Life Cycle Assessment (LCA) plays a crucial role in assessing the environmental impacts of products and systems across their entire lifecycle. However, applying LCA in China presents notable challenges due to the scarcity of region-specific and transparent data. International databases currently unable to capture the distinct features of China’s industrial environment, resulting in inaccuracies in environmental assessments. In response, the TianGong Database has been collaboratively developed to provide comprehensive and transparent LCA datasets tailored to China’s industrial system. As a core milestone, we have systematically collected, organized, and published high-quality unit process datasets. These comprise 2000 high-spatial-resolution unit process datasets, covering diverse industry sectors and providing detailed records of raw material use, energy consumption, and waste generation. Additionally, the database incorporates 157 Input-Output (IO) datasets and 2277 environmental reference parameter datasets. The TianGong Database is built on principles of openness, traceability, and transparency, following internationally recognized methodologies and is freely accessible under the MIT license. Users can access the database through dedicated platforms, facilitating data retrieval and supporting informed decision-making in environmental policy and industrial practices in China. Through continuous updates and community-driven contributions, the localized unit process data of TianGong Database fill critical gaps and serve as a reliable foundation for LCA studies, promoting sustainable development and resource efficiency in Chinese industries.

Global commercial aviation growth has made aircraft exhaust a core source of airport-area air pollution. Despite ICAO’s EEDB on conventional pollutants, emissions are regulated by multiple factors, with sampling variations reducing emission index comparability and leaving organic component gaps. This study integrates engine test and plume sampling data via systematic review and meta-analysis, revealing differential impacts of thrust, testing methods, and fuel types. CO and HC peak at 52.04 g/kg and 11.02 g/kg during idle, declining with thrust; NOx and PM reach 22.75 g/kg and 147.74 mg/kg at takeoff, with particle number concentration bottoming at 2.61×1015/kg during climb. Testing method differences cause a 2.5-fold deviation in key pollutant emission factors, reflecting exhaust's secondary atmospheric transformation. Jet A-1 shows lower PN emissions than Jet A; blending sustainable aviation fuel with conventional fuel yields limited primary pollutant improvements. Organic component studies indicate idle phase contributes ∼70% of organic emissions, while high-thrust phases are alkane/alkene-dominated. Gaps exist in takeoff-phase IVOC data, full SAF emission characteristics, and testing standardization. This study supports improved emission testing, refined inventories, and airport emission reduction policies.

Individual molecular characteristics of organosulfur and organonitrogen compounds (OrgSs and OrgNs) in PM2.5, resolved at a high time resolution, are critical for assessing their roles in climate change and health impacts. In this study, four typical individual OrgSs and OrgNs were quantitatively analyzed, while six biogenic volatile organic compound (VOC)-derived organic sulfates (OSs) and nine nitro-aromatic compounds (NACs) were semiquantified using a combination of UHPLC-Q-Orbitrap MS/MS and UHPLC/ESI-MS. Hourly resolved data for online sulfate, nitrate, and carbonaceous species, as well as the above 15 OrgSs and OrgNs, were obtained from 187 hourly filter samples collected during summer and winter pollution episodes in Beijing in 2019. Both OrgSs and OrgNs exhibited pronounced seasonal and diurnal variations, influenced by anthropogenic and biogenic VOC emissions in the respective seasons. The findings highlight the dynamic conversion pathways between OrgSs and sulfate (heterogeneous processes vs hydrolysis) and between OrgNs and nitrate (heterogeneous processes vs photolysis), particularly under conditions of high humidity, strong acidity, and enhanced atmospheric oxidation capacity. These mechanisms should be adequately considered in PM2.5 control strategies and in modeling secondary species formation, especially regarding the additional sulfate and nitrate sources derived from organic compound conversions.

Atmospheric mercury pollution remains a serious threat for human health and ecosystems, as recognized by the Minamata Convention on Mercury adopted in 2013. Coal-fired power units are major emitters of various environmental pollutants globally, including mercury. Here, we show the historical co-benefits of air pollution control measures and coal power retirement, identify coal-fired power units with disproportionately high mercury emissions, which we define as super emitters, and propose country-specific mitigation strategies. We find that super emitters were primarily concentrated in emerging countries by 2020. Our unit-level analysis highlights that substantial, near-term and cost-effective reductions can be achieved by prioritizing the retirement of super emitters and upgrading pollution control equipment, especially in countries with large coal fleets. In the long term, mercury-specific control technologies will be needed for deeper reductions. Our findings provide insights into customized and stage-based mitigation strategies for phasing down key sources of mercury emissions from coal-fired power units.

Remote sensing (RS) can monitor in-use vehicle emissions but suffers from variable data quality. This study obtained high-quality RS (HQRS) data via a controlled campaign and developed a machine learning framework (RDEV) to improve RS data usability. RDEV exploits the characteristic NO emission pattern (higher in older vehicles than in newer ones), to assess the reliability of remote sensing records, based on the accuracy of classifying vehicles of known-age. RDEV model achieved an accuracy of 86.95 % on the HQRS test subset. When applied to routine monitoring data, RDEV reduced variability in repeated vehicle measurements and aligned gasoline vehicle emission trends more closely with established literature, demonstrating its effectiveness in selecting high-credibility data. This study presents an alternative machine learning application that learns established emission patterns to screen massive RS datasets, offering a method to improve data quality and unlock the value of historical RS data.

As precursors of organic aerosols, organic vapors in the atmosphere have a wide range of concentrations and complicated compositions. Online measurements of atmospheric organic vapors are fundamental to understanding their interactions with aerosols. The chemical ionization Orbitrap mass spectrometry (CI-Orbitrap) is a powerful tool for resolving organic vapors with an ultra-high mass resolution. However, when measuring trace vapors in the atmosphere, this advantage in the resolving power is partially masked by the non-linear sensitivity of CI-Orbitrap to trace species. In this study, we improve the sensitivity of a nitrate CI-Orbitrap to low-concentration organic vapors by excluding reagent ions from the measurement and addressing the challenge of quantification that arises with the exclusion of reagent ions. We introduce a workflow that includes CI-Orbitrap measurement with its mass range switched between a full mass range and a reagent-ion-excluded mass range, and data inversion with corrections for sensitivity and transmission. Using this workflow, the signal of trace vapors detected by the nitrate CI-Orbitrap can be increased by up to 20 times, and the concentration at which the sensitivity reduces by 50% can be reduced to 1 x 103 #/cm3. Using the nitrate CI-Orbitrap with mass range switching, we measured oxygenated organic molecules (OOMs) in urban Beijing. Enabled by the improved sensitivity, trace OOMs (especially those with high masses and oxidation states, e.g., OOM dimers) are better resolved, and the homologous and oxygen-addition characteristics in OOM formulas at high masses are uncovered.Copyright (c) 2025 American Association for Aerosol Research

Sea ice retreat is opening up Arctic shipping routes, reducing transit times and enhancing access to regions with valuable resources. However, increased shipping has a negative impact on the Arctic environment. In this Review, we discuss the drivers and impacts of Arctic shipping and outline opportunities for its sustainable development. The Arctic sea ice area in September decreased by 35.8% during 1980–2024; consequently, the number of ships entering the Polar Code Arctic area increased by 37.3% between 2013 and 2023, increasing CO2 emissions from shipping by 6.3%. Economic incentives, governance frameworks, technology and infrastructure are also key drivers. The impacts of Arctic shipping span multiple environmental spheres, including changes in wildlife behaviour, invasive species, pollution and climate forcing. For example, ship-based emissions contributed to 560–1,100 premature deaths in the Nordic Arctic in 2015; biofouling increases the risk of invasive species by a factor of 3–20; one oil spill caused up to 300,000 bird deaths; and the concentration of microplastics near Brønnøysund is one to four orders of magnitude higher than the global average probably owing to wastewater from ships. Sustainable Arctic shipping will require stricter regulations on fuel standards and greywater release alongside improvements in navigation and emission filtration technologies. Arctic shipping is increasing owing to sea ice melt offering more efficient alternatives to traditional shipping routes, leading to negative impacts across the atmosphere, cryosphere, hydrosphere and biosphere. This Review discusses the factors influencing trends in Arctic shipping, the associated environmental impacts and potential pathways towards sustainable solutions.

Achieving carbon neutrality and improving air quality are pivotal sustainability strategies for the Global South countries. However, their global climate impacts over a realistic timescale remain unclear. Here we evaluate the climate impacts of China's carbon neutrality and Beautiful China policies using a fully coupled Earth system model and updated future anthropogenic emission scenarios. We find that, for an unexpectedly long time through ~2070, China's air pollutant reductions can cause a large global surface warming (0.12 ± 0.09 K for 2050-2070) that almost offsets the cooling from concurrent CO2 emission reduction (0.16 ± 0.05 K for 2050-2070), compared to a business-as-usual scenario. This warming is mainly attributed to reduced SO2 and organic matter emissions. Moreover, combined air pollutants and CO2 declines create a striking hemispheric temperature change contrast, because of the stronger aerosol-induced heating in the Northern Hemisphere. Considering that most future air pollutant reductions represent synergistic effects of carbon neutrality policies, the associated inevitable warming effect over decades highlights the importance of exploring more aggressive policies including early carbon neutrality, methane reductions, and negative carbon emissions.

With the progress of global climate actions, amine-based carbon capture technology is being rapidly deployed. However, they potentially emit amines into the atmosphere, posing risks to air quality, climate, and human health. In this study, we conducted atmospheric measurements in Beijing during 2024 using Vocus Proton-Transfer-Reaction Mass Spectrometry. Several emerging amines of potential carbon capture relevance including C2H7NO, C4H10N2, C4H11NO, C4H11NO2, C5H13NO2 were identified in urban atmosphere. Their median mixing ratios range from 0.69 to 5.21 pptv, comparable to those of typical atmospheric alkylamines. They have different diurnal patterns in comparison to those of alkylamines (e.g., C2-amines). The presence of their oxidation products identified in laboratory studies was verified in the atmosphere, including C4H8N2 (tetrahydropyrazine) that is a potential indicator for C4H10N2 (piperazine) oxidation in the atmosphere. To further support these findings, a modified Orbitrap mass spectrometer was deployed at the same site in 2025 and its high resolution allowed for unambiguous identification of these amine peaks. Flue gas samples from a pilot carbon capture facility were also analyzed using the same Vocus instrument and confirmed the detection of C4H10N2, C4H11NO and C4H11NO2. In recent years, multiple carbon capture facilities have been deployed in Beijing and its surrounding areas. Backward-trajectory analysis of air masses suggests their potential influence to the site.

Air pollution poses significant threats to human health through both chronic and acute exposures. Future climate warming and population aging may lead to increased health risks from air pollution, while emission reductions can help alleviate the associated risks. Yet, the joint impacts of future climate change and emission reductions on both chronic and acute air pollution exposure and related premature deaths remain unclear. Here, we utilize dynamical downscaling and multi-model ensemble simulations to systematically assess projected chronic and acute exposure of O3 and PM2.5 and the associated premature deaths in China in 2056-2060 under two climate scenarios. We find that future climate change under the high warming scenario (SSP3-7.0) is projected to lead to a moderate increase of 4%-19% in chronic PM2.5 and O3 pollution exposure and premature deaths but a substantial increase of 19%-89% in acute exposure and deaths in China by midcentury. Deep emission reductions from China's carbon neutrality efforts will effectively mitigate pollution health risks, especially for acute pollution exposure, while health risks for chronic exposure remain a concern under an aging population. Our results reveal future changes in air pollution health risks, suggesting an urgent need for targeted air quality and health management policies.

Land use and land cover changes (LULCCs) influence air quality via modifications in local meteorology and natural emissions, yet their future impacts and pathway contributions remain inadequately quantified. Here, we employed an online coupled meteorology-chemistry model to assess the effects of LULCCs by the mid-21st century on O3 and PM2.5 in China, and to disentangle the roles of meteorological influences versus biogenic volatile organic compound (BVOC) emission changes. Our results show that, with anthropogenic emissions and meteorological fields fixed at current conditions, LULCCs under SSP1-2.6 and Afforestation scenarios (characterized by forest expansion) induce a summer cooling of 0.04 degrees C and 0.09 degrees C in China but raise summertime daily maximum 8-h O3 by 1.8 & micro;g/m3 and 4.7 & micro;g/m3 due to the dominance of BVOC-driven enhancement. Meanwhile, afforestation triggers north-south and seasonal variations in PM2.5 changes: winter decreases in the north but increases in the south, with the pattern reversing in summer, resulting in a net national increase. Conversely, deforestation under SSP5-8.5 would cause warming but reduce BVOC emissions, slightly lowering summer O3 (-0.8 & micro;g/m3) and winter PM2.5 (-0.1 & micro;g/m3) across China. These findings underscore the potential importance of incorporating land-use strategies to support future integrated climate and air quality governance.

Fine particulate matter (PM2.5) remains a leading environmental health risk, yet air pollution control policies typically assume equal toxicity across emission sources. Unravelling the unequal toxicities in global PM2.5 emissions can support more effective air pollution control. Here, we integrate cell-based toxicological profiles with global emission inventories to develop the first global dataset of toxicity-adjusted PM2.5 emissions. We show that global toxicity-adjusted emissions are dominated by residential solid-fuel combustion, and that hotspots of PM2.5 mass and toxicity diverge substantially, with the highest toxicities occurring largely in regions reliant on traditional biomass. Low-income countries exhibit disproportionately high toxicity-adjusted emissions relative to their energy use, revealing a strong global environmental inequity. Incorporating unequal toxicities reshapes emission-control priorities, shifting many countries from mass-dominated industrial or power sectors towards residential combustion. We propose a toxicity-informed framework for air pollution control, which is adaptable to diverse socioeconomic contexts and can enhance global health and sustainability.

Atmospheric ultrafine particles (UFP, aerodynamic diameter ⩽ 100 nm) are an emerging global air quality and public health concern. UFP dominate ambient particle number concentrations while constituting only a minor fraction of particulate mass. Their small sizes and high specific surface areas promote deep lung deposition, translocation, and the adsorption of redox-active substances like organics and transition metals, contributing to their adverse health impacts. In this perspective, we summarized epidemiological and toxicological studies of UFP, highlighting the discrepancies in the nanotoxicity using number-, versus surface area-based dose metrics. Current studies have linked UFP exposure to increased respiratory, cardiovascular, and central nervous system mortalities and morbidities, both short term and long term. In addition, surface area-based metric captured stronger associations with natural mortality and cardiovascular-related hospital admissions than number concentration, suggesting particle surface area might better reflect the toxic potential of UFP. However, current literature cannot support definitive associations, because of the dynamic nature of UFP, confounding co-pollutants, and differed measurement techniques. Advancing UFP health science and policy requires coordinated particle size distribution monitoring that reports both particle number and surface concentrations. These measurements are essential for comprehensive risk assessment, exposure modeling, and ultimately for evidence-based air quality standards capable of addressing the distinct hazards posed by UFP.

Secondary organic aerosols (SOAs) can be generated in both gas phase and aqueous phase, but the factors determining the major mechanism have not been fully clarified. In this study, field measurements were conducted at a rural background station on the North China Plain (NCP) from October 8 to 23, 2019. During the campaign, air quality was generally good, but there was some particle pollution when environmental conditions did not significantly deteriorate, with rapid secondary reactions acting as the driving force. Although atmospheric oxidation of volatile organic compounds (VOCs) has been generally recognized as the predominant source of SOA, a significant contribution of aqueous-phase chemistry was observed under high aerosol water content based on the characteristics of NMVOCs concentrations, O/C ratio, components of OA, droplet concentrations, and results of gasSOA estimation. Furthermore, the relationship between the AWC and the aqueous phase reaction rate was quantified based on the modelling of phenol, and the results showed that the consumption rate of phenol would increase to ∼0.04 μg m-3 h-1 when the AWC reached to 40 μg m-3. However, only reactions under illumination could effectively contribute to the SOA mass. Therefore, AWC rebounding in the afternoon was shown to be critical for rapid SOA growth.

The energy transition to net-zero carbon emissions may exacerbate regional inequities, impeding an orderly national transition and threatening global climate goals. This challenge might be particularly severe in China, as it simultaneously faces significant regional disparities, carbon-intensive industrial and energy structures, and a relatively short transition period. Yet, the inequity risks rooted in regional economic linkages among technologies and sectors during the energy transition remain insufficiently addressed. Here, we newly developed a sector-extended multi-regional input-output model of China with a detailed representation of power production technologies (multi-regional input-output table with a disaggregated power sector [MRIO-DPS]) and further coupled it with the global change analysis model with China provincial-level details (GCAM-China) to assess regional inequities and responses in China's carbon-neutral energy transition (CNET). By 2060, ∼40% of China's provinces (mainly economically underdeveloped) are projected to face gross domestic product (GDP) declines ranging from 0.2% to 15.8%, while more developed provinces are expected to see GDP growth of 0.2%-3.5% (CNET scenario). We propose industrial spatial reconfiguration as a countermeasure: relocating energy-intensive industries to renewable-rich provinces while expanding electricity transmission from these provinces to load centers (power transmission combined with industrial transfer [PTIT] scenario). Scenario analysis shows that this reconfiguration significantly narrows subnational inequities, reduces the number of provinces with GDP declines by 42%, and boosts national GDP by 0.06% and employment by 0.68 million in 2060.

This work outlines the current status of ozone (O3) pollution in China, which has become increasingly prominent in recent years, and control strategies that can be used to address this issue. O3 is a secondary product from the complex photochemical reactions of volatile organic compounds (VOCs) coupled with the nitrogen oxide (NOx) cycle. Considering the sources of precursors (i.e., VOCs and NOx) and the maturity of corresponding control technologies, substantially reducing NOx is a more feasible strategy for reducing O3 concentrations than focusing on VOCs, although it is undeniable that implementing coordinated control of NOx and VOCs in an optimal reduction ratio based on the specific conditions of different regions is the most effective strategy for controlling O3 pollution. Additionally, direct O3-decomposition technologies using catalytic materials coated on artificial surfaces offer a promising solution: These technologies can remove O3 without additional energy consumption, providing a practical complement to traditional emission-control strategies.

Aerosol particles, profoundly influenced by human activities, play pivotal roles in air quality and climate. The formation and growth of new atmospheric particles is a leading source of high-concentration aerosol particles in urban environments and also the largest source of uncertainties in global climate predictions. Recent advances in experimental and theoretical research have dramatically improved our understanding of urban new particle formation (NPF), showing that the abundant anthropogenic pollutants in complex urban atmospheres enable the fast formation of new particles that are highly selective toward the gaseous precursors and chemical processes. The uniqueness of urban atmospheres causes the underrepresentation of urban NPF in regional and global models, while the evolving urban environments complicate the prediction of future environmental and climate effects of NPF. In this review, we link the latest molecular-level chemical mechanisms and implications on climate predictions and air pollution control by assessing the methodology to investigate urban NPF, sorting out the latest mechanistic findings, and discussing their implementation in three-dimensional models.

ABSTRACT Particulate nitrate is a major component of haze pollution, yet substantial debate exists regarding its effective control policies. Here, we develop a multiphase dissociation equilibrium equation, based on which the influence of meteorological conditions and chemical profiles can be decoupled, and the analytical expression of nitrate sensitivity to different species can be derived. With this framework, four nitrate control regimes are identified, namely the nitric-acid-control, ammonia-control, transition, and meteorology regimes. The framework also explains the trade-offs between sulfate and nitrate, and elucidates the influence of sulfate and non-volatile cations on the regime transitions. Across most Northern Hemisphere continental regions, and nearly all of China, particulate nitrate is generally more sensitive to nitric acid than to ammonia due to the universal NH3 excess. The framework provides transparent criteria for interpreting nitrate sensitivity and control regime classifications, serving as an important scientific basis for nitrate control policies and reactive nitrogen interactions.