Wintertime pollution level, size distribution and personal daily exposure to particulate matters in the northern and southern rural Chinese homes and variation in different household fuels

Enhancing indoor PM2.5 predictions based on land use and indoor environmental factors by applying machine learning and spatial modeling approaches

The presence of fine particulate matter (PM2.5) indoors constitutes a significant component of overall PM2.5 exposure, as individuals spend 90% of their time indoors; however, personal monitoring for large cohorts is often impractical. In light of this, this study seeks to employ a novel geospatial artificial intelligence (Geo-AI) coupled with machine learning (ML) approaches to develop indoor PM2.5 models. Multiple predictor variables were collected from 102 residential households, including meteorological data; elevation; land use; indoor environmental factors including human activities, building characteristics, infiltration factors, and real-time measurements; and various other factors. Geo-AI, which integrates land use regression, inverse distance weighting, and ML algorithms, was utilized to construct outdoor PM2.5 and PM10 estimates for residential households. The most influential variables were identified via correlation analysis and stepwise regression. Three ML methods, namely support vector machine, multiple linear regression, and multilayer perceptron (MLP) were used to estimate indoor PM2.5 concentration. Then, MLP was employed to blend three ML algorithms. The resulting model demonstrated commendable performance, achieving a 10-fold cross-validation R2 of 0.92 and a root mean square error of 2.3 μg/m3 for indoor PM2.5 estimations. Notably, the combination of Geo-AI and ensembled ML models in this study outperformed all other individual models. In addition, the present study pointed out the most influential factors for indoor PM2.5 model were outdoor PM2.5, PM2.5/PM10 ratio, sampling month, infiltration factor, located near factory, cleaning frequency, number of door entrance linked with outdoor, and wall material. Further exploration of diverse ensemble model formats to integrate estimates from different models could enhance overall performance. Consequently, the potential applications of this model extend to estimating real individual exposure to PM2.5 for further epidemiological research. Moreover, the model offers valuable insights for efficient indoor air quality management and control strategies.

Particulate polycyclic aromatic hydrocarbons in rural households burning solid fuels in Xuanwei County, Southwest China: occurrence, size distribution, and health risks

The study is about the size distribution and health risks of polycyclic aromatic hydrocarbons (PAHs) in indoor environment of Xuanwei, Southwest China particle samples were collected by Anderson 8-stage impactor which was used to gather particle samples to nine size ranges. Size-segregated samples were collected in indoor from a rural village in Xuanwei during the non-heating and heating seasons. The results showed that the total concentrations of the indoor particulate matter (PM) were 757 ± 60 and 990 ± 78 μg/m3 in non-heating and heating seasons, respectively. The total concentration of indoor PAHs reached to 8.42 ± 0.53 μg/m3 in the heating season, which was considerably greater than the concentration in the non-heating season (2.85 ± 1.72 μg/m3). The size distribution of PAHs showed that PAHs were mainly enriched in PMs with the diameter <1.1 μm. The diagnostic ratios (DR) and principal component analysis (PCA) showed that coal and wood for residential heating and cooking were the main sources of indoor PAHs. The results of the health risk showed that the total deposition concentration (DC) in the alveolar region (AR) was 0.25 and 0.68 μg/m3 in the non-heating and heating seasons respectively. Throughout the entire sampling periods, the lifetime cancer risk (R) based on DC of children and adults varied between 3.53 ×10-5 to 1.79 ×10-4. During the heating season, the potential cancer risk of PAHs in adults was significant, exceeding 10-4, with a rate of 96%.

Understanding the time-activity pattern to improve the measurement of personal exposure: An exploratory and experimental research

Although ambient fine particulate matter (PM2.5) concentrations and their components are commonly used as proxies for personal exposure monitoring, developing an accurate and cost-effective method to use these proxies for personal exposure measurement continues to pose a significant challenge. Herein, we propose a scenario-based exposure model to precisely estimate personal exposure level of heavy metal(loid)s (HMs) using scenario HMs concentrations and time-activity patterns. Personal exposure levels and ambient pollution levels for PM2.5 and HMs differed significantly with corresponding personal/ambient ratios of approximately 2, and exposure scenarios could narrow the assessment error gap by 26.1-45.4%. Using a scenario-based exposure model, we assessed the associated health risks of a large sample population and identified that the carcinogenic risk of As exceeded 1 × 10-6, while we observed non-carcinogenic risks from As, Cd, Ni, and Mn in personal exposure to PM2.5. We conclude that the scenario-based exposure model is a preferential alternative for monitoring personal exposure compared to ambient concentrations. This method ensures the feasibility of personal exposure monitoring and health risk assessments in large-scale studies.

Mapping the personal PM2.5 exposure of China's population using random forest

Ambient monitoring may cause estimation errors, and wearable monitoring is expensive and labor-intensive when assessing PM_2.5 personal exposure. Estimation errors have limited the development of exposure science and environmental epidemiology. Thus, we developed a scenario-based exposure (SBE) model that covered 8 outdoor exposure scenarios and 1 indoor scenario with corresponding time-activity patterns in Baoding City. The linear regression analysis of the SBE yielded an R² value of 0.913 with satisfactory accuracy and reliability. To apply the SBE model to large-scale studies, we predicted time-activity patterns with the random forest model and atmosphere-to-scenario ratios with the linear regression model to obtain the essential parameters of the SBE model; their R² was 0.65-0.93. The developed model would economize the study expenditure of field sampling for personal PM_2.5 and deepen the understanding of the influences of indoor and outdoor factors on personal PM_2.5. Using this method, we found that the personal PM_2.5 exposure of Chinese residents was 10.50-347.02 μg/m³ in 2020, higher than the atmospheric PM_2.5 concentration. Residents in North and Central China, especially the Beijing-Tianjin-Hebei region and the Fen-Wei Plains, had higher personal PM_2.5 exposure than those in other areas.

Quantifying the dynamic characteristics of indoor air pollution using real-time sensors: Current status and future implication

People generally spend most of their time indoors, making indoor air quality be of great significance to human health. Large spatiotemporal heterogeneity of indoor air pollution can be hardly captured by conventional filter-based monitoring but real-time monitoring. Real-time monitoring is conducive to change air assessment mode from static and sparse analysis to dynamic and massive analysis, and has made remarkable strides in indoor air evaluation. In this review, the state of art, strengths, challenges, and further development of real-time sensors used in indoor air evaluation are focused on. Researches using real-time sensors for indoor air evaluation have increased rapidly since 2018, and are mainly conducted in China and the USA, with the most frequently investigated air pollutants of PM_2.5. In addition to high spatiotemporal resolution, real-time sensors for indoor air evaluation have prominent advantages in 3-dimensional monitoring, pollution peak and source identification, and short-term health effect evaluation. Huge amounts of data from real-time sensors also facilitate the modeling and prediction of indoor air pollution. However, challenges still remain in extensive deployment of real-time sensors indoors, including the selection, performance, stability, as well as calibration of sensors. In future, sensors with high performance, long-term stability, low price, and low energy consumption are welcomed. Furthermore, more target air pollutants are also expected to be detected simultaneously by real-time sensors in indoor air monitoring.

Household solid fuel use and stroke incidence: Evidence from a national cohort study

Stroke is one of the leading causes of global mortality and disability. No specific study has focused on the association between household solid fuel use for different purposes and incident stroke. Therefore, we explored the associations between household solid fuel use purposes and switches and incident stroke based on a national prospective cohort study. There were 12,485 participants included in this study after exclusions. The incidence density of stroke was 8.29 for every 1,000 person-years. Household solid fuel use simultaneously for heating and cooking had the largest hazard effect on stroke occurrence [hazard ratio (HR), 1.35; 95% confidence interval (CI), 1.07, 1.70] with a significant linear trend (P < 0.01). Solid fuel use for cooking was significantly associated with increased risk of stroke occurrence (HR, 1.27; 95% CI, 1.06, 1.51). Persistent clean fuel use for both heating and cooking associated with a lower risk of stroke occurrence (HR, 0.79; 95% CI: 0.64, 0.99), and switching from solid fuel to clean-fuel use for cooking associated with a lower risk of stroke occurrence (HR, 0.89; 95% CI, 0.73, 1.09) compared with persistent solid fuel use. Effective measures to improve the household cooking environment may be necessary to prevent incident stroke.

Comparing human exposure to fine particulate matter in low and high-income countries: A systematic review of studies measuring personal PM2.5 exposure

BACKGROUND

Due to the adverse health effects of air pollution, researchers have advocated for personal exposure measurements whereby individuals carry portable monitors in order to better characterise and understand the sources of people's pollution exposure.

OBJECTIVES

The aim of this systematic review is to assess the differences in the magnitude and sources of personal PM2.5 exposures experienced between countries at contrasting levels of income.

METHODS

This review summarised studies that measured participants personal exposure by carrying a PM2.5 monitor throughout their typical day. Personal PM2.5 exposures were summarised to indicate the distribution of exposures measured within each country income category (based on low (LIC), lower-middle (LMIC), upper-middle (UMIC), and high (HIC) income countries) and between different groups (i.e. gender, age, urban or rural residents).

RESULTS

From the 2259 search results, there were 140 studies that met our criteria. Overall, personal PM2.5 exposures in HICs were lower compared to other countries, with UMICs exposures being slightly lower than exposures measured in LMICs or LICs. 34% of measured groups in HICs reported below the ambient World Health Organisation 24-h PM2.5 guideline of 15 μg/m3, compared to only 1% of UMICs and 0% of LMICs and LICs. There was no difference between rural and urban participant exposures in HICs, but there were noticeably higher exposures recorded in rural areas compared to urban areas in non-HICs, due to significant household sources of PM2.5 in rural locations. In HICs, studies reported that secondhand smoke, ambient pollution infiltrating indoors, and traffic emissions were the dominant contributors to personal exposures. While, in non-HICs, household cooking and heating with biomass and coal were reported as the most important sources.

CONCLUSION

This review revealed a growing literature of personal PM2.5 exposure studies, which highlighted a large variability in exposures recorded and severe inequalities in geographical and social population subgroups.

Reliability and accuracy analysis of time-weighted average exposure to heavy metals based on personal exposure

Time-weighted average (TWA) exposure has been used as a surrogate for personal air exposure in some large-scale studies. However, the uncertainties of TWA exposure remain to be determined, although its boundedness has been widely recognized. This study aims to evaluate the reliability and accuracy of TWA exposure based on personal exposure. A total of 180 combined indoor-outdoor-personal air samples were collected of six cities during the non-heating and heating periods. The personal exposure levels of Hg, As, Cd, and Pb were 0.16, 21.20, 0.74, and 34.47 ng/m³ in the non-heating period, respectively, but were 0.20, 34.53, 3.45, and 18.59 ng/m³ in the heating period, respectively. The ratios of TWA and personal exposure of heavy metal(loid)s ranged from 0.91 to 1.53. Indoor pollution was the most significant factor of TWA exposure, accounting for 78.3-97.6% and 88.4-98.6% in the heating and non-heating period, respectively. Based on the results of redundancy analysis and risk assessment by TWA exposure, we concluded that TWA exposure could be used for qualitative investigation, as a substitute for personal exposure, but it may result in large bias when used for quantitative investigation. Larger sample size and more exposure scenarios can reduce the estimation error of TWA.

Longitudinal Associations Between Household Solid Fuel Use and Handgrip Strength in Middle-Aged and Older Chinese Individuals: The China Health and Retirement Longitudinal Study

Background

Household solid fuel have been associated with changes of handgrip strength (HGS). However, no study has explored the longitudinal associations between household solid fuel use and HGS. Thus, the aim of our cohort study was to investigate the longitudinal associations between household fuel use and HGS.

Methods

The study was based on the China Health and Retirement Longitudinal Study. A handheld dynamometer was used to measure HGS. Household fuel use statuses were collected using questionnaires. Analyses of covariance were performed to examine the associations between household fuel use and HGS.

Results

The study included 9,382 participants during a 4-year follow-up. The participants who used solid fuel for cooking had more decreases of HGS than those who used clean fuel (P < 0.0001). The least square means (95% CIs) of changes of HGS for participants who used solid fuel and those who used clean fuel for cooking were −1.67 (−2.15, −1.19) and−2.27 (−2.75, −1.79), respectively. The association between fuel use for heating and HGS was non-significant (P = 0.63). The interaction terms of sex to cooking fuel (P = 0.04) and smoking to cooking fuel (P < 0.001) were significant; men and participants who had ever smoked had higher decreases in HGS.

Conclusion

Using household solid fuel for cooking but not heating was associated with more decreases in HGS. Proper ventilation and clean fuel should be promoted for public health.

Household PM2.5 pollution in rural Chinese homes: Levels, dynamic characteristics and seasonal variations

Humans generally spend most of their time indoors, and fine particulate matter (PM_2.5) in indoor air can have seriously adverse effects on human health due to the long exposure time. This study conducted field measurements to explore seasonal variations of PM_2.5 concentrations in household air by revisiting the same rural homes in southern China and factors influencing indoor PM_2.5 concentrations were explored mainly by one-way ANOVA. The PM_2.5 concentrations of outdoor, kitchen and living room air were 38.9 ± 12.2, 47.1 ± 20.3 and 50.8 ± 24.1 μg/m³ in summer, respectively, which were 2.3 to 2.9 times lower than those in winter (p < 0.05). The lower indoor PM_2.5 pollution in summer was attributed to the transition to clean household energy and better ventilation. Fuel type can significantly affect PM_2.5 concentrations in the kitchen, with greater PM_2.5 pollution associated with wood combustion than electricity. Our study firstly found mosquito coil emission was an important contributor to PM_2.5 in the living room of rural households, which should be investigated further. Dynamic variations of PM_2.5 suggested that cooking, heating and mosquito coil emission can rapidly increase indoor PM_2.5 concentrations (up to one order of magnitude higher than baseline values), as well as the indoor/outdoor PM_2.5 ratios. This study had the first insight of seasonal differences of household PM_2.5 in the same rural homes using real-time monitors, confirming the different patterns and characteristics of household PM_2.5 pollution in different seasons.

Short-term exposure to ambient air pollution and risk of daily hospital admissions for anxiety in China: A multicity study

The potential impact of short-term exposure to ambient air pollution on risk of anxiety remains uncertain. We performed a detailed evaluation based on data from national insurance databases in China. Daily hospital admissions for anxiety disorders were identified in 2013-2017 from the national insurance databases covering up to 261 million urban residents in 56 cities in China. A two-stage time-series study was conducted to evaluate the associations between short-term exposure to major ambient air pollutants, including fine particles, inhalable particles, nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone, and carbon monoxide, and risk of daily hospital admissions for anxiety. Significant associations between short-term exposures to ambient NO₂ and SO₂ and risk of daily hospital admissions for anxiety were found in the overall analysis. Per 10 μg/m³ increases in NO₂ at lag0 and SO₂ at lag6 were associated with significant increases of 1.37% (95% CI: 0.14%, 2.62%) and 1.53% (95% CI: 0.59%, 2.48%) in anxiety admissions, respectively. Stronger associations were found in the southern region and patients <65 years for SO₂. Short-term exposure to ambient air pollution is associated with increased risk of anxiety admissions, which may provide important implications for promotion of mental health in the public.

Quantify individual variation of real-time PM2.5 exposure in urban Chinese homes based on a novel method

Fine particulate matter (PM_2.5 ) concentrations show high variations in different microenvironments indoors, which has considerable impact on risk management. However, the real-time variations of PM_2.5 exposure associated with per activity/microenvironment and intra-variation among family members remain undefined. In this study, real-time monitors were used to collect real-time PM_2.5 data in different microenvironments in 32 households in urban community of China. Peak concentrations of PM_2.5 were found in kitchen. The parallel levels of PM_2.5 household indoor and outdoor indicated the benefit of clean energies use. To validly assess the health risk of individuals, we proposed a novel method to estimate the real-time exposure of all residents and firstly investigate the intra-variation of PM_2.5 exposure among family members. The member who is responsible for cooking in the family had the maximum PM_2.5 exposure. The ratios among intraindividual variations demonstrated children usually had lower exposure compared to the adults as they stayed more time in lower polluted microenvironments such as living room and bedroom. The exposure intensity in living room was above 1.0 for most residents, indicating it is warranted to alleviate the air pollution in living room. This study firstly focused on the intra differences of PM_2.5 exposure among family members and provided a new insight for indoor air pollution management. The results suggested when adopting measures to reduce exposure, the microenvironments pattern of each member should be taken into consideration. Future work is welcomed to move another big step on this issue to protect the human health.

Substantial leakage into indoor air from on-site solid fuel combustion in chimney stoves

Exposure to household air pollution (HAP) from solid fuel use (SFU) causes millions of premature deaths globally. Direct leakage from stoves into indoor air is believed to be the main cause of severe HAP. However, previous laboratory-based measurements reported leakage of minimal fractions from wood fuel combustion. Using a newly developed measurement method, on-site measurements were conducted to quantitatively evaluate the leakage of gases and particulate matter from different fuel-stove combinations. The fraction of indoor leakage to the total emission (F) of the measured air pollutants varied from 23 ± 11% to 40 ± 16% for different pollutants and fuel-stove combinations, and these were significantly higher than previously lab-based results. Fuel differences overwhelmed stove differences in influencing F values, with higher values from biomass burning than from coal combustion. The particles had higher F values than gases. Fugitive emission rates (ERs) were log-normally distributed, and biomass burning had higher ERs than coal burning. Indoor PM_2.5 (fine particulate matter) and CO (carbon monoxide) concentrations measured during the burning period increased by nearly 1-2 orders of magnitude compared to concentrations before or after burning, confirming substantially high indoor leakage from fuel combustion in cookstoves. High fugitive emissions in indoor cookstoves quantified from the present on-site measurements effectively explain the high HAP levels observed in rural SFU households, and call for interventions to improve indoor air quality.

Characterization and exposure assessment of household fine particulate matter pollution in China

Household fine particulate matter (PM_2.5 ) pollution greatly impacts residents' health. To explore the current national situation of household PM_2.5 pollution in China, a study was conducted based on literature published from 1998 to 2018. After extracting data from the literature in conformity with the requirements, the nationwide household-weighted mean concentration of household PM_2.5 (HPL) was calculated. Subgroup analyses of spatial, geographic, and temporal differences were also done. The estimated overall HPL in China was 132.2 ± 117.7 μg/m³ . HPL in the rural area (164.3 ± 104.5 μg/m³ ) was higher than that in the urban area (123.9 ± 122.3 μg/m³ ). For HPLs of indoor sampling sites, the kitchen was the highest, followed by the bedroom and living room. There were significant differences of geographic distributions. The HPLs in the South were higher than the North in four seasons. The inhaled dose of household PM_2.5 among school-age children differed from provinces with the highest dose up to 5.9 μg/(kg·d). Countermeasures should be carried out to reduce indoor pollution and safeguard health urgently.

Influence of COVID-19 lockdown overlapping Chinese Spring Festival on household PM2.5 in rural Chinese homes

During the 2019 novel coronavirus (COVID-19) pandemic, many countries took strong lockdown policy to reduce disease spreading, resulting in mitigating the ambient air pollution due to less traffic and industrial emissions. However, limited studies focused on the household air pollution especially in rural area, the potential risk induced by indoor air pollution exposure was unknown during this period. This field study continuously measured real-time PM_2.5 levels in kitchen, living room, and outdoor in the normal days (Period-1) and the days of COVID-19 lockdown overlapping the Chinese Spring Festival (Period-2) in rural homes in China. The average daily PM_2.5 concentrations increased by 17.4 and 5.1 μg/m³ in kitchen and living room during Period-2, respectively, which may be due to more fuel consumption for cooking and heating caused by larger family sizes than those during the normal days. The ambient PM_2.5 concentration in rural areas in Period-2 decreased by 6.7 μg/m³ compared to the Period-1, less than the drop in urban areas (26.8 μg/m³). An increase of mass fraction of very fine particles in ambient air was observed during lockdown overlapping annual festival days, which could be explained by the residential solid fuel burning. Due to higher indoor air pollution level and longer time spent in indoor environments, daily personal exposure to PM_2.5 was 134 ± 40 μg/m³ in Period-2, which was significantly higher than that during in Period-1 (126 ± 27 μg/m³, p < 0.05). The increase of personal PM_2.5 exposure during Period-2 could potentially have negative impact on human health, indicating further investigations should be performed to estimate the health impact of global COVID-19 lockdown on community, especially in rural homes using solid fuels as the routine fuels.

Indoor/outdoor relationships, signatures, sources, and carcinogenic risk assessment of polycyclic aromatic hydrocarbons-enriched PM2.5 in an emerging port of northern China

Humans spend most of their time in indoor environments, thus a thorough understanding of indoor and outdoor PM_2.5-bound polycyclic aromatic hydrocarbons (PAHs) origins for accurate assessment of health risks is required. In the present study, 84 pairs of PM_2.5 samples from indoor (laboratory) and outdoor (campus) locations were collected from April to December 2018 in Caofeidian, China. The annual median concentration of PM_2.5 outdoors was 90.80 µg/m³, 9.08 times higher than the annual standard of WHO guideline (10 µg/m³). Indoor PM_2.5 annual median concentration (41.80 µg/m³) was also higher than the annual standard of ASHRAE guideline (15 µg/m³). The annual median concentrations of ∑₁₈PAHs indoors (44.23 ng/m³) and outdoors (189.6 ng/m³) were highest in winter and descended in the order of autumn > spring > summer. Contrary to summer and autumn, indoor/outdoor concentration ratios were less than 1 in spring and winter, indicating that the contribution of outdoor particle infiltration was more significant than that of indoor sources. The positive matrix factorization model suggested that indoor PAHs came from three sources: vehicle emissions (43%), biomass burning (37%), industry emissions, and coal combustion (20%). Outdoor PAHs came from four sources: petroleum volatilization (39%), vehicle emissions (30%), coal combustion (18%), and biomass burning (13%). The incremental lifetime cancer risk values of indoor and outdoor PAHs in winter exceeded the acceptable level (10^-6), and the carcinogenic risk of adults was higher than that of children and teenagers. These results indicated that simultaneous monitoring of indoor and outdoor PAHs is recommended for accurate assessment of health risk, and the analysis in the current work should be helpful to formulate policies to reduce PAHs emissions.

Impacts of Chinese spring festival on household PM2.5 pollution and blood pressure of rural residents

BACKGROUND

Household air pollution (HAP) from residential combustion considerably affects human health in rural China. Large-scale population migration and rural lifestyle changes during the Spring Festival are supposed to change the household air pollution and health risks; however, limited field study has determined its impacts on HAP and short-term health outcomes.

METHODS

A field study was conducted in rural areas of Southern China before and during the Spring Festival to explore the associations between HAP and blood pressure considering different factors such as cooking fuel, heating fuel, and smoking. Stationary real-time PM_2.5 monitors were used to measure PM_2.5 concentrations of the kitchen, living room, and yard of 156 randomly selected households. Personal exposure to PM_2.5 was calculated based on the results of stationary samplers and corresponding time local residents spent in different microenvironments, and one adult resident was recruited of each family for the blood pressure measurement.

RESULTS

Both personal exposure to PM_2.5 and blood pressures of local residents increased during Spring Festival compared to the days before the holiday. Based on generalized linear model coupled with dominance analysis approach, it was found that personal PM_2.5 exposure was positively associated with the factors of population size and the types of cooking and heating fuels with the relative contributions of approximately 82%, and systolic blood pressure (SBP, 100-120 mmHg as normal range for adults) was positively and significantly associated with personal PM_2.5 exposures with the relative contribution of 11%.

CONCLUSION

The findings in this study demonstrated that Spring Festival can give rise to increase of HAP and hypertension risks, also related to tremendous solid fuel use, suggesting further policy making on promoting cleaner energy in rural areas and more attention on large population migration during national holidays.

Temporal and spatial variation of PM2.5 in indoor air monitored by low-cost sensors

Indoor air pollution has significant adverse health impacts, but its spatiotemporal variations and source contributions are not well quantified. In this study, we used low-cost sensors to measure PM_2.5 concentrations in a typical apartment in Beijing. The measurements were conducted at 15 indoor sites and one outdoor site on 1-minute temporal resolution (convert to 10-minute averages for data analysis) from March 14 to 24, 2020. Based on these highly spatially-and temporally-resolved data, we characterized spatiotemporal variations and source contributions of indoor PM_2.5 in this apartment. It was found that indoor particulate matter predominantly originates from outdoor infiltration and cooking emissions with the latter contributing more fine particles. Indoor PM_2.5 concentrations were found to be correlated with ambient levels but were generally lower than those outdoors with an average I/O of 0.85. The predominant indoor source was cooking, leading to occasional high spikes. The variations observed in most rooms lagged behind those measured outdoors and in the studied kitchen. Differences between rooms were found to depend on pathway distances from sources. On average, outdoor sources contributed 36% of indoor PM_2.5, varying extensively over time and among rooms. From observed PM_2.5 concentrations at the indoor sites, source strengths, and pathway distances, a multivariate regression model was developed to predict spatiotemporal variations of PM_2.5. The model explains 79% of the observed variation and can be used to dynamically simulate PM_2.5 concentrations at any site indoors. The model's simplicity suggests the potential for regional-scale application for indoor air quality modeling.

Inhalation exposure to size-segregated fine particles and particulate PAHs for the population burning biomass fuels in the Eastern Tibetan Plateau area

Indoor biomass burning produces large amounts of small particles and hazardous contaminants leading to severe air pollution and potentially high health risks associated with inhalation exposure. Personal samplers provide more accurate estimates of inhalation exposure. In this study, inhalation exposure to size-segregated particles and particulate polycyclic aromatic hydrocarbons (PAHs) for the biomass user was studied by deploying personal samplers. The study found that daily PM_2.5 inhalation exposure level was as high as 121 ± 96 μg/m³, and over 84% was finer PM_1.0. For PAHs, the exposure level was 113 ± 188 ng/m³, with over 77% in PM_1.0. High molecular weight PAHs with larger toxic potentials enriched in smaller particles resulting in much high risks associated with PAHs inhalation exposure. Indoor exposure contributed to ~80% of the total inhalation exposure as a result of high indoor air pollution and longer residence spent indoor. The highest exposure risk was found for the male smoker who conducted cooking activities at home.

Longitudinal associations between household solid fuel use and depression in middle-aged and older Chinese population: A cohort study

BACKGROUND

Previous studies found that ambient air pollution was associated with a higher prevalence of depressive symptoms. However, the longitudinal associations between household solid fuel use, which is the main source of household air pollution, and depressive symptoms remain unclear. This cohort study aimed to explore the associations between household solid fuel use and incidence of depressive symptoms in China.

METHODS

In total, 8637 participants were enrolled in this prospective cohort study. Depressive symptoms were assessed using the 10-item Center for Epidemiological Studies Depression Scale. The associations between baseline household solid fuel use and the incidence of depressive symptoms were examined using Cox proportional hazards regression models.

RESULTS

During the 4-year of follow-up, 2074 of 8637 participants developed depressive symptoms. Compared with participants who used clean fuel for both heating and cooking, the multivariate-adjusted hazard ratio (HR) (95% confidence intervals [95% CI]) for depressive symptoms incidence in participants who used solid fuels for two purposes (cooking and heating) was 1.15 (1.01, 1.31). In the solid fuel use subgroup analysis, use of solid fuels for cooking (HR, 1.12; 95% CI, 1.02-1.24) was associated with a higher incidence of depressive symptoms after adjustments while use for heating (HR, 1.05; 95% CI, 0.93-1.18) was not. Moreover, compared with persistent solid fuel users, switching from solid to clean fuels for cooking resulted in a lower risk of depressive symptoms before adjustments (HR, 0.82; 95% CI, 0.71-0.95) and a non-significant association (HR, 0.90; 95% CI, 0.77-1.04) afterwards.

CONCLUSIONS

The results suggest that household solid fuel use for cooking was associated with a higher incidence of depressive symptoms. Preventive strategies based on improving household cooking environment for depressive symptoms should be established.

A novel model for regional indoor PM2.5 quantification with both external and internal contributions included

PM_2.5 (particulate matter with an aerodynamic size ≤ 2.5 μm) of indoor origins is a dominant contributor to the overall air pollution exposure. Although some sophisticated models have been developed to simulate indoor air quality for individual households, it is still challenging to quantify indoor PM_2.5 on a regional scale, which is critical for health impact assessments. In this study, a new model was developed to predict indoor PM_2.5 concentrations by quantifying the external penetration, as well as the internal contributions. The model was parameterized based on a set of simultaneously measured indoor and outdoor PM_2.5 concentrations at five-second temporal resolution for 53 households in Beijing. This study found that indoor PM_2.5 concentrations were significantly correlated with those in the outdoor environment with an approximately 1-h lag-time on average. Outdoor-to-indoor penetration dominated the contribution to indoor PM_2.5 during polluted hours with relatively high ambient PM_2.5 concentrations, while the indoor PM_2.5, during clean hours, was contributed by internal sources, including smoking, cooking, incense burning, and human disturbance. The influence of windows, house area, and air purifier use was addressed in the new model. The model was applied to evaluate indoor PM_2.5 concentrations in six urban districts of Beijing via an uncertainty analysis. The model was developed based on and applied to households using clean residential energy, and it would be interesting also important to evaluate it in households using solid fuels.

Determinants of personal exposure to fine particulate matter in the retired adults - Results of a panel study in two megacities, China

This study aimed to investigate the relationship between outdoor, indoor, and personal PM_2.5 exposure in the retired adults and explore the effects of potential determinants in two Chinese megacities. A longitudinal panel study was conducted in Nanjing (NJ) and Beijing (BJ), China, and thirty-three retired non-smoking adults aged 43-86 years were recruited in each city. Repeated measurements of outdoor-indoor-personal PM_2.5 concentrations were measured for five consecutive 24-h periods during both heating and non-heating seasons using real-time and gravimetric methods. Time-activity and household characteristics were recorded. Mixed-effects models were applied to analyze the determinants of personal PM_2.5 exposure. In total, 558 complete sets of collocated 24-h outdoor-indoor-personal PM_2.5 concentrations were collected. The median 24-h personal PM_2.5 exposure concentrations ranged from 43 to 79 μg/m³ across cities and seasons, which were significantly greater than their corresponding indoor levels (ranging from 36 to 68 μg/m³, p < 0.001), but significantly lower than outdoor levels (ranging from 43 to 95 μg/m³, p < 0.001). Indoor and outdoor PM_2.5 concentrations were the strongest determinants of personal exposures in both cities and seasons, with R_M² ranging from 0.814 to 0.915 for indoor and from 0.698 to 0.844 for outdoor PM_2.5 concentrations, respectively. The personal-outdoor regression slopes varied widely among seasons, with a pronounced effect in BJ (NHS: 0.618 ± 0.042; HS: 0.834 ± 0.023). Ventilation status, indoor PM_2.5 sources, personal characteristics, and meteorological factors, were also found to influence personal exposure levels. The city and season-specific models developed here are able to account for 89%-93% of the variance in personal PM_2.5 exposure. A LOOCV analysis showed an R² (RMSE) of 0.80-0.90 (0.21-0.36), while a 10-fold CV analysis demonstrated a R² (RMSE) of 0.83-0.90 (0.20-0.35). By incorporating potentially significant determinants of personal exposure, this modeling approach can improve the accuracy of personal PM_2.5 exposure assessment in epidemiologic studies.

Particle size dynamics and risk implication of atmospheric aerosols in South-Asian subcontinent

Presented here are size-resolved aerosol measurements conducted using cascade impactor set at breathing zone in indoor-outdoor residential microenvironments. PM_2.5 contributed about 64-80% of PM₁₀ in which over 29% of mass was shared by PM_0.25. Total PM concentration varied from 261 ± 22 μg/m³ (indoors) to 256 ± 64 μg/m³ (outdoors) annually; whilst summer and monsoon demonstrated 1.2- and 1.9- times lower concentration than winters. The measured metals ranged between 9% (in PM_2.5-10) to 18% (in PM_1-2.5) of aerosol concentration; whereby crustal elements dominated coarse fractions with relatively higher proportion of toxic elements (Ba, Cd, Co, Cr, Cu, Ni) in ultrafine range. Considering lognormal particle size distribution (PSD), accumulation mode represented the main surface area during entire monitoring period (Mass Median Aerodynamic Diameter (MMAD) < 1). PSD of metal species reflected their different emission sources with respect to season integrated samples. High air exchange conditions permitted the shift of indoor PSD pattern closer to that of outdoor air while low ventilation in winters reflected modal shift of metals (Pb, Mg. K) towards larger size particles. Relative surge towards smaller diameter size of soluble metal fraction relative to the total concentration of toxic elements was noted on an annual basis with high infiltration capacity of smaller size particulates (Finf =1.36 for ultrafine particles in summers) identified through indoor-outdoor regression analysis. Principal Component Analysis identified sources such as vehicular traffic, combustion, crustal emission with activities viz. smoking and those involving use of electric appliances.

Distribution characteristics of and personal exposure with polycyclic aromatic hydrocarbons and particulate matter in indoor and outdoor air of rural households in Northern China

Gaseous and particulate polycyclic aromatic hydrocarbons (PAHs) and size-segregated particulate matter (PM) in indoor air and outdoor air, along with personal exposure, were monitored in rural households of Northern China. The daily average concentrations of 28 species were 1310 ± 811, 738 ± 321, 465 ± 247, and 655 ± 250 ng/m³ in kitchen air, bedroom air, and outdoor air, and for personal exposure, respectively. PAHs tended to occur in the particulate phase with increasing molecular weight. Absorption by particulate organic carbon was dominant in the gas-particle partitioning process. The daily averaged concentrations of PM_2.5 and PM_1.0 were 104 ± 39.5 and 88.4 ± 39.3 μg/m³ in kitchen air, 79.0 ± 63.2 and 65.7 ± 57.5 μg/m³ in bedroom air, 52.9 ± 16.5 and 41.5 ± 12.5 μg/m³ in outdoor air, and 71.7 ± 30.8 and 61.5 ± 28.4 μg/m³ for personal exposure, respectively. The non-priority components contributed 5.5 ± 2.8% to the total PAHs, while their fraction of carcinogenic risk reached 85.6 ± 6.9%. The mean cancer risk posed to rural residents via inhalation exposure to PAHs exceeded the current acceptable threshold of 1.0 × 10^-6 and the national average estimated in China. The personal exposure levels of PAHs and PM in households using clean energy were lower than those in households using traditional biomass by 30.0%, 29.4%, and 38.5% for PAH₂₈, PM_2.5, and PM_1.0, respectively. However, the cancer risk of personal inhalation exposure to PAH₂₈ from using liquid petroleum gas (LPG) was higher than that from using firewood, implying the adoption of LPG may not effectively reduce the cancer risk despite the decreasing exposure levels of PAH₂₈ and PM with respect to the use of firewood. Cooking individuals suffered higher exposure levels of PAH₂₈ and PM_1.0 compared with non-cooking individuals, and the cancer risk of personal inhalation exposure to PAH₂₈ for cooking individuals was 1.7 times that for non-cooking individuals. Cooking was a critical factor that affected the personal exposure levels of the local male and female residents.

The impact on T-regulatory cell related immune responses in rural women exposed to polycyclic aromatic hydrocarbons (PAHs) in household air pollution in Gansu, China: A pilot investigation

Previous studies found associations between impairments of immune functions and exposure to polycyclic aromatic hydrocarbons (PAHs) in ambient air pollution in the U. S. and China. However, the results remain inconclusive due to the limitations of these studies. In this study, we aimed to examine the direction and magnitude of immune changes related to PAH exposure from household air pollution among rural women living in Gansu, China. Healthy village women (n = 34) were recruited and enrolled in the study. Questionnaires were administered. Blood and urine samples were collected and analyzed during non-heating (September 2017, "summer") and heating (January 2018, "winter") seasons. Urinary 1-hydroxypyrene (1-OHP) was quantified as the biomarker of PAH exposure. To evaluate Treg cell related immune functions, we examined immunoglobulin E (IgE), percent of T-regulatory (Treg) cells, and gene expression of following: forkhead box transcription factor 3 (Foxp3), transforming growth factor-β (TGF-β), interleukin 10 (IL-10), and interleukin 35 (IL-35), composed of interleukin-12 alpha (IL-12α) and Epstein-Barr-virus-induced gene 3 (EBi3). Urinary 8-hydroxy-2-deoxyguanosine (8-OHdG) was measured to evaluate oxidative DNA damage. The results showed that the concentration of 1-OHP increased from 0.90 to 17.4 μmol mol-Cr ^-1 from summer to winter (p < 0.001). Meanwhile, average percent of Treg cells decreased from 5.01% to 1.15% (p < 0.001); IgE and mRNA expressions of Foxp3, TGF-β, IL-10, IL-12α and EBi3 all significantly decreased (p < 0.001); Urinary 8-OHdG increased from 12.7 to 30.3 ng mg-Cr ^-1 (p < 0.001). The changes in 8-OHdG, Foxp3 and TGF-β were significantly associated with the increase of 1-OHP. The results suggested that we observed a substantial increase of PAH exposure in winter, which was significantly associated with the repression on Treg cell function and oxidative DNA damage. Exposure to PAHs in household air pollution possibly induced immune impairments among rural women in northwest China.

Personal exposure to PM2.5 in Chinese rural households in the Yangtze River Delta

High levels of PM_2.5 exposure and associated health risks are of great concern in rural China. For this study, we used portable PM_2.5 monitors for monitoring concentrations online, recorded personal time-activity patterns, and analyzed the contribution from different microenvironments in rural areas of the Yangtze River Delta, China. The daily exposure levels of rural participants were 66 μg/m³ (SD 40) in winter and 65 μg/m³ (SD 16) in summer. Indoor exposure levels were usually higher than outdoor levels. The exposure levels during cooking in rural kitchens were 140 μg/m³ (SD 116) in winter and 121 μg/m³ (SD 70) in summer, the highest in all microenvironments. Winter and summer values were 252 μg/m³ (SD 103) and 204 μg/m³ (SD 105), respectively, for rural people using biomass for fuel, much higher than those for rural people using LPG and electricity. By combining PM_2.5 concentrations and time spent in different microenvironments, we found that 92% (winter) and 85% (summer) of personal exposure to PM_2.5 in rural areas was attributable to indoor microenvironments, of which kitchens accounted for 24% and 27%, respectively. Consequently, more effective policies and measures are needed to replace biomass fuel with LPG or electricity, which would benefit the health of the rural population in China.

Vertical distributions of black carbon aerosols over rural areas of the Yangtze River Delta in winter

Based on a field campaign in Shouxian, a rural site on the Yangtze River Delta, China, from December 14, 2016 to January 4, 2017, the vertical profiles of black carbon (BC) and planetary boundary layer (PBL) structures were studied. In total, 58 vertical profiles were obtained, including of the PM_2.5, BC mass concentration (m_BC) and relevant meteorological parameters. Four profile types were categorized: I: uniform vertical distributions (38%), II: higher values at lower altitudes (29%), III: bimodal distributions with high values near the ground and at higher altitudes (17%), and IV: unimodal distributions with high values at higher altitudes (11%). A further analysis confirmed that all types were mainly influenced by the PBL diurnal evolution and local emissions, while types III and IV were strongly associated with the temperature inversions at low altitudes. The diurnal variations of the BC vertical profiles mainly followed the evolution of the PBL. In the early morning, the average m_BC within the PBL (M_{BL, BC}) increased significantly, reaching the highest level in the diurnal cycles, i.e., approximately 13.0 μg m^-3. The pollutants were confined to a thin layer <0.2 km above the ground, which contributed to the smoke produced by local residential biomass burning. Around noon, the accumulated BC in the layer was diluted as a result of the development of the PBL. The height of the PBL (H_PBL) reached its maximum in the afternoon, with an average of 0.65 km, while M_BL, _BC dropped to its minimum, with an average of 7.8 μg m^-3. As evening approached, the BC produced by local residential biomass burning gradually accumulated near the ground and linearly declined along the standardized height (H_S) within the nocturnal boundary layer (NBL). There were large differences in the BC concentration within and above the PBL both in the daytime and at night.

Population-weighted exposure to PM2.5 pollution in China: An integrated approach

Fine particulate matter air pollution (PM_2.5) is a major risk factor for premature death globally. Studies of the PM_2.5 health burden usually treat exposure to ambient air pollution (AAP) and household air pollution from solid fuels (HAP) as separate risk factors. AAP and HAP can, however, be closely interrelated. Taking as the starting point that the total exposure to PM_2.5 is what matters for health, and recognizing the curvilinear form of exposure-response functions for important health effects, we develop a method for estimating the total annual mean population-weighted personal exposure, denoted integrated population-weighted exposure (IPWE). To establish the IPWE in China, we used recent emission inventories, Chemical Transport Models, China Census data on population and residential fuel use, and estimates of the PM_2.5 exposure among solid fuel users. We found an IPWE of 151 [123-179] μg/m³, of which 62-74% was attributable to residential solid fuels through HAP exposure and the residential sector emissions' contribution to AAP. We found large disparities in the PM_2.5 exposure burden, with an estimated IPWE in rural populations nearly twice the level in urban populations. Using the IPWE metric, we estimated that 1.15 [1.09-1.19] million premature deaths were attributable to PM_2.5 exposure annually in the period 2010-2013. Using the same data set, but calculating premature deaths from AAP and HAP in isolation, the estimated number was nearly 50% higher. The IPWE metric enables integration across AAP and HAP in policy analyses and could mitigate the concern of a potential double counting of the health burden that may arise from treating AAP and HAP as separate health risk factors.

Impacts of stove use patterns and outdoor air quality on household air pollution and cardiovascular mortality in southwestern China

BACKGROUND

Decades of intervention programs that replaced traditional biomass stoves with cleaner-burning technologies have failed to meet the World Health Organization (WHO) interim indoor air quality target of 35-μg m-3 for PM2.5. Many attribute these results to continued use of biomass stoves and poor outdoor air quality, though the relative impacts of these factors have not been empirically quantified.

METHODS

We measured 496 days of real-time stove use concurrently with outdoor and indoor air pollution (PM2.5) in 150 rural households in Sichuan, China. The impacts of stove use patterns and outdoor air quality on indoor PM2.5 were quantified. We also estimated the potential avoided cardiovascular mortality in southwestern China associated with transition from traditional to clean fuel stoves using established exposure-response relationships.

RESULTS

Mean daily indoor PM2.5 was highest in homes using both wood and clean fuel stoves (122 μg m-3), followed by exclusive use of wood stoves (106 μg m-3) and clean fuel stoves (semi-gasifiers: 65 μg m-3; gas or electric: 55 μg m-3). Wood stoves emitted proportionally higher indoor PM2.5 during ignition, and longer stove use was not associated with higher indoor PM2.5. Only 24% of days with exclusive use of clean fuel stoves met the WHO indoor air quality target, though this fraction rose to 73% after subtracting the outdoor PM2.5 contribution. Reduced PM2.5 exposure through exclusive use of gas or electric stoves was estimated to prevent 48,000 yearly premature deaths in southwestern China, with greater reductions if local outdoor PM2.5 is also reduced.

CONCLUSIONS

Clean stove and fuel interventions are not likely to reduce indoor PM2.5 to the WHO target unless their use is exclusive and outdoor air pollution is sufficiently low, but may still offer some cardiovascular benefits.

Household air pollution and personal exposure to air pollutants in rural China - A review

Solid fuels, an important source of severe Household Air Pollution (HAP) linked to many adverse health outcomes, has been widely consumed around the world. China consumes large amounts of solid fuels and suffers from serious indoor and outdoor air pollution. Though global HAP issues had been reviewed in previous literatures, peer-reviewed Chinese publications were seldom included in those reviews. We conducted a literature review on the studies of HAP and personal exposure in rural China with inputs from peer-reviewed publications in both English and Chinese. A total of 36,572 articles were retrieved, 294 were read in full text, of which 92 were included in final data extraction and in-depth analysis. Although HAP is a very serious issue in China, studies on either HAP or personal exposure assessment were very limited. From existing studies, levels of air pollutants including carbon monoxide, sulfur dioxide, particulate matter (PM), organic carbon, elemental carbon, polycyclic aromatic hydrocarbons (PAHs), etc., in indoor and ambient air were analyzed for their temporal and spatial variations, and the differences across different fuel types were compared. The studies showed that PM and PAHs levels in most rural homes exceeded the World Health Organization (WHO) and Chinese National Standards, especially during the heating season in northern China. Replacing traditional fuels with cleaner ones (such as liquid petroleum gas (LPG), biogas or electricity) was considered as the most appropriate way to mitigate HAP. The daily exposure to PM and PAHs from using LPG, biogas or electricity was considerably lower than that from using traditional solid fuels. However, the level was still higher than the guideline values for PM and PAHs set by WHO to protect human health. To achieve a more effective control, the current data gap need to be closed and suggestions for future research were discussed in this review.

Household air pollution and personal inhalation exposure to particles (TSP/PM2.5/PM1.0/PM0.25) in rural Shanxi, North China

Personal exposure to size-segregated particles among rural residents in Shanxi, China in summer, 2011 were investigated using portable carried samplers (N = 84). Household air pollution was simultaneously studied using stationary samplers in nine homes. Information on household fuel types, cooking activity, smoking behavior, kitchen ventilation conditions etc., were also collected and discussed. The study found that even in the summer period, the daily average concentrations of PM_2.5 and PM_1.0 in the kitchen were as high as 376 ± 573 and 288 ± 397 μg/m³ (N = 6), that were nearly 3 times of 114 ± 81 and 97 ± 77 μg/m³ in the bedroom (N = 8), and significantly higher than those of 64 ± 28 and 47 ± 21 μg/m³ in the outdoor air (N = 6). The personal daily exposure to PM_2.5 and PM_1.0 were 98 ± 52 and 77 ± 47 μg/m³, respectively, that were lower than the concentrations in the kitchen but higher than the outdoor levels. The mass fractions of PM_2.5 in TSP were 90%, 72%, 65% and 68% on average in the kitchen, bedroom, outdoor air and personal inhalation exposure, respectively, and moreover, a majority of particles in PM_2.5 had diameters less than 1.0 μm. Calculated time-weighted average exposure based on indoor and outdoor air concentrations and time spent indoor and outdoor were positively correlated but, was ∼33% lower than the directly measured exposure. The daily exposure among those burning traditional solid fuels could be lower by ∼41% if the kitchen was equipped with an outdoor chimney, but was still 8-14% higher than those household using cleaning energies, like electricity and gas. With a ventilator in the kitchen, the exposure among the population using clean energies could be further reduced by 10-24%.