Indoor exposure to polycyclic aromatic hydrocarbons associated with solid fuel use in rural China.

Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental contaminants associated with various health risks including lung cancer. Indoor exposure to PAHs, particularly from the indoor burning of fuels, is significant; however, long-term large-scale assessments of indoor PAHs are hampered by high costs and time-consuming in field sampling and laboratory experiments. A simple fuel-based approach and statistical regression models were developed as a trial to predict indoor BaP, as a typical PAH, in China, and consequently spatiotemporal variations in indoor BaP and indoor exposure contributions were discussed. The results show that the national population-weighted indoor BaP concentration has decreased substantially from 46.1 ng/m3 in 1992 to 6.60 ng/m3 in 2017, primarily due to the increased use of clean energies for cooking and heating. Indoor BaP exposure contributed to > 70% of the total inhalation exposure in most cities, particularly in regions where solid fuels are widely utilized. With limited experimental observation data in building statistical models, quantitative results of the study are associated with high uncertainties; however, the study undoubtedly supports effective countermeasures on indoor PAHs from solid fuel use and the importance of promoting clean household energy usage to improve household air quality.

Trends in air pollutants emissions in the Qinghai-Tibet Plateau and its surrounding areas under different socioeconomic scenarios.

The Qinghai-Tibetan Plateau (QTP) and its surrounding areas are undergoing rapid changes in socioeconomic conditions, activity sectors, and emission levels. These changes underscore the significance of conducting local environmental assessments in the future and generating air pollutant emission forecasts necessary for effective evaluation. Current pollutants emissions pathways exhibit regional limitation since their based historical inventory could not accurately reflect the emission characteristics in QTP. This study constructed a high spatial resolution (0.1° × 0.1°) atmospheric pollutant emissions dataset in the Qinghai-Tibet Plateau and its surrounding Areas (QTPA) based on updated emission inventory and various socioeconomic scenarios. We found that the pollutant emissions levels are distinct among different social development scenarios, with SSP3-7.0 demonstrating the highest magnitude of emissions. Regional and sectoral contributions exhibit substantial variations. Notably, solid fuel combustion originating from residential sectors in Northeast India and open fires in Myanmar are identified as high-density sources of PM2.5 emissions. Current pollutant emission patterns in the QTPA are more akin to SSP2-4.5, however, specific regions such as Qinghai and Tibet have exhibited more pronounced trends of emission reduction. The comparison with previous datasets reveals that the predicted pollutant emissions in this study are lower than Scenario Model Intercomparison Project (SMIP) dataset but higher than Asian-Pacific Integrated Model (AIM) dataset due to the revised inventory data and model variations, in which the latter might be the main obstacle to accurate emissions prediction.

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.

Identification of Factors Determining Household PM2.5 Variations at Regional Scale and Their Implications for Pollution Mitigation.

Indoor PM2.5, particulate matter no more than 2.5 µm in aerodynamic equivalent diameter, has very high spatiotemporal variabilities; and exploring the key factors influencing the variabilities is critical for purifying air and protecting human health. Here, we conducted a longer-term field monitoring campaign using low-cost sensors and evaluated inter- and intra-household PM2.5 variations in rural areas where energy or stove stacking is common. Household PM2.5 varied largely across different homes but also within households. Using generalized linear models and dominance analysis, we estimated that outdoor PM2.5 explained 19% of the intrahousehold variation in indoor daily PM2.5, whereas factors like the outdoor temperature and indoor-outdoor temperature difference that was associated with energy use directly or indirectly, explained 26% of the temporal variation. Inter-household variation was lower than intrahousehold variation. The inter-household variation was strongly associated with distinct internal sources, with energy-use-associated factors explaining 35% of the variation. The statistical source apportionment model estimated that solid fuel burning for heating contributed an average of 31%-55% of PM2.5 annually, whereas the contribution of sources originating from the outdoors was ≤10%. By replacing raw biomass or coal with biomass pellets in gasifier burners for heating, indoor PM2.5 could be significantly reduced and indoor temperature substantially increased, providing thermal comforts in addition to improved air quality.

Divergent Energy-Climate Nexus in the Global Fuel Combustion Processes.

Fuel combustion provides basic energy for the society but also produces CO2 and incomplete combustion products that threaten human survival, climate change, and global sustainability. A variety of fuels burned in different facilities expectedly have distinct impacts on climate, which remains to be quantitatively assessed. This study uses updated emission inventories and an earth system model to evaluate absolute and relative contributions in combustion emission-associated climate forcing by fuels, sectors, and regions. We showed that, from 1970 to 2014, coal burned in the energy sector and oil used in the transportation sector contributed comparable energies consumed (24 and 20% of the total) but had distinct climate forcing (1 and 40%, respectively). Globally, coal burned for energy production had negative impacts on climate forcing but positive effects in the residential sector. In many developing countries, coal combustion in the energy sector had negative radiative forcing (RF) per unit energy consumed due to insufficient controls on sulfur and scattering aerosol levels, but oils in the transportation sector had high positive RF values. These results had important implications on the energy transition and emission reduction actions in response to climate change. Distinct climate efficiencies of energies and the spatial heterogeneity implied differentiated energy utilization strategies and pollution control policies by region and sector.

Reduced inequality in ambient and household PM2.5 exposure in China.

The society has high concerns on the inequality that people are disproportionately exposed to ambient air pollution, but with more time spent indoors, the disparity in the total exposure considering both indoor and outdoor exposure has not been explored; and with the socioeconomical development and efforts in fighting against air pollution, it is unknown how the exposure inequality changed over time. Based on the city-level panel data, this study revealed the Concentration Index (C) in ambient PM2.5 exposure inequality was positive, indicating the low-income group exposed to lower ambient PM2.5; however, the total PM2.5 exposure was negatively correlated with the income, showing a negative C value. The low-income population exposed to high PM2.5 associated with larger contributions of indoor exposure from the residential emissions. The total PM2.5 exposure caused 1.13 (0.63-1.73) million premature deaths in 2019, with only 14 % were high-income population. The toughest-ever air pollution countermeasures have reduced ambient PM2.5 exposures effectively that, however, benefited the rich population more than the others. The transition to clean household energy sources significantly affected on indoor air quality improvements, as well as alleviation of ambient air pollution, resulting in notable reductions of the total PM2.5 exposure and especially benefiting the low-income groups. The negative C values decreased from 2000 to 2019, indicating a significantly reducing trend in the total PM2.5 exposure inequality over time.

Impacts of Household Coal Combustion on Indoor Ultrafine Particles-A Preliminary Case Study and Implication on Exposure Reduction.

Ultrafine particles (UFPs) significantly affect human health and climate. UFPs can be produced largely from the incomplete burning of solid fuels in stoves; however, indoor UFPs are less studied compared to outdoor UFPs, especially in coal-combustion homes. In this study, indoor and outdoor UFP concentrations were measured simultaneously by using a portable instrument, and internal and outdoor source contributions to indoor UFPs were estimated using a statistical approach based on highly temporally resolved data. The total concentrations of indoor UFPs in a rural household with the presence of coal burning were as high as 1.64 × 105 (1.32 × 105-2.09 × 105 as interquartile range) #/cm3, which was nearly one order of magnitude higher than that of outdoor UFPs. Indoor UFPs were unimodal, with the greatest abundance of particles in the size range of 31.6-100 nm. The indoor-to-outdoor ratio of UFPs in a rural household was about 6.4 (2.7-16.0), while it was 0.89 (0.88-0.91) in a home without strong internal sources. A dynamic process illustrated that the particle number concentration increased by ~5 times during the coal ignition period. Indoor coal combustion made up to over 80% of indoor UFPs, while in an urban home without coal combustion sources indoors, the outdoor sources may contribute to nearly 90% of indoor UFPs. A high number concentration and a greater number of finer particles in homes with the presence of coal combustion indicated serious health hazards associated with UFP exposure and the necessity for future controls on indoor UFPs.

Attributed radiative forcing of air pollutants from biomass and fossil burning emissions.

Energy is vital to human society but significantly contributes to the deterioration of environmental quality and the global issue of climate change. Biomass and fossil fuels are important energy sources but have distinct pollutant emission characteristics during the burning process. This study aimed at attributing radiative forcing of climate forcers, including greenhouse gases but also short-lived climate pollutants, from the burning of fossil and biomass fuels, and the spatiotemporal characteristics. We found that air pollutant emissions from the burning process of biofuel and fossil fuels induced RFs of 68.2 ± 36.8 mW m-2 and 840 ± 225 mW m-2, respectively. The relatively contribution of biomass burning emissions was 7.6% of that from both fossil and biofuel combustion processes, while its contribution in energy supply was 11%. These relative contributions varied obviously across different regions. The per unit energy consumption of biomass fuel in the developed regions, such as North America (0.57 ± 0.33 mW m-2/107TJ) and Western Europe (0.98 ± 0.79 mW m-2/107TJ), had higher impacts of combustion emission related RFs compared to that of developing regions, like China (0.40 ± 0.26 mW m-2/107TJ), and South and South-East Asia (0.31 ± 0.71 mW m-2/107TJ) where low efficiency biomass burning in residential sector produced significant amounts of organic matter that had a cooling effect. Note that the study only evaluated fuel combustion emission related RFs, and those associated with the production of fuels and land use change should be studied later in promoting a comprehensive understanding on the climate impacts of biomass utilization.

Contributions of internal emissions to peaks and incremental indoor PM2.5 in rural coal use households.

Indoor air quality is critically important to the human as people spend most time indoors. Indoor PM2.5 is related to the outdoor levels, but more directly influenced by internal sources. Severe household air pollution from solid fuel use has been recognized as one major risk for human health especailly in rural area, however, the issue is significantly overlooked in most national air quality controls and intervention policies. Here, by using low-cost sensors, indoor PM2.5 in rural homes burning coals was monitored for ~4 months and analyzed for its temporal dynamics, distributions, relationship with outdoor PM2.5, and quantitative contributions of internal sources. A bimodal distribution of indoor PM2.5 was identified and the bimodal characteristic was more significant at the finer time resolution. The bimodal distribution maxima were corresponding to the emissions from strong internal sources and the influence of outdoor PM2.5, respectively. Indoor PM2.5 was found to be correlated with the outdoor PM2.5, even though indoor coal combustion for heating was thought to be predominant source of indoor PM2.5. The indoor-outdoor relationship differed significantly between the heating and non-heating seasons. Impacts of typical indoor sources like cooking, heating associated with coal use, and smoking were quantitatively analyzed based on the highly time-resolved PM2.5. Estimated contribution of outdoor PM2.5 to the indoor PM2.5 was ~48% during the non-heating period, but decreased to about 32% during the heating period. The contribution of indoor heating burning coals comprised up to 47% of the indoor PM2.5 during the heating period, while the other indoor sources contributed to ~20%. The study, based on a relatively long-term timely resolved PM2.5 data from a large number of rural households, provided informative results on temporal dynamics of indoor PM2.5 and quantitative contributions of internal sources, promoting scientific understanding on sources and impacts of household air pollution.