Daily trends and source apportionment of ultrafine particulate mass (PM0.1) over an annual cycle in a typical California city

Short-term exposure to reduced specific-size ambient particulate matter increase the risk of cause-specific cardiovascular disease: A national-wide evidence from hospital admissions

Evidence for the health effects of ambient PM1 (particulate matter with an aerodynamic diameter ≤ 1 µm) pollution is limited, and it remains unclear whether a smaller particulate matter has a greater impact on human health. We conducted a time-series study in 184 major cities by extracting daily hospital data on admissions for ischemic heart disease, heart failure, heart rhythm disturbances, and stroke between 2014 and 2017 from a medical insurance claims database of 0.28 billion beneficiaries. City-specific associations were estimated with over-dispersed generalized additive models. A random-effects meta-analysis was used to estimate regional and national average associations. We conducted stratified and meta-regression analyses to explore potential effect modifiers of the association. We recorded 8.83 million cardiovascular admissions during the study period. At the national-average level, a 10-μg/m3 increase in same-day PM1, PM2.5(particulate matter with an aerodynamic diameter ≤ 2.5 µm) and PM10(particulate matter with an aerodynamic diameter ≤ 10 µm) concentrations corresponded to a 1.14% (95% confidence interval 0.88-1.41%), 0.55% (0.40-0.70%), and 0.45% (0.36-0.55%) increase in cardiovascular admissions, respectively. PM1 exposure was also positively associated with all cardiovascular disease subtypes, including ischemic heart disease (1.28% change; 0.99-1.56%), heart failure (1.30% change; 0.70-1.91%), heart rhythm disturbances (1.11% change; 0.65-1.58%), and ischemic stroke (1.29% change; 0.88-1.71%). The associations between PM1 and cardiovascular admissions were stronger in cities with lower PM1 levels, higher air temperatures and relative humidity, as well as in subgroups with elder age (all P < 0.05). This study provides robust evidence of short-term associations between PM1 concentrations and increased hospital admissions for all major cardiovascular diseases in China. Our findings suggest a greater short-term impact on cardiovascular risk from PM1 in comparison to PM2.5 and PM10.

Comparison of size-resolved PM elements measured using aluminum foil and Teflon impaction substrates: Implications for ultrafine particle source apportionment and future sampling networks in California

Measurement networks for ultrafine particulate matter (PM_0.1) have been limited by the high costs for equipment, supplies, and labor associated with the need to collect PM_0.1 samples on multiple substrates for full chemical analysis. Here we explore whether a single cascade impactor loaded with aluminum foil substrates is sufficient for PM_0.1 source apportionment calculations in order to reduce those costs. An extraction method previously designed to measure elements on Teflon substrates was modified to accommodate features of aluminum foil substrates. Regression analysis between co-located aluminum foil and Teflon substrates in the particle diameter range 0.1-1.8 μm showed good agreement (R > 0.7) for 18 elements. Regression in the diameter range 0.1-0.18 μm (quasi-ultrafine particulate matter) was used to characterize the uncertainty introduced by the aluminum foil extraction method for the elements Li, K, V, Br, Rb, Mo, Cd, Sn, Sb, and Ba. This uncertainty was used to generate 30 simulated aluminum foil PM_0.1 datasets at each of three sites, followed by source apportionment analysis using Positive Matrix Factorization (PMF). At two of the three sites, the PM_0.1 source contributions calculated using aluminum foil substrates alone were almost identical to the PMF results from combined aluminum foil and Teflon substrates. The PM_0.1 source contributions calculated using aluminum foil substrates at the third site were closer to the results from a previous Chemical Mass Balance (CMB) study than to the PMF results from the combined aluminum foil and Teflon substrates, possibly because the CMB study also relied exclusively on samples collected using aluminum foil substrates. The success of the PM_0.1 source apportionment approach using aluminum foil substrates in a single cascade impactor provides a viable method for reducing costs in PM_0.1 sampling networks by 40-47%. Similar results may be achievable at locations outside of California.

Predicting intraurban airborne PM1.0-trace elements in a port city: Land use regression by ordinary least squares and a machine learning algorithm

Airborne particulate matter (PM) has been associated with cardiovascular and respiratory morbidity and mortality, and there is some evidence that spatially varying metals found in PM may contribute to adverse health effects. We developed spatially refined models for PM trace elements using ordinary least squares land use regression (OLS-LUR) and machine leaning random forest land-use regression (RF-LUR). Two-week integrated measurements of PM_1.0 (median aerodiameter < 1.0 μm) were collected at 50 sampling sites during fall (2010), winter (2011), and summer (2011) in the Halifax Regional Municipality, Nova Scotia, Canada. PM_1.0 filters were analyzed for metals and trace elements using inductively coupled plasma-mass spectrometry. OLS- and RF-LUR models were developed for approximately 30 PM_1.0 trace elements in each season. Model predictors included industrial, commercial, and institutional/ government/ military land use, roadways, shipping, other transportation sources, and wind rose information. RF generated more accurate models than OLS for most trace elements based on 5-fold cross validation. On average, summer models had the highest cross validation R² (OLS-LUR = 0.40, RF-LUR = 0.46), while fall had the lowest (OLS-LUR = 0.27, RF-LUR = 0.31). Many OLS-LUR models displayed overprediction in the final exposure surface. In contrast, RF-LUR models did not exhibit overpredictions. Taking overpredictions and cross validation performances into account, OLS-LUR performed better than RF-LUR in roughly 20% of the seasonal trace element models. RF-LUR models provided more interpretable predictors in most cases. Seasonal predictors varied, likely due to differences in seasonal distribution of trace elements related to source activity, and meteorology.

Particle emissions from mobile sources: Discussion of ultrafine particle emissions and definition

There is no universally agreed upon definition for ultrafine particles (UFP). Commonly used definitions for UFP are either particle number below 100 nm or total particle number, but without an agreed upon lower cut point. For example, a lower cut point of 3 nm compared to 10 nm could result in a substantially higher count. Another definition for UFP is total particle mass but without a commonly agreed upon aerodynamic diameter upper cut point, e.g., below 100 nm, 200 nm, 300 nm, etc. Yet another definition is lung deposited surface area weighted by lung deposition fraction, found mainly in the particle mobility diameter range from 20 to 400 nm. It is clear from these definitions that there are inconsistencies in the way UFP is used and defined in the literature. Sometimes these metrics are well correlated, sometimes not. In this paper we suggest three exposure metrics: UFP-N, UFP-M, and UFP-S, that we believe will add clarity. These metrics represent total number, mass, and surface area below 500 nm, respectively. For surface area and mass, the 500 nm cut point can be either aerodynamic or mobility diameter depending upon measurement methodology. For all metrics, this cut point captures nearly all of the primary particle emissions from mobile sources. Furthermore, UFP-N would include a lower cut point of 3-6 nm and would not require an upper size cut point because there is very little particle number above 500 nm or even above 100 nm. Thus, our definition of UFP-N is consistent with the current definition of ultrafine number except for, importantly, the specification of a lower cut point. These exposure metrics can help facilitate consistency in the characterization of both short- and long-term UFP ambient exposures and associated health effects in epidemiological studies.

Evaluation of Fine and Ultrafine Particles Proportion in Airborne Dust in an Industrial Area

The health impacts of suspended particulate matter (SPM) are significantly associated with size-the smaller the aerosol particles, the stronger the biological effect. Quantitative evaluation of fine and ultrafine particles (FP and UFP) is, therefore, an integral part of ongoing epidemiological studies. The mass concentrations of SPM fractions (especially PM_2.5, PM_1.0, PM_0.25) were measured in an industrial area using cascade personal samplers and a gravimetric method, and their mass ratio was determined. The results of PM_2.5, PM_1.0 were also compared with the reference measurement at stationary stations. The mean ratios PM_2.5/SPM, PM_1.0/SPM, and PM_1.0/PM_2.5 were 0.76, 0.65, and 0.86, respectively. Surprisingly, a mass dominance of UFP with an aerodynamic diameter <0.25 μm (PM_0.25) was found with mean ratios of 0.43, 0.57, 0.67 in SPM, PM_2.5 and PM_1.0. The method used showed satisfactory agreement in comparison with reference measurements. The respirable fraction may consist predominantly of UFP. Despite the measures currently being taken to improve air quality, the most biologically efficient UFP can escape and remain in the air. UFP are currently determined primarily as particle number as opposed to the mass concentration used for conventional fractions. This complicates their mutual comparison and determination of individual fraction ratios.

Contribution of tailpipe and non-tailpipe traffic sources to quasi-ultrafine, fine and coarse particulate matter in southern California

Exposure to traffic-related air pollution (TRAP) in the near-roadway environment is associated with multiple adverse health effects. To characterize the relative contribution of tailpipe and non-tailpipe TRAP sources to particulate matter (PM) in the quasi-ultrafine (PM_0.2), fine (PM_2.5) and coarse (PM_2.5-10) size fractions and identify their spatial determinants in southern California (CA). Month-long integrated PM_0.2, PM_2.5 and PM_2.5-10 samples (n = 461, 265 and 298, respectively) were collected across cool and warm seasons in 8 southern CA communities (2008-9). Concentrations of PM mass, elements, carbons and major ions were obtained. Enrichment ratios (ER) in PM_0.2 and PM₁₀ relative to PM_2.5 were calculated for each element. The Positive Matrix Factorization model was used to resolve and estimate the relative contribution of TRAP sources to PM in three size fractions. Generalized additive models (GAMs) with bivariate loess smooths were used to understand the geographic variation of TRAP sources and identify their spatial determinants. EC, OC, and B had the highest median ER in PM_0.2 relative to PM_2.5. Six, seven and five sources (with characteristic species) were resolved in PM_0.2, PM_2.5 and PM_2.5-10, respectively. Combined tailpipe and non-tailpipe traffic sources contributed 66%, 32% and 18% of PM_0.2, PM_2.5 and PM_2.5-10 mass, respectively. Tailpipe traffic emissions (EC, OC, B) were the largest contributor to PM_0.2 mass (58%). Distinct gasoline and diesel tailpipe traffic sources were resolved in PM_2.5. Others included fuel oil, biomass burning, secondary inorganic aerosol, sea salt, and crustal/soil. CALINE4 dispersion model nitrogen oxides, trucks and intersections were most correlated with TRAP sources. The influence of smaller roadways and intersections became more apparent once Long Beach was excluded. Non-tailpipe emissions constituted ~8%, 11% and 18% of PM_0.2, PM_2.5 and PM_2.5-10, respectively, with important exposure and health implications. Future efforts should consider non-linear relationships amongst predictors when modeling exposures. Implications: Vehicle emissions result in a complex mix of air pollutants with both tailpipe and non-tailpipe components. As mobile source regulations lead to decreased tailpipe emissions, the relative contribution of non-tailpipe traffic emissions to near-roadway exposures is increasing. This study documents the presence of non-tailpipe abrasive vehicular emissions (AVE) from brake and tire wear, catalyst degradation and resuspended road dust in the quasi-ultrafine (PM_0.2), fine and coarse particulate matter size fractions, with contributions reaching up to 30% in PM_0.2 in some southern California communities. These findings have important exposure and policy implications given the high metal content of AVE and the efficiency of PM_0.2 at reaching the alveolar region of the lungs and other organ systems once inhaled. This work also highlights important considerations for building models that can accurately predict tailpipe and non-tailpipe exposures for population health studies.

Chemical characterization and source apportionment of ambient nanoparticles: a case study in Hanoi, Vietnam

PM_0.1 has been believed to have adverse short- and long-term effects on human health. However, the information of PM_0.1 that is needed to fully evaluate its influence on human health and environment is still scarce in many developing countries. This is a comprehensive study on the levels, chemical compositions, and source apportionment of PM_0.1 conducted in Hanoi, Vietnam. Twenty-four-hour samples of PM_0.1 were collected during the dry season (November to December 2015) at a mixed site to get the information on mass concentrations and chemical compositions. Multiple linear regression analysis was utilized to investigate the simultaneous influence of meteorological factors on fluctuations in the daily levels of PM_0.1. Multiple linear regression models could explain about 50% of the variations of PM_0.1 concentrations, in which wind speed is the most important variable. The average concentrations of organic carbon (OC), elemental carbon (EC), water-soluble ions (Ca²⁺, K⁺, Mg²⁺, Na⁺, NH₄⁺, Cl^-, NO₃^-, SO₄^2-, C₂O₄^2-), and elements (Be, Al, V, Cr, Mn, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Sb, Ba, Tl, Pb, Na, Fe, Mg, K, and Ca) were 2.77 ± 0.90 μg m^-3, 0.63 ± 0.28 μg m^-3, 0.88 ± 0.39 μg m^-3, and 0.05 ± 0.02 μg m^-3, accounting for 51.23 ± 9.32%, 11.22 ± 2.10%, 16.28 ± 2.67%, and 1.11 ± 0.94%, respectively. A positive matrix factorization model revealed the contributions of five major sources to the PM_0.1 mass including traffic (gasoline and diesel emissions, 46.28%), secondary emissions (31.18%), resident/commerce (12.23%), industry (6.05%), and road/construction (2.92%).

Positive matrix factorization of ultrafine particle mass (PM0.1) at three sites in California

Ultrafine particles (UFPs) are an emerging air quality concern because of their enhanced toxicity compared to larger airborne particles. This study aims to better understand source contributions to UFP mass (PM_0.1) at multiples sites across California. Three-day average samples of PM_0.1 collected over a full year at San Pablo, East Oakland, and Los Angeles were analyzed using Positive Matrix Factorization (PMF). Seven PM_0.1 source-factors were identified at all locations: Factor1- Gasoline+Motor Oil+Meat Cooking+Natural Gas+SOA (31-53% PM_0.1 mass), Factor 2- Diesel+Motor Oil (25-45% PM_0.1 mass), Factor 3-Wood Burning (6-12% PM_0.1 mass), Factor 4-Shipping and other heavy fuel oil combustion (2-3% PM_0.1 mass), Factor 5-Sea Spray (4-8% PM_0.1 mass), Factor 6-Sb Brake Wear (1-3% PM_0.1 mass) and Factor 7-Sn - Unknown (1-7% PM_0.1 mass). PM_0.1 wood burning contributions were highest in the winter season when residential wood combustion was active. The monthly-averaged PM_0.1 source apportionment results calculated by PMF are consistent with the PM_0.1 source apportionment results calculated using Chemical Mass Balance (CMB) from the same sampling campaign. PMF distinguished Diesel+Motor Oil from Gasoline+Motor Oil+Meat Cooking+Natural Gas+SOA based on the species EC3 (a sub-fraction of elemental carbon that is volatilized and oxidized at temperatures between 700 and 775 °C), but PMF failed to further resolve the major sources of PM_0.1 OC because unique tracers were not measured. PMF resolved "Shipping and other heavy fuel oil combustion" and Sea Spray sources based on inorganic tracers V and Br. The PMF factor rich in Sb very likely comes from brake wear associated with on-road vehicles and railway operations. The undefined Sn factor may be indicative of local industrial sources and traffic emission, but further research will be required to confirm this hypothesis. The PM_0.1 source apportionment results contained in the current study further characterize the seasonal and spatial patterns of UFP concentrations in California.

Ultrafine Particles from Residential Biomass Combustion: A Review on Experimental Data and Toxicological Response

Biomass burning is considered an important source of indoor and outdoor air pollutants worldwide. Due to competitive costs and climate change sustainability compared to fossil fuels, biomass combustion for residential heating is increasing and expected to become the major source of primary particulate matter emission over the next 5-15 years. The understanding of health effects and measures necessary to reduce biomass emissions of harmful compounds is mandatory to protect public health. The intent of this review is to report available data on ultrafine particles (UFPs, i.e., particles with diameter smaller than 100 nm) emitted by residential biomass combustion and their effects on human health (in vitro and in vivo studies). Indeed, as far as we know, papers focusing specifically on UFPs originating from residential biomass combustion and their impact on human health are still lacking.

Seasonal and Annual Source Appointment of Carbonaceous Ultrafine Particulate Matter (PM0.1) in Polluted California Cities

Samples of ultrafine particle matter mass (PM_0.1) were collected over 12 months at three cities in California: Los Angeles, East Oakland, San Pablo, and over six months at Fresno. Molecular markers adjusted for volatility and reactivity were used to calculate PM_0.1 source contributions. Wood burning was a significant source of PM_0.1 organic carbon (OC) during the winter months in northern California (17-47%) but made smaller contributions in other months (0-8%) and was minor in all seasons in Los Angeles (0-5%), except December (17%) during holiday celebrations. Meat cooking was the largest source of PM_0.1 OC across all sites (13-29%), followed by gasoline combustion (7-21%). Motor oil and diesel fuel combustion made smaller contributions to PM_0.1 OC (3-10% and 3-7%, respectively). Unresolved sources accounted for 22-56% of the PM_0.1 OC. The lack of a clear seasonal profile for this unresolved OC suggests that it may be a primary source rather than secondary organic aerosol (SOA). PM_0.1 elemental carbon (EC) was dominated by diesel fuel combustion with less than 15% contribution from other sources. All sources besides wood smoke exhibited relatively constant seasonal source contributions to PM_0.1 OC reflecting approximately constant emissions over the annual cycle. Annual-average source contributions to PM_0.1 OC calculated with traditional molecular markers were similar to the source contributions calculated with the modified molecular markers that account for volatility and reactivity.

Insight into the critical factors determining the particle number concentrations during summer at a megacity in China

To identify the critical factors impacting the number concentration of particles with the aerodynamic diameters less than 2.5μm (PNC_2.5), the continuous measurement of PNC_2.5, chemical components in PM_2.5, gaseous pollutants and meteorological conditions were conducted at an urban site in Tianjin in June 2015. Results indicated that the average PNC_2.5 was 2839±2430 dN/dlogDp 1/cm³ during the campaign. Compared to other meteorological parameters, the relative humidity (RH) had the strongest relationship with PNC_2.5, with a Pearson's correlation coefficient of 0.53, and RH larger than 30% influenced strongly PNC_2.5. The important influence of secondary reactions on PNC_2.5 was inferred due to higher correlation coefficients between PNC_2.5 and SO₄^2-, NO₃^-, NH₄⁺ (r=0.78-0.89; p<0.01) and between PNC_2.5 and ratios that represent the conversion of nitrogen and sulfur oxides to particulate matter (r=0.42-0.49; p<0.01). Under specific RH conditions, there were even stronger correlations between PNC_2.5 and NO₃^-, SO₄^2-, NH₄⁺, while those between PNC_2.5 and EC, OC were relatively weak, especially when RH exceeded 50%. Principal component analysis (PCA) and Pearson's correlation analysis indicated that secondary sources, vehicle emission and coal combustion might be major contributors to PNC_2.5. Backward trajectory and potential source contribution function (PSCF) analysis suggested that the transport of air masses originated from these regions around Tianjin (Liaoning, Hebei, Shandong and Jiangsu) influenced critically PNC_2.5. The north of Jiangsu, the west of Shandong, and the east of Hebei were distinguished as major potential source-areas of PNC_2.5 by PSCF model.

Organic speciation of ambient quasi-ultrafine particulate matter (PM0.36) in Augsburg, Germany: Seasonal variability and source apportionment

To investigate the organic composition and their sources of very fine atmospheric particulate matter (PM), size-segregated PM was sampled using rotating drum impactor (RDI) in series with a sequential filter sampler in Augsburg, Germany, from April 2014 to February 2015. Organic speciation analysis and organic carbon/elemental carbon (OC/EC) analysis was performed for the smallest size fraction PM_0.36 (PM<360nm). Different OC fractions were determined by thermal optical EC/OC analyzer, and OC2, OC3 and OC4 refer to OC fractions that were derived at 280, 480 and 580°C, respectively. Positive matrix factorization (PMF) analysis was applied for source apportionment study. PMF resolved 5 sources including biogenic dominated secondary organic aerosol (bioSOA), isoprene dominated SOA (isoSOA), traffic, biomass burning (BB) and biomass burning originated SOA (bbSOA). On annual average, PMF results indicate the largest contribution of biogenic originated SOA (bioSOA plus isoSOA) to OC, followed by traffic and then BB related sources (BB plus bbSOA). Traffic was found to be associated with the smallest particles; whereas bioSOA and BB are associated with larger particles. Secondary organic marker compounds from biogenic precursors, OC2, OC3 and bioSOA, isoSOA source factors show summer maximum. Polycyclic aromatic hydrocarbons (PAHs), biomass burning markers, OC4 and BB, bbSOA source factors show winter maximum. Hopanes and the traffic source factor show little seasonal variation. Summer peaks of OC3 and OC2 are well modeled by PMF and are attributed mainly to biogenic SOA. OC4 was generally poorly modeled due to lack of characteristic low volatile markers. Summer maxima of biogenic SOA related compounds and source factors are positively correlated with temperature, global radiation, O₃ concentration and mixing layer height (MLH). Winter maxima of BB related compounds and source factors are negatively correlated with temperature and MLH; whereas positively correlated with NO₂ level.

Inhalation exposure to three-dimensional printer emissions stimulates acute hypertension and microvascular dysfunction

Fused deposition modeling (FDM™), or three-dimensional (3D) printing has become routine in industrial, occupational and domestic environments. We have recently reported that 3D printing emissions (3DPE) are complex mixtures, with a large ultrafine particulate matter component. Additionally, we and others have reported that inhalation of xenobiotic particles in this size range is associated with an array of cardiovascular dysfunctions. Sprague-Dawley rats were exposed to 3DPE aerosols via nose-only exposure for ~3h. Twenty-four hours later, intravital microscopy was performed to assess microvascular function in the spinotrapezius muscle. Endothelium-dependent and -independent arteriolar dilation were stimulated by local microiontophoresis of acetylcholine (ACh) and sodium nitroprusside (SNP). At the time of experiments, animals exposed to 3DPE inhalation presented with a mean arterial pressure of 125±4mmHg, and this was significantly higher than that for the sham-control group (94±3mmHg). Consistent with this pressor response in the 3DPE group, was an elevation of ~12% in resting arteriolar tone. Endothelium-dependent arteriolar dilation was significantly impaired after 3DPE inhalation across all iontophoretic ejection currents (0-27±15%, compared to sham-control: 15-120±21%). Endothelium-independent dilation was not affected by 3DPE inhalation. These alterations in peripheral microvascular resistance and reactivity are consistent with elevations in arterial pressure that follow 3DPE inhalation. Future studies must identify the specific toxicants generated by FDM™ that drive this acute pressor response.

Nanometer-sized emissions from municipal waste incinerators: A qualitative risk assessment

Municipal waste incinerators (MWI) are beneficial alternatives to landfills for waste management. A recent constituent of concern in emissions from these facilities is incidental nanometer-sized particles (INP_MWI), i.e., particles smaller than 1 micrometer in size that may deposit in the deepest parts of the lungs, cross into the bloodstream, and affect different regions of the body. With limited data, the public may fear INP_MWI due to uncertainty, which may affect public acceptance, regulatory permitting, and the increased lowering of air quality standards. Despite limited data, a qualitative risk assessment paradigm can be applied to determine the relative risk due to INP_MWI emissions. This review compiles existing data on nanometer-sized particle generation by MWIs, emissions control technologies used at MWIs, emission releases into the atmosphere, human population exposure, and adverse health effects of nanometer-sized particles to generate a qualitative risk assessment and identify data gaps. The qualitative risk assessment conservatively concludes that INP_MWI pose a low to moderate risk to individuals, primarily due to the lack of relevant toxicological data on INP_MWI mixtures in ambient particulate matter.

Association of urban particle numbers and sources with lung function among children with asthma or allergies

Previous studies have reported sources of particle number pollution in urban air, but have not evaluated relationships between respiratory health and these sources. We compared, among children with asthma or allergies, the associations of spirometric lung functions with increased exposure to source-specific versus size-segregated particle number concentrations (PNC). Hourly measurements of PNC were acquired from the aerosol Supersite in New Taipei, Taiwan. Spirometry (FVC, FEV1, and FEF) was recorded monthly for 59 children with asthma or allergies at five schools during 2007-2008. After co-pollutant adjustment for ozone, we found a 0.21 and 0.17 L decrease in FVC [95% confidence interval (CI): -0.35, -0.06 L] and FEV1 (95% CI: -0.32, -0.03 L), respectively, with an interquartile range increase (1879.7#/cm(3)) in secondary aerosol contribution observed on the previous day. In addition, we found no significant associations of FVC with accumulation mode (0.1 μm<aerodynamic diameter<2.5 μm) PNC. Our findings suggest that PNC of secondary origin is most responsible for pollution-related respiratory effects among children living in urban Taipei. Studies that rely on exposure to size-segregated PNC may underestimate PM health impacts.

Origin of high particle number concentrations reaching the St. Louis, Midwest Supersite

Ultrafine particles are associated with adverse health effects. Total Particle Number Concentration (TNC) of fine particles were measured during 2002 at the St. Louis - Midwest supersite. The time series showed overall low level with frequent large peaks. The time series was analyzed alongside criteria pollutant measurements and meteorological observations. Multiple regression analysis was used to identify further contributing factors and to determine the association of different pollutants with TNC levels. This showed the strong contribution of sulfur dioxide (SO2) and nitrogen oxides (NOx) to high TNC levels. The analysis also suggested that increased dispersion resulting from faster winds and higher mixing heights led to higher TNC levels. Overall, the results show that there were intense particle nucleation events in a SO2 rich plume reaching the site which contributed around 29% of TNC. A further 40% was associated with primary emissions from mobile sources. By separating the remaining TNC by time of day and clear sky conditions, we suggest that most likely 8% of TNC are due to regional nucleation events and 23% are associated with the general urban background.

Associations of mortality with long-term exposures to fine and ultrafine particles, species and sources: results from the California Teachers Study Cohort

BACKGROUND

Although several cohort studies report associations between chronic exposure to fine particles (PM2.5) and mortality, few have studied the effects of chronic exposure to ultrafine (UF) particles. In addition, few studies have estimated the effects of the constituents of either PM2.5 or UF particles.

METHODS

We used a statewide cohort of > 100,000 women from the California Teachers Study who were followed from 2001 through 2007. Exposure data at the residential level were provided by a chemical transport model that computed pollutant concentrations from > 900 sources in California. Besides particle mass, monthly concentrations of 11 species and 8 sources or primary particles were generated at 4-km grids. We used a Cox proportional hazards model to estimate the association between the pollutants and all-cause, cardiovascular, ischemic heart disease (IHD), and respiratory mortality.

RESULTS

We observed statistically significant (p < 0.05) associations of IHD with PM2.5 mass, nitrate, elemental carbon (EC), copper (Cu), and secondary organics and the sources gas- and diesel-fueled vehicles, meat cooking, and high-sulfur fuel combustion. The hazard ratio estimate of 1.19 (95% CI: 1.08, 1.31) for IHD in association with a 10-μg/m3 increase in PM2.5 is consistent with findings from the American Cancer Society cohort. We also observed significant positive associations between IHD and several UF components including EC, Cu, metals, and mobile sources.

CONCLUSIONS

Using an emissions-based model with a 4-km spatial scale, we observed significant positive associations between IHD mortality and both fine and ultrafine particle species and sources. Our results suggest that the exposure model effectively measured local exposures and facilitated the examination of the relative toxicity of particle species.

Predicting primary PM2.5 and PM0.1 trace composition for epidemiological studies in California

The University of California-Davis_Primary (UCD_P) chemical transport model was developed and applied to compute the primary airborne particulate matter (PM) trace chemical concentrations from ∼ 900 sources in California through a simulation of atmospheric emissions, transport, dry deposition and wet deposition for a 7-year period (2000-2006) with results saved at daily time resolution. A comprehensive comparison between monthly average model results and available measurements yielded Pearson correlation coefficients (R) ≥ 0.8 at ≥ 5 sites (out of a total of eight) for elemental carbon (EC) and nine trace elements: potassium, chromium, zinc, iron, titanium, arsenic, calcium, manganese, and strontium in the PM2.5 size fraction. Longer averaging time increased the overall R for PM2.5 EC from 0.89 (1 day) to 0.94 (1 month), and increased the number of species with strong correlations at individual sites. Predicted PM0.1 mass and PM0.1 EC exhibited excellent agreement with measurements (R = 0.92 and 0.94, respectively). The additional temporal and spatial information in the UCD_P model predictions produced population exposure estimates for PM2.5 and PM0.1 that differed from traditional exposure estimates based on information at monitoring locations in California Metropolitan Statistical Areas, with a maximum divergence of 58% at Bakersfield. The UCD_P model has the potential to improve exposure estimates in epidemiology studies of PM trace chemical components and health.