Contribution of indoor and outdoor environments to PM2.5 personal exposure of children--VESTA study

Construction and evaluation of hourly average indoor PM2.5 concentration prediction models based on multiple types of places

Background

People usually spend most of their time indoors, so indoor fine particulate matter (PM2.5) concentrations are crucial for refining individual PM2.5 exposure evaluation. The development of indoor PM2.5 concentration prediction models is essential for the health risk assessment of PM2.5 in epidemiological studies involving large populations.

Methods

In this study, based on the monitoring data of multiple types of places, the classical multiple linear regression (MLR) method and random forest regression (RFR) algorithm of machine learning were used to develop hourly average indoor PM2.5 concentration prediction models. Indoor PM2.5 concentration data, which included 11,712 records from five types of places, were obtained by on-site monitoring. Moreover, the potential predictor variable data were derived from outdoor monitoring stations and meteorological databases. A ten-fold cross-validation was conducted to examine the performance of all proposed models.

Results

The final predictor variables incorporated in the MLR model were outdoor PM2.5 concentration, type of place, season, wind direction, surface wind speed, hour, precipitation, air pressure, and relative humidity. The ten-fold cross-validation results indicated that both models constructed had good predictive performance, with the determination coefficients (R2) of RFR and MLR were 72.20 and 60.35%, respectively. Generally, the RFR model had better predictive performance than the MLR model (RFR model developed using the same predictor variables as the MLR model, R2 = 71.86%). In terms of predictors, the importance results of predictor variables for both types of models suggested that outdoor PM2.5 concentration, type of place, season, hour, wind direction, and surface wind speed were the most important predictor variables.

Conclusion

In this research, hourly average indoor PM2.5 concentration prediction models based on multiple types of places were developed for the first time. Both the MLR and RFR models based on easily accessible indicators displayed promising predictive performance, in which the machine learning domain RFR model outperformed the classical MLR model, and this result suggests the potential application of RFR algorithms for indoor air pollutant concentration prediction.

Personal exposure to PM2.5 oxidative potential and its association to birth outcomes

BACKGROUND

Prenatal exposure to fine particulate matter (PM2.5) assessed through its mass concentration has been associated with foetal growth restriction in studies based on outdoor levels. Oxidative potential of PM2.5 (OP) is an emerging metric a priori relevant to mechanisms of action of PM on health, with very limited evidence to indicate its role on birth outcomes.

OBJECTIVES

We investigated the association of OP with birth outcomes and compared it with that of PM2.5 mass concentration.

METHODS

405 pregnant women from SEPAGES cohort (Grenoble area) carried PM2.5 personal dosimeters for one or two one-week periods. OP was measured using dithiothreitol (DTT) and ascorbic acid (AA) assays from the collected filters. Associations of each exposure metric with offspring weight, height, and head circumference at birth were estimated adjusting for potential confounders.

RESULTS

The correlation between PM2.5 mass concentration and [Formula: see text] was 0.7. An interquartile range increase in .. was associated with reduced weight (adjusted change, -64 g, -166 to -11, p = 0.02) and height (-4 mm, -6 to -1, p = 0.01) at birth. PM2.5 mass concentration showed similar associations with weight (-53 g, -99 to -8, p = 0.02) and height (-2 mm, -5 to 0, p = 0.05). In birth height models mutually adjusted for the two exposure metrics, the association with [Formula: see text] was less attenuated than that with mass concentration, while for weight both effect sizes attenuated similarly. There was no clear evidence of associations with head circumference for any metric, nor for [Formula: see text] with any growth parameter.

IMPACT

PM2.5 pregnancy exposure assessed from personal dosimeters was associated with altered foetal growth. Personal OP exposure was associated with foetal growth restrictions, specifically decreased weight and height at birth, possibly to a larger extent than PM2.5 mass concentration alone. These results support OP assessed from DTT as being a health-relevant metric. Larger scale cohort studies are recommended to support our findings.

Maternal NO2 exposure disturbs the long noncoding RNA expression profile in the lungs of offspring in time-series patterns

Gestation is a sensitive window to nitrogen dioxide (NO₂) exposure, which may disturb fetal lung development and lung function later in life. Animal and epidemiological studies indicated that long noncoding RNAs (lncRNAs) participate in abnormal lung development induced by environmental pollutant exposure. In the present study, pregnant C57BL/6J mice were exposed to 2.5 ppm NO₂ (mimicking indoor occupational exposure) or clean air, and lncRNAs expression profiles in the lungs of offspring mice were determined by lncRNA-seq on embryonic day 13.5 (E13.5), E18.5, postnatal day 1 (P1), and P14. The lung histopathology examination of offspring was performed, followed by weighted gene coexpression network analysis (WGCNA), prediction of lncRNAs-target genes, and the biological processes enrichment analysis of lncRNAs. Our results indicated that maternal NO₂ exposure induced hypoalveolarization on P14 and differentially expressed lncRNAs showed a time-series pattern. Following WGCNA and enrichment analysis, 2 modules participated in development-related pathways. Importantly, the expressions of related genes were altered, some of which were confirmed to be related to abnormal vascular development and even lung diseases. The research points out that the maternal NO₂ exposure leads to abnormal lung development in offspring that might be related to altered lncRNAs expression profiles with time-series-pattern.

Comparing human exposure to fine particulate matter in low and high-income countries: A systematic review of studies measuring personal PM2.5 exposure

BACKGROUND

Due to the adverse health effects of air pollution, researchers have advocated for personal exposure measurements whereby individuals carry portable monitors in order to better characterise and understand the sources of people's pollution exposure.

OBJECTIVES

The aim of this systematic review is to assess the differences in the magnitude and sources of personal PM2.5 exposures experienced between countries at contrasting levels of income.

METHODS

This review summarised studies that measured participants personal exposure by carrying a PM2.5 monitor throughout their typical day. Personal PM2.5 exposures were summarised to indicate the distribution of exposures measured within each country income category (based on low (LIC), lower-middle (LMIC), upper-middle (UMIC), and high (HIC) income countries) and between different groups (i.e. gender, age, urban or rural residents).

RESULTS

From the 2259 search results, there were 140 studies that met our criteria. Overall, personal PM2.5 exposures in HICs were lower compared to other countries, with UMICs exposures being slightly lower than exposures measured in LMICs or LICs. 34% of measured groups in HICs reported below the ambient World Health Organisation 24-h PM2.5 guideline of 15 μg/m3, compared to only 1% of UMICs and 0% of LMICs and LICs. There was no difference between rural and urban participant exposures in HICs, but there were noticeably higher exposures recorded in rural areas compared to urban areas in non-HICs, due to significant household sources of PM2.5 in rural locations. In HICs, studies reported that secondhand smoke, ambient pollution infiltrating indoors, and traffic emissions were the dominant contributors to personal exposures. While, in non-HICs, household cooking and heating with biomass and coal were reported as the most important sources.

CONCLUSION

This review revealed a growing literature of personal PM2.5 exposure studies, which highlighted a large variability in exposures recorded and severe inequalities in geographical and social population subgroups.

Long-term exposure to PM2.5 and cardiovascular disease incidence and mortality in an Eastern Mediterranean country: findings based on a 15-year cohort study

BACKGROUND

Evidence concerning the impact of long-term exposure to fine Particulate Matter ≤2.5 μm (PM2.5) on Cardio-Vascular Diseases (CVDs) for those people subject to ambient air pollution in developing countries remains relatively scant. This study assessed the relationship of 15-year PM2.5 exposure with cardiovascular incidence and mortality rate in Isfahan province, Iran.

METHODS

The cohort comprised 3081 participants over 35 years old who were free of CVDs. They were selected through multi-stage cluster sampling in Isfahan, Iran. PM2.5 exposure was determined separately for each individual via satellite-based spatiotemporal estimates according to their residential addresses. In this context, CVD is defined as either fatal and non-fatal Acute Myocardial Infarctions (AMI) or stroke and sudden cardiac death. The incidence risk for CVD and the ensuing mortality was calculated based on the average PM2.5 exposure within a study period of 15 years using the Cox proportional hazards frailty model upon adjusting individual risk factors. The mean annual rate of PM2.5 and the follow-up data of each residential area were combined.

RESULTS

Mean three-year PM2·5 exposure for the cohort was measured at 45.28 μg/m3, ranging from 20.01 to 69.80 μg/m3. The median time period for conducting necessary follow-ups was 12.3 years for the whole population. Notably, 105 cardiovascular and 241 all-cause deaths occurred among 393,786 person-months (27 and 61 per 100,000 person-months, respectively). In well-adjusted models, 10 μg/m3 increase in PM2.5 corresponded to a 3% increase in the incidence rate of CVDs [0.95 CI = 1.016, 1.036] (in case of p = 0.000001 per 10 μg/m3 increase in PM2.5, the Hazard Ratio (HR) for AMI and Ischemic Heart Disease (IHD) was 1.031 [0.95 CI = 1.005, 1.057] and 1.028 [0.95 CI = 1.017, 1.039]), respectively. No consistent association was observed between PM2.5 concentration and fatal CVD (fatal AMI, fatal stroke, SCD (Sudden Cardiac Death)) and all-cause mortality.

CONCLUSIONS

Results from analyses suggest that the effect of PM2.5 on cardiovascular disease occurrence was stronger in the case of older people, smokers, and those with high blood pressure and diabetes. The final results revealed that long-term exposure to ambient PM2.5 with high concentrations positively correlated with IHD incidence and its major subtypes, except for mortality. The outcome accentuates the need for better air quality in many countries.

Indoor air quality of 5,000 households and its determinants. Part A: Particulate matter (PM2.5 and PM10-2.5) concentrations in the Japan Environment and Children's Study

Exposure to particulate matter (PM) is one of the important risk factors for morbidity and mortality. Although PM concentrations have been assessed using air quality monitoring stations or modelling, few studies have measured indoor PM in large-scale birth cohorts. The Japan Environment and Children's Study (JECS) measured indoor and outdoor air quality in approximately 5000 households when the participating children were aged 1.5 and 3 years. PM was collected using portable pumps for 7 days (total of 24 h), inside and outside each home. Prediction models for indoor PM concentrations were built using data collected at age 1.5 years and post-validated against data collected at age 3 years. Median indoor/outdoor PM_2.5 and PM_10-2.5 concentrations at age 1.5 years [3 years] were 12.9/12.7 [12.5/11.3] μg/m³ and 5.0/6.3 [5.1/6.1] μg/m³, respectively. Random forest regression analysis found that the major predictors of indoor PM_2.5 were indoor PM_10-2.5, outdoor PM_2.5, indoor smoking, observable smoke and indoor/outdoor temperature. Indoor PM_2.5, outdoor PM_10-2.5, indoor humidity and opening room windows were important predictors of indoor PM_10-2.5 concentrations. Indoor benzene, acetaldehyde, ozone and nitrogen dioxide concentrations were also found to predict indoor PM_2.5 and PM_10-2.5 concentrations, possibly due to the formation of secondary organic aerosols. These findings demonstrate the importance of reducing outdoor PM concentrations, avoiding indoor smoking, using air cleaner in applicable and diminishing sources of VOCs that could form secondary organic aerosols, and the resulting models can be used to predict indoor PM concentrations for the rest of the JECS cohort.

Liaison between exposure to sub-micrometric particulate matter and allergic response in children from a petrochemical industry city

The study examines the association between exposure to sub-micrometric Particulate Matter (PM₁) and allergic response in a group of sensitive young children (age: 2-10 years) from Ploiesti city, Romania. The city is the only urban agglomeration in Europe surrounded by four oil refineries. A panel study was conducted by collecting medical information from children with respiratory illnesses and atopy (n = 135). Hot Spot Analysis revealed the areas of the city that are susceptible to high levels of PM₁. We found a close interaction between exposure to PM₁ outdoor concentrations and various physiological changes and clinical symptoms in children including triggering of allergic reactions, rhinitis, alteration of lung function, upper and lower respiratory tract symptoms, and bronchial asthma. During the 2-year study period, the incidence of hospitalizations was 40.7%. Strong correlations (p < 0.001) were observed between the PM₁ exposure and hospitalizations, and exposure and Immunoglobulin E (IgE). PM₁ exposure was also correlated with eosinophils (p < 0.05). Another positive correlation was observed between hospitalizations and IgE levels (p < 0.05). The mean results of tested indicators were as follows: wheezing (5.3, 95% CI (1.4-1.8); Coeff. of var. (CV) = 30%), IgE (382, 95% CI (349-445); CV = 102%), and EO% (5.3, 95% CI (3.3-4.2); CV = 69.5%). We can conclude that exposure to PM₁ influenced the frequency of wheezing episodes, increased hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers. CAPSULE: Exposure to sub-micrometric particles (PM₁) influences the frequency of wheezing episodes, hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers.

Effect of Air Pollution on Female Labor Supply: An Empirical Analysis Based on Data of Labor Force Dynamic Survey of China

The current study investigates the relationship between air pollution and female labor supply using China Labor Force Dynamic Survey Data (CLDS). The two-stage least squares method (2SLS) was used to approach the study objective. Moreover, the maximum wind speed was used as an instrumental variable for air pollution to solve the endogenous problem. The results found that air pollution directly impacted on female labor supply and working hours. The regression results confirmed a negative and significant impact of air pollution on female labor participation. Furthermore, the labor supply behavior of middle-aged and elderly women was significant and positively related to air pollution, while the labor supply behavior of young women had a negative relationship with air pollution. The study results stress the Chinese government to implement rigorous air pollution regulations to improve air quality. Furthermore, it is necessary to improve the female labor supply to maintain economic activities.

Predicting gestational personal exposure to PM2.5 from satellite-driven ambient concentrations in Shanghai

BACKGROUND

It has been widely reported that gestational exposure to fine particulate matters (PM_2.5) is associated with a series of adverse birth outcomes. However, the discrepancy between ambient PM_2.5 concentrations and personal PM_2.5 exposure would significantly affect the estimation of exposure-response relationship.

OBJECTIVE

Our study aimed to predict gestational personal exposure to PM_2.5 from the satellite-driven ambient concentrations and analyze the influence of other potential determinants.

METHOD

We collected 762 72-h personal exposure samples from a panel of 329 pregnant women in Shanghai, China as well as their time-activity patterns from Feb 2017 to Jun 2018. We established an ambient PM_2.5 model based on MAIAC AOD at 1 km resolution, then used its output as a major predictor to develop a personal exposure model.

RESULTS

Our ambient PM_2.5 model yielded a cross-validation R² of 0.96. Personal PM_2.5 exposure levels were almost identical to the corresponding ambient concentrations. After adjusting for time-activity patterns and meteorological factors, our personal exposure has a CV R² of 0.76.

CONCLUSION

We established a prediction model for gestational personal exposure to PM_2.5 from satellite-based ambient concentrations and provided a methodological reference for further epidemiological studies.

Evaluation of random forest regression and multiple linear regression for predicting indoor fine particulate matter concentrations in a highly polluted city

BACKGROUND

Indoor and outdoor fine particulate matter (PM_2.5) are both leading risk factors for death and disease, but making indoor measurements is often infeasible for large study populations.

METHODS

We developed models to predict indoor PM_2.5 concentrations for pregnant women who were part of a randomized controlled trial of portable air cleaners in Ulaanbaatar, Mongolia. We used multiple linear regression (MLR) and random forest regression (RFR) to model indoor PM_2.5 concentrations with 447 independent 7-day PM_2.5 measurements and 87 potential predictor variables obtained from outdoor monitoring data, questionnaires, home assessments, and geographic data sets. We also developed blended models that combined the MLR and RFR approaches. All models were evaluated in a 10-fold cross-validation.

RESULTS

The predictors in the MLR model were season, outdoor PM_2.5 concentration, the number of air cleaners deployed, and the density of gers (traditional felt-lined yurts) surrounding the apartments. MLR and RFR had similar performance in cross-validation (R² = 50.2%, R² = 48.9% respectively). The blended MLR model that included RFR predictions had the best performance (cross validation R² = 81.5%). Intervention status alone explained only 6.0% of the variation in indoor PM_2.5 concentrations.

CONCLUSIONS

We predicted a moderate amount of variation in indoor PM_2.5 concentrations using easily obtained predictor variables and the models explained substantially more variation than intervention status alone. While RFR shows promise for modelling indoor concentrations, our results highlight the importance of out-of-sample validation when evaluating model performance. We also demonstrate the improved performance of blended MLR/RFR models in predicting indoor air pollution.

Influence of the Natural and Built Environment on Personal Exposure to Fine Particulate Matter (PM2.5) in Cyclists Using City Designated Bicycle Routes

Urban cyclists are exposed to many traffic-related air pollutants including particulate matter (PM) that may increase vulnerability to health effects. This study investigates second-by-second personal exposure to PM2.5 (fine particulate matter that is 2.5 microns in diameter and less) along bicycle commuting paths, and assesses elements of the natural and built environment for the relative importance of these factors in understanding the variability in PM2.5 personal exposure. Urban cyclists were carrying high resolution PM2.5 monitors (placed in a backpack) in combination with portable GPS trackers to provide a spatial identity to each one-second pollutant measurement. The results of this study indicate that daily averages of PM2.5 concentrations from all bicycle routes were weakly correlated with meteorological variables, however, a strong influence of regional levels of PM2.5 was observed. Geospatial analysis of PM2.5 personal exposure concentrations showed a considerable variation within routes, correlated with land use (with lower concentrations in parks and higher in industrial areas) and clustered at four areas: busiest bridge, heavily trafficked road segments, the downtown urban core, and two construction sites. This study has found many incidences of personal exposure to PM2.5 exceeding the provincial guidelines for healthy activity (e.g., very poor (PM2.5 > 91 μg/m3) pollution concentrations are clustered in three regions: approaching the bridge in the west part of the city; the downtown urban core; and two under construction spots), which suggests behavioural and infrastructure modifications in balancing the health benefits of cycling with the environmental exposure to air pollutants.

Design and application of a web-based real-time personal PM2.5 exposure monitoring system

Growing demand from public health research for conduct large-scale epidemiological studies to explore health effect of PM_2.5 was well-documented. To address this need, we design a web-based real-time personal PM_2.5 exposure monitoring system (RPPM2.5 system) which can help researcher to get big data of personal PM_2.5 exposure with low-cost, low labor requirement, and low operating technical requirements. RPPM2.5 system can provide relative accurate real-time personal exposure data for individuals, researches, and decision maker. And this system has been used in a survey of PM_2.5 personal exposure level conducted in 5 cities of China and has provided mass of valuable data for epidemiological research.

Fine Particulate Matter in Urban Environments: A Trigger of Respiratory Symptoms in Sensitive Children

The overall objective of this research was to study children’s respiratory illness levels in Targoviste (Romania) in relationship to the outdoor concentrations of airborne particulate matter with an aerodynamic diameter below 2.5 µm (PM_2.5). We monitored and analysed the PM_2.5 concentrations according to a complex experimental protocol. The health trial was conducted over three months (October–December 2015) and required the active cooperation of the children’s parents to monitor carefully the respiratory symptoms of the child, i.e., coughing, rhinorrhoea, wheezing, and fever, as well as their outdoor program. We selected the most sensitive children (n = 25; age: 2–10 years) with perturbed respiratory health, i.e., wheezing, asthma, and associated symptoms. The estimated average PM_2.5 doses were 0.8–14.5 µg·day⁻¹ for weekdays, and 0.4–6.6 µg·day⁻¹ for the weekend. The frequency and duration of the symptoms decreased with increasing age. The 4- to 5-year old children recorded the longest duration of symptoms, except for rhinorrhoea, which suggested that this age interval is the most vulnerable to exogenous trigger agents (p < 0.01) compared to the other age groups. PM_2.5 air pollution was found to have a direct positive correlation with the number of wheezing episodes (r = 0.87; p < 0.01) in November 2015. Monitoring of wheezing occurrences in the absence of fever can provide a reliable assessment of the air pollution effect on the exacerbation of asthma and respiratory disorders in sensitive children.

Water-soluble ionic species of coarse and fine particulate matter and gas precursor characteristics at urban and rural sites of central Taiwan

Coarse and fine particulate matter (PM) were taken by a dichotomous sampler, and gas precursors were determined by a denuder sampler at two stations in central Taiwan. Water-soluble ionic constituents of PM and their precursor gases were analyzed by ionic chromatograph. In summer, the daytime/nighttime PM10 concentrations were 37 ± 10/41 ± 18 μg m(-3) and 36 ± 14/34 ± 18 μg m(-3) for Xitun and Jhushan, respectively. Average PM10 concentration in winter was 1.55 and 1.76 times that of summer for Xitun and Jhushan, respectively. PM mass concentrations were similar for both stations, although one station is located in the downtown area of Taichung, and the other is in a rural area with no heavy pollution sources. Water-soluble ionic species content was 38-53 % of PM2.5 and 43-48 % of PM10 mass concentration. HNO3, HCl, and SO2 were high in the daytime; the daytime-to-nighttime concentration ratio was 3.75-6.88 for HNO3,1.7-7.8 for HCl, and 1.45-2.77 for SO2. High NH3 levels were determined in the area, especially in winter, which could be a precursor of NH4 (+) to form particulate matter. In Xitun, motor vehicles downtown and in the industrial district could be sources of air pollution. In contrast, there are few industrial sources at Jhushan; therefore, the transport of air pollutants from upwind of other regions and the accumulation of pollutants could be important PM sources at Jhushan.

Estimation of exposure to atmospheric pollutants during pregnancy integrating space-time activity and indoor air levels: Does it make a difference?

Studies of air pollution effects during pregnancy generally only consider exposure in the outdoor air at the home address. We aimed to compare exposure models differing in their ability to account for the spatial resolution of pollutants, space-time activity and indoor air pollution levels. We recruited 40 pregnant women in the Grenoble urban area, France, who carried a Global Positioning System (GPS) during up to 3 weeks; in a subgroup, indoor measurements of fine particles (PM2.5) were conducted at home (n=9) and personal exposure to nitrogen dioxide (NO2) was assessed using passive air samplers (n=10). Outdoor concentrations of NO2, and PM2.5 were estimated from a dispersion model with a fine spatial resolution. Women spent on average 16 h per day at home. Considering only outdoor levels, for estimates at the home address, the correlation between the estimate using the nearest background air monitoring station and the estimate from the dispersion model was high (r=0.93) for PM2.5 and moderate (r=0.67) for NO2. The model incorporating clean GPS data was less correlated with the estimate relying on raw GPS data (r=0.77) than the model ignoring space-time activity (r=0.93). PM2.5 outdoor levels were not to moderately correlated with estimates from the model incorporating indoor measurements and space-time activity (r=-0.10 to 0.47), while NO2 personal levels were not correlated with outdoor levels (r=-0.42 to 0.03). In this urban area, accounting for space-time activity little influenced exposure estimates; in a subgroup of subjects (n=9), incorporating indoor pollution levels seemed to strongly modify them.

Comparison of sources of variability in school age children exposure to ambient PM₂.₅

School age children are particularly susceptible to exposure to ambient fine particle (PM2.5). To provide insight into factors affecting variability in ambient PM2.5 exposure, distributions of daily PM2.5 exposures for school age children are estimated for four seasons in three climatic zones of the United States using a stochastic microenvironmental exposure model, based on ambient concentration, air exchange rate, penetration factor, deposition rate, census data, meteorological data, and time pattern data. Estimated daily individual exposure varies largely among seasons, regions, and individuals. The mean ratio of ambient exposure to ambient concentration (Ea/Ca) ranges from 0.46 to 0.61 among selected regions and seasons, resulting from differences in air exchange rate. The individual Ea/Ca varies by a factor of 2 to 3 over a 95% frequency range among simulated children, resulting from variability in children's time patterns. These patterns are similar among age groups, but vary with the day of the week and outdoor temperature. Variability in exposure is larger between individuals than between groups. The high end ratio of the Ea/Ca, at the 95th percentile of inter-individual variability, is 30% to 50% higher than the mean Ea/Ca ratio. Results can be used to intepret and adjust exposure errors in epidemiology and to assist in development of exposure mitigation strategies.

The microenvironmental modelling approach to assess children's exposure to air pollution - A review

Exposures to a wide spectrum of air pollutants were associated to several effects on children's health. Exposure assessment can be used to establish where and how air pollutants' exposures occur. However, a realistic estimation of children's exposures to air pollution is usually a great ethics challenge, especially for young children, because they cannot intentionally be exposed to contaminants and according to Helsinki declaration, they are not old enough to make a decision on their participation. Additionally, using adult surrogates introduces bias, since time-space-activity patterns are different from those of children. From all the different available approaches for exposure assessment, the microenvironmental (ME) modelling (indirect approach, where personal exposures are estimated or predicted from microenvironment measurements combined with time-activity data) seemed to be the best to assess children's exposure to air pollution as it takes into account the varying levels of pollution to which an individual is exposed during the course of the day, it is faster and less expensive. Thus, this review aimed to explore the use of the ME modelling approach methodology to assess children's exposure to air pollution. To meet this goal, a total of 152 articles, published since 2002, were identified and titles and abstracts were scanned for relevance. After exclusions, 26 articles were fully reviewed and main characteristics were detailed, namely: (i) study design and outcomes, including location, study population, calendar time, pollutants analysed and purpose; and (ii) data collection, including time-activity patterns (methods of collection, record time and key elements) and pollution measurements (microenvironments, methods of collection and duration and time resolution). The reviewed studies were from different parts of the world, confirming the worldwide application, and mostly cross-sectional. Longitudinal studies were also found enhancing the applicability of this approach. The application of this methodology on children is different from that on adults because of data collection, namely the methods used for collecting time-activity patterns must be different and the time-activity patterns are itself different, which leads to select different microenvironments to the data collection of pollutants' concentrations. The most used methods to gather information on time-activity patterns were questionnaires and diaries, and the main microenvironments considered were home and school (indoors and outdoors). Although the ME modelling approach in studies to assess children's exposure to air pollution is highly encouraged, a validation process is needed, due to the uncertainties associated with the application of this approach.

Indoor aerosols: from personal exposure to risk assessment

Motivated by growing considerations of the scale, severity, and risks associated with human exposure to indoor particulate matter, this work reviewed existing literature to: (i) identify state-of-the-art experimental techniques used for personal exposure assessment; (ii) compare exposure levels reported for domestic/school settings in different countries (excluding exposure to environmental tobacco smoke and particulate matter from biomass cooking in developing countries); (iii) assess the contribution of outdoor background vs indoor sources to personal exposure; and (iv) examine scientific understanding of the risks posed by personal exposure to indoor aerosols. Limited studies assessing integrated daily residential exposure to just one particle size fraction, ultrafine particles, show that the contribution of indoor sources ranged from 19% to 76%. This indicates a strong dependence on resident activities, source events and site specificity, and highlights the importance of indoor sources for total personal exposure. Further, it was assessed that 10-30% of the total burden of disease from particulate matter exposure was due to indoor-generated particles, signifying that indoor environments are likely to be a dominant environmental factor affecting human health. However, due to challenges associated with conducting epidemiological assessments, the role of indoor-generated particles has not been fully acknowledged, and improved exposure/risk assessment methods are still needed, together with a serious focus on exposure control.

Analysis of indoor air pollution trends and characterization of infiltration delay time using a cross-correlation method

High-density housing in close proximity to freeways in conjunction with high concentrations of traffic emissions may contribute to significant degradation of indoor air quality. Densely populated areas may also be targeted for intentional releases of biological or chemical agents because an urban release could result in higher morbidity and mortality from the attack. Since people tend to spend the majority of their time indoors, it is paramount to explore the relationships between outdoor and indoor air quality and, specifically, the time scales that characterize transport of airborne contaminants from outdoors to indoors. In the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study, a three-story row house with a flat face and roof and multiple rooms was used to investigate outdoor-to-indoor contaminant time scales. The building was located in the Sunset Park neighborhood of Brooklyn, NY, USA, in the vicinity of a major expressway and a heavily trafficked arterial road. It was found that the building shell has a profound impact on the indoor concentrations. A strong hourly periodicity (see Eisner et al., this issue, DOI: 10.1039/b907132f) in concentration outside the building during the morning "rush hour" was used as evidence to suggest that indoor contaminants originated from outdoor air penetration. Although the indoor concentrations followed a similar pattern, indoor concentrations were found to be more persistent than outdoor concentrations. Stronger persistency is used here to describe the tendency of the indoor concentration to continue to rise even if the outdoor concentration has started to drop, or vice versa. This may be an important factor in assessing negative health risks to inhabitants or first responders. A cross-correlation technique was employed to study the correlation between outdoor and indoor time series. In the high-density housing residential building used in the study, it was found that a long lag time exists (11 min) before indoor and outdoor concentrations reach maximal correlation.

Personal PM10 exposure in asthmatic adults in Padova, Italy: seasonal variability and factors affecting individual concentrations of particulate matter

Personal exposure to PM(10) measured in different seasons in a sample of asthmatic subjects living in Padova (Northern Italy) was compared with simultaneously measured outdoor PM(10) concentrations. The specific contribution of ambient PM(10) and other factors to individual exposure was evaluated in one of the areas of Europe with the worst air pollution. Thirty-one asthmatic subjects (21 non-smokers and 10 smokers) carried personal PM(10) monitors for six 24-hr sessions, in different seasons of the year. Concomitant daily 24-hr ambient PM(10) concentrations were measured by air quality monitoring networks. A multivariate analysis was performed to identify factors explaining personal exposure to PM(10), using a random effect model. The analysis on the 31 subjects referred to a total of 155 observations. The mean personal PM(10) exposure was higher (range 79.3-126.1microg/m(3)) than the outdoor concentrations (range 37.3-85.4microg/m(3)) in all seasons; and personal exposures varied less than outdoor PM(10) levels from one season to another. Smokers had significantly higher personal PM(10) concentrations than non-smokers (127.99 vs 78.8microg/m(3); T=-5.70; p<0.001). Moderate correlations emerged between outdoor and personal PM(10) concentrations. The correlation improved after excluding subjects exposed to active or passive smoking (median Pearson's R 0.41 vs 0.26). Considering all the subjects, smoking was the main factor affecting personal exposure, contributing to 41% of the variability. Outdoor PM(10) concentrations (25%), temperature (12%) and season (15%) also contributed to personal PM(10) exposure. Outdoor PM(10) (46%), temperature (20%), season (19%) and time spent indoors (6%) were significantly associated with personal exposure in non-smokers. We concluded that it is crucial to perform personal monitoring and to evaluate the complexity of factors that contribute to individual PM exposure. While tobacco smoke was the primary source of PM(10) in all subjects, the contribution of ambient components was particularly relevant for the personal exposure levels of our non-smokers living in a highly-polluted environment.

Predicting personal exposure of pregnant women to traffic-related air pollutants

As epidemiological studies report associations between ambient air pollution and adverse birth outcomes, it is important to understand determinants of exposures among pregnant women. We measured (48-h, personal exposure) and modeled (using outdoor ambient monitors and a traffic-based land-use regression model) NO, NO(2), fine particle mass and absorbance in 62 non-smoking pregnant women in Vancouver, Canada on 1-3 occasions during pregnancy (total N=127). We developed predictive models for personal measurements using modeled ambient concentrations and individual determinants of exposure. Geometric mean exposures of personal samples were relatively low (GM (GSD) NO=37 ppb (2.0); NO(2)=17 ppb (1.6); 'soot', as filter absorbance=0.8 10(-5) m(-1) (1.5); PM(2.2)=10 microg m(-3) (1.6)). Having a gas stove (vs. electric stove) in the home was associated with exposure increases of 89% (NO), 44% (NO(2)), 20% (absorbance) and 35% (fine PM). Interpolated concentrations from outdoor fixed-site monitors were associated with all personal exposures except NO(2). Land-use regression model estimates of outdoor air pollution were associated with personal NO and NO(2) only. The effects of outdoor air pollution on personal samples were consistent, with and without adjustment for other individual determinants (e.g. gas stove). These findings improve our understanding of sources of exposure to air pollutants among pregnant women and support the use of outdoor concentration estimates as proxies for exposure in epidemiologic studies.

Relationship between indoor, outdoor, and personal fine particle concentrations for individuals with COPD and predictors of indoor-outdoor ratio in Mexico city

Personal exposure and indoor and outdoor exposure to PM(10) and PM(2.5) of 38 individuals with chronic obstructive pulmonary disease (COPD) was characterized from February through November 2000. All participants lived in Mexico City and were selected based on their area of residence southeast (n=15), downtown (n=15), and southwest (n=8). Participants were monitored at home using personal PM(2.5) monitoring devices. Indoor and outdoor levels of PM(10) and PM(2.5) were measured using MiniVol samplers. Concurrent individual exposure measurements, indoor and outdoor levels of PM(2.5), which averaged 38.4 (SD 21.4), 30.6 (SD 15.8), and 30.5 mug/m(3) (SD 19.4), respectively. Indoor PM(2.5) concentrations explained 40% of the variability of personal exposure. In addition, the factors that most affected personal exposure were regular indoor contact with animals, mold, cooking activities, and aerosol use, indicating that internal sources may largely affect individual exposure.

Long-term personal exposure to traffic-related air pollution among school children, a validation study

Several recent studies suggest an association between long-term exposure to traffic-related air pollution and health. Most studies use indicators of exposure such as outdoor air pollution or traffic density on the street of residence. Little information is available about the validity of these measurements as an estimate of long-term personal exposure to traffic-related air pollution. In this pilot study, we assessed outdoor and personal exposure to traffic-related air pollution in children living in homes on streets with different degree of traffic intensity. The personal exposure of 14 children aged 9-12 years to 'soot', NO(x) (NO and NO(2)) was assessed in Amsterdam between March and June 2003. Each child's personal exposure was monitored during four repeated 48-h periods. Concurrently, in- and outdoor NO(x) measurements were carried out at the school and at the home of each participating child. Measurements were supplemented by a questionnaire on time activity patterns and possible indoor sources. Flow-controlled battery operated pumps in a made-to-fit backpack were used to sample personal exposure to 'soot', determined from the reflectance of PM(2.5) filters. Exposure to NO(x) was assessed using Ogawa passive samplers. Children living near busy roads were found to have a 35% higher personal exposure to 'soot' than children living at an urban background location, despite that all children attended the same school that was located away from busy roads. Smaller contrasts in personal exposure were found for NO (14%), NO(2) (15%) and NO(x) (14%). This finding supports the use of 'living near a busy road' as a measure of exposure in epidemiological studies on the effects of traffic-related air pollution in children.

Variability of total exposure to PM2.5 related to indoor and outdoor pollution sources Krakow study in pregnant women

The study is a part of an ongoing prospective cohort study on the relationship between the exposure to environmental factors during pregnancy and birth outcomes and health of newborns. We have measured personal PM(2.5) level in the group of 407 non-smoking pregnant women during the 2nd trimester of pregnancy. On average, the participants from the city center were exposed to higher exposure than those from the outer city area (GM=42.0 microg/m(3), 95% CI: 36.8-48.0 vs. 35.8 microg/m(3), 95% CI: 33.5-38.2 microg/m(3)). More than 20% of study subjects were affected by high level of PM(2.5) pollution (above 65 microg/m(3)). PM(2.5) concentrations were higher during the heating season (GM=43.4 microg/m(3), 95% CI: 40.1-46.9 microg/m(3)) compared to non-heating season (GM=29.8 microg/m(3), 95% CI: 27.5-32.2 microg/m(3)). Out of all potential outdoor air pollution sources (high traffic density, bus depot, waste incinerator, industry etc.) considered in the bivariate analysis, only the proximity of industrial plant showed significant impact on the personal exposure (GM=54.3 microg/m(3), 95% CI: 39.4-74.8 microg/m(3)) compared with corresponding figure for those who did not declare living near the industrial premises (GM=36.2 microg/m(3), 95% CI: 34.1-38.4 microg/m(3)). The subjects declaring high exposure to ETS (>10 cigarettes daily) have shown very high level of personal exposure (GM=88.8 microg/m(3), 95% CI: 73.9-106.7 microg/m(3)) compared with lower ETS exposure (< or =10 cigarettes) (GM=46.3 microg/m(3), 95% CI: 40.0-53.5 microg/m(3)) and no-ETS exposure group (GM=33.9 microg/m(3), 95% CI: 31.8-36.1 microg/m(3)). The contribution of the background ambient PM(10) level was very strong determinant of the total personal exposure to PM(2.5) and it explained about 31% of variance between the subjects followed by environmental tobacco smoke (10%), home heating by coal/wood stoves (2%), other types of heating (2%) and the industrial plant localization in the proximity of household (1%).

[Air pollution and asthma in children]

The prevalence of asthma and allergic diseases has increased world-wide during the last quarter of the 20th century, particularly among children and adolescents. No change common to all sites where asthma has increased throughout the world has been identified, suggesting that this 'epidemic' phenomenon is likely due to multiple factors. The following have been most discussed: exposure to indoor and outdoor allergens, modification of the patterns of respiratory infections, decreasing trends of physical activity, evolution in the make-up of environmental irritants, including tobacco smoke and urban air toxicants. In this review, we point out the role of exposure to air pollutants, in addition to and in combination with other asthma enhancers or precipitators. Whereas concentrations of the 'classical' air quality indicators (SO2, CO) have more or less steadily decreased, asthma prevalence augmented in developed countries during the same period. However, the nature of the air pollution mix has deeply evolved, and should also be considered. Ambient air concentrations of industrial and house heating combustion sources of pollutants in the city have substantially decreased, but by contrast the concentrations of various ultrafine particles have increased. Now, there is in vitro and in vivo evidence that exposure to urban air particles, and particularly to diesel exhausts, elicits chronic oxidative stress and repeated inflammatory responses, so that they may enhance allergic inflammation and airway hyper-responsiveness. Several epidemiological studies suggested an association between traffic density close to places of children's residence and prevalence of respiratory symptoms, and more specifically of asthma or allergic rhinitis symptoms in them. Chronic exposure during infancy to traffic-related pollutants may accelerate or even provoke, among genetically sensitive subjects, disruption of the normal regulatory and repair processes eventually contributing to the increase of asthma incidence.

Long duration tests of room air filters in cigarette smokers' homes

Information regarding the long-term performance of stand-alone room airfilters is limited. In this study, laboratory and field tests were carried out to determine the effectiveness and performance of room filters that are easily deployed in essentially any type of house. Tests were conducted in houses containing strong PM sources, specifically cigarette smokers. Using commercially available four-speed HEPA filter units, we tested flow rate, pressure drop, and power consumption as a function of fan speed and filter loading. Filters were then deployed in four single-family homes over a 2 month period. Between 15 and 40 cigarettes were smoked daily by several smokers in each home. Occupants were instructed to continuously operate the unit at one of the higher speeds. Periodically, we monitored filter usage, fan speed, particulate matter (PM) mass concentrations, PM number concentrations, volatile organic compound (VOC) levels, and other parameters with the filter fan operating and with filters both installed and removed. The filters decreased PM concentrations by 30-70%, depending on size fraction and occupant activities, and significantly reduced the half-life of PM3-1.0. The half-life of 1-5 microm particles, CO2 concentrations, and VOC concentrations, including 2,5-dimethyl furan (a tracer for environmental tobacco smoke), did not change, indicating that occupancy and cigarette smoking intensity did not change overthe monitoring periods. Occupants generally kept the filters operating at a moderate speed. Filter air flow rates decreased 7-14% with extended operation, largely due to the loading of prefilters. Air exchange rates, deposition loss rates, and clean air delivery rates were estimated from the field data. Continuous operation at an intermediate fan speed would incur a total annualized cost of $236. While acceptance of the filters was very high, occupants might benefit from instructions and reminders to clean the prefilter and to keep the unit on. We conclude that adequately sized room air filters can substantially lower PM concentrations in smoker's homes if air exchange rates are limited and that the filters can maintain their performance over extended periods.

Indoor exposures and acute respiratory effects in two general population samples from a rural and an urban area in Italy

A study of indoor air exposures and acute respiratory effects in adults was conducted in the Po Delta (rural) and Pisa (urban) areas of Italy. Indoor exposures were monitored for nitrogen dioxide (NO(2)) and particulate matter <2.5 microm (PM(2.5)) for 1 week during the winter or summer in a total of 421 houses (2/3 in Pisa). Information on house characteristics, subjects' daily activity pattern and presence of acute respiratory symptoms was collected by a standardized questionnaire. Peak expiratory flow (PEF) maneuvers were performed by adult subjects four times daily; maximum amplitude and diurnal variation were taken into account. Indices of NO(2) and PM(2.5) exposures were computed as the product of weekly mean pollutant concentration by the time of daily exposure. Mean levels of pollutants were significantly higher in winter than in summer, regardless of the area. The relationship between exposure indices and acute respiratory symptoms was investigated only in winter. In spite of a slightly lower indoor level in the urban than in the rural area in winter (NO(2): 15 vs. 22 ppb; PM(2.5): 67 vs. 76 microg/m(3)), prevalence rates of acute respiratory symptoms were significantly higher in the urban than in the rural area. Acute respiratory illnesses with fever were significantly associated with indices of NO(2) (odds ratio (OR)=1.66; 95% CI=1.08-2.57) and PM(2.5) exposures (OR=1.62; 95% CI=1.04-2.51), while bronchitic/asthmatic symptoms were associated only with PM(2.5) (OR=1.39; 95% CI=1.17-1.66). PEF variability was positively related only to PM(2.5) exposure index (OR=1.38; 95% CI=1.24-1.54, for maximum amplitude; OR=1.37; 95% CI=1.23-1.53, for diurnal variation). In conclusion, indoor pollution exposures were associated with the presence of acute respiratory symptoms and mild lung function impairment in a rural and an urban area of Northern-Central Italy.