Time-activity Patterns Research Articles

Increased air pollution exposure among the Chinese population during the national quarantine in 2020.

The COVID-19 quarantine in China is thought to have reduced ambient air pollution. The overall exposure of the population also depends, however, on indoor air quality and human mobility and activities. Here, by integrating real-time mobility data and a questionnaire survey on time-activity patterns during the pandemic, we show that despite a decrease in ambient PM2.5 during the quarantine, the total population-weighted exposure to PM2.5 considering both indoor and outdoor environments increased by 5.7 μg m-3 (95% confidence interval, 1.2-11.0 μg m-3). The increase in population-weighted exposure was mainly driven by a nationwide urban-to-rural population migration before the Spring Festival coupled with the freezing of the migration backward due to the quarantine, which increased household energy consumption and the fraction of people exposed to rural household air pollution indoors. Our analysis reveals an increased inequality of air pollution exposure during the quarantine and highlights the importance of household air pollution for population health in China.

Impacts of implementing Healthy Building guidelines for daily PM2.5 limit on premature deaths and economic losses in urban China: A population-based modeling study

Given a large fraction of people’s exposure to urban PM2.5 occur indoors, reducing indoor PM2.5 levels may offer a more feasible and immediate way to save substantial lives and economic losses attributable to PM2.5 exposure. We aimed to estimate the premature mortality and economic loss reductions associated with achieving the newly established Chinese indoor air guideline and a few hypothetical indoor PM2.5 guideline values. We used outdoor PM2.5 concentrations from 1497 monitoring sites in 339 Chinese cities in 2015, coupled with a steady-state mass balance model, to estimate indoor concentrations of outdoor-infiltrated PM2.5. Using province-specific time-activity patterns for urban residents, we estimated outdoor and indoor exposures to PM2.5 of outdoor origin. We then proceeded to use localized census-based concentration-response models and the value of statistical life estimates to calculate premature deaths and economic losses attributable to PM2.5 exposure across urban China. Finally, we estimated potentially avoidable mortality and corresponding economic losses by meeting the current 24-hour based guideline and various hypothetical indoor limits for PM2.5. In 2015 in urban areas of mainland China, the city-specific annual mean outdoor and indoor PM2.5 concentrations ranged 9–108 μg/m3 and 5–56 μg/m3, respectively. Indoor exposures contributed 62%–91% daily and 68%–83% annually to the total time-weighted exposures. The potential reductions in total deaths and economic losses for the scenario in which daily indoor concentrations met the current guideline of 75 μg/m3, 37.5 μg/m3, and 25 μg/m3 were 16.9 (95% CI: 0.7–62.1) thousand, 87.7 (95% CI: 9.7–197.7) thousand, and 165.5 (95% CI: 30.8–304.0) thousand, respectively. The corresponding reductions in economic losses were 5.7 (95% CI: 0.2–34.8) billion, 29.4 (95% CI: 2.4–109.6) billion, and 55.2 (95% CI: 7.7–168.0) billion US Dollars, respectively. Deaths and economic losses would be reduced exponentially within the range of 0–75 μg/m3 for hypothetical indoor PM2.5 limits. The findings demonstrate the effectiveness of reducing indoor concentrations of outdoor-originated PM2.5 in saving substantial lives and economic losses in China. The analysis provides quantitative evidence to support the implementation of an indoor air quality guideline or standard for PM2.5.

Black Carbon Exposure Characteristics in Diesel Engine Vehicle-related Jobs

ABSTRACT We aimed to characterize the black carbon (BC) exposure from eight types of jobs involving diesel engine vehicles—namely, machinery operation, forklift operation, automobile assembly, garbage collection, garbage truck driving, delivery, toll operation, and crane operation—across seven industries. The workers chosen for this study (N = 106) measured their exposure every minute using an AE51 microAethalometer affixed to a microcyclone and also recorded their time-activity patterns and whereabouts in detail during working hours. We then categorized and analyzed 71,987 of these 1-min observations based on four potential exposure determinants: the operation of a diesel engine vehicle (yes or no), proximity to the source of BC (near or far), location of the workplace (indoor or outdoor), and type of work (moving or stationary). Among the participants, the geometric mean (GM) exposure was highest for forklift operators in indoor environments (9.5 µg m–3), followed by toll operators (GM = 7.4 µg m–3), machinery operators (GM = 7.4 µg m–3), and garbage collectors (GM = 5.5 µg m–3). After accounting for the random effects of the individual workers and working dates (evaluated per occupation) as well as the fixed effects of the determinants and their pairwise interaction terms (p < 0.001), we found that all four of the determinants significantly differed in their associated levels of BC exposure. In particular, working near instead of far from diesel engine equipment doubled the average level of exposure. Additionally, upon investigating different combinations of the determinants, we identified proximity to diesel exhaust sources and indoor working conditions as the main factors of BC exposure. Thus, installing diesel particulate filters on diesel engine vehicles effectively reduces exposure. Our findings potentially contribute to the development of a model that predicts the level of exposure for various types of jobs.

Indoor to Outdoor Ratio of Fine Particulate Matter by Time of the Day in House According to Time-activity Patterns

Indoor to Outdoor Ratio of Fine Particulate Matter by Time of the Day in House According to Time-activity Patterns

Daily submicron particle doses received by populations living in different low- and middle-income countries.

In the present study, the daily dose in terms of particle surface area received by citizens living in different low- and middle-income countries, characterized by different lifestyles, habits, and climates, was evaluated. The level of exposure to submicron particles and the dose received by the populations of Accra (Ghana), Cairo (Egypt), Florianopolis (Brazil), and Nur-Sultan (Kazakhstan) were analyzed. A direct exposure assessment approach was adopted to measure the submicron particle concentration levels of volunteers at a personal scale during their daily activities. Non-smoking adult volunteers performing non-industrial jobs were considered. Exposure data were combined with time-activity pattern data (characteristic of each population) and the inhalation rates to estimate the daily dose in terms of particle surface area. The received dose of the populations under investigation varied from 450mm2 (Florianopolis, Brazil) to 1300mm2 (Cairo, Egypt). This work highlights the different contributions of the microenvironments to the daily dose with respect to high-income western populations. It was evident that the contribution of the Cooking & Eating microenvironment to the total exposure (which was previously proven to be one of the main exposure routes for western populations) was only 8%-14% for low- and middle-income populations. In contrast, significant contributions were estimated for Outdoor day and Transport microenvironments (up to 20% for Cairo, Egypt) and the Sleeping & Resting microenvironment (up to 28% for Accra, Ghana), highlighting the effects of different site-specific lifestyles (e.g. time-activity patterns), habits, socioeconomic conditions, climates, and outdoor air quality.

Inferring patterns of sympatry among large carnivores in Manas National Park – a prey‐rich habitat influenced by anthropogenic disturbances

AbstractInferring the mechanisms that facilitate sympatry amongst large mammalian carnivores in anthropogenically altered habitats is critical if conservation initiatives aimed to recover populations are to be effective. In this study, we assessed the utilization of space, time and prey resources by tigers Panthera tigris, leopards P. pardus and dholes Cuon alpinus in Manas National Park (MNP), India – a site where prey densities are not limiting, yet anthropogenic influences alter the spatial and temporal behaviour of prey. We use photographic capture data and predator scats collected over three sampling years (2014–15, 2015–16 and 2016–17) to assess patterns of (a) spatial use using a multispecies species occupancy framework, (b) time–activity patterns and overlap between predators and prey using non‐parametric circular kernel‐density functions, (c) fine‐scale spatio‐temporal behaviour by comparing time‐to‐encounters of subsequent events and (d) predator diets by analysing prey remains in predator scats. Our results highlight that the predators segregate through fine‐scale spatio‐temporal avoidance rather than displaying population‐level changes in space‐use, activity patterns or food habits. Overlap in space‐use between tigers and leopards was high and time–activity patterns of the predators closely matched those of prey, suggesting that predators likely maximize resource acquisition in this prey‐rich environment. Ungulate prey dominated the diet of predators, resulting in the high dietary overlap. From our results, we infer patterns of sympatry among large carnivores in the face of anthropogenic influences and highlight the need to understand interspecific interactions within a community before initiating conservation actions aimed at recovering these endangered species.

Characteristics of Non-Smokers’ Exposure Using Indirect Smoking Indicators and Time Activity Patterns

Since the global enforcement of smoke-free policies, indoor smoking has decreased significantly, and the characteristics of non-smokers’ exposure to secondhand smoke (SHS) has changed. The purpose of this study was to assess the temporal and spatial characteristics of SHS exposure in non-smokers by combining questionnaires and biomarkers with time activity patterns. To assess SHS exposure, biomarkers such as cotinine and 4-(methylnitrosamino)-1-3-(pyridyl)-1-butanol (NNAL) in urine and nicotine in hair were collected from 100 non-smokers in Seoul. Questionnaires about SHS exposure and time activity patterns were also obtained from the participants. The analysis of biomarker samples indicated that about 10% of participants were exposed to SHS when compared with the criteria from previous studies. However, 97% of the participants reported that they were exposed to SHS at least once weekly. The participants were most exposed to SHS in the outdoor microenvironment, where they spent approximately 1.2 h daily. There was a significant correlation between the participants’ time spent outdoors and self-reported SHS exposure time (r2 = 0.935). In this study, a methodology using time activity patterns to assess temporal and spatial characteristics of SHS exposure was suggested. The results of this study may help develop policies for managing SHS exposure, considering the time activity patterns.

Lifestyle associated with physical fitness related to health and cardiometabolic risk factors in Chilean schoolchildren

BackgroundExcessive screen time (ST) and lower physical activity (PA) patterns have been reported to have an impact on cardiometabolic risk (CMR); however, their impact on physical fitness needs in-depth study. ObjectiveTo determine the association between lifestyle (i.e. ST and PA after school) with physical fitness related to health and CMR (i.e. abdominal obesity and hypertension) in Chilean schoolchildren. MethodsThe sample for this cross-sectional study comprised 263 girls (11.87±0.83 years) and 319 boys (12.02±0.88 years). The body mass index (BMI), waist circumference (WC), waist to height ratio (WtHR), CMR (WtHR≥0.5), body fat (BF), systolic (SBP) and diastolic blood pressure (DBP), physical fitness, ST (h/day), and PA after school (h/week) were evaluated. ResultsSchoolchildren with good lifestyle had a lower BMI, WC, and WtHR (P<0.001) as well as a better VO2max (P<0.001) and standing long jump test (SLJ) (P=0.002). The schoolchildren with bad lifestyle had the highest proportion of students with abdominal obesity (WtHR≥0.5) (30.6%, P=0.009) and hypertension. (40.9%, P<0.001). Likewise, PA after school (β; −0.02, P=0.002) and cardiorespiratory fitness (β; −0.02, P=0.002) adjusted by age and sex reported inverse associations with abdominal obesity (WtHR≥0.5). Likewise, ST presented a positive association with SBP (β; 0.14, P=0.030). Moreover, handgrip strength (β; −0.17, P=0.010) and SLJ (β; −0.05, P=0.023) reported inverse associations with SBP. ConclusionIn schoolchildren, a bad lifestyle was associated with low physical fitness related to health and CMR (i.e. abdominal obesity and hypertension).

Application of time-activity estimates in a representative population to a cohort study: the ELSA cohort

Background/AimApplication of modelled air pollution exposure estimates to cohort study respondents most often rely on the assumption that the individual remains outside (at their residential address) and static throughout the exposure period. This method likely leads to overestimation of exposure to outdoor air pollution. A lack of information on time-activity patterns and movement of a population throughout a study area therefore has the potential to limit heterogeneity in exposure estimates applied to cohort respondents in epidemiological study. In the present study, the London Travel Demand Survey (LTDS) and London Hybrid Exposure Model (LHEM) incorporate time-activity information of London residents alongside air pollution model estimates applied to respondents of the English Longitudinal Study of Ageing (ELSA).MethodsAnnual average CMAQ-urban (Community Multiscale Air Quality) dispersion model estimates were applied to the residential address of ELSA respondents. LTDS data for ~75,000 London residents were incorporated into the LHEM in order to calculate average time-activity patterns stratified by age and location. Estimates of exposure to NO2, PM10 and PM2.5 for ELSA respondents were then calculated as a reflection of both CMAQ-urban and LTDS/LHEM adjustments.ResultsTime-activity patterns were shown to be significantly different between age groups, as well as by location across London. At recruitment to the ELSA study, London-based respondents (n = 1,037) showed a 62.9% reduction in modelled NO2 exposure when representative time-activity estimates were incorporated. A reduction of 67.7% and 38.3% were observed for PM10 and PM2.5, respectively.ConclusionsA framework through which estimates of time-activity patterns in representative populations are calculated will likely improve the accuracy of modelled outdoor air pollution estimates when both are applied to respondents of cohorts in epidemiological study. The framework described here will be utilised in a study assessing the true association of air pollution on cognition in the elderly respondents of ELSA.

Indoor &amp; outdoor PM2.5 concentrations in Chennai, India prior to &amp; during the COVID-19 lockdown

Background: The Tamil Nadu Air Pollution and Health Effects follow-up study, known as TAPHE-2, is evaluating the relationship between air pollution and birth outcomes in a rural-urban cohort of 300 pregnant mothers. Due to COVID-19 related lockdowns, TAPHE-2 work has been delayed; however, continuous indoor and outdoor air monitoring data are available prior to and during the COVID-19 lockdown in and around Chennai, India.Methods: Indoor concentrations of PM2.5 are being measured in peri-urban Chennai, India, using Atmos, a relatively low-cost, real-time PM2.5 monitor developed in India. Continuous indoor measurements are validated and calibrated by periodic collocation with gravimetric samplers. Additionally, we looked at public air quality data from Indian authorities. The combined dataset provides semi-continuous indoor and outdoor measurements before and during the lockdown.Results: In six households, data exists on average for 11.6 days (SD 9.4) pre-lockdown, and for 37 days (SD 0) during the lockdown. During these periods, the mean uncorrected real-time PM2.5 concentrations are 36 µg/m3 (SD 40) and 24 µg/m3 (SD 18), respectively. Self-reported time activity patterns - verified by changes in PM concentrations measured by the Atmos - are different, with notable changes in indoor concentrations. Ambient concentrations prior to and during the lockdown, as reported by Indian regulatory monitors in Chennai, are 38 µg/m3 (SD 25) and 20 µg/m3 (SD 27), respectively. There is a reasonable correlation between indoor Atmos measurements and gravimetric measurements (R2 = 0.84).Conclusions: We took advantage of ongoing measurements to evaluate the impact of the COVID19-related lockdown on indoor and outdoor PM2.5 concentrations. We note changes in time-activity patterns and indoor and outdoor concentrations of PM2.5 across Chennai. Raw data from the Atmos monitor has a reasonably good correlation with gravimetric measures, indicating its potential suitability for studies of both indoor and outdoor PM concentrations.

Exposure assessment of PM2.5 for entire population in the region of interest using sensor-based air monitoring system and similar time-activity groups

PM2.5 is an air pollutant that can cause various adverse health effects. Although the fixed ambient air monitoring stations provides ambient PM2.5 concentration within a community, it is still weak to assess actual exposure of population account for time-activity patterns. However, the exposure of the entire population in a region of interest may be estimated by classifying the population according to time-activity pattern and modeling their exposure. In this study, we tried to suggest the methodology to assess exposure to PM2.5 of entire population in a region of interest. The five field technicians representing similar time-activity groups (STG) of preschool children, students, housewives, office workers, and the elderly conducted exposure simulation with PM2.5 personal exposure monitor in Guro-gu, Seoul, Korea. The PM2.5 exposure concentrations (cs) were modeled by interpolation (point in polygon, inverse distance weighted and ordinary kriging) and regression model using GPS data and sensor-based air monitoring instruments network and compared with MicroPEM data (cm). The exposure of the entire population to PM2.5 was estimated by population-weighted average through Monte-Carlo simulation. The elderly had the highest average cm follows by office workers, housewives, preschool children, and students. The correlation between c¬m and cs was good in order of ordinary kriging (R2=0.822), inverse distance weighted (R2=0.747), and point in polygon method (R2=0.721). The 33.8% of the entire population exposed to PM2.5 higher than Atmospheric Environmental Standard of PM2.5 for 24-hour average. In this study, the possibility of assessing the exposure of the entire population for real-time and long-term cumulative exposure was suggested by applying this methodology, and it is expected that the exposure surveillance system can be developed based on these results.

Acute Effects of Individual Exposure to Fine Particulate Matter on Pulmonary Function in Schoolchildren

ObjectiveThis panel study aimed to determine the acute effects of exposure to fine particulate matter (PM2.5) on schoolchildren's pulmonary function. MethodsWe selected 51 schoolchildren aged 9–12 years attending a full-time boarding school in Beijing, China, measured the indoor and outdoor PM2.5 concentrations for five consecutive days, calculated the PM2.5 time-weighted individual exposure levels based on the school micro-environmental concentrations and the time activity pattern recorded by schoolchildren, measured schoolchildren's pulmonary function on the fifth day. The survey was performed three times from December 2018 to April 2019. We used a linear mixed-effects model to evaluate the associations between PM2.5 and pulmonary function. ResultsDuring the three surveys, the median PM2.5 time-weighted individual exposure concentrations were 15.30 µg/m3, 48.92 µg/m3, and 42.89 µg/m3, respectively. There was a significant difference between the three surveys in vital capacity (VC), forced vital capacity (FVC), forced expiratory volume in one second (FEV1) and forced expiratory volume in one second/forced vital capacity (FEV1/FVC) (P < 0.05). The relevance analysis found that PM2.5 had lag effect on schoolchildren's pulmonary function, each 10 µg/m3 increase in PM2.5 could cause largest decreases in FEF25%–75%, FEV1/FVC, FEF75%, and FEV1 on lag 0–1 d (80.44 mL/s, 35.85%, 78.58 mL/s, and 61.34 mL, respectively), and largest decreases in FEF25% on lag 1 d (83.68 mL/s), in VC on lag 4 d (32.34 mL), and in FVC on lag 0–4 d (37.76 mL). Gender subgroup analysis revealed that the increase in PM2.5 caused a decrease in FEV1/FVC and VC on the day of physical examination only in boys, and on lag days it caused changes in different pulmonary function indicators, both for boys and girls, but most of the pulmonary function indicators decreased more in boys than in girls. ConclusionOur findings show that acute PM2.5 exposure has significant effects on pulmonary function within 0–4 d, on both small airway indicators and large airway indicators. Boys’ pulmonary function is more sensitive to PM2.5 than girls.

Indoor and outdoor particulate matter and serum levels of lead and cadmium among Korean housewives: a panel study

Introduction Lead (Pb) and cadmium (Cd) are heavy metals that could cause harmful health effects to humans. It is known that particulate matter ≤μg (PM2.5) contains heavy metals, but whether they are significantly associated with body burden of heavy metals has yet been studied. We aimed to investigate the association between exposure to particulate matter and serum concentration of Pb and Cd. Methods A total of 101 housewives living in 2 Korean urban communities were recruited and were examined repeatedly 2 times during a 1-year period. We obtained lifestyle information including the time-activity pattern and dietary habits. and collected the blood samples of participants at the baseline for measuring serum concentration of Pb and CD. We measured indoor PM2.5 by using Gravimetric methods for a week before each examination, and indoor PM2.5 by using the IoT smart sensor gadget between examinations. Results Exposure to particulate matter was significantly associated with serum Pb and serum Cd of Korean housewives, by using linear mixed model for considering repeated measurements. In crude analysis, 2-fold increase of PM2.5 was associated with 0.089 ug/L increase of serum Pb and 0.097 ug/L increase of serum Cd. Discussion Our study shows significant association between air pollution and serum Cd and Pb, with the precise measurement of particulate matter. This result suggest that additional body burden of heavy metals caused by air pollution. More precautionary policy for potential health hazard of particulate matter on housewives are necessary to protect the health of women.

Effect of housewife's activity pattern on indoor particulate matter concentration: Ko-CHENS Mom study

Background/Aim Most housewives spend a lot of time at home and do housework such as cleaning and cooking. Low-cost sensors have advantage of being able to measure indoor particulate matter concentration in real time. Activities such as cooking, eating and cleaning can affect exposure patterns of indoor particulate matter. The purpose of this study was to identify changes in indoor particulate matter concentration according to the time-activity patterns of housewives. Methods We enrolled 306 participants in the study for the housewives located in Seoul and Ulsan, Korea. Housewives were measured their indoor exposures by low-cost sensor and completed time-activity diaries for a 7-days monitoring period. PM data is obtained every 5 minutes via Wi-Fi and cloud system connection. Participants self-reported their major activities every hour in their time-activity diary. The time activity diary provides hourly information on participants' activities and locations. Indoor PM concentrations over time were compared with participants' behavior patterns. We also performed the stratified analysis based on weekdays/weekends and seasons. The accuracy of the sensor measurment was evaluated by examining the correlation between the indoor PM measured by the sensor and the indoor PM measured by the GRIMM. Results During the study, the indoor occupancy rate of the participants was about 82%. The average age of the participants was 34 years. The time having highest average of indoor PM concentration was 10 am (PM2.5: 21.8 μg/m3, PM10: 26.3 μg/m3). Activity patterns related to cooking/eating, and cleaning influenced changes in indoor particulate matter concentrations. There was no difference in indoor PM concentration during weekdays/weekends. The correlation coefficients between concentrations measured by sensor and GRIMM were 0.9. Conclusion This study provides a comprehensive assessment of the variation in indoor particulate matter concentration associated with housewives’ time-activities. Our results found that indoor PM concentrations increased with indoor cooking /cleaning behavior.

Effects of personal air pollution exposure on inflammatory responses: potential mediation by endogenous melatonin

Background/Aim: Melatonin is a free radical scavenger and an anti-inflammatory molecule. Air pollution exposure has been associated with increased inflammatory responses. We hypothesize that endogenous melatonin plays a role in inflammatory responses to air pollution exposure. Methods: We tested this hypothesis in a cohort of 53 healthy adults (22-52 years old, 16 women), none of whom were on melatonin supplementation. Early morning urine and blood were collected from each participant for up to three times. We analyzed urinary 6-sulfatoxymelatonin (aMT6s), as a surrogate of circulating melatonin, and pro- and anti-inflammatory cytokines in plasma. Indoor and outdoor air pollutants were measured and combined with participants' time-activity pattern to calculate personal exposure to O3, PM2.5, NO2, and SO2 averaged over 12-hour, 24-hour, 1-week, and 2-week prior to biospecimen collection, respectively. Linear mixed effects models were used to examine the relationships of urinary aMT6s with personal pollution exposure and plasma cytokines controlling for covariates including temperature, humidity, sex, age, and respiratory infection &amp; smoking status. Mediation analysis was conducted to test whether aMT6s is a mediator for the relationships between pollution exposure and inflammatory cytokines. Results: A one interquartile range (4.2 ppb) increase in 2-week O3 exposure was associated with a -29.4% (95% CI: -50.0%, -0.50%) decrease in aMT6s, while the relationships of aMT6s with other pollutant exposures were nonsignificant. Within the range of endogenous aMT6s concentration (0.5-53.0 ng/ng creatinine), increasing aMT6s level was associated with decreasing levels of pro-inflammatory cytokines, including IL-1β, IL-6, IL-8, IL-17A, IFN-γ, and TNF-α. The mediation analysis showed that 5.2%, 7.7%, 8.2%, 10.5%, 16.1%, and 8.3% of the total effects of 2-week O3 exposure on IL-1β, IL-6, IL-8, IL-17A, IFN-γ, and TNF-α were mediated by urinary aMT6s, respectively. Conclusions: Our findings suggest that air pollution exposure may decrease endogenous melatonin, which may further contribute to enhanced pro-inflammatory responses.

Associations of ozone exposure with urinary metabolites of arachidonic acid

BackgroundOzone (O3) exposure has been associated with biomarkers of platelet activation and oxidative stress. The metabolism of arachidonic acid (AA) plays an important role in platelet activation and oxidative stress. However, AA metabolic pathways have not been examined in relation to O3 and other air pollutants. MethodsEarly morning urine and fasting blood were longitudinally collected up to four times from 89 healthy adults (22–52 years old, 25 women) in Changsha City, China. We measured three urinary AA metabolites, namely 11-dehydro-Thromboxane B2 (11-dhTXB2) produced from the arachidonic cyclooxygenase pathway, 20-hydroxyeicosatetraenoic acid (20-HETE) from the CYPs pathway, and 8-isoprostane from the non-enzymatic pathway. Urinary malondialdehyde (MDA) and 8-hydroxy-2′-deoxyguanosine (8-OHdG) were measured as indicators of oxidative damage to lipids and DNA, respectively. We measured soluble P-selectin (sCD62p) concentrations in plasma as an indicator of platelet activation. Indoor and outdoor air pollutants were measured and combined with participants’ time-activity pattern to calculate personal exposure to O3, PM2.5, NO2, and SO2 averaged over 12-hour, 24-hour, 1-week, and 2-week periods prior to biospecimen collection, respectively. Linear mixed-effects models were used to examine the relationships of AA metabolites with air pollutant exposures, plasma sCD62p, and urinary MDA & 8-OHdG. ResultsWe found that a 10% increase in 12 h and 24 h O3 exposure were associated with increases in urinary11-dhTXB2 by 1.4% (95%, 0.1% to 2.6%) and 1.3% (0.05% to 2.5%), respectively. These associations remained robust after adjusting for co-pollutant exposures. No significant associations were observed between 11-dhTXB2 and other pollutants or between O3 exposures and other AA metabolites. All the three AA metabolites were significantly and positively associated with urinary MDA and 8-OHdG, whereas only urinary 11-dhTXB2 was significantly and positively associated with plasma sCD62p. ConclusionsA metabolite of AA from the cyclooxygenase pathway was positively associated with short-term O3 exposure, and with a plasma marker of platelet activation and two urinary markers of oxidative stress. The results suggest that O3 exposure may contribute to increased platelet activation and oxidative damages via altering the metabolism of AA.

Environmental Health Surveillance System for a Population Using Advanced Exposure Assessment.

Human exposure to air pollution is a major public health concern. Environmental policymakers have been implementing various strategies to reduce exposure, including the 10th-day-no-driving system. To assess exposure of an entire population of a community in a highly polluted area, pollutant concentrations in microenvironments and population time–activity patterns are required. To date, population exposure to air pollutants has been assessed using air monitoring data from fixed atmospheric monitoring stations, atmospheric dispersion modeling, or spatial interpolation techniques for pollutant concentrations. This is coupled with census data, administrative registers, and data on the patterns of the time-based activities at the individual scale. Recent technologies such as sensors, the Internet of Things (IoT), communications technology, and artificial intelligence enable the accurate evaluation of air pollution exposure for a population in an environmental health context. In this study, the latest trends in published papers on the assessment of population exposure to air pollution were reviewed. Subsequently, this study proposes a methodology that will enable policymakers to develop an environmental health surveillance system that evaluates the distribution of air pollution exposure for a population within a target area and establish countermeasures based on advanced exposure assessment.

Assessment of PM2.5 population exposure of a community using sensor-based air monitoring instruments and similar time-activity groups

Although fixed ambient air monitoring stations provide data regarding ambient PM2.5 concentrations within a given community, they present limitations in terms of assessing the actual exposure to individuals and populations using time-activity patterns. The population exposure of a community may be estimated by classifying the population according to the time-activity pattern and modeling their exposure. In this study, we provide a possible methodology to assess the population exposure to PM2.5 in a given community. Five field technicians conducted exposure simulations for similar time-activity groups of preschool children, school students, homemakers, office workers, and elderly, with PM2.5 personal exposure monitoring (PEM) equipment, in Guro-gu, Seoul, Korea. The PM2.5 exposure concentrations were modeled by interpolation (point in polygon, inverse distance weighted, and ordinary kriging methods) and regression models using GPS data and a sensor-based air monitoring instrument network, and were compared with the PEM data. The population exposure to PM2.5 was estimated using the population-weighted average through Monte–Carlo simulation. Elderly presented the highest average PM2.5 exposure concentration followed by office workers, homemakers, preschool children, and school students. The correlation between the measured and modeled exposure was good, in the order of ordinary kriging (R2 = 0.822), inverse distance weighted (R2 = 0.747), and point in polygon methods (R2 = 0.721). Thirty-seven percent of the population in a community was exposed to PM2.5 concentrations higher than 35 μg/m3, which is the Korean Atmospheric Environmental Standard for PM2.5 (24-h average). It is suggested that this methodology could be applied to assess the real-time and long-term cumulative exposures of a given community. It is expected that an exposure surveillance system can be developed based on these results.

Endogenous melatonin mediation of systemic inflammatory responses to ozone exposure in healthy adults

Background/aimMelatonin is a free radical scavenger and an anti-inflammatory biomolecule. Air pollution exposure has been associated with increased inflammatory responses. We hypothesize that endogenous melatonin plays a role in inflammatory responses to air pollution exposure. MethodsWe tested this hypothesis in a cohort of 53 healthy adults (22–52 years old, 16 women), none of whom were on melatonin supplementation. Early morning urine and fasting blood were collected from each participant longitudinally up to three times. We analyzed urinary 6-sulfatoxymelatonin (aMT6s), as a surrogate of circulating melatonin, and pro- and anti-inflammatory cytokines in the plasma samples. Indoor and outdoor air pollutants were measured and combined with participants' time-activity patterns to calculate personal exposure to O3, PM2.5, NO2, and SO2 averaged over 12-hour, 24-hour, 1-week, and 2-week periods prior to biospecimen collection, respectively. Linear mixed-effects models were used to examine the relationships among urinary aMT6s, personal pollutant exposure, and plasma cytokines. A mediation analysis was conducted to examine the role of aMT6s in the relationships between pollutant exposures and inflammatory cytokines. ResultsOne interquartile range (4.2 ppb) increase in 2-week O3 exposure was associated with a ‐26.2% (95% CI: −43.9% to −2.8%) decrease in aMT6s. Within the range of endogenous aMT6s concentrations (0.5–53.0 ng/ng creatinine) across the participants, increased aMT6s was associated with decreased pro-inflammatory cytokines including IL-1β, IL-8, IL-17A, IFN-γ, and TNF-α. These cytokines were significantly and positively associated with 2-week average O3 exposure. Furthermore, 7.4% to 17.4% of the O3-cytokine associations were mediated by aMT6s. We did not find similar effects for the other pollutants. ConclusionsPro-inflammatory responses to O3 exposure in the preceding 2 weeks partly resulted from the depletion of endogenous melatonin by O3.

Influence of methodology on the estimation of the particle surface area dose received by a population in all-day activities

In everyday life, people are exposed to different concentrations of airborne particles depending on the microenvironment where they perform their different activities. Such exposure can lead to high sub-micron particle doses. The received dose depends on particle concentration to which people are exposed (typically expressed in terms of number or surface area), time spent in each activity or microenvironment (time activity pattern) and amount of air inhaled (inhalation rate). To estimate an actual value of the received dose, all these parameters should be measured under real-life conditions; in fact, the concentrations should be measured on a personal scale (i.e. through a direct exposure assessment), whereas time activity patterns and inhalation rates specific to the activity performed should be considered. The difficulties in obtaining direct measurements of these parameters usually lead to adopt time activity patterns and inhalation rates already available in scientific literature for typical populations, and local outdoor particle concentrations measured with fixed monitoring stations and extrapolated for all the other microenvironments.To overcome these limitations, we propose a full-field method for estimating the received dose of a population sample, in which all the parameters (concentration levels, time activity patterns and inhalation rates) are measured under real-life conditions (also including the inhalation rates, that were evaluated on the basis of the measured heart rates). Specifically, 34 volunteers were continuously monitored for seven days and the data of sub-micron particle concentrations, activities performed, and inhalation rates were recorded. The received dose was calculated with the proposed method and compared with those obtained from different simplified methodologies that consider typical data of particle concentrations, time activity patterns and inhalation rates obtained from literature. The results show that, depending on the methodology used, the differences in the received daily dose can be significant, with a general underestimation of the most simplified method.