Microenvironmental time-activity patterns in Chongqing, China

Distributions and determinants of time spent outdoors among school-age children in China

BACKGROUND

The outdoor time is a key factor that determines children's exposure to environmental contaminants. Meanwhile, children reap numerous physical and mental health benefits from playing outdoors.

OBJECTIVE

This study aimed to characterize the distributions and identify determinants of the time spent outdoors among school-age children in China.

METHODS

The study recruited 41,439 children aged 6-17 years in Mainland China using a multi-stage cluster random sampling method. This sample was nationally representative with sample weights created to account for the complex survey design. Information on time-activity patterns were collected with a standard questionnaire through face-to-face interviews. Frequency distributions of time outdoors were created by age group, gender, region, and other sociodemographic factors with sample weights. The key factors influencing time outdoors were identified using multivariable linear regression models.

RESULTS

The grand mean (±standard deviation) time outdoors was 101 ± 51 min/day for all the study participants, 22.3% having <60 min/day. Children spent longer time outdoors in warm seasons and on weekends. Children's outdoor time was significantly influenced by gender, age, urbanicity, region, annual total household expenditure, building environment, and meteorological conditions (annual mean temperature, sunshine time, and precipitation). Girls, 15-17 year old, and urban children had 6 min/day, 8 min/day, and 13 min/day less outdoor time than boys, 6-8 year old, and rural children, respectively. Most significantly, urban girls and high school students had the shortest outdoor time. The cement ground was the most important type of ground for children playing outside.

SIGNIFICANCE

This was the first national-scale study that characterized the time outdoors and where is it spent among school-age children in China. It revealed that one-fifth of Chinese children spent less than one hour outdoors every day, and urban girls had particular "indoor tendencies". The findings provide bases for future interventions and guidelines aimed at promoting children's physical activities.

The Effects of Ventilation and Filtration on Indoor PM2.5 in Office Buildings in Four Countries

Fine particulate matter (PM2.5) is an airborne pollutant associated with negative acute and chronic human health outcomes. Although the majority of PM2.5 research has focused on outdoor exposures, people spend the majority of their time indoors, where PM2.5 of outdoor origin can penetrate. In this work, we measured indoor PM2.5 continuously for one year in 37 urban commercial offices with mechanical or mixed-mode ventilation in China, India, the United Kingdom, and the United States. We found that indoor PM2.5 concentrations were generally higher when and where outdoor PM2.5 was elevated. In India and China, mean workday indoor PM2.5 levels exceeded the World Health Organization's 24-hour exposure guideline of 25 µg/m3 about 17% and 27% of the time, respectively. Our statistical models found evidence that the operation of mechanical ventilation systems could mitigate the intrusion of outdoor PM2.5: during standard work hours, a 10 µg/m3 increase in outdoor PM2.5 was associated with 19.9% increase in the expected concentration of indoor PM2.5 (p<0.0001), compared to a larger 23.4% increase during non-work hours (p<0.0001). Finally, our models found that using filters with ratings of MERV 13-14 or MERV 15+ was associated with a 30.9% (95% CI: -55.0%, +6.2%) or 39.4% (95% CI: -62.0%, -3.4%) reduction of indoor PM2.5, respectively, compared to filters with lower MERV 7-12 ratings. Our results demonstrate the potential efficacy of mechanical ventilation with efficient filtration as a public health strategy to protect workers from PM2.5 exposure, particularly where outdoor levels of PM2.5 are elevated.

Household Exposure to Secondhand Smoke among Chinese Children: Status, Determinants, and Co-Exposures

Smoking prevalence stays high among adults in China, which also makes children exposed to secondhand smoke (SHS) in their households. This study aimed to investigate the status of SHS exposure among Chinese children, identify the influencing factors, and determine "co-exposure" to tobacco and other smokes in households. A total of 41,439 children aged 6-17 years were recruited from 30 provinces in Mainland China through the first Chinese Environmental Exposure-Related Human Activity Model Survey for Children (CEERHAPS-C). Information regarding children's demographics, socioeconomic status, and exposures to SHS and solid fuel smoke (SFS) in households was collected using a comprehensive questionnaire. Factors that affected exposures to household smokes were identified using multivariable logistic regressions. The overall prevalence of household SHS exposure was 41.7%, and the average duration was 14.7 ± 14.6 min/day among the exposed participants. Prevalence of household SHS exposure increased among children in older age groups and with parents in lower education levels. Among SHS-exposed children, 34% had co-exposure to SFS, and they had a significantly higher risk of co-exposure than non-SHS exposed children (odds ratio = 1.12, 95% confidence interval: 1.061, 1.162). The prevalence of household SHS exposure remains high among school-age children, suggesting the need to develop and implement smoking-free home programs.

Indoor inhalation intake fractions of fine particulate matter: review of influencing factors

Exposure to fine particulate matter (PM_2.5 ) is a major contributor to the global human disease burden. The indoor environment is of particular importance when considering the health effects associated with PM_2.5 exposures because people spend the majority of their time indoors and PM_2.5 exposures per unit mass emitted indoors are two to three orders of magnitude larger than exposures to outdoor emissions. Variability in indoor PM_2.5 intake fraction (iF_in,total ), which is defined as the integrated cumulative intake of PM_2.5 per unit of emission, is driven by a combination of building-specific, human-specific, and pollutant-specific factors. Due to a limited availability of data characterizing these factors, however, indoor emissions and intake of PM_2.5 are not commonly considered when evaluating the environmental performance of product life cycles. With the aim of addressing this barrier, a literature review was conducted and data characterizing factors influencing iF_in,total were compiled. In addition to providing data for the calculation of iF_in,total in various indoor environments and for a range of geographic regions, this paper discusses remaining limitations to the incorporation of PM_2.5 -derived health impacts into life cycle assessments and makes recommendations regarding future research.

Indoor concentrations of nitrogen dioxide and sulfur dioxide from burning solid fuels for cooking and heating in Yunnan Province, China

The Chinese national pollution census has indicated that the domestic burning of solid fuels is an important contributor to nitrogen dioxide (NO2 ) and sulfur dioxide (SO2 ) emissions in China. To characterize indoor NO2 and SO2 air concentrations in relation to solid fuel use and stove ventilation in the rural counties of Xuanwei and Fuyuan, in Yunnan Province, China, which have among the highest lung cancer rates in the nation, a total of 163 participants in 30 selected villages were enrolled. Indoor 24-h NO2 and SO2 samples were collected in each household over two consecutive days. Compared to smoky coal, smokeless coal use was associated with higher NO2 concentrations [geometric mean (GM) = 132 μg/m(3) for smokeless coal and 111 μg/m(3) for smoky coal, P = 0.065] and SO2 [limit of detection = 24 μg/m(3) ; percentage detected (%Detect) = 86% for smokeless coal and 40% for smoky coal, P < 0.001]. Among smoky coal users, significant variation of NO2 and SO2 air concentrations was observed across different stove designs and smoky coal sources in both counties. Model construction indicated that the measurements of both pollutants were influenced by stove design. This exposure assessment study has identified high levels of NO2 and SO2 as a result of burning solid fuels for cooking and heating.

Source apportionment of indoor PM10 in Elderly Care Centre

Source contribution to atmospheric particulate matter (PM) has been exhaustively modelled. However, people spend most of their time indoors where this approach is less explored. This evidence worsens considering elders living in Elderly Care Centres, since they are more susceptible. The present study aims to investigate the PM composition and sources influencing elderly exposure. Two 2-week sampling campaigns were conducted-one during early fall (warm phase) and another throughout the winter (cold phase). PM10 were collected with two TCR-Tecora(®) samplers that were located in an Elderly Care Centre living room and in the correspondent outdoor. Chemical analysis of the particles was performed by neutron activation analysis for element characterization, by ion chromatography for the determination of water soluble ions and by a thermal optical technique for the measurement of organic and elemental carbon. Statistical analysis showed that there were no statistical differences between seasons and environments. The sum of the indoor PM10 components measured in this work explained 57 and 53 % of the total PM10 mass measured by gravimetry in warm and cold campaigns, respectively. Outdoor PM10 concentrations were significantly higher during the day than night (p value < 0.05), as well as Ca(2+), Fe, Sb and Zn. The contribution of indoor and outdoor sources was assessed by principal component analysis and showed the importance of the highways and the airport located less than 500 m from the Elderly Care Centre for both indoor and outdoor air quality.

Evaluation and comparison of measurement methods for personal exposure to fine particles in Beijing, China

Ambient measurement and microenvironmental modeling were compared with personal measurement in Beijing, China to evaluate their capacity to determine personal exposure to PM(2.5). The comparison showed the association was insignificant between ambient and personal concentrations, but was significant between modeled and personal concentrations. The association between ambient and personal concentrations was improved for non-smoking dormitories, on heavily polluted days and on weekdays. The median difference was 41% between ambient and personal concentrations and 17% between modeled and personal concentrations. The factors affecting the association and agreement between methods were indoor sources and ubiquitous "personal cloud".