Climate Change In China Research Articles

Change of spermatophyte family diversity in distribution patterns with climate change in China

The global climate is undergoing extraordinary changes, profoundly influencing a variety of ecological processes. Understanding the distribution patterns and predicting the future of plant diversity is crucial for biodiversity conservation in the context of climate change. However, current studies on predictive geographic patterns of plant diversity often fail to separate the effects of global climate change from other influencing factors. In this study, we developed a spatial simulation model of spermatophyte family diversity (SSMSFD) based on data collected from 200 nature reserves covering approximately 1,500,000 km2, where direct anthropogenic disturbances to plant diversity and the surrounding environment are absent. We predicted the spermatophyte family diversity for all provinces in China in 2020, 2040, and 2080, considering the impacts of global climate change. On average, China currently exhibits 118 plant families per 25 km2, with a decreasing trend from southeast to northwest. When considering only the effects of global climate change, excluding direct anthropogenic disturbances, our results indicate that under the Shared Socioeconomic Path Scenarios (SSPs) 245 and 585, spermatophyte family diversity is projected to slowly increase in most Chinese provinces from 2021 to 2080. Notably, the increase is more pronounced under SSPs585 compared to SSPs245. Global climate change has a positive effect on plant diversity, in contrast to the negative impact of anthropogenic disturbances that often lead to declines in plant diversity. This research highlights the contrasting outcomes of future plant diversity under the sole influence of global climate change and the significant negative effects of anthropogenic disturbances on diversity.

Research on the legal regulation and improvement of carbon emission trading

Carbon emission trading system is a kind of environmental institutional arrangement to solve externalities through market mechanism, which is one of the most effective ways to deal with climate change in China and to control air pollution represented by haze pollution. In accordance with the requirement of "using system to protect ecological environment", China should position carbon emission trading system as the basic legal system of environmental protection in the new Environmental Protection Law, and from the aspects of reasonable determination of total carbon emission control mechanism, allocation of carbon emission trading quota, selection of pricing mechanism, and improvement of government supervision mechanism, etc. To improve China's emissions trading system.

CLIMATE CHANGE AND HOUSEHOLD ELECTRICITY CONSUMPTION INEQUALITY IN CHINA

Based on the micro-data of China’s Urban Household Survey, this paper investigates the impact of climate change on household electricity consumption inequality by using a two-way fixed effect model. The result reveals that households are more likely to purchase air conditioning (AC) and consume more electricity in response to extreme weather shocks. Furthermore, it is observed that high-income households are better equipped to mitigate the negative effects of extreme weather, as they possess a larger proportion of AC units and are more likely to acquire new ones to cope with extremely high temperatures. Finally, the study finds that extreme weather shocks exacerbate inequality in household electricity consumption.

Cotton yield responses to climate change and adaptability of sowing date simulated by AquaCrop model

The feedback mechanism of cotton yield to climate change is important knowledge for cotton planting planning and stable production. However, the impact of sowing date on cotton yield in China's main cotton producing areas under future climate change is still unclear. To deal with it, this study first evaluated the applicability of the AquaCrop model using actual observed cotton growth and yield data. Then, based on the 27 Global Climate Models (GCMs) multi-model ensemble data in the Sixth Coupled Model Intercomparison Project (CMIP6), the future climate changes in China 's main cotton producing areas from 2021 and 2060 (2040 s) and 2061–2100 (2080 s) under two typical Shared Socioeconomic Pathways (SSP) 2–4.5 and SSP5–8.5 were predicted. Finally, the effects of different sowing dates on cotton yield under SSP2–4.5 and SSP5–8.5 scenarios were simulated. The results showed that: (1) AquaCrop model had good applicability and it could accurately simulate cotton growth and yield. (2) The temperature under the SSP2–4.5 and SSP5–8.5 scenarios increased significantly compared with the baseline period (1985–2020). Precipitation during the cotton growth period mainly showed an increasing trend, but the spatial and temporal variability was large. The reference crop evapotranspiration (ETo) during the cotton growth period mainly showed a decreasing trend under the SSP2–4.5 (2040 s) scenario, while it mainly showed an increasing trend in other future periods. (3) The cotton yield under the SSP2–4.5 and SSP5–8.5 scenarios increased by an average of 10.51% and 13.67%, 14.76% and 28.04% in 2040 s and 2080 s compared to the baseline period (1981–2015), respectively. (4) Early sowing was beneficial to increase cotton yield, cotton yield sown on March 31 increased by an average of 5.32% compared to May 10. In conclusion, future climate change will have positive impacts on cotton production in China, and early sowing is an effective adaptation measure to cope with climate change.

Changes in photovoltaic power output variability due to climate change in China: A multi-model ensemble mean analysis

Solar photovoltaic (PV) power plays a crucial role in mitigating climate change. However, climate change may amplify weather variability and extreme conditions. The extreme conditions can increase the very low PV output and thereby increase the need for grid stabilization services. This study examined how weather variability affects PV power output in the near- (2025–2054) and far-future (2071–2100). The ensemble mean calculated using seven global climate models participating in the coupled model intercomparison project phase 6 for three different shared socioeconomic pathways (SSPs) (SSP126, SSP245, SSP585) was used for the assessment. The standard deviation of the monthly PV power output and the share of very low monthly PV power output were used to assess the variability of PV power output. The findings indicate that the summer PV power output was projected to decrease by 6%–8% in central and northern Tibet under a high emissions scenario (SSP585). The summer months with low PV power output were projected to increase in western regions of China, known for its abundant solar resources. The findings of this study provide valuable insight for energy planners to make up for the influence of future weather variability.

Predicting the Distributions of Morus notabilis C. K. Schneid under Climate Change in China

As one of the common mulberry tree species, Morus notabilis C. K. Schneid plays a significant role in various industries such as silkworm rearing, papermaking, and medicine due to its valuable mulberry leaves, fruits, and wood. This study utilizes the maximum entropy (MaxEnt) model to predict the potential distribution of M. notabilis in China under future environmental changes. By integrating the relative percentage contribution score of environmental factors with jackknife test analysis, important variables influencing the distribution of M. notabilis were identified along with their optimal values. The results indicate that Annual Precipitation (bio12), Precipitation of Driest Month (bio14), Min Temperature of Coldest Month (bio6), Temperature Annual Range (bio5–bio6) (bio7), Precipitation of Warmest Quarter (bio18), and Precipitation of Coldest Quarter (bio19) are the primary environmental variables affecting its potential distribution. Currently, M. notabilis exhibits high suitability over an area spanning 11,568 km2, while medium suitability covers 34,244 km2. Both current and future suitable areas for M. notabilis are predominantly concentrated in Sichuan, Yunnan, and Guizhou provinces, as well as Chongqing city in southwest China. Under the SSP5-8.5 scenario representing high greenhouse gas concentrations by 2050s and 2090s, there is an increase in high suitability area by 2952 km2 and 3440 km2, with growth rates reaching 25.52% and 29.74%, respectively. Notably, these two scenarios exhibit substantial expansion in suitable habitats for this species compared to others analyzed within this study period.

Exploring the relationship between land use/land cover and apparent temperature in China (1996–2020): implications for urban planning

In recent decades, rising air temperatures (AT) and apparent temperatures (AP) have posed growing health risks. In the context of China's rapid urbanization and global climate change, it is crucial to understand the impact of urban land use/land cover (LULC) changes on AP. This study investigates the spatial distribution and long-term variation patterns of AT and AP, using data from 834 meteorological stations across China from 1996 to 2020. It also explores the relationship between AT, AP, and LULC in the urban core areas of 30 major cities. Study reveals that AT and AP exhibit overall high spatial similarity, albeit with greater spatial variance in AP. Notably, regions with significant disparities between the two have been identified. Furthermore, it's observed that the spatial range of high AP change rates is wider than that of AT. Moreover, the study suggests a potential bivariate quadratic function relationship between ΔT (the difference between AT and AP) and Wa_ratio and Ar_ratio, indicating the presence of a Least Suitable Curve (LSC), Wa_ratio=0.263(±0.0269)-0.437(±0.0417)×Ar_ratio\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{W}}_{{\ ext{a}}} \\_{\ ext{ratio}} = {0}{{.263(}} \\pm {0}{{.0269)}} - {0}{{.437(}} \\pm {0}{{.0417)}} \ imes {\ ext{Ar}}\\_{\ ext{ratio}}$$\\end{document}. Urban LULC planning should carefully avoid intersecting with this curve. These findings can provide valuable insights for urban LULC planning, ultimately enhancing the thermal comfort of urban residents.

Who Sets the Agenda for Climate Change in China? A Longitudinal Analysis of Primary Actors that Drive Online Discussions on Social Media

ABSTRACT Multiple actors may harness social media to promote their own stances and influence others on climate change. Our investigation focused on second-level agenda-setting, determining which actors drove climate change conversations by attracting public attention to various topics. We examined the primary topics and actors involved in climate change discussions on Weibo (N = 1,090,420 posts) from 2010 to 2020. Our findings indicate that most discussions centered around environmental impact rather than culture, politics and government, or action advocacy. Celebrities, ordinary users, and civil society organizations were found to be influential for many topics, challenging the notion that governments and media lead the online climate change discourse. This study contributes to a deeper understanding of second-level agenda-setting in the digital age and highlights the importance of leveraging different social actors, especially celebrities, in China to achieve global climate change mitigation goals.

Long-Term Dynamics of Atmospheric Sulfur Dioxide in Urban and Rural Regions of China: Urbanization and Policy Impacts

High levels of sulfur dioxide (SO2) due to human activities pose a serious air pollution issue in China, especially in urban agglomerations. However, limited research has investigated the impact of anthropogenic emissions on higher SO2 concentrations in urban regions compared to rural areas in China. Here, we analyzed the trends in SO2 concentrations from 1980 to 2021 in China using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) dataset. SO2 column concentrations from the Copernicus Atmosphere Monitoring Service (CAMS) and the Ozone Monitoring Instrument (OMI) during the years 2007–2021 were also examined for validation and comparison purposes. Eight representative areas, including four urban regions (Pearl River Delta [PRD], Beijing-Tianjin-Hebei [BTH], Yangtze River Delta [YRD], and Sichuan Basin [SCB]) and four rural regions (Northeast Region [NER], Mongolian Region [MR], West Region [WR], and Tibetan Plateau Region [TR]) were selected for the analysis. Overall, a significant but fluctuating increase in SO2 concentrations over China was observed during 1980–2021. During 1980–1997 and 2000–2010, there was an increase in SO2 concentration, while during 1997–2000 and 2010–2021, a decreasing trend was observed. The average increase in SO2 concentration was approximately 16 times higher in urban regions than in the rural background. We also found that SO2 dynamics were highly associated with expansion of urban areas, population density, and gross domestic product. Nonetheless, since 2007, SO2 concentrations have exhibited a downward trend, which is mainly attributed to the air pollution policies implemented by the Chinese government. Our findings highlight the need for further studies on the impact of SO2 on regional climate change in China.

Response of Matching Degree between Precipitation and Maize Water Requirement to Climate Change in China

The synchronicity of rain and heat in the summer of China’s monsoon region provides sufficient water and heat resources for maize growth. However, the intra-annual distribution of precipitation and the probability of extreme precipitation have been inevitably altered by the ongoing climate change, thus affecting the matching degree between precipitation and crop water requirements (MDPCWR). Evaluating the extent to which the MDPCWR will change in the future is of great importance for food security and the sustainable management of water resources. In this study, considering that different growth stages of crops have different sensitivities to water stress, the AquaCrop model was used to calculate the MDPCWR more accurately. In addition, a cumulative distribution function-transform (CDF-t) method was used to remove the bias of 11 global climate models (GCMs) under two typical emission scenarios (SSP2-4.5 and SSP5-8.5) from phase six of the Coupled Model Intercomparison Project (CMIP6). A comprehensive investigation was conducted on how maize growth, water consumption, and the MDPCWR will respond to future climate change with CO2 concentration enrichment in the Huang–Huai–Hai (3H) region in China by driving a well-tested AquaCrop model with the bias-corrected GCMs outputs. The results indicate the following: (1) The CDF-t method can effectively remove seasonal bias, and it also performs well in eliminating the bias of extreme climate events. (2) Under the SSP2-4.5 scenario, the average maximum temperature will increase by 1.31 °C and 2.44 °C in 2021–2050 and 2051–2080, respectively. The average annual precipitation will increase up to 96.8 mm/year, but it will mainly occur in the form of heavy rain. (3) The increased maize evapotranspiration rate does not compensate for the decreased crop water requirement (up to −32 mm/year), due to a shorter growth cycle. (4) The farmland cultivation layer is not able to hold a significant amount of precipitation, due to the increased frequency of heavy rains, resulting in increased irrigation water requirements for maize over the next two periods, with the maximum value of 12 mm/year. (5) Under different scenarios, the projected future MDPCWR will decrease by 9.3–11.6% due to changes in precipitation patterns and crop water requirements, indicating that it will be more difficult for precipitation to meet the water demand of maize growing in the 3H region. The results can provide comprehensive information to understand the impact of climate change on the agricultural water balance and improve the regional strategy for water resource utilization in the 3H region.

Modeling the potential distribution of the energy tree species Triadica sebifera in response to climate change in China

As an important woody oilseed species in China, Triadica sebifera is not only concerned with the substitution of traditional energy sources, but also plays a considerable role in coping with energy shortages. Accurately predicting the potential geographic distribution of Triadica sebifera in China and understanding its ecological needs are crucial for alleviating the energy crisis and effectively implementing energy substitution strategies. In this study, the potential geographic distribution of Triadica sebifera in China at contemporary and future periods was predicted based on the distribution data of Triadica sebifera in China and the environmental factor variables by Maxent model and ArcGIS software. The combination of important factors governing the potential geographic distribution of Triadica sebifera was assessed by the contribution of environmental factor variables. The accuracy of Maxent model's predictions was assessed by AUC values, TSS values and Kappa statistics. The results show that: High AUC and TSS values indicate high accuracy and performance of the model. The crucial environmental factors limiting the potential geographic distribution of Triadica sebifera are the temperature factor (mean air temperature of the driest quarter), precipitation factor (precipitation of the coldest quarter, precipitation of the wettest month), and the intensity of human activities (hf). The total suitable area for Triadica sebifera is 233.64 × 104 km2, primarily located in Yunnan, Sichuan, Hubei, Guizhou, Jiangxi, Guangdong province and Guangxi Zhuang Autonomous Region; its high suitability area is 30.89 × 104 km2, accounting for 13.22% of the total suitable area, mainly distributed in Jiangxi, Sichuan and Hunan provinces in the shape of a cake. Under the four typical greenhouse gas emission concentration patterns in the 2050s and 2070s, the areas of high and medium suitable areas for Triadica sebifera will increase, while the area of its low suitable area will decrease. However, the total suitable area will remain relatively unchanged. Its potential suitable habitats show a trend of shifting towards lower latitudes and southeast regions. The study predicted the pattern of Triadica sebifera under different climate change conditions, which can provide guidance for future cultivation of Triadica sebifera as well as for biofuel development and utilization.

Social network platforms and climate change in China: Evidence from TikTok

The actions and policies enacted by today's youth hold profound implications for future generations, underscoring their pivotal role in advocating for climate issues. Younger cohorts exhibit heightened concern regarding climate change and are highly visible on social media platforms. Hence, this study aims to delineate the portrayal of climate-related news and disasters on TikTok. The research draws upon fifty TikTok accounts focused on climate-related content. Employing social network analysis, PageRank, and Superedge Rank methodologies, this investigation evaluates how TikTok users—called TikTokers—address climate change and its impact on social media. The assessment scrutinizes climate-related news, disasters, and the resultant networks to gauge the influence wielded by social influencers in disseminating messages. Results reveal that among the four key entities—internet influencers, government, scientists, and producers—internet influencers exert the most substantial influence on climate change news dissemination on TikTok, while the government plays an influential role in climate disasters. Like other social media platforms, TikTok is a valuable arena for gauging public sentiment on critical health concerns like global warming. Nonetheless, ensuring the reliability and depth of messages shared on TikTok necessitates the presence of credible experts who can deliver comprehensive and scientifically sound information within the platform's time constraints.

The ecological suitability area of Cirsium lineare (Thunb.) Sch.-Bip. under future climate change in China based on MaxEnt modeling.

Many kinds of medicinal ingredients occur in Cirsium lineare that have good clinical efficacy, conferring on this species its high medicinal development value. However, with a rapidly changing global climate, it is increasingly imperative to study the factors affecting the habitat distribution and survival of species. We predicted the current and future distribution areas of suitable habitats for C. lineare, analyzed the importance of environmental variables in influencing habitat shifts, and described the alterations to suitable habitats of C. lineare in different periods (modern, 2050s, and 2070s) and scenarios (RCP2.6, RCP4.5, and RCP8.5). The results show that, under the current climate, the total suitable area of C. lineare is about 2,220,900 km2, of which the highly suitable portion amounts to ca. 292,600 km2. The minimum temperature of the coldest month, annual precipitation, and mean daily temperature range are the chief environmental variables affecting the distribution of habitat for C. lineare. In the same period, with rising greenhouse gas emission concentrations, the total suitable area will increase. In general, under future climate change, the suitable habitat for C. lineare will gradually migrate to the west and north, and its total suitable area will also expand. The results of this experiment can be used for the conservation and management of the wild resources of C. lineare. We can choose suitable growth areas to protect the medicinal resources of C. lineare through insitu conservation and artificial breeding.

Spatial and temporal variation of net primary productivity of herbaceous marshes and its climatic drivers in China.

Herbaceous marshes are widely distributed in China and are vital to regional ecological security and sustainable development. Vegetation net primary productivity (NPP) is a vital indicator of vegetation growth. Climatic change can significantly affect NPP, but variations in NPP of herbaceous marsh and their responses to climate change in China remain unclear. Using meteorological data and MODIS NPP data during 2000-2020, this study analyzed the spatial and temporal variations of NPP and their responses to climate change in Chinese herbaceous marshes. We found that the annual NPP of herbaceous marshes in China increased significantly at a rate of 3.34 g C/m2/a from 2000 to 2020, with an average value of 336.60 g C/m2. The increased annual total precipitation enhanced the national average NPP, whereas annual mean temperature had no significant effect on the national average NPP. Regionally, precipitation had a significant positive effect on the NPP in temperate semi-arid and arid and temperate semi-humid and humid marsh regions. For the first time, we discovered asymmetry effects of daytime and nighttime temperatures on NPP in herbaceous marshes of China. In temperate humid and semi-humid marsh regions, increased summer daytime temperature decreased the NPP while increased summer nighttime temperature increased the NPP. In the Tibetan Plateau, increased autumn daytime temperature, as well as summer daytime and nighttime temperatures could increase the NPP of herbaceous marshes. This study highlights the different influences of seasonal climate change on the NPP of herbaceous marshes in China and indicates that the differential effects of daytime and nighttime temperatures should be considering in simulating the NPP of herbaceous marshes in terrestrial ecosystem models, especially under the background of global asymmetric diurnal warming.

Impacts of climate change on sustainable agricultural development and adaptation countermeasures

Sustainable agricultural development is crucial for ensuring food security. However, climate change is increasingly affecting sustainable agricultural development. The purpose of this paper is to explore the impact of climate change on sustainable agricultural development and sustainable agricultural technologies for adaptation to climate change. It first analyses the trends and characteristics of global climate change and the characteristics of climate change in China, highlighting the negative impacts of the increased frequency of extreme weather events on agricultural production. Subsequently, the negative impacts of climate change on crop production, water resource use and soil are examined in depth, and the challenges of climate change to sustainable agricultural development are comprehensively assessed. Finally, some feasible sustainable agricultural technologies to cope with climate change are proposed. For example, by adjusting the agricultural layout, locally appropriate crops can be grown at the appropriate time and climate. In addition, new seedlings with high adaptive capacity can be cultivated, and emphasis can be placed on growing high-quality crop varieties that are resistant to drought, high temperatures, pests and diseases, and adversity. It is also possible to strengthen farmland water conservancy infrastructure to improve the stability of crop production and the adaptive capacity of crops, and to better cope with global climate change.

How to recognize and characterize land use-based carbon emissions within city networks in the Beijing-Tianjin-Hebei region of China

Human-induced land modification is a significant contributor to carbon emissions. To facilitate the collective reduction of emissions within city clusters and promote eco-friendly urban development, this paper developed a research framework for analyzing carbon emissions. An empirical study was conducted within the Beijing-Tianjin-Hebei (BTH) region of China, focusing on the spatio-temporal patterns of carbon emissions and network features. The results showed that: (1) Carbon emissions among cities in the BTH region displayed significant variation from 2005 to 2020, with an increasing gap in carbon deficit. (2) Inter-city carbon emission correlation showed a declining trend, accompanied by pronounced spatial spillover effects in the region. (3) The network exhibited a bicentric pattern, centered around BJ and TJ, and the network correlations were more likely to occur between nearby developed cities, with poor regional synergistic emission reduction capacity. The implications of this study are valuable for promoting the establishment of an economic system that fosters green, low-carbon, and circular development. Furthermore, the findings contribute to the effective pursuit of carbon reduction and mitigation of climate change in China.

Climate change, cropland adjustments, and food security: Evidence from China

Climate change is expected to reduce crop yields, but knowledge on how it affects agricultural land use is still limited. This paper empirically investigates the induced cropland adjustments in responding to long-run climate change in China. Based on county-level data over several decades, we employ a moving-average specification that exploits within-county variation in local climate normals. We show that cropland expands with rising temperature (precipitation) in cold (dry) areas, while the effect is reversed in hot (humid) areas. The results are consistent with the “long-difference” estimates and robust to a host of different specifications. Besides, local crop mix also evolves with the changing climate. However, accounting for the crop-mix adjustments, climate change by the mid-century is still predicted to significantly lower the national calorie provision through induced cropland adjustments, and an average yield growth of 17.6% (21.2%) would be required to offset the associated loss under RCP 4.5 (RCP 8.5).

Exploring role of green financing in blockchain markets for climate change mitigation in China.

This study explores the potential of green finance as a strategic method to addressing climate change mitigation in China's blockchain industry. This research methodically analyzes a large dataset collected from many sources across the period between 1999 and 2020. Using a mixed approach of quantitative research and qualitative case studies, this study delves into the tangled web of relationships between alternative finance sources for green initiatives and the use of blockchain technology to promote more environmentally friendly business practices. The results provide light on how green finance and blockchain technologies might work together to boost China's climate change mitigation efforts, revealing fresh insights into the possible synergies and obstacles that erupt from this intersection. In response to the worsening climate problem, there is a pressing need for unconventional methods of financing that can lead holistic sustainable growth. Concurrently, blockchain technology's disruptive potential reverberates across numerous sectors. However, research on blockchain's potential for combating climate change, especially in conjunction with green funding systems, is still in its infancy. Intrinsic interest has motivated this study, which provides a new viewpoint on paths that might transform climate change mitigation in China by mapping the unexplored territory at the intersection of the green finance and blockchain sectors. This research hopes that by examining this interface, it will shed light on the hidden opportunities presented by the combination of green financing and blockchain innovation, allowing for more well-informed and effective decisions to be made in support of environmentally sustainable futures.

Role of fintech, green finance, and natural resource rents in sustainable climate change in China. Mediating role of environmental regulations and government interventions in the pre-post COVID eras

The recent advancement in financial technologies is impressive in various aspects. Nevertheless, emerging green finance literature highlights that due to such advancement, a limited positive impact is observed on green finance. This further raises various concerns regarding the gauged benefits from sustainability point of view. This curiosity leads to investigate the impact of fintech on environmental sustainability via mediating role of green finances and natural resource volatility. The study explores the proposed association from the perspective of governmental interventions and environmental regulation. To achieve the purpose of the study, a dataset comprising 10 years from 2013 to 2022 is collected from China. Based on different regression-based models, it is inferred that the development of fintech in China facilitates the reduction of carbon emissions and promotes climate quality. Green finance as a mediator enhances while natural resource volatility as a mediator deteriorates climate sustainability. Furthermore, industrial structure and environmental regulations also shed inverse impacts on environmental quality. Government interventions play a crucial role in the betterment of climate quality. It is also observed that fintech-associated carbon emission intensity varies with higher-order quartiles. Moreover, the impact of fintech on carbon emission is heterogeneous across different COVID-based sub-samples.

Co-drivers of Air Pollutant and CO2 Emissions from On-Road Transportation in China 2010-2020.

Co-controlling the emissions of air pollutants and CO2 from automobiles is crucial for addressing the intertwined challenges of air pollution and climate change in China. Here, we analyze the synergetic characteristics of air pollutant and CO2 emissions from China's on-road transportation and identify the co-drivers influencing these trends. Using detailed emission inventories and employing index decomposition analysis, we found that despite notable progress in pollution control, minimizing on-road CO2 emissions remains a formidable task. Over 2010-2020, the estimated sectoral emissions of VOCs, NOx, PM2.5, and CO declined by 49.9%, 25.9%, 75.2%, and 63.5%, respectively, while CO2 emissions increased by 46.1%. Light-duty passenger vehicles and heavy-duty trucks have been identified as the primary contributors to carbon-pollution co-emissions, highlighting the need for tailored policies. The driver analysis indicates that socioeconomic changes are primary drivers of emission growth, while policy controls, particularly advances in emission efficiency, can facilitate co-reductions. Regional disparities emphasize the need for policy refinement, including reducing dependency on fuel vehicles in the passenger subsector and prioritizing co-reduction strategies in high-emission provinces in the freight subsector. Overall, our study confirms the effectiveness of China's on-road control policies and provides valuable insights for future policy makers in China and other similarly positioned developing countries.