Fuel Use Trends for Boiling Water in Rural China (1992-2012) and Environmental Health Implications: A National Cross-Sectional Study

Household energy stacking and structures in Pakistan - Results from a multiple-energy study in Azad Kashmir and Punjab

Solid fuel use (SFU) is common in most developing countries and would release many hazardous air pollutants posing high risks on human health. The Global Burden of Disease (GBD) study highlighted risks associated with household SFU in Pakistan, however, high uncertainties prevail because of scanty data on SFU and unaccounted energy stacking. This study conducted a field campaign aiming at collecting first-hand data on household energy mix in Pakistan. The first survey was in Punjab and Azad Kashmir, and revealed that stacked energy use was pervasive, especially for cooking. The stacking was found to be much more obvious in SFU households (defined as those using SFU dominantly) compared to those non-SFU. There were significantly substantial differences between Azad Kashmir and Punjab because of distinct resources available and economic conditions. Woody materials comprised up to nearly 70% in Azad Kashmir, but in Punjab, gas was frequently used for cooking. Only investigating primary household energy would probably overestimate main energy types that being used for a longer time but underestimated other supplements, suggesting the preference of multiple-energy surveys in household energy studies.

Drinking Water in Rural China: Water Sources, Treatment, and Boiling Energy

Access to safe drinking water is a major public concern in China. A national survey of 57 029 households was conducted to fill major knowledge gaps on drinking water sources, end-of-use treatment methods, and energy used to boil water. Herein, we show that surface water and well water were frequently used by >147 million rural residents living in low-income inland and mountainous areas. Driven by socioeconomic development and government intervention, the level of access to tap water in rural China increased to 70% by 2017. Nevertheless, the rate was considerably lower than that in cities and unevenly distributed across the country. Approximately 90% of drinking water was boiled, an increase from 85% a decade ago. The contribution of electricity, mainly electric kettles, to the boiling of water was 69%. Similar to cooking, living conditions and heating requirements are the main influencing indicators of energy used to boil water. In addition to socioeconomic development, government intervention is a key factor driving the transition to safe water sources, universal access to tap water, and clean energy. Further improvement in drinking water safety in poor and remote rural areas remains challenging, and more intervention and more investment are needed.

Source identification and ecological risks of parent and substituted polycyclic aromatic hydrocarbons in river surface sediment-pore water systems: Effects of multiple factors

Substituted polycyclic aromatic hydrocarbons (SPAHs) have shown higher health and ecological risks than the corresponding parent PAHs (PPAHs) from laboratory studies, their variations in freshwater system, especially in surface sediment and pore water, remain inadequate understanding. In this study, we revealed the coexistence, ecological risk, and multiple factors affecting variations and sources of PPAHs and SPAHs (nitrated PAHs (NPAHs), oxygenated PAHs (OPAHs)) in the surface sediment-pore water system from a typical urban river in Northern China. The concentration ranges of Σ₂₆PPAHs, Σ₁₀NPAHs, and Σ₄OPAHs in the surface sediments were 153.0-5367.4, not detected (N.D.)-105.4, and 42.2-1177.0 ng·g^-1 dry weight, and fell within 0.6-38.8, N.D.-297.9, and N.D.-212.6 ng·mL^-1 in the pore waters. The t-distributed stochastic neighbor embedding (SNE) coupled with the partitioning around medoids (PAM) elucidated spatiotemporal the variations in PAHs, emphasizing the impacts of industrial activities and sewage discharges. Besides the geochemical and hydrochemical conditions, SPAHs were affected by the potential secondary formation, especially during the wet season. The method comparisons indicated the advantages of principal component analysis-multivariate linear regression (PCA-MLR) and n-alkanes model on source identification. PAHs mainly originated from fossil fuel combustion and vehicular exhaust. The top risk quotient (RQ) values for PAHs occurred in the urban and industrial sections. A majority of the surface sediment samples emerged with low to moderate exposure risks, while all the pore water samples showed high exposure risks. The RQs of OPAHs were significantly higher (p < 0.01) than those of PPAHs. The results suggested the secondary formation of SPAHs as an important role in ecological risks of PAHs in the urban river system.

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.

Regional Policies Targeting Residential Solid Fuel and Agricultural Emissions Can Improve Air Quality and Public Health in the Greater Bay Area and Across China

Air pollution exposure is a leading public health problem in China. The majority of the total air pollution disease burden is from fine particulate matter (PM2.5) exposure, with smaller contributions from ozone (O3) exposure. Recent emission reductions have reduced PM2.5 exposure. However, levels of exposure and the associated risk remain high, some pollutant emissions have increased, and some sectors lack effective emission control measures. We quantified the potential impacts of relevant policy scenarios on ambient air quality and public health across China. We show that PM2.5 exposure inside the Greater Bay Area (GBA) is strongly controlled by emissions outside the GBA. We find that reductions in residential solid fuel use and agricultural fertilizer emissions result in the greatest reductions in PM2.5 exposure and the largest health benefits. A 50% transition from residential solid fuel use to liquefied petroleum gas outside the GBA reduced PM2.5 exposure by 15% in China and 3% within the GBA, and avoided 191,400 premature deaths each year across China. Reducing agricultural fertilizer emissions of ammonia by 30% outside the GBA reduced PM2.5 exposure by 4% in China and 3% in the GBA, avoiding 56,500 annual premature deaths across China. Our simulations suggest that reducing residential solid fuel or industrial emissions will reduce both PM2.5 and O3 exposure, whereas other policies may increase O3 exposure. Improving particulate air quality inside the GBA will require consideration of residential solid fuel and agricultural sectors, which currently lack targeted policies, and regional cooperation both inside and outside the GBA.

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.

Spatial and Temporal Distributions and Sources of Anthropogenic NMVOCs in the Atmosphere of China: A Review

As the key precursors of O₃, anthropogenic non-methane volatile organic compounds (NMVOCs) have been studied intensively. This paper performed a meta-analysis on the spatial and temporal variations of NMVOCs, their roles in photochemical reactions, and their sources in China, based on published research. The results showed that both non-methane hydrocarbons (NMHCs) and oxygenated VOCs (OVOCs) in China have higher mixing ratios in the eastern developed cities compared to those in the central and western areas. Alkanes are the most abundant NMHCs species in all reported sites while formaldehyde is the most abundant among the OVOCs. OVOCs have the highest mixing ratios in summer and the lowest in winter, which is opposite to NMHCs. Among all NMVOCs, the top eight species account for 50%-70% of the total ozone formation potential (OFP) with different compositions and contributions in different areas. In devolved regions, OFP-NMHCs are the highest in winter while OFP-OVOCs are the highest in summer. Based on positive matrix factorization (PMF) analysis, vehicle exhaust, industrial emissions, and solvent usage in China are the main sources for NMHCs. However, the emission trend analysis showed that solvent usage and industrial emissions will exceed vehicle exhaust and become the two major sources of NMVOCs in near future. Based on the meta-analysis conducted in this work, we believe that the spatio-temporal variations and oxidation mechanisms of atmospheric OVOCs, as well as generating a higher spatial resolution of emission inventories of NMVOCs represent an area for future studies on NMVOCs in China.

Boiled or Bottled: Regional and Seasonal Exposures to Drinking Water Contamination and Household Air Pollution in Rural China

BACKGROUND

Inadequate access to safe drinking water remains a global health problem, particularly in rural areas. Boiling is the most commonly used form of point-of-use household water treatment (HWT) globally, although the use of bottled water in low- and middle-income countries (LMICs) is increasing rapidly.

OBJECTIVES

We assessed the regional and seasonal prevalence of HWT practices (including bottled water use) in low-income rural areas in two Chinese provinces, evaluated the microbiological safety of drinking water and associated health outcomes, and estimated the air pollution burden associated with the use of solid fuels for boiling.

METHODS

We conducted cross-sectional surveys and collected drinking water samples from 1,033 rural households in Guangxi and Henan provinces. Temperature sensors affixed to pots and electric kettles were used to corroborate self-reported boiling frequencies and durations, which were used to model household air pollution (HAP) in terms of estimated particulate matter ≤ 2.5 μ m in aerodynamic diameter (PM 2.5 ) concentrations.

RESULTS

Based on summer data collection in both provinces, after controlling for covariates, boiling with electric kettles was associated with the largest log reduction in thermotolerant coliforms (TTCs) (- 0.66 log 10 TTC most probable number/ 100 mL ), followed by boiling with pots (- 0.58 ), and bottled water use (- 0.39 ); all were statistically significant (p < 0.001 ). Boiling with electric kettles was associated with a reduced risk of TTC contamination [risk ratio ( RR ) = 0.25 , p < 0.001 ] and reported diarrhea (RR = 0.80 , p = 0.672 ). TTCs were detected in 51% (n = 136 ) of bottled water samples. For households boiling with biomass, modeled PM 2.5 concentrations averaged 79   μ g / m 3 (standard deviation = 21 ).

DISCUSSION

Our findings suggest that where boiling is already common and electricity access is widespread, the promotion of electricity-based boiling may represent a pragmatic stop-gap means of expanding safe water access until centralized, or decentralized, treated drinking water is available; displacing biomass use for water boiling could also reduce HAP concentrations and exposures. Our results also highlight the risks of increasing bottled water use in rural areas, and its potential to displace other sources of safe drinking water, which could in turn hamper efforts in China and other LMICs toward universal and affordable safe water access. https://doi.org/10.1289/EHP7124.

Using the Machine Learning Method to Study the Environmental Footprints Embodied in Chinese Diet

The food system profoundly affects the sustainable development of the environment and resources. Numerous studies have shown that the food consumption patterns of Chinese residents will bring certain pressure to the environment. Food consumption patterns have individual differences. Therefore, reducing the pressure of food consumption patterns on the environment requires the precise positioning of people with high consumption tendencies. Based on the related concepts of the machine learning method, this paper designs an identification method of the population with a high environmental footprint by using a decision tree as the core and realizes the automatic identification of a large number of users. By using the microdata provided by CHNS(the China Health and Nutrition Survey), we study the relationship between residents’ dietary intake and environmental resource consumption. First, we find that the impact of residents’ food system on the environment shows a certain logistic normal distribution trend. Then, through the decision tree algorithm, we find that four demographic characteristics of gender, income level, education level, and region have the greatest impact on residents’ environmental footprint, where the consumption trends of different characteristics are also significantly different. At the same time, we also use the decision tree to identify the population characteristics with high consumption tendency. This method can effectively improve the identification coverage and accuracy rate and promotes the improvement of residents’ food consumption patterns.