Microenvironmental Concentrations Research Articles

Personal exposure to PM2.5 in different microenvironments and activities for retired adults in two megacities, China

Microenvironmental concentrations and time-activity patterns influence personal exposure to fine particulate matter (PM2.5). However, the variations and contributions of PM2.5 exposures from various microenvironments (MEs) and activities remain unclear. In this study, gravimetrically corrected real-time personal PM2.5 measurements were collected during routine activities in different MEs from 66 non-smoking retired adults. Exposure data were collected for five consecutive days over two seasons in Nanjing (NJ) and Beijing (BJ), China. Measured PM2.5 concentrations varied substantially both between and within different MEs and activities. The highest average concentrations were observed in restaurants (NJ: mean 192 μg/m3, SD 242 μg/m3; BJ: mean 91 μg/m3, SD 79 μg/m3) and were associated with sources such as passive smoking and cooking emissions. Overall, PM2.5 concentrations in different MEs and activities were moderately to highly correlated with outdoor PM2.5 concentrations (Spearman's r = 0.51–0.97) except in restaurants and during passive smoking. The at-home ME contributed approximately 85 % of the total PM2.5 exposure, corresponding to the participants spending about 87 % of their time there. The majority of household exposures occurred during sleeping, cooking, and other home-based activities. Transportation accounted for <5 % of total exposure. Our results indicate that improving indoor air quality, especially residential indoors, is important to reduce personal exposure to PM2.5.

Inter- and Intra-Individual Variability of Personal Health Risk of Combined Particle and Gaseous Pollutants across Selected Urban Microenvironments

Exposure surrogates, such as air quality measured at a fixed-site monitor (FSM) or residence, are typically used for health estimates. However, people spend various amounts of time in different microenvironments, including the home, office, outdoors and in transit, where they are exposed to different magnitudes of particle and gaseous air pollutants. Health risks caused by air pollution exposure differ among individuals due to differences in activity, microenvironmental concentration, as well as the toxicity of pollutants. We evaluated individual and combined added health risks (AR) of exposure to PM2.5, NO2, and O3 for 21 participants in their daily life based on real-world personal exposure measurements. Exposure errors from using surrogates were quantified. Inter- and intra-individual variability in health risks and key contributors in variations were investigated using linear mixed-effects models and correlation analysis, respectively. Substantial errors were found between personal exposure concentrations and ambient concentrations when using air quality measurements at either FSM or the residence location. The mean exposure errors based on the measurements taken at either the FSM or residence as exposure surrogates was higher for NO2 than PM2.5, because of the larger spatial variability in NO2 concentrations in urban areas. The daily time-integrated AR for the combined PM2.5, NO2, and O3 (TIARcombine) ranged by a factor of 2.5 among participants and by a factor up to 2.5 for a given person across measured days. Inter- and intra-individual variability in TIARcombine is almost equally important. Several factors were identified to be significantly correlated with daily TIARcombine, with the top five factors, including PM2.5, NO2 and O3 concentrations at ‘home indoor’, O3 concentrations at ‘office indoor’ and ambient PM2.5 concentrations. The results on the contributors of variability in the daily TIARcombine could help in targeting interventions to reduce daily health damage related to air pollutants.

Ultrafine particles in key microenvironments in rural and urban areas of Ghana

Urban air pollution presents significant health risks to urban dwellers around the world. Knowledge of the levels of air pollution at various spatial locations in a city, offers insight into the personal exposure of residents and facilitates the control of air pollution. This study investigated ultrafine particles (UFP) in key microenvironments in which people spend a significant amount of their time in three suburbs of Accra (the capital city of Ghana) and in a nearby rural community (Berekuso). The ambient concentrations of UFP across the study area were also mapped. The median daily ambient UFP concentration at a reference site at Kwabenya, a suburb of Accra, was 5.8(IQR:1.6−17.1)×104cm−3. The UFP on the reference site were mainly influenced by vehicular traffic, and open-air burning in communities near the site, and by extention, wind direction. The mean (±SEM) UFP concentrations reported in five school and household microenvironments in two suburbs in Accra (Madina and Agbogbloshie) and in Berekuso ranged between 9.1×103(±7.3×102) and 1.5×105(±1.9×104)cm−3. The microenvironmental concentrations were mainly influenced by lifestyle and sociocultural factors. The results highlight the high levels of UFP in many of the microenvironments investigated, the potential health risks that UFP pose to sensitive groups, and the overall urgency for the control of air pollution in Accra.

Shedding Light on the Role of Neurotransmitters in the Microenvironment of Pancreatic Cancer.

Pancreatic cancer (PC) is a highly lethal malignancy with a 5-year survival rate of less than 8%. The fate of PC is determined not only by the malignant behavior of the cancer cells, but also by the surrounding tumor microenvironment (TME), consisting of various cellular (cancer cells, immune cells, stromal cells, endothelial cells, and neurons) and non-cellular (cytokines, neurotransmitters, and extracellular matrix) components. The pancreatic TME has the unique characteristic of exhibiting increased neural density and altered microenvironmental concentration of neurotransmitters. The neurotransmitters, produced by both neuron and non-neuronal cells, can directly regulate the biological behavior of PC cells via binding to their corresponding receptors on tumor cells and activating the intracellular downstream signals. On the other hand, the neurotransmitters can also communicate with other cellular components such as the immune cells in the TME to promote cancer growth. In this review, we will summarize the pleiotropic effects of neurotransmitters on the initiation and progression of PC, and particularly discuss the emerging mechanisms of how neurotransmitters influence the innate and adaptive immune responses in the TME in an autocrine or paracrine manner. A better understanding of the interplay between neurotransmitters and the immune cells in the TME might facilitate the development of new effective therapies for PC.

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.

Factors affecting variability in gaseous and particle microenvironmental air pollutant concentrations in Hong Kong primary and secondary schools.

School-age children are particularly susceptible to exposure to air pollutants. To quantify factors affecting children's exposure at school, indoor and outdoor microenvironmental air pollutant concentrations were measured at 32 selected primary and secondary schools in Hong Kong. Real-time PM10 , PM2.5 , NO2, and O3 concentrations were measured in 76 classrooms and 23 non-classrooms. Potential explanatory factors related to building characteristics, ventilation practice, and occupant activities were measured or recorded. Their relationship with indoor measured concentrations was examined using mixed linear regression models. Ten factors were significantly associated with indoor microenvironmental concentrations, together accounting for 74%, 61%, 46%, and 38% of variations observed for PM2.5 , PM10 , O3, and NO2 microenvironmental concentrations, respectively. Outdoor concentration is the single largest predictor for indoor concentrations. Infiltrated outdoor air pollution contributes to 90%, 70%, 75%, and 50% of PM2.5 , PM10 , O3, and NO2 microenvironmental concentrations, respectively, in classrooms during school hours. Interventions to reduce indoor microenvironmental concentrations can be prioritized in reducing ambient air pollution and infiltration of outdoor pollution. Infiltration factors derived from linear regression models provide useful information on outdoor infiltration and help address the gap in generalizable parameter values that can be used to predict school microenvironmental concentrations.

Modeling Exposure Reduction for Personal Level Interventions

Through the APIC-ESTEE (Air Pollution Impacts on Cardiopulmonary Disease in Beijing: An integrated study of Exposure Science, Toxicogenomics and Environmental Epidemiology) project, we have developed a model for the reduction of personal exposures to air pollution to assess the health impacts of interventions such as face mask wearing and use of indoor air purifiers. The model accounts for population level time activity patterns and micro-environmental concentrations. A preliminary analysis for Beijing used data on time activity patterns based on Chinese exposure factors; indoor and outdoor fine particulate (PM2.5) concentrations came from residential home studies, a study of public indoor environments, and a feasibility personal monitoring study. In-transit concentrations were estimated as 110% of ambient concentrations. Three intervention scenarios were modelled &amp;#8211; wearing a highly effective or a poorly effective facemask whenever a person is outdoors or in transit and use of an air purifier in the home environment. The effects of these interventions were modelled assuming &amp;#8216;average&amp;#8217; (84 µg/m3) and high (396 µg/m3) outdoor PM2.5 concentrations. Data for potential exposure reduction for the face mask scenario came from a study of total inward leakage in a volunteer trial with diesel exhaust exposure. Data for the air purifier scenario came from a literature review. Use of a highly effective mask reduced 24-hr average personal exposure by 27% over the baseline scenario of no intervention, while the air purifier reduced exposure by 29% for the average ambient condition. For the high ambient concentration scenario, the highly effective mask reduced exposure by 26% compared to 25% for the air purifier. With a poorly effective mask, the personal exposure reduction under average and high ambient concentrations was 11%. The model will be further developed in a probabilistic form for modelling population level exposure interventions and health impacts.

Wearable Sensors for Geolocation, Physical Activity and Air Pollution: Challenges and Opportunities

Introduction: Procedures for measuring continuous data on geolocation, physical activity (PA), and air pollution (AP) have improved greatly in recent years but storing, cleaning and analyzing these can be challenging. Data collected from mobile phones is useful to estimate for example geolocation, transport mode, and PA levels, but more data does not always lead to better outcomes.Method: We use the results from three different studies (AirMAP, CAVA and PASTA) to illustrate the challenges in managing datasets for AP exposure estimates, and comment on their strengths and weaknesses. The datasets vary greatly: AirMAP was part of the Telecom Italia Big Data challenge 2015 which combined aggregated data from cellular towers (~8 million users) in grid cells of varying sizes (10 &amp;#8211; 300m) in seven Italian cities; in CAVA, GPS and accelerometer readings derived from a smartphone app were collected from 180 participants in Barcelona; PASTA collected detailed geolocation, PA, and AP exposure data from 120 free-living individuals in three European cities using separate monitors for each in a relatively burdensome and resource intensive approach. For each study, daily exposures estimated as a function of daily activity patterns were compared to estimates based on home location.Results: Processing large and complex datasets to identify people&amp;#8217;s daily activities and account for microenvironmental concentrations in estimating personal exposures is still challenging. Mode for example is key in daily pollutant intake (modal choice may result in differences of up to 20%) but identifying it is a difficult task. AirMAP data suggests that home-based exposures overestimate daily activity-based exposures (by 6%), contrary to the other two studies (~18%).Conclusion: The comparison gives insights into difficulties of collecting, processing and interpreting data from current state of the art wearable devices, and into opportunities for large scale ubiquitous sensing.

Integrating travel behavior with land use regression to estimate dynamic air pollution exposure in Hong Kong

BackgroundEpidemiological studies typically use subjects' residential address to estimate individuals' air pollution exposure. However, in reality this exposure is rarely static as people move from home to work/study locations and commute during the day. Integrating mobility and time-activity data may reduce errors and biases, thereby improving estimates of health risks. ObjectivesTo incorporate land use regression with movement and building infiltration data to estimate time-weighted air pollution exposures stratified by age, sex, and employment status for population subgroups in Hong Kong. MethodsA large population-representative survey (N = 89,385) was used to characterize travel behavior, and derive time-activity pattern for each subject. Infiltration factors calculated from indoor/outdoor monitoring campaigns were used to estimate micro-environmental concentrations. We evaluated dynamic and static (residential location-only) exposures in a staged modeling approach to quantify effects of each component. ResultsHigher levels of exposures were found for working adults and students due to increased mobility. Compared to subjects aged 65 or older, exposures to PM2.5, BC, and NO2 were 13%, 39% and 14% higher, respectively for subjects aged below 18, and 3%, 18% and 11% higher, respectively for working adults. Exposures of females were approximately 4% lower than those of males. Dynamic exposures were around 20% lower than ambient exposures at residential addresses. ConclusionsThe incorporation of infiltration and mobility increased heterogeneity in population exposure and allowed identification of highly exposed groups. The use of ambient concentrations may lead to exposure misclassification which introduces bias, resulting in lower effect estimates than ‘true’ exposures.

A multipollutant evaluation of APEX using microenvironmental ozone, carbon monoxide, and particulate matter (PM2.5) concentrations measured in Los Angeles by the exposure classification project.

This paper describes an operational evaluation of the US Environmental Protection Agency's (EPA) Air Pollution Exposure Model (APEX). APEX simulations for a multipollutant ambient air mixture, i.e. ozone (O3), carbon monoxide (CO), and particulate matter 2.5 microns in diameter or less (PM2.5), were performed for two seasons in three study areas in central Los Angeles. APEX predicted microenvironmental concentrations were compared with concentrations of these three pollutants monitored in the Exposure Classification Project (ECP) study during the same periods. The ECP was designed expressly for evaluating exposure models and measured concentrations inside and outside 40 microenvironments. This evaluation study identifies important uncertainties in APEX inputs and model predictions useful for guiding further exposure model input data and algorithm development efforts. This paper also presents summaries of the concentrations in the different microenvironments.

Contribution of microenvironments to personal exposures to PM10 and PM2.5 in summer and winter

Personal exposure to particulate matter (PM) can be affected by time–activity patterns and microenvironmental concentrations. Particle size is closely associated with potential health problems, where smaller particles have greater effects on health. We investigated the effects of time–activity patterns on personal exposure and the contribution of the microenvironment to personal exposure to PM with maximal diameters of 10 μm and 2.5 μm (PM10 and PM2.5, respectively) in summer and winter. Technicians carried a nephelometer to detect various sizes of PM while engaging in one of nine scripted time–location–activity patterns. The scripted activities were based on the time–activity patterns of nine groups of inhabitants of Seoul, Korea. The monitoring was repeated in summer and winter to assess seasonal variation. The differences of personal exposures to PM10 and PM2.5 in summer and winter were not significant. The greatest PM concentrations occurred in restaurants. The PM2.5/PM10 ratios were varied from 0.35 at schools to 0.92 at stores. In both seasons, the residential indoor microenvironment was the largest contributor to personal PM exposure. The other major contributors were restaurants, offices, schools, buses, and walking, although their contributions differed by season and particle size. The different microenvironmental contributions among the activity pattern groups suggest that personal exposure significantly differs according to activity pattern.

Polyanhydride Nanoparticle Delivery Platform Dramatically Enhances Killing of Filarial Worms.

Filarial diseases represent a significant social and economic burden to over 120 million people worldwide and are caused by endoparasites that require the presence of symbiotic bacteria of the genus Wolbachia for fertility and viability of the host parasite. Targeting Wolbachia for elimination is a therapeutic approach that shows promise in the treatment of onchocerciasis and lymphatic filariasis. Here we demonstrate the use of a biodegradable polyanhydride nanoparticle-based platform for the co-delivery of the antibiotic doxycycline with the antiparasitic drug, ivermectin, to reduce microfilarial burden and rapidly kill adult worms. When doxycycline and ivermectin were co-delivered within polyanhydride nanoparticles, effective killing of adult female Brugia malayi filarial worms was achieved with approximately 4,000-fold reduction in the amount of drug used. Additionally the time to death of the macrofilaria was also significantly reduced (five-fold) when the anti-filarial drug cocktail was delivered within polyanhydride nanoparticles. We hypothesize that the mechanism behind this dramatically enhanced killing of the macrofilaria is the ability of the polyanhydride nanoparticles to behave as a Trojan horse and penetrate the cuticle, bypassing excretory pumps of B. malayi, and effectively deliver drug directly to both the worm and Wolbachia at high enough microenvironmental concentrations to cause death. These provocative findings may have significant consequences for the reduction in the amount of drug and the length of treatment required for filarial infections in terms of patient compliance and reduced cost of treatment.

Illumination, lighting technologies, and indoor environmental quality

Illumination, lighting technologies, and indoor environmental quality

Seasonal and geographic effects on predicting personal exposure to nitrogen dioxide by time-weighted microenvironmental model

The purposes of this study were to investigate the impact of microenvironment concentrations on personal exposure by season and city, and to develop statistical models to predict personal exposure to nitrogen dioxide (NO2). Personal exposures, residential indoor, residential outdoor and workplace indoor levels of NO2 were measured in four cities in Korea (Seoul, Daegu, Asan and Suncheon) using a passive sampler for five weekdays. The measurements were conducted in summer and winter during 2008–2009. Average personal NO2 exposures were 20.5 ppb in summer and 18.6 ppb in winter. The average personal exposures of NO2 and residential indoor levels were the highest in Seoul and the lowest in Suncheon both summer and winter. Personal exposure was significantly different by season. Personal exposure was significantly correlated with residential indoor concentration in all cities. The personal exposure estimated by residential indoor, workplace indoor and outdoor levels explained 38% and 41% of the measured personal exposure variance in summer and winter, respectively. The low correlation may be due to the longer time spent in other microenvironments in the Korean population. Personal exposure was significantly correlated with working day and city. Correlation between the estimated personal exposure and measured personal exposure was significantly associated with the season and city. The model can provide reasonable estimation of population exposure with appropriate microenvironmental concentrations and time activity data. However, season- and city-specific models should be considered.

New approach for particulate exposure monitoring: determination of inhaled particulate mass by 24 h real-time personal exposure monitoring

The objectives of this study were to measure particulate pollution (PM(10), PM(2.5), and PM(1.0)) continuously (24 h/day for 7 day) using real-time exposure monitoring and to estimate total inhalation mass using breathing rate and time-activity. Breathing rates were calculated from measured heart rates. Participants were asked to record a time-activity diary every 15 min. Five microenvironments were defined based on the time-activity diary: home, workplace/school, other indoor, outdoor, and transportation. The average masses of inhaled PM(10) were 530, 316, and 280 μg/day for two office workers, a housewife, and three students, respectively; those of PM(2.5) were 316, 279, and 210 μg/day; and those of PM(1.0) were 251, 264, and 187 μg/day, respectively. We found that home and office/school microenvironments were the main contributors of PM(10), PM(2.5), and PM(1.0) inhaled mass during weekdays and weekends because dwelling time was a determinant factor for inhaled mass. Considering microenvironmental concentration, breathing rate, and dwelling time in each microenvironment, indoor home microenvironments were the largest source of particulate inhalation, followed in order by workplace, transportation, other indoor, and outdoor microenvironments. 34.6% and 69.6% of PM(10) inhalation mass were accumulated in home microenvironments during weekdays and weekends, respectively. The inhaled mass of particulate <1.0 μm (PM(1.0)) in size occupied largest, followed in order by particulate 10-2.5 μm (coarse particle) and 2.5-1.0 μm in size for all occupations.

Formaldehyde personal exposure measurements and time weighted exposure estimates in children

Residential concentrations of formaldehyde have been associated with poor respiratory health in children, where formaldehyde has been measured using stationary monitors inside homes. Although children spend most of their time indoors at home, there are few studies of children’s personal exposure to formaldehyde. The aim of this study was to investigate the relationship between personal exposure formaldehyde concentrations, microenvironmental concentrations and time weighted exposure estimates in children.Forty-one primary school children (aged between 9 and 12years) wore a personal passive sampler over two 24h periods in two seasons and completed 24h daily activity diaries and a questionnaire about lifestyle and behaviour. Samplers were co located indoors at home, outdoors at centralised locations and indoors at school for the corresponding period.Personal exposure formaldehyde concentrations in this group of children were generally low with a geometric mean concentration of 9.1ppb (range <detection limit to 27.3ppb). There were strong correlations between personal exposure concentrations and both domestic indoor (rs=.779, p<0.001) and time weighted estimated (rs=.802, p<0.001) concentrations. The time weighted model did not improve the estimate of personal exposure compared with stationary indoor concentrations. Indoor air concentration measured with a single stationary monitor was a suitable surrogate for personal exposure.

Personal exposures to PM2.5 and their relationships with microenvironmental concentrations

Abstract Personal exposure to particulate matter of aerodynamic diameters less than 2.5 μm (PM2.5) can be affected by various factors. The purpose of this study was to determine the impact of activity pattern and the contribution of each microenvironment to personal PM2.5 exposure. Technicians carried a nephelometer for PM2.5 while engaging in scripted time location activities. The scripted activities of 10 different population groups were based on time activity patterns of the Seoul population in Korea. A total of 58 daily PM2.5 personal exposures were available for analysis. The average PM2.5 personal exposure was 19.8 ± 15.3 μg m−3. The average personal exposure of each population group ranged from 9.8 to 43.1 μg m−3. High peak and average concentrations were observed in restaurants and bars; such high concentrations were due to secondhand smoke and cooking with charcoal on tables. The residential indoor level of the nine microenvironments was the largest contributor to personal exposure. The contributions from residential indoor, non-residential indoor, transportation, and outdoor levels were 36.2%, 53.4%, 6.7%, and 3.7%, respectively. The contributions of microenvironments varied among population groups; these variations suggest that the impact of activity pattern on personal exposure is significant.

Exposure to VOCs and NO2 According to Similar Time-activity Group

O-31A6-4 Background/Aims: The information about time spent in microenvironments plays a critical role for personal exposure to environmental pollutants. Human activity patterns of timing and location play a key role in explaining exposure variation along with the level of pollutant in microenvironments. The purpose of this paper was to present time activity patterns of Korean and to characterize the exposure according to similar time-activity group. Methods: Time-activity pattern was analyzed with 31,634 subjects from 12,651 households, provided by the Korea National Statistical Office (KNSA) survey. The activity pattern survey was initially collected for social and economical purposes in 2004. Detailed study population method was presented in KNSA web site (kostat.go.kr). We classified participants into similar time-activity groups using cluster analysis, and measured time activity pattern and personal volatile organic compounds (VOCs) and nitrogen dioxide (NO2) exposures of about 400 subjects with 3 similar time-activity groups (workers, housewives, university students), along with microenvironmental concentrations such as residential indoors, residential outdoors, and workplace indoors. Results: Korea population spent the majority of their time indoors (87%), outdoors (5%) and in transportation (7%). Specially, residential indoor time (59%) in Korea was different from those of western countries (about 65%–75%). By cluster analysis of time-activity pattern, about 10 similar time-activity groups were classified. Among 10 similar time-activity groups, 3 similar time-activity groups were worker, housewife, and university student. Exposures to VOCs and NO2 for 3 similar time-activity groups were different. Conclusion: Similar time-activity group may cause different exposure and risk to air pollutants such as VOCs and NO2. This exposure study can provide valuable information to understand population exposure and impact from exposure related behaviors.

Non-invasive measurement of carbon monoxide burden in Guatemalan children and adults following wood-fired temazcal (sauna-bath) use.

The use of wood-fired steam baths, or temazcales, is a potentially dangerous source of CO exposure in Guatemalan Highland communities where adults and children use them regularly for bathing, relaxation, and healing purposes. Physical characteristics of children predispose them to absorb CO faster than adults, placing them at greater exposure and health risks. Efforts to quantify temazcal exposures across all age groups, however, have been hampered by the limitations in exposure measurement methods. In this pilot study we measured COHb levels in children and adults following use of the temazcal using three field-based, non-invasive CO measurement methods: CO-oximetry, exhaled breath, and by estimation of COHb using micro-environmental concentrations and time diaries. We then performed a brief comparison of methods. Average CO concentrations measured during temazcal use were 661 ± 503 ppm, approximately 10 times the 15 min WHO guideline. Average COHb levels for all participants ranged from 12-14% (max of 30%, min 2%), depending on the method. COHb levels measured in children were not significantly different from adults despite the fact that they spent 66% less time exposed. COHb measured by CO-oximetry and exhaled breath had good agreement, but precision of the former was affected substantially by random instrument error. The version of the field CO-oximeter device used in this pilot could be useful in screening for acute CO exposure events in children but may lack the precision for monitoring the burden from less extreme, but more day-to-day CO exposures (e.g. indoor solid fuel use). In urban settings, health effects in children and adults have been associated with chronic exposure to ambient CO concentrations much lower than measured in this study. Future research should focus on reducing exposure from temazcales through culturally appropriate modifications to their design and practices, and targeted efforts to educate communities on the health risks they pose and actions they can take to reduce this risk.

Relationship Between Personal Exposures and Microenvironmental Concentrations of NO2 in Korea

Relationship Between Personal Exposures and Microenvironmental Concentrations of NO2 in Korea