Assessment of Ambient Air Toxics and Wood Smoke Pollution among Communities in Sacramento County.

Ambient air monitoring and phone survey data were collected in three environmental justice (EJ) and three non-EJ communities in Sacramento County during winter 2016-2017 to understand the differences in air toxics and in wood smoke pollution among communities. Concentrations of six hazardous air pollutants (HAPs) and black carbon (BC) from fossil fuel (BCff) were significantly higher at EJ communities versus non-EJ communities. BC from wood burning (BCwb) was significantly higher at non-EJ communities. Correlation analysis indicated that the six HAPs were predominantly from fossil fuel combustion sources, not from wood burning. The HAPs were moderately variable across sites (coefficient of divergence (COD) range of 0.07 for carbon tetrachloride to 0.28 for m- and p-xylenes), while BCff and BCwb were highly variable (COD values of 0.46 and 0.50). The BCwb was well correlated with levoglucosan (R2 of 0.68 to 0.95), indicating that BCwb was a robust indicator for wood burning. At the two permanent monitoring sites, wood burning comprised 29-39% of the fine particulate matter (PM2.5) on nights when PM2.5 concentrations were forecasted to be high. Phone survey data were consistent with study measurements; the only significant difference in the survey results among communities were that non-EJ residents burn with indoor devices more often than EJ residents.

Measuring Spatial and Temporal PM2.5 Variations in Sacramento, California, Communities Using a Network of Low-Cost Sensors.

Low-cost sensors can provide insight on the spatio-temporal variability of air pollution, provided that sufficient efforts are made to ensure data quality. Here, 19 AirBeam particulate matter (PM) sensors were deployed from December 2016 to January 2017 to determine the spatial variability of PM2.5 in Sacramento, California. Prior to, and after, the study, the 19 sensors were deployed and collocated at a regulatory air monitoring site. The sensors demonstrated a high degree of precision during all collocated measurement periods (Pearson R2 = 0.98 - 0.99 across all sensors), with little drift. A sensor-specific correction factor was developed such that each sensor reported a comparable value. Sensors had a moderate degree of correlation with regulatory monitors during the study (R2 = 0.60 - 0.68 at two sites). In a multi-linear regression model, the deviation between sensor and reference measurements of PM2.5 had the highest correlation with dew point and relative humidity. Sensor measurements were used to estimate the PM2.5 spatial variability, finding an average pairwise coefficient of divergence of 0.22 and a range of 0.14 to 0.33, indicating mostly homogeneous distributions. No significant difference in the average sensor PM concentrations between environmental justice (EJ) and non-EJ communities (p value = 0.24) was observed.

Characterization of the chronic risk and hazard of hazardous air pollutants in the United States using ambient monitoring data.

BACKGROUND: Ambient measurements of hazardous air pollutants (air toxics) have been used to validate model-predicted concentrations of air toxics but have not been used to perform risk screening at the national level. OBJECTIVES: We used ambient concentrations of routinely measured air toxics to determine the relative importance of individual air toxics for chronic cancer and noncancer exposures. METHODS: We compiled 3-year averages for ambient measurement of air toxics collected at monitoring locations in the United States from 2003 through 2005. We then used national distributions of risk-weighted concentrations to identify the air toxics of most concern. RESULTS: Concentrations of benzene, carbon tetrachloride, arsenic, 1,3-butadiene, and acetaldehyde were above the 10(-6) cancer risk level at most sites nationally with a high degree of confidence. Concentrations of tetrachloroethylene, ethylene oxide, acrylonitrile, and 1,4-dichlorobenzene were also often greater than the 10(-6) cancer risk level, but we have less confidence in the estimated risk associated with these pollutants. Formaldehyde and chromium VI concentrations were either above or below the 10(-6) cancer risk level, depending on the choice of agency-recommended 10(-6) level. The method detection limits of eight additional pollutants were too high to rule out that concentrations were above the 10(-6) cancer risk level. Concentrations of 52 compounds compared with chronic noncancer benchmarks indicated that only acrolein concentrations were greater than the noncancer reference concentration at most monitoring sites. CONCLUSIONS: Most pollutants with national site-level averages greater than health benchmarks were also pollutants of concern identified in modeled national-scale risk assessments. Current monitoring networks need more sensitive ambient measurement techniques to better characterize the air toxics problem in the United States.

Source apportionment of fine particulate matter in Phoenix, AZ, using positive matrix factorization.

Speciated particulate matter (PM)2.5 data collected as part of the Interagency Monitoring of Protected Visual Environments (IMPROVE) program in Phoenix, AZ, from April 2001 through October 2003 were analyzed using the multivariate receptor model, positive matrix factorization (PMF). Over 250 samples and 24 species were used, including the organic carbon and elemental carbon analytical temperature fractions from the thermal optical reflectance method. A two-step approach was used. First, the species excluding the carbon fractions were used, and initially eight factors were identified; non-soil potassium was calculated and included to better refine the burning factor. Next, the mass associated with the burning factor was removed, and the data set rerun with the carbon fractions. Results were very similar (i.e., within a few percent), but this step enabled a separation of the mobile factor into gasoline and diesel vehicle emissions. The identified factors were burning (on average 2% of the mass), secondary transport (7%), regional power generation (13%), dust (25%), nitrate (9%), industrial As/Pb/Se (2%), Cu/Ni/V (7%), diesel (9%), and general mobile (26%). The overall contribution from mobile sources also increased, as some mass (OC and nitrate) from the nitrate and regional power generation factors were apportioned with the mobile factors. This approach allowed better apportionment of carbon as well as total mass. Additionally, the use of multiple supporting analyses, including air mass trajectories, activity trends, and emission inventory information, helped increase confidence in factor identification.

Analysis and apportionment of organic carbon and fine particulate matter sources at multiple sites in the midwestern United States.

Speciated fine particulate matter (PM2.5) data collected as part of the Speciation Trends Network at four sites in the Midwest (Detroit, MI; Cincinnati, OH; Indianapolis, IN; and Northbrook, IL) and as part of the Interagency Monitoring of Protected Visual Environments program at the rural Bondville, IL, site were analyzed to understand sources contributing to organic carbon (OC) and PM2.5 mass. Positive matrix factorization (PMF) was applied to available data collected from January 2002 through March 2005, and seven to nine factors were identified at each site. Common factors at all of the sites included mobile (gasoline)/secondary organic aerosols with high OC, diesel with a high elemental carbon/OC ratio (only at the urban sites), secondary sulfate, secondary nitrate, soil, and biomass burning. Identified industrial factors included copper smelting (Northbrook, Indianapolis, and Bondville), steel/manufacturing with iron (Northbrook), industrial zinc (Northbrook, Cincinnati, Indianapolis, and Detroit), metal plating with chromium and nickel (Detroit, Indianapolis, and Bondville), mixed industrial with copper and iron (Cincinnati), and limestone with calcium and iron (Bondville). PMF results, on average, accounted for 96% of the measured PM2.5 mass at each site; residuals were consistently within tolerance (+/-3), and goodness-of-fit (Q) was acceptable. Potential source contribution function analysis helped identify regional and local impacts of the identified source types. Secondary sulfate and soil factors showed regional characteristics at each site, whereas industrial sources typically appeared to be locally influenced. These regional factors contributed approximately one third of the total PM2.5 mass, on average, whereas local mobile and industrial sources contributed to the remaining mass. Mobile sources were a major contributor (55-76% at the urban sites) to OC mass, generally with at least twice as much mass from nondiesel sources as from diesel. Regional OC associated with secondary sulfate and soil was generally low.

Transport and dispersion during wintertime particulate matter episodes in the San Joaquin Valley, California.

Data analysis and modeling were performed to characterize the spatial and temporal variability of wintertime transport and dispersion processes and the impact of these processes on particulate matter (PM) concentrations in the California San Joaquin Valley (SJV). Radar wind profiler (RWP) and radio acoustic sounding system (RASS) data collected from 18 sites throughout Central California were used to estimate hourly mixing heights for a 3-month period and to create case studies of high-resolution diagnostic wind fields, which were used for trajectory and dispersion analyses. Data analyses show that PM episodes were characterized by an upper-level ridge of high pressure that generally produced light winds through the entire depth of the atmospheric boundary layer and low mixing heights compared with nonepisode days. Peak daytime mixing heights during episodes were -400 m above ground level (agl) compared with -800 m agl during nonepisodes. These episode/nonepisode differences were observed throughout the SJV. Dispersion modeling indicates that the range of influence of primary PM emitted in major population centers within the SJV ranged from -15 to 50 km. Trajectory analyses revealed that little intrabasin pollutant transport occurred among major population centers in the SJV; however, interbasin transport from the northern SJV and Sacramento regions into the San Francisco Bay Area (SFBA) was often observed. In addition, this analysis demonstrates the usefulness of integrating RWP/RASS measurements into data analyses and modeling to improve the understanding of meteorological processes that impact pollution, such as aloft transport and boundary layer evolution.

Background concentrations of 18 air toxics for North America.

The U.S. Clean Air Act identifies 188 hazardous air pollutants (HAPs), or "air toxics," associated with adverse human health effects. Of these air toxics, 18 were targeted as the most important in a 10-City Pilot Study conducted in 2001 and 2002 as part of the National Air Toxics Trend Sites Program. In the present analysis, measurements available from monitoring networks in North America were used to estimate boundary layer background concentrations and trends of these 18 HAPs. The background concentrations reported in this study are as much as 85% lower than those reported in recent studies of HAP concentrations. Background concentrations of some volatile organic compounds were analyzed for trends at the 95% confidence level; only carbon tetrachloride (CCI4) and tetrachloroethylene decreased significantly in recent years. Remote background concentrations were compared with the one-in-a-million (i.e., 10(6)) cancer benchmarks to determine the possible causes of health risk in rural and remote areas; benzene, chloroform, formaldehyde, and chromium (Cr) fine particulate were higher than cancer benchmark values. In addition, remote background concentrations were found to contribute between 5% and 99% of median urban concentrations.

Weekday versus weekend activity patterns for ozone precursor emissions in California's South Coast Air Basin.

Ambient O3 concentrations in California's South Coast Air Basin (SoCAB) can be as much as 55% higher on weekends than on weekdays under comparable meteorological conditions. This is paradoxical because emissions of O3 precursors (hydrocarbons, CO, and nitrogen oxides [NOx]) are lower on weekends. Day-of-week emissions activity data were collected and analyzed to investigate the hypothesized causes of the "weekend O3 effect." Emission activity data were collected for various mobile, area, and point sources throughout the SoCAB, including on-road vehicles, lawn and garden equipment, barbecues, fireplaces, solvent use, and point sources with continuous emission monitoring data. The results of this study indicate significant differences between weekday and weekend emission activity patterns and emissions. Their combined effect results in a 12-18% decrease in reactive organic gases (ROGs) and a 35-41% decrease in NOx emissions on Saturdays and Sundays, respectively, relative to weekdays in summer 2000. These changes in emissions result in an increase of more than 30% in the ROG/NOx ratio on weekends compared with weekdays, which, along with lower NOx emissions, leads to increased O3 production on weekends.