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.     

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.     

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.     

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.     

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.     

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%。     

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.     

A comprehensive particulate matter monitoring system and dosimetry-based ambient particulate matter standards

A numerical particulate matter (PM) measurement model is developed to characterize and evaluate PM sampling methods. Simulations are conducted using the model to evaluate currently widely used PM samplers, including Federal Reference Method (FRM) samplers. The simulations show that current PM samplers are very vulnerable to both changes in measurement target (i.e., natural variability of particle size distribution) and the sampler's design, manufacturing, and operating conditions, potentially resulting in significant errors in the monitoring data. The numerical model is used in conjunction with two types of commercially available PM monitoring devices to form a Comprehensive Particulate Matter Monitoring System (CPMMS). The first type of device can be any mass-based PM monitor with a well-defined sampling efficiency curve. The second type of device is one capable of measuring particle size distribution with a reasonably good relative accuracy between size categories but not necessarily accurate in measuring absolute mass concentrations. This study shows that CPMMS can produce much higher quality PM monitoring data than the current PM samplers under the same conditions. In addition, unlike past and current PM monitoring data such as total suspended particulates, coarse PM (PM10), fine PM (PM2.5), etc., the CPMMS monitoring data will survive changes in PM regulatory definition. A new concept, dosimetry-based PM metrics and standards, is proposed to define ambient PM level based on the deposition fraction of particles in the human respiratory tract. The dosimetry-based PM metrics is more meaningful because it correlates the ambient PM level with the portion that can be deposited in the respiratory tract without an arbitrary cutoff particle diameter. CPMMS makes dosimetry-based PM metrics and standards feasible.     

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.     

Assessment of human exposure to ambient particulate matter

Recent epidemiological studies have consistently shown that the acute mortality effects of high concentrations of ambient particulate matter (PM), documented in historic air pollution episodes, may also be occurring at the low to moderate concentrations of ambient PM found in modern urban areas. In London in December 1952, the unexpected deaths due to PM exposure could be identified and counted as integers by the coroners. In modern times, the PM-related deaths cannot be as readily identified, and they can only be inferred as fractional average daily increases in mortality rates using sophisticated statistical filtering and analyses of the air quality and mortality data. The causality of the relationship between exposure to ambient PM and acute mortality at these lower modern PM concentrations has been questioned because of a perception that there is little significant correlation in time between the ambient PM concentrations and measured personal exposure to PM from all sources (ambient PM plus indoor-generated PM). This article shows that the critical factor supporting the plausibility of a linear PM mortality relationship is the expected high correlation in time of people's exposure to PM of ambient origin with measured ambient PM concentrations, as used in the epidemiological time series studies. The presence of indoor and personal sources of PM masks this underlying relationship, leading to confusion in the scientific literature about the strong underlying temporal relationship between personal exposure to PM of ambient origin and ambient PM concentration. The authors show that the sources of PM of non-ambient origin operate independently of the ambient PM concentrations, so that the mortality effect of non-ambient PM, if any, must be independent of the effects of the ambient PM exposures.     

Assessment of Human Exposure to Ambient Particulate Matter

ABSTRACT

Recent epidemiological studies have consistently shown that the acute mortality effects of high concentrations of ambient particulate matter (PM), documented in historic air pollution episodes, may also be occurring at the low to moderate concentrations of ambient PM found in modern urban areas. In London in December 1952, the unexpected deaths due to PM exposure could be identified and counted as integers by the coroners. In modern times, the PM-related deaths cannot be as readily identified, and they can only be inferred as fractional average daily increases in mortality rates using sophisticated statistical filtering and analyses of the air quality and mortality data. The causality of the relationship between exposure to ambient PM and acute mortality at these lower modern PM concentrations has been questioned because of a perception that there is little significant correlation in time between the ambient PM concentrations and measured personal exposure to PM from all sources (ambient PM plus indoor-generated PM).

This article shows that the critical factor supporting the plausibility of a linear PM mortality relationship is the expected high correlation in time of people's exposure to PM of ambient origin with measured ambient PM concentrations, as used in the epidemiological time series studies. The presence of indoor and personal sources of PM masks this underlying relationship, leading to confusion in the scientific literature about the strong underlying temporal relationship between personal exposure to PM of ambient origin and ambient PM concentration. The authors show that the sources of PM of non-ambient origin operate independently of the ambient PM concentrations, so that the mortality effect of non-ambient PM, if any, must be independent of the effects of the ambient PM exposures.     

Estimating Separately Personal Exposure to Ambient and Nonambient Particulate Matter for Epidemiology and Risk Assessment: Why and How

ABSTRACT

This paper discusses the legal and scientific reasons for separating personal exposure to PM into ambient and nonambient components. It then demonstrates by several examples how well-established models and data typically obtained in exposure field studies can be used to estimate both individual and community average exposure to ambient-generated PM (ambient PM outdoors plus ambient PM that has infiltrated indoors), indoor-generated PM, and personal activity PM. Ambient concentrations are not highly correlated with personal exposure to nonambient PM or total PM but are highly correlated with personal exposure to ambient-generated PM. Therefore, ambient concentrations may be used in epidemiology as an appropriate surrogate for personal exposure to ambient-generated PM. Suggestions are offered as to how exposure to ambient-generated PM may be obtained and used in epidemiology and risk assessment.     

Estimating separately personal exposure to ambient and nonambient particulate matter for epidemiology and risk assessment: why and how

This paper discusses the legal and scientific reasons for separating personal exposure to PM into ambient and nonambient components. It then demonstrates by several examples how well-established models and data typically obtained in exposure field studies can be used to estimate both individual and community average exposure to ambient-generated PM (ambient PM outdoors plus ambient PM that has infiltrated indoors), indoor-generated PM, and personal activity PM. Ambient concentrations are not highly correlated with personal exposure to nonambient PM or total PM but are highly correlated with personal exposure to ambient-generated PM. Therefore, ambient concentrations may be used in epidemiology as an appropriate surrogate for personal exposure to ambient-generated PM. Suggestions are offered as to how exposure to ambient-generated PM may be obtained and used in epidemiology and risk assessment.     

The relationship between real-time and time-integrated coarse (2.5-10 micrm), intermodal (1-2.5 microm), and fine (<2.5 microm) particulate matter in the Los Angeles basin

A periodic review of the National Ambient Air Quality Standards for Particulate Matter by the U.S. Environmental Protection Agency (EPA) will assess the standards with respect to levels, particle size, and averaging times. Some members of the scientific community in the United States and Europe have suggested the use of PM1 instead of PM2.5 as the fine particle measurement standard. This proposed standard is intended to reduce the influence of coarse particle sources on PM2.5, because some evidence suggests that PM1-2.5 is dominated by coarse particulate matter (PM) sources. In this study, coarse (PM2.5-10), intermodal (PM1-2.5), and fine (PM2.5) mass concentrations at four different sites are measured with continuous and time-integrated sampling devices. The main objective is to compare variations in these three size ranges while considering the effects of location, sources, weather, wind speed, and wind direction. Results show strong correlations between PM1 and intermodal PM in receptor sites. The contribution of PM1-2.5 to PM2.5 is highest in the summer months, most likely due to enhanced long-range transport. Coarse PM is poorly correlated with intermodal PM. Continuous data suggest that PM1 is growing into PM1-2.5 via complex processes involving stagnation of the aerosol during high relative humidity conditions, followed by advection during daytime hours.     

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.     

Windblown dust contributes to high PM2.5 concentrations

The revised National Ambient Air Quality Standards for PM include fine particulate standards based upon mass measurements of PM2.5. It is possible in arid and semi-arid regions to observe significant coarse mode intrusion in the PM2.5 measurement. In this work, continuous PM10, PM2.5, and PM1.0 were measured during several windblown dust events in Spokane, WA. PM2.5 constituted approximately 30% of the PM10 during the dust event days, compared with approximately 48% on the non-dusty days preceding the dust events. Both PM10 and PM2.5 were enhanced during the dust events. However, PM1.0 was not enhanced during dust storms that originated within the state of Washington. During a dust storm that originated in Asia and impacted Spokane, PM1.0 was also enhanced, although the Asian dust reached Washington during a period of stagnation and poor dispersion, so that local sources were also contributing to high particulate levels. The "intermodal" region of PM, defined as particles ranging in aerodynamic size from 1.0 to 2.5 microns, was found to represent a significant fraction of PM2.5 (approximately 51%) during windblown dust events, compared with 28% during the non-dusty days before the dust events.     

Chemical speciation of PM2.5 and PM10 in south Phoenix, AZ, USA

Phoenix, AZ, experiences high particulate matter (PM) episodes, especially in the wintertime. The spatial variation of the PM concentrations and resulting differences in exposure is of particular concern. In this study, PM2.s (PM with aerodynamic diameter <2.5 microm) and PM10 (PM with aerodynamic diameter <10 microm) samples were collected simultaneously from the east and west sides of South Phoenix and at a control site in Tempe and analyzed for trace elements and bulk elemental and organic carbon. Measurements showed that although PM2.5 concentrations had similar trends in temporal scale across all sites, concentrations of PM10 did not. The difference in PM10 concentrations and fluctuation across the three sites suggest effects of a local soil source as evidenced by high concentrations of Al, Ca, and Fe in PM10. K and anthropogenic elements (e.g., Cu, Pb, and Zn) in PM2.5 samples on January 1 were strikingly high, suggesting the influence of New Year's fireworks. Concentrations of toxic elements (e.g., Pb) in the study presented here are not different from similar studies in other U.S. cities. Application of principal component analysis indicated two broad categories of emission sources--soil and combustion--together accounting for 80 and 90% of variance, respectively, in PM2.5 and PM10. The soil and combustion components explained approximately 60 and 30% of the variance in PM10, respectively, whereas combustion sources dominated PM2.5 (>50% variance). Many elements associated with anthropogenic sources were highly enriched, with enrichment factors in PM2.5 an order of magnitude higher than in PM10 relative to surface soil composition in the study area.     

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.     

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。