate that total BC concentrations nearly doubled in colder period compared to the warm period. Source apportionment results revealed that fossil fuel combustion has higher annual contributions (ranging from 82% in Riverside to 91% in CELA) than biomass burning (ranging from 9.3% in CELA to 18.7% in Riverside) to the total BC concentrations at all sites. This trend was more clearly observed at the sites closer to major freeways, such as CELA and Anaheim. The relative contribution of fossil fuel to total BC concentrations was higher in the warm period, whereas biomass burning had higher contributions in the colder period. The diurnal variation of fossil-fuel-originated BC (BCff) to the total BC concentrations revealed major rises during the traffic rush hours, especially in the warm period. In contrast, the fraction of BC originating from biomass burning (BCbb) peaked at nighttime, particularly in the cold period, reaching values as high as 25-30% of total BC concentration. Moreover, we observed a clear decrease in both absolute BC concentrations as well as relative contributions of BCff to total BC concentrations from 2012-2013 to 2016-2017, which can be attributed to the implementation of strict regulations in California to reduce transportation-related PM emissions. Results from the present study suggest that as these regulations become increasingly stricter, the relative contributions of traffic sources to BC also decrease, thereby making the impact of non-fossil fuel combustion sources, such as biomass burning, to the overall BC levels more significant.

Associations of Source-apportioned Fine Particles with Cause-specific Mortality in California.

BACKGROUND: Exposure to ambient fine particulate matter (PM2.5) has been linked with premature mortality, but sources of PM2.5 have been less studied. METHODS: We evaluated associations between source-specific PM2.5 exposures and cause-specific short-term mortality in eight California locations from 2002 to 2011. Speciated PM2.5 measurements were source-apportioned using Positive Matrix Factorization into eight sources and combined with death certificate data. We used time-stratified case-crossover analysis with conditional logistic regression by location and meta-analysis to calculate pooled estimates. RESULTS: Biomass burning was associated with all-cause mortality lagged 2 days after exposure (lag2) (% changelag2 in odds per interquartile range width increase in biomass burning PM2.5 = 0.8, 95% confidence interval [CI] = 0.2, 1.4), cardiovascular (% changelag2 = 1.3, 95% CI = 0.3, 2.4), and ischemic heart disease (% changelag2 = 2.0, 95% CI = 0.6, 3.5). Vehicular emissions were associated with increases in cardiovascular mortality (% changelag0 = 1.4, 95% CI = 0.0, 2.9). Several other sources exhibited positive associations as well. Many findings persisted during the cool season. Warm season biomass burning was associated with respiratory/thoracic cancer mortality (% changelag1 = 5.9, 95% CI = 0.7, 11.3), and warm season traffic was associated with all-cause (% changelag0 = 1.9, 95% CI = 0.1, 3.6) and cardiovascular (% changelag0 = 2.9, 95% CI = 0.1, 5.7) mortality. CONCLUSIONS: Our results suggest that acute exposures to biomass burning and vehicular emissions are linked with cardiovascular mortality, with additional sources (i.e., soil, secondary nitrate, secondary sulfate, aged sea salt, and chlorine sources) showing associations with other specific mortality types.

Cause-specific stillbirth and exposure to chemical constituents and sources of fine particulate matter.

The stillbirth rate in the United States is relatively high, but limited evidence is available linking stillbirth with fine particulate matter (PM2.5), its chemical constituents and sources. In this study, we explored associations between cause-specific stillbirth and prenatal exposures to those pollutants with using live birth and stillbirth records from eight California locations during 2002-2009. ICD-10 codes were used to identify cause of stillbirth from stillbirth records. PM2.5 total mass and chemical constituents were collected from ambient monitors and PM2.5 sources were quantified using Positive Matrix Factorization. Conditional logistic regression was applied using a nested case-control study design (N = 32,262). We found that different causes of stillbirth were associated with different PM2.5 sources and/or chemical constituents. For stillbirths due to fetal growth, the odds ratio (OR) per interquartile range increase in gestational age-adjusted exposure to PM2.5 total mass was 1.23 (95% confidence interval (CI): 1.06, 1.44). Similar associations were found with resuspended soil (OR=1.25, 95% CI: 1.10, 1.42), and secondary ammonium sulfate (OR=1.45, 95% CI: 1.18, 1.78). No associations were found between any pollutants and stillbirths caused by maternal complications. This study highlighted the importance of investigating cause-specific stillbirth and the differential toxicity levels of specific PM2.5 sources and chemical constituents.

Source apportionment of fine particulate matter and risk of term low birth weight in California: Exploring modification by region and maternal characteristics.

Previous studies have demonstrated associations between fine particulate matter (PM2.5) and risk of term low birth weight (TLBW; birth weight<2500g and gestational weeks≥37weeks). However, it remains unclear which PM2.5 sources mainly contribute to these associations, and which subgroups (e.g. by residential region and maternal characteristics) may be more susceptible to these exposures. Using California birth records and PM2.5 data from eight monitoring sites from 2002 to 2009, we examined the relationship between exposures to total PM2.5 and PM2.5 sources and risk of TLBW. Source apportionment was performed for each site using Positive Matrix Factorization, and five PM2.5 sources (i.e., secondary ammonium sulfate, secondary ammonium nitrate, vehicular emissions, biomass burning, and resuspended soil) were included in our analysis. Mean gestational and trimester exposures were calculated for mothers with ZIP codes located within a 20km radius of monitors (N=1,050,330). Logistic regression was conducted and adjusted for maternal age, race/ethnicity, and education, as well as gestational age, year of birth, apparent temperature exposure during gestation, and neighborhood level percentage of households below poverty level. Increased risks of TLBW associated with each interquartile range increase in exposure were 4.9% (95% confidence interval: 2.6, 7.3) for total PM2.5, 7.7% (4.7, 10.7) for secondary ammonium sulfate, 5.6% (3.5, 7.7) for resuspended soil, and 3.1% (1.3, 4.9) for secondary ammonium nitrate. Differences in associations were found between inland and coastal regions, and between northern and southern regions for several sources. Results also showed effect measure modification by maternal race/ethnicity and education, with the lowest risk of TLBW associated with PM2.5 exposures found in mothers with at least a college education and Asian mothers. Some PM2.5 sources may be more harmful than others, and a better understanding of the relative toxicity of PM2.5 from each source could lead to more targeted and cost-effective regulations to protect public health.

Associations of Source-Specific Fine Particulate Matter With Emergency Department Visits in California.

While many studies have investigated the health effects associated with acute exposure to fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5)), very few have considered the risks of specific sources of PM2.5 We used city-specific source apportionment in 8 major metropolitan areas in California from 2005-2009 to examine the associations of source-specific PM2.5 exposures from vehicular emissions, biomass burning, soil, and secondary nitrate and sulfate sources with emergency department visits (EDVs) for cardiovascular and respiratory diseases, including 7 subclasses. Using a case-crossover analysis, we observed associations of vehicular emissions with all cardiovascular EDVs (excess risk = 1.6%, 95% confidence interval: 0.9, 2.4 for an interquartile-range increment of 2.8 µg/m(3)) and with several subclasses of disease. In addition, vehicular emissions, biomass burning, and soil sources were associated with all respiratory EDVs and with EDVs for asthma. The soil source, which includes resuspended road dust, generated the highest risk estimate for asthma (excess risk = 4.5%, 95% confidence interval: 1.1, 8.0). Overall, our results provide additional evidence of the public health consequences of exposure to specific sources of PM2.5 and indicate that some sources of PM2.5 may pose higher risks than the overall PM2.5 mass.

Associations between microvascular function and short-term exposure to traffic-related air pollution and particulate matter oxidative potential.

BACKGROUND: Short-term exposure to ambient air pollution has been associated with acute increases in cardiovascular hospitalization and mortality. However, causative chemical components and underlying pathophysiological mechanisms remain to be clarified. We hypothesized that endothelial dysfunction would be associated with mobile-source (traffic) air pollution and that pollutant components with higher oxidative potential to generate reactive oxygen species (ROS) would have stronger associations. METHODS: We carried out a cohort panel study in 93 elderly non-smoking adults living in the Los Angeles metropolitan area, during July 2012-February 2014. Microvascular function, represented by reactive hyperemia index (RHI), was measured weekly for up to 12 weeks (N = 845). Air pollutant data included daily data from regional air-monitoring stations, five-day average PM chemical components and oxidative potential in three PM size-fractions, and weekly personal nitrogen oxides (NOx). Linear mixed-effect models estimated adjusted changes in microvascular function with exposure. RESULTS: RHI was inversely associated with traffic-related pollutants such as ambient PM2.5 black carbon (BC), NOx, and carbon monoxide (CO). An interquartile range change increase (1.06 µg/m(3)) in 5-day average BC was associated with decreased RHI, -0.093 (95 % CI: -0.151, -0.035). RHI was inversely associated with other mobile-source components/tracers (polycyclic aromatic hydrocarbons, elemental carbon, and hopanes), and PM oxidative potential as quantified in two independent assays (dithiothreitol and in vitro macrophage ROS) in accumulation and ultrafine PM, and transition metals. CONCLUSIONS: Our findings suggest that short-term exposures to traffic-related air pollutants with high oxidative potential are major components contributing to microvascular dysfunction.

Associations of oxidative stress and inflammatory biomarkers with chemically-characterized air pollutant exposures in an elderly cohort.

BACKGROUND: Exposure to air pollution has been associated with cardiorespiratory morbidity and mortality. However, the chemical constituents and pollution sources underlying these associations remain unclear. METHOD: We conducted a cohort panel study involving 97 elderly subjects living in the Los Angeles metropolitan area. Airway and circulating biomarkers of oxidative stress and inflammation were measured weekly over 12 weeks and included, exhaled breath condensate malondialdehyde (EBC MDA), fractional exhaled nitric oxide (FeNO), plasma oxidized low-density lipoprotein (oxLDL), and plasma interleukin-6 (IL-6). Exposures included 7-day personal nitrogen oxides (NOx), daily criteria-pollutant data, five-day average particulate matter (PM) measured in three size-fractions and characterized by chemical components including transition metals, and in vitro PM oxidative potential (dithiothreitol and macrophage reactive oxygen species). Associations between biomarkers and pollutants were assessed using linear mixed effects regression models. RESULTS: We found significant positive associations of airway oxidative stress and inflammation with traffic-related air pollutants, ultrafine particles and transition metals. Positive but nonsignificant associations were observed with PM oxidative potential. The strongest associations were observed among PM variables in the ultrafine range (PM <0.18µm). It was estimated that an interquartile increase in 5-day average ultrafine polycyclic aromatic hydrocarbons was associated with a 6.3% (95% CI: 1.1%, 11.6%) increase in EBC MDA and 6.7% (95% CI: 3.4%, 10.2%) increase in FeNO. In addition, positive but nonsignificant associations were observed between oxLDL and traffic-related pollutants, ultrafine particles and transition metals while plasma IL-6 was positively associated with 1-day average traffic-related pollutants. CONCLUSION: Our results suggest that exposure to pollutants with high oxidative potential (traffic-related pollutants, ultrafine particles, and transition metals) may lead to increased airway oxidative stress and inflammation in elderly adults. This observation was less clear with circulating biomarkers.

The relative importance of tailpipe and non-tailpipe emissions on the oxidative potential of ambient particles in Los Angeles, CA.

This study examines the associations between the oxidative potential of ambient PM2.5 and PM0.18, measured by means of the dithiothreitol (DTT) assay, and their chemical constituents and modeled sources. Particulate matter (PM) samples were collected from 2012-2013 in Central Los Angeles (LA) and 2013-2014 in Anaheim, California, USA. Detailed chemical analyses of the PM samples, including carbonaceous species, inorganic elements and water-soluble ions, were conducted. Univariate analysis indicated a high correlation (R > 0.60) between the DTT activity and the concentrations of carbonaceous species at both sites. The strongest correlations were observed between DTT and organic tracers of primary vehicle tailpipe emissions including polycyclic aromatic hydrocarbons (PAHs) and hopanes as well as EC, with higher correlations for PM0.18versus PM2.5 components. Moreover, metals and trace elements (e.g., Ba, Cu, Fe, Mn, Pb and Sb) in both size ranges were also associated with DTT activity. Multiple linear regression (MLR) analysis was performed on DTT activity and PM sources identified by a Molecular Marker-Chemical Mass Balance (MM-CMB) model (i.e. major carbonaceous sources: vehicle tailpipe emissions, wood smoke, primary biogenic and secondary organic carbon) together with other typical sources of ambient PM (i.e. crustal material, vehicular abrasion, secondary ions and sea salt). Overall, our findings illustrate the relative importance of different traffic sources on the oxidative potential of ambient PM. Despite major reductions of tailpipe emissions, the lack of similar reductions (and possibly an increase) in non-tailpipe emissions makes them an important source of traffic-related PM in Los Angeles and their increasing role in the overall PM toxicity raises concerns for public health.

Urban traffic-derived nanoparticulate matter reduces neurite outgrowth via TNFα in vitro.

BACKGROUND: The basis for air pollution-associated neurodegenerative changes in humans is being studied in rodent models. We and others find that the ultrafine particulate matter (PM) derived from vehicular exhaust can induce synaptic dysfunction and inflammatory responses in vivo and in vitro. In particular, a nano-sized subfraction of particulate matter (nPM, PM0.2) from a local urban traffic corridor can induce glial TNFα production in mixed glia (astrocytes and microglia) derived from neonatal rat cerebral cortex. METHODS: Here, we examine the role of TNFα in neurite dysfunctions induced by nPM in aqueous suspensions at 12 µg/ml. First, we show that the proximal brain gateway to nPM, the olfactory neuroepithelium (OE), rapidly responds to nPM ex vivo, with induction of TNFα, activation of macrophages, and dendritic shrinkage. Cell interactions were further analyzed with mixed glia and neurons from neonatal rat cerebral cortex. RESULTS: Microglia contributed more than astrocytes to TNFα induction by nPM. We then showed that the threefold higher TNFα in conditioned media (nPM-CM) from mixed glia was responsible for the inhibition of neurite outgrowth by small interfering RNA (siRNA) TNFα knockdown and by TNFα immunoneutralization. Despite lack of TNFR1 induction by nPM in the OE, experimental blocking of TNFR1 by TNFα receptor blockers restored total neurite length. CONCLUSIONS: These findings implicate microglia-derived TNFα as a mediator of nPM in air pollution-associated neurodegenerative changes which alter synaptic functions and neuronal growth.

Fine and ultrafine particulate organic carbon in the Los Angeles basin: Trends in sources and composition.

In this study, PM2.5 and PM0.18 (particles with dp<2.5 µm and dp<0.18 µm, respectively) were collected during 2012-2013 in Central Los Angeles (LA) and 2013-2014 in Anaheim. Samples were chemically analyzed for carbonaceous species (elemental and organic carbons) and individual organic compounds. Concentrations of organic compounds were reported and compared with many previous studies in Central LA to quantify the impact of emissions control measurements that have been implemented for vehicular emissions over the past decades in this area. Moreover, a novel hybrid approach of molecular marker-based chemical mass balance (MM-CMB) analysis was conducted, in which a combination of source profiles that were previously obtained from a Positive Matrix Factorization (PMF) model in Central LA, were combined with some traditional source profiles. The model estimated the relative contributions from mobile sources (including gasoline, diesel, and smoking vehicles), wood smoke, primary biogenic sources (including emissions from vegetative detritus, food cooking, and re-suspended soil dust), and anthropogenic secondary organic carbon (SOC). Mobile sources contributed to 0.65 ± 0.25 µg/m(3) and 0.32 ± 0.25 µg/m(3) of PM2.5 OC in Central LA and Anaheim, respectively. Primary biogenic and anthropogenic SOC sources were major contributors to OC concentrations in both size fractions and sites. Un-apportioned OC ("other OC") accounted for an average 8.0 and 26% of PM2.5 OC concentration in Central LA and Anaheim, respectively. A comparison with previous studies in Central LA revealed considerable reduction of EC and OC, along with tracers of mobile sources (e.g. PAHs, hopanes and steranes) as a result of implemented regulations on vehicular emissions. Given the significant reduction of the impacts of mobile sources in the past decade in the LA Basin, the impact of SOC and primary biogenic emissions have a larger relative impact and the new hybrid model allows the impact of these sources to be better quantified.

Oxidative potential of coarse particulate matter (PM(10-2.5)) and its relation to water solubility and sources of trace elements and metals in the Los Angeles Basin.

In this study, potential sources of water-soluble (WS) and water-insoluble (WI) fractions of metals and trace elements in coarse particulate matter (CPM) (PM(10-2.5), 2.5 < dp < 10 µm) were identified and their association with the redox properties of CPM, measured by means of reactive oxygen species (ROS), was explored. CPM was collected during 2012-2013 in Central Los Angeles (LA) and 2013-2014 in Anaheim, CA. Generally, WI components contributed to a larger fraction of CPM ROS activity (as much as 64% and 54% at Central LA and Anaheim, respectively). Two major source factors were identified by principal component analysis for both the WS and WI fractions: vehicular abrasion and re-suspended road dust. Univariate analysis indicated that several species were correlated with CPM ROS activity: in WS fraction, metals such as Mn, Fe, Cd and Zn were associated with WS ROS, while in WI fraction Ti, Fe, Ni, Pb and Cr had the highest correlations with WI ROS activity. Multiple linear regression analysis revealed that both vehicular abrasion and re-suspension of road dust were associated with WS ROS activity, while only vehicular abrasion contributed significantly to the WI ROS activity. Moreover, comparison with previous studies indicated that the ROS activity of CPM has increased in the past 5 years in Central LA. We attribute this increase mainly to the elevated levels of re-suspension of road dust caused by the increase in vehicle speed and number of trucks in recent years in this area, reaffirming the growing importance of non-tailpipe traffic emissions on CPM toxicity.