Fine particulate matter and carbon monoxide exposure concentrations in urban street transport microenvironments

Personal exposure studies are crucial alongside microenvironment and ambient studies in order to get a better understanding of the health risks posed by fine particulate matter and carbon monoxide in the urban transport microenvironment and for making informed decisions to manage and reduce the health risks. Studies specifically assessing the PM_2.5, ultrafine particle count and carbon monoxide personal exposure concentrations of adults in an urban transport microenvironment have steadily increased in number over the last decade. However, no recent collective summary is available, particularly one which also considers ultrafine particles; therefore, we present a review of the personal exposure concentration studies for the above named pollutants on different modes of surface transportation (walking, cycling, bus, car and taxi) in the urban transport microenvironment. Comparisons between personal exposure measurements and concentrations recorded at fixed monitoring sites are considered in addition to the factors influencing personal exposure in the transport microenvironment.In general, the exposure studies examined revealed pedestrians and cyclists to experience lower fine particulate matter and CO exposure concentrations in comparison to those inside vehicles—the vehicle shell provided no protection to the passengers. Proximity to the pollutant sources had a significant impact on exposure concentration levels experienced, consequently individuals should be encouraged to use back street routes. Fixed monitoring stations were found to be relatively poor predictors of CO and PM_2.5 exposure concentration levels experienced by individuals in the urban transport microenvironment. Although the mode of transport, traffic and meteorology parameters were commonly identified as significant factors influencing exposure concentrations to the different pollutants under examination, a large amount of the exposure concentration variation in the exposure studies remained unexplained.     

Fine particulate matter emissions inventories: comparisons of emissions estimates with observations from recent field programs

Emissions inventories of fine particulate matter (PM2.5) were compared with estimates of emissions based on data emerging from U.S. Environment Protection Agency Particulate Matter Supersites and other field programs. Six source categories for PM2.5 emissions were reviewed: on-road mobile sources, nonroad mobile sources, cooking, biomass combustion, fugitive dust, and stationary sources. Ammonia emissions from all of the source categories were also examined. Regional emissions inventories of PM in the exhaust from on-road and nonroad sources were generally consistent with ambient observations, though uncertainties in some emission factors were twice as large as the emission factors. In contrast, emissions inventories of road dust were up to an order of magnitude larger than ambient observations, and estimated brake wear and tire dust emissions were half as large as ambient observations in urban areas. Although comprehensive nationwide emissions inventories of PM2.5 from cooking sources and biomass burning are not yet available, observational data in urban areas suggest that cooking sources account for approximately 5-20% of total primary emissions (excluding dust), and biomass burning sources are highly dependent on region. Finally, relatively few observational data were available to assess the accuracy of emission estimates for stationary sources. Overall, the uncertainties in primary emissions for PM2.s are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods.     

Acute effects of particulate matter with different sizes on respiratory mortality in Shenzhen,China

Environmental Science and Pollution Research - There are relatively few studies that focus on the health effects of exposure to size-specific particles on respiratory mortality in China. We aimed...     

Theoretical study of the impact of particulate matter gravitational settling on ambient coarse particulate matter monitoring for agricultural emissions

The particle size distributions (PSDs) of particulate matter (PM) in the downwind plume from simulated sources of a cotton gin were analyzed to determine the impact of PM settling on PM monitoring. The PSD of PM in a plume varies as a function of gravitational settling. Gravitational settling has a greater impact on the downwind PSD from sources with PSDs having larger mass median diameters (MMDs). The change in PSD is a function of the source PSD of emitted PM, wind speed, and downwind distance. Both MMD and geometric standard deviation (GSD) in the downwind plume decrease with an increase in downwind distance and source MMD. The larger the source MMD, the greater the change in the downwind MMD and GSD. Also, the greater the distance from the source to the sampler, the greater the change in the downwind MMD and GSD. Variations of the PSD in the downwind plume significantly impact PM10 sampling errors associated with the U.S. Environmental Protection Agency (EPA) PM10 samplers. For the emission sources with MMD > 10 microm, the PM10 oversampling rate increases with an increase in downwind distance caused by the decrease of GSD of the PSD in the downwind plume. Gravitational settling of particles does not help reduce the oversampling problems associated with the EPA PM10 sampler. Furthermore, oversampling rates decrease with an increase of the wind speed.     

Fine particulate matter and visibility in the Lake Tahoe Basin: chemical characterization, trends, and source apportionment

Speciated PM2.5 (particulate matter with an aerodynamic diameter相似文献   

Size fraction of hazardous particulate matter governing the respiratory deposition and inhalation risk in the highly polluted city Delhi

Environmental Science and Pollution Research - Delhi has been identified as one of the highly polluted cities in the world and recently associated with the highest population weighted PM2.5...     

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains: Part II. Fine particulate matter and visibility

As part of the Southern Appalachian Mountains Initiative, a comprehensive air quality modeling system was developed to evaluate potential emission control strategies to reduce atmospheric pollutant levels at the Class I areas located in the Southern Appalachian Mountains. Six multiday episodes between 1991 and 1995 were simulated, and the skill of the modeling system was evaluated. Two papers comprise various parts of this study. Part I details the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. This paper (part II) addresses issues involved with modeling particulate matter (PM) and its relationship to visibility. For most of the episodes, the fractional error was approximately 50% or less for the major constituents of the fine PM (i.e., sulfate [SO4] and organics) in the region. The mean normalized errors and fractional errors are generally larger for the NO3 and soil components, but these components are relatively small. Variations in modeling bias with pollutant levels were also examined. The model showed a systematic overestimation for low levels and an underestimation for high levels for most PM species. For ammonium, the model showed better performance at lower SO4 concentrations when the measured SO4 was assumed to be completely neutralized (ammonium sulfate) and better performance at higher SO4 concentrations when the partially neutralized (ammonium bisulfate) assumption was made. The contributions of various components of PM to reductions in visibility were also calculated; SO4 was found to be the major contributor.     

An evaluation of the protein mass of particulate matter

This research study provides the characterization of mass percent of protein-based particulate matter in total ambient particulate matter collected in a metropolitan area of NC. The project determined the percentages of protein-based ambient bioaerosols for particles in the 2.5–10 μm range and for particles in the range of 2.5 μm or less in 298 samples taken over a six-month period. The analysis of total protein mass was used as an all-inclusive indicator of biologically based aerosols. These organic bioaerosols may have nucleated with inorganic non-biological aerosols, or they may be combined with inert aerosols. The source of these bioaerosols may be any combination of pollen, mold, bacteria, insect debris, fecal matter, or dander, and they may induce irritational, allergic, infectious, and chemical responses in exposed individuals. Ambient samples of PM_2.5 and PM_10−2.5 were analyzed for gravimetric mass and total protein mass. The results for 19 of 24 sample periods indicated that between 1% and 4% of PM_10−2.5 and between 1% and 2% of PM_2.5 mass concentrations were made of ambient protein bioaerosols. (The remaining 5 of 24 sample periods yielded protein results which were below detectable limits.)     

Fine and coarse particulate matter chemical characterization in a heavily industrialized city in central Mexico during Winter 2003

This paper presents the results of the first reported study on fine particulate matter (PM) chemical composition at Salamanca, a highly industrialized urban area of Central Mexico. Samples were collected at six sites within the urban area during February and March 2003. Several trace elements, organic carbon (OC), elemental carbon (EC), and six ions were analyzed to characterize aerosols. Average concentrations of PM with aerodynamic diameter of less than 10 microm (PM10) and fine PM with aerodynamic diameter of less than 2.5 microm (PM2.5) ranged from 32.2 to 76.6 [g m(-3) and 11.1 to 23.7 microg m(-3), respectively. OC (34%), SO4= (25.1%), EC (12.9%), and geological material (12.5%) were the major components of PM2.5. For PM10 geological material (57.9%), OC (17.3%), and SO4= (9.7%) were the major components. Coarse fraction (PM,, -PM2.5), geological material (81.7%), and OC (8.6%) were the dominant species, which amounted to 90.4%. Correlation analysis showed that sulfate in PM2.5 was present as ammonium sulfate. Sulfate showed a significant spatial variation with higher concentrations to the north resulting from predominantly southwesterly winds above the surface layer and by major SO2 sources that include a power plant and refinery. At the urban site of Cruz Roja it was observed that PM2.5 mass concentrations were similar to the submicron fraction concentrations. Furthermore, the correlation between EC in PM2.5 and EC measured from an aethalometer was r(2) = 0.710. Temporal variations of SO2 and nitrogen oxide were observed during a day when the maximum concentration of PM2.5 was measured, which was associated with emissions from the nearby refinery and power plant. From cascade impactor measurements, the three measured modes of airborne particles corresponded with diameters of 0.32, 1.8, and 5.6 microm.     

Performance evaluation of the portable MiniVOL particulate matter sampler

The MiniVOL sampler is a popular choice for use in air quality assessments because it is portable and inexpensive relative to fixed site monitors. However, little data exist on the performance characteristics of the sampler. The reliability, precision, and comparability of the portable MiniVOL PM₁₀ and PM_2.5 sampler under typical ambient conditions are described in this paper. Results indicate that the MiniVOL (a) operated reliably and (b) yielded statistically similar concentration measurements when co-located with another MiniVOL (r²=0.96 for PM₁₀ measurements and r²=0.95 for PM_2.5 measurements). Thus, the characterization of spatial distributions of PM₁₀ and PM_2.5 mass concentrations with the MiniVOL can be accomplished with a high level of confidence. The MiniVOL also produced statistically comparable results when co-located with a Dichotomous Sampler (r²=0.83 for PM₁₀ measurements and r²=0.85 for PM_2.5 measurements) and a continuous mass sampling system (r²=0.90 for PM₁₀ measurements). Environmental factors such as ambient concentration, wind speed, temperature, and humidity may influence the relative measurement comparability between these sampling systems.     

Inflammatory effects of particulate matter air pollution

Environmental Science and Pollution Research - Air pollution is an important cause of non-communicable diseases globally with particulate matter (PM) as one of the main air pollutants. PM is...     

Fine particulate matter source apportionment for the Chemical speciation Trends Network site at Birmingham, Alabama, using Positive Matrix Factorization

The Positive Matrix Factorization (PMF) receptor model version 1.1 was used with data from the fine particulate matter (PM2.5) Chemical Speciation Trends Network (STN) to estimate source contributions to ambient PM2.5 in a highly industrialized urban setting in the southeastern United States. Model results consistently resolved 10 factors that are interpreted as two secondary, five industrial, one motor vehicle, one road dust, and one biomass burning sources. The STN dataset is generally not corrected for field blank levels, which are significant in the case of organic carbon (OC). Estimation of primary OC using the elemental carbon (EC) tracer method applied on a seasonal basis significantly improved the model's performance. Uniform increase of input data uncertainty and exclusion of a few outlier samples (associated with high potassium) further improved the model results. However, it was found that most PMF factors did not cleanly represent single source types and instead are "contaminated" by other sources, a situation that might be improved by controlling rotational ambiguity within the model. Secondary particulate matter formed by atmospheric processes, such as sulfate and secondary OC, contribute the majority of ambient PM2.5 and exhibit strong seasonality (37 +/- 10% winter vs. 55 +/- 16% summer average). Motor vehicle emissions constitute the biggest primary PM2.5 mass contribution with almost 25 +/- 2% long-term average and winter maximum of 29 +/- 11%. PM2.5 contributions from the five identified industrial sources vary little with season and average 14 +/- 1.3%. In summary, this study demonstrates the utility of the EC tracer method to effectively blank-correct the OC concentrations in the STN dataset. In addition, examination of the effect of input uncertainty estimates on model results indicates that the estimated uncertainties currently being provided with the STN data may be somewhat lower than the levels needed for optimum modeling results.     

Transport of atmospheric fine particulate matter: part 2--findings from recent field programs on the intraurban variability in fine particulate matter

Air quality field data, collected as part of the fine particulate matter Supersites Program and other field measurements programs, have been used to assess the degree of intraurban variability for various physical and chemical properties of ambient fine particulate matter. Spatial patterns vary from nearly homogeneous to quite heterogeneous, depending on the city, parameter of interest, and the approach or method used to define spatial variability. Secondary formation, which is often regional in nature, drives fine particulate matter mass and the relevant chemical components toward high intraurban spatial homogeneity. Those particulate matter components that are dominated by primary emissions within the urban area, such as black carbon and several trace elements, tend to exhibit greater spatial heterogeneity. A variety of study designs and data analysis approaches have been used to characterize intraurban variability. High temporal correlation does not imply spatial homogeneity. For example, there can be high temporal correlation but with spatial heterogeneity manifested as smooth spatial gradients, often emanating from areas of high emissions such as the urban core or industrial zones.     

Nitro-PAH in ambient particulate matter in the atmosphere of Athens

Nitrated polynuclear aromatic hydrocarbons (NPAH) with a molecular mass of 247 Daltons were found in soot collected in downtown Athens during a campaign performed in 1996. In particular, 2-nitrofluoranthene (2-NFa) and 2-nitropyrene (2-NPy), which are mainly related to photo-induced chemical processes occurring in the atmosphere, were more abundant than 1-nitropyrene (1-NPy) usually associated to motor vehicle exhaust.     

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.     

Size-segregated particulate matter and its association with respiratory deposition doses among outdoor exercisers in Dhanbad City,India

Regular exercise improves physiological processes and yields positive health outcomes. However, it is relatively less known that particulate matter (PM) exposure during outdoor exercises may increase several respiratory health problems depending on PM levels. In this study, the respiratory deposition doses (RDDs) in head airway (HD), tracheobronchial (TB), and alveolar (AL) regions of various PM size fractions (<10, <2.5, and <1 μm; PM₁₀, PM_2.5, and PM₁) were estimated in healthy male and female exercisers in urban outdoors and within house premises. The highest RDDs were found for PM during morning hours in winter compared with remaining periods. RDDs in AL region for males and females, respectively, were 34.7 × 10^?2 and 28.8 × 10^?2 µg min^?1 for PM₁₀, 65.7 × 10^?2 and 56.9 × 10^?2 µg min^?1 for PM_2.5, and 76.5 × 10^?2 and 66.3 × 10^?2 µg min^?1 for PM₁. The RDD values in AL region were significantly higher in PM₁ (27%) compared with PM_2.5 (13%) and PM₁₀ (2%) during exercise in all periods. This result showed that the morning peak hours in winter are more harmful to urban outdoor exercisers compared with other periods. This study also showed that the AL region would have been the main affected zone through fine particle (PM₁) to all the exercisers.

Implications: Size-segregated particle concentrations in urban outdoors and within house premises were measured. The highest respiratory deposition doses (RDDs) were found for PM during morning hours in winter compared with remaining periods. During light exercise, the RDD values in alveolar (AL) region for PM₁₀, PM_2.5, and PM₁ for male exercisers were significantly higher, 20.4%, 15.5%, and 15.4%, respectively, compared with female exercisers during morning peak hours in winter.     

Long-term assessment of particulate matter using CHIMERE model

Particulate matter (PM) and aerosols have became a critical pollutant and object of several research applications, due to their increasing levels, especially in urban areas, causing air pollution problems and thus effects on human health. The main purpose of this study is to perform a first long-term air quality assessment for Portugal, regarding aerosols and PM pollution. The CHIMERE chemistry-transport model, forced by the MM5 meteorological fields, was applied over Portugal for 2001 year, with 10 km horizontal resolution, using an emission inventory obtained from a spatial top-down disaggregation of the 2001 national inventory database. The evaluation model exercise shows a model trend to overestimate particulate pollution episodes (peaks) at urban sites, especially in winter season. This could be due to an underprediction of the winter model vertical mixing and also to an overestimation of PM emissions. Simulated inorganic components (ammonium and sulfate) and secondary organic aerosols (SOA) were compared to measurements taken at Aveiro (northwest coast of Portugal). An underestimation of the three components was verified. However, the model is able to predict their seasonal variation. Nevertheless, as a first approach, and despite the complex topography and coastal location of Portugal affected by sea salt natural aerosols emissions, the results obtained show that the model reproduces the PM levels, temporal evolution, and spatial patterns. The concentration maps reveal that the areas with high PM values are covered by the air quality monitoring network.