PM10 source apportionment in a Swiss Alpine valley impacted by highway traffic

Although trans-Alpine highway traffic exhaust is one of the major sources of air pollution along the highway valleys of the Alpine regions, little is known about its contribution to residential exposure and impact on respiratory health. In this paper, source-specific contributions to particulate matter with an aerodynamic diameter?<?10 μm (PM₁₀) and their spatio-temporal distribution were determined for later use in a pediatric asthma panel study in an Alpine village. PM₁₀ sources were identified by positive matrix factorization using chemical trace elements, elemental, and organic carbon from daily PM₁₀ filters collected between November 2007 and June 2009 at seven locations within the village. Of the nine sources identified, four were directly road traffic-related: traffic exhaust, road dust, tire and brake wear, and road salt contributing 16 %, 8 %, 1 %, and 2 % to annual PM₁₀ concentrations, respectively. They showed a clear dependence with distance to highway. Additional contributions were identified from secondary particles (27 %), biomass burning (18 %), railway (11 %), and mineral dust including a local construction site (13 %). Comparing these source contributions with known source-specific biomarkers (e.g., levoglucosan, nitro-polycyclic aromatic hydrocarbons) showed high agreement with biomass burning, moderate with secondary particles (in winter), and lowest agreement with traffic exhaust.     

Measurement of fine particulate matter nonvolatile and semi-volatile organic material with the Sunset Laboratory Carbon Aerosol Monitor

Semi-volatile organic material (SVOM) in fine particles is not reliably measured with conventional semicontinuous carbon monitors because SVOM is lost from the collection media during sample collection. We have modified a Sunset Laboratory Carbon Aerosol Monitor to allow for the determination of SVOM. In a conventional Sunset monitor, gas-phase organic compounds are removed in the sampled airstream by a diffusion denuder employing charcoal-impregnated cellulose filter (CIF) surfaces. Subsequently, particles are collected on a quartz filter and the instrument then determines both the organic carbon and elemental carbon fractions of the aerosol using a thermal/optical method. However, some of the SVOM is lost from the filter during collection, and therefore is not determined. Because the interfering gas-phase organic compounds are removed before aerosol collection, the SVOM can be determined by filtering the particles at the instrument inlet and then replacing the quartz filter in the monitor with a charcoal-impregnated glass fiber filter (CIG), which retains the SVOM lost from particles collected on the inlet filter. The resulting collected SVOM is then determined in the analysis step by measurement of the carbonaceous material thermally evolved from the CIG filter. This concept was tested during field studies in February 2003 in Lindon, UT, and in July 2003 in Rubidoux, CA. The results obtained were validated by comparison with Particle Concentrator-Brigham Young University Organic Sampling System (PC-BOSS) results. The sum of nonvolatile organic material determined with a conventional Sunset monitor and SVOM determined with the modified Sunset monitor agree with the PC-BOSS results. Linear regression analysis of total carbon concentrations determined by the PC-BOSS and the Sunset resulted in a zero-intercept slope of 0.99 +/- 0.02 (R2 = 0.92) and a precision of sigma = +/- 1.5 microg C/m3 (8%).     

Characterization of ambient fine particles in the northwestern area and Anchorage, Alaska

Ambient PM2.5 (particulate matter less than 2.5 microm in aerodynamic diameter) in the northwestern United States and Alaska is dominated by carbonaceous compounds associated with wood burning and transportation sources. PM2.5 source characterization studies analyzing recent PM2.5 speciation data have not been previously reported for these areas. In this study, ambient PM2.5 speciation samples collected at two monitoring sites located in the northwestern area, Olympic Peninsula, WA, and Portland, OR, and one monitoring site located in Anchorage, AK, were characterized through source apportionments. Gasoline vehicle, secondary sulfate, and wood smoke were the largest sources of PM2.5 collected at the Anchorage, Olympic, and Portland monitoring sites, respectively. Secondary sulfates showed an April peak at Anchorage and a November peak at Portland that are likely related to the increased photochemical reaction and long-range transport in Anchorage and meteorological stagnation in Portland. Secondary nitrate at the Olympic site showed a weak summer high peak that could be caused by seasonal tourism in the national park. Backward trajectories suggested that the elevated aged sea salt concentrations at the Portland monitoring site could be regional transport of sea salt that passed through other contaminated air sheds along the coast. Oil combustion emissions that might originate from ships and ferries were observed at the Olympic monitoring site.     

Sources of fine urban particulate matter in Detroit, MI

Data from the speciation trends network (STN) was used to evaluate the amount and temporal patterns of particulate matter originating from local industrial sources and long-range transport at two sites in Detroit, MI: Allen Park, MI, southwest of both Detroit and the areas of heavy industrial activity; Dearborn, MI, located on the south side of Detroit near the most heavily industrialized region. Using positive matrix factorization (PMF) and comparing source contributions at Allen Park to those in Dearborn, contributions made by local industrial sources (power plants, coke refineries, iron smelting, waste incineration), local area sources (automobile and diesel truck) and long range sources of PM(2.5) can be distinguished in greater Detroit. Overall, the mean mass concentration measured at Dearborn was 19% higher than that measured at Allen Park. The mass at Allen Park was apportioned as: secondary sulfate 31%, secondary nitrate 28%, soil 8%, mixed aged sea and road salts 4%, gasoline 15%, diesel 4%, and biomass burning 3%. At Dearborn the mass was apportioned as: secondary sulfate 25%, secondary nitrate 20%, soil 12%, mixed aged sea and road salts 4%, gasoline 20%, diesel 8%, iron and steel, 5%, and mixed industrial 7%. The impact of the iron and steel, soil, and mixed aged sea and road salt was much higher at the Dearborn site than at the Allen Park site, suggesting that close proximity to a local industrial complex has a direct negative impact on local air quality.     

A study on the potential sources of air pollutants observed at Tjörn,Sweden

The Potential Source Contribution Function (PSCF) receptor model combines both chemical and meteorological information. In this study, PSCF was employed to identify the potential source emission regions for aerosol compositions measured at Tjörn, Sweden (58.01 °N, 11.36 °E). PSCF was for the first time applied on a European scale. One hundred and fifty-two four-day air parcel backward trajectories were combined with concentrations of sixteen elements determined in 33 coarse and fine aerosol samples. The observations were made between February 17 and March 26, 1985. The modeling results of the heavy metals V, Pb, Zn, and As are presented and compared with available emission inventory data. A number of known industrialized regions in the former USSR and Europe are found of high potential to be the emission source areas. These areas are in good agreement with the known emission information. The PSCF maps of total sulfur, Non-Seasalt-Sulfur (N.S.S.) and chlorine are also presented. High potential regions in the Arctic area exist in the PSCF map for total sulfur wheres they do not occur in that for N.S.S.     

Application of Artificial Neural Networks to Modeling and Prediction of Ambient Ozone Concentrations

ABSTRACT

The deterministic modeling of ambient O₃ concentrations is difficult because of the complexity of the atmospheric system in terms of the number of chemical species; the availability of accurate, time-resolved emissions data; and the required rate constants. However, other complex systems have been successfully approximated using artificial neural networks (ANNs). In this paper, ANNs are used to model and predict ambient O₃ concentrations based on a limited number of measured hydrocarbon species, NO_x compounds, temperature, and radiant energy. In order to examine the utility of these approaches, data from the Coastal Oxidant Assessment for Southeast Texas (COAST) program in Houston, TX, have been used. In this study, 53 hydrocarbon compounds, along with O₃, nitrogen oxides, and meteorological data were continuously measured during summer 1993. Steady-state ANN models were developed to examine the ability of these models to predict current O₃ concentrations from measured VOC and NO concentrations. To predict the future concentrations of O₃, dynamic models were also explored and were used for extraction of chemical information such as reactivity estimations for the VOC species.

The steady-state model produced an approximation of O₃ data and demonstrated the functional relationship between O₃ and VOC-NO_x concentrations. The dynamic models were able to the adequately predict the O₃ concentration and behavior of VOC-NO_x-O₃ system a number of hourly intervals into the future. For 3 hr into the future, O₃ concentration could be predicted with a root-mean squared error (RMSE) of 8.21 ppb. Extending the models further in time led to an RMSE of 11.46 ppb for 5-hr-ahead values. This prediction capability could be useful in determining when control actions are needed to maintain measured concentrations within acceptable value ranges.     

Influence of atmospheric dispersion and new particle formation events on ambient particle number concentration in Rochester, United States, and Toronto, Canada

Continuous measurements of particle number concentrations were performed in Rochester, NY, and Toronto, Ontario, Canada during the 2003 calendar year. Strong seasonal dependency in particle number concentration was observed at two sites. The average number concentration of ambient particles was 9670 +/- 6960 cm(-3) in Rochester, whereas in Toronto the average number of particles was 28,010 +/- 13,350 cm(-3). The particle number concentrations were higher in winter months than in summer months by a factor of 1.5 in Rochester and 1.6 in Toronto. In general, there were also distinct diurnal variations of aerosol number concentration. The highest weekdays/weekends ratio of number concentration was typically observed during the rush-hour period in winter months with a ratio of 2.1 in Rochester and 2.0 in Toronto. The correlation in the total particle number concentrations between the two urban sites was stronger in winter because of the common urban traffic patterns, but weaker in summer because of local sulfur dioxide (SO2)-related particle formation events in Rochester in the summer. Strong morning particle formation events were frequently observed during colder winter months. Good correlations between particle number and carbon monoxide (CO) as well as temperature suggested that motorvehicle emissions lead to the formation of new particles as the exhaust mixes with the cold air. Regional nucleation and growth events frequently occurred in April. Local SO2-related particle formation events most frequently occurred in August. SO2 and UV-B were highly correlated with particle concentration, suggesting a high association of photochemical processes with these local events. A high directionality in a northerly direction was observed for particle number and SO2, indicating the influence of point sources located north of Rochester.     

Measurement of ultrafine particle size distributions from coal-, oil-, and gas-fired stationary combustion sources

Currently, we have limited knowledge of the physical and chemical properties of emitted primary combustion aerosols and the changes in those properties caused by nucleation, condensation growth of volatile species, and particle coagulations under dilution and cooling in the ambient air. A dilution chamber was deployed to sample exhaust from a pilot-scale furnace burning various fuels at a nominal heat input rate of 160 kW/h(-1) and 3% excess oxygen. The formation mechanisms of particles smaller than 420 nm in electrical mobility diameter were experimentally investigated by measurement with a Scanning Mobility Particle Sizer (SMPS) as a function of aging times, dilution air ratios, combustion exhaust temperatures, and fuel types. Particle formation in the dilution process is a complex mixture of nucleation, coagulation, and condensational growth, depending on the concentrations of available condensable species and solid or liquid particles (such as soot, ash) in combustion exhausts. The measured particle size distributions in number concentrations measured show peaks of particle number concentrations for medium sulfur bituminous coal, No. 6 fuel oil, and natural gas at 40-50 nm, 70-100 nm, and 15-25 nm, respectively. For No. 6 fuel oil and coal, the particle number concentration is constant in the range of a dilution air ratio of 50, but the number decreases as the dilution air ratio decreases to 10. However, for natural gas, the particle number concentration is higher at a dilution air ratio of 10 and decreases at dilution air ratios of 20-50. At a dilution air ratio of 10, severe particle coagulation occurs in a relatively short time. Samples taken at different combustion exhaust temperatures for these fuel types show higher particle number concentrations at 645 K than at 450 K. As the aging time of particles increases, the particles increase in size and the number concentrations decrease. The largest gradient of particle number distribution occurs within the first 10 sec after dilution but shows only minor differences between 10 and 80 sec. The lifetimes of the ultrafine particles are relatively short, with a scale on the order of a few seconds. Results from this study suggest that an aging time of 10 sec and a dilution air ratio of 20 are sufficient to obtain representative primary particle emission samples from stationary combustion sources.     

Spatial-temporal variability of aerosol sources based on chemical composition and particle number size distributions in an urban settlement influenced by metallurgical industry

Environmental Science and Pollution Research - The Moravian-Silesian region of the Czech Republic with its capital city Ostrava is a European air pollution hot spot for airborne particulate matter...     

Hospital admissions in Iran for cardiovascular and respiratory diseases attributed to the Middle Eastern Dust storms

Environmental Science and Pollution Research - The main objective of this study was to assess the possible effects of airborne particulate matter less than 10&nbsp;μm in diameter (PM10)...