Characterization of fine particulate matter produced by combustion of residual fuel oil

Combustion experiments were carried out on four different residual fuel oils in a 732-kW boiler. PM emission samples were separated aerodynamically by a cyclone into fractions that were nominally less than and greater than 2.5 microns in diameter. However, examination of several of the samples by computer-controlled scanning electron microscopy (CCSEM) revealed that part of the PM2.5 fraction consists of carbonaceous cenospheres and vesicular particles that range up to 10 microns in diameter. X-ray absorption fine structure (XAFS) spectroscopy data were obtained at the S, V, Ni, Fe, Cu, Zn, and As K-edges and at the Pb L-edge. Deconvolution of the X-ray absorption near edge structure (XANES) region of the S spectra established that the dominant molecular forms of S present were sulfate (26-84% of total S) and thiophene (13-39% of total S). Sulfate was greater in the PM2.5 samples than in the PM2.5+ samples. Inorganic sulfides and elemental sulfur were present in lower percentages. The Ni XANES spectra from all of the samples agreed fairly well with that of NiSO4, while most of the V spectra closely resembled that of vanadyl sulfate (VO.SO4.xH2O). The other metals investigated (i.e., Fe, Cu, Zn, and Pb) also were present predominantly as sulfates. Arsenic was present as an arsenate (As+5). X-ray diffraction patterns of the PM2.5 fraction exhibit sharp lines due to sulfate compounds (Zn, V, Ni, Ca, etc.) superimposed on broad peaks due to amorphous carbons. All of the samples contain a significant organic component, with the loss on ignition (LOI) ranging from 64 to 87% for the PM2.5 fraction and from 88 to 97% for the PM2.5+ fraction. Based on 13C nuclear magnetic resonance (NMR) analysis, the carbon is predominantly condensed in graphitic structures. Aliphatic structure was detected in only one of seven samples examined.     

Study on fractions of adsorbed Pb and Cd onto natural surface coatings

The speciation and extent of migration of adsorbed Pb and Cd in natural surface coatings (NSCs) were investigated using sequential extraction procedure to provide an understanding of distribution of the adsorbed Pb and Cd. Extractions were conducted on NSCs before and after Pb and Cd adsorption treatment under controlled laboratory conditions with initial Pb and Cd concentrations ranging from 0.2-2.5 mol/l. The Langmuir adsorption isotherms were applied to estimate equilibrium coefficients of Pb and Cd adsorption to NSCs components. The results showed that 58.50% of adsorbed Pb in average existed in tightly adsorbed form, and the remaining Pb was mostly present as solid oxides/hydroxides (34.00%) and exchangeable and soluble form (7.50%) in NSCs, respectively. Large amount of adsorbed Cd (70.51% in average) was present in exchangeable and soluble form, following a decreasing order in tightly adsorbed form (18.61%), solid oxides/hydroxides (9.87%), and easily oxidizable solids/compounds (1.01%), respectively. No Cd was found in strongly held oxides and precipitates. Compared to the distribution of adsorbed Pb in NSCs, Cd distribution showed that less migration of Cd from exchangeable and soluble form to solid oxides/hydroxides after adsorbed to NSCs, indicating fewer sites for Cd to adsorb to NSCs and less affinity of Cd to the NSCs. These percent distributions of metals provided an additional interpretation to that Pb adsorption to the NSCs greater than that of Cd, less retention of Cd than that of Pb and less roles attributed for Pb/Cd adsorption by organic materials in NSCs, which were observed based on the selective extraction techniques in the independent investigations.     

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.     

Fractionation and mobility of metals in bauxite red mud

Red mud (RM) is a strongly alkaline residue generated in enormous amounts worldwide from bauxite refining using the Bayer chemical process. RM is composed mainly of Fe, Ti and Al oxides and hydroxides, but it also contains an array of trace metals and metalloids at different concentrations. The purpose of this paper is to assess the potential mobility of metals in RM, with special emphasis on pH effect. The ‘operational’ distribution and leachability of metals within/from RM was studied by applying a sequential extraction procedure (SEP) and several leaching tests (rapid titration, equilibration acidification, batch leaching with acetic acid and also the toxicity characteristics leaching procedure (TCLP) and the DIN 38414-S4 procedures, used as reference methods) carried out at different pH, solid/liquid ratio, extraction period and type of acid (HCl or acetic acid). Chemical analysis showed that, in addition to the major metals Fe, Al and Ti, RM contains several trace metals, some of them (Cr, Cu and Ni) in concentrations exceeding the regulatory limits. SEP showed that a majority of the metals in the RM (between the 32.2?±?8.5 for Cd and 95.3?±?0.4 % for Ni) were found in the residual fraction, suggesting that they are not readily mobile under normal environmental conditions. Leaching tests performed at different pH showed that a significant fraction of the metals is mobilised from RM only under very strong acid conditions (pH?<?2), whereas Al is released in considerable amounts at pH?<?5.3. Among the trace metals, Cr requires special attention because of its relative high concentration in RM and the higher concentrations of this metal mobilised at low pH. The leaching tests using acetic acid showed that the standard TCLP largely underestimates the release of trace metals from RM, and therefore it is not advisable to evaluate the actual potential leaching of trace metals from this residue.     

Estimating national-scale ground-level PM25 concentration in China using geographically weighted regression based on MODIS and MISR AOD

Taking advantage of the continuous spatial coverage, satellite-derived aerosol optical depth (AOD) products have been widely used to assess the spatial and temporal characteristics of fine particulate matter (PM2.5) on the ground and their effects on human health. However, the national-scale ground-level PM2.5 estimation is still very limited because the lack of ground PM2.5 measurements to calibrate the model in China. In this study, a national-scale geographically weighted regression (GWR) model was developed to estimate ground-level PM2.5 concentration based on satellite AODs, newly released national-wide hourly PM2.5 concentrations, and meteorological parameters. The results showed good agreements between satellite-retrieved and ground-observed PM2.5 concentration at 943 stations in China. The overall cross-validation (CV) R ² is 0.76 and root mean squared prediction error (RMSE) is 22.26 μg/m³ for MODIS-derived AOD. The MISR-derived AOD also exhibits comparable performance with a CV R ² and RMSE are 0.81 and 27.46 μg/m³, respectively. Annual PM2.5 concentrations retrieved either by MODIS or MISR AOD indicated that most of the residential community areas exceeded the new annual Chinese PM2.5 National Standard level 2. These results suggest that this approach is useful for estimating large-scale ground-level PM2.5 distributions especially for the regions without PMs monitoring sites.     

Spatial and temporal variations of PM(2.5) concentration and composition throughout an urban area with high freeway density-the Greater Cincinnati study

The PM(2.5) concentration and its elemental composition were measured in the Cincinnati metropolitan area, which is characterized by intense highway traffic. The spatial and temporal variations were investigated for various chemical elements that contributed to the PM(2.5) fraction during a 1-year-long measurement campaign (December 2001-November 2002). The ambient aerosol monitoring was performed in 11 locations around the city during nine measurement cycles. During each cycle, four Harvard-type impactors were operating in parallel in specific locations to explore various factors affecting the PM(2.5) elemental concentrations. The sampling was performed during business days, thus assuring traffic uniformity. The 24-h PM(2.5) samples were collected on Teflon and quartz filters. Teflon filters were analyzed by X-ray fluorescence (XRF) analysis while quartz filters were analyzed by thermal-optical transmittance (TOT) analysis. In addition to PM(2.5) measurements, particle size-selective sampling was performed in two cycles using micro-orifice uniform deposit impactor; the collected fractionated deposits were analyzed by XRF. It was found that PM(2.5) concentration ranged from 6.70 to 48.3 mug m(-3) and had low spatial variation (median coefficient of variation, CV=11.3%). The elemental concentrations demonstrated high spatial variation, with the median CV ranged from 38.2% for Fe to 68.7% for Ni. For traffic-related trace metals, the highest concentration was detected in the city center site, which was close to a major highway. The particle size selective measurement revealed that mass concentration of the trace metals, such as Zn, Pb, Ni, as well as that of sulfur reach their peak values in the particle size range of 0.32-1.0 mum. Meteorological parameters and traffic intensity were not found to have a significant influence on the PM(2.5) elemental concentrations.     

The sensitivity of the CHIMERE model to emissions reduction scenarios on air quality in Northern Italy

The sensitivity of the CHIMERE model to emission reduction scenarios on particulate matter PM2.5 and ozone (O₃) in Northern Italy is studied. The emissions of NO_x, PM2.5 SO₂, VOC or NH₃ were reduced by 50% for different source sectors for the Lombardy region, together with 5 additional scenarios to estimate the effect of local measures on improving the air quality for the Po valley area. Firstly, we evaluate the model performance by comparing calculated surface aerosol concentrations for the standard case (no emission reductions) with observations for January and June 2005. Calculated monthly mean PM10 concentrations are in general underestimated. For June, modelled PM10 concentrations slightly overestimate the measurements. Calculated monthly mean SO₄, NO₃^?, NH₄⁺ concentrations are in good agreement with the observations for January and June. Secondly, the model sensitivity of emission reduction scenarios on PM2.5 and O₃ calculated concentrations for the Po valley area is evaluated. The most effective scenarios to abate PM2.5 concentration are based on the SNAP2 (non-industrial combustion plants) and SNAP7 (road traffic) sectors, for which the NO_x and PM2.5 emissions are reduced by 50%. The number of days that the 2015 PM2.5 limit value of 25 μg m^?3 in Milan is exceeded by reducing primary PM2.5 and NO_x emissions for SNAP2 and 7 by 50%, does not change in January when compared to the standard case for the Milan area. It appears that 40% of the PM2.5 concentration in the greater Milan area is caused by the emissions surrounding the Lombardy region and from the model boundary conditions.This study also showed that a more effective pollutant reduction (emissions) per ton of pollutant reduced (concentrations) for the greater Milan area is obtained by reducing the primary PM2.5 emissions for SNAP7 by 50%. The most effective scenario on PM2.5 decrease for which precursor emissions are reduced is achieved by reducing SO₂ emissions by 50% for SNAP7.Our study showed that during summer time, the largest reductions in O₃ concentrations are achieved for SNAP7 emission reductions, when volatile organic compounds (VOCs) are reduced by 50%.     

Determination of Levoglucosan in Atmospheric Fine Particulate Matter

Abstract

A microanalytical method suitable for the quantitative determination of the sugar anhydride levoglucosan in low-volume samples of atmospheric fine particulate matter (PM) has been developed and validated. The method incorporates two sugar anhydrides as quality control standards. The recovery standard sedoheptulosan (2,7-anhydro-β-D-altro-heptulopyranose) in 20 μL solvent is added onto samples of the atmospheric fine PM and aged for 1 hr before ultrasonic extraction with ethylacetate/ triethylamine. The extract is reduced in volume, an internal standard is added (1,5-anhydro-D-mannitol), and a portion of the extract is derivatized with 10% by volume N-trimethylsilylimidazole. The derivatized extract is analyzed by gas chromatography/mass spectrometry (GC/MS). The recovery of levoglucosan using this procedure was 69 ± 6% from five filters amended with 2 μg levoglu-cosan, and the reproducibility of the assay is 9%. The limit of detection is ～0.1 μg/mL, which is equivalent to ～3.5 ng/m³ for a 10 L/min sampler or ～8.7 ng/m³ for a 4 L/min personal sampler (assuming 24-hr integrated samples). We demonstrated that levoglucosan concentrations in collocated samples (expressed as ng/m³) were identical irrespective of whether samples were collected by PM with aerodynamic diameter ≤2.5 μm or PM with aerodynamic diameter ≤10 μm impactors. It was also demonstrated that X-ray fluorescence analysis of samples of atmospheric PM, before levoglucosan determinations, did not alter the levels of levoglucosan.     

The Steubenville Comprehensive Air Monitoring Program (SCAMP): concentrations and solubilities of PM(2.5) trace elements and their implications for source apportionment and health research

The elemental compositions of the water-soluble and acid-digestible fractions of 24-hr integrated fine particulate matter (PM(2.5)) samples collected in Steubenville, OH, from 2000 to 2002 were determined using dynamic reaction cell inductively coupled plasma-mass spectrometry. The water-soluble elemental compositions of PM(2.5) samples collected at four satellite monitoring sites in the surrounding region were also determined. Fe was the most abundant but least water soluble of the elements determined at the Steubenville site, having a mean ambient concentration of 272 ng/m3 and a median fractional solubility of 6%. Fe solubility and its correlations with SO4(2-) and temperature varied significantly by season, consistent with the hypothesis that secondary sulfates may help to mobilize soluble Fe under suitable summertime photochemical conditions. Significantly higher ambient concentrations were observed at Steubenville than at each of the four satellite sites for 10 of the 18 elements (Al, As, Ca, Cd, Fe, Mg, Mn, Na, Pb, and Zn) determined in the water-soluble PM(2.5) fraction. Concentrations of Fe, Mn, and Zn at Steubenville were substantially higher than concentrations reported recently for larger U.S. cities. Receptor modeling identified seven sources affecting the Steubenville site. An (NH4)2SO4-dominated source, likely representing secondary PM(2.5) from coal-fired plants to the west and southwest of Steubenville, accounted for 42% of the PM(2.5) mass, and two sources likely dominated by emissions from motor vehicles and from iron and steel facilities in the immediate Steubenville vicinity accounted for 20% and 10%, respectively. Other sources included an NH4NO3 source (15%), a crustal source (6%), a mixed nonferrous metals and industrial source (3%), and a primary coal combustion source (3%). Results suggest the importance of very different regional and local source mechanisms in contributing to PM(2.5) mass at Steubenville and reinforce the need for further research to elucidate whether metals such as Fe, Mn, and Zn play a role in the PM(2.5) health effects observed previously there.     

Resolving the interactions between population density and air pollution emissions controls in the San Joaquin Valley, USA

The effectiveness of emissions control programs designed to reduce concentrations of airborne particulate matter with an aerodynamic diameter < 2.5 microm (PM2.5) in California's San Joaquin Valley was studied in the year 2030 under three growth scenarios: low, medium, and high population density. Base-case inventories for each choice of population density were created using a coupled emissions modeling system that simultaneously considered interactions between land use and transportation, area source, and point source emissions. The ambient PM2.5 response to each combination of population density and emissions control was evaluated using a regional chemical transport model over a 3-week winter stagnation episode. Comparisons between scenarios were based on regional average and population-weighted PM2.5 concentrations. In the absence of any emissions control program, population-weighted concentrations of PM2.5 in the future San Joaquin Valley are lowest undergrowth scenarios that emphasize low population density. A complete ban on wood burning and a 90% reduction in emissions from food cooking operations and diesel engines must occur before medium- to high-density growth scenarios result in lower population-weighted concentrations of PM2.5. These trends partly reflect the fact that existing downtown urban cores that naturally act as anchor points for new high-density growth in the San Joaquin Valley are located close to major transportation corridors for goods movement. Adding growth buffers around transportation corridors had little impact in the current analysis, since the 8-km resolution of the chemical transport model already provided an artificial buffer around major emissions sources. Assuming that future emissions controls will greatly reduce or eliminate emissions from residential wood burning, food cooking, and diesel engines, the 2030 growth scenario using "as-planned" (medium) population density achieves the lowest population-weighted average PM2.5 concentration in the future San Joaquin Valley during a severe winter stagnation event. Implications: The San Joaquin Valley is one of the most heavily polluted air basins in the United States that are projected to experience strong population growth in the coming decades. The best plan to improve air quality in the region combines medium- or high-density population growth with rigorous emissions controls. In the absences of controls, high-density growth leads to increased population exposure to PM2.5 compared with low-density growth scenarios (urban sprawl).     

Determination of levoglucosan in atmospheric fine particulate matter

A microanalytical method suitable for the quantitative determination of the sugar anhydride levoglucosan in low-volume samples of atmospheric fine particulate matter (PM) has been developed and validated. The method incorporates two sugar anhydrides as quality control standards. The recovery standard sedoheptulosan (2,7-anhydro-beta-D-altro-heptulopyranose) in 20 microL solvent is added onto samples of the atmospheric fine PM and aged for 1 hr before ultrasonic extraction with ethylacetate/ triethylamine. The extract is reduced in volume, an internal standard is added (1,5-anhydro-D-mannitol), and a portion of the extract is derivatized with 10% by volume N-trimethylsilylimidazole. The derivatized extract is analyzed by gas chromatography/mass spectrometry (GC/MS). The recovery of levoglucosan using this procedure was 69 +/- 6% from five filters amended with 2 microg levoglucosan, and the reproducibility of the assay is 9%. The limit of detection is approximately 0.1 microg/mL, which is equivalent to approximately 3.5 ng/m3 for a 10 L/min sampler or approximately 8.7 ng/m3 for a 4 L/min personal sampler (assuming 24-hr integrated samples). We demonstrated that levoglucosan concentrations in collocated samples (expressed as ng/m3) were identical irrespective of whether samples were collected by PM with aerodynamic diameter < or = 2.5 microm or PM with aerodynamic diameter < or = 10 microm impactors. It was also demonstrated that X-ray fluorescence analysis of samples of atmospheric PM, before levoglucosan determinations, did not alter the levels of levoglucosan.     

Chemical characterization and factor analysis of PM2.5 in two sites of Monterrey, Mexico

The Monterrey Metropolitan Area (MMA) has shown a high concentration of PM2.5 in its atmosphere since 2003. The contribution of possible sources of primary PM2.5 and its precursors is not known. In this paper we present the results of analyzing the chemical composition of sixty 24-hr samples of PM2.5 to determine possible sources of PM2.5 in the MMA. The samples were collected at the northeast and southeast of the MMA between November 22 and December 12, 2007, using low-volume devices. Teflon and quartz filters were used to collect the samples. The concentrations of 16 airborne trace elements were determined using x-ray fluorescence (XRF). Anions and cations were determined using ion chromatography. Organic carbon (OC) and elemental carbon (EC) were determined by thermal optical analysis. The results show that Ca had the maximum mean concentration of all elements studied, followed by S. Enrichment factors above 50 were calculated for S, Cl, Cu, Zn, Br and Pb. This indicates that these elements may come from anthropogenic sources. Overall, the major average components of PM2.5 were OC (41.7%), SO4(2-) (22.9%), EC (7.4%), crustal material (11.4%), and NO3- (12.6%), which altogether accounted for 96% of the mass. Statistically, we did not find any difference in SO4(2-) concentrations between the two sites. The fraction of secondary organic carbon was between 24% and 34%. The results of the factor analysis performed over 10 metals and OC and EC show that there are three main sources of PM2.5: crustal material and vehicle exhaust; industrial activity; and fuel oil burning. The results show that SO4(2-), OC, and crustal material are important components of PM2.5 in MMA. Further work is necessary to evaluate the proportion of secondary inorganic and organic aerosol in order to have a better understanding of the sources and precursors of aerosols in the MMA.     

Fractionation of heavy metals in liquefied chromated copper arsenate 9-treated wood sludge using a modified BCR-sequential extraction procedure

Chromated copper arsenate (CCA)-treated wood was liquefied with polyethylene glycol/glycerin and sulfuric acid. After liquefaction, most CCA metals (98% As, 92% Cr, and 83% Cu) were removed from liquefied CCA-treated wood by precipitation with calcium hydroxide. The original CCA-treated wood and liquefied CCA-treated wood sludge were fractionated by a modified Community Bureau of Reference (BCR) sequential extraction procedure. The purpose of the BCR-sequential extraction used in this study was to examine the availability of CCA metals in treated wood for reuse. Both As and Cr had a slightly higher concentration in the sludge sample than in original CCA-treated wood. The sequential extraction showed that As and Cr were principally existed in an oxidizable fraction (As, 67%; Cr, 88%) in original CCA-treated wood. Only 1% of both As and Cr were extracted by hot nitric acid with the last extraction step. The distribution of As and Cr changed markedly in liquefied CCA-treated wood sludge.The amount of As in the exchangeable/acid extractable fraction increased from 16% to 85% while the amount of Cr increased from 3% to 54%. Only about 3% of As was present in the oxidizable fraction. However, there was still about 34% of Cr in the same fraction. Based on these results from sequential extraction procedures, it can be concluded that the accessibilities of CCA metals increase markedly by the liquefaction–precipitation process.     

Feasibility of using low-cost portable particle monitors for measurement of fine and coarse particulate matter in urban ambient air

Exposure to ambient particulate matter (PM) is known as a significant risk factor for mortality and morbidity due to cardiorespiratory causes. Owing to increased interest in assessing personal and community exposures to PM, we evaluated the feasibility of employing a low-cost portable direct-reading instrument for measurement of ambient air PM exposure. A Dylos DC 1700 PM sensor was collocated with a Grimm 11-R in an urban residential area of Houston Texas. The 1-min averages of particle number concentrations for sizes between 0.5 and 2.5 µm (small size) and sizes larger than 2.5 µm (large size) from a DC 1700 were compared with the 1-min averages of PM_2.5 (aerodynamic size less than 2.5 µm) and coarse PM (aerodynamic size between 2.5 and 10 µm) concentrations from a Grimm 11-R. We used a linear regression equation to convert DC 1700 number concentrations to mass concentrations, utilizing measurements from the Grimm 11-R. The estimated average DC 1700 PM_2.5 concentration (13.2 ± 13.7 µg/m³) was similar to the average measured Grimm 11-R PM_2.5 concentration (11.3 ± 15.1 µg/m³). The overall correlation (r²) for PM_2.5 between the DC 1700 and Grimm 11-R was 0.778. The estimated average coarse PM concentration from the DC 1700 (5.6 ± 12.1 µg/m³) was also similar to that measured with the Grimm 11-R (4.8 ± 16.5 µg/m³) with an r² of 0.481. The effects of relative humidity and particle size on the association between the DC 1700 and the Grimm 11-R results were also examined. The calculated PM mass concentrations from the DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.

Implications: The performance of a low-cost particulate matter (PM) sensor was evaluated in an urban residential area. Both PM_2.5 and coarse PM (PM_10-2.5) mass concentrations were estimated using a DC1700 PM sensor. The calculated PM mass concentrations from the number concentrations of DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.     

Chemical fingerprint and source apportionment of PM 2.5 in highly polluted events of southern Taiwan

To investigate the spatial distribution and diurnal variation of the chemical composition of PM2.5 pollution in an industrial city of southern Taiwan, 12-h PM2.5 was diurnally continuously collected simultaneously at the Kaoping Air Quality Zone (KAQZ) during one highly PM2.5-polluted episode. Water-soluble ions, metallic elements, carbonaceous contents, dicarboxylic acids, and anhydrosugars were analyzed to characterize the chemical fingerprint of PM2.5. Backward trajectory simulation and chemical mass balance (CMB) receptor modeling were applied to identify the potential sources of PM2.5 and their contributions. It showed that Chaozhou (rural area) accompanying the highest SORs and NORs suffered from the most severe PM2.5 pollution during the episode. Sulfate (SO42−) was probably formed by the atmospheric chemical reaction in the daytime, while NO3− processed at nighttime at the KAQZ. A homogeneous formation of NO3− occurred at Chaozhou. The concentrations of Zn, Pb, Fe, Cu, V, and Al, mainly emitted from anthropogenic sources, increased significantly at the KAQZ. The highest OC, SOC/OC, and DA/OCs at Daliao (industrial area) were attributed to the transformation of primary VOCs to secondary OC via photo-oxidation during the episode. Oxalic acid was mainly produced through photochemical reactions since a high correlation between oxalic acid and Ca2+ was observed at Nanzi (urban area) and Daliao during the episode. During the episode, PM2.5 mostly originated from local primary or secondary aerosol than long-range overseas transport. The dominant source was anthropogenic emissions, accounting for 67.1% and 70.4% of PM2.5 at Nanzi and Daliao, respectively. At Chaozhou, the contribution of anthropogenic emissions was the lowest (42.4%), but secondary aerosols had the highest contribution of 38.3% of PM2.5 among the three areas during the episode.     

Source Apportionment Using Positive Matrix Factorization on Daily Measurements of Inorganic and Organic Speciated PM(2.5)

Particulate matter less than 2.5 microns in diameter (PM(2.5)) has been linked with a wide range of adverse health effects. Determination of the sources of PM(2.5) most responsible for these health effects could lead to improved understanding of the mechanisms of such effects and more targeted regulation. This has provided the impetus for the Denver Aerosol Sources and Health (DASH) study, a multi-year source apportionment and health effects study relying on detailed inorganic and organic PM(2.5) speciation measurements.In this study, PM(2.5) source apportionment is performed by coupling positive matrix factorization (PMF) with daily speciated PM(2.5) measurements including inorganic ions, elemental carbon (EC) and organic carbon (OC), and organic molecular markers. A qualitative comparison is made between two models, PMF2 and ME2, commonly used for solving the PMF problem. Many previous studies have incorporated chemical mass balance (CMB) for organic molecular marker source apportionment on limited data sets, but the DASH data set is large enough to use multivariate factor analysis techniques such as PMF.Sensitivity of the PMF2 and ME2 models to the selection of speciated PM(2.5) components and model input parameters was investigated in depth. A combination of diagnostics was used to select an optimum, 7-factor model using one complete year of daily data with pointwise measurement uncertainties. The factors included 1) a wintertime/methoxyphenol factor, 2) an EC/sterane factor, 3) a nitrate/polycyclic aromatic hydrocarbon (PAH) factor, 4) a summertime/selective aliphatic factor, 5) an n-alkane factor, 6) a middle oxygenated PAH/alkanoic acid factor and 7) an inorganic ion factor. These seven factors were qualitatively linked with known PM(2.5) emission sources with varying degrees of confidence. Mass apportionment using the 7-factor model revealed the contribution of each factor to the mass of OC, EC, nitrate and sulfate. On an annual basis, the majority of OC and EC mass was associated with the summertime/selective aliphatic factor and the EC/sterane factor, respectively, while nitrate and sulfate mass were both dominated by the inorganic ion factor. This apportionment was found to vary substantially by season. Several of the factors identified in this study agree well with similar assessments conducted in St. Louis, MO and Pittsburgh, PA using PMF and organic molecular markers.     

Size distribution and diurnal characteristics of particle-bound metals in source and receptor sites of the Los Angeles Basin

Measurement of daily size-fractionated ambient PM₁₀ mass, metals, inorganic ions (nitrate and sulfate) and elemental and organic carbon were conducted at source (Downey) and receptor (Riverside) sites within the Los Angeles Basin. In addition to 24-h concentration measurements, the diurnal patterns of the trace element and metal content of fine (0–2.5 μm) and coarse (2.5–10 μm) PM were studied by determining coarse and fine PM metal concentrations during four time intervals of the day.The main source of crustal metals (e.g., Al, Si, K, Ca, Fe and Ti) can be attributed to the re-suspension of dust at both source and receptor sites. All the crustals are predominantly present in supermicron particles. At Downey, potentially toxic metals (e.g., Pb, Sn, Ni, Cr, V, and Ba) are predominantly partitioned (70–85%, by mass) in the submicron particles. Pb, Sn and Ba have been traced to vehicular emissions from nearby freeways, whereas Ni and Cr have been attributed to emissions from powerplants and oil refineries upwind in Long Beach. Riverside, adjacent to Southern California deserts, exhibits coarser distributions for almost all particle-bound metals as compared to Downey. Fine PM metal concentrations in Riverside seem to be a combination of few local emissions and those transported from urban Los Angeles. The majority of metals associated with fine particles are in much lower concentrations at Riverside compared to Downey. Diurnal patterns of metals are different in coarse and fine PM modes in each location. Coarse PM metal concentration trends are governed by variations in the wind speeds in each location, whereas the diurnal trends in the fine PM metal concentrations are found to be a function both of the prevailing meteorological conditions and their upwind sources.     

Apportionment of ambient primary and secondary fine particulate matter at the Pittsburgh National Energy Laboratory particulate matter characterization site using positive matrix factorization and a potential source contributions function analysis

Fine particulate matter (PM2.5) concentrations associated with 202 24-hr samples collected at the National Energy Technology Laboratory (NETL) particulate matter (PM) characterization site in south Pittsburgh from October 1999 through September 2001 were used to apportion PM2.5 into primary and secondary contributions using Positive Matrix Factorization (PMF2). Input included the concentrations of PM2.5 mass determined with a Federal Reference Method (FRM) sampler, semi-volatile PM2.5 organic material, elemental carbon (EC), and trace element components of PM2.5. A total of 11 factors were identified. The results of potential source contributions function (PSCF) analysis using PMF2 factors and HYSPLIT-calculated back-trajectories were used to identify those factors associated with specific meteorological transport conditions. The 11 factors were identified as being associated with emissions from various specific regions and facilities including crustal material, gasoline combustion, diesel combustion, and three nearby sources high in trace metals. Three sources associated with transport from coal-fired power plants to the southeast, a combination of point sources to the northwest, and a steel mill and associated sources to the west were identified. In addition, two secondary-material-dominated sources were identified, one was associated with secondary products of local emissions and one was dominated by secondary ammonium sulfate transported to the NETL site from the west and southwest. Of these 11 factors, the four largest contributors to PM2.5 were the secondary transported material (dominated by ammonium sulfate) (47%), local secondary material (19%), diesel combustion emissions (10%), and gasoline combustion emissions (8%). The other seven factors accounted for the remaining 16% of the PM2.5 mass. The findings are consistent with the major source of PM2.5 in the Pittsburgh area being dominated by ammonium sulfate from distant transport and so decoupled from local activity emitting organic pollutants in the metropolitan area. In contrast, the major local secondary sources are dominated by organic material.     

Identification of dicarboxylic acids and aldehydes of PM10 and PM2.5 aerosols in Nanjing,China

In this study aerosol samples of PM10 and PM2.5 collected from 18 February 2001 to 1 May 2001 in Nanjing, China were analyzed for their water-soluble organic compounds. A series of homologous dicarboxylic acids (C_2–10) and two kinds of aldehydes (methylglyoxal and 2-oxo-malonaldehyde) were detected by GC and GC/MS. Among the identified compounds, the concentration of oxalic acid was the highest at all the five sites, which ranged from 178 to 1423 ng/m³. The second highest concentration of dicarboxylic acids were malonic and succinic acids, which ranged from 26.9 to 243 ng/m³. Higher level of azelaic acid was also observed, of which the maximum was 301 ng/m³. As the highest fraction of dicarboxylic acids, oxalic acid comprised from 28% to 86% of total dicarboxylic acids in PM10 and from 41% to 65% of total dicarboxylic acids in PM2.5. The dicarboxylic acids (C₂, C₃, C₄) together accounted for 38–95% of total dicarboxylic acids in PM10 and 59–87% of dicarboxylic acids in PM2.5. In this study, the total dicarboxylic acids accounted for 2.8–7.9% of total organic carbon (TOC) of water-soluble matters for PM10 and 3.4–11.8% of TOC for PM2.5. All dicarboxylic acids detected in this study together accounted for about 1% of particle mass. The concentration of azelaic acid was higher at one site than others, which may be resulted from higher level of volatile fat used for cooking. The amounts of dicarboxyic acids (C_2,3,4,9) and 2-oxo-malonaldehyde of PM2.5 were higher in winter and lower in spring. Compared with other major metropolitans in the world, the level of oxalic acid concentration of Nanjing is much higher, which may be contributed to higher level of particle loadings, especially for fine particles.     

还原焙烧电镀污泥中的金属形态和浸出性

分别以煤粉和稻杆为还原剂对电镀污泥进行还原焙烧,并通过酸浸回收焙烧渣中的金属。研究了焙烧温度、焙烧时间和还原剂投加量对目标金属Cu浸出率的影响以及主要杂质金属的浸出性,并采用BCR逐级提取法分析了焙烧前后污泥中的金属形态分布。结果表明,当在电镀污泥中投加30％的煤粉在600℃下焙烧1h后Cu的浸出率达到97．78％,当投加50％的稻杆时浸出率为89．47％,而氧化焙烧后浸出率仅为37．71％;并且还原焙烧渣中多数杂质金属的浸出率较低,从而可以实现Cu与杂质金属的初步分离。氧化焙烧容易导致金属从易浸出的非残渣态向难浸出的残渣态转化,而还原焙烧则能抑制这种转化过程,金属形态是决定其浸出性的重要因素。