Relationships between size segregated mass concentration data and ultrafine particle number concentrations in urban areas

Mass concentration data derived from samples collected with a micro-orifice uniform deposit impactor (MOUDI) in six Australian urban centers during periods of significant particle loading have been used to investigate the relationships between TSP, PM10, PM2.5, PM1 and ultrafine particles. While PM10 and PM2.5 display a clear relationship, the lack of correlation between PM10 and the coarse fraction of PM10 (PM10–PM2.5) suggests that variation in PM10 is dominated by variance in PM2.5. Given that particles of less than 2.5 μm are suspected to have adverse health effects, increasing the extent of PM2.5 monitoring may improve detection of relationships between air pollution and human health. A lack of correlation between both PM10 and PM2.5 with ultrafine mass concentrations indicates that PM10 and PM2.5 cannot be used as a surrogate for ultrafine mass concentration. Similarly, ultrafine number concentrations cannot be inferred from mass concentration information determined by the MOUDI.     

PM10 and PM2.5 source apportionment in the Barcelona Metropolitan area, Catalonia, Spain

Levels of total suspended particles, PM10, PM2.5 and PM1 were continuously monitored at an urban kerbside in the Metropolitan area of Barcelona from June 1999 to June 2000. The results show that hourly levels of PM2.5 and PM1 are consistent with the daily cycle of gaseous pollutants emitted by traffic, whereas TSP and PM10 do not follow the same trend, at least in the diurnal period. The PM2.5/PM10 ratio is dependent on the traffic emissions, whereas additional contribution sources for the >10 μm fraction must be taken into account in the diurnal period. Different PM10 and PM2.5 source apportionment techniques were compared. A methodology based on the chemical determination of 83% of both PM10 and PM2.5 masses allowed us to quantify the marine (4% in PM10 and <1% in PM2.5), crustal (26% in PM10 and 8% in PM2.5) and anthropogenic (54% in PM10 and 73% in PM2.5) loads. Peaks of crustal contribution to PM10 (up to 44% of the PM10 mass) were recorded under Saharan air mass intrusions. A different seasonal trend was observed for levels of sulphate and nitrate, probably as a consequence of the different thermodynamic behaviour of these PM species and the higher summer oxidation rate of SO₂.     

Characterization of PM2.5 and PM10 in the South Coast Air Basin of southern California: Part 1--Spatial variations

In December 1994, the South Coast Air Quality Management District (SCAQMD) initiated a comprehensive program, the PM10 Technical Enhancement Program (PTEP), to characterize fine PM in the South Coast Air Basin (SCAB). A 1-year special particulate monitoring project was conducted from January 1995 to February 1996 as part of the PTEP. Under this enhanced monitoring, HNO3, NH3, and speciated PM10 and PM2.5 concentrations were measured at five stations (Anaheim, downtown Los Angeles, Diamond Bar, Fontana, and Rubidoux) in the SCAB and at one background station at San Nicolas Island. PM2.5 and PM10 mass and 43 individual species were analyzed for a full chemical speciation of the particle data. The PTEP data indicate that the most abundant chemical components of PM10 and PM2.5 in the SCAB are NH4+ (8-9% of PM10 and 14-17% of PM2.5), NO3- (23-26% of PM10 and 28-41% of PM2.5), SO4- (6-11% of PM10 and 9-18% of PM2.5), organic carbon (OC) (15-19% of PM10 and 18-26% of PM2.5), and elemental carbon (EC) (5-8% of PM10 and 8-13% of PM2.5). On an annual average basis, PM2.5 comprises 52-59% of the SCAB PM10. Annual average PM10 and PM2.5 concentrations showed strong spatial variations, low at coastal sites and high at inland sites. Annual average PM10 concentrations varied from 40.8 micrograms/m3 at Anaheim to 76.8 micrograms/m3 at Rubidoux, while annual average PM2.5 concentrations varied from 21.7 micrograms/m3 at Anaheim to 39.8 micrograms/m3 at Rubidoux. The chemical characterizations of the PM2.5 and PM10 concentrations, as well as their spatial variations, were examined; the important findings are summarized in this paper, and the temporal variations are discussed in the companion paper.     

区域大气环境中PM_(2.5)/PM_(10)空间分布研究

提出了一种利用移动监测技术研究区域大气环境中PM2.5/PM10空间分布的方法,并在2004年12月进行了宁波市全市域PM2.5/PM10空间分布的研究.数据显示:相同路径所代表的地区PM2.5和PM10具有很好的相关性,多数路径上PM2.5与PM10数据的相关系数平方在0.95以上,而不同路径上PM2.5与PM10的比值不同.文中给出了宁波市PM2.5/PM10污染的空间分布图,直观地显示出PM2.5/PM10污染的空间分布情况,突出了污染的重点点位和地区.     

PM source identification at Sunland Park, New Mexico, using a simple heuristic meteorological and chemical analysis

The causes for evening low-wind PM10 and PM2.5 peaks at Sunland Park, NM, were investigated by using wind sector analysis and by assessing relationships between PM loadings and meteorological parameters through canonical ordination analysis. Both PM10 and PM2.5 concentrations during the evening hours accounted for approximately 50% of their respective 24-hr averages, and the PM10 was mainly composed of coarse material (PM10-2.5 amounted to 77% of PM10). A wind sector analysis based on data from three surface meteorological monitoring stations in the region narrowed the potential source region for PM10 and PM2.5 to an area within a few kilometers south of Sunland Park. Canonical ordination analysis confirmed that the peak frequently occurred under stable conditions with weak southerly winds. Chemical analyses of PM showed that elemental and organic carbon (EC and OC, respectively) dominate PM2.5 and inorganic elements dominate PM10-2.5. The combined data for EC/OC, geologic elements, and various trace elements indicate that under low wind and stable conditions, traffic-related PM emissions (motor vehicle exhausts and re-suspended road dust) from the south of the site are the most likely sources for the evening PM10 and PM2.5 peaks.     

Identification and chemical characterization of industrial particulate matter sources in southwest Spain

A detailed physical and chemical characterization of coarse particulate matter (PM10) and fine particulate matter (PM2.5) in the city of Huelva (in Southwestern Spain) was carried out during 2001 and 2002. To identify the major emission sources with a significant influence on PM10 and PM2.5, a methodology was developed based on the combination of: (1) real-time measurements of levels of PM10, PM2.5, and very fine particulate matter (PM1); (2) chemical characterization and source apportionment analysis of PM10 and PM2.5; and (3) intensive measurements in field campaigns to characterize the emission plumes of several point sources. Annual means of 37, 19, and 16 microg/m3 were obtained for the study period for PM10, PM2.5, and PM1, respectively. High PM episodes, characterized by a very fine grain size distribution, are frequently detected in Huelva mainly in the winter as the result of the impact of the industrial emission plumes on the city. Chemical analysis showed that PM at Huelva is characterized by high PO4(3-) and As levels, as expected from the industrial activities. Source apportionment analyses identified a crustal source (36% of PM10 and 31% of PM2.5); a traffic-related source (33% of PM10 and 29% of PM2.5), and a marine aerosol contribution (only in PM10, 4%). In addition, two industrial emission sources were identified in PM10 and PM2.5: (1) a petrochemical source, 13% in PM10 and 8% in PM2.5; and (2) a mixed metallurgical-phosphate source, which accounts for 11-12% of PM10 and PM2.5. In PM2.5 a secondary source has been also identified, which contributed to 17% of the mass. A complete characterization of industrial emission plumes during their impact on the ground allowed for the identification of tracer species for specific point sources, such as petrochemical, metallurgic, and fertilizer and phosphate production industries.     

Numerical study of the effect of ventilation pattern on coarse, fine, and very fine particulate matter removal in partitioned indoor environment

An indoor size-dependent particulate matter (PM) transport approach is developed to investigate coarse PM (PM10), fine PM (PM2.5), and very fine PM (PM1) removal behaviors in a ventilated partitioned indoor environment. The approach adopts the Eulerian large eddy simulation of turbulent flow and the Lagrangian particle trajectory tracking to solve the continuous airflow phase and the discrete particle phase, respectively. Model verification, including sensitivity tests of grid resolution and particle numbers, is conducted by comparison with the full-size experiments conducted previously. Good agreement with the measured mass concentrations is found. Numerical scenario simulations of the effect of ventilation patterns on PM removal are performed by using three common ventilation patterns (piston displacement, mixing, and cross-flow displacement ventilation) with a measured indoor PM10 profile in the Taipei metropolis as the initial condition. The temporal variations of suspended PM10, PM2.5, and PM1 mass concentrations and particle removal mechanisms are discussed. The simulated results show that for all the of the three ventilation patterns, PM2.5 and PM1 are much more difficult to remove than PM10. From the purpose of health protection for indoor occupants, it is not enough to only use the PM10 level as the indoor PM index. Indoor PM2.5 and PM1 levels should be also considered. Cross-flow displacement ventilation is more effective to remove all PM10, PM2.5, and PM1 than the other ventilation patterns. Displacement ventilation would result in more escaped particles and less deposited particles than mixing ventilation.     

重庆主城区春季典型天气的大气颗粒物浓度变化分析

选取重庆大气超级站2010年春季典型天气时段的颗粒物实时监测数据,将β射线法和震荡天平法(TEOM法)的PM10监测值进行了比对,分析了PM10、PM2.5和PM1质量浓度百分比例关系及10μm以下颗粒物数浓度随粒径大小的分布规律。结果表明,β射线法与TEOM法的PM10监测结果基本一致,β射线法比TEOM法监测值平均偏低5.4%;PM2.5、PM1和PM0.5的数浓度均占PM10数浓度的98%以上;PM0.25数浓度占PM10数浓度的平均比例为34.9%,占PM1数浓度的平均比例为35.1%;TEOM法监测的PM2.5占PM10日均质量浓度平均比例为51.2%;β射线法监测的PM2.5占PM10日均质量浓度平均比例为56.9%,PM1占PM10平均比例为30.9%。     

Influence of sea-land breezes on the tempospatial distribution of atmospheric aerosols over coastal region

The influence of sea-land breezes (SLBs) on the spatial distribution and temporal variation of particulate matter (PM) in the atmosphere was investigated over coastal Taiwan. PM was simultaneously sampled at inland and offshore locations during three intensive sampling periods. The intensive PM sampling protocol was continuously conducted over a 48-hr period. During this time, PM2.5 and PM(2.5-10) (PM with aerodynamic diameters < 2.5 microm and between 2.5 and 10 microm, respectively) were simultaneously measured with dichotomous samplers at four sites (two inland and two offshore sites) and PM10 (PM with aerodynamic diameters < or =10 microm) was measured with beta-ray monitors at these same 4 sites and at 10 sites of the Taiwan Air Quality Monitoring Network. PM sampling on a mobile air quality monitoring boat was further conducted along the coastline to collect offshore PM using a beta-ray monitor and a dichotomous sampler. Data obtained from the inland sites (n=12) and offshore sites (n=2) were applied to plot the PM10 concentration contour using Surfer software. This study also used a three-dimensional meteorological model (Pennsylvania State University/National Center for Atmospheric Research Meteorological Model 5) and the Comprehensive Air Quality Model with Extensions to simulate surface wind fields and spatial distribution of PM10 over the coastal region during the intensive sampling periods. Spatial distribution of PM10 concentration was further used in investigating the influence of SLBs on the transport of PM10 over the coastal region. Field measurement and model simulation results showed that PM10 was transported back and forth across the coastline. In particular, a high PM10 concentration was observed at the inland sites during the day because of sea breezes, whereas a high PM10 concentration was detected offshore at night because of land breezes. This study revealed that the accumulation of PM in the near-ocean region because of SLBs influenced the tempospatial distribution of PM10 over the coastal region.     

冬季沈阳市典型源排放PM10浓度分布模拟分析

选取沈阳市7个典型的大气污染源2006年12月～2007年2月的PM10排放浓度资料,利用CALPUFF对PM10浓度月平均分布做模拟分析。模拟结果分析表明：冬季月平均PM10浓度分布的范围与风场、地形有直接的关系。地势平坦、风速大时,污染物扩散范围大,污染物浓度小;地势不平、风速小时,污染物扩散范围小,污染物浓度大。1月份是沈阳市冬季月平均大气污染最严重的月份,污染物分布主要集中在市区的北部、东部和南部地区,东部地区大气污染最为严重。     

Retrospective prediction of intraurban spatiotemporal distribution of PM2.5 in Taipei

Numerous studies have shown that fine airborne particulate matter particles (PM2.5) are more dangerous to human health than coarse particles, e.g. PM10. The assessment of the impacts to human health or ecological effects by long-term PM2.5 exposure is often limited by lack of PM2.5 measurements. In Taipei, PM2.5 was not systematically observed until August, 2005. Taipei is the largest metropolitan area in Taiwan, where a variety of industrial and traffic emissions are continuously generated and distributed across space and time. PM-related data, i.e., PM10 and Total Suspended Particles (TSP) are independently systematically collected by different central and local government institutes. In this study, the retrospective prediction of spatiotemporal distribution of monthly PM2.5 over Taipei will be performed by using Bayesian Maximum Entropy method (BME) to integrate (a) the spatiotemporal dependence among PM measurements (i.e. PM10, TSP, and PM2.5), (b) the site-specific information of PM measurements which can be certain or uncertain information, and (c) empirical evidence about the PM2.5/PM10 and PM10/TSP ratios. The performance assessment of the retrospective prediction for the spatiotemporal distribution of PM2.5 was performed over space and time during 2003–2004 by comparing the posterior pdf of PM2.5 with the observations. Results show that the incorporation of PM10 and TSP observations by BME method can effectively improve the spatiotemporal PM2.5 estimation in the sense of lower mean and standard deviation of estimation errors. Moreover, the spatiotemporal retrospective prediction with PM2.5/PM10 and PM2.5/TSP ratios can provide good estimations of the range of PM2.5 levels over space and time during 2003–2004 in Taipei.     

Personal exposures to particles and their relationships with personal activities for chronic obstructive pulmonary disease patients living in Boston

An exposure study of 18 subjects with chronic obstructive pulmonary disease (COPD) living in the Boston, MA, area was conducted. The objective was to examine determinants of personal exposures to particulate matter (PM) with aerodynamic diameters of less than 2.5 microm (PM2.5), less than 10 microm (PM10), and between 2.5 and 10 microm (PM2.5-10). In a previous publication, the analyses of the longitudinal individual-specific relationships among indoor, outdoor, and personal levels showed that the relationships varied by subject and by particle size fraction. In the present paper, statistical and physical models were used to examine personal PM2.5, PM10, and PM2.5-10 exposure covariates. Results indicated that time-weighted indoor concentrations were significant predictors of personal PM2.5, PM10, and PM2.5-10 exposures. Also, time-weighted outdoor concentrations, time spent near smokers, and time spent during transportation were important predictors for PM2.5 but not for personal PM2.5-10 exposures. In turn, time spent cleaning contributed to all size-fraction personal exposures, whereas cooking affected only personal PM2.5-10 exposures. The findings showed that the relationship between personal PM2.5 exposures and the corresponding ambient concentrations was influenced by home air exchange rates (or by ventilation status). Because the particle properties or components causing the health effects are unknown, it is not certain to what extent the risk posed by ambient particles can be reduced by controlling any one of these factors.     

区域大气环境中PM2．5／PM10空间分布研究

提出了一种利用移动监测技术研究区域大气环境中PM2.5／PM10空间分布的方法,并在2004年12月进行了宁波市全市域PM2.5／PM10空间分布的研究。数据显示：相同路径所代表的地区PM2.5和PM10具有很好的相关性,多数路径上PM2.5与PM10数据的相关系数平方在0．95以上,而不同路径上PM2.5与PM10的比值不同。文中给出了宁波市PM2.5／PM10污染的空间分布图,直观地显示出PM2.5／PM10污染的空间分布情况,突出了污染的重点点位和地区。     

Particulate emissions from U.S. Department of Defense artillery backblast testing

There is a dearth of information on dust emissions from sources that are unique to the U.S. Department of Defense testing and training activities. However, accurate emissions factors are needed for these sources so that military installations can prepare accurate particulate matter (PM) emission inventories. One such source, coarse and fine PM (PM10 and PM2.5) emissions from artillery backblast testing on improved gun positions, was characterized at the Yuma Proving Ground near Yuma, AZ, in October 2005. Fugitive emissions are created by the shockwave from artillery pieces, which ejects dust from the surface on which the artillery is resting. Other contributions of PM can be attributed to the combustion of the propellants. For a 155-mm howitzer firing a range of propellant charges or zones, amounts of emitted PM10 ranged from -19 g of PM10 per firing event for a zone 1 charge to 92 g of PM10 per firing event for a zone 5. The corresponding rates for PM2.5 were approximately 9 g of PM2.5 and 49 g of PM2.5 per firing. The average measured emission rates for PM1o and PM2.5 appear to scale with the zone charge value. The measurements show that the estimated annual contributions of PM10 (52.2 t) and PM2.5 (28.5 t) from artillery backblast are insignificant in the context of the 2002 U.S. Environment Protection Agency (EPA) PM emission inventory. Using national-level activity data for artillery fire, the most conservative estimate is that backblast would contribute the equivalent of 5 x 10(-4) % and 1.6 x 10(-3)% of the annual total PM10 and PM2.5 fugitive dust contributions, respectively, based on 2002 EPA inventory data.     

In-stack condensible particulate matter measurements and issues

Particulate matter (PM) emitted from fossil fuel-fired units can be classified as either filterable or condensible PM. Condensible PM typically is not measured because federal and most state regulations do not require sources to do so. To determine the magnitude of condensible PM emissions relative to filterable PM emissions and to better understand condensible PM measurement issues, a review and analysis of actual U.S. Environmental Protection Agency (EPA) Method 202 (for in-stack condensible PM10) and EPA Method 201/201A (for in-stack filterable PM10) results were conducted. Methods 202 and 201/201A results for several coal-burning boilers showed that the condensible PM, on average, comprises approximately three-fourths (76%) of the total PM10 stack emissions. Methods 202 and 201/201A results for oil- and natural gas-fired boilers showed that the condensible PM, on average, comprises 50% of the total PM10 stack emissions. Methods 202 and 201/201A results for oil-, natural gas-, and kerosene-fired combustion turbines showed that the condensible PM, on average, comprises 69% of the total PM10 stack emissions. Based on these limited measurements, condensible PM can make a significant contribution to total PM10 emissions for fossil fuel-fired units. A positive bias (indicating more condensible PM than is actually emitted) may exist in the measured data due to the conversion of dissolved sulfur dioxide to sulfate compounds in the sampling procedure. In addition, these Method 202 results confirm that condensible PM, on average, is composed mostly of inorganic matter, regardless of the type of fuel burned.     

宁波市大气可吸入颗粒物PM1o和PM2.5的源解析研究

在宁波市布设4个代表性点位,于2010年春季、夏季和冬季进行大气PM10和PM2.s的采样,同时采集了多种颗粒物源样品,建立了PM10、PM2.5和源样品的化学成分谱.采用化学质量平衡模型(CMB)对宁波市PM10、PM2.5进行源解析.结果表明,城市扬尘、煤烟尘、机动车尾气尘是宁波市PM10、PM2.5的3大污染源,...     

Monitoring and source apportionment of particulate matter near a large phosphorus production facility

A source apportionment study was conducted to identify sources within a large elemental phosphorus plant that contribute to exceedances of the National Ambient Air Quality Standards (NAAQS) for 24-hr PM10. Ambient data were collected at three monitoring sites from October 1996 through July 1999, and included the following: 24-hr PM10 mass, 24-hr PM2.5 and PM10-2.5 mass and chemistry, continuous PM10 and PM2.5 mass, continuous meteorological data, and wind-direction-resolved PM2.5 and PM10 mass and chemistry. Ambient-based receptor modeling and wind-directional analysis were employed to help identify major sources or source locations and source contributions. Fine-fraction phosphate was the dominant species observed during PM10 exceedances, though in general, resuspended coarse dusts from raw and processed materials at the plant were also needed to create an exceedance. Major sources that were identified included the calciners, the CO flares, process-related dust, and electric-arc furnace operations.     

Field evaluation of particulate matter measurements using tapered element oscillating microbalance in a layer house

The tapered element oscillating microbalance (TEOM) is one type of continuous ambient particulate matter (PM) monitor. Adsorption and desorption of moisture and semivolatile species may cause positive or negative artifacts in TEOM PM mass measurement. The objective of this field study was to investigate possible uncertainties associated with TEOM measurements in the poultry operation environment. For comparisons of TEOM with filter-based gravimetric method, four instruments (TEOM-PM10, low-volume PM10 sampler TEOM-PM2.5, and PM2.5 speciation sampler) were collocated and tested inside a poultry house for PM2.5 and PM10 (PM with aerodynamic equivalent diameter < or =2.5 and < or =10 microm, respectively) measurements. Fifteen sets of 24-hr PM10 concentrations and 13 sets of 24-hr PM2.5 measurements were obtained. Results indicate that compared with filter-based gravimetric method, TEOM gave significantly lower values of both PM10 and PM2.5 mass concentrations. For PM10, the average ratio of TEOM to the gravimetric method was 0.936. For PM2.5, the average ratio of TEOM to the gravimetric method was 0.738. Particulate matter in the poultry houses possibly contains semivolatile compounds and moisture due to high levels of relative humidity (RH) and gas pollutants. The internal heating mechanism of the TEOM may cause losses in mass through volatilization. To investigate the effects of TEOM settings on concentration measurements, the heaters of two identical TEOMs were set at 50 degrees C, 30 degrees C, or no heating at all. They were collocated and tested for total suspended particle (TSP), PM10, and PM25 measurements in layer house for 6 weeks. For all TSR PM10, and PM2.5 measurements, the internal TEOM temperature setting had a significant effect (P < 0.05). Significantly higher PM mass concentrations were measured at lower temperature settings. The effects of environmental (i.e., temperature, RH, NH3 and CO2 concentrations) and instrumental (i.e., filter loading and noise) parameters on PM measurements were also assessed using regression analysis.     

Source apportionment of PM10 and PM2.5 in five Chilean cities using factor analysis

Chile is a fast-growing country with important industrial activities near urban areas. In this study, the mass and elemental concentrations of PM10 and PM2.5 were measured in five major Chilean urban areas. Samples of particles with diameter less than 10 microm (PM10) and 2.5 microm (PM2.5) were collected in 1998 in Iquique (northern Chile), Valparaiso, Vi?a del Mar, Rancagua (central Chile), and Temuco (southern Chile). Both PM10 and PM2.5 annual mean concentrations (PM10: 56.9-77.6 microg/m3; PM2.5: 22.4-42.6 microg/m3) were significantly higher than the corresponding European Union (EU) and U.S. Environmental Protection Agency (EPA) air quality standards. Moreover, the 24-hr PM10 and PM2.5 U.S. standards were exceeded infrequently for some of the cities (Rancagua and Valparaiso). Elements ranging from Mg to Pb were detected in the aerosol samples using X-ray fluorescence (XRF). For each of the five cities, factor analysis (FA) was applied to identify and quantify the sources of PM10 and PM2.5. The agreement between calculated and measured mass and elemental concentrations was excellent in most of the cities. Both natural and anthropogenic sources were resolved for all five cities. Soil and sea were the most important contributors to coarse particles (PM10-PM2.5), whereas their contributions to PM2.5 were negligible. Emissions from Cu smelters and oil refineries (and/or diesel combustion) were identified as important sources of PM2.5, particularly in the industrial cities of Rancagua, Valparaiso, and Vi?a del Mar. Finally, motor vehicles and wood burning were significant sources of both PM2.5 and PM10 in most of the cities (wood burning was not identified in Iquique).     

Contribution of harbour activities to levels of particulate matter in a harbour area: Hada Project-Tarragona Spain

The present study seeks to estimate the impact of harbour activities on PM10 levels based on a complete chemical characterisation of 90 PM10 samples periodically collected between September 2004 and September 2005 in the harbour of Tarragona as part of the HADA (LIFE Program EC) project. Interpretation of the time series of major and trace PM10 components allowed us to identify peaks of PM10 components related to the activities in the harbour. A factor analysis of PM10 enabled us to identify the crustal, traffic, secondary and sea spray sources, and one other source related to the re-suspension of materials handled in the harbour. The multi-linear regression analysis demonstrated a high anthropogenic contribution (62%) for PM10 at the harbour, mainly related to traffic (34% of PM10). Comparison with an earlier study, using the same methodology, at an urban background monitoring station in Tarragona, showed a good correlation for the annual average concentrations of most PM10 components at the two stations. At the harbour higher concentrations were obtained for tracers (P and Mn, and V and Ni in a lesser extent) of some mineral bulk cargo materials. Re-suspension of loose materials by means of wind and/or traffic was identified as one of the major contributors to PM10 in the harbour. Abatement strategies designed to reduce levels of PM10 in the harbour and nearby areas are provided.