Household fuel and direct carbon emission disparity in rural China.

Universal access to clean fuels in household use is one explicit indicator of sustainable development while currently still billions of people rely on solid fuels for daily cooking. Despite of the recognized clean transition trend in general, disparities in household energy mix in different activities (e.g. cooking and heating) and historical trends remain to be elucidated. In this study, we revealed the historical changing trend of the disparity in household cooking and heating activities and associated carbon emissions in rural China. The study found that the poor had higher total direct energy consumption but used less modern energy, especially in cooking activities, in which the poor consumed 60 % more energy than the rich. The disparity in modern household energy use decreased over time, but conversely the disparity in total residential energy consumption increased due to the different energy elasticities as income increases. Though per-capita household CO2 and Black Carbon (BC) emissions were decreasing under switching to modern energies, the disparity in household CO2 and BC deepened over time, and the low-income groups emitted âˆ¼ 10 kg CO2 more compared to the high-income population. Relying solely on spontaneous clean cooking transition had limited impacts in reducing disparities in household energy and carbon emissions, whereas improving access to modern energy had substantial potential to reduce energy consumption and carbon emissions and its disparity. Differentiated energy-related policies to promote high-efficiency modern heating energies affordable for the low-income population should be developed to reduce the disparity, and consequently benefit human health and climate change equally.

Health burden from food systems is highly unequal across income groups.

Food consumption contributes to the degradation of air quality in regions where food is produced, creating a contrast between the health burden caused by a specific population through its food consumption and that faced by this same population as a consequence of food production activities. Here we explore this inequality within China's food system by linking air-pollution-related health burden from production to consumption, at high levels of spatial and sectorial granularity. We find that low-income groups bear a 70% higher air-pollution-related health burden from food production than from food consumption, while high-income groups benefit from a 29% lower health burden relative to their food consumption. This discrepancy largely stems from a concentration of low-income residents in food production areas, exposed to higher emissions from agriculture. Comprehensive interventions targeting both production and consumption sides can effectively reduce health damages and concurrently mitigate associated inequalities, while singular interventions exhibit limited efficacy.

Convolutional Neural Networks Facilitate Process Understanding of Megacity Ozone Temporal Variability.

Ozone pollution is profoundly modulated by meteorological features such as temperature, air pressure, wind, and humidity. While many studies have developed empirical models to elucidate the effects of meteorology on ozone variability, they predominantly focus on local weather conditions, overlooking the influences from high-altitude and broader regional meteorological patterns. Here, we employ convolutional neural networks (CNNs), a technique typically applied to image recognition, to investigate the influence of three-dimensional spatial variations in meteorological fields on the daily, seasonal, and interannual dynamics of ozone in Shenzhen, a major coastal urban center in China. Our optimized CNNs model, covering a 13° × 13° spatial domain, effectively explains over 70% of daily ozone variability, outperforming alternative empirical approaches by 7 to 62%. Model interpretations reveal the crucial roles of 2-m temperature and humidity as primary drivers, contributing 16% and 15% to daily ozone fluctuations, respectively. Regional wind fields account for up to 40% of ozone changes during the episodes. CNNs successfully replicate observed ozone temporal patterns, attributing -5-6 µg·m-3 of interannual ozone variability to weather anomalies. Our interpretable CNNs framework enables quantitative attribution of historical ozone fluctuations to nonlinear meteorological effects across spatiotemporal scales, offering vital process-based insights for managing megacity air quality amidst changing climate regimes.

Temperature-Dependent Evaporative Anthropogenic VOC Emissions Significantly Exacerbate Regional Ozone Pollution.

The evaporative emissions of anthropogenic volatile organic compounds (AVOCs) are sensitive to ambient temperature. This sensitivity forms an air pollution-meteorology connection that has not been assessed on a regional scale. We parametrized the temperature dependence of evaporative AVOC fluxes in a regional air quality model and evaluated the impacts on surface ozone in the Beijing-Tianjin-Hebei (BTH) area of China during the summer of 2017. The temperature dependency of AVOC emissions drove an enhanced simulated ozone-temperature sensitivity of 1.0 to 1.8 µg m-3 K-1, comparable to the simulated ozone-temperature sensitivity driven by the temperature dependency of biogenic VOC emissions (1.7 to 2.4 µg m-3 K-1). Ozone enhancements driven by temperature-induced AVOC increases were localized to their point of emission and were relatively more important in urban areas than in rural regions. The inclusion of the temperature-dependent AVOC emissions in our model improved the simulated ozone-temperature sensitivities on days of ozone exceedance. Our results demonstrated the importance of temperature-dependent AVOC emissions on surface ozone pollution and its heretofore unrepresented role in air pollution-meteorology interactions.

Internal exposure potential of water-soluble organic molecules in urban PM2.5 evaluated by non-covalent adductome of human serum albumin.

Water-soluble organic molecules (WSOMs) in inhaled PM2.5 can readily translocate from the lungs into the blood circulation, facilitating their distribution to and health effects on distant organs and tissues in the human body. Human serum albumin (HSA), the most abundant protein carrier in the blood, readily binds exogenous substances to form non-covalent adducts and subsequently transports them throughout the circulatory system, thereby indicating their internal exposure. The direct internal exposure of WSOMs in PM2.5 needs to be understood. In this study, the non-covalent HSA-WSOM adductome was developed as a dosimeter to evaluate the internal exposure potential of WSOMs in urban PM2.5. The WSOM composition was acquired from non-target high-resolution mass spectrometry analysis coupled with multiple ionizations. The binding level of HSA-WSOM non-covalent adducts was obtained from surface plasma resonance. Machine learning combined WSOM composition and the binding level of HSA-WSOM non-covalent adducts to screen bindable (also internalizable) WSOMs. The concentration of WSOM ranged from 4 to 13 µg/m3 during our observation period. Of the 17,513 mass spectral features detected, 9,484 contributed to the non-covalent adductome and possessed the internal exposure potential. 102 major contributors accounted for 90.6 % of the HSA-WSOM binding level. The fraction of internalizable WSOMs in PM2.5 varied from 11.9 % to 61.3 %, averaging 26.2 %. WSOMs that have internal exposure potential were primarily lignin-like and lipid-like substances. The HSA-WSOMs non-covalent adductome represents direct internal exposure potential, which can provide crucial insights into the molecular diagnosis of PM2.5 exposure and precise assessments of PM2.5 health effects.

Fertilizer management for global ammonia emission reduction.

Crop production is a large source of atmospheric ammonia (NH3), which poses risks to air quality, human health and ecosystems1-5. However, estimating global NH3 emissions from croplands is subject to uncertainties because of data limitations, thereby limiting the accurate identification of mitigation options and efficacy4,5. Here we develop a machine learning model for generating crop-specific and spatially explicit NH3 emission factors globally (5-arcmin resolution) based on a compiled dataset of field observations. We show that global NH3 emissions from rice, wheat and maize fields in 2018 were 4.3 ± 1.0 Tg N yr-1, lower than previous estimates that did not fully consider fertilizer management practices6-9. Furthermore, spatially optimizing fertilizer management, as guided by the machine learning model, has the potential to reduce the NH3 emissions by about 38% (1.6 ± 0.4 Tg N yr-1) without altering total fertilizer nitrogen inputs. Specifically, we estimate potential NH3 emissions reductions of 47% (44-56%) for rice, 27% (24-28%) for maize and 26% (20-28%) for wheat cultivation, respectively. Under future climate change scenarios, we estimate that NH3 emissions could increase by 4.0 ± 2.7% under SSP1-2.6 and 5.5 ± 5.7% under SSP5-8.5 by 2030-2060. However, targeted fertilizer management has the potential to mitigate these increases.

Impact of antioxidants on PM2.5 oxidative potential, radical level, and cytotoxicity.

Antioxidants are typically seen as agents that mitigate environmental health risks due to their ability to scavenge free radicals. However, our research presents a paradox where these molecules, particularly those within lung fluid, act as prooxidants in the presence of airborne particulate matter (PM2.5), thus enhancing PM2.5 oxidative potential (OP). In our study, we examined a range of antioxidants found in the respiratory system (e.g., vitamin C, glutathione (GSH), and N-acetylcysteine (NAC)), in plasma (vitamin A, vitamin E, and ß-carotene), and in food (tert-butylhydroquinone (TBHQ)). We aimed to explore antioxidants' prooxidant and antioxidant interactions with PM2.5 and the resulting OP and cytotoxicity. We employed OH generation assays and electron paramagnetic resonance assays to assess the pro-oxidative and anti-oxidative effects of antioxidants. Additionally, we assessed cytotoxicity interaction using a Chinese hamster ovary cell cytotoxicity assay. Our findings revealed that, in the presence of PM2.5, all antioxidants except vitamin E significantly increased the PM2.5 OP by generating more OH radicals (OH generation rate: 0.16-24.67 pmol·min-1·m-3). However, it's noteworthy that these generated OH radicals were at least partially neutralized by the antioxidants themselves. Among the pro-oxidative antioxidants, vitamin A, ß-carotene, and TBHQ showed the least ability to quench these radicals, consistent with their observed impact in enhancing PM2.5 cytotoxicity (PM2.5 LC50 reduced to 91.2 %, 88.8 %, and 75.1 % of PM2.5's original level, respectively). Notably, vitamin A and TBHQ-enhanced PM2.5 OP were strongly associated with the presence of metals and organic compounds, particularly with copper (Cu) contributing significantly (35 %) to TBHQ's pro-oxidative effect. Our study underscores the potential health risks associated with the interaction between antioxidants and ambient pollutants.

Investigation of Plant-Level Volatile Organic Compound Emissions from Chemical Industry Highlights the Importance of Differentiated Control in China.

The chemical industry is a significant source of nonmethane volatile organic compounds (NMVOCs), pivotal precursors to ambient ozone (O3), and secondary organic aerosol (SOA). Despite their importance, precise estimation of these emissions remains challenging, impeding the implementation of NMVOC controls. Here, we present the first comprehensive plant-level assessment of NMVOC emissions from the chemical industry in China, encompassing 3461 plants, 127 products, and 50 NMVOC compounds from 2010 to 2019. Our findings revealed that the chemical industry in China emitted a total of 3105 (interquartile range: 1179-8113) Gg of NMVOCs in 2019, with a few specific products accounting for the majority of the emissions. Generally, plants engaged in chemical fibers production or situated in eastern China pose a greater risk to public health due to their higher formation potentials of O3 and SOA or their proximity to residential areas or both. We demonstrated that targeting these high-risk plants for emission reduction could enhance health benefits by 7-37% per unit of emission reduction on average compared to the current situation. Consequently, this study provides essential insights for developing effective plant-specific NMVOC control strategies within China's chemical industry.

Iron and Steel Industry Emissions: A Global Analysis of Trends and Drivers.

The iron and steel industry (ISI) is important for socio-economic progress but emits greenhouse gases and air pollutants detrimental to climate and human health. Understanding its historical emission trends and drivers is crucial for future warming and pollution interventions. Here, we offer an exhaustive analysis of global ISI emissions over the past 60 years, forecasting up to 2050. We evaluate emissions of carbon dioxide and conventional and unconventional air pollutants, including heavy metals and polychlorinated dibenzodioxins and dibenzofurans. Based on this newly established inventory, we dissect the determinants of past emission trends and future trajectories. Results show varied trends for different pollutants. Specifically, PM2.5 emissions decreased consistently during the period 1970 to 2000, attributed to adoption of advanced production technologies. Conversely, NOx and SO2 began declining recently due to stringent controls in major contributors such as China, a trend expected to persist. Currently, end-of-pipe abatement technologies are key to PM2.5 reduction, whereas process modifications are central to CO2 mitigation. Projections suggest that by 2050, developing nations (excluding China) will contribute 52-54% of global ISI PM2.5 emissions, a rise from 29% in 2019. Long-term emission curtailment will necessitate the innovation and widespread adoption of new production and abatement technologies in emerging economies worldwide.

Antagonism between ambient ozone increase and urbanization-oriented population migration on Chinese cardiopulmonary mortality.

Ever-increasing ambient ozone (O3) pollution in China has been exacerbating cardiopulmonary premature deaths. However, the urban-rural exposure inequity has seldom been explored. Here, we assess population-scale O3 exposure and mortality burdens between 1990 and 2019 based on integrated pollution tracking and epidemiological evidence. We find Chinese population have been suffering from climbing O3 exposure by 4.3 ± 2.8 ppb per decade as a result of rapid urbanization and growing prosperity of socioeconomic activities. Rural residents are broadly exposed to 9.8 ± 4.1 ppb higher ambient O3 than the adjacent urban citizens, and thus urbanization-oriented migration compromises the exposure-associated mortality on total population. Cardiopulmonary excess premature deaths attributable to long-term O3 exposure, 373,500 (95% uncertainty interval [UI]: 240,600-510,900) in 2019, is underestimated in previous studies due to ignorance of cardiovascular causes. Future O3 pollution policy should focus more on rural population who are facing an aggravating threat of mortality risks to ameliorate environmental health injustice.

Char dominates black carbon aerosol emission and its historic reduction in China.

Emission factors and inventories of black carbon (BC) aerosols are crucial for estimating their adverse atmospheric effect. However, it is imperative to separate BC emissions into char and soot subgroups due to their significantly different physicochemical properties and potential effects. Here, we present a substantial dataset of char and soot emission factors derived from field and laboratory measurements. Based on the latest results of the char-to-soot ratio, we further reconstructed the emission inventories of char and soot for the years 1960-2017 in China. Our findings indicate that char dominates annual BC emissions and its huge historical reduction, which can be attributable to the rapid changes in energy structure, combustion technology and emission standards in recent decades. Our results suggest that further BC emission reductions in both China and the world should focus on char, which mainly derives from lower-temperature combustion and is easier to decrease compared to soot.

Emission factors of oxygenated polycyclic aromatic hydrocarbons from ships in China.

The rapid growth of maritime traffic, transportation, and fishery activities has increased shipping emissions and degraded the air quality in coastal areas. As a result, controlling ocean-based pollution sources have become increasingly important. This study investigated the real-world emission characteristics of oxygenated polycyclic aromatic hydrocarbons (OPAHs, a group of highly toxic semi-volatile organic compounds) from five types of offshore ships using diesel oil: small and medium fishing ships, tug boats, ferry, and engineering ships, under various driving mode. Both gaseous and particle emission factors (EF) of four specific OPAHs were determined in our study. Among the OPAHs species emitted from ships, 9-fluorenone (9FO; 72%) and anthrathrace-9,10-quinone (ATQ; 25%) were the most abundant. The arithmetic mean of the sum of gaseous OPAHs EFs for all ships in this study was 2.5 ± 4.4 mg/kg fuel burned, and the mean particulate OPAHs EF was 4.7 ± 7.9 mg/kg. Small fishing ships had the highest total OPAHs EFs (31.0 ± 17.0 mg/kg). Apart from small fishing ships, there was no significant difference in the total EF of OPAHs for the other four types of ships. The emissions of the four OPAHs are predominantly in the particulate phase. There were no significant differences in the emissions of the four OPAHs under different driving mode. According to estimates, the annual OPAH emissions from the four types of ships in Hainan in 2017 were approximately 4.2 (range: 2.7-7.0) tons, dwarfing the OPAH emissions from diesel-powered on-road vehicles in China (23.5 kg).

Impact of Ship Emissions on Air Quality in the Greater Bay Area in China under the Latest Global Marine Fuel Regulation.

As the main anthropogenic source in open seas and coastal areas, ship emissions impact the climate, air quality, and human health. The latest marine fuel regulation with a sulfur content limit of 0.5% went into effect globally on January 1, 2020. Investigations of ship emissions after fuel switching are necessary. In this study, online field measurements at an urban coastal site and modeling simulations were conducted to detect the impact of ship emissions on air quality in the Greater Bay Area (GBA) in China under new fuel regulation. By utilizing a high mass-resolution single particle mass spectrometer, the vanadium(V) signal was critically identified and was taken as a robust indicator for ship-emitted particles (with relative peak area > 0.1). The considerable number fractions of high-V particles (up to 30-40% during ship plumes) indicated that heavy fuel oils via simple desulfurization or blending processes with low-sulfur fuels were extensively used in the GBA to meet the global 0.5% sulfur cap. Our results showed that ship-emitted particulate matter and NOx contributed up to 21.4% and 39.5% to the ambient, respectively, in the summertime, significantly affecting the air quality in the GBA. The sea-land breeze circulation also played an important role in the transport pattern of ship-emitted pollutants in the GBA.

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.

[Characteristics and Differences of Household Fine Particulate Matter Pollution Caused by Fuel Burning in Urban and Rural Areas in China].

Objective To explore the overall level,distribution characteristics,and differences in household fine particulate matter (PM2.5) pollution caused by fuel burning in urban and rural areas in China. Methods The relevant articles published from 1991 to 2021 were retrieved and included in this study.The data including the average concentration of household PM2.5 and urban and rural areas were extracted,and the stoves and fuel types were reclassified.The average concentration of PM2.5 in different areas was calculated and analyzed by nonparametric test. Results The average household PM2.5 concentration in China was (178.81±249.91) µg/m3.The mean household PM2.5 concentration was higher in rural areas than in urban areas[(206.08±279.40) µg/m3 vs. (110.63±131.16) µg/m3;Z=-5.45,P<0.001] and higher in northern areas than in southern areas[(224.27±301.66) µg/m3 vs.(130.11±140.61) µg/m3;Z=-2.38,P=0.017].The north-south difference in household PM2.5 concentration was more significant in rural areas than in urban areas[(324.19±367.94) µg/m3 vs.(141.20±151.05) µg/m3,χ2=-5.06,P<0.001].The PM2.5 pollution level showed differences between urban and rural households using different fuel types (χ2=92.85,P<0.001),stove types (χ2=74.42,P<0.001),and whether they were heating (Z=-4.43,P<0.001).Specifically,rural households mainly used solid fuels (manure,charcoal,coal) and traditional or improved stoves,while urban households mainly used clean fuels (gas) and clean stoves.The PM2.5 concentrations in heated households were higher than those in non-heated households in both rural and urban areas (Z=-4.43,P<0.001). Conclusions The household PM2.5 pollution caused by fuel combustion in China remains a high level.The PM2.5 concentration shows a significant difference between urban and rural households,and the PM2.5 pollution is more serious in rural households.The difference in the household PM2.5 concentration between urban and rural areas is more significant in northern China.PM2.5 pollution in the households using solid fuel,traditional stoves,and heating is serious,and thus targeted measures should be taken to control PM2.5 pollution in these households.

Significant but Inequitable Cost-Effective Benefits of a Clean Heating Campaign in Northern China.

Residential emissions significantly contribute to air pollution. To address this issue, a clean heating campaign was implemented to replace coal with electricity or natural gas among 13.9 million rural households in northern China. Despite great success, the cost-benefits and environmental equity of this campaign have never been fully investigated. Here, we modeled the environmental and health benefits, as well as the total costs of the campaign, and analyzed the inequality and inequity. We found that even though the campaign decreased only 1.1% of the total energy consumption, PM2.5 emissions and PM2.5 exposure experienced 20% and 36% reduction, respectively, revealing the amplification effects along the causal pathway. Furthermore, the number of premature deaths attributable to residential emissions reduced by 32%, suggesting that the campaign was highly beneficial. Governments and residents shared the cost of 2,520 RMB/household. However, the benefits and the costs were unevenly distributed, as the residents in mountainous areas were not only less benefited from the campaign but also paid more because of the higher costs, resulting in a notably lower cost-effectiveness. Moreover, villages in less developed areas tended to choose natural gas with a lower initial investment but a higher total cost (2,720 RMB/household) over electricity (2,190 RMB/household). With targeted investment and subsidies in less developed areas and the promotion of electricity and other less expensive alternatives, the multidevelopment goals of improved air quality, reduced health impacts, and reduced inequity in future clean heating interventions could be achieved.

Plastic waste discharge to the global ocean constrained by seawater observations.

Marine plastic pollution poses a potential threat to the ecosystem, but the sources and their magnitudes remain largely unclear. Existing bottom-up emission inventories vary among studies for two to three orders of magnitudes (OMs). Here, we adopt a top-down approach that uses observed dataset of sea surface plastic concentrations and an ensemble of ocean transport models to reduce the uncertainty of global plastic discharge. The optimal estimation of plastic emissions in this study varies about 1.5 OMs: 0.70 (0.13-3.8 as a 95% confidence interval) million metric tons yr-1 at the present day. We find that the variability of surface plastic abundance caused by different emission inventories is higher than that caused by model parameters. We suggest that more accurate emission inventories, more data for the abundance in the seawater and other compartments, and more accurate model parameters are required to further reduce the uncertainty of our estimate.

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.