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

A review of relevant parameters for assessing indoor air quality in educational facilities

Indoor air quality (IAQ) in educational facilities is crucial due to the extended time students spend in those environments, affecting their health, academic performance, and attendance. This paper aimed to review relevant parameters (building characteristics and factors related with occupancy and activities) for assessing IAQ in educational facilities, and to identify the parameters to consider when performing an IAQ monitoring campaign in schools. It also intended to identify literature gaps and suggest future research directions. A narrative literature review was conducted, focusing on seven key parameters: building location, layout and construction materials, ventilation and air cleaning systems, finishing materials, occupant demographics, occupancy, and activities. The findings revealed that carbon dioxide (CO2) levels were predominantly influenced by classroom occupancy and ventilation rates, while particulate matter (PM) concentrations were significantly influenced by the building's location, design, and occupant activities. Furthermore, this review highlighted the presence of other pollutants, such as trace metals, polycyclic aromatic hydrocarbons (PAHs), carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), and radon, linking them to specific factors within the school environment. Different IAQ patterns, and consequently different parameters, were observed in various school areas, including classrooms, canteens, gymnasiums, computer rooms, and laboratories. While substantial literature exists on IAQ in schools, significant gaps still remain. This study highlighted the need for more studies in middle and high schools, as well as in other indoor microenvironments within educational settings beyond classrooms. Additionally, it underscored the need for comprehensive exposure assessments, long-term studies, and the impacts of new materials on IAQ including the effects of secondary reactions on surfaces. Seasonal variations and the implications of emerging technologies were also identified as requiring further investigation. Addressing those gaps through targeted research and considering the most updated standards and guidelines for IAQ, could lead to define more effective strategies for improving IAQ and safeguarding the students' health and performance.

Elemental composition and health risk assessment of PM10, PM2.5, at different microenvironments: Addis Ababa, Ethiopia

This study was designed to evaluate the health risks faced by inhabitants living in the slum areas of Addis Ababa, Ethiopia. The levels of PM2.5 and PM10 and elemental composition of the PM10 were measured in indoors (in the kitchen and living room) and outdoors (at the roadside). A total of 75 sampling locations (45 indoor and 30 outdoor) were selected for the study. The levels of PM2.5 and PM10 were determined using an AROCET531S instrument, while an universal air pump was used for the sampling of PM10 for the determination of trace elements by inductively coupled plasma-optical emission spectroscopy (ICP‒OES). The health impacts of PMs on the inhabitants of twelve microenvironments (MEs), where they spend much of their daily time, were estimated. The total amounts of PM2.5 and PM10, and trace metals in PM10 found in the nine or twelve MEs ranged from 10.6-119, 128-185, and 0.007-0.197 μg m-3, respectively. According to the United States Environment Protection Agency (USEPA) guidelines, ten of the twelve MEs can cause significant health problems for inhabitants (HI > 1) due to PM2.5 and PM10. Thus, special attention should be given by stakeholders/inhabitants to minimize the health impacts on long-term exposure. This study assessed the risk of levels of trace elements on the inhabitants who spend most of their daily lives. The study revealed that the lifetime cancer risk values for the individual and cumulative trace elements were within the tolerable range set by the USEPA guidelines.

Refining Children's exposure assessment to NO2, SO2, and O3: Incorporating indoor-to-outdoor concentration ratios and individual daily routine

Exposure to air pollutants like sulfur dioxide (SO2), nitrogen oxides (NOx), and ozone (O3) is associated with adverse health effects, particularly with exacerbations of asthma symptoms and new asthma cases in both children and adults. While fixed-site monitoring (FSM) stations are commonly used in air pollutant exposure studies, they may not fully capture personal exposures due to limitations such as inadequate consideration of daily routines and indoor/outdoor concentration variations. In this study, to enhance the accuracy of personal exposure calculated by using FSM data, individual's daily activity routine, encompassing both indoor and outdoor environments, were incorporated by using indoor-to-outdoor concentration ratios. Three methodologies were compared to assess the accuracy of exposure calculations: (i) direct exposure determination employing passive samplers (PS), (ii) personal exposure calculated using FSM data alone, and (iii) personal exposure calculated using FSM data refined by integrating local average individual daily activity routines and indoor-to-outdoor ratios. The results demonstrate that the refined method (iii) yields substantial improvements in estimated exposure levels, reducing the average error from 1.4% to 0.4% for NO2, from 72.1% to 12.7% for SO2, and from 323.4% to 24.9% for O3.

Associations of long-term exposure to air pollution and noise with body composition in children and adults: Results from the LEAD general population study

BACKGROUND

While long-term air pollution and noise exposure has been linked to increasing cardiometabolic disease risk, potential effects on body composition remains unclear. This study aimed to investigate the associations of long-term air pollution, noise and body composition.

METHODS

We used repeated data from the LEAD (Lung, hEart, sociAl, boDy) study conducted in Vienna, Austria. Body mass index (BMI; kg/m2), fat mass index (FMI; z-score), and lean mass index (LMI; z-score) were measured using dual-energy x-ray absorptiometry at the first (t0; 2011-ongoing) and second (t1; 2017-ongoing) examinations. Annual particulate matter (PM10) and nitrogen dioxide (NO2) concentrations were estimated with the GRAMM/GRAL model (2015-2021). Day-evening-night (Lden) and night-time (Lnight) noise levels from transportation were modeled for 2017 following the European Union Directive 2002/49/EC. Exposures were assigned to residential addresses. We performed analyses separately in children/adolescents and adults, using linear mixed-effects models with random participant intercepts and linear regression models for cross-sectional and longitudinal associations, respectively. Models were adjusted for co-exposure, lifestyle and sociodemographics.

RESULTS

A total of 19,202 observations (nt0 = 12,717, nt1 = 6,485) from participants aged 6-86 years (mean age at t0 = 41.0 years; 52.9 % female; mean PM10 = 21 µg/m3; mean follow-up time = 4.1 years) were analyzed. Among children and adolescents (age ≤ 18 years at first visit), higher PM10exposure was cross-sectionally associated with higher FMI z-scores (0.09 [95 % Confidence Interval (CI): 0.03, 0.16]) and lower LMI z-scores (-0.05 [95 % CI: -0.10, -0.002]) per 1.8 µg/m3. Adults showed similar trends in cross-sectional associations as children, though not reaching statistical significance. We observed no associations for noise exposures. Longitudinal analyses on body composition changes over time yielded positive associations for PM10, but not for other exposures.

CONCLUSION

Air pollution exposure, mainly PM10, was cross-sectionally and longitudinally associated with body composition in children/adolescents and adults. Railway/road-traffic noise exposures showed no associations in both cross-sectional and longitudinal analyses.

A qualitative characterization of meso-activity factors to estimate soil exposure for agricultural workers

BACKGROUND

Agricultural workers' exposure to soil contaminants is not well characterized. Activity pattern data are a useful exposure assessment tool to estimate extent of soil contact, though existing data do not sufficiently capture the range and magnitude of soil contact in the agricultural context.

OBJECTIVE

We introduce meso-activity, or specific tasks, to improve traditional activity pattern methodology. We propose a conceptual framework to organize the factors that may modify soil exposure and impact soil contact estimates within each meso-activity in agriculture. We build upon models from the US EPA to demonstrate an application of this framework to dose estimation.

METHODS

We conducted in-depth interviews with sixteen fruit and vegetable growers in Maryland to characterize factors that influence soil exposure in agriculture. For illustrative purposes, we demonstrate the application of the framework to translate our qualitative data into quantitative estimates of soil contact using US EPA models for ingestion and dermal exposure.

RESULTS

Growers discussed six tasks, or meso-activities, involving interaction with soil and described ten factors that may impact the frequency, duration and intensity of soil contact. We organized these factors into four categories (i.e., Environmental, Activity, Timing and Receptor; EAT-R) and developed a framework to improve agricultural exposure estimation and guide future research. Using information from the interviews, we estimated average daily doses for several agricultural exposure scenarios. We demonstrated how the integration of EAT-R qualitative factors into quantitative tools for exposure assessment produce more rigorous estimates of exposure that better capture the true variability in agricultural work.

SIGNIFICANCE

Our study demonstrates how a meso-activity-centered framework can be used to refine estimates of exposure for agricultural workers. This framework will support the improvement of indirect exposure assessment tools (e.g., surveys and questionnaires) and inform more comprehensive and appropriate direct observation approaches to derive quantitative estimations of soil exposure.

IMPACT STATEMENT

We propose a novel classification of activity pattern data that links macro and micro-activities through the quantification and characterization of meso-activities and demonstrate how the application of our qualitative framework improves soil exposure estimation for agricultural workers. These methodological advances may inform a more rigorous approach to the evaluation of pesticide and other chemical and biological exposures incurred by persons engaged in the cultivation of agricultural commodities in soil.

Model development and validation of personal exposure to PM2.5 among urban elders

Indirect measurements through a combination of microenvironment concentrations and personal activity diaries provide a potentially useful alternative for PM_2.5 exposure estimates. This study was to optimize a personal exposure model based on spatiotemporal model predictions for PM_2.5 exposure in a sub-cohort study. Personal, home indoor, home outdoor, and ambient monitoring data of PM_2.5 were conducted for an elderly population in the Taipei city of Taiwan. The proposed microenvironment exposure (ME) models incorporate PM_2.5 measurements and individual time-activity information with a generalized estimating equation (GEE) analysis. We evaluated model performance with daily personal PM_2.5 exposure based on the coefficient of determination, accuracy, and mean bias error. Ambient and home outdoor measures as exposure surrogates are likely to under- and overestimate personal exposure to PM_2.5 in our study population, respectively. Measured and predicted indoor exposures were highly correlated with personal PM_2.5 exposure. The awareness of peculiar smells is an important factor that significantly increases personal PM_2.5 exposure by 46-70%. The model incorporating home indoor PM_2.5 can achieve the highest agreement (R² = 0.790) with personal exposure and the lowest measurement error. The ME model with the GEE analysis combining home outdoor PM_2.5 determined by LUR model with a machine learning technique can improve the prediction (R² = 0.592) of personal PM_2.5 exposure, compared with the prediction of the traditional LUR model (R² = 0.385).

Radon in Indoor Air: Towards Continuous Monitoring

Radon poses significant health risks. Thus, the continuous monitoring of radon concentrations in buildings’ indoor air is relevant, particularly in schools. Low-cost sensors devices are emerging as promising technologies, although their reliability is still unknown. Therefore, this is the first study aiming to evaluate the performance of low-cost sensors devices for short-term continuous radon monitoring in the indoor air of nursery and primary school buildings. Five classrooms of different age groups (infants, pre-schoolers and primary school children) were selected from one nursery and one primary school in Porto (Portugal). Radon indoor concentrations were continuously monitored using one reference instrument (Radim 5B) and three commercially available low-cost sensors devices (Airthings Wave and RandonEye: RD200 and RD200P2) for short-term sampling (2–4 consecutive days) in each studied classroom. Radon concentrations were in accordance with the typical profiles found in other studies (higher on weekends and non-occupancy periods than on occupancy). Both RadonEye low-cost sensors devices presented similar profiles with Radim 5B and good performance indices (R2 reaching 0.961), while the Airthings Wave behavior was quite different. These results seem to indicate that the RadonEye low-cost sensors devices studied can be used in short-term radon monitoring, being promising tools for actively reducing indoor radon concentrations.

Exposure and dose assessment of school children to air pollutants in a tropical coastal-urban area

This study estimates exposure and inhaled dose to air pollutants of children residing in a tropical coastal-urban area in Southeast Brazil. For that, twenty-one children filled their time-activities diaries and wore the passive samplers to monitor NO₂. The personal exposure was also estimated using data provided by the combination of WRF-Urban/GEOS-Chem/CMAQ models, and the nearby monitoring station. Indoor/outdoor ratios were used to consider the amount of time spent indoors by children in homes and schools. The model's performance was assessed by comparing the modelled data with concentrations measured by urban monitoring stations. A sensitivity analyses was also performed to evaluate the impact of the model's height on the air pollutant concentrations. The results showed that the mean children's personal exposure to NO₂ predicted by the model (22.3 μg/m³) was nearly twice to those measured by the passive samplers (12.3 μg/m³). In contrast, the nearest urban monitoring station did not represent the personal exposure to NO₂ (9.3 μg/m³), suggesting a bias in the quantification of previous epidemiological studies. The building effect parameterisation (BEP) together with the lowering of the model height enhanced the air pollutant concentrations and the exposure of children to air pollutants. With the use of the CMAQ model, exposure to O₃, PM₁₀, PM_2.5, and PM₁ was also estimated and revealed that the daily children's personal exposure was 13.4, 38.9, 32.9, and 9.6 μg/m³, respectively. Meanwhile, the potential inhalation daily dose was 570-667 μg for PM_2.5, 684-789 μg for PM₁₀, and 163-194 μg for PM₁, showing to be favourable to cause adverse health effects. The exposure of children to air pollutants estimated by the numerical model in this work was comparable to other studies found in the literature, showing one of the advantages of using the modelling approach since some air pollutants are poorly spatially represented and/or are not routinely monitored by environmental agencies in many regions.

"I am an air quality scientist"- Using citizen science to characterise school children's exposure to air pollution

Children are particularly vulnerable to the harmful effects of air pollution. To tackle this issue and implement effective strategies to reduce child exposure, it is important to understand how children are exposed to this risk. This study followed a citizen science approach to air pollution monitoring, aiming to characterise school children's exposure to air pollution and to analyse how a citizen science approach to data collection could contribute to and enhance the research process. 258 children across five London primary schools attended air pollution education sessions and measured air pollution for a week using backpacks with built-in air quality sensors. Children received a summary of the results, advice and information on how to reduce exposure to air pollution. Data on the impact of the approach on the school community were collected using surveys and focus groups with children and their parents and interviews with the teachers involved. The unique data set obtained permitted us to map different routes and modes of transport used by the children and quantify different exposure levels. We identified that, on average, children were exposed to higher levels of air pollution when travelling to and from school, particularly during the morning journey where air pollution levels were on average 52% higher than exposures at school. Children who walked to and from school through busy main roads were exposed to 33% higher levels of air pollution than those who travelled through back streets. The findings from this study showed that using a citizen science approach to data collection, where children are actively involved in the research process, not only facilitated the gathering of a large data set by encouraging participation and stimulating adherence with the study protocol, but also increased children's awareness of air pollution, encouraging them to adopt positive behaviour changes to reduce their exposure.

The Impact of Individual Mobility on Long-Term Exposure to Ambient PM2.5: Assessing Effect Modification by Travel Patterns and Spatial Variability of PM2.5

The impact of individuals' mobility on the degree of error in estimates of exposure to ambient PM2.5 concentrations is increasingly reported in the literature. However, the degree to which accounting for mobility reduces error likely varies as a function of two related factors-individuals' routine travel patterns and the local variations of air pollution fields. We investigated whether individuals' routine travel patterns moderate the impact of mobility on individual long-term exposure assessment. Here, we have used real-world time-activity data collected from 2013 participants in Erie/Niagara counties, New York, USA, matched with daily PM2.5 predictions obtained from two spatial exposure models. We further examined the role of the spatiotemporal representation of ambient PM2.5 as a second moderator in the relationship between an individual's mobility and the exposure measurement error using a random effect model. We found that the effect of mobility on the long-term exposure estimates was significant, but that this effect was modified by individuals' routine travel patterns. Further, this effect modification was pronounced when the local variations of ambient PM2.5 concentrations were captured from multiple sources of air pollution data ('a multi-sourced exposure model'). In contrast, the mobility effect and its modification were not detected when ambient PM2.5 concentration was estimated solely from sparse monitoring data ('a single-sourced exposure model'). This study showed that there was a significant association between individuals' mobility and the long-term exposure measurement error. However, the effect could be modified by individuals' routine travel patterns and the error-prone representation of spatiotemporal variability of PM2.5.

A simple physical-activity-based model for managing children's activities against exposure to air pollutants

Air pollution has been a major health concern worldwide, such that there is an urgent need for exposure assessments of human exposure to air pollutants. As children are more active and may experience more exposure events than adults, it is more challenging to conduct exposure assessments for children. To obtain a general understanding of the impact that children's activity, associated with their respiratory rate (IR), has on estimated exposure risks, we adopted a simple model to narrow down children's exposure behaviors to four categories, which integrated children's regular schedules and the indoor-outdoor ratio (r_I/O) of air pollutants. Although outdoor play only occupies approximately 8.6% of the total weekly time, the results indicate that, in general, outdoor play contributes to over 50% of the total exposure to air pollutants when r_I/O is less than 0.1, which is due to children's relatively large IR during high-intensity activities. When air pollutants mainly originate from indoor sources (i.e., r_I/O=3.0), indoor sitting (28%) and sleeping (36%) account for the major portion of the total exposure due to the longer exposure duration while outdoor events, including playing, walking, and sitting, account for ~15% of the total exposure. In addition, we applied a ratio function (R_M/C) to compare our simple model to a common basic model, revealing that our simulated results are consistent with the basic model, i.e., 0.94≤R_M/C≤1.12, if the r_I/O of air pollutants falls in the range between 0.5 and 1.5. The sensitivity analysis indicates that indoor or outdoor play has a larger impact on the output results than other activity-related variables because of the correspondingly largest IR. We also incorporated weather factors to adjust children's activity schedules for winter and non-winter days showing the change in the contributions of children's activities to total exposure. For example, the contribution differential of outdoor play to the total exposure between winter and non-winter days is ~8% for air pollutants with an r_I/O value of 0.1. Although other factors, such as the activity intensity level and concentration of air pollutant in the microenvironment, must be refined in future studies, our simple model can be applied as a convenient approach to arrange children's activity schedules against possible air pollutant exposure.

Impact of indoor air pollution in nursery and primary schools on childhood asthma

Poor indoor air quality in scholar environments have been frequently reported, but its impact on respiratory health in schoolchildren has not been sufficiently explored. Thus, this study aimed to evaluate the associations between children's exposure to indoor air pollution (IAP) in nursery and primary schools and childhood asthma. Multivariate models (independent and multipollutant) quantified the associations of children's exposure with asthma-related health outcomes: reported active wheezing, reported and diagnosed asthma, and lung function (reduced FEV₁/FVC and reduced FEV₁). A microenvironmental modelling approach estimated individual inhaled exposure to major indoor air pollutants (CO₂, CO, formaldehyde, NO₂, O₃, TVOC, PM_2.5 and PM₁₀) in nursery and primary schools from both urban and rural sites in northern Portugal. Questionnaires and medical tests (spirometry pre- and post-bronchodilator) were used to obtain information on health outcomes and to diagnose asthma following the newest international clinical guidelines. After testing children for aeroallergen sensitisation, multinomial models estimated the effect of exposure to particulate matter on asthma in sensitised individuals. The study population were 1530 children attending nursery and primary schools, respectively 648 pre-schoolers (3-5 years old) and 882 primary school children (6-10 years old). This study found no evidence of a significant association between IAP in nursery and primary schools and the prevalence of childhood asthma. However, reported active wheezing was associated with higher NO₂, and reduced FEV₁ was associated with higher O₃ and PM_2.5, despite NO₂ and O₃ in schools were always below the 200 μg m^-3 threshold from WHO and National legislation, respectively. Moreover, sensitised children to common aeroallergens were more likely to have asthma during childhood when exposed to particulate matter in schools. These findings support the urgent need for mitigation measures to reduce IAP in schools, reducing its burden to children's health.

Dynamic classification of personal microenvironments using a suite of wearable, low-cost sensors

Human exposure to air pollution is associated with increased risk of morbidity and mortality. However, personal air pollution exposures can vary substantially depending on an individual's daily activity patterns and air quality within their residence and workplace. This work developed and validated an adaptive buffer size (ABS) algorithm capable of dynamically classifying an individual's time spent in predefined microenvironments using data from global positioning systems (GPS), motion sensors, temperature sensors, and light sensors. Twenty-two participants in Fort Collins, CO were recruited to carry a personal air sampler for a 48-h period. The personal sampler was retrofitted with a GPS and a pushbutton to complement the existing sensor measurements (temperature, motion, light). The pushbutton was used in conjunction with a traditional time-activity diary to note when the participant was located at "home", "work", or within an "other" microenvironment. The ABS algorithm predicted the amount of time spent in each microenvironment with a median accuracy of 99.1%, 98.9%, and 97.5% for the "home", "work", and "other" microenvironments. The ability to classify microenvironments dynamically in real time can enable the development of new sampling and measurement technologies that classify personal exposure by microenvironment.

Children's microenvironmental exposure to PM2.5 and ozone and the impact of indoor air filtration

BACKGROUND

In highly polluted urban areas, personal exposure to PM_2.5 and O₃ occur daily in various microenvironments. Identifying which microenvironments contribute most to exposure can pinpoint effective exposure reduction strategies and mitigate adverse health impacts.

METHODS

This work uses real-time sensors to assess the exposures of children with asthma (N = 39) in Shanghai, quantifying microenvironmental exposure to PM_2.5 and O₃. An air cleaner was deployed in participants' bedrooms where we hypothesized exposure could be most efficiently reduced. Monitoring occurred for two 48-h periods: one with bedroom filtration (portable air cleaner with HEPA and activated carbon filters) and the other without.

RESULTS

Children spent 91% of their time indoors with the majority spent in their bedroom (47%). Without filtration, the bedroom and classroom environments were the largest contributors to PM_2.5 exposure. With filtration, bedroom PM_2.5 exposure was reduced by 75% (45% of total exposure). Although filtration status did not impact O₃, the largest contribution of O₃ exposure also came from the bedroom.

CONCLUSIONS

Actions taken to reduce bedroom PM_2.5 and O₃ concentrations can most efficiently reduce total exposure. As real-time pollutant monitors become more accessible, similar analyses can be used to evaluate new interventions and optimize exposure reductions for a variety of populations.

PM2.5 exposure of various microenvironments in a community: Characteristics and applications

While the measurement of particulate matter (PM) with a diameter of less than 2.5 μm (PM_2.5) has been conducted for personal exposure assessment, it remains unclear how models that integrate microenvironmental levels with resolved activity and location information predict personal exposure to PM. We comprehensively investigated PM_2.5 concentrations in various microenvironments and estimated personal exposure stratified by the microenvironment. A variety of microenvironments (>200 places and locations, divided into 23 components according to indoor, outdoor, and transit modes) in a community were selected to characterize PM_2.5 concentrations. Infiltration factors calculated from microenvironmental/central-site station (M/S) monitoring campaigns with time-activity patterns were used to estimate time-weighted exposure to PM_2.5 for university students. We evaluated exposures using a four-stage modeling approach and quantified the performance of each component. It was found that the SidePak monitor overestimated the concentration by 3.5 times as compared with the filter-based measurements. Higher mean concentrations of PM_2.5 were observed in the Taoist temple and night market microenvironments; in contrast, lower concentrations were observed in air-conditioned offices and car microenvironments. While the exposure model incorporating detailed time-location information and infiltration factors achieved the highest prediction (R² = 0.49) of personal exposure to PM_2.5, the use of indoor, outdoor, and transit components for modeling also generated a consistent result (R² = 0.44).

Quantification of air pollution exposure to in-pram babies and mitigation strategies

Young children are particularly vulnerable to air pollution exposure during their early childhood development, yet research on exposure to in-pram babies in different types of single/double prams is limited. This work aims to mimick their exposure to multiple air pollutants - particulate matter ≤10 µm in aerodynamic diameter (PM₁₀), ≤2.5 µm (PM_2.5; fine particles), ≤1 µm (PM₁), ≤0.10 µm (measured as particle number concentration, PNC) - in three different types of prams (single pram facing the road; single pram facing parents; double pram facing the road). We also assessed the differences in exposure concentrations between typical adult and in-pram baby breathing height via simultaneous measurements besides assessing their physico-chemical properties (morphology and elemental composition). In addition, we analysed the impact of pram covers in mitigating in-pram exposure concentrations of selected pollutants. We carried out a total of 89 single runs, repeating on a 2.1 km long pre-defined route between an origin-destination pair (the University of Surrey to a local school) during the morning (08:00-10:00 h; local time) and afternoon (15:00-17:00 h) hours. These run simulated morning drop-off and afternoon pick-off times of school children. Overall, the experimental runs took about 66 h and covered the total length of 145 km. Substantial variability is observed in measured concentrations of different pollutants within each run (e.g., up to 290-times for PNC) and between different runs performed during different times of the day (e.g., ~62% variability in average PNC; ~7% for PM₁ and 8% for PM_2.5 during morning versus afternoon). The average in-pram concentration of fine particles was always higher by up to 44% compared with adult breathing height during both morning and afternoon runs. The comparison of exposure concentrations at two different sitting heights of double pram showed that PNC concentrations were higher by about 72% at the bottom seat compared to the top seat. Scanning electron microscope (SEM) analysis of PM_2.5-10 revealed traces of brake wear, tyre wear and re-suspended dust minerals with the predominance of brake and tyre wear emissions at baby height compared with a relatively larger share of earth crust elements at adult height. For mitigation measures, pram covers reduced concentrations of small-sized particles by as much as 39% (fine particles) and 43% (coarse particles). Our results reinforce the need for mitigating exposures to in-pram babies, especially at urban pollution hotspots such as busy congested roads, bus stops, and traffic intersections.

Schoolchildren's personal exposure to ultrafine particles in and near Accra, Ghana

Exposure to air pollution is a significant health risk, and children who are exposed to it are likely to have lifelong consequences. Ultrafine particles (UFPs) are emitted by all combustion sources, and can be used as a proxy for the presence of combustion products. The present study, the first of its kind to be conducted in Africa, assessed schoolchildren's exposure to UFPs, and apportioned their daily exposure to seven different microenvironments that they inhabited on a typical school day. The personal exposure of 61 pupils attending three junior high schools was measured for 24 h each using wearable monitors over a period of 10 weeks. Two of the schools were located in suburbs of Accra and the third in Berekuso, a nearby rural community. The results of our study revealed the complex nature of children's UFP exposure and its overall high to very high levels, significantly influenced by the locality (suburb) of residence and the type of activities in which the children were engaged. The mean (±standard error) daily exposure to UFPs (cm^-3) was6.9×10⁴(±6.8×10³),4.9(±1.0)×10⁴ and 1.6×10⁴±1.9×10³for pupils attending the Ashia Mills, Faith Baptist and Berekuso Basic Schools, respectively. Pupils attending the schools in urban Accra received higher exposure than those attending the school in the rural environment of Berekuso. The highest mean microenvironmental exposure was registered in the Home other microenvironment in an urban school and in Bedroom in another urban school and the rural school. The high exposure in Home other was due to pupils conducting trash burning and encountering environmental tobacco smoke, and the high exposure in Bedroom microenvironment was due to the burning of mosquito coils at night to prevent malaria. The principal sources that heightened exposure to UFPs were emissions from cooking (using firewood and charcoal), vehicular traffic and combustion of biomass and trash. All pupils recorded the highest exposure intensity in the Kitchen microenvironment.

Quantifying indoor air quality determinants in urban and rural nursery and primary schools

Poor indoor air quality can adversely affect children's health, comfort and school performance, but existing literature on quantifying indoor air pollutants (IAP) determinants' in nursery and primary schools is limited. Following previous studies, this study mainly aimed to quantify determinants of selected IAP, in nursery and primary schools from both urban and rural sites, accounting for seasonal variations. In 101 indoor microenvironments (classrooms, bedrooms and canteens) from 25 nursery and primary schools, CO₂, CO, HCOH, NO₂, O₃, total volatile organic compounds, PM₁, PM_2.5, PM₁₀, total suspended particles (TSP), and meteorological/comfort parameters were continuously sampled (occupancy and background levels), from at least 24 h to 9 consecutive days (not simultaneously) in each studied room; in some cases weekend was also considered. Children faced thermal discomfort and inadequate humidity, respectively in 60.1% and 44.1% of the studied classrooms. They were also exposed to high levels of IAP, namely PM_2.5 and CO₂ respectively in 69.0% and 41.3% of the studied classrooms, mostly in urban sites, depending on season and on occupancy and activity patterns (different amongst age groups). As PM_2.5 and CO₂ were the major concerning IAP, multivariate linear regression models were built to quantify (explained variability and relative importance) their main determinants, in both occupancy and non-occupancy (background) periods. Models for occupancy periods showed higher explained variability (R² = 0.64, 0.57 and 0.47, respectively, for CO₂, PM_2.5 and PM₁₀) than for non-occupancy. Besides background concentrations (43.5% of relative importance), relative humidity (21.1%), flooring material (17.0%), heating (6.7%) and age group of the occupants (5.3%), adjusted for season of sampling (6.4%) were predictors in CO₂ occupancy model. In the cases of PM_2.5 and PM₁₀ occupancy concentrations, besides background concentrations (71.2% and 67.2% of relative importance, respectively for PM_2.5 and PM₁₀), type of school management (8.8% and 15.2%) and flooring material (13.9% and 13.9%), adjusted for season of sampling (6.1% and 3.8%), were the main predictors. These findings support the need of mitigation measures to reduce IAP levels, and prevention actions to avoid children's exposure. Reducing the time spent indoors in the same microenvironment by doing more and/or longer breaks, improving ventilation and cleaning actions, and avoiding or making a better maintenance hardwood flooring materials, chalkboard use and VOC emitting materials, are practices that should be implemented and their impacts quantified.

A review of factors surrounding the air pollution exposure to in-pram babies and mitigation strategies

Air pollution exposure to in-pram babies poses a serious threat to their early childhood development, necessitating a need for effective mitigation measures. We reviewed the scientific and grey literature on in-pram babies and their personal exposure to traffic generated air pollutants such as particulate matter ≤10 μm (PM₁₀), ≤2.5 μm (PM_2.5), ≤0.10 μm (ultrafine particles) in size, black carbon and nitrogen oxides and potential mitigation pathways. In-pram babies can be exposed up to ~60% higher average concentrations depending on the pollutant types compared with adults. The air within the first few meters above the road level is usually most polluted. Therefore, we classified various pram types based on criteria such as height, width and the seating capacity (single versus twin) and assessed the breathing heights of sitting babies in various pram types available in the market. This classification revealed the pram widths between 0.56 and 0.82 m and top handle heights up to ~1.25 m as opposed to breathing height between 0.55 and 0.85 m, suggesting that the concentration within the first meter above the road level is critical for exposure to in-pram babies. The assessment of flow features around the prams suggests that meteorological conditions (e.g., wind speed and direction) and traffic-produced turbulence affect the pollution dispersion around them. A survey of the physicochemical properties of particles from roadside environment demonstrated the dominance of toxic metals that have been shown to damage their frontal lobe as well as cognition and brain development when inhaled by in-pram babies. We then assessed a wide range of active and passive exposure mitigation strategies, including a passive control at the receptor such as the enhanced filtration around the breathing zone and protection of prams via covers. Technological solutions such as creating a clean air zone around the breathing area can provide instant solutions. However, a holistic approach involving a mix of innovative technological solutions, community empowerment and exposure-centric policies are needed to help limit personal exposure of in-pram babies.

Personal Exposure to PM2.5 Black Carbon and Aerosol Oxidative Potential using an Automated Microenvironmental Aerosol Sampler (AMAS)

Traditional methods for measuring personal exposure to fine particulate matter (PM2.5) are cumbersome and lack spatiotemporal resolution; methods that are time-resolved are limited to a single species/component of PM. To address these limitations, we developed an automated microenvironmental aerosol sampler (AMAS), capable of resolving personal exposure by microenvironment. The AMAS is a wearable device that uses a GPS sensor algorithm in conjunction with a custom valve manifold to sample PM2.5 onto distinct filter channels to evaluate home, school, and other (e.g., outdoors, in transit, etc.) exposures. Pilot testing was conducted in Fresno, CA where 25 high-school participants ( n = 37 sampling events) wore an AMAS for 48-h periods in November 2016. Data from 20 (54%) of the 48-h samples collected by participants were deemed valid and the filters were analyzed for PM2.5 black carbon (BC) using light transmissometry and aerosol oxidative potential (OP) using the dithiothreitol (DTT) assay. The amount of inhaled PM2.5 was calculated for each microenvironment to evaluate the health risks associated with exposure. On average, the estimated amount of inhaled PM2.5 BC (μg day-1) and OP [(μM min-1) day-1] was greatest at home, owing to the proportion of time spent within that microenvironment. Validation of the AMAS demonstrated good relative precision (8.7% among collocated instruments) and a mean absolute error of 22% for BC and 33% for OP when compared to a traditional personal sampling instrument. This work demonstrates the feasibility of new technology designed to quantify personal exposure to PM2.5 species within distinct microenvironments.

Geographic Information Science and the Analysis of Place and Health

The representation of place is a key theoretical advancement that Geographic Information Science can offer to improve the understanding of environmental determinants of health, but developing robust computational representations of place requires a substantial departure from conventional notions of geographic representation in Geographic Information Systems (GIS). Unlike conventional GIS representations based on either objects or locations, we suggest place representation should incorporate dynamic subjective, experiential, and relational aspects of place, as the influence of place on health behavior concerns not only the features that can be objectively observed at a particular location but also the environmental perceptions of the individual, as molded by biological, social, and experiential characteristics. In addition, assessments of environmental exposures on health outcomes should focus on individuals' time-activity patterns and microenvironment profiles, which form a potentially unique personalized exposure environment for each individual. Addressing these representational challenges via collaborative research has the potential to advance both Geographic Information Science and health research.

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 (PM_2.5), 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.

A critical review of developmental exposure to particulate matter, autism spectrum disorder, and attention deficit hyperactivity disorder

Autism spectrum disorder (ASD) and attention deficit (hyperactivity) disorder (ADD/ADHD) are key focuses of current health research due to their increasing prevalence. The objective of this systematic literature search and critical review was to evaluate whether the human epidemiologic data indicate a pattern of association between ASD or ADD/ADHD and developmental exposure to particulate matter (PM), with a focus on exposures encountered before the age of three. A MEDLINE and EMBASE search was conducted; following preliminary and full-text screening, 14 relevant articles were identified for review. Three of the 14 studies were prospective cohort studies evaluating exposure to PM₁₀; 11 studies had a case-control design. There was no consistent association between developmental PM exposure and ASD across the three of the cohort studies. Seven of the case-control studies examined the relationship between PM_2.5 and/or PM₁₀ and ASD; four examined the relationship between developmental diesel PM exposure and ASD. Overall, there was low external consistency in results among studies of PM_2.5/PM₁₀ and ASD, with some reporting high internal consistency without significant associations, others showing associations with high internal consistency for specific exposure windows only (e.g., third trimester), and still others showing high consistency for moderate to strong associations between PM and ASD. The majority of studies reporting significant results had low effect sizes in conjunction with small sample sizes. The four studies of diesel PM and ASD also had low external consistency of results. Only one study evaluated associations with ADD/ADHD, and it found no significant associations with PM₁₀. The inconsistent findings across studies of developmental exposure to PM and ASD may be attributed to differences in the study populations, exposure assessments, outcome assessments, or chance. Further research is needed to understand the underlying biological mechanisms that lead to ASD and ADD/ADHD and how PM might be involved in those mechanisms, if at all. High-quality epidemiologic studies are also needed to conclusively determine whether developmental PM exposure is a causal factor for ASD or ADD/ADHD, with focus on a well-developed exposure assessment.

Personal measurement of exposure to black carbon and ultrafine particles in schoolchildren from PARIS cohort (Paris, France)

This study aimed to measure in French children personal exposure concentrations of black carbon (BC) and ultrafine particles (UFP) and to quantify the contribution of different microenvironments (home, school, places of extracurricular activities, transport) to their total exposure. It was conducted on 96 9-year-old children from the PARIS birth cohort. BC and UFP were continuously measured by portable devices (microAeth^® AE51 and DiSCmini^® ) for a minimum of 24 hours, while participating families simultaneously filled in a space-time-activities-budget questionnaire. BC exposure concentration was higher during trips (principally metro/train and bus), while UFP exposure concentration was higher during indoor activities (mainly eating at restaurants) and in trips. The most important UFP peaks were measured at home, especially during cooking. Home and school together accounted for much of the total exposure, 83.8% for BC and 85.3% for UFP. The contribution of transport to total exposure was 12.4% for BC and 9.7% for UFP, while extracurricular activities were responsible for 3.8% and 5% of the total exposure to BC and UFP, respectively.

Evaluation of Low-Cost Mitigation Measures Implemented to Improve Air Quality in Nursery and Primary Schools

Indoor air pollution mitigation measures are highly important due to the associated health impacts, especially on children, a risk group that spends significant time indoors. Thus, the main goal of the work here reported was the evaluation of mitigation measures implemented in nursery and primary schools to improve air quality. Continuous measurements of CO₂, CO, NO₂, O₃, CH₂O, total volatile organic compounds (VOC), PM₁, PM_2.5, PM₁₀, Total Suspended Particles (TSP) and radon, as well as temperature and relative humidity were performed in two campaigns, before and after the implementation of low-cost mitigation measures. Evaluation of those mitigation measures was performed through the comparison of the concentrations measured in both campaigns. Exceedances to the values set by the national legislation and World Health Organization (WHO) were found for PM_2.5, PM₁₀, CO₂ and CH₂O during both indoor air quality campaigns. Temperature and relative humidity values were also above the ranges recommended by American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). In general, pollutant concentrations measured after the implementation of low-cost mitigation measures were significantly lower, mainly for CO₂. However, mitigation measures were not always sufficient to decrease the pollutants’ concentrations till values considered safe to protect human health.

Decreased blood pressure associated with in-vehicle exposure to carbon monoxide in Korean volunteers

Background

Carbon monoxide (CO) is one of the primary components of emissions from light-duty vehicles, and reportedly comprises 77% of all pollutants emitted in terms of concentration. Exposure to CO aggravates cardiovascular disease and causes other health disorders. The study was aimed to assess the negative effects by injecting different amounts of CO concentration directly to human volunteers boarding in the car.

Methods

Human volunteers were exposed to CO concentrations of 0, 33.2, and 72.4 ppm, respectively during the first test and 0, 30.3, and 48.8 ppm respectively during the second test while seated in the car. The volunteers were exposed to each concentration for approximately 45 min. After exposure, blood pressure measurement, blood collection (carboxyhemoglobin [COHb] analysis), medical interview, echocardiography test, and cognitive reaction test were performed.

Result

In patients who were exposed to a mean concentration of CO for 72.4 ± 1.4 ppm during the first exposure test and 48.8 ± 3.7 ppm during the second exposure test, the COHb level exceeded 2%. Moreover, the diastolic blood pressure was decreased while increasing in CO concentration after exposure. The medical interview findings showed that the degree of fatigue was increased and the degree of concentration was reduced when the exposed concentration of CO was increased.

Conclusion

Although the study had a limited sample size, we found that even a low concentration of CO flowing into a car could have a negative influence on human health, such as change of blood pressure and degree of fatigue.

Exposure estimation errors to nitrogen oxides on a population scale due to daytime activity away from home

Accurate estimation of exposure to air pollution is necessary for assessing the impact of air pollution on the public health. Most environmental epidemiology studies assign the home address exposure to the study subjects. Here, we quantify the exposure estimation error at the population scale due to assigning it solely at the residence place. A cohort of most schoolchildren in Israel (~950,000), age 6-18, and a representative cohort of Israeli adults (~380,000), age 24-65, were used. For each subject the home and the work or school addresses were geocoded. Together, these two microenvironments account for the locations at which people are present during most of the weekdays. For each subject, we estimated ambient nitrogen oxide concentrations at the home and work or school addresses using two air quality models: a stationary land use regression model and a dynamic dispersion-like model. On average, accounting for the subjects' work or school address as well as for the daily pollutant variation reduced the estimation error of exposure to ambient NO_x/NO₂ by 5-10ppb, since daytime concentrations at work/school and at home can differ significantly. These results were consistent regardless which air quality model as used and even for subjects that work or study close to their home. Yet, due to their usually short commute, assigning schoolchildren exposure solely at their residential place seems to be a reasonable estimation. In contrast, since adults commute for longer distances, assigning exposure of adults only at the residential place has a lower correlation with the daily weighted exposure, resulting in larger exposure estimation errors. We show that exposure misclassification can result from not accounting for the subjects' time-location trajectories through the spatiotemporally varying pollutant concentrations field.

Measurement and health risk assessment of PM2.5, flame retardants, carbonyls and black carbon in indoor and outdoor air in kindergartens in Hong Kong

Indoor air pollution is closely related to children's health. Polybrominated diphenyl ethers (PBDEs) and dechlorane plus (DP) transmitted through indoor PM_2.5 and dust, along with carbonyl compounds and black carbon (BC) aerosol were analysed in five Hong Kong kindergartens. The results showed that 60% of the median PM_2.5 levels (1.3×10¹ to 2.9×10¹μg/m³ for indoor; 9.5 to 8.8×10¹μg/m³ for outdoor) in the five kindergartens were higher than the guidelines set by the World Health Organization (2.5×10¹μg/m³). Indoor PM_2.5 mass concentrations were correlated with outdoor PM_2.5 in four of the kindergartens. The PBDEs (0.10-0.64ng/m³ in PM_2.5; 0.30-2.0×10²ng/g in dust) and DP (0.05-0.10ng/m³ in PM_2.5; 1.3-8.7ng/g in dust) were detected in 100% of the PM_2.5 and dust samples. Fire retardant levels in the air were not correlated with the levels of dust in this study. The median BC concentrations varied by >7-fold from 8.8×10²ng/m^-3 to 6.7×10³ng/m^-3 and cooking events might have caused BC concentrations to rise both indoors and outdoors. The total concentrations of 16 carbonyls ranged from 4.7×10¹μg/m³ to 9.3×10¹μg/m³ indoors and from 1.9×10¹μg/m³ to 4.3×10¹μg/m³ outdoors, whilst formaldehyde was the most abundant air carbonyl. Indoor carbonyl concentrations were correlated with outdoor carbonyls in three kindergartens. The health risk assessment showed that hazard indexes (HIs) HIs of non-cancer risks from PBDEs and DPs were all lower than 0.08, whilst non-cancer HIs of carbonyl compounds ranged from 0.77 to 1.85 indoors and from 0.50 to 0.97 outdoors. The human intake of PBDEs and DP through inhalation of PM_2.5 accounted for 78% to 92% of the total intake. The cancer hazard quotients (HQs) of formaldehyde ranged from 4.5E-05 to 2.1E-04 indoors and from 1.9E-05 to 6.2E-05 outdoors. In general, the indoor air pollution in the five Hong Kong kindergartens might present adverse effects to children, although different schools showed distinct pollution levels, so indoor air quality might be improved through artificial measures. The data will be useful to developing a feasible management protocol for indoor environments.

Children's Exposure to Radon in Nursery and Primary Schools

The literature proves an evident association between indoor radon exposure and lung cancer, even at low doses. This study brings a new approach to the study of children's exposure to radon by aiming to evaluate exposure to indoor radon concentrations in nursery and primary schools from two districts in Portugal (Porto and Bragança), considering different influencing factors (occupation patterns, classroom floor level, year of the buildings' construction and soil composition of the building site), as well as the comparison with IAQ standard values for health protection. Fifteen nursery and primary schools in the Porto and Bragança districts were considered: five nursery schools for infants and twelve for pre-schoolers (seven different buildings), as well as eight primary schools. Radon measurements were performed continuously. The measured concentrations depended on the building occupation, classroom floor level and year of the buildings' construction. Although they were in general within the Portuguese legislation for IAQ, exceedances to international standards were found. These results point out the need of assessing indoor radon concentrations not only in primary schools, but also in nursery schools, never performed in Portugal before this study. It is important to extend the study to other microenvironments like homes, and in time to estimate the annual effective dose and to assess lifetime health risks.

Gaseous pollutants on rural and urban nursery schools in Northern Portugal

Indoor air quality in nursery schools is different from other schools and this has been largely ignored, particularly in rural areas. Urban and rural nursery schools have different environmental characteristics whose knowledge needs improvement. Thus, this study aimed to evaluate continuously the concentrations of CO2, CO, NO2, O3, CH2O and total VOC in three rural nursery schools and one urban, being the only one comparing urban and rural nurseries with continuous measurements, thus considering occupation and non-occupation periods. Regarding CO2, urban nursery recorded higher concentrations (739-2328 mg m(-3)) than rural nurseries (653-1078 mg m(-3)). The influence of outdoor air was the main source of CO, NO2 and O3 indoor concentrations. CO and NO2 concentrations were higher in the urban nursery and O3 concentrations were higher in rural ones. CH2O and TVOC concentrations seemed to be related to internal sources, such as furniture and flooring finishing and cleaning products.

Children's exposure to indoor air in urban nurseries-part I: CO₂ and comfort assessment

Indoor air quality (IAQ) in nurseries is an emerging case-study. Thus, this study, as the Part I of the larger study "Children's exposure to indoor air in urban nurseries", aimed to: i) evaluate nurseries' indoor concentrations of carbon dioxide (CO2), a global IAQ indicator, in class and lunch rooms; ii) assess indoor comfort parameters-temperature (T) and relative humidity (RH); and iii) analyse them according to guidelines and references for IAQ, comfort and children's health. Indoor continuous measurements were performed. Non-compliances with guidelines were found in comfort parameters, which could cause discomfort situations and also microbial proliferation. Exceedances in CO2 concentrations were also found and they were caused by poor ventilation and high classroom occupation. More efficient ventilation and control of comfort parameters, as well as to reduce occupation by reviewing Portuguese legislation on that matter, would certainly improve IAQ and comfort in nurseries and consequently safeguard children's health.

Particulate matter in rural and urban nursery schools in Portugal

Studies have been showing strong associations between exposures to indoor particulate matter (PM) and health effects on children. Urban and rural nursery schools have different known environmental and social differences which make their study relevant. Thus, this study aimed to evaluate indoor PM concentrations on different microenvironments of three rural nursery schools and one urban nursery school, being the only study comparing urban and rural nursery schools considering the PM1, PM2.5 and PM10 fractions (measured continuously and in terms of mass). Outdoor PM2.5 and PM10 were also obtained and I/O ratios have been determined. Indoor PM mean concentrations were higher in the urban nursery than in rural ones, which might have been related to traffic emissions. However, I/O ratios allowed concluding that the recorded concentrations depended more significantly of indoor sources. WHO guidelines and Portuguese legislation exceedances for PM2.5 and PM10 were observed mainly in the urban nursery school.

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

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