Development of ASTM International D8405-Standard Test Method for Evaluating PM2.5 Sensors or Sensor Systems Used in Indoor Applications.

Sensors and sensor systems for monitoring fine particles with aerodynamic diameters smaller than 2.5 µm can provide real-time feedback on indoor air quality and thus can help guide actions to manage indoor air pollutant concentrations. Standardized verification of the performance and accuracy of sensors and sensor systems is crucial for predicting the efficacy of such monitoring. A new ASTM International standard test method (ASTM D8405) was created for this need and is the most exacting laboratory protocol published to date for evaluating indoor air quality sensors and sensor systems measuring particles smaller than 2.5 µm in diameter. ASTM D8405 subjects sensors and sensor systems to five test phases: (1) an initial particle concentration ramp; (2) exposure to various temperature and humidity conditions; (3) exposure to interfering particles; (4) temperature cycling; and (5) a final particle concentration ramp to assess drift. This paper discusses the development of the standard test method, key aspects of the testing process, example evaluation results, and a comparison of this standard test method against peer evaluation protocols.

Towards the Development of a Sensor Educational Toolkit to Support Community and Citizen Science.

As air quality sensors increasingly become commercially available, a deeper consideration of their usability and usefulness is needed to ensure effective application by the public. Much of the research related to sensors has focused on data quality and potential applications. While this information is important, a greater understanding of users' experience with sensors would provide complementary information. Under a U.S. EPA-funded Science to Achieve Results grant awarded to the South Coast Air Quality Management District in California, titled "Engage, Educate, and Empower California Communities on the Use and Applications of Low-Cost Air Monitoring Sensors", approximately 400 air quality sensors were deployed with 14 California communities. These communities received sensors and training, and they participated in workshops. Widely varying levels of sensor installation and engagement were observed across the 14 communities. However, despite differences between communities (in terms of participation, demographics, and socioeconomic factors), many participants offered similar feedback on the barriers to sensor use and strategies leading to successful sensor use. Here, we assess sensor use and participant feedback, as well as discuss the development of an educational toolkit titled "Community in Action: A Comprehensive Toolkit on Air Quality Sensors". This toolkit can be leveraged by future community and citizen science projects to develop networks designed to collect air quality information that can help reduce exposure to and the emissions of pollutants, leading to improved environmental and public health.

Long-term evaluation of a low-cost air sensor network for monitoring indoor and outdoor air quality at the community scale.

Given the growing interest in community air quality monitoring using low-cost sensors, 30 PurpleAir II sensors (12 outdoor and 18 indoor) were deployed in partnership with community members living adjacent to a major interstate freeway from December 2017- June 2019. Established quality assurance/quality control techniques for data processing were used and sensor data quality was evaluated by calculating data completeness and summarizing PM2.5 measurements. To evaluate outdoor sensor performance, correlation coefficients (r) and coefficients of divergence (CoD) were used to assess temporal and spatial variability of PM2.5 between sensors. PM2.5 concentrations were also compared to traffic levels to assess the sensors' ability to detect traffic pollution. To evaluate indoor sensors, indoor/outdoor (I/O) ratios during resident-reported activities were calculated and compared, and a linear mixed-effects regression model was developed to quantify the impacts of ambient air quality, microclimatic factors, and indoor human activities on indoor PM2.5. In general, indoor sensors performed more reliably than outdoor sensors (completeness: 73% versus 54%). All outdoor sensors were highly temporally correlated (r > 0.98) and spatially homogeneous (CoD<0.06). The observed I/O ratios were consistent with existing literature, and the mixed-effects model explains >85% of the variation in indoor PM2.5 levels, indicating that indoor sensors detected PM2.5 from various sources. Overall, this study finds that community-maintained sensors can effectively monitor PM2.5, with main data quality concerns resulting from outdoor sensor data incompleteness.

Development of a Performance Evaluation Protocol for Air Sensors Deployed on a Google Street View Car.

Performance evaluation studies of low-cost sensors (LCS) measuring air pollutants have been conducted by academic and governmental groups for stationary applications. In contrast, evaluation protocols are nonexistent for LCS used in mobile deployments, though LCS are used in this manner by research groups and may be employed to complement regulatory directives for community monitoring. Mobile measurements with LCS are a nascent but growing use-case, and questions of data quality will become increasingly important. The South Coast Air Quality Management District's Air Quality Sensor Performance Evaluation Center has developed the first evaluation protocol in which LCS are compared to reference- or research-grade instruments while deployed on a ground-based mobile platform. LCS are assessed in test scenarios of various degrees of environmental control, ranging from placement in a controlled flow sampling duct to unsheltered mounting on a vehicle rooftop. The testing procedures aim to quantify the performance of LCS and the effects of sensor siting, orientation, and vehicle velocity, the results of which can guide users on appropriate LCS and configurations for their applications. Unexpected performance effects have been revealed through pilot-testing of this evaluation protocol that would likely have not been known from stationary field and laboratory testing.

Development of a Network of Accurate Ozone Sensing Nodes for Parallel Monitoring in a Site Relocation Study.

Recent technological advances in both air sensing technology and Internet of Things (IoT) connectivity have enabled the development and deployment of remote monitoring networks of air quality sensors. The compact size and low power requirements of both sensors and IoT data loggers allow for the development of remote sensing nodes with power and connectivity versatility. With these technological advancements, sensor networks can be developed and deployed for various ambient air monitoring applications. This paper describes the development and deployment of a monitoring network of accurate ozone (O3) sensor nodes to provide parallel monitoring in an air monitoring site relocation study. The reference O3 analyzer at the station along with a network of three O3 sensing nodes was used to evaluate the spatial and temporal variability of O3 across four Southern California communities in the San Bernardino Mountains which are currently represented by a single reference station in Crestline, CA. The motivation for developing and deploying the sensor network in the region was that the single reference station potentially needed to be relocated due to uncertainty that the lease agreement would be renewed. With the implication of siting a new reference station that is also a high O3 site, the project required the development of an accurate and precise sensing node for establishing a parallel monitoring network at potential relocation sites. The deployment methodology included a pre-deployment co-location calibration to the reference analyzer at the air monitoring station with post-deployment co-location results indicating a mean absolute error (MAE) < 2 ppb for 1-h mean O3 concentrations. Ordinary least squares regression statistics between reference and sensor nodes during post-deployment co-location testing indicate that the nodes are accurate and highly correlated to reference instrumentation with R2 values > 0.98, slope offsets < 0.02, and intercept offsets < 0.6 for hourly O3 concentrations with a mean concentration value of 39.7 ± 16.5 ppb and a maximum 1-h value of 94 ppb. Spatial variability for diurnal O3 trends was found between locations within 5 km of each other with spatial variability between sites more pronounced during nighttime hours. The parallel monitoring was successful in providing the data to develop a relocation strategy with only one relocation site providing a 95% confidence that concentrations would be higher there than at the current site.

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.

Impact of California Fires on Local and Regional Air Quality: The Role of a Low-Cost Sensor Network and Satellite Observations.

PM2.5, or fine particulate matter, is a category of air pollutant consisting of particles with effective aerodynamic diameter equal to or less than 2.5 µm. These particles have been linked to human health impacts as well as regional haze, visibility, and climate change issues. Due to cost and space restrictions, the U.S. Environmental Protection Agency monitoring network remains spatially sparse. To increase the spatial resolution of monitoring, previous studies have used satellite data to estimate ground-level PM concentrations, despite these estimates being associated with moderate to large uncertainties when relating a column measure of aerosol (aerosol optical depth) with surface measurements. To this end, we discuss a low-cost air quality monitor (LCAQM) network deployed in California. In this study, we present an application of LCAQM and satellite data for quantifying the impact of wildfires in California during October 2017. The impacts of fires on PM2.5 concentration at varying temporal (hourly, daily, and weekly) and spatial (local to regional) scales have been evaluated. Comparison between low-cost air quality sensors and reference-grade air quality instruments shows expected performance with moderate to high uncertainties. The LCAQM measurements, in the absence of federal equivalent method data, were also found to be very useful in developing statistical models to convert aerosol optical depth into PM2.5 with performance of satellite-derived PM2.5, similar to that obtained using the federal equivalent method data. This paper also highlights challenges associated with both LCAQM and satellite-based PM2.5 measurements, which require further investigation and research.

Correction methods for organic carbon artifacts when using quartz-fiber filters in large particulate matter monitoring networks: the regression method and other options.

Sampling and handling artifacts can bias filter-based measurements of particulate organic carbon (OC). Several measurement-based methods for OC artifact reduction and/or estimation are currently used in research-grade field studies. OC frequently is not artifact-corrected in large routine sampling networks (e.g., U.S. Environmental Protection Agency (EPA)'s Chemical Speciation Network). In some cases, the OC artifact has been corrected using a regression method (RM) for artifact estimation. In this method, the gamma-intercept of the regression of the OC concentration on the fine particle (PM2.5) mass concentration is taken to be an estimate of the average OC sampling artifact (net of positive and negative artifacts). This paper discusses options for artifact correction in large routine sampling networks. Specifically, the goals are to (1) articulate the assumptions and limitations inherent to the RM, (2) describe other artifact correction approaches, and (3) suggest a cost-effective method for artifact correction in large monitoring networks. The RM assumes a linear relationship between measured OC and PM mass: a constant slope (OC mass fraction) and a constant intercept (RM artifact estimate). These assumptions are not always valid. Additionally, outliers and other individual data points can have a large influence on the RM artifact estimates. The RM yields results within the range of measurement-based methods for some datasets and not for others. Given that the adsorption of organic gases increases with atmospheric concentrations of organics, subtraction of an average artifact from all samples (e.g., across multiple sites) will underestimate OC for lower-concentration samples (e.g., clean sites) and overestimate OC for higher-concentration samples (e.g., polluted sites). For relatively accurate, simple, and cost-effective artifact OC estimation in large networks, the authors suggest backup filter sampling on at least 10% of sampling days at all sites with artifact correction on a sample-by-sample basis as described herein.

Electrocardiographic ST-segment depression and exposure to traffic-related aerosols in elderly subjects with coronary artery disease.

BACKGROUND: Air pollutants have not been associated with ambulatory electrocardiographic evidence of ST-segment depression ≥ 1 mm (probable cardiac ischemia). We previously found that markers of primary (combustion-related) organic aerosols and gases were positively associated with circulating biomarkers of inflammation and ambulatory blood pressure in the present cohort panel study of elderly subjects with coronary artery disease. OBJECTIVES: We specifically aimed to evaluate whether exposure markers of primary organic aerosols and ultrafine particles were more strongly associated with ST-segment depression of ≥ 1 mm than were secondary organic aerosols or PM2.5 (particulate matter with aerodynamic diameter ≤ 2.5 µm) mass. METHODS: We evaluated relations of air pollutants to ambulatory electrocardiographic evidence of cardiac ischemia over 10 days in 38 subjects without ST depression on baseline electrocardiographs. Exposures were measured outdoors in retirement communities in the Los Angeles basin, including daily size-fractionated particle mass and hourly markers of primary and secondary organic aerosols and gases. Generalized estimating equations were used to estimate odds of hourly ST-segment depression (≥ 1 mm) from hourly air pollution exposures and to estimate relative rates of daily counts of ST-segment depression from daily average exposures, controlling for potential confounders. RESULTS: We found significant positive associations of hourly ST-segment depression with markers of combustion-related aerosols and gases averaged 1-hr through 3-4 days, but not secondary (photochemically aged) organic aerosols or ozone. The odds ratio per interquartile increase in 2-day average primary organic carbon (5.2 µg/m3) was 15.4 (95% confidence interval, 3.5-68.2). Daily counts of ST-segment depression were consistently associated with primary combustion markers and 2-day average quasi-ultrafine particles < 0.25 µm. CONCLUSIONS: Results suggest that exposure to quasi-ultrafine particles and combustion-related pollutants (predominantly from traffic) increase the risk of myocardial ischemia, coherent with our previous findings for systemic inflammation and blood pressure.

Associations of primary and secondary organic aerosols with airway and systemic inflammation in an elderly panel cohort.

BACKGROUND: Exposure-response information about particulate air-pollution constituents is needed to protect sensitive populations. Particulate matter <2.5 mm (PM2.5) components may induce oxidative stress through reactive-oxygen-species generation, including primary organics from combustion sources and secondary organics from photochemically oxidized volatile organic compounds. We evaluated differences in airway versus systemic inflammatory responses to primary versus secondary organic particle components, particle size fractions, and the potential of particles to induce cellular production of reactive oxygen species. METHODS: A total of 60 elderly subjects contributed up to 12 weekly measurements of fractional exhaled nitric oxide (NO; airway inflammation biomarker), and plasma interleukin-6 (IL-6; systemic inflammation biomarker). PM2.5 mass fractions were PM0.25 (<0.25 µm) and PM0.25-2.5 (0.25-2.5 µm). Primary organic markers included PM2.5 primary organic carbon, and PM0.25 polycyclic aromatic hydrocarbons and hopanes. Secondary organic markers included PM2.5 secondary organic carbon, and PM0.25 water soluble organic carbon and n-alkanoic acids. Gaseous pollutants included carbon monoxide (CO) and nitrogen oxides (NOx; combustion emissions markers), and ozone (O3; photochemistry marker). To assess PM oxidative potential, we exposed rat alveolar macrophages in vitro to aqueous extracts of PM0.25 filters and measured reactive-oxygen-species production. Biomarker associations with exposures were evaluated with mixed-effects models. RESULTS: Secondary organic markers, PM0.25-2.5, and O3 were positively associated with exhaled NO. Primary organic markers, PM0.25, CO, and NOx were positively associated with IL-6. Reactive oxygen species were associated with both outcomes. CONCLUSIONS: Particle effects on airway versus systemic inflammation differ by composition, but overall particle potential to induce generation of cellular reactive oxygen species is related to both outcomes.

Traffic-related air pollution and blood pressure in elderly subjects with coronary artery disease.

BACKGROUND: Associations between blood pressure (BP) and ambient air pollution have been inconsistent. No studies have used ambulatory BP monitoring and outdoor home air-pollutant measurements with time-activity-location data. We address these gaps in a study of 64 elderly subjects with coronary artery disease, living in retirement communities in the Los Angeles basin. METHODS: Subjects were followed up for 10 days with hourly waking ambulatory BP monitoring (n = 6539 total measurements), hourly electronic diaries for perceived exertion and location, and real-time activity monitors (actigraphs). We measured hourly outdoor home pollutant gases, particle number, PM2.5, organic carbon, and black carbon. Data were analyzed with mixed models controlling for temperature, posture, actigraph activity, hour, community, and season. RESULTS: We found positive associations of systolic and diastolic BP with air pollutants. The strongest associations were with organic carbon (especially its estimated fossil-fuel- combustion fraction), multiday average exposures, and time periods when subjects were at home. An interquartile increase in 5-day average organic carbon (5.2 microg/m) was associated with 8.2 mm Hg higher mean systolic BP (95% confidence interval = 3.0-13.4) and 5.8 mm Hg higher mean diastolic BP (3.0-8.6). Associations of BP with 1-8 hour average air pollution were stronger with reports of moderate to strenuous physical exertion but not with higher actigraph motion. Associations were also stronger among 12 obese subjects. CONCLUSIONS: Exposure to primary organic components of fossil fuel combustion near the home were strongly associated with increased ambulatory BP in a population at potential risk of heart attack. Low fitness or obesity may increase the effects of pollutants.

Association of biomarkers of systemic inflammation with organic components and source tracers in quasi-ultrafine particles.

BACKGROUND: Evidence is needed regarding the air pollutant components and their sources responsible for associations between particle mass concentrations and human cardiovascular outcomes. We previously found associations between circulating biomarkers of inflammation and mass concentrations of quasi-ultrafine particles

Chemical characteristics and oxidative potential of particulate matter emissions from gasoline, diesel, and biodiesel cars.

Three light-duty vehicles in five different configurations [a Honda Accord operating with diesel with a closed-coupled oxidation catalyst and an underfloor catalyst replaced in some tests with a diesel particle filter (DPF), a Toyota Corolla operating with gasoline, and a VW Golf alternatively operating with petrodiesel or biodiesel] were tested in a dynamometer facility to develop an improved understanding of the factors affecting the toxicity of particulate exhaust emissions. The vehicles were tested using a variety of real-world driving cycles, more than the certification test (New European Driving Cycle). Particle samples were collected and analyzed for elemental and organic carbon (EC and OC, respectively), water soluble and water insoluble organic carbon (WSOC and WISOC, respectively), and inorganic ions, and the emission rates (mg/km) for each vehicle/configuration were determined. A dithiothreitol (DTT) assay was used to assess the oxidative potential of the particulate matter (PM) samples. The DPF-equipped diesel and gasoline vehicles were characterized by the lowest overall PM mass emissions, while the diesel and biodiesel cars produced the most potent exhaust in terms of oxidative activity. When the DPF was fitted on the Honda Accord diesel vehicle, the mass emission rates and distance-based oxidative potential were both decreased by 98%, compared to the original configuration. Correlation analysis showed that the DTT consumption rate was highly associated with WSOC, WISOC, and OC (R = 0.98, 0.93, and 0.94, respectively), consistent with previous findings.

Air pollution exposures and circulating biomarkers of effect in a susceptible population: clues to potential causal component mixtures and mechanisms.

BACKGROUND: Mechanisms involving oxidative stress and inflammation have been proposed to explain associations of ambient air pollution with cardiovascular morbidity and mortality. Experimental evidence suggests that organic components and ultrafine particles (UFP) are important. METHODS: We conducted a panel study of 60 elderly subjects with coronary artery disease living in retirement communities within the Los Angeles, California, air basin. Weekly biomarkers of inflammation included plasma interleukin-6, tumor necrosis factor-alpha soluble receptor II (sTNF-RII), soluble platelet selectin (sP-selectin), and C-reactive protein (CRP). Biomarkers of erythrocyte antioxidant activity included glutathione peroxidase-1 and superoxide dismutase. Exposures included outdoor home daily particle mass [particulate matter < 0.25, 0.25-2.5, and 2.5-10 microm in aerodynamic diameter (PM(0.25), PM(0.25-2.5), PM(2.5-10))], and hourly elemental and black carbon (EC-BC), estimated primary and secondary organic carbon (OC(pri), SOC), particle number (PN), carbon monoxide (CO), and nitrogen oxides-nitrogen dioxide (NO(x)-NO(2)). We analyzed the relation of biomarkers to exposures with mixed effects models adjusted for potential confounders. RESULTS: Primary combustion markers (EC-BC, OC(pri), CO, NO(x)-NO(2)), but not SOC, were positively associated with inflammatory biomarkers and inversely associated with erythrocyte anti-oxidant enzymes (n = 578). PN and PM(0.25) were more strongly associated with biomarkers than PM(0.25-2.5). Associations for all exposures were stronger during cooler periods when only OC(pri), PN, and NO(x) were higher. We found weaker associations with statin (sTNF-RII, CRP) and clopidogrel use (sP-selectin). CONCLUSIONS: Traffic-related air pollutants are associated with increased systemic inflammation, increased platelet activation, and decreased erythrocyte antioxidant enzyme activity, which may be partly behind air pollutant-related increases in systemic inflammation. Differences in association by particle size, OC fraction, and seasonal period suggest components carried by UFP are important.

Associations between personal, indoor, and residential outdoor pollutant concentrations: implications for exposure assessment to size-fractionated particulate matter.

The physical and chemical characteristics of indoor, outdoor, and personal quasi-ultrafine (<0.25 microm)-, accumulation (0.25-2.5 microm)-, and coarse (2.5-10 microm)-mode particles were studied at four different retirement communities in southern California between 2005 and 2007. Linear mixed-effects models and Spearman's correlation coefficients were then used to elucidate the relationships among size-segregated particulate matter (PM) levels, their particle components, and gaseous co-pollutants. Seasonal and spatial differences in the concentrations of all measured species were evaluated at all sites on the basis of P values for product terms. Outdoor quasi-ultrafine (UF) and, to a lesser extent, accumulation-mode particles were the two fractions that best correlated with outdoor concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), nitrogen oxides (NOx; during both phases of the study), and ozone (O3; only during the warmer months). Outdoor and indoor concentrations of CO, NO2, and NOx were more positively correlated to personal quasi-UF particles than larger size fractions. Despite these findings, it seems unlikely that these gaseous co-pollutants could confound epidemiologic associations between quasi-UF particles and adverse health effects. Overall, measured gaseous co-pollutants were weak surrogates of personal exposure to accumulation-mode PM, at least for subjects with similar exposure profiles and living in similar urban locations. Indoor sources were not significant contributors to personal exposure of accumulation and quasi-UF PM, which is predominantly influenced by primary emitted pollutants of outdoor origin. Correlations between personal coarse-mode PM and both outdoor and indoor gaseous co-pollutant concentrations were weak at all sites and during all seasons.

Physicochemical and toxicological profiles of particulate matter in Los Angeles during the October 2007 southern California wildfires.

To characterize the impact of the October 2007 wildfires on the air quality of Los Angeles, integrated ambient particulate matter (PM) samples were collected near the University of Southern California between October 24 and November 14, 2007. Samples were analyzed for different chemical species (i.e.,water-soluble organic carbon, water-soluble elements, and several organic compounds), and the redox activity of PM was evaluated using two different assays: the dithiothreitol (DTT) and macrophage reactive oxygen species (ROS) assays. Tracers of biomass burning such as potassium and levoglucosan were elevated by 2-fold during the fire period (October 24-28), compared to the postfire period (November 1-14). Water-soluble organic carbon (WSOC) concentrations were also higher during the fire event (170 and 78 microg/mg of PM, during fire and postfire, respectively). While the DTT activity (on a per PM mass basis) increased for samples collected during the fire event (0.024 nmol DTT/min x microg on October 24) compared to the postfire samples (0.005 nmol DTT/min x microg on November 14), the ROS activity appears to be unaffected by the wildfires, probably because these two assays are driven by different PM species. While the DTT assay reflected the redox potential of polar organic compounds, which are abundant in wood-smoke, the ROS assay was mainly influenced by transition metals (e.g., Fe, Cu, Cr, Zn, Ni, and V), emitted mostly by vehicular traffic and other combustion sources, but not by the wildfires.

Circulating biomarkers of inflammation, antioxidant activity, and platelet activation are associated with primary combustion aerosols in subjects with coronary artery disease.

BACKGROUND: Biomarkers of systemic inflammation have been associated with risk of cardiovascular morbidity and mortality. OBJECTIVES: We aimed to clarify associations of particulate matter (PM) air pollution with systemic inflammation using models based on size-fractionated PM mass and markers of primary and secondary aerosols. METHODS: We followed a panel of 29 nonsmoking elderly subjects with a history of coronary artery disease (CAD) living in retirement communities in the Los Angeles, California, air basin. Blood plasma biomarkers were measured weekly over 12 weeks and included C-reactive protein (CRP), fibrinogen, tumor necrosis factor-alpha (TNF-alpha) and its soluble receptor-II (sTNF-RII), interleukin-6 (IL-6) and its soluble receptor (IL-6sR), fibrin D-dimer, soluble platelet selectin (sP-selectin), soluble vascular cell adhesion molecule-1 (sVCAM-1), intracellular adhesion molecule-1 (sICAM-1), and myeloperoxidase (MPO). To assess changes in antioxidant capacity, we assayed erythrocyte lysates for glutathione peroxidase-1 (GPx-1) and copper-zinc superoxide dismutase (Cu,Zn-SOD) activities. We measured indoor and outdoor home daily size-fractionated PM mass, and hourly pollutant gases, total particle number (PN), fine PM elemental carbon (EC) and organic carbon (OC), estimated secondary organic aerosol (SOA) and primary OC (OCpri) from total OC, and black carbon (BC). We analyzed data with mixed models controlling for temperature and excluding weeks with infections. RESULTS: We found significant positive associations for CRP, IL-6, sTNF-RII, and sP-selectin with outdoor and/or indoor concentrations of quasi-ultrafine PM < or = 0.25 microm in diameter, EC, OCpri, BC, PN, carbon monoxide, and nitrogen dioxide from the current-day and multiday averages. We found consistent positive but largely nonsignificant coefficients for TNF-alpha, sVCAM-1, and sICAM-1, but not fibrinogen, IL-6sR, or D-dimer. We found inverse associations for erythrocyte Cu,Zn-SOD with these pollutants and other PM size fractions (0.25-2.5 and 2.5-10 microm). Inverse associations of GPx-1 and MPO with pollutants were largely nonsignificant. Indoor associations were often stronger for estimated indoor EC, OCpri, and PN of outdoor origin than for uncharacterized indoor measurements. There was no evidence for positive associations with SOA. CONCLUSIONS: Results suggest that traffic emission sources of OCpri and quasi-ultrafine particles lead to increased systemic inflammation and platelet activation and decreased antioxidant enzyme activity in elderly people with CAD.

How does infiltration behavior modify the composition of ambient PM2.5 in indoor spaces? An analysis of RIOPA data.

The indoor environment is an important venue for exposure to fine particulate matter (PM2.5) of ambient (outdoor) origin. In this work, paired indoor and outdoor PM2.5 species concentrations from three geographically distinct cities (Houston, TX, Los Angeles County, CA, and Elizabeth, NJ) were analyzed using positive matrix factorization (PMF) and demonstrate that the composition and source contributions of ambient PM2.5 are substantially modified by outdoor-to-indoor transport. Our results suggest that predictions of "indoor PM2.5 of ambient origin" are improved when ambient PM2.5 is treated as a combination of four distinct particle types with differing infiltration behavior (primary combustion, secondary sulfate and organics, secondary nitrate, and mechanically generated PM) rather than as a "single internally mixed entity". Study-wide average infiltration factors (i.e., fraction of ambient PM2.5 found indoors) for Relationship of Indoor, Outdoor, and Personal Air (RIOPA) study homes were 0.51, 0.78, and 0.04 (consistent with P = 0.6, 0.9, and 0.09; k = 0.2, 0.1, and 0.6 h(-1)) for PM2.5 associated with primary combustion, secondary formation (excluding nitrate), and mechanical generation, respectively. Modification of the composition, properties, and source contributions of ambient PM2.5 in indoor environments has important implications for exposure mitigation strategies, development of health hypotheses, and evaluation of exposure error in epidemiological studies that use ambient central-site PM2.5 as a surrogate for PM2.5 exposure.