Validity of using annual mean particulate matter concentrations as measured at fixed site in assessing personal exposure: An exposure assessment study in Japan

Michikawa, Takehiro; Nakai, S.; Nitta, Hiroshi; Tamura, Kenji

doi:10.1016/j.scitotenv.2013.07.084

Cited by 18 publications

(7 citation statements)

References 21 publications

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“…In many presentations elsewhere they analyzed PM satellite data, which may not truly reflect population exposure, given unknown time spent indoors/outdoors, smoking pattern, level of physical activity, buildings density in the city and other unmeasured confounding. Although the correlation between fixed-site measurements and personal mean concentrations for PM 10 was acceptable (r = 0.58) [15], personal measurements are advantageous, but require more resources and may yield variability in concentrations. Another strength of this analysis is the overall long sampling time, 960 hours.…”

Section: Discussionmentioning

confidence: 98%

“…Despite moderate to high correlation between the ambient PM 10 concentrations and personal exposure [14,15], the former can unlikely serve a surrogate to estimate personal exposure to PM 10 in the outdoor workplaces, given that the correlation is different for PM 10 compared to PM 2.5 [14]. Furthermore, no personal exposure to PM 10 in the outdoor workplaces has ever been verified in the cities of Kazakhstan.…”

Section: Introductionmentioning

confidence: 99%

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Occupational exposure to particulate matter from air pollution in the outdoor workplaces in Almaty during the cold season

2020

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Background A large fraction of population in Almaty and other Kazakhstan cities is employed in the outdoor jobs and likely exposed to high levels of particulate matter (PM) during the cold season. The magnitude of such occupational exposure remains unknown; therefore, the aim was to quantify the levels of exposure to PM 10 in the outdoor workplaces in Almaty in order to guide future interventions of primary prevention. Methods Outdoor security non-smoking guards (N = 12) wore TSI DustTrack AM520 aerosol monitors with a 10-μm impactor for 8 hours of outdoor shift. Ten samples (k = 10) from each worker were obtained for the cold season (November-March) from various locations across Almaty. Total sampling time was 57600 minutes. We compared normalized time-weighted average (TWA) concentrations for 8-hour shifts within and between workers using analysis of variance (ANOVA) and assessed compliance with environmental exposure limit (EEL) (0.060 mg/m 3) via exceedance (γ) and probability of overexposure (θ). Results PM 10 TWA ranged from 0.050 to 2.075 mg/m 3 with the geometric mean 0.366 and median 0.352 mg/m 3. PM 10 TWA distribution was left-skewed with large variation. The fold-range of within-person variability, containing 95% of the exposure concentration (w R 0.95) was 13, whereas between-person fold-range (b R 0.95) was 3. However, between-person variance exceeded the one within with F-ratio 2.797 (p = 0.003) with statistical power 97% at α = 0.05. Only two of 120 samples had TWA below EEL, yielding γ = 0.995 and θ = 1. Conclusions Outdoor workers in polluted cities like Almaty are exposed to very high levels of PM 10 during the cold season. Urgent action should be taken to regulate such occupational exposure and to raise awareness of workers and employers on hazards associated with it.

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Section: Discussionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Occupational exposure to particulate matter from air pollution in the outdoor workplaces in Almaty during the cold season

2020

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“…Space-time kriging technique, when lacking adequate number of monitors, may fail to capture a concentration hotspot in microenvironments such as locations found near roadways. Further, using ambient concentrations to represent exposure can introduce exposure error because people spend more time indoors [ 8 , 9 , 10 ]. These findings motivated this study to quantify the associated potential exposure error to reduce the possible bias in future epidemiological analysis for the CADEE study.…”

Section: Discussion and Limitationsmentioning

confidence: 99%

“…A more accurate method for estimating personal exposure is with direct measurement using personal sampling devices [ 8 , 9 ]. For example, Delfino et al [ 10 ] compared the association between the reduction in forced expiratory volume in the first second (FEV1) of asthmatic children and four particulate matter (PM) exposure metrics: personal sampling device, indoor concentration at home, outdoor concentration at home, and data from central monitor.…”

Section: Introductionmentioning

confidence: 99%

“…Although ambient concentration is widely used in health studies as an exposure metric, certain studies have found that indoor concentrations would be a better exposure metric due to time spent indoors [ 8 , 9 , 10 ]. The Windsor, Ontario Exposure Assessment study has shown that children spend on average more than 67% of their time indoors and receive more than 50% of their PM 2.5 exposure while indoors [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Highly Resolved Model-Based Exposure Metrics for Traffic-Related Air Pollutants to Support Environmental Health Studies

Chang

Vizuete

Breen

et al. 2015

IJERPH

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Human exposure to air pollution in many studies is represented by ambient concentrations from space-time kriging of observed values. Space-time kriging techniques based on a limited number of ambient monitors may fail to capture the concentration from local sources. Further, because people spend more time indoors, using ambient concentration to represent exposure may cause error. To quantify the associated exposure error, we computed a series of six different hourly-based exposure metrics at 16,095 Census blocks of three Counties in North Carolina for CO, NOx, PM2.5, and elemental carbon (EC) during 2012. These metrics include ambient background concentration from space-time ordinary kriging (STOK), ambient on-road concentration from the Research LINE source dispersion model (R-LINE), a hybrid concentration combining STOK and R-LINE, and their associated indoor concentrations from an indoor infiltration mass balance model. Using a hybrid-based indoor concentration as the standard, the comparison showed that outdoor STOK metrics yielded large error at both population (67% to 93%) and individual level (average bias between −10% to 95%). For pollutants with significant contribution from on-road emission (EC and NOx), the on-road based indoor metric performs the best at the population level (error less than 52%). At the individual level, however, the STOK-based indoor concentration performs the best (average bias below 30%). For PM2.5, due to the relatively low contribution from on-road emission (7%), STOK-based indoor metric performs the best at both population (error below 40%) and individual level (error below 25%). The results of the study will help future epidemiology studies to select appropriate exposure metric and reduce potential bias in exposure characterization.

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Particulate Matter (PM) and Fibers

Fromme

2023

Indoor Air Quality

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Validity of using annual mean particulate matter concentrations as measured at fixed site in assessing personal exposure: An exposure assessment study in Japan

Cited by 18 publications

References 21 publications

Occupational exposure to particulate matter from air pollution in the outdoor workplaces in Almaty during the cold season

Occupational exposure to particulate matter from air pollution in the outdoor workplaces in Almaty during the cold season

Comparison of Highly Resolved Model-Based Exposure Metrics for Traffic-Related Air Pollutants to Support Environmental Health Studies

Particulate Matter (PM) and Fibers

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