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1.
ABSTRACT

In population exposure studies, personal exposure to PM is typically measured as a 12- to 24-hr integrated mass concentration. To better understand short-term variation in personal PM exposure, continuous (1-min averaging time) nephelometers were worn by 15 participants as part of two U.S. Environmental Protection Agency (EPA) longitudinal PM exposure studies conducted in Baltimore County, MD, and Fresno, CA. Participants also wore iner-tial impactor samplers (24-hr integrated filter samples) and recorded their daily activities in 15-min intervals. In Baltimore, the nephelometers correlated well (R2 = 0.66) with the PM25 impactors. Time-series plots of personal nephelometer data showed each participant's PM exposure to consist of a series of peaks of relatively short duration. Activities corresponding to a significant instrument response included cooking, outdoor activities, transportation, laundry, cleaning, shopping, gardening, moving between microenvironments, and removing/putting on the instrument. On average, 63-66% of the daily PM exposure occurred indoors at home (about 2/3 of which occurred during waking hours), primarily due to the large amount of time spent in that location (an average of 7277%). Although not a reference method for measuring mass concentration, the nephelometer did help identify PM sources and the relative contribution of those sources to an individual's personal exposure.  相似文献   

2.
Particulate matter (PM) exposure data from the U.S. Environmental Protection Agency (EPA)-sponsored 1998 Baltimore and 1999 Fresno PM exposure studies were analyzed to identify important microenvironments and activities that may lead to increased particle exposure for select elderly (>65 years old) subjects. Integrated 24-hr filter-based PM2.5 or PM10 mass measurements [using Personal Environmental Monitors (PEMs)] included personal measurements, indoor and outdoor residential measurements, and measurements at a central indoor site and a community monitoring site. A subset of the participants in each study wore passive nephelometers that continuously measured (1-min averaging time) particles ranging in size from 0.1 to approximately 10 microm. Significant activities and locations were identified by a statistical mixed model (p < 0.01) for each study population based on the measured PM2.5 or PM10 mass and time activity data. Elevated PM concentrations were associated with traveling (car or bus), commercial locations (store, office, mall, etc.), restaurants, and working. The modeled results were compared to continuous PM concentrations determined by the nephelometers while participants were in these locations. Overall, the nephelometer data agreed within 6% of the modeled PM2.5 results for the Baltimore participants and within approximately 20% for the Fresno participants (variability was due to zero drift associated with the nephelometer). The nephelometer did not agree as well with the PM10 mass measurements, most likely because the nephelometer optimally responds to fine particles (0.3-2 microm). Approximately one-half (54 +/- 31%; mean +/- standard deviation from both studies) of the average daily PM2.5 exposure occurred inside residences, where the participants spent an average of 83 +/- 10% of their time. These data also showed that a significant portion of PM2.5 exposure occurred in locations where participants spent only 4-13% of their time.  相似文献   

3.
ABSTRACT

Particulate matter (PM) exposure data from the U.S. Environmental Protection Agency (EPA)-sponsored 1998 Baltimore and 1999 Fresno PM exposure studies were analyzed to identify important microenvironments and activities that may lead to increased particle exposure for select elderly (>65 years old) subjects. Integrated 24-hr filter-based PM2.5 or PM10 mass measurements [using Personal Environmental Monitors(PEMs)] included personal measurements, indoor and outdoor residential measurements, and measurements at a central indoor site and a community monitoring site. A subset of the participants in each study wore passive nephelometers that continuously measured (1-min averaging time) particles ranging in size from 0.1 to ~10 um. Significant activities and locations were identified by a statistical mixed model (p < 0.01) for each study population based on the measured PM2.5 or PM10 mass and time activity data. Elevated PM concentrations were associated with traveling (car or bus), commercial locations (store, office, mall, etc.), restaurants, and working.

The modeled results were compared to continuous PM concentrations determined by the nephelometers while participants were in these locations. Overall, the nephelometer data agreed within 6% of the modeled PM2.5 results for the Baltimore participants and within ~20% for the Fresno participants (variability was due to zero drift associated with the nephelometer). The nephelom-eter did not agree as well with the PM10 mass measurements, most likely because the nephelometer optimally responds to fine particles (0.3–2 um). Approximately one-half (54 ± 31%; mean ± standard deviation from both studies) of the average daily PM2.5 exposure occurred inside residences, where the participants spent an average of 83 ± 10% of their time. These data also showed that a significant portion of PM2.5 exposure occurred in locations where participants spent only 4–13% of their time.  相似文献   

4.
To provide a scientific basis for the selection and use of continuous monitors for exposure and/or health effects studies, and for compliance and episode measurements at strategic locations in the State of New Jersey, we evaluated the performance of seven continuous fine particulate matter (PM2.5) monitors in the present study. Gravimetric samplers, as reference methods, were collocated with realtime instruments in both laboratory and field tests. The results of intercomparison of real-time monitors showed that the two nephelometers used in this study correlated extremely well (r2 approximately 0.97), and two tapered element oscillating monitors (TEOM 1400 and TEOM filter dynamics measurement system [FDMS]) correlated well (r2 > 0.85), whereas two beta gauges displayed a weaker correlation (r2 < 0.6). During a summertime controlled (laboratory) evaluation, the measurements made with the gravimetric method correlated well with the 24-hr integrated measurements made with the real-time monitors. The SidePak nephelometer overestimated the particle concentration by a factor of approximately 3.4 compared with the gravimetric method. During a summertime field evaluation, the TEOM FDMS monitor reported approximately 30% higher mass concentration than the Federal Reference Method (FRM); and the difference could be explained by the loss of semi-volatile materials from the FRM sampler. Results also demonstrated that 24-hr average PM2.5 mass concentrations measured by beta gauges and TEOM (50 degrees C) in winter correlated well with the integrated gravimetric method. Seasonal differences were observed in the performance of the TEOM (50 degrees C) monitor in measuring the particle mass attributed to the higher semi-volatile material loss in the winter weather. In applying the realtime particulate matter monitoring data into Air Quality Index (AQI) reporting, the Conroy method and the 8-hr end-hour average method were both found to be suitable.  相似文献   

5.
We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (> 64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM2.5, PM10, SO4(2-), O3, NO2, SO2, and exhaust-related VOCs. Results of this study showed that longitudinal associations between ambient PM2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM2.5 exposures and resulting personal-ambient associations. Associations between personal PM2.5 exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM2.5 sources. Evidence for this was provided by SO4(2-) measurements, which can be thought of as a tracer for ambient PM2.5. For SO4(2-), personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM2.5 sources to personal PM2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments. Results also indicate that the potential for confounding by PM2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM2.5 exposures were not significantly correlated with personal exposures to PM2.5-10, PM2.5 of non-ambient origin, O3, NO2, and SO2. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM2.5 epidemiologic studies are unlikely to be due to confounding by the PM2.5 co-pollutants measured in this study.  相似文献   

6.
Measurements of 15-min average PM2.5 concentrations were made with a real-time light-scattering instrument at both outdoor (central monitoring sites in three communities) and indoor (residential) locations over two seasons in the Minneapolis-St. Paul metropolitan area. These data are used to examine within-day variability of PM2.5 concentrations indoors and outdoors, as well as matched indoor-to-outdoor (I/O) ratios. Concurrent gravimetric measurements of 24-hr average PM2.5 concentrations were also obtained as a way to compare real-time measures with this more traditional metric. Results indicate that (1) within-day variability for both indoor and outdoor 15-min average PM2.5 concentrations was substantial and comparable in magnitude to day-to-day variability for 24-hr average concentrations; (2) some residences exhibited substantial variability in indoor aerosol characteristics from one day to the next; (3) peak values for indoor short-term (15-min) average PM2.5 concentrations routinely exceeded 24-hr average outdoor values by factors of 3-4; and (4) relatively strong correlations existed between indoor and outdoor PM2.5 concentrations for both 24-hr and 15-min averages.  相似文献   

7.
In response to community concerns, the air quality impact of imploding a 22-story building in east Baltimore, MD, was studied. Time- and space-resolved concentrations of indoor and outdoor particulate matter (PM) (nominally 0.5-10 microm) were measured using a portable nephelometer at seven and four locations, respectively. PM10 levels varied in time and space; there was no measurable effect observed upwind of the implosion. The downwind peak PM10 levels varied with distance (54,000-589 microg/m3) exceeding pre-implosion levels for sites 100 and 1130 m 3000- and 20-fold, respectively. Estimated outdoor 24-hr integrated mass concentrations varied from 15 to 72 microg/m3. The implosion did not result in the U.S. Environmental Protection Agency (EPA) National Ambient Air Quality Standard (NAAQS) for PM10 being exceeded. X-ray fluorescence analysis indicated that the elemental composition was dominated by crustal elements: calcium (57%), silicon (23%), aluminum (7.6%), and iron (6.1%). Lead was above background but at a low level (0.17 microg/m3). Peak PM10 concentrations were short-lived; most sites returned to background within 15 min. No increase in indoor PM10 was observed even at the most proximate 250 m location. These results demonstrate that a building implosion can have a severe but short-lived impact on community air quality. Effective protection is offered by being indoors or upwind.  相似文献   

8.
This study compares an indoor-outdoor air-exchange mass balance model (IO model) with a chemical mass balance (CMB) model. The models were used to determine the contribution of outdoor sources and indoor resuspension activities to indoor particulate matter (PM) concentrations. Simultaneous indoor and outdoor measurements of PM concentration, chemical composition, and air-exchange rate were made for five consecutive days at a single-family residence using particle counters, nephelometers, and filter samples of integrated PM with an aerodynamic diameter of less than or equal to 2.5 microm (PM2.5) and PM with an aerodynamic diameter of less than or equal to 5 microm (PM5). Chemical compositions were determined by inductively coupled plasma mass-spectrometry. During three high-activity days, prescribed activities, such as cleaning and walking, were conducted over a period of 4-6 hr. For the remaining two days, indoor activities were minimal. Indoor sources accounted for 60-89% of the PM2.5 and more than 90% of the PM5 for the high-activity days. For the minimal-activity days, indoor sources accounted for 27-47% of PM2.5 and 44-60% of the PM5. Good agreement was found between the two mass balance methods. Indoor PM2.5 originating outdoors averaged 53% of outdoor concentrations.  相似文献   

9.
Particle light scattering (Bsp) from nephelometers and fine particulate matter (PM2.5) mass determined by filter samplers are compared for summer and winter at 35 locations in and around California's San Joaquin Valley from December 2, 1999 to February 3, 2001. The relationship is described using particle mass scattering efficiency (sigmasp) derived from linear regression of Bsp on PM2.5 that can be applied to estimated PM2.5 from nephelometer data within the 24-hr filter sampling periods and between the every-6th-day sampling frequency. An average of sigmaSp = 4.9 m2/g was found for all of the sites and seasons; however, sigmasp averaged by site type and season provided better PM2.5 estimates. On average, the sigmasp was lower in summer than winter, consistent with lower relative humidities, lower fractions of hygroscopic ammonium nitrate, and higher contributions from fugitive dust. Winter average sigmasp were similar at non-source-dominated sites, ranging from 4.8 m2/g to 5.9 m2/g. The sigmasp was 2.3 m2/g at the roadside, 3.7 m2/g at a dairy farm, and 4.1 m2/g in the Kern County oilfields. Comparison of Bsp from nephelometers with and without a PM2.5 inlet at the Fresno Supersite showed that coarse particles contributed minor amounts to light scattering. This was confirmed by poorer correlations between Bsp and coarse particulate matter measured during a fall sampling period.  相似文献   

10.
Individuals are exposed to particulate matter from both indoor and outdoor sources. The aim of this study was to compare the relative contributions of three sources of personal exposure to fine particles (PM2.5) by using chemical tracers. The study design incorporated repeated 24-hr personal exposure measurements of air pollution from 28 cardiac-compromised residents of Toronto, Ontario, Canada. Each study participant wore the Rupprecht & Patashnick ChemPass Personal Sampling System 1 day a week for a maximum of 10 weeks. During their individual exposure measurement days the subjects reported to have spent an average of 89% of their time indoors. Particle phase elemental carbon, sulfate, and calcium personal exposure data were used in a mixed-effects model as tracers for outdoor PM2.5 from traffic-related combustion, regional, and local crustal materials, respectively. These three sources were found to contribute 13% +/- 10%, 17% +/- 16%, and 7% +/- 6% of PM2.5 exposures. The remaining fraction of the personal PM2.5 is hypothesized to be predominantly related to indoor sources. For comparison, central site outdoor PM2.5 measurements for the same dates as personal measurements were used to construct a receptor model using the same three tracers. In this case, traffic-related combustion, regional, and local crustal materials were found to contribute 19% +/- 17%, 52% +/- 22%, and 10% +/- 7%, respectively. Our results indicate that the three outdoor PM2.5 sources considered are statistically significant contributors to personal exposure to PM2.5. Our results also suggest that among the Toronto subjects, who spent a considerable amount of time indoors, exposure to outdoor PM2.5 includes a greater relative contribution from combustion sources compared with outdoor PM2.5 measurements where regional sources are the dominant contributor.  相似文献   

11.
Time-resolved data is needed for public notification of unhealthful air quality and to develop an understanding of atmospheric chemistry, including insights important to control strategies. In this research, continuous fine particulate matter (PM2.5) mass concentrations were measured with tapered element oscillating microbalances (TEOMs) across New Jersey from July 1997 to June 1998. Data features indicating the influence of local sources and long-distance transport are examined, as well as differences between 1-hr maxima and 24-hr average concentrations that might be relevant to acute health effects. Continuous mass concentrations were not significantly different from filter-collected gravimetric mass concentrations with 95% confidence intervals during any season. Annual mean PM2.5 concentrations from July 1997 to June 1998 were 17.3, 16.4, 14.1, and 15.3 micrograms/m3 at Newark, Elizabeth, New Brunswick, and Camden, NJ, respectively. Monthly averaged 24- and 1-hr daily maximum PM2.5 concentrations suggest the existence of a high PM2.5 (May-October) and a low PM2.5 (November-April) season. PM2.5 magnitudes and temporal trends were very similar across the state during high PM2.5 events. In fact, the between-site coefficients of determination (R2) for daily PM2.5 measurements were 84-98% for June and July. Additionally, during the most pronounced PM2.5 episode, PM2.5 concentrations closely tracked the daily maximum 1-hr O3 concentrations. These observations suggest the importance of transport and atmospheric chemistry (i.e., secondary formation) to PM2.5 episodes in New Jersey. The influence of local sources was observed in diurnal concentration profiles and annual average between-site differences. Urban wintertime data illustrate that high 1-hr maximum PM2.5 concentrations can occur on low 24-hr PM2.5 days.  相似文献   

12.
This paper presents a new statistical model designed to extend our understanding from prior personal exposure field measurements of urban populations to other cities where ambient monitoring data, but no personal exposure measurements, exist. The model partitions personal exposure into two distinct components: ambient concentration and nonambient concentration. It is assumed the ambient and nonambient concentration components are uncorrelated and add together; therefore, the model is called a random component superposition (RCS) model. The 24-hr ambient outdoor concentration is multiplied by a dimensionless "attenuation factor" between 0 and 1 to account for deposition of particles as the ambient air infiltrates indoors. The RCS model is applied to field PM10 measurement data from three large-scale personal exposure field studies: THEES (Total Human Environmental Exposure Study) in Phillipsburg, NJ; PTEAM (Particle Total Exposure Assessment Methodology) in Riverside, CA; and the Ethyl Corporation study in Toronto, Canada. Because indoor sources and activities (smoking, cooking, cleaning, the personal cloud, etc.) may be similar in similar populations, it was hypothesized that the statistical distribution of nonambient personal exposure is invariant across cities. Using a fixed 24-hr attenuation factor as a first approximation derived from regression analysis for the respondents, the distributions of nonambient PM10 personal exposures were obtained for each city. Although the mean ambient PM10 concentrations in the three cities varied from 27.9 micrograms/m3 in Toronto to 60.9 micrograms/m3 in Phillipsburg to 94.1 micrograms/m3 in Riverside, the mean nonambient components of personal exposures were found to be closer: 52.6 micrograms/m3 in Toronto; 52.4 micrograms/m3 in Phillipsburg; and 59.2 micrograms/m3 in Riverside. The three frequency distributions of the nonambient components of exposure also were similar in shape, giving support to the hypothesis that nonambient concentrations are similar across different cities and populations. These results indicate that, if the ambient concentrations were completely controlled and set to zero in all three cities, the median of the remaining personal exposures to PM10 would range from 32.0 micrograms/m3 (Toronto) to 34.4 micrograms/m3 (Phillipsburg) to 48.8 micrograms/m3 (Riverside). The highest-exposed 30% of the population in the three cities would still be exposed to 24-hr average PM10 concentrations of 47-74 micrograms/m3; the highest 20% would be exposed to concentrations of 56-92 micrograms/m3; the highest 10% to concentrations of 88-131 micrograms/m3; and the highest 5% to 133-175 micrograms/m3, due only to indoor sources and activities. The distribution for the difference between personal exposures and indoor concentrations, or the "personal cloud," also was similar in the three cities, with a mean of 30-35 micrograms/m3, suggesting that the personal cloud accounts for more than half of the nonambient component of PM10 personal exposure in the three cities. Using only the ambient measurements in Toronto, the nonambient data from THEES in Phillipsburg was used to predict the entire personal exposure distribution in Toronto. The PM10 exposure distribution predicted by the model showed reasonable agreement with the PM10 personal exposure distribution measured in Toronto. These initial results suggest that the RCS model may be a powerful tool for predicting personal exposure distributions and statistics in other cities where only ambient particle data are available.  相似文献   

13.
14.
As part of a large exposure assessment and health-effects panel study, 33 trace elements and light-absorbing carbon were measured on 24-hr fixed-site filter samples for particulate matter with an aerodynamic diameter <2.5 microm (PM2.5) collected between September 26, 2000, and May 25, 2001, at a central outdoor site, immediately outside each subject's residence, inside each residence, and on each subject (personal sample). Both two-way (PMF2) and three-way (PMF3) positive matrix factorization were used to deduce the sources contributing to PM2.5. Five sources contributing to the indoor and outdoor samples were identified: vegetative burning, mobile emissions, secondary sulfate, a source rich in chlorine, and a source of crustal-derived material. Vegetative burning contributed more PM2.5 mass on average than any other source in all microenvironments, with average values estimated by PMF2 and PMF3, respectively, of 7.6 and 8.7 microg/m3 for the outdoor samples, 4 and 5.3 microg/m3 for the indoor samples, and 3.8 and 3.4 microg/m3 for the personal samples. Personal exposure to the combustion-related particles was correlated with outdoor sources, whereas exposure to the crustal and chlorine-rich particles was not. Personal exposures to crustal sources were strongly associated with personal activities, especially time spent at school among the child subjects.  相似文献   

15.
To estimate plausible health effects associated with peak sulfur dioxide (SO2) levels from three coal-fired power plants in the Baltimore, Maryland, area, air monitoring was conducted between June and September 2013. Historically, the summer months are periods when emissions are highest. Monitoring included a 5-day mobile and a subsequent 61-day stationary monitoring study. In the stationary monitoring study, equipment was set up at four sites where models predicted and mobile monitoring data measured the highest average concentrations of SO2. Continuous monitors recorded ambient concentrations each minute. The 1-min data were used to calculate 5-min and 1-hr moving averages for comparison with concentrations from clinical studies that elicited lung function decrement and respiratory symptoms among asthmatics. Maximum daily 5-min moving average concentrations from the mobile monitoring study ranged from 70 to 84 ppb (183–220 µg/m3), and maximum daily 1-hr moving average concentrations from the mobile monitoring study ranged from 15 to 24 ppb (39–63 µg/m3). Maximum 5-min moving average concentrations from stationary monitoring ranged from 39 to 229 ppb (102–600 µg/m3), and maximum daily 1-hr average concentrations ranged from 15 to 134 ppb (40–351 µg/m3). Estimated exposure concentrations measured in the vicinity of monitors were below the lowest levels that have demonstrated respiratory symptoms in human clinical studies for healthy exercising asthmatics. Based on 5-min and 1-hr monitoring, the exposure levels of SO2 in the vicinity of the C.P. Crane, Brandon Shores, and H.A. Wagner power plants were not likely to elicit respiratory symptoms in healthy asthmatics.

Implications: Mobile and stationary air monitoring for SO2 were conducted to quantify short-term exposure risk, to the surrounding community, from peak emissions of three coal-fired power plants in the Baltimore area. Concentrations were typically low, with only a few 5-min averages higher than levels indicated during clinical trials to induce changes in lung capacity for healthy asthmatics engaged in exercise outdoors.  相似文献   

16.
To evaluate the validity of fixed-site fine particle levels as exposure surrogates in air pollution epidemiology, we considered four indicator groups: (1) PM2.5 total mass concentrations, (2) sulfur and potassium for regional air pollution, (3) lead and bromine for traffic-related particles, and (4) calcium for crustal particles. Using data from the European EXPOLIS (Air Pollution Exposure Distribution within Adult Urban Populations in Europe) study, we assessed the associations between 48-hr personal exposures and home outdoor levels of the indicators. Furthermore, within-city variability of fine particle levels was evaluated. Personal exposures to PM2.5 mass were not correlated to corresponding home outdoor levels (n = 44, rSpearman (Sp) = 0.07). In the group reporting neither relevant indoor sources nor relevant activities, personal exposures and home outdoor levels of sulfur were highly correlated (n = 40, rSp = 0.85). In contrast, the associations were weaker for traffic (Pb: n = 44, rSp = 0.53; Br: n = 44, rSp = 0.21) and crustal (Ca: n = 44, rSp = 0.12) indicators. This contrast is consistent with spatially homogeneous regional pollution and higher spatial variability of traffic and crustal indicators observed in Basel, Switzerland. We conclude that for regional air pollution, fixed-site fine particle levels are valid exposure surrogates. For source-specific exposures, however, fixed-site data are probably not the optimal measure. Still, in air pollution epidemiology, ambient PM2.5 levels may be more appropriate exposure estimates than total personal PM2.5 exposure, since the latter reflects a mixture of indoor and outdoor sources.  相似文献   

17.
Mot time-series studies of particulate air pollution and acute health outcomes assess exposure of the study population using fixed-site outdoor measurements. To address the issue of exposure misclassification, we evaluate the relationship between ambient particle concentrations and personal exposures of a population expected to be at risk of particle health effects. Sampling was conducted within the Vancouver metropolitan area during April-September 1998. Sixteen subjects (non-smoking, ages 54-86) with physician-diagnosed chronic obstructive pulmonary disease (COPD) wore personal PM2.5 monitors for seven 24-hr periods, randomly spaced approximately 1.5 weeks apart. Time-activity logs and dwelling characteristics data were also obtained for each subject. Daily 24-hr ambient PM10 and PM2.5 concentrations were measured at five fixed sites spaced throughout the study region. SO4(2-), which is found almost exclusively in the fine particle fraction and which does not have major indoor sources, was measured in all PM2.5 samples as an indicator of accumulation mode particulate matter of ambient origin. The mean personal and ambient PM2.5 concentrations were 18 micrograms/m3 and 11 micrograms/m3, respectively. In analyses relating personal and ambient measurements, ambient concentrations were expressed either as an average of the values obtained from five ambient monitoring sites for each day of personal sampling, or as the concentration obtained at the ambient site closest to each subject's home. The mean personal to ambient concentration ratio of all samples was 1.75 (range = 0.24 to 10.60) for PM2.5, and 0.75 (range = 0.09 to 1.42) for SO4(2-). Regression analyses were conducted for each subject separately and on pooled data. The median correlation (Pearson's r) between personal and average ambient PM2.5 concentrations was 0.48 (range = -0.68 to 0.83). Using SO4(2-) as the exposure metric, the median r between personal and average ambient concentrations was 0.96 (range = 0.66 to 1.0). Use of the closest ambient site did not improve the median correlation of the group for either PM2.5 or SO4(2-). All pooled analyses resulted in lower correlation coefficients than the median correlation coefficient of individual regressions. Personal SO4(2-) was more highly correlated with all ambient measures than PM2.5. Inclusion of time-activity and dwelling characteristics data did not result in a useful predictive regression model for PM2.5 personal exposure, but improved the model fit from simply regressing against ambient concentration (R2 = 0.27). The model for SO4(2-) was predictive (R2 = 0.82), as personal exposures were largely explained by ambient levels. These results indicate a relatively low correlation between personal exposure and ambient PM2.5 that is not improved by assigning exposure to the closest ambient monitor. The correlation between personal exposure and ambient concentration is high, however, when using SO4(2-), an indicator of accumulation mode particulate matter of ambient origin.  相似文献   

18.
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.  相似文献   

19.
Epidemiological studies of particulate matter (PM) routinely use concentrations measured with stationary outdoor monitors as surrogates for personal exposure. Despite the frequently reported poor correlations between ambient concentrations and total personal exposure, the epidemiologic associations between ambient concentrations and health effects depend on the correlation between ambient concentrations and personal exposure to ambient-generated PM. This paper separates personal PM exposure into ambient and nonambient components and estimates the outdoor contribution to personal PM exposures with continuous light scattering data collected from 38 subjects in Seattle, WA. Across all subjects, the average exposure encountered indoors at home was lower than in all other microenvironments. Cooking and being at school were associated with elevated levels of exposure. Previously published estimates of particle infiltration (Finf) were combined with time-location data to estimate an ambient contribution fraction (alpha, mean = 0.66+/-0.21) for each subject. The mean alpha was significantly lower for subjects monitored during the heating season (0.55+/-0.16) than for those monitored during the nonheating season (0.80+/-0.17). Our modeled alpha estimates agreed well with those estimated with the sulfur-tracer method (slope = 1.08; R2 = 0.67). We modeled exposure to ambient and nonambient PM with both continuous light scattering and 24-hr gravimetric data and found good agreement between the two methods. On average, ambient particles accounted for 48% of total personal exposure (range = 21-80%). The personal activity exposure was highly influenced by time spent away from monitored microenvironments. The median hourly longitudinal correlation between central site concentrations and personal exposures was 0.30. Although both alpha and the nonambient sources influence the personal-central relationship, the latter seems to dominate. Thus, total personal exposure may be poorly predicted by stationary outdoor monitors, particularly among persons whose PM exposure is dominated by nonambient exposures, for example, those living in tightly sealed homes, those who cook, and children.  相似文献   

20.
Measurements in urban Atlanta of transient aerosol events in which PM2.5 mass concentrations rapidly rise and fall over a period of 3-6 hr are reported. The data are based on new measurement techniques demonstrated at the U.S. Environmental Protection Agency (EPA) Atlanta Supersite Experiment in August 1999. These independent instruments for aerosol chemical speciation of NO3-, SO4(2-), NH4+, and organic and elemental carbon (OC and EC), reconstructed the observed hourly dry PM2.5 mass to within 20% or better. Data from the experiment indicated that transient PM2.5 events were ubiquitous in Atlanta and were typically characterized by a sudden increase of EC (soot) and OC in the early morning or SO4(2-) in the late afternoon. The frequent temporal decoupling of these events provides insights into their origins, suggesting mobile sources in metro Atlanta as the main contributor to early morning PM2.5 and more regionally located point SO2 sources for afternoon PM2.5 events. The transient events may also have health implications. New data suggest that short-term PM2.5 exposures may lead to adverse health effects. Standard integrated filter-based techniques used in PM2.5 compliance monitoring networks and in most past PM2.5 epidemiologic studies collect samples over 24-hr periods and thus are unable to capture these transient events. Moreover, health-effects studies that focus on daily PM2.5 mass alone cannot evaluate the health implications of the unique and variable chemical properties of these episodes.  相似文献   

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