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

Household air pollution and attributable burden of disease in rural China: A literature review and a modelling study

Household air pollution prevails in rural residences across China, yet a comprehensive nationwide comprehending of pollution levels and the attributable disease burdens remains lacking. This study conducted a systematic review focusing on elucidating the indoor concentrations of prevalent household air pollutants-specifically, PM2.5, PAHs, CO, SO2, and formaldehyde-in rural Chinese households. Subsequently, the premature deaths and economic losses attributable to household air pollution among the rural population of China were quantified through dose-response relationships and the value of statistical life. The findings reveal that rural indoor air pollution levels frequently exceed China's national standards, exhibiting notable spatial disparities. The estimated annual premature mortality attributable to household air pollution in rural China amounts to 966 thousand (95% CI: 714-1226) deaths between 2000 and 2022, representing approximately 22.2% (95% CI: 16.4%-28.1%) of total mortality among rural Chinese residents. Furthermore, the economic toll associated with these premature deaths is estimated at 486 billion CNY (95% CI: 358-616) per annum, constituting 0.92% (95% CI: 0.68%-1.16%) of China's GDP. The findings quantitatively demonstrate the substantial disease burden attributable to household air pollution in rural China, which highlights the pressing imperative for targeted, region-specific interventions to ameliorate this pressing public health concern.

Experimental evaluation of the impact of ventilation on cooking-generated fine particulate matter in a Chinese apartment kitchen and adjacent room

Cooking is one of the major contributors to indoor pollution. Fine particulate matter (PM2.5) produced during cooking commonly mix into adjacent rooms and elevates indoor PM2.5 concentrations. The risk of human exposure to cooking-generated PM2.5 is mainly related to the exposure duration and particulate matter (PM) concentration. The PM2.5 concentration is influenced by cooking methods and ventilation patterns. Range hoods and open windows are conventional strategies for lowering the concentration of cooking-generated particles. To decrease PM emissions, kitchen air supply systems have been proposed, providing alternative possibilities for kitchen ventilation patterns. The effects of cooking methods, air supply systems, range hoods, and windows on PM2.5 concentrations must be analyzed and compared. To understand and provide advice on reducing exposure to PM2.5 due to cooking activities, we measured the PM2.5 mass concentration in a kitchen and adjacent room during cooking. The identified factors, including cooking method, range hood use, window status, and air supply system, were varied based on orthogonal design. The delay time between the PM2.5 peak in the kitchen and that in the adjacent room was determined. The degree of exposure risk for cooking-generated PM2.5 was evaluated using the mean exposure dose. The results indicated that the mean PM2.5 mass concentration in the kitchen ranged from 22 to 2296 μg/m3. In descending order, the factors affecting the indoor PM2.5 concentration in the apartment studied were range hood use, cooking methods, window status, and air supply system. The PM2.5 peak in the adjacent room occurred 200-800 s later than that in the kitchen. Other conditions being constant in these experiments, the use of range hoods, air supply systems, and windows reduce exposure doses by 90%, 37%, and 51%, respectively. These research results provide insights for reducing human exposure to cooking-generated PM2.5.

Systematically quantifying the dynamic characteristics of PM2.5 in multiple indoor environments in a plateau city: Implication for internal contribution

People generally spend most of their time indoors, making a comprehensive evaluation of air pollution characteristics in various indoor microenvironments of great significance for accurate exposure estimation. In this study, field measurements were conducted in Kunming City, Southwest China, using real-time PM2.5 sensors to characterize indoor PM2.5 in ten different microenvironments including three restaurants, four public places, and three household settings. Results showed that the daily average PM2.5 concentrations in restaurants, public spaces, and households were 78.4 ± 24.3, 20.1 ± 6.6, and 18.0 ± 4.3 µg/m3, respectively. The highest levels of indoor PM2.5 in restaurants were owing to strong internal emissions from cooking activities. Dynamic changes showed that indoor PM2.5 levels increased during business time in restaurants and public places, and cooking time in residential kitchens. Compared with public places, restaurants generally exhibit more rapid increases in indoor PM2.5 due to cooking activities, which can elevate indoor PM2.5 to high levels (5.1 times higher than the baseline) in a short time. Furthermore, indoor PM2.5 in restaurants were dominated by internal emissions, while outdoor penetration contributed mostly to indoor PM2.5 in public places and household settings. Results from this study revealed large variations in indoor PM2.5 in different microenvironments, and suggested site-specific measures for indoor PM2.5 pollution alleviation.

Interpreting Highly Variable Indoor PM2.5 in Rural North China Using Machine Learning

Household air pollution associated with solid fuel use is a long-standing public concern. The global population mainly using solid fuels for cooking remains large. Besides cooking, large amounts of coal and biomass fuels are burned for space heating during cold seasons in many regions. In this study, a wintertime multiple-region field campaign was carried out in north China to evaluate indoor PM2.5 variations. With hourly resolved data from ∼1600 households, key influencing factors of indoor PM2.5 were identified from a machine learning approach, and a random forest regression (RFR) model was further developed to quantitatively assess the impacts of household energy transition on indoor PM2.5. The indoor PM2.5 concentration averaged at 120 μg/m3 but ranged from 16 to ∼400 μg/m3. Indoor PM2.5 was ∼60% lower in families using clean heating approaches compared to those burning traditional coal or biomass fuels. The RFR model had a good performance (R2 = 0.85), and the interpretation was consistent with the field observation. A transition to clean coals or biomass pellets can reduce indoor PM2.5 by 20%, and further switching to clean modern energies would reduce it an additional 30%, suggesting many significant benefits in promoting clean transitions in household heating activities.

Impacts of household PM2.5 pollution on blood pressure of rural residents: Implication for clean energy transition

High blood pressure associated with PM_2.5 exposure is of great concern, especially for rural residents exposed to high PM_2.5 levels. However, the impact of short-term exposure to high PM_2.5 on blood pressure (BP) has not been well elucidated. Thus, this study aims to focus on the association between short-term PM_2.5 exposure with BP of rural residents and its variation between summer and winter. Our results showed that the summertime PM_2.5 exposure concentration was 49.3 ± 20.6 μg/m³, among which, mosquito coil users had 1.5-folds higher PM_2.5 exposure than non-mosquito coil users (63.6 ± 21.7 vs 43.0 ± 16.7 μg/m³, p < 0.05). The mean systolic and diastolic BP (SBP and DBP, respectively) of rural participants were 122 ± 18.2 and 76.2 ± 11.2 mmHg in summer, respectively. The PM_2.5 exposure, SBP, and DBP in summer were 70.7 μg/m³, 9.0 mmHg, and 2.8 mmHg lower than that in winter, respectively. Furthermore, the correlation between PM_2.5 exposure and SBP was stronger in winter than that in summer, possibly due to higher PM_2.5 exposure levels in winter. The transition of household energy from solid fuels in winter to clean fuels in summer would be benefit to the decline of PM_2.5 exposure as well as BP. Results from this study suggested that the reduction of PM_2.5 exposure would have positive effect on human health.

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.

Impact of differential occupational LPG exposure on cardiopulmonary indices, liver function, and oxidative stress in Northwestern city of Nigeria

Exposure to hydrocarbon products has been associated with numerous health risks and toxicities. Outdoor or indoor occupational exposure to highly volatile and lipid-soluble hydrocarbons has been linked to impairment of respiratory, cardiovascular, and liver functions. This study is aimed at determining the potential impact of occupational exposure to liquefied petroleum gas (LPG) in varying work environments. Respiratory symptoms, oxidative stress, cardio-pulmonary, and liver function parameters were assessed among LPG workers in the Kano metropolis, Nigeria. Study subjects were recruited from LPG filling stations and street LPG retail shops. Results of the study showed that the forced vital capacity (FVC) of LPG station workers was significantly lower (2.81 L/min; H = 22.473, p < 0.001) relative to the values recorded among LPG retail shop workers and the controls (3.54 L/min and 4.24 L/min respectively). A similar reduction was seen in the forced expiratory volume in the first second (FEV₁) and the forced expiratory flow in 25-75 % of forced vital capacity (FEF_25-75) obtained from the filling station workers (H = 32.722, p < 0.001 & H = 15.655, p <0.001 respectively). Furthermore, exposure to non-combusted LPG increased systolic blood pressure, mean arterial pressure, and serum liver enzymes. Findings from this study revealed that despite the high amount of coarse particulate matter in LPG retail shops, the filling station workers are more susceptible to the impairment of lung function possibly due to the high quantity of total volatile organic compounds (TVOCs) in the filling station environment.

Assessment of Indoor Levels of Carbon Monoxide Emission from Smoldering Mosquito Coils Used in Nigeria

Mosquito coils are commonly burnt in indoor environments to drive away mosquitoes which are vectors for malaria parasites. The levels of carbon monoxide (CO) emitted and human health implications during smoldering of 5 different brands of mosquito coils commonly used in Nigeria were investigated in 4 microenvironments of different sizes. The experiments were done by taking a scenario of a sleeping arrangement and the farthest distance between the coil burning and an arbitrary bed position in 4 different bedrooms of different sizes in poor ventilation condition of closed doors and windows. With monitoring device, ALTAIR 5X portable gas analyzer, at the position of the bed, measurements were taking at 2 minutes interval from start to the end of burning of each coil. The emission profile was determined by making concentration-time plots of CO emission to determine its levels from the burning of each brand of the mosquito coils in each microenvironment. From the emission profile, coils A, C, and D showed that CO levels exceeded Nigeria's Federal Ministry of Environment (FMEnv) and the World Health Organization (WHO) statutory limit of 9.0 ppm for indoor environments in each of the microenvironments between 3 and 7 hours after the burning commenced. It was concluded that the CO concentrations from smoldering mosquito coils is a function of the size of the microenvironment in which it is used. It was recommended that the size of a microenvironment be determined for consumption of a mosquito coil before it is released into the market.