Understanding the sources and composition of the incremental excess of fine particles across multiple sampling locations in one air shed

Well-designed health studies and the development of effective regulatory policies need to rely on an understanding of the incremental differences in particulate matter concentrations and their sources. Although only a limited number of studies have been conducted to examine spatial differences in sources to particulate matter within an air shed, routine monitoring data can be used to better understand these differences. Measurements from the US EPA Chemical Speciation Network （CSN） collected between 2002-2008 were analyzed to demonstrate the utility of regulatory data across three sites located within 100 km of each other. Trends in concentrations, source contribution, and incremental excesses across three sites were investigated using the Positive Matrix Factorization model. Similar yearly trends in chemical composition were observed across all sites, however, excesses of organic matter and elemental carbon were observed in the urban center that originated from local emissions of mobile sources and biomass buming. Secondary sulfate and secondary nitrate constituted over half of the PM2.5 with no spatial differences observed across sites. For these components, the excess of emissions from industrial sources could be directly quantified. This study demonstrates that CSN data from multiple sites can be successfully used to derive consistent source profiles and source contributions for regional pollution, and that CSN data can be used to quantify incremental differences in source contributions of across these sites. The analysis strategy can be used in other regions of the world to take advantage of existing ambient particulate matter monitoring data to better the understanding of spatial differences in source contributions within a given air shed.     

Chemical speciation of PM emissions from heavy-duty diesel vehicles equipped with diesel particulate filter (DPF) and selective catalytic reduction (SCR) retrofits

Four heavy-duty diesel vehicles (HDDVs) in six retrofitted configurations (CRT^®, V-SCRT^®, Z-SCRT^®, Horizon, DPX and CCRT^®) and a baseline vehicle operating without after--treatment were tested under cruise (50 mph), transient UDDS and idle driving modes. As a continuation of the work by Biswas et al. [Biswas, S., Hu, S., Verma, V., Herner, J., Robertson, W.J., Ayala, A., Sioutas, C., 2008. Physical properties of particulate matter (PM) from late model heavy-duty diesel vehicles operating with advanced emission control technologies. Atmospheric Environment 42, 5622–5634.] on particle physical parameters, this paper focuses on PM chemical characteristics (Total carbon [TC], Elemental carbon [EC], Organic Carbon [OC], ions and water-soluble organic carbon [WSOC]) for cruise and UDDS cycles only. Size-resolved PM collected by MOUDI–Nano-MOUDI was analyzed for TC, EC and OC and ions (such as sulfate, nitrate, ammonium, potassium, sodium and phosphate), while Teflon coated glass fiber filters from a high volume sampler were extracted to determine WSOC. The introduction of retrofits reduced PM mass emissions over 90% in cruise and 95% in UDDS. Similarly, significant reductions in the emission of major chemical constituents (TC, OC and EC) were achieved. Sulfate dominated PM composition in vehicle configurations (V-SCRT^®-UDDS, Z-SCRT^®-Cruise, CRT^® and DPX) with considerable nucleation mode and TC was predominant for configurations with less (Z-SCRT^®-UDDS) or insignificant (CCRT^®, Horizon) nucleation. The transient operation increases EC emissions, consistent with its higher accumulation PM mode content. In general, solubility of organic carbon is higher (average ～5 times) for retrofitted vehicles than the baseline vehicle. The retrofitted vehicles with catalyzed filters (DPX, CCRT^®) had decreased OC solubility (WSOC/OC: 8–25%) unlike those with uncatalyzed filters (SCRT^®s, Horizon; WSOC/OC ～ 60–100%). Ammonium was present predominantly in the nucleation mode, indicating that ternary nucleation may be the responsible mechanism for formation of these particles.     

Source identification of personal exposure to fine particulate matter using organic tracers

Personal exposure to fine particulate matter (PM2.5) is due to both indoor and outdoor sources. Contributions of sources to personal exposure can be quite different from those observed at ambient sampling locations. The primary goal of this study was to investigate the effectiveness of using trace organic speciation data to help identify sources influencing PM2.5 exposure concentrations. Sixty-four 24-h PM2.5 samples were obtained on seven different subjects in and around Boulder, CO. The exposure samples were analyzed for PM2.5 mass, elemental and organic carbon, organic tracer compounds, water-soluble metals, ammonia, and nitrate. This study is the first to measure a broad distribution of organic tracer compounds in PM2.5 personal samples. PM2.5 mass exposure concentrations averaged 8.4 μg m^?3. Organic carbon was the dominant constituent of the PM2.5 mass. Forty-four organic species and 19 water-soluble metals were quantifiable in more than half of the samples. Fifty-four organic species and 16 water-soluble metals had measurement signal-to-noise ratios larger than two after blank subtraction.The dataset was analyzed by Principal Component Analysis (PCA) to determine the factors that account for the greatest variance. Eight significant factors were identified; each factor was matched to its likely source based primarily on the marker species that loaded the factor. The results were consistent with the expectation that multiple marker species for the same source loaded the same factor. Meat cooking was an important source of variability. The factor that represents meat cooking was highly correlated with organic carbon concentrations (r = 0.84). The correlation between ambient PM2.5 and PM2.5 exposure was relatively weak (r = 0.15). Time participants spent performing various activities was generally not well correlated with PCA factor scores, likely because activity duration does not measure emissions intensity. The PCA results demonstrate that organic tracers can aid in identifying factors that influence personal exposures to PM2.5.     

Determining the agricultural ammonia immission using bark bio-monitoring: comparison with passive sampler measurements

Bark samples of spruce, pine and oak trees were collected at two sites in southern Bavaria which are characterized by high agricultural ammonia emissions. The samples were taken using a recently developed bark sampling device which removes a defined layer of the bark. The bark was then analysed for ammonium concentration in order to reflect the environmental ammonia immission. The measured bark concentrations decreased with rising distance between the sample trees and the ammonia source. This applied (i) to measurements inside a closed forest stand ranging from forest edge with high immission to forest interior with much lower immission, and (ii) to the open field where single-standing trees were sampled. Comparing the ammonium concentrations among the three different tree species revealed significant correlations. Thus, it could be shown that old spruce trees are as usable for bark bio-monitoring as the traditionally used pine and oak trees. The ammonium concentrations of the bark were significantly correlated to measurements taken by ammonia passive samplers at the same locations. These results indicate that bark samples may be used for a standardised monitoring of airborne ammonia load. A major advantage of the technique is the determination of the long-term accumulative ammonia load using a single measurement.