Air Pollution Control Research Articles

Impact of air pollution prevention and control on urban green economy efficiency: evidence from China

Impact of air pollution prevention and control on urban green economy efficiency: evidence from China

Assessment of PM2.5 pollution features and health advantages in Northwest China.

The elevated concentration of suspended particulate matter in the atmosphere is closely associated with the morbidity and mortality of human diseases. In northwest China, fine particulate matter pollution has persistently affected local health, production, and daily life due to climatic factors and economic development. This paper first examines the distribution and variation of PM2.5 concentrations in northwest China from 2013 to 2022 to understand changes in PM2.5 exposure levels, as well as their associated health and economic benefits since the implementation of the "Air Pollution Prevention and Control Action Plan." Second, we estimated the number of premature deaths in the research region under various control scenarios based on PM2.5 concentrations recorded in 2013 and 2021, utilizing existing epidemiological studies for reference. Finally, we calculated the financial benefits resulting from variations in PM2.5 concentrations within this region. Results indicated that (1) from 2013 to 2022, the Tarim Basin exhibited the highest PM2.5 concentration among all studied areas, while northern Xinjiang and Qinghai Province had notably lower levels. Additionally, wintertime concentrations were consistently higher than those observed during summer months; however, there has been a general trend toward reduced PM2.5 content over the past decade. (2) A significant inverse relationship was found between premature mortality rates and PM2.5 concentrations; specifically, fluctuations in PM2.5 levels exerted a more pronounced impact on premature deaths attributable to cardiovascular diseases compared to respiratory conditions within this northwest region. (3) Males were disproportionately affected by increases in PM2.5 concentration relative to females-experiencing two to three times more early fatalities than their female counterparts did. (4) Over a 9-year period within this research area, fiscal benefits derived from interventions targeting PM2.5 treatment increased by approximately 891 million yuan.

Life Course Associations Between Ambient Fine Particulate Matter and the Prevalence of Prediabetes and Diabetes: A Longitudinal Cohort Study in Taiwan and Hong Kong.

Both air pollution and diabetes are key urban challenges. The association between particulate matter with a diameter of <2.5 μm (PM2.5) exposure and prediabetes/diabetes in adults is well documented, but the health effects of life course exposure remain unclear. This study evaluated the impact of PM2.5 exposure throughout various life stages on the prevalence of prediabetes/diabetes in adulthood. We included 4,551 individuals with 19,593 medical visits from two open cohorts in Taiwan and Hong Kong between 2000 and 2018. Ambient PM2.5 exposure was assessed using a satellite-based model, delivering a 2-year average exposure at a resolution of 1 km2. Logistic mixed-effects models were used to investigate longitudinal associations between PM2.5 exposure and the prevalence of prediabetes/diabetes. Life course models were used to examine the impact of PM2.5 exposure at different life stages on prediabetes/diabetes in adulthood. Over an average follow-up period of 9.93 years, 1,660 individuals with prediabetes/diabetes were observed. For the longitudinal association, every 10 μg/m3 increase in PM2.5 was associated with an increased odds of having prediabetes/diabetes (odds ratio 1.32, 95% CI 1.13, 1.54). The odds of adulthood prediabetes/diabetes increased by 15%, 18%, and 29% for each 10 μg/m3 increase in PM2.5 exposure during school age, adolescence, and adulthood, respectively. Our findings suggest a link between PM2.5 exposure during each life stage and the prevalence of prediabetes/diabetes in adulthood, with the health impacts of exposure during adulthood being slightly greater. This study underscores the need for life course air pollution control strategies to mitigate the substantial disease burden of diabetes.

Prediction of Hydrogen Production from Solid Oxide Electrolytic Cells Based on ANN and SVM Machine Learning Methods

In recent years, the application of machine learning methods has become increasingly common in atmospheric science, particularly in modeling and predicting processes that impact air quality. This study focuses on predicting hydrogen production from solid oxide electrolytic cells (SOECs), a technology with significant potential for reducing greenhouse gas emissions and improving air quality. We developed two models using artificial neural networks (ANNs) and support vector machine (SVM) to predict hydrogen production. The input variables are current, voltage, communication delay time, and real-time measured hydrogen production, while the output variable is hydrogen production at the next sampling time. Both models address the critical issue of production hysteresis. Using 50 h of SOEC system data, we evaluated the effectiveness of the ANN and SVM methods, incorporating hydrogen production time as an input variable. The results show that the ANN model is superior to the SVM model in terms of hydrogen production prediction performance. Specifically, the ANN model shows strong predictive performance at a communication delay time ε = 0.01–0.02 h, with RMSE = 2.59 × 10−2, MAPE = 33.34 × 10−2%, MAE = 1.70 × 10−2 Nm3/h, and R2 = 99.76 × 10−2. At delay time ε = 0.03 h, the ANN model yields RMSE = 2.74 × 10−2 Nm3/h, MAPE = 34.43 × 10−2%, MAE = 1.73 × 10−2 Nm3/h, and R2 = 99.73 × 10−2. Using the SVM model, the prediction error values at delay time ε = 0.01–0.02 h are RMSE = 2.70 × 10−2 Nm3/h, MAPE = 44.01 × 10−2%, MAE = 2.24 × 10−2 Nm3/h, and R2 = 99.74 × 10−2, while at delay time ε = 0.03 h they become RMSE = 2.67 × 10−2 Nm3/h, MAPE = 43.44 × 10−2%, MAE = 2.11 × 10−2 Nm3/h, and R2 = 99.75 × 10−2. With this precision, the ANN model for SOEC hydrogen production prediction has positive implications for air pollution control strategies and the development of cleaner energy technologies, contributing to overall improvements in air quality and the reduction of atmospheric pollutants.

Chemical Profiles of Particulate Matter Emitted from Anthropogenic Sources in Selected Regions of China

Particulate matter (PM) emissions from anthropogenic sources contribute substantially to air pollution. The unequal adverse health effects caused by source-emitted PM emphasize the need to consider the discrepancy of PM-bound chemicals rather than solely focusing on the mass concentration of PM when making air pollution control strategies. Here, we present a dataset about chemical compositions of real-world PM emissions from typical anthropogenic sources in China, including industrial (power, industrial boiler, iron & steel, cement, and other industrial process), residential (coal/biomass burning, and cooking), and transportation sectors (on-road vehicle, ship, and non-exhaust emission). The data was obtained under the same strict quality control condition on field measurements and chemical analysis, minimizing the uncertainty caused by different study approaches. The concentrations of PM-bound chemical components, including toxic elements and PAHs, exhibit substantial discrepancies among different emission sectors. This dataset provides experimental data with informative inputs to emission inventories, air quality simulation models, and health risk estimation. The obtained results can gain insight into understanding on source-specific PMs and tailoring effective control strategies.

Successful NH3 abatement policies and regulations in German agriculture

Anthropogenic ammonia (NH3) emissions, of which about 95 % are from agriculture, have led to environmental pollution, resulting in tremendous damage to human health and ecosystems. Thus, the NEC Directive 2016/2284/EU sets national reduction targets for NH3 emissions in individual EU countries. To implement the NEC Directive for NH3 emission targets, Germany amended the Fertilizer Application Ordinance in 2017 and 2020 (DüV_amended) and set the air pollution control regulation, Technical Instructions on Air Quality Control (TA_Luft). This study aimed to evaluate the impact of the DüV_amended on NH3 mitigation from applying livestock manure, digestates, synthetic nitrogen (N) fertilizers, and TA_Luft on housing and storage. This study showed that Germany reached the first national NH3 reduction target in 2020, as set by the NEC directive. The German DüV_amended, a significant policy change, has profoundly impacted NH3 emission mitigation from agriculture after 2017 by implementing measures aimed directly at NH3 reduction, reducing N surpluses, and improving N use efficiency. The reduction in NH3 emissions from synthetic N fertilizers between 2016 and 2022 contributed about 51 % to the decrease from the agricultural sector over the same period. Among the synthetic fertilizers, NH3 reduction from urea between 2016 and 2022 accounted for around 83 % of the total reduction from synthetic N, indicating that the NH3 emissions from urea fertilizer by reducing urea application and mandating urea to be incorporated immediately or to be stabilized with urease inhibitors played a crucial role in the sharp decrease in NH3 emissions over the last years in Germany. Achieving a high yield by lowering the synthetic N rate in this study strongly suggests that optimal reduction in N rate does not necessarily result in yield losses but rather in a pivotal relationship between the agronomic and environmental performance and indicates that the DüV_amended was an effective measure that can reduce the NH3 emissions.Over 80 % of Germany's annual agricultural NH3 emissions in 2021 and 2022 originated from livestock and digestates from energy crops. Mandatory close to the soil band application of slurry and digestates on cultivated cropland since 2020 reduced NH3 emissions. In addition, banning of broadcast application of slurry to grassland and manure incorporation within one hour on uncultivated soils will become mandatory in 2025 to comply with NEC 2030´s target of 29 % NH3 reduction relative to 2005. The recent German air pollution control regulation (TA_Luft) enforces abatement measures such as air purifiers in large poultry and pig housings and covered storage of slurry and digestate storages of large farms. The results of the German NH3 abatement strategy for synthetic N fertilizers may help reduce NH3 emissions worldwide, especially for countries consuming high amounts of urea fertilizers.

Volatile Organic Compound (VOC) Contamination in Hotel Rooms: A Pilot Study to Understand Sources and Health Risks

The COVID-19 pandemic drove the use of cleaning products, causing organic solvent contamination in hospitality environments. This pilot study investigated the presence and concentrations of volatile organic compounds (VOCs) in selected hotels in four different US cities with varying star ratings at the end of the pandemic period. Targeting 139 VOCs, 57 were detected across eight groups: alcohols, halocarbons, aromatics, alkanes, terpenes, carbonyls, ethers, and esters, in the indoor air. Alcohols were the most prevalent, especially in lower-rated hotels, suggesting higher use of cleaning supplies. Elevated levels of aromatics were detected in hotels rated under three stars, with a notable disparity compared to higher-rated hotels. Additionally, alkanes and terpenes such as n-tetradecane and d-limonene were consistently detected. Health risk assessment showed concentrations of all VOCs remained below their health criteria for customers. The cumulative cancer risk was 2.25 × 10−6 for hotel workers from chronic occupational exposure to eight carcinogenic VOCs, representing 1/3 of the lifetime risk from these chemicals in the ambient air. Cancer risks from individual VOCs ranged from 0.001 × 10−6 to 1.07 × 10−6, with chloroform accounting for nearly half of the cumulative risk. The findings underscore the need for careful selection and use of furnishings and cleaning supplies and for effective indoor air pollution control and management in hotel indoor environments.

The Impact of Environmental Regulation on Enterprise Green Innovation

This paper evaluates the real effects of the environmental regulation at the firm level. Using the implementation of Chinese Air Pollution Prevention and Control in 2013 as a quasi-natural experiment,difference-in-differences estimation shows that: (1) environmental regulation significantly improve the application of green innovation by firms, and this relationship is robust to different specifications and alternative measures; (2) three possible channels are the improved levels of the environmental protection subsidy, total factor productivity (TFP) and environmental protection investment of enterprises; (3) our findings are particularly pronounced in subsamples with the application of utility green innovation and state-owned enterprises (SOEs). Overall, this paper reveals the micro-mechanisms behind the real effects of environmental regulation on firm green innovation, thus providing timely implications for regulators concerned with environmental protection.

Does the Air Pollution Joint Prevention and Control Policy Work: Evidence from China

Does the Air Pollution Joint Prevention and Control Policy Work: Evidence from China

PM2.5 Induces Developmental Neurotoxicity in Cortical Organoids

There is mounting evidence implicating the potential neurotoxic effects of PM2.5 during brain development, as it has been observed to traverse both the placental barrier and the fetal blood-brain barrier. However, the current utilization of 2D cell culture and animal models falls short in providing an accurate representation of human brain development. Consequently, the precise mechanisms underlying PM2.5-induced developmental neurotoxicity in humans remain obscure. To address this research gap, we constructed three-dimensional (3D) cortical organoids that faithfully recapitulate the initial stages of human cerebral cortex development. Our goal is to investigate the mechanisms of PM2.5-induced neurotoxicity using 3D brain organoids that express cortical layer proteins. Our findings demonstrate that exposure to PM2.5 concentrations of 5 μg/mL and 50 μg/mL induces neuronal apoptosis and disrupts normal neural differentiation, thereby suggesting a detrimental impact on neurodevelopment. Furthermore, transcriptomic analysis revealed PM2.5 exposure induced aberrations in mitochondrial complex I functionality, which is reminiscent of Parkinson's syndrome, potentially mediated by misguided axon guidance and compromised synaptic maintenance. This study is a pioneering assessment of the neurotoxicity of PM2.5 pollution on human brain tissues based on 3D cortical organoids, and the results are of great significance in guiding the formulation of the next air pollution prevention and control policies in China to achieve the sustainable improvement of air quality and to formulate pollution abatement strategies that can maximize the benefits to public health.

Estimation of carbon sequestration potential and air quality impacts of biochar production from straw in China

Aiming to optimize straw resource utilization and to reduce air pollutant and greenhouse gas emissions in China, the environmental benefits of biochar production using straw and utilization need to be assessed. Two biochar production scenarios were studied: centralized production scenario (CPS) utilizing an industrialized production method with advanced air pollution control devices, and decentralized production scenario (DPS) based on a distributed production method of biochar at the village level, compared to an open-burning scenario (OBS). The potential GHG emission reductions under DPS, including the benefit of soil biochar application, were evaluated as 680 Tg CO2-eq yr-1, which was lower than the reductions under CPS (780 Tg CO2-eq yr-1). Although the attentional centralized production method of biochar has more potential environmental benefits, at present the distributed production method is more practical in China due to its convenience, management ease, and lower costs. Modeling on air quality in China showed that in comparison with OBS, DPS could reduce the average monthly PM2.5 concentration of key regions by 19%, and about 190 Tg yr-1 biochar could be produced with 150 Tg C yr-1 sequestered in biochar. Our findings support widespread biochar use in China for improved air quality and climate neutrality.

Quantitative Decoupling Analysis for Assessing the Meteorological, Emission, and Chemical Influences on Fine Particle Pollution

AbstractA comprehensive understanding of meteorological, emission and chemical influences on severe haze is essential for air pollution mitigation. However, the nonlinearity of the atmospheric system greatly hinders this understanding. In this study, we developed the quantitative decoupling analysis (QDA) method by applying the Factor Separation (FS) method into the model processes to quantify the effects of emissions (E), meteorology (M), chemical reactions (C), and their nonlinear interactions and impact on fine particulate matter (PM2.5) pollution. Taking a heavy‐haze episode in Beijing as an example, we show that different from the integrated process rate (IPR) and the scenario analysis approach (SAA) in previous studies, the QDA method explicitly demonstrate the nonlinear effects by decomposing the variation of PM2.5 concentration into individual contributions of E, M and C terms as well as the contributions from interactions among these processes. Results showed that M dominated the hourly fluctuation of the PM2.5 concentration. The C terms increase with increasing the level of haze, reaching maximum (0.37 μg m−3 h−1) at the maintenance stage. Moreover, our method reveals that there are non‐negligible non‐linear effects of meteorological, emission, and chemical processes during pollution stage, with the mean accounting for 50% of the increase in PM2.5 concentrations, which is often ignored in the current air pollution control strategies. This study highlights that the QDA approach can be used to gain insight into the formation of heavy pollution, and to identify uncertainty in numerical models.

Heterogeneity of population exposure to particulate matter pollution and its socioeconomic driving mechanism in Shaanxi Province, China

The rapid pace of economic and social development has led to a surge of particulate matter (PM) pollution incidents, which is detrimental to human health. Air quality in China has improved in recent years, but differences in PM exposure remain due to spatial heterogeneity in pollution and population. The identification of socioeconomic factors associated with PM pollution has attracted widespread attention. Current research predominantly targets cities, overlooking regional and county scale disparities. An analytical framework is established to evaluate the spatial heterogeneity in PM exposure and to identify the socioeconomic factors contributing to its pollution. The results revealed that: (1) the Theil index increased from 0.06 to 0.12, indicating a gradual increase in the inequality of PM exposure in Shaanxi Province. The differences within the Guanzhong Plain are obvious and the interregional differences substantially outweigh the intraregional variations. (2) Energy transition is pivotal in curbing air pollution in a region and economic growth consistently fuels particulate emissions. (3) For effective pollution mitigation, further emphasis on vegetation preservation and environmental inputs is imperative. The findings of this research provide decision support for optimizing air pollution control measures at the county scale.

Achieving Air Pollution Control Targets with Technology‑Aided Monitoring: Better Enforcement or Localized Efforts?

Weak enforcement of environmental regulations remains a global issue due to inadequate monitoring and misaligned incentives. This paper examines the effects of automated monitoring on achieving air pollution control targets amidst China’s war on pollution. Utilizing the staggered rollout process and remote-sensing data, we find local governments respond to the advanced monitoring system by strategically targeting areas near monitors, resulting in a 3.2 percent decrease in pollution adjacent to automated monitors compared to areas farther away. Furthermore, we observe heterogeneity in response across cities with varying degrees of preexisting data manipulation and among officials facing different incentives and public pressure. (JEL O13, O18, P25, P28, Q53, Q55, R11)

Health risks of environmentally persistent free radicals in atmospheric particulate matter during the spring festival travel season in Tainan, Taiwan.

Environmentally persistent free radicals (EPFRs) and polycyclic aromatic hydrocarbons (PAHs) are persistent pollutants in atmospheric particulate matter that are detrimental to human health. This study collected atmospheric particulate matter during and after the spring festival travel season in Tainan, Taiwan, from various locations and analyzed the carbon composition and PAH isomeric ratios to identify the sources. In this study, EPFR concentrations were measured using electron paramagnetic resonance spectroscopy, with the highest concentration found to be 3.04 × 10(12) spins/m3. EPFRs contained predominantly oxygen-centered radicals in PM2.5, which are mainly existed in PM1. The results show that EPFR concentrations on PM, measured per unit volume (spins/m3) or mass (spins/g), were highest during the spring festival travel season. The daily inhalation exposure to the sum of EPFRs and PAHs in PM2.5 was estimated to be equivalent to inhaling 0.11-0.15 cigarette tar EPFRs per day. This report is the first to document EPFRs in environmental atmospheric particulate matters in Taiwan, which has significantly contributed to local air pollution control and reduced exposure risks to public health in Tainan.

Who takes the lead: Synergistic emission reduction effects of proactive government and efficient market in atmospheric pollution mitigation

In environmental protection, government and market forces must work together. However, existing literature often separates the two and discusses their roles independently. Therefore, this study incorporates both the market and government into a unified analytical framework. It redefines government force as environmental regulation and market force as allocation efficiency in environmental protection. The study empirically examines the synergistic emission reduction effects of active government and efficient market on air pollution, using data from 272 prefectural-level cities in China from 2003 to 2019. The results show: (1) Both government and market interventions can significantly reduce air pollution levels, and their combination achieves a synergistic emission reduction effect.(2) Within this synergy, government intervention remains dominant, while the market plays a supportive role. (3) Analyzing the heterogeneous effects under different scenarios reveals that collaboration and mutual monitoring between the government and the market can effectively counteract the adverse effects of economic policy uncertainty and corruption on the environment. Furthermore, when a single entity undertakes environmental protection, it may encounter issues of diminishing effectiveness over time. However, the synergistic effects of government and market cooperation can mitigate these challenges. (4) The synergy exhibits a threshold effect based on the varying strengths of government and market forces. (5) Public participation enhances the synergistic emission reduction effect of government and market, acting as a vital complement to their environmental protection efforts. This study provides new empirical evidence on the synergistic effect of current environmental protection measures in improving air pollution control.

Future photovoltaic potential in India: navigating the interplay between air pollution control and climate change mitigation

Abstract India has set ambitious solar energy targets to meet its climate commitments. However, climate change, already evident in the country, poses significant challenges to solar power generation. Therefore, assessing the impact of climate change on future photovoltaic potential in India is essential. This study evaluates the mid-century (2041-2050) solar photovoltaic potential across Indian power grids using CMIP6 models under two scenarios: SSP2-4.5 (moderate climate action with intermediate air pollution) and SSP5-8.5 (weak climate action with strong air pollution control). The results indicate that the nationally averaged photovoltaic potential is projected to decrease by -2.3±0.6% (SSP5-8.5) to -3.3±0.9% (SSP2-4.5) compared to the 1985-2014 baseline, primarily due to reduced radiation and increased temperatures. Additionally, cell temperatures are expected to rise by 1.5±0.13°C (SSP2-4.5) to 2±0.11°C (SSP5-8.5), leading to efficiency losses and additional 18±5 days under SSP2-4.5 (26±3 days under SSP5-8.5) of efficiency de-rating, particularly in solar-rich regions. This translates to a loss of 600±160 GWh under SSP2-4.5 and 840±100 GWh under SSP5-8.5, based on the solar generation status of 2023-24. Overall, SSP5-8.5 projects a smaller reduction in photovoltaic potential, it also predicts greater temperature-induced efficiency losses compared to SSP2-4.5, due to aerosol direct effect and weak climate action. Finally, this assessment highlights the need for combined climate and pollution mitigation efforts to boost India’s photovoltaic potential and secure a sustainable, resilient energy future.

Forecasting mortality and DALYs from air pollution in SAARC nations

This study investigates the projected impact of air pollution on mortality and Disability-Adjusted Life Years (DALYs) across SAARC countries. Utilizing Time Series and Machine Learning methodologies such as Autoregressive Integrated Moving Average, Exponential Smoothing, and Neural Network, the research aims to accurately forecast the mortality and DALYs attributed to air pollution from 2020 to 2030. Statistical analyses reveal a consistent upward trend in deaths and DALYs during the forecasting period, primarily driven by Ambient Particulate Matter Pollution (APM) and Ambient Ozone Pollution (AOP). Comparing the predictive accuracy of the models, Neural Network outperformed other methods, as indicated by Root Mean Square Error (RMSE) values. Specifically, the study finds that deaths and DALYs due to Ambient Particulate Matter pollution are least prevalent in the Maldives, while India and Pakistan exhibit the highest rates, and deaths and DALYs due to Ambient Ozone pollution are lowest in the Maldives and highest in Bangladesh and Pakistan. Moreover, deaths and DALYs attributed to Household Air Pollution (HAP) are lowest in Pakistan and highest in Nepal. These findings underscore the urgent need for air pollution control measures and informed policymaking in SAARC countries to mitigate the escalating health burden associated with air pollution.

Spatial-temporal variations and Attribution analysis of SO2 concentration in Beijing-Tianjin-Hebei regions from 2013 to 2022

Based on the monitoring data of air pollutants in Beijing-Tianjin-Hebei regions from 2012 to 2022, the spatial-temporal distribution of SO2 concentration and main influencing factors were analyzed through multi-methods of Daniel trend test, KZ filtering and WRF/CMAQ model simulations. From 2013 to 2022, the annual averaged concentrations of SO2 in Beijing, Tianjin and Hebei regions were all in obvious downward trends, and all passed the Daniel trend test (α=0.01). The annual averaged concentration of SO2 in Beijing, Tianjin and Hebei regions decreased from 26.6~114.3μg·m-3 in 2013 to 3.0~11.0μg·m-3, with the decline rates fluctuating from 2.62~11.81μg/(m3·yr) while the decrease rate of SO2 in Beijing was the lowest. The average annual concentration of SO2 in Tangshan city decreased the most, reaching 92.3% and it changed to be the smallest, about 78.2% in Chengde City. The reduction of coal consumption in the Beijing-Tianjin-Hebei regions significantly reduced atmospheric SO2 emissions and directly reduced the regional average concentration of SO2. Meteorological factors were generally conducive to the diffusion of SO2 concentration during 2013~2022, and the meteorological factors contributed about 0.4~5.5% in 13 cities in Jingjinji area while the contribution of anthropogenic emission reduction was 94.5~99.6%. The inter-annual variation of meteorological factors in summer from 2013 to 2022 was not conducive to the diffusion of SO2 concentration on the whole, and the contribution changed to -52.6 ~ -1.0% in 13 cities. From June to August in summer under the easterly and southerly winds, the SO2 concentration in Beijing was basically twice that of the northerly and westerly winds. The contribution of southwest transport channel to SO2 concentration in Beijing was 33.5%, while it changed to 38.9% in the southeast transport channel. Therefore, strengthening the management and control of air pollutants in surrounding area of Beijing is helpful for Beijing to further reduce the levels of air pollutants and achieve targets of air quality improvement in the 14th Five-Year Plan period.

The Synergy Between CO2 and Air Pollution Emissions in Chinese Cities by 2060: An Assessment Based on the Emissions Inventory and Dynamic Projection Model

Synergizing air pollution control and climate change mitigation has been of significant academic and policy concern. The synergy between air pollution and carbon emissions is one of the measures to understand the characteristics and process of the air pollution–carbon synergistic control, which will also provide valuable information for collaboratively achieving Sustainable Development Goals (SDGs) (such as SDGs 11 and 13). This study establishes a systematic framework integrating emissions inventory and projection models, correlation mining and typology analysis methods to predictively evaluate the synergy and comprehensive coordination between air pollution and carbon dioxide (CO2) emissions in Chinese cities by 2030, 2050, and 2060 under different policy scenarios for air pollution and CO2 emissions control. The results reveal the significant effects of synergistically implementing clean air and aggressive carbon-reducing policies on mitigating air pollution and CO2 emissions. Under the On-time Peak-Net Zero-Clean Air and Early Peak-Net Zero-Clean Air scenarios, the total reduction and synergy for air pollution and CO2 emissions will be more significant, particularly by 2050 and 2060. This study is the first to integrate scenario projection and synergy evaluation in air pollution and CO2 research, providing a novel supplement to the air pollution–climate change synergy methodology based on co-benefit estimation. The methods and findings will also contribute to measuring the achievement and analyzing the interaction of the SDGs.