Fixed-site Monitoring Data Research Articles

Refining Children's exposure assessment to NO2, SO2, and O3: Incorporating indoor-to-outdoor concentration ratios and individual daily routine

Exposure to air pollutants like sulfur dioxide (SO2), nitrogen oxides (NOx), and ozone (O3) is associated with adverse health effects, particularly with exacerbations of asthma symptoms and new asthma cases in both children and adults. While fixed-site monitoring (FSM) stations are commonly used in air pollutant exposure studies, they may not fully capture personal exposures due to limitations such as inadequate consideration of daily routines and indoor/outdoor concentration variations. In this study, to enhance the accuracy of personal exposure calculated by using FSM data, individual's daily activity routine, encompassing both indoor and outdoor environments, were incorporated by using indoor-to-outdoor concentration ratios. Three methodologies were compared to assess the accuracy of exposure calculations: (i) direct exposure determination employing passive samplers (PS), (ii) personal exposure calculated using FSM data alone, and (iii) personal exposure calculated using FSM data refined by integrating local average individual daily activity routines and indoor-to-outdoor ratios. The results demonstrate that the refined method (iii) yields substantial improvements in estimated exposure levels, reducing the average error from 1.4% to 0.4% for NO2, from 72.1% to 12.7% for SO2, and from 323.4% to 24.9% for O3.

Comparison of personal exposure to black carbon levels with fixed-site monitoring data and with dispersion modelling and the influence of activity patterns and environment

BackgroundShort-term studies of health effects from ambient air pollution usually rely on fixed site monitoring data or spatio-temporal models for exposure characterization, but the relation to personal exposure is often not known.ObjectiveWe aimed to explore this relation for black carbon (BC) in central Stockholm.MethodsFamilies (n = 46) with an infant, one parent working and one parent on parental leave, carried battery-operated BC instruments for 7 days. Routine BC monitoring data were obtained from rural background (RB) and urban background (UB) sites. Outdoor levels of BC at home and work were estimated in 24 h periods by dispersion modelling based on hourly real-time meteorological data, and statistical meteorological data representing annual mean conditions. Global radiation, air pressure, precipitation, temperature, and wind speed data were obtained from the UB station. All families lived in the city centre, within 4 km of the UB station.ResultsThe average level of 24 h personal BC was 425 (s.d. 181) ng/m3 for parents on leave, and 394 (s.d. 143) ng/m3 for working parents. The corresponding fixed-site monitoring observations were 148 (s.d. 139) at RB and 317 (s.d. 149) ng/m3 at UB. Modelled BC levels at home and at work were 493 (s.d. 228) and 331 (s.d. 173) ng/m3, respectively. UB, RB and air pressure explained only 21% of personal 24 h BC variability for parents on leave and 25% for working parents. Modelled home BC and observed air pressure explained 23% of personal BC, and adding modelled BC at work increased the explanation to 34% for the working parents.ImpactShort-term studies of health effects from ambient air pollution usually rely on fixed site monitoring data or spatio-temporal models for exposure characterization, but the relation to actual personal exposure is often not known. In this study we showed that both routine monitoring and modelled data explained less than 35% of variability in personal black carbon exposure. Hence, short-term health effects studies based on fixed site monitoring or spatio-temporal modelling are likely to be underpowered and subject to bias.

Development and demonstration of a data visualization platform of short-term guidelines for ambient air levels of benzene during disaster response in Houston, Texas.

Industrial disasters have caused hazardous air pollution and public health impacts. Response officials have developed limited exposure guidelines to direct them during the event; often, guidelines are outdated and may not represent relevant elevated-exposure periods. The 2019 Intercontinental Terminals Company (ITC) fire in Houston, Texas led to large-scale releases of benzene and presented a public health threat. This incident highlights the need for effective response and nimble, rapid public health communication. We developed a data-driven visualization tool to store, display, and interpret ambient benzene concentrations to assist health officials during environmental emergencies. Guidance values to interpret risk from acute exposure to benzene were updated using recent literature that also considers exposure periodicity. The visualization platform can process data from different sampling instruments and air monitors automatically, and displays information publicly in real time, along with the associated risk information and action recommendations. The protocol was validated by applying it retrospectively to the ITC event. The new guidance values are 6-30 times lower than those derived by the Texas regulatory agency. Fixed-site monitoring data, assessed using the protocol and revised thresholds, indicated that eight shelter-in-place and 17 air-quality alerts may have been considered. At least one of these shelter-in-place alerts corresponded to prolonged, elevated benzene concentrations (~1000 ppb). This new tool addresses essential gaps in the timely communication of air pollution measurements, provides context to understand potential health risks from exposure to benzene, and provides a clear protocol for local officials in responding to industrial air releases of benzene. Integr Environ Assess Manag 2024;20:533-546. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Joint effect of multiple air pollutants on cardiometabolic health in normal-weight and obese adults: A novel insight into the role of circulating free fatty acids

The cardiometabolic effects of air pollution in the context of mixtures and the underlying mechanisms remain not fully understood. This study aims to investigate the joint effect of air pollutant mixtures on a broad range of cardiometabolic parameters, examine the susceptibility of obese individuals, and determine the role of circulating fatty acids. In this panel study, metabolically healthy normal-weight (MH-NW, n = 49) and obese (MHO, n = 39) adults completed three longitudinal visits (257 person-visits in total). Personal exposure levels of PM2.5, PM10, O3, NO2, SO2, CO and BC were estimated based on fixed-site monitoring data, time-activity logs and infiltration factor method. Blood pressure, glycemic homeostasis, lipid profiles, systematic inflammation and coagulation biomarkers were measured. Targeted metabolomics was used to quantify twenty-eight plasma free fatty acids (FFAs). Bayesian kernel machine regression models were applied to establish the exposure-response relationships and identify key pollutants. Significant joint effects of measured air pollutants on systematic inflammation and coagulation biomarkers were observed in the MHO group, instead of the MH-NW group. Lipid profiles showed the most significant changes in both groups and O3 contributed the most to the total effect. Specific FFA patterns were identified, and de novo lipogenesis (DNL)-related pattern was most closely related to blood lipid profiles. In particular, interaction analysis suggested that DNL-related FFA pattern augmented the effects of O3 on triglyceride (TG, Pinteraction = 0.040), high-density lipoprotein cholesterol (HDL-C, Pinteraction = 0.106) and TG/HDL-C (Pinteraction = 0.020) in the MHO group but not MH-NW group. This modification was further confirmed by interaction analysis with estimated activity of SCD1, a key enzyme in the DNL pathway. Therefore, despite being metabolically healthy, obese subjects have a higher cardiometabolic susceptibility to air pollution, especially O3, and the DNL pathway may represent an intrinsic driver of lipid susceptibility. This study provides new insights into the cardiometabolic susceptibility of obese individuals to air pollution.

Personal exposure to black carbon in Stockholm, Sweden, compared to fixed-site monitoring and dispersion modelling

INTRODUCTION AND AIM Short-term studies of health effects from ambient air pollution usually rely on fixed site monitoring data or spatio-temporal models for exposure characterization, but the relation to personal exposure is often not known. We aimed to explore this relation for black carbon (BC) in central Stockholm. METHODS Families (n=36) with an infant, one parent working and one parent on leave, agreed to perform personal measurements of BC for the parents, with battery-operated aethalometers for 7 days. Routine monitoring data were from rural background (RB) and urban background (UB). Outdoor levels at home and work were estimated in 24h periods by dispersion modelling with real-time meteorological data. Global radiation, air pressure, precipitation, temperature, and wind speed data were achieved from an urban background station. All families lived within 4 km from the city center. RESULTS The average level of 24h personal BC was 370 (s.d. 200) ng/m3 for parents on leave, and 357 (s.d. 175) ng/m3 for working parents. The corresponding fixed-site monitoring observations were 148 (s.d. 139) at RB and 317 (s.d. 149) at UB. Modelled BC at home and at work were 493 (s.d. 228) and 331 (s.d. 173) ng/m3, respectively. UB, RB and air pressure explained only 21% of personal 24h BC variability for parents on leave and 25% for working parents. Modelled home BC and air pressure explained 23% of personal BC, and adding modelled BC at work increased the explanation to 34% for the working parents. CONCLUSION Both routine monitoring and modeled data explained less than 35% of variability in personal 24h observations of BC exposure. Any associated short-term health effects are likely to be underestimated in studies using such exposure data. KEYWORDS Black carbon, Personal exposure, Dispersion modelling

Comparison of measured residential black carbon levels outdoors and indoors with fixed-site monitoring data and with dispersion modelling

Epidemiologic studies on health effects of air pollution usually rely on time-series of ambient monitoring data or on spatially modelled levels. Little is known how well these estimate residential outdoor and indoor levels. We investigated the agreement of measured residential black carbon (BC) levels outdoors and indoors with fixed-site monitoring data and with levels calculated using a Gaussian dispersion model. One-week residential outdoor and indoor BC measurements were conducted for 15 families living in central Stockholm. Time-series from urban background and street-level monitors were compared to these measurements. The observed weekly concentrations were also standardized to reflect annual averages, using urban background levels, and compared spatially to long-term levels as estimated by dispersion modelling. Weekly average outdoor BC level was 472 ng/m3 (range 261–797 ng/m3). The corresponding fixed-site urban background and street levels were 313 and 1039 ng/m3, respectively. Urban background variation explained 50% of the temporal variation in residential outdoor levels averaged over 24 h. Modelled residential long-term outdoor levels were on average comparable with the standardized measured home outdoor levels, and explained 49% of the spatial variability. The median indoor/outdoor ratio across all addresses was 0.79, with no difference between day and night time. Common exposure estimation approaches in the epidemiology of health effects related to BC displayed high validity for residencies in central Stockholm. Urban background monitored levels explained half of the outdoor day-to-day variability at residential addresses. Long-term dispersion modelling explained half of the spatial differences in outdoor levels. Indoor BC concentrations tended to be somewhat lower than outdoor levels.

From Smoking-Permitted to Smokefree Prisons: A 3-Year Evaluation of the Changes in Occupational Exposure to Second-Hand Smoke Across a National Prison System.

ObjectivesPrisons in Scotland were one of the few workplaces exempt from the 2006 comprehensive smoking ban in indoor public places, excluding the prison workforce from the health benefits of smokefree workplaces. The November 2018 introduction of comprehensive restrictions on smoking in Scottish prisons aimed to protect prison staff and people in custody from the harmful impacts of second-hand smoke (SHS) exposure. This study presents SHS exposure data gathered after smokefree policy implementation and compares these with data gathered during and before policy development.MethodsDylos DC1700 monitors were used to measure concentrations of fine particulate matter (PM2.5) derived from SHS across Scotland’s 15 prisons. Six days of fixed-site monitoring (09.00 22 May 2019 to 09.00 28 May 2019) were conducted in residential halls in each prison 6 months post-smokefree policy implementation. Prison staff task-based measurements were conducted to assess concentrations of SHS in various locations (e.g. gyms and workshops) and during specific activities (e.g. cell searches, maintenance, and meal service). Utilizing the fixed-site monitoring data, typical daily PM2.5 exposure profiles were constructed for the prison service and time-weighted average (TWA) exposure concentrations were estimated for the typical shift patterns of residential staff pre- and post-smokefree policy implementation. Staff perceptions of changes to SHS exposure were assessed using online surveys.ResultsAnalysis of both fixed-site and mobile task-based PM2.5 measurements showed the smokefree policy implementation was successful in reducing SHS exposures across the Scottish prison estate. Measured PM2.5 in residential halls declined markedly; median fixed-site concentrations reduced by more than 91% compared with measures in 2016 before policy announcement. The changes in the TWA concentrations across shifts (over 90% decrease across all shifts) and task-based measurements (89% average decrease for high-exposure tasks) provide evidence that prison staff exposure to SHS has significantly reduced. Following smokefree policy implementation, the majority of staff reported no longer being exposed to SHS at work.ConclusionsTo our knowledge, this is the first comprehensive international study to objectively measure SHS levels before, during, and after implementation of a smokefree policy across a country’s prison system. The findings confirm that such a policy change can be successfully implemented to eliminate occupational exposures to SHS. The results are highly relevant for other jurisdictions considering changes to prison smoking legislation.

Health Burden of PM2.5 and Socioeconomic Status in the New South Wales Greater Metropolitan Region

Background/Aim: Exposure to ambient particulate matter is not uniformly distributed in urban environments. In addition, there is a social gradient in the population level susceptibility to the health effects of air pollution. Such disparities may result in vulnerable populations bearing a relatively greater burden of disease attributed to this exposure compared with the population at large. Methods: Using high resolution chemical transport modelling, blended with fixed-site monitoring data, of particulate matter of diameter less than 2.5 μm (PM2.5), baseline health incidence rates and known health risk estimates, we implemented a health impact assessment methodology to estimate the burden of disease by quintile of socioeconomic status in the New South Wales Greater Metropolitan Region (GMR). Results: We found that for each health endpoint, there was an increasing burden of disease attributable to anthropogenic PM2.5 exposure with decreasing socioeconomic status in the GMR and subregions with the difference in burden exceeding the difference in baseline incidence. The areas with the lowest socioeconomic status had 50% more years of life lost (YLL) attributable to PM2.5 than the areas of highest socioeconomic status in the whole GMR. Conclusions: The disparity that we found in burden due to PM2.5 contributes to a growing body of evidence in the field of environmental justice and supports the need for policy to protect vulnerable communities from inequitable exposure to environmental hazards.

Combining land use regression models and fixed site monitoring to reconstruct spatiotemporal variability of NO2 concentrations over a wide geographical area

The epidemiological research benefits from an accurate characterization of both spatial and temporal variability of exposure to air pollution. This work aims at proposing a method to combine the high spatial resolution of Land Use Regression (LUR) models with the high temporal resolution of fixed site monitoring data, to model spatiotemporal variability of NO2 over a wide geographical area in Northern Italy. We developed seasonal LUR models to reconstruct the spatial distribution of a scaling factor that relates local concentrations to those measured at two reference central sites, one for the northern flat area and one for the southern mountain area. We calculated the daily average concentrations at 19 locations spread over the study areas as the product of the local scaling factor and the reference central site concentrations. We evaluated model performance comparing modeled and measured NO2 data. LUR model's R2 ranges from 0.76 to 0.92. The main predictors refers substantially to traffic, industrial land use, buildings volume and altitude a.s.l. The model's performance in reproducing measured concentrations was satisfactory. The temporal variability of concentrations was well captured: Spearman correlation between model and measures was >0.7 for almost all sites. Model's average absolute errors were in the order of 10μgm−3. The model for the southern area tends to overestimate measured concentrations. Our modeling framework was able to reproduce spatiotemporal differences in NO2 concentrations. This kind of model is less data-intensive than usual regional atmospheric models and it may be very helpful to assess population exposure within studies in which individual relevant exposure occurs along periods of days or months.

Particulate air pollution and mortality in a cohort of Chinese men

Few prior cohort studies exist in developing countries examining the association of ambient particulate matter (PM) with mortality. We examined the association of particulate air pollution with mortality in a prospective cohort study of 71,431 middle-aged Chinese men. Baseline data were obtained during 1990–1991. The follow-up evaluation was completed in January, 2006. Annual average PM exposure between 1990 and 2005, including TSP and PM10, were estimated by linking fixed-site monitoring data with residential communities. We found significant associations between PM10 and mortality from cardiopulmonary diseases; each 10 μg/m3 PM10 was associated with a 1.6% (95%CI: 0.7%, 2.6%), 1.8% (95%CI: 0.8%, 2.9%) and 1.7% (95%CI: 0.3%, 3.2%) increased risk of total, cardiovascular and respiratory mortality, respectively. For TSP, we observed significant associations only for cardiovascular morality. These data contribute to the scientific literature on long-term effects of particulate air pollution for high exposure settings typical in developing countries.

Personal versus fixed-site monitoring for assessing PM2.5 exposure in an industrial city, Saudi Arabia

Background: Air pollution is a known risk factor for adverse health effects. Many epidemiological studies use outdoor air pollution levels based on fixed-site monitoring data as a surrogate for human exposure, however individuals spend, on average, 85% of their time indoors, where exposure sources differ from outdoors. Personal monitoring allows more appropriate exposure estimation, but, to date, little has been done to compare exposure based on fixed-site versus personal monitoring, and no such comparisons have been carried out in the Middle East. Aims: To investigate the validity of fixed-site versus personal monitoring of PM2.5 in an industrial city in Saudi Arabia. Methods: We collected 24-hour personal monitoring of PM2.5 exposure from 28 students aged 16-18 years, using a SidePak AM510 set to record PM2.5 levels every minute. Students completed a time-activity diary to identify time spent in key microenvironments, especially outdoors and indoors. Students also carried a GPS device to log their geogr...

Comparisons of personal exposure to PM2.5 and CO by different commuting modes in Beijing, China

BackgroundEpidemiological studies have shown that commuting in traffic is associated with adverse health effects. It is vital to investigate commuters' exposure to traffic-related air pollutants before considering potential health risks. However, there are relatively few publications considering commuters' personal exposure in China. MethodWe carried out a field investigation measuring commuters' personal exposure to particulate matter ≤2.5μm in aerodynamic diameter (PM2.5) and carbon monoxide (CO) by three commuting modes in Beijing. Both PM2.5 and CO personal concentrations and whole trip exposures were compared among the three commuting modes. ResultsAfter controlling confounding factors, we found that taxi commuters were exposed to lower concentrations of PM2.5 (31.64±20.77μg/m3) compared with bus commuters (42.40±23.36μg/m3) and cyclists (49.10±26.60μg/m3). By contrast, CO personal concentrations were significantly higher when commuting by taxi (5.21±1.52ppm) than by bus (2.41±0.99ppm) and bicycle (1.90±0.55ppm). However, when inhalation rates and trip duration were taken into consideration, cyclists experienced the highest whole trip exposures to both PM2.5 and CO (p<0.05). We also found fixed site monitoring data were not appropriate surrogates for personal exposure while commuting, especially during traffic heavy times. ConclusionPM2.5 and CO personal concentrations were greatly influenced by the commuting mode. Furthermore, the highest whole trip exposures to PM2.5 and CO which cyclists experienced indicates it is not preferable to commute by bicycle in a relatively high air polluted environment. Cyclists are possibly subject to greater health risks than other commuters. Thus further research needs to be conducted to investigate the health risks associated with cycling.

Creating National Air Pollution Models for Population Exposure Assessment in Canada

Background: Population exposure assessment methods that capture local-scale pollutant variability are needed for large-scale epidemiological studies and surveillance, policy, and regulatory purposes. Currently, such exposure methods are limited.Methods: We created 2006 national pollutant models for fine particulate matter [PM with aerodynamic diameter ≤ 2.5 μm (PM2.5)], nitrogen dioxide (NO2), benzene, ethylbenzene, and 1,3-butadiene from routinely collected fixed-site monitoring data in Canada. In multiple regression models, we incorporated satellite estimates and geographic predictor variables to capture background and regional pollutant variation and used deterministic gradients to capture local-scale variation. The national NO2 and benzene models are evaluated with independent measurements from previous land use regression models that were conducted in seven Canadian cities. National models are applied to census block-face points, each of which represents the location of approximately 89 individuals, to produce estimates of population exposure.Results: The national NO2 model explained 73% of the variability in fixed-site monitor concentrations, PM2.5 46%, benzene 62%, ethylbenzene 67%, and 1,3-butadiene 68%. The NO2 model predicted, on average, 43% of the within-city variability in the independent NO2 data compared with 18% when using inverse distance weighting of fixed-site monitoring data. Benzene models performed poorly in predicting within-city benzene variability. Based on our national models, we estimated Canadian ambient annual average population-weighted exposures (in micrograms per cubic meter) of 8.39 for PM2.5, 23.37 for NO2, 1.04 for benzene, 0.63 for ethylbenzene, and 0.09 for 1,3-butadiene.Conclusions: The national pollutant models created here improve exposure assessment compared with traditional monitor-based approaches by capturing both regional and local-scale pollution variation. Applying national models to routinely collected population location data can extend land use modeling techniques to population exposure assessment and to informing surveillance, policy, and regulation.

Association between long-term exposure to outdoor air pollution and mortality in China: A cohort study

No prior cohort studies exist in China examining the association of outdoor air pollution with mortality. We studied 70,947 middle-aged men and women in the China National Hypertension Survey and its follow-up study. Baseline data were obtained in 1991 using a standard protocol. The follow-up evaluation was conducted in 1999 and 2000. Annual average air pollution exposure between 1991 and 2000, including total suspended particle (TSP), sulfur dioxide (SO2) and nitrogen oxides (NOx), were estimated by linking fixed-site monitoring data with resident zip code. We examined the association of air pollution with mortality using proportional hazards regression model. We found significant associations between air pollution levels and mortality from cardiopulmonary diseases and from lung cancer. Each 10μg/m3 elevation of TSP, SO2 and NOx was associated with a 0.9% (95%CI: 0.3%, 1.5%), 3.2% (95%CI: 2.3%, 4.0%), and 2.3% (95%CI: 0.6%, 4.1%) increased risk of cardiovascular mortality, respectively. We found significant effects of SO2 on mortality after adjustment for TSP. Conclusively, ambient air pollution was associated with increased cardiopulmonary and lung cancer mortality in China. These data contribute to the scientific literature on long-term effects of air pollution for high exposure settings typical in developing countries.

Comparisons of commuter's exposure to particulate matters while using different transportation modes

This study compared commuters' exposures to particulate matter (PM) while using motorcycles, cars, buses, and the mass rapid transit (MRT) on the same routes in Taipei, Taiwan. Motorcycle commuters who had the shortest travel time (28.4 ± 4.2 min) were exposed to the highest concentrations of PM 10 (112.8 ± 38.3 μg/m 3), PM 2.5 (67.5 ± 31.3 μg/m 3), and PM 1.0 (48.4 ± 24.7 μg/m 3) among four commuting modes. By contrast, car commuters were exposed to the lowest PM concentrations and had the second shortest travel time among them. Motorcycle commuters' high trip-averaged PM concentrations and bus commuters' long commuting time (43.1 ± 5.1 min) resulted in their high whole-trip PM exposures. Size fractions of PM were relatively consistent across PM exposures of the four commuting modes with fine particles (PM 2.5) contributing to 53–60% of PM 10 and submicron particle (PM 1) contributing to 39–43% of PM 10. Motorcycles idled at traffic lights and bus doors opened at stops increased commuters' PM exposures. Fixed-site monitoring data explained well the variation of whole-trip PM 10 exposure of car ( r 2 = 0.63) and MRT ( r 2 = 0.52) commuters, and of whole-trip PM 2.5 exposure of car ( r 2 = 0.76), MRT ( r 2 = 0.73) and motorcycle ( r 2 = 0.64) commuters in regression analyses. The coefficients (slopes) of regression between fixed-site monitoring data and PM 2.5 exposures were less than 1 for car and MRT commuters but greater than 1 for motorcycle commuters. In conclusion, proximity to traffic emissions contributes to a person's high PM exposure during his or her daily commute. This proximity occurs when people use motorcycles on roads and when bus/MRT commuters walk or wait along commuting routes. Fixed-site air monitoring data can under-estimate motorcycle commuters' PM 2.5 exposures but over-estimate car and MRT commuters' PM 2.5 exposures.

#61 Particulate air pollution and lung cancer

Abstract PURPOSE: To evaluate the association between particulate air pollution and lung cancer in a retrospective study in Connecticut, Utah and southern Idaho. METHODS: We collected detailed residence histories from 1,474 pathologically confirmed lung cancer cases and 1,811 population controls selected with randomized recruitment. Analysis was limited to the 3,073 participants who lived only in Connecticut, Utah and Idaho during the period 5–20 years before lung cancer diagnosis for cases or interview for controls. Using geographical information system technology to interpolate total suspended particle (TSP) exposure from fixed-site monitoring data, we assigned a TSP exposure level to each residence and averaged individual exposures over the 15-year period from 5 to 20 years before the diagnosis/interview. Odds ratios (OR) associated with average TSP were estimated with logistic regression after adjusting for age, gender and decade-specific pack-years of cigarette smoking and taking into account selection probabilities used in randomized recruitment. RESULTS: The OR for a 10 μg/m 3 increase in TSP was 2.4 (95% CI = 2.0, 3.0) in Connecticut and 1.3 (95% CI = 1.1, 1.5) in Utah and Idaho. ORs were similar for smokers and nonsmokers. The OR associated with the top tertile for TSP and heavy smoking compared with nonsmokers in the lowest tertile was 57.4 (95% CI = 26.7, 123.4) in Connecticut and 75.7 (95% CI = 37.6, 152.5) in Utah/Idaho. CONCLUSION: Long-term exposure to higher levels of TSP may increase the risk for lung cancer. The higher observed OR in Connecticut despite lower average TSP exposures may be due to differences in the physical and chemical composition of TSP between Connecticut and Utah/Idaho, or to differences in the extent of exposure misclassification between those two regions. Alternatively, these differences might be an accurate reflection of the shape of the dose-response curve and our use of a measure of relative rather than absolute risk.

Can personal exposure to particulate matter be predicted by time activity diaries and fixed site monitoring data?

Georgoulis, L. B.; Samoli, E.; Oglesby, L.; Kuenzli, N.; Katsouyanni, K.; Jantunen, M. Author Information

Predicting personal exposure levels to carbon monoxide (CO) in Taipei, based on actual CO measurements in microenvironments and a Monte Carlo simulation method

Abstract In order to evaluate the severity of carbon monoxide (CO) pollution in Taipei, this study conducted a survey of commuting patterns (in a district) for random samples of primary school students and adult workers, and carried out CO measurements in vehicles and near roadsides. A Monte Carlo simulation was then implemented to estimate 1- and 8-h CO exposure levels for the population. The microenvironment of the roadside included both the sidewalk and the corridor (a sheltered walkaway further removed from the road than the sidewalk). By computer simulations, this study showed that commuters on motorcycles and public buses were exposed to the highest CO exposure levels among all commuters on the roads in Taipei. This study also demonstrated that the Monte Carlo simulation method could better estimate CO exposure levels for the general public. It was found that roadside-fixed monitoring stations operated by the Taipei BEP (Bureau of Environmental Protection) underestimated the general population's 1-h CO exposure levels. For adult workers, the roadside-fixed monitoring stations reasonably estimated the roadside business workers' 8-h CO exposure levels, but overestimated the exposure levels of general adult workers commuting by public bus, except for bus drivers whose CO exposure levels were underestimated. It is suggested that the computer simulation method can be used to better guide air quality management plans instead of only using the fixed-site monitoring data. The simulated results indicate that the CO exposure levels of commuters on motorcycles and public buses are high enough that prompt control measures are warranted in Taipei.

An Examination of the Intra-SMSA Distribution of Carbon Monoxide Exposure

Although fixed-site monitoring data have been used to estimate the spatial pattern of human exposure, the intra-urban distribution of actual exposure has not been documented. This paper used the data collected during the Environmental Protection Agency's (EPA) field investigation of personal exposure to carbon monoxide (CO) to investigate the nature of the distribution of CO with respect to residential location in the Washington, D.C. SMSA. Dot-distribution maps and analysis of variance were used to document the spatial pattern of individual-level in-home CO concentrations. The results show sampled individuals living in the SMSA center are exposed to statistically significantly higher levels of CO than are those living in the suburbs. The most important implications of this work are for exposure modeling. Further investigation is needed to determine whether incorporation of a geographic component will improve exposure prediction.

The estimation of personal exposures to air pollutants for a community-based study of health effects in asthmatics--exposure model.

Estimates of individual personal exposure to ozone, nitrogen dioxide, pollen, temperature, and relative humidity for a group of asthmatics participating in a health effects study were obtained by means of a modelling approach utilizing fixed site monitoring data, regression relationships between fixed site and indoor and outdoor microenvironment concentrations, study subject activity patterns and study household characteristics. A considerable improvement in the accuracy of exposure assessment using the exposure model instead of fixed site measurements alone was demonstrated for ozone. This large refinement of zone exposure estimates was achieved using a simplified approach which emphasized the large differences between indoor and outdoor microenvironmental concentrations, and assumed relatively little heterogeneity in exposure within either of these two broad microenvironmental categories. Major sources of error in the exposure model for ozone include: failure to include indoor microenvironments with no air conditioning in the development of the model, inability to accurately apportion within-hour time spent in different microenvironments, and misclassification of hour-specific personal location by study subjects.