Temporal associations of ambient PM2.5 elemental concentrations with indoor and personal concentrations

doi:10.1016/j.atmosenv.2013.12.021

Atmospheric Environment

Volume 86, April 2014, Pages 203-211

https://doi.org/10.1016/j.atmosenv.2013.12.021 Get rights and content

Highlights

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Temporal associations of outdoor with indoor/personal concentrations were examined.
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We investigated Cu, Zn, Fe, K, Ni, V, Si and S elemental concentrations of PM_2.5.
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High temporal correlations were found for most elements.
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The highest correlations were found for S and V, the lowest for Cu.

Abstract

Time series studies increasingly evaluate health relevance of the elemental composition of particles smaller than 2.5 μm (PM_2.5). Validation studies have documented that temporal variation of outdoor PM_2.5 concentration is correlated with temporal variation of personal exposure, but very few papers have investigated the temporal correlation between outdoor concentration and personal exposure for the elemental composition of PM_2.5. We evaluated the temporal association between outdoor concentration and personal exposure for the elements copper (Cu), zinc (Zn), iron (Fe), potassium (K), nickel (Ni), vanadium (V), silicon (Si) and sulfur (S) in three European cities.

In Helsinki (Finland), Utrecht (the Netherlands) and Barcelona (Spain) five participants from urban background, five from suburban/rural background and five from busy street sites were selected (15 participants per city). Six outdoor, indoor and personal 96-h average PM_2.5 concentrations were measured simultaneously in three different seasons (winter, summer and spring/autumn). Concurrently, samples were collected at a central reference site, reflecting urban background air pollution levels. The temporal variation at the central site was highly correlated with personal exposure for all elements, except Cu. The highest correlations (Pearson's R) were found for S and V (R between 0.87 and 0.98). Lower correlations were found for the elements Cu, Fe and Si associated with non-tailpipe traffic emissions and road dust (Pearson's R between −0.34 and 0.79). For PM_2.5 mass the R was lower (between 0.37 and 0.70). Exclusion of observations most affected by indoor sources increased the personal to central site correlations but did not fully explain differences between elements. The generally high correlation between temporal variation of the outdoor concentration and personal exposure supports the use of a central site for assessing exposure of PM components in time series studies for most elements. The different correlations found for the eight elements suggests that epidemiological associations are affected by differences in measurement error.

Introduction

Particulate matter with a diameter of less than 2.5 μm (PM_2.5) has been associated with adverse health effects. However, less is known about which constituents of PM_2.5 or which sources of particles are primarily responsible for these adverse health effects (Stanek et al., 2011, Kelly and Fussell, 2012, Rohr and Wyzga, 2012, Bell, 2012). The ambient concentrations of these components vary temporally due to changes in weather and emissions. For many epidemiologic air pollution time series studies, a central monitoring site is used to determine the exposure of study subjects. Previous studies have shown that the ambient concentrations of PM_2.5 at a fixed site can be a good predictor for personal exposure, but the accuracy is dependent on the characteristics of participants, studies, and the environments in which they are conducted (Avery et al., 2010). Very few papers have investigated the short term temporal correlations between outdoor and personal elemental concentrations of PM_2.5 (Janssen et al., 2005). A study in Amsterdam and Helsinki found that with the exception of sulfur and PM absorbance as a measure of Black Carbon, longitudinal correlations between personal and outdoor Cu, Zn, Fe, K, Ni, V, Si and S elemental concentrations were less than the correlations for PM_2.5 which were 0.76 in Amsterdam and 0.74 in Helsinki (Janssen et al., 2005).

The aim of this paper is to assess the association between temporal variation in ambient concentrations of fine particle components at a central reference site and temporal variation in indoor and personal concentrations.

The study utilized repeated personal exposure measurements in Barcelona, Utrecht and Helsinki performed in the framework of the Validation of ESCAPE Exposure EstimateS using Personal exposure Assessment (VE³SPA) project (Montagne et al., 2013). VE³SPA was designed to evaluate how well land use regression models developed by the European Study of Cohorts for Air Pollution Effects (ESCAPE) project reflected spatial variation of outdoor, indoor and personal exposure (Eeftens et al., 2012b). The results for the spatial analyses have been published elsewhere for PM2.5, NO₂ and soot (Montagne et al., 2013) and will be published elsewhere for the elemental composition.

Section snippets

Study design

PM_2.5, soot (light absorbance of PM_2.5 filters), NO₂ and NO_x were measured and the PM_2.5 filters samples were chemically analyzed for elemental composition. Eight trace elements were a priori selected to represent different sources of air pollution, copper (Cu), zinc (Zn), iron (Fe), potassium (K), nickel (Ni), vanadium (V), silicon (Si) and sulfur (S). These eight elements were the elements selected in ESCAPE for land use regression modeling and epidemiological analysis (De Hoogh et al., 2013

Quality control

For most elements, more than 75% of the samples exceeded the detection limit (Table 1). For zinc (Zn) this percentage was slightly lower (68%), but was 100% if one extreme blank was excluded. This high blank measurement was excluded in all analyses. The coefficients of variance (CV) for the duplicate measurements, including the personal duplicate measurements, are shown in Table 2. CV values were fairly high, often exceeding 20%.

Descriptive results

The median, first and third quartile concentrations for the

Correlations with elemental exposure

Central site concentrations correlated well with home outdoor concentrations. Correlations were higher for S and V than for Cu, Fe and Si. The latter elements reflect the tail of coarse particles, which have more local sources compared to fine particles and therefore show different temporal patterns at different sites (close/far away from source) (Puustinen et al., 2007).

A statistically significant temporal relationship of the concentrations at a central site with personal concentrations was

Acknowledgments

The authors thank the volunteers for their participation and dedication in the project. The project was funded by Concawe (conservation of clean air and water in Europe), contract number 200907200, date 20-07-09.

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Personal exposure to PM_2.5, and the elemental composition therein, may vary greatly from ambient measurements at fixed monitoring sites. Here, we characterized the differences between personal, indoor, and outdoor concentrations of PM_2.5-bound elements, and predicted personal exposures to 21 PM_2.5-bound elements. Personal-indoor-outdoor PM_2.5 filter samples were collected for five consecutive days across two seasons from 66 healthy non-smoking retired adults in Beijing (BJ) and Nanjing (NJ), China. Personal element-specific models were developed using liner mixed effects models and evaluated by R² and root mean square error (RMSE). The mean (SD) concentrations of personal exposures varied by element and city, ranging from 2.5 (1.4) ng/m³ for Ni in BJ to 4271.2 (1614.8) ng/m³ for S in NJ. Personal exposures to PM_2.5 and most elements were significantly correlated with both indoor and outdoor (except Ni in BJ) measurements, but frequently exceeded indoor levels and fell below outdoor levels. Indoor and outdoor PM_2.5 elemental concentrations were the strongest determinants of most personal elemental exposures, with $R_{M}^{2}$ ranging from 0.074 to 0.975 for indoor and from 0.078 to 0.917 for outdoor levels, respectively. Home ventilation conditions (especially window opening behavior), time-activity patterns, meteorological factors, household characteristics, and season were also key factors influencing personal exposure levels. The final models accounted for 24.2 %–94.0 % (RMSE: 0.135–0.718) of the variance in personal PM_2.5 elemental exposures. By incorporating these crucial determinants, the modeling approach used here can improve PM_2.5-bound elemental exposure estimates and better associate compositionally dependent PM_2.5 exposures and health risks.
Validity of using ambient concentrations as surrogate exposures at the individual level for fine particle and black carbon: A systematic review and meta-analysis
2022, Environmental Pollution
Exposure measurement error is an important source of bias in epidemiological studies. We assessed the validity of employing ambient (outdoor) measurements as proxies of personal exposures at individual levels focusing on fine particles (PM_2.5) and black carbon (BC)/elemental carbon (EC) on a global scale. We conducted a systematic review and meta-analysis and searched databases (ISI Web of Science, Scopus, PubMed, Ovid MEDLINE®, Ovid Embase, and Ovid BIOSIS) to retrieve observational studies in English language published from 1 January 2006 until 5 May 2021. Correlation coefficients (r) between paired ambient (outdoor) concentration and personal exposure for PM_2.5 or BC/EC were standardized as effect size. We used random-effects meta-analyses to pool the correlation coefficients and investigated the causes of heterogeneity and publication bias. Furthermore, we employed subgroup and meta-regression analyses to evaluate the modification of pooled estimates by potential mediators. This systematic review identified thirty-two observational studies involving 1744 subjects from ten countries, with 28 studies for PM_2.5 and 11 studies for BC/EC. Personal PM_2.5 exposure is more strongly correlated with ambient (outdoor) concentrations (0.63, 95% confidence interval [CI]: 0.57–0.68) than personal BC/EC exposure (0.49, 95% CI: 0.38–0.59), with significant differences in ṝ (0.14, 95% CI: 0.03–0.25; p < 0.05). The results demonstrated that the health status of participants was a significant modifier of pooled correlations. In addition, the personal to ambient (P/A) ratio for PM_2.5 and average ambient BC/EC levels were potential effect moderators of the pooled $ṝ$ . The funnel plots and Egger's regression test indicated inevident publication bias. The pooled estimates were robust through sensitivity analyses. The results support the growing consensus that the validity coefficient of proxy measures should be addressed when interpreting results from epidemiological studies to better understand how strong health outcomes are affected by different levels of PM_2.5 and their components.
Chemical characteristics and oxidative potential of indoor and outdoor PM<inf>2.5</inf> in densely populated urban slums
2022, Environmental Research
Citation Excerpt :
Previous studies conducted in the cities of United States (Baxter et al., 2007; Hasheminassab et al., 2014), Spain (Montagne et al., 2014; Rivas et al., 2015), China (Han et al., 2016) and Qatar (Saraga et al., 2017) reported strong correlation between indoor and outdoor concentrations of S (r ranging 0.88–0.95), BC (0.70–0.97) and Zn (0.53–0.97) as observed in this study. Baxter et al. (2007) and Montagne et al. (2014) reported strong indoor vs outdoor correlation for K (r ranging 0.72–0.89) similar to this study. BC and Zn are identified as exhaust and non-exhaust emissions respectively (Perrino et al., 2015; Jeong et al., 2019).
A significant proportion of population in metropolitan cities in India live in slums which are highly dense and crowded informal housing settlements with poor environmental conditions including high exposure to air pollution. Recent studies report that toxicity is induced by oxidative processes, mediated by the water-soluble PM chemical components leading to reactive oxygen species production thereby causing inflammatory disorders. Hence, for the first time, this study assessed the chemical characteristics and oxidative potential (OP) of indoor and outdoor PM_2.5 in two slums in Mumbai, India. Daily gravimetric PM_2.5 was measured in ∼40 homes each in a low- and a high-traffic slum and analysed for 18 water-soluble elements and organic carbon (WSOC). Subsequently, OP was assessed through the Dithiothreitol (DTT) assay. Average WSOC was similar in indoor and outdoor environments while the water-soluble concentrations of total elements ranged 4.5–6.5 μg/m³ indoors and 6.4–19.2 μg/m³ outdoors, with S, Ca, K, Na and Zn being the most abundant elements. Spatial distributions of indoor concentrations were influenced by outdoor sources such as local traffic emissions for Cd, Fe, Al and Zn. The influence of outdoor-origin particles was enhanced in homes reporting high air exchange rates. OP was higher outdoors than indoors in both low-traffic slum (0.04–0.51 nmol min⁻¹m⁻³ outdoors and 0.02–0.38 nmol min⁻¹m⁻³ indoors) and high-traffic slum (0.03–1.06 nmol min⁻¹m⁻³ outdoors and 0.04–0.77 nmol min⁻¹m⁻³ indoors). Outdoor and indoor OP was also more influenced by outdoor road dust showing significant correlation with tracer elements Cu and Al (r ≥ 0.45; p < 0.05). Similar to OP, the non-carcinogenic health risk associated with indoor PM_2.5 were also higher in high-traffic slum (Hazard Index, HI = 1.60) than in low-traffic slum (HI = 0.43). Overall, this study shows that the indoor PM_2.5 and its chemical constituents in Mumbai slums are primarily of outdoor origin with higher toxicity and non-carcinogenic health risk in high-traffic slums.
Comparing human exposure to fine particulate matter in low and high-income countries: A systematic review of studies measuring personal PM<inf>2.5</inf> exposure
2022, Science of the Total Environment
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.
The aim of this systematic review is to assess the differences in the magnitude and sources of personal PM_2.5 exposures experienced between countries at contrasting levels of income.
This review summarised studies that measured participants personal exposure by carrying a PM_2.5 monitor throughout their typical day. Personal PM_2.5 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).
From the 2259 search results, there were 140 studies that met our criteria. Overall, personal PM_2.5 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 PM_2.5 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 PM_2.5 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.
This review revealed a growing literature of personal PM_2.5 exposure studies, which highlighted a large variability in exposures recorded and severe inequalities in geographical and social population subgroups.
A review and analysis of personal and ambient PM<inf>2.5</inf> measurements: Implications for epidemiology studies
2022, Environmental Research
In epidemiology studies, ambient measurements of PM_2.5 are often used as surrogates for personal exposures. However, it is unclear the degree to which ambient PM_2.5 reflects personal exposures.
In order to examine potential sources of bias in epidemiology studies, we conducted a review and meta-analysis of studies to determine the extent to which short-term measurements of ambient PM_2.5 levels are related to short-term measurements of personal PM_2.5 levels.
We conducted a literature search of studies reporting both personal and ambient measurements of PM_2.5 published in the last 10 years (2009–2019) and incorporated studies published prior to 2009 from reviews.
Seventy-one studies were identified. Based on 17 studies reporting slopes, a meta-analysis revealed an overall slope of 0.56 μg/m³ (95% CI: [0.39, 0.73]) personal PM_2.5 per μg/m³ increase in ambient PM_2.5. Slopes for summer months were higher (slope = 0.73, 95% CI: [0.64, 0.81]) than for winter (slope = 0.46, 95% CI: [0.36, 0.57]). Based on 44 studies reporting correlations, we calculated an overall personal-ambient PM_2.5 correlation of 0.63 (95% CI: [0.55, 0.71]). Correlations were stronger in studies conducted in Canada (r = 0.86, 95% CI: [0.67, 0.94]) compared to the USA (r = 0.60, 95% CI: [0.49, 0.70]) and China (r = 0.60, 95% CI: [0.46, 0.71]). Correlations also were stronger in urban areas (r = 0.53, 95% CI: [0.43, 0.62]) vs. suburban areas (r = 0.36, 95% CI: [0.21, 0.49]).
Our results suggest a large degree of variability in the personal-ambient PM_2.5 association and the potential for exposure misclassification and measurement error in PM_2.5 epidemiology studies.
Short-term personal and outdoor exposure to ultrafine and fine particulate air pollution in association with blood pressure and lung function in healthy adults
2021, Environmental Research
Studies reporting on associations between short-term exposure to outdoor fine (PM_2.5), and ultrafine particles (UFP) and blood pressure and lung function have been inconsistent. Few studies have characterized exposure by personal monitoring, which especially for UFP may have resulted in substantial exposure measurement error. We investigated the association between 24-h average personal UFP, PM_2.5, and soot exposure and dose and the health parameters blood pressure and lung function. We further assessed the short-term associations between outdoor concentrations measured at a central monitoring site and near the residences and these health outcomes.
We performed three 24-h personal exposure measurements for UFP, PM_2.5, and soot in 132 healthy adults from Basel (Switzerland), Amsterdam and Utrecht (the Netherlands), and Turin (Italy). Monitoring of each subject was conducted in different seasons in a one-year study period. Subject's activity levels and associated ventilation rates were measured using actigraphy to calculate the inhaled dose. After each 24-h monitoring session, blood pressure and lung function were measured. Contemporaneously with personal measurements, UFP, PM_2.5 and soot were measured outdoor at the subject's residential address and at a central site in the research area. Associations between short-term personal and outdoor exposure and dose to UFP, PM_2.5, and soot and health outcomes were tested using linear mixed effect models.
The 24-h mean personal, residential and central site outdoor UFP exposures were not associated with blood pressure or lung function. UFP mean exposures in the 2-h prior to the health test was also not associated with blood pressure and lung function. Personal, central site and residential PM_2.5 exposure were positively associated with systolic blood pressure (about 1.4 mmHg increase per Interquartile range). Personal soot exposure and dose were positively associated with diastolic blood pressure (1.2 and 0.9 mmHg increase per Interquartile range). No consistent associations between PM_2.5 or soot exposure and lung function were observed.
Short-term personal, residential outdoor or central site exposure to UFP was not associated with blood pressure or lung function. Short-term personal PM_2.5 and soot exposures were associated with blood pressure, but not lung function.

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Temporal associations of ambient PM2.5 elemental concentrations with indoor and personal concentrations

Highlights

Abstract

Introduction

Section snippets

Study design

Quality control

Descriptive results

Correlations with elemental exposure

Acknowledgments

Atmos. Environ.

Environ. Res.

Atmos. Environ.

Atmos. Environ.

Atmos. Environ.

Atmos. Environ.

Atmos. Environ.

Atmos. Environ.

Atmos. Environ.

Atmos. Environ.

Atmos. Environ.

Atmos. Environ.

J. Aeros. Sci.

Estimating error in using ambient PM2.5 concentrations as proxies for personal exposures: a review

Epidemiology

Temporal associations of ambient PM_2.5 elemental concentrations with indoor and personal concentrations