Atmospheric particulate matter in the city of Sao Carlos/SP, Brazil

This paper presents experimental data and source apportionment simulations on particulate matter (PM₁₀ and PM_2.5) in the atmosphere of Sao Carlos/SP, Brazil. Both a Hi-vol sampler equipped with glass fibre filters and a Dichotomous sampler with nucleopore filters were used. The collected material was analysed for total carbon, using a thermometric method, and for traces of several chemical species, using X-ray fluorescence spectroscopy. Source apportionment estimations were made with a chemical mass balance receptor model software (CMB8), with source profiles taken and adapted from the literature. The results indicate that both PM₁₀ concentration and source apportionment vary seasonally, and that vegetative burning can be a significant source of PM₁₀ in the dry season     

Transport and dispersion during wintertime particulate matter episodes in the San Joaquin Valley, California

Data analysis and modeling were performed to characterize the spatial and temporal variability of wintertime transport and dispersion processes and the impact of these processes on particulate matter (PM) concentrations in the California San Joaquin Valley (SJV). Radar wind profiler (RWP) and radio acoustic sounding system (RASS) data collected from 18 sites throughout Central California were used to estimate hourly mixing heights for a 3-month period and to create case studies of high-resolution diagnostic wind fields, which were used for trajectory and dispersion analyses. Data analyses show that PM episodes were characterized by an upper-level ridge of high pressure that generally produced light winds through the entire depth of the atmospheric boundary layer and low mixing heights compared with nonepisode days. Peak daytime mixing heights during episodes were -400 m above ground level (agl) compared with -800 m agl during nonepisodes. These episode/nonepisode differences were observed throughout the SJV. Dispersion modeling indicates that the range of influence of primary PM emitted in major population centers within the SJV ranged from -15 to 50 km. Trajectory analyses revealed that little intrabasin pollutant transport occurred among major population centers in the SJV; however, interbasin transport from the northern SJV and Sacramento regions into the San Francisco Bay Area (SFBA) was often observed. In addition, this analysis demonstrates the usefulness of integrating RWP/RASS measurements into data analyses and modeling to improve the understanding of meteorological processes that impact pollution, such as aloft transport and boundary layer evolution.     

Using a dispersion model to estimate emission rates of particulate matter from paved roads

From January 1996 to June 1997, we carried out a series of measurements to estimate emissions of PM₁₀ from paved roads in Riverside County, California. The program involved the measurement of upwind and downwind vertical profiles of PM₁₀, in addition to meteorological variables such as wind speed and vertical turbulent intensity. This information was analyzed using a new dispersion model that incorporates current understanding of micrometeorology and dispersion. The emission rate was inferred by fitting model predictions to measurements. The inferred emission factors ranged from 0.2 g VKT^-1 for freeways to about 3 g VKT^-1 for city roads. The uncertainty in these factors is estimated to be approximately a factor of two since the contributions of paved road PM₁₀ emissions to ambient concentrations were comparable to the uncertainty in the mean value of the measurement. At this stage, our best estimate of emission factor lies between 0.1 and 10 g VKT^-1; there is some indication that it is about 0.1 g VKT^-1 for heavily traveled freeways, and is an order of magnitude higher for older city roads. We found that measured silt loadings were poor predictors of emission factors.The measured emission factors imply that paved road emissions may contribute about 30% to the total PM₁₀ emissions from a high traffic area such as Los Angeles. This suggests that it is necessary to develop methods that are more reliable than the upwind–downwind concentration difference technique.     

Application of a microscale emission factor model for particulate matter to calculate vehicle-generated contributions to fine particulate emissions

This paper discusses the evaluation and application of a new generation of particulate matter (PM) emission factor model (MicroFacPM). MicroFacPM that was evaluated in Tuscarora Mountain Tunnel, Pennsylvania Turnpike, PA shows good agreement between measured and modeled emissions. MicroFacPM application is presented to the vehicle traffic on the main approach road to the Ambassador Bridge, which is one of the most important international border entry points in North America, connecting Detroit, MI, with Windsor, Ontario, Canada. An increase in border security has forced heavy-duty diesel vehicles to line up for several kilometers through the city of Windsor causing concern about elevated concentrations of ambient PM. MicroFacPM has been developed to model vehicle-generated PM (fine [PM2.5] and coarse < or = 10 microm [PM10]) from the on-road vehicle fleet, which in this case includes traffic at very low speeds (10 km/h). The Windsor case study gives vehicle generated PM2.5 sources and their breakdown by vehicle age and class. It shows that the primary sources of vehicle-generated PM2.5 emissions are the late-model heavy-duty diesel vehicles. We also applied CALINE4 and AERMOD in conjunction with MicroFacPM, using Canadian traffic and climate conditions, to describe the vehicle-generated PM2.5 dispersion near this roadway during the month of May in 2003.     

Regional scale modelling of particulate matter in the UK,source attribution and an assessment of uncertainties

The models HARM and ELMO are used to investigate the importance of different source categories contributing to total PM₁₀ (SIA, SOA and primary particulate matter) across the UK and the impact of uncertainties on both present day and future concentration estimates. Modelled concentrations of SIA (secondary inorganic aerosol) are compared against data from the UK's Nitric Acid and Aerosol Network and SOA (secondary organic aerosol) against measurements made at the Bush Estate, Edinburgh. These data indicate that the HARM/ELMO modelling approach comes close to achieving mass closure. Comparison with national maps of total PM₁₀ indicate that the models underestimate particulate matter concentrations around large conurbations, probably due to the localised nature of emissions of primary particulates in these areas and model scale. The models are used to attribute particulate matter to different source and size categories, assessing the relative importance of primaries, SIA and SOA; the contributions of anthropogenic and biogenic precursors of SOA; the relative importance of PM_coarse (PM₁₀–PM_2.5) and PM_fine (PM_2.5) and UK vs. other EMEP area sources. The implications of these attributions for emissions control policies are discussed. The impact of uncertainties in emissions of the sources of primaries, SIA and SOA are explored. For primary PM₁₀ and SOA this has been achieved through emissions scaling and for SIA using the GLUE (Generalised Likelihood Uncertainty Estimation) approach. The selection of acceptable model parameter sets has been based on the need to retain the capability to model deposition of S and N species. The impact of uncertainty on estimates of present day SIA concentrations is illustrated for sites in the Nitric Acid and Aerosol Network. A more limited assessment for 2010 has been carried out at the national scale, illustrating that inclusion of uncertainty can change modelled concentrations from no exceedance of current air quality objectives, to one of exceedance over large areas of south and east England.     

杭州市主城区大气颗粒物的酸缓冲能力及来源解析

通过酸缓冲能力的测定实验,研究杭州市主城区大气颗粒物的酸缓冲能力,并利用二重源解析技术,解析了大气颗粒物中碱性组分的来源.结果表明,杭州市主城区大气颗粒物呈弱碱性,对降水酸度有一定的缓冲作用,但作用较小.总体而言,TSP与PM10的酸缓冲能力与其浓度呈负相关,但相关关系不明显,TSP的酸缓冲能力比PM10强.Ca是影响大气颗粒物酸缓冲能力的关键化学组分.TSP的酸缓冲能力主要来自建筑水泥尘.     

Metals in airborne particulate matter from the first and second industrial complex area of Taejon city, Korea

To understand the metal distribution characteristics in a rapidly urbanized area, we collected and analyzed particulate matter (PM) samples for the metal concentrations. Using our measurement data for various metal species, we examined both the extent of metal pollution in the study area and the seasonality in their distribution characteristics. Results showed that each metal exhibited their occurrences in diverse concentration ranges over several orders of magnitude such as the mean values ranging from minimum value of 0.07 (Be) to maximum value of 1633 ng m(-3) (Fe). In addition, the extent of metal pollution in the study area was in general comparable with those typically observed from a strongly polluted urban area, if comparison was made with the results of previous studies. Examinations of their temporal distribution patterns indicated that most of metals tend to exhibit seasonal peaks during winter (or spring) seasons, similarly to the observed pattern for PMs. Moreover to explain the factors regulating their mobilization properties, the data were analyzed through the application of correlation analysis. Results of our correlation analysis showed that most metals can exhibit strong positive correlations each other, while they tend to be inversely correlated with most of important meteorological parameters (including air temperature and precipitation). Based on the overall results of our study, we conclude that the site may be strongly impacted by man-made sources but that many characteristics of their cycling are not significantly different from those generally observed from natural environments.     

Simulation of boundary layer trajectory dispersion sensitivity to soil moisture conditions: MM5 and Noah-based investigation

In this study, the sensitivity of trajectory paths to anomalous soil moisture was analyzed during three different synoptic episodes in June 2006. The MM5 and Noah land surface models were used to simulate the response of the planetary boundary layer. The HYSPLIT model was used for trajectory analysis. It was found that the response in horizontal lower-level wind field was larger at regions where vertical wind velocity changes were also large. In addition, the sensitivity to soil moisture changes was significant and localized where convective activity was well developed and synoptic effects did not dominate. A non-local effect was felt over the rest of the domain where convection was not present since the model atmosphere reacted as a whole to compensate for induced changes in vertical velocity. This finding was supported by the fact that domain averaged vertical velocities changes were of the order of 0.2 cm s^?1 or less at about 650 hPa and about 200 times smaller than modeled local vertical velocity changes. The largest change in horizontal wind field near the surface was found for weak synoptic events on June 11–12 and June 22–23 while the stronger synoptic event of June 17–18 showed smaller differences. These changes in wind field conditions impacted the transport and dispersion of pollutants. To quantify the sensitivity of air quality estimates to soil moisture uncertainty, we have used three well known measures of trajectory differences: the absolute horizontal transport deviation (AHTD), the relative horizontal transport deviation (RHTD) and the absolute vertical transport deviation (AVTD) for an ensemble of 98 trajectories departing from a region well within the computational domain. For the June 11–12 event it was found that for wet and dry soil moisture experiments, AHTD, RHTD, and AVGTD can reach values in the range 60–100 km, 10–20% and 500–900 m at 24 h run time, respectively. For the June 17–18 and June 22–23 events these values of trajectory differences were reduced more than half. These differences in behavior between time periods are largely attributed to the combined effects of synoptic forcing and the sensitivity of planetary boundary layer to soil moisture changes during well developed convection. The implication for air quality studies is that the soil moisture anomaly and related uncertainty in planetary boundary layer response needs to be incorporated in order to construct an ensemble of the most probable scenarios in which pollutants are released and transported throughout a given target region.     

Personal exposure to fine particulate matter concentrations in central business district of a tropical coastal city

In the present study, personal exposure to fine particulate matter (particulate matter with an aerodynamic diameter <2.5 μm [PM_2.5]) concentrations in an urban hotspot (central business district [CBD]) was investigated. The PM monitoring campaigns were carried out at an urban hotspot from June to October 2015. The personal exposure monitoring was performed during three different time periods, i.e., morning (8 a.m.?9 a.m.), afternoon (12.30 p.m.–1.30 p.m.), and evening (4 p.m.–5 p.m.), to cover both the peak and lean hour activities of the CBD. The median PM_2.5 concentrations were 38.1, 34.9, and 40.4 µg/m³ during the morning, afternoon, and evening hours on the weekends. During weekdays, the median PM_2.5 concentrations were 59.5, 29.6, and 36.6 µg/m³ in the morning, afternoon, and evening hours, respectively. It was observed that the combined effect of traffic emissions, complex land use, and micrometeorological conditions created localized air pollution hotspots. Furthermore, the total PM_2.5 lung dose levels for an exposure duration of 1 hr were 8.7 ± 5.7 and 12.3 ± 5.2 µg at CBD during weekends and weekdays, respectively, as compared with 2.5 ± 0.8 µg at the urban background (UB). This study emphasizes the need for mobile measurement for short-term personal exposure assessment complementing the fixed air quality monitoring.

Implications: Personal exposure monitoring at an urban hotspot indicated space and time variation in PM concentrations that is not captured by the fixed air quality monitoring networks. The short-term exposure to higher concentrations can have a significant impact on health that need to be considered for the health risk–based air quality management. The study emphasizes the need of hotspot-based monitoring complementing the already existing fixed air quality monitoring in urban areas. The personal exposure patterns at hotspots can provide additional insight into sustainable urban planning.     

Modelling the transport of suspended particulate matter by the Rhone River plume (France). Implications for pollutant dispersion

A model to simulate the transport of suspended particulate matter by the Rhone River plume has been developed. The model solves the 3D hydrodynamic equations, including baroclinic terms and a 1-equation turbulence model, and the suspended matter equations including advection/diffusion of particles, settling and deposition. Four particle classes are considered simultaneously according to observations in the Rhone. Computed currents, salinity and particle distributions are, in general, in good agreement with observations or previous calculations. The model also provides sedimentation rates and the distribution of different particle classes over the sea bed. It has been found that high sedimentation rates close to the river mouth are due to coarse particles that sink rapidly. Computed sedimentation rates are also similar to those derived from observations. The model has been applied to simulate the transport of radionuclides by the plume, since suspended matter is the main vector for them. The radionuclide transport model, previously described and validated, includes exchanges of radionuclides between water, suspended matter and bottom sediment described in terms of kinetic rates. A new feature is the explicit inclusion of the dependence of kinetic rates upon salinity. The model has been applied to 137Cs and 239,240Pu. Results are, in general, in good agreement with observations.     

Extending the Kolmogorov-Zurbenko filter: application to ozone, particulate matter, and meteorological trends

Tropospheric ozone (O3) and particulate matter (PM) are pollutants of great concern to air quality managers. Federal standards for these pollutants have been promulgated in recent years because of the known adverse effects of the pollutants on human health, the environment, and visibility. Local meteorological conditions exert a strong influence over day-to-day variations in pollutant concentrations; therefore, the meteorological signal must be removed in order for air quality planners and managers to examine underlying emissions-related trends and make better air quality management decisions for the future. Although the Kolmogorov-Zurbenko (KZ) filter has been widely used for this type of trend separation in O3 studies in the eastern United States, this article aims to extend the method in three key ways. First, whereas the KZ filter is known as a useful tool for O3 analysis, this study also evaluates its effectiveness when applied to PM. Second, the method was applied to Tucson, AZ, a city in the semi-arid southwestern United States (Southwest), to evaluate the appropriateness of the method in a region with weaker synoptic weather controls on air quality than the eastern United States. Third, additional forms of output were developed and tailored to be more applicable to decision-makers' needs through a partnership between academic researchers and air quality planners and managers. Results of the study indicate that the KZ filter is a useful method for examining emissions-related PM trends, resulting in small, but potentially significant, differences after adjustment. For the Tucson situation with weaker synoptic controls, the KZ method identified mixing height as a more important variable than has been found in other cities.     

Source apportionment of particulate matter (PM2.5) in an urban area using dispersion,receptor and inverse modelling

Air pollution emission inventories are the basis for air quality assessment and management strategies. The quality of the inventories is of great importance since these data are essential for air pollution impact assessments using dispersion models. In this study, the quality of the emission inventory for fine particulates (PM_2.5) is assessed: first, using the calculated source contributions from a receptor model; second, using source apportionment from a dispersion model; and third, by applying a simple inverse modelling technique which utilises multiple linear regression of the dispersion model source contributions together with the observed PM_2.5 concentrations. For the receptor modelling the chemical composition of PM_2.5 filter samples from a measurement campaign performed between January 2004 and April 2005 are analysed. Positive matrix factorisation is applied as the receptor model to detect and quantify the various source contributions. For the same observational period and site, dispersion model calculations using the Air Quality Management system, AirQUIS, are performed. The results identify significant differences between the dispersion and receptor model source apportionment, particularly for wood burning and traffic induced suspension. For wood burning the receptor model calculations are lower, by a factor of 0.54, but for the traffic induced suspension they are higher, by a factor of 7.1. Inverse modelling, based on regression of the dispersion model source contributions and the PM_2.5 concentrations, indicates similar discrepancies in the emissions inventory. In order to assess if the differences found at the one site are generally applicable throughout Oslo, the individual source category emissions are rescaled according to the receptor modelling results. These adjusted PM_2.5 concentrations are compared with measurements at four independent stations to evaluate the updated inventory. Statistical analysis shows improvement in the estimated concentrations for PM_2.5 at all sites. Similarly, inverse modelling is applied at these independent sites and this confirms the validity of the receptor model results.     

Assessment of population exposure to particulate matter pollution in Chongqing, China

To determine the population exposure to PM(10) in Chongqing, China, we developed an indirect model by combining information on the time activity patterns of various demographic subgroups with estimates of the PM(10) concentrations in different microenvironments (MEs). The spatial and temporal variations of the exposure to PM(10) were illustrated in a geographical information system (GIS). The population weighted exposure (PWE) for the entire population was 229, 155 and 211 microg/m(3), respectively, in winter, summer and as the annual average. Indoor PM(10) level at home was the largest contributor to the PWE, especially for the rural areas where high pollution levels were found due to solid fuels burning. Elder people had higher PM(10) exposure than adults and youth, due to more time spent in indoor MEs. The highest health risk due to particulate was found in the city zone and northeast regions, suggesting that pollution abatement should be prioritized in these areas.     

An integrated MM5–CMAQ modeling approach for assessing trans-boundary PM10 contribution to the host city of 2008 Olympic summer games—Beijing,China

In this paper, an integrated MM5–CMAQ modeling approach was employed to investigate the PM₁₀ air pollution issue in Beijing, China, with a focus on assessing pollution contributions from surrounding provinces. A 2-level-nested grid domain with spatial resolutions of 36 and 12 km was designed for the study region. Seven monitoring stations across Beijing municipality were selected to provide hourly PM₁₀ measurement data. The months of January, April, July and October in 2002 were taken as target periods for model performance evaluation. Five emission scenarios were designed and run in order to quantitatively assess the trans-boundary PM₁₀ contributions. The results show that, while Beijing needs to take positive steps to reduce its own pollution emissions, much effort should also be placed on demanding more pollution reduction and better environmental performance from surrounding provinces.     

Cytotoxic, phytotoxic, and mutagenic appraisal to ascertain toxicological potential of particulate matter emitted from automobiles

Vehicular air pollution is a mounting health issue of the modern age, particularly in urban populations of the developing nations. Auto-rickshaws are not considered eco-friendly as to their inefficient engines producing large amount of particulate matter (PM), thus posing significant environmental threat. The present study was conducted to ascertain the cytotoxic, phytotoxic, and mutagenic potential of PM from gasoline-powered two-stroke auto-rickshaws (TSA) and compressed natural gas-powered four-stroke auto-rickshaws (FSA). Based on the increased amount of aluminum quantified during proton-induced X-ray emission analysis of PM from TSA and FSA, different concentrations of aluminum sulfate were also tested to determine its eco-toxicological potential. The MTT assay demonstrated significant (p?<?0.001) dose-dependent cytotoxic effects of different concentrations of TSA, FSA, and aluminum sulfate on BHK-21 cell line. LC₅₀ of TSA, FSA, and aluminum sulfate was quantified at 16, 11, and 23.8 μg/ml, respectively, establishing PM from FSA, a highly cytotoxic material. In case of phytotoxicity screening using Zea mays, the results demonstrated that all three tested materials were equally phytotoxic at higher concentrations producing significant reduction (p?<?0.001) in seed germination. Aluminum sulfate proved to be a highly phytotoxic agent even at its lowest concentration. Mutagenicity was assessed by fluctuation Salmonella reverse mutation assay adopting TA100 and TA98 mutant strains with (+S9) and without (?S9) metabolic activation. Despite the fact that different concentrations of PM from both sources, i.e., TSA and FSA were highly mutagenic (p?<?0.001) even at lower concentrations, the mutagenic index was higher in TSA. Data advocate that all tested materials are equally ecotoxic, and if the existing trend of atmospheric pollution by auto-rickshaws is continued, airborne heavy metals will seriously affect the normal growth of local inhabitants and increased contamination of agricultural products, which will amplify the dietary intake of the toxic elements and could result in genetic mutation or long-term health implications.     

An alternative way to determine the size distribution of airborne particulate matter

We developed and tested a methodology to extract both the size-segregated source apportionment of atmospheric aerosol and the size distribution of each detected element. The experiment is based on the parallel use of a standard low-volume sampler to collect Particulate Matter (PM) and an Optical Particle Counter (OPC). The approach is complementary to size-segregated PM sampling, and it was tested versus a 12-stage cascade impactor. Samples were collected inside the urban area of Genoa (Italy) and their elemental composition was measured by Energy Dispersive-X Ray Fluorescence (ED-XRF). Positive Matrix Factorization (PMF) was applied to time series of elemental concentrations to identify major PM sources, and both PM mass concentration and size-segregated particle number concentration were apportioned. Source profiles and temporal trends extracted by PMF were analyzed together with the OPC data to obtain the size distribution for several elements. The new methodology proved to be reliable for the PM apportionment as well as in providing the elemental concentrations in PM10, PM2.5, and PM1 (PM with aerodynamic diameter, D_ae < 10, 2.5, and 1 μm, respectively). The elemental size distributions are in good agreement with those obtained by the cascade impactor for several elements but some discrepancies, in particular for traffic emissions, are stressed and discussed in the text. The new methodology has two main advantages: it only requires standard semi-automatic sampling equipment and compositional analysis and it provides size-segregated information averaged over quite long periods (typically several months). This is particularly important since campaigns with cascade impactors are generally laborious and thus limited to short periods.     

Trends in the elemental composition of fine particulate matter in Santiago, Chile, from 1998 to 2003

Santiago, Chile, is one of the most polluted cities in South America. As a response, over the past 15 yr, numerous pollution reduction programs have been implemented by the environmental authority, Comisión Nacional del Medio Ambiente. This paper assesses the effectiveness of these interventions by examining the trends of fine particulate matter (PM(2.5)) and its associated elements. Daily fine particle filter samples were collected in Santiago at a downtown location from April 1998 through March 2003. Additionally, meteorological variables were measured continuously. Annual average concentrations of PM(2.5) decreased only marginally, from 41.8 microg/m3 for the 1998-1999 period to 35.4 microg/m3 for the 2002-2003 period. PM(2.5) concentrations exceeded the annual U.S. Environmental Protection Agency standard of 15 microg/m3. Also, approximately 20% of the daily samples exceeded the old standard of 65 microg/m3, whereas approximately half of the samples exceeded the new standard of 35 microg/m3 (effective in 2006). Mean PM(2.5) levels measured during the cold season (April through September) were three times higher than those measured in the warm season (October through March). Particulate mass and elemental concentration trends were investigated using regression models, controlling for year, month, weekday, wind speed, temperature, and relative humidity. The results showed significant decreases for Pb, Br, and S concentrations and minor but still significant decreases for Ni, Al, Si, Ca, and Fe. The larger decreases were associated with specific remediation policies implemented, including the removal of lead from gasoline, the reduction of sulfur levels in diesel fuel, and the introduction of natural gas. These results suggest that the pollution reduction programs, especially the ones related to transport, have been effective in reducing various important components of PM(2.5). However, particle mass and other associated element levels remain high, and it is thus imperative to continue the efforts to improve air quality, particularly focusing on industrial sources.     

DEARS particulate matter relationships for personal,indoor, outdoor,and central site settings for a general population

This analysis provides the initial summary of PM_2.5 mass concentrations relationships for all seasons and participants for a general population in the Detroit Exposure and Aerosol Research Study (DEARS). The summary presented highlights the utility of the new methodologies applied, in addition to summarizing the particulate matter (PM) data.Results include the requirement to adjust the exposure data for monitor wearing compliance and measured environmental tobacco smoke (ETS) levels, even though the study design specified a non-smoking household. A 40% wearing compliance acceptance level was suggested as necessary to balance minimizing exposure misclassification (from poor compliance) and having sufficient data to conduct robust statistical analyses. An ETS threshold level equivalent to adding more than 1.5 μg m^?3 to the collected sample was found to be necessary to detect changes in the personal exposure factor (F_pex). It is not completely clear why such a large threshold level was necessary.Statistically significant spatial PM_2.5 gradients were identified in three of the six DEARS neighborhoods in Wayne County. These were expected, given the number of strong, localized PM sources in the Detroit (Michigan) metro area. Some residential outdoor bias levels compared with the central site at Allen Park exceeded 15%. After adjusting for ETS biases, the outdoor contributions to the personal exposure were typically larger by factors from 1.75 to 2.2 compared with those of the non-outdoor sources. The outdoor contribution was larger in the summer than in the winter, which is consistent with the fractions of time spent outdoors in the summer vs. the winter (6.7% vs. 1.1% of the time).Mean personal PM_2.5 cloud levels for the general population DEARS cohort ranged from 1.5 to 3.8 (after ETS adjustment) and were comparable to those reported previously. The personal exposure collections indoors were typically at least 13 times greater than those contributed outdoors.     

Alternatives to the gravimetric method for quantification of diesel particulate matter near the lower level of detection

This paper is part of the Journal of the Air & Waste Management Association's 2010 special issue on combustion aerosol measurements. The issue is a combination of papers that synthesize and evaluate ideas and perspectives that were presented by experts at a series of workshops sponsored by the Coordinating Research Council that aimed to evaluate the current and future status of diesel particulate matter (DPM) measurement. Measurement of DPM is a complex issue with many stakeholders, including air quality management and enforcement agencies, engine manufacturers, health experts, and climatologists. Adoption of the U.S. Environmental Protection Agency 2007 heavy-duty engine DPM standards posed a unique challenge to engine manufacturers. The new standards reduced DPM emissions to the point that improvements to the gravimetric method were required to increase the accuracy and the sensitivity of the measurement. Despite these improvements, the method still has shortcomings. The objectives of this paper are to review the physical and chemical properties of DPM that make gravimetric measurement difficult at very low concentrations and to review alternative metrics and methods that are potentially more accurate, sensitive, and specific. Particle volatility, size, surface area, and number metrics are considered, as well as methods to quantify them. Although the authors believe that an alternative method is required to meet the needs of engine manufacturers, the methods reviewed in the paper are applicable to other areas where the gravimetric method detection limit is approached and greater accuracy and sensitivity are required. The paper concludes by suggesting a method to measure active surface area, combined with a method to separate semi-volatile and solid fractions to further increase the specificity of the measurement, has potential for reducing the lower detection limit of DPM and enabling engine manufacturers to reduce DPM emissions in the future.     

A procedure for use in estimating human exposure to particulate matter of ambient origin

Modern epidemiology has shown that fluctuations of mortality data are statistically significantly correlated with fluctuations of ambient particulate matter (PM) concentration data. This relation cannot be confounded by exposure to PM of indoor origin because the concentrations of ambient PM are not correlated with concentrations of PM of indoor origin. It has been suggested, given the above understanding, that modern PM exposure measurements and analysis should create separate estimates of exposure to all PM of ambient origin and exposure to all PM of nonambient origin (primarily of indoor origin), and not exposure to total PM. This paper reviews the developments of the form of the general microenvironmental mass balance equation that can be utilized for estimating human exposure to PM of ambient origin and for estimating the portion of total PM exposure that is attributable to nonambient origin PM. The equation is perfectly general and can be applied to conditions of time-varying factors that influence exposure, such as rapidly changing air-exchange rates in a home as doors and windows are opened and closed, and turning on and off air cleaners in a home. It is suggested that this procedure be applied in exposure assessment studies and validated using independent techniques of estimating exposure to PM of ambient origin available in the literature.