Spatial variability of carbonaceous aerosols and associated source tracers in two cites in the Midwestern United States

Semi-continuous and 24-h averaged measurements of fine carbonaceous aerosols were made concurrently at three sites within each of two U.S. Midwestern Cities; Detroit, Michigan and Cleveland, Ohio; during two, one-month intensive campaigns conducted in July of 2007 and January & February of 2008. A comparison of 24-h measurements revealed substantial intra-urban variability in carbonaceous aerosols consistent with the influence of local sources, and excesses in both PM_2.5 organic carbon (OC) and elemental carbon (EC) were identified at individual sites within each city. High time-resolved black carbon (BC) measurements indicated that elemental carbon concentrations were higher at sites adjacent to freeways and busy surface streets, and temporal patterns suggested that excess EC at sites adjacent to freeways was dominated by mobile source emissions while excesses in EC away from traffic corridors was dominated by point/area source emissions. The site-to-site variability in OC concentrations was approximately 7% within the neighborhood scale (0.5–4 km) and between 4 and 27% at the urban scale (4–100 km). In contrast, measurements of organic source tracers, in conjunction with a Chemical Mass Balance (CMB) source-apportionment model, indicated that the spatial variation in the contribution of both mobile and stationary sources to PM_2.5 OC often exceeded the variation in OC mass concentration by a factor of 3 or more. Markers for mobile sources, biomass smoke, natural gas, and coal combustion differed by as much as 60% within the neighborhood scale and by greater than 200% within the urban scale. The observations made during this study suggest that the urban excess of carbonaceous aerosols is much more complex than has been previously reported and that a more rigorous, source-oriented approach should be taken in order to assess the risk associated with exposure to carbonaceous aerosols within the industrialized environments of the Midwestern United States.     

The Need for Representative Ambient Air Carbon Monoxide Sampling

Recent investigations have indicated that ambient air CO measurements may not reflect population exposure to CO. The lack of correlation may be due to improper siting of CO instruments, improper interpretation of air quality data, or both. Studies of population carboxy-hemoglobin levels are evaluated and compared with ambient air data.,

No significant correlation was found between median population COHb levels and reductions in CO concentrations required to meet ambient air standards when calculations used to estimate reductions were based on the second highest 8 hour average. However, calculated reductions based on annual average concentrations and a trend analysis technique correlated significantly with COHb levels in five cities from which both CAMP and COHb data were available.

Studies to determine the nature of the relationship between ambient air CO concentrations and population COHb levels are needed. The differences between the Occupational Safety and Health Act Regulations and the National Ambient Air Standards for carbon monoxide should be scrutinized to determine if a redefinition of the standards or their applicability is warranted. A reevaluation of the controls necessary to make reductions in population COHb burden may be necessary.     

Real-world vehicle emissions: A summary of the 15th coordinating research council on-road vehicle emissions workshop

The Coordinating Research Council held its 15th workshop in April 2005, with nearly 90 presentations describing the most recent mobile source-related emissions research. In this paper, the authors summarize the presentations from researchers who are engaged in improving our understanding of the contribution of mobile sources to air quality. Participants in the workshop discussed emission models and emission inventories, results from gas- and particle-phase emissions studies from spark-ignition and diesel-powered vehicles (with an emphasis in this workshop on particle emissions), effects of fuels on emissions, evaluation of in-use emissions control programs, and efforts to improve our capabilities in performing on-board emissions measurements, as well as topics for future research.     

Organochlorine pesticides in soil under irrigated cotton farming systems in Vertisols of the Namoi Valley, north-western New South Wales, Australia

Organochlorine pesticides (OCPs) such as DDT and DDE have been detected in the surface 0.2 m of Vertisols in the lower Namoi Valley of north western New South Wales, Australia even though they have not been applied to crops since 1982. However, their presence in the deeper soil horizons has not been investigated. The objective of this study was to determine if OCPs were present to a depth of 1.2 m in Vertisols under irrigated cotton farming systems in the lower Namoi Valley of New South Wales. Soil was sampled from the 0-1.2 m depths in three sites, viz. the Australian Cotton Research Institute, ACRI, near Narrabri (149°36′E, 30°12′S), and two cotton farms near Wee Waa (149°27′E, 30°13′S) and Merah North (149°18′E, 30°12′S) in northern New South Wales, Australia. The OCPs detected and their metabolites were α-endosulfan, β-endosulfan, endosulfan sulphate, DDD, DDE, DDT and endrin. The metabolite DDE, a breakdown product of DDT, was the most persistent OCP in all depths analysed. Endosulfan sulphate was the second most persistent followed by endrin > α-endosulfan > β-endosulfan > DDT and DDD. DDT was sprayed extensively in the lower Namoi Valley up to the early 1980s and may explain the persistence of DDE in the majority of soil samples. Dicofol and Dieldrin, two OCPs previously undocumented in Vertisols were also detected. The movement of OCPs into the subsoil of Vertisols may occur when irrigation or rain transports soil colloids and organic matter via preferential flow systems into the deeper layers of a soil profile. Persistence of OCPs was closely correlated to soil organic carbon concentrations. The persistence in soil of OCP’s applied to cotton crops grown more than two decades ago suggests that they could enter the food chain. Their presence at depths of 1.2 m suggests that they could move into groundwater that may eventually be used for domestic and stock consumption.     

Comparing universal kriging and land-use regression for predicting concentrations of gaseous oxides of nitrogen (NOx) for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

BACKGROUND: Epidemiological studies that assess the health effects of long-term exposure to ambient air pollution are used to inform public policy. These studies rely on exposure models that use data collected from pollution monitoring sites to predict exposures at subject locations. Land use regression (LUR) and universal kriging (UK) have been suggested as potential prediction methods. We evaluate these approaches on a dataset including measurements from three seasons in Los Angeles, CA. METHODS: The measurements of gaseous oxides of nitrogen (NOx) used in this study are from a "snapshot" sampling campaign that is part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). The measurements in Los Angeles were collected during three two-week periods in the summer, autumn, and winter, each with about 150 sites. The design included clusters of monitors on either side of busy roads to capture near-field gradients of traffic-related pollution. LUR and UK prediction models were created using geographic information system (GIS)-based covariates. Selection of covariates was based on 10-fold cross-validated (CV) R(2) and root mean square error (RMSE). Since UK requires specialized software, a computationally simpler two-step procedure was also employed to approximate fitting the UK model using readily available regression and GIS software. RESULTS: UK models consistently performed as well as or better than the analogous LUR models. The best CV R(2) values for season-specific UK models predicting log(NOx) were 0.75, 0.72, and 0.74 (CV RMSE 0.20, 0.17, and 0.15) for summer, autumn, and winter, respectively. The best CV R(2) values for season-specific LUR models predicting log(NOx) were 0.74, 0.60, and 0.67 (CV RMSE 0.20, 0.20, and 0.17). The two-stage approximation to UK also performed better than LUR and nearly as well as the full UK model with CV R(2) values 0.75, 0.70, and 0.70 (CV RMSE 0.20, 0.17, and 0.17) for summer, autumn, and winter, respectively. CONCLUSION: High quality LUR and UK prediction models for NOx in Los Angeles were developed for the three seasons based on data collected for MESA Air. In our study, UK consistently outperformed LUR. Similarly, the 2-step approach was more effective than the LUR models, with performance equal to or slightly worse than UK.     

A comparison of X-ray fluorescence and wet chemical analysis of air filter samples from a scrap lead smelting operation

Personal and area air samples were taken at a scrap lead smelter operation in a bullet manufacturing facility. Samples were taken using the 37-mm styrene-acrylonitrile closed-face filter cassette (CFC, the current US standard device for lead sampling), the 37-mm GSP or "cone" sampler, the 25-mm Institute of Occupational Medicine (IOM) inhalable sampler, and the 25-mm Button sampler (developed at the University of Cincinnati). Polyvinylchloride filters were used for sampling. The filters were pre- and post-weighed, and analyzed for lead content using a field-portable X-ray fluorescence (XRF) analyzer. The filters were then extracted with dilute nitric acid in an ultrasonic extraction bath and the solutions were analyzed by inductively coupled plasma optical emission spectroscopy. The 25-mm filters were analyzed using a single XRF reading, while three readings on different parts of the filter were taken from the 37-mm filters. The single reading from the 25-mm filters was adjusted for the nominal area of the filter to obtain the mass loading, while the three readings from the 37-mm filters were inserted into two different algorithms for calculating the mass loadings, and the algorithms were compared. The IOM sampler was designed for material collected in the body of the sampler to be part of the collected sample as well as that on the filter. Therefore, the IOM sampler cassettes were rinsed separately to determine if wall-loss corrections were necessary. All four samplers gave very good correlations between the two analytical methods above the limit of detection of the XRF procedure. The limit of detection for the 25-mm filters (5 microg) was lower than for the 37-mm filters (10 microg). The percentage of XRF results that were within 25% of the corresponding ICP results was evaluated. In addition, the bias from linear regression was estimated. Linear regression for the Button sampler and the IOM sampler using single readings and the GSP using all tested techniques for total filter loading gave acceptable XRF readings at loadings equivalent to sampling at the OSHA 8-hour Action Level and Permissible Exposure Limit. However, the CFC only had acceptable results when the center reading corrected for filter area was used, which was surprising, and may be a result of a limited data set. In addition to linear regression, simple estimation of bias indicated reasonable agreements between XRF and ICP results for single XRF readings on the Button sampler filters, (82% of the individual results within criterion), and on the IOM sampler filters (77% or 61%--see text), and on the GSP sampler filters using the OSHA algorithm (78%). As a result of this pilot project, all three samplers were considered suitable for inclusion in further field research studies.     

Investigating toxic metal levels in popular edible fishes from the South Durban basin: implications for public health and food security

Contamination of the ocean by heavy metals may have ecosystem-wide implications because they are toxic even if present in trace levels, and the relative ease of their bioaccumulation by marine organisms may affect human health, primarily through consumption of contaminated fish. We evaluated metal concentrations in six different popular edible fish species and estimated the potential health risks from consumption of contaminated fish. There was no correlation between fish length and average metal accumulation although the fish species tended to accumulate significantly more Al and Zn (P?<?0.05) than any of the other metals. Significantly higher Mn concentrations were found in fish gills compared to other body parts in all fish species. Bronze seabream, Catface rockcod, and Slinger seabream had significantly higher mean Cr concentration in the liver than in either the tissues or gills. The highest concentration of Zn in fleshy tissue was in Horse mackerel (56.71 μg g^?1) followed by Bronze seabream (31.07 μg g^?1). Al levels ranged from 5.6 μg g^?1 in Atlantic mackerel to 35.04 μg g^?1 in Horse mackerel tissue while Cu and Cr concentrations were highest in the tissues of Horse mackerel (6.83 and 1.81 μg g^?1, respectively) followed by Santer seabream (3.15; 1.09 μg g^?1) and Bronze seabream (3.09; 1.30 μg g^?1), respectively. The highest tissue concentration of Mn was detected in Bronze seabream (8.23 μg g^?1) followed by Catface rockcod (6.05 μg g^?1) and Slinger seabream (5.21 μg g^?1) while Pb concentrations ranged from a high of 8.44 μg g^?1 in Horse mackerel to 1.09 μg g^?1 in Catface rockcod. However, the estimated potential health risks from fish consumption as determined by the target hazard quotient (THQ) and hazard index (HI) were significantly lower than 1, implying that metals were not present in sufficiently high quantities to be of any health and/or food and security concern in the studied fishes.     

Statistical analysis of aerosol species, trace gasses, and meteorology in Chicago

Both canonical correlation analysis (CCA) and principal component analysis (PCA) were applied to atmospheric aerosol and trace gas concentrations and meteorological data collected in Chicago during the summer months of 2002, 2003, and 2004. Concentrations of ammonium, calcium, nitrate, sulfate, and oxalate particulate matter, as well as, meteorological parameters temperature, wind speed, wind direction, and humidity were subjected to CCA and PCA. Ozone and nitrogen oxide mixing ratios were also included in the data set. The purpose of statistical analysis was to determine the extent of existing linear relationship(s), or lack thereof, between meteorological parameters and pollutant concentrations in addition to reducing dimensionality of the original data to determine sources of pollutants. In CCA, the first three canonical variate pairs derived were statistically significant at the 0.05 level. Canonical correlation between the first canonical variate pair was 0.821, while correlations of the second and third canonical variate pairs were 0.562 and 0.461, respectively. The first canonical variate pair indicated that increasing temperatures resulted in high ozone mixing ratios, while the second canonical variate pair showed wind speed and humidity’s influence on local ammonium concentrations. No new information was uncovered in the third variate pair. Canonical loadings were also interpreted for information regarding relationships between data sets. Four principal components (PCs), expressing 77.0 % of original data variance, were derived in PCA. Interpretation of PCs suggested significant production and/or transport of secondary aerosols in the region (PC1). Furthermore, photochemical production of ozone and wind speed’s influence on pollutants were expressed (PC2) along with overall measure of local meteorology (PC3). In summary, CCA and PCA results combined were successful in uncovering linear relationships between meteorology and air pollutants in Chicago and aided in determining possible pollutant sources.