Reduction In China Research Articles

Can big data reduce urban environmental pollution? Evidence from China's digital technology experimental zone.

This paper investigates the impact of the digital economy on urban environmental pollution by analyzing panel data from 283 prefecture-level cities in China from 2011 to 2019 and using the digital technology comprehensive pilot zone of China as a natural experiment. The results demonstrate that digital technology has a significant effect in reducing pollutant emissions and empowering urban environmental governance. The findings are proven to be robust based on various tests, including parallel trend, PSM-DID, and placebo tests. Our analysis further shows that digital technology is particularly effective in controlling pollution in old industrial areas, high digital areas, and low energy efficiency areas. We also find that the national digital technology integrated pilot zone can mitigate environmental pollution in prefecture-level cities by increasing public environmental awareness and encouraging green technology innovation. Moreover, our research indicates that digital technology-enabled urban pollution control can contribute to the formation of a new urbanization pattern in China. These findings provide valuable insights for promoting the digital economy and achieving the goal of carbon reduction in China.

How Upgrading of Provincial Development Zones Reduces Urban Carbon Emission: Evidence from a Time-Varying DID Analysis

This study examines the impact of upgrading provincial development zones on urban carbon emission reduction in China, a vital policy instrument for achieving the nation’s dual objectives of economic growth and green development under the “carbon neutrality and carbon peak” framework. Utilizing panel data from 276 Chinese cities spanning 2006 to 2019, this study employs a time-varying difference-in-differences model to empirically assess the effects of these upgrades. The findings indicate that these upgrades significantly reduce urban carbon emissions through policy, agglomeration, and regulatory effects. The heterogeneity analysis further reveals that the policy’s effectiveness is amplified by higher levels of government participation, increased attention to environmental protection, and greater urban emission reduction pressures. Moreover, while the policy facilitates carbon emission reductions in neighboring cities through spatial spillover effects, it does not achieve synergistic control over multiple pollutants, showing no significant impact on other industrial pollutants emissions. These findings provide value insights for policymakers aiming to balance economic development with environmental sustainability.

The Synergistic Effect of the Carbon Emission Trading Scheme on Pollution and Carbon Reduction in China’s Power Industry

The synergistic effect of pollution and carbon reduction can alleviate the dual pressure of improving environmental quality and reducing greenhouse gas emissions in China. The carbon emission trading scheme (CETS) is a crucial market-based tool for carbon emission reduction, and understanding its synergistic impact on air pollution control is essential. Based on data from 30 provincial panels in China spanning from 2007 to 2021, we employ the difference-in-differences (DID) method to analyze the synergistic effects of the carbon emission trading plan in the power industry and its influence mechanisms are examined. We observe that the CETS significantly enhances both pollution and carbon reduction in China’s power sector, particularly demonstrating effective synergy in reducing CO2, SO2, and PM2.5 emissions. Furthermore, mechanism analysis reveals that the CETS achieves joint emission reductions by lowering energy consumption, influencing the power industry’s generation structure, promoting technological innovation among enterprises, and thereby realizing synergistic pollution and carbon reduction effects in China’s power sector. Heterogeneity analysis shows that regions with limited power facility, low electricity generation, and small economic scale exhibit the most pronounced synergistic benefits from pollution and carbon reduction efforts.

Differentiated strategies for synergistic mitigation of ammonia and methane emissions from agricultural cropping systems in China

Ammonia (NH3) and methane (CH4) emissions from agricultural cropping systems in China have substantially impacted environmental quality and climate change, which become the key sector for synergizing pollution control and carbon reduction. However, the experiences of synergistic NH3 and CH4 emission governance at fine scales in this sector are still lacking. Here, we estimated NH3 and CH4 emissions from agricultural cropping systems in China in 2019 and identified regional characteristics of these emissions using advanced spatial analysis techniques. Subsequently, we developed an innovative synergistic mitigation zoning identification method to establish targeted and spatially differentiated reduction measures, addressing a critical gap in mitigation strategies for agricultural cropping systems in China. The results showed that NH3 and CH4 emissions from the three most important crops were 3.04 Tg N yr-1 and 8.13 Tg C yr-1, respectively. NH3 and CH4 emissions exhibited the highest values in Eastern China, but the highest emission densities of NH3 (49.8 kg N ha-1 yr-1) and CH4 (394 kg C ha-1 yr-1) were observed in Northwest and South China, respectively. Further, bivariate local indicators of spatial association (LISA) maps revealed that the middle and lower reaches of the Yangtze River were hotspots for simultaneous high emissions of NH3 and CH4. Finally, based on the identified eight categories of zones, region-specific mitigation measures were proposed, including improved fertilization practices, irrigation methods, and straw management. These targeted, spatially differentiated mitigation strategies provide a reference framework and feasible approach for synergistic pollution control and carbon reduction in China's agricultural sector.

Pension Insurance Contribution and Corporate Maturity Mismatch of Investment and Financing: Evidence from Contribution Rate Reduction in China

ABSTRACT Pension insurance contribution is an important factor affecting corporate financial decision-making. This study investigates the influence of the pension insurance contribution rate reduction policy on the corporate maturity mismatch between investment and financing. We found that the pension contribution reduction policy reduces actual contribution burden of firms, and the average actual contribution rate decreases by 0.26% after the nominal rate is reduced by 1%. However, the policy also significantly aggravates the corporate maturity mismatch of investment and financing, which survives a battery of robustness tests. The positive effect of pension insurance contribution rate reduction on the maturity mismatch of investment and financing is more apparent in private, smaller-scale firms and in firms with higher ownership concentration and lower management incentive levels. The pension contribution reduction policy strengthens long-term investment tendency by reducing the actual contribution burden of companies and shortens debt maturity by increasing principal-agent costs. The results of this study provide a new perspective for understanding the mismatch between corporate investment and financing.

Greenhouse gas emissions from Chinese livestock sector can be decreased by one third in 2030 by the improvement in management

China is one of the largest contributors to global greenhouse gas (GHG) emissions, and the livestock sector is a major source of non-CO2 GHG emissions. Mitigation of GHG emissions from the livestock sector is beneficial to the sustainable development of the livestock sector in China. This study investigated the provincial level of GHG emissions from the livestock sector between 2000 and 2020 in China, to determine the driving factors affecting the provincial-level GHG emissions from the livestock sector, based on the logarithmic mean Divisia index (LMDI) model, which took into account of technological progress, livestock structure, economic factor, and agricultural population. Moreover, a gray model GM (1, 1) was used to predict livestock GHG emissions in each province until 2030 in China. The results showed that the GHG of Chinese livestock sector was decreased from 195.1 million tons (MT) CO2e in 2000 to 157.2 MT CO2e in 2020. Henan, Shandong, and Hebei provinces were the main contributors to the reduction in Chinese livestock GHG emissions, with their livestock GHG emissions reduced by 60.1%, 53.5% and 45.5%, respectively, in 2020 as compared to 2000. The reduction in GHG emissions from the Chinese livestock sector can be attributed to two main factors: technological progress and the shrinking of the agricultural laborers. In contrast, the agricultural economic development model with high input and high emissions showed a negative impact on GHG emission reduction in China’s livestock sector. Furthermore, the different livestock structure in each province led to different GHG reduction effects on the livestock sector. Under the gray model GM (1,1), the GHG emissions of the livestock sector will be reduced by 33.7% in 2030 as compared with 2020 in China, and the efficiency factor will account for 76.6% of the positive effect of GHG reduction in 2030. The eastern coastal region will be the main contributor to the reduction of GHG emissions from the Chinese livestock sector in 2030. Moreover, recommendations (such as upgrading livestock management methods and promoting carbon emission mitigation industries) should be proposed for the environmentally sustainable development of the livestock sector in the future.

Spatiotemporal Characteristics and Influencing Factors of the Synergistic Effect of Pollution Reduction and Carbon Reduction in China

Based on the use of the coupling coordination model to calculate the coupling coordination degree of carbon emission and pollutant control, the national, regional, and provincial spatiotemporal characteristics of the synergistic effect of pollution control and carbon emissions reduction in China were further analyzed, facilitating the crucial to identification of key areas. The fixed effects regression models and provincial panel data from 2006 to 2020 were used to explore factors contributing to better synergizing the reduction of pollution and carbon emissions in China. On this basis, the adjustment variable of R&D investment intensity was introduced, and the regulation effect model was constructed to further explore the influence mechanism of the synergistic effect of pollution reduction and carbon reduction. The results showed that： synergy exists between carbon emission reduction and the air pollution control system, the evolution of the synergistic effect of pollution reduction and carbon reduction in China presented an inverted "U"-shaped trend from 2006 to 2020, and there was spatial aggregation and a spatial spillover effect in pollution reduction and carbon reduction. The synergistic governance of carbon emission and pollutant control was still at a relatively low level. The carbon emission and air pollutant emission systems were still in an unstable and uncoordinated state. The results showed that： The degree of coordination of eastern China, central China, and western China decreased in turn. At the national level, energy consumption structure, per capita GDP, and the proportion of green investment were the main factors affecting the synergistic effect of pollution reduction and carbon. The heterogeneity of the influencing factors existed in the central, eastern, and western regions on industrial structure, energy consumption structure, energy utilization efficiency, per capita GDP, urbanization rate, the proportion of green investment, and transportation structure. The intensity of R&D played a significant moderating effect in the whole country, eastern, and central regions. However, no significant moderating effect was identified in the western region. In the eastern region, the urbanization rate, the proportion of green investment, and the transportation structure could not have a significant effect on the synergistic effect of pollution reduction and carbon reduction alone, and it must be coordinated with the intensity of R&D.

Health equity and synergistic abatement strategies of carbon dioxide and air pollutant emissions reduction in China’s eastern coastal area

Abstract Quantifying regional health disparities linked to air pollution is essential for enhancing air quality and attaining carbon neutrality objectives. Nonetheless, the efficacy of proactive policies in ensuring equitable health protection in China’s Eastern Coastal Area (ECA) remains uncertain. Here, we employed an integrated assessment model to assess the combined reduction of carbon dioxide (CO2) and atmospheric pollutants and their health repercussions in the ECA of China. Our findings reveal that 273 000 premature deaths are attributable to air pollution in 2060 in the ECA in the absence of mitigation policies. Conversely, carbon reduction policies are poised to curtail 80% of CO2 emissions, alongside reductions of 76% for NOx, 79% for SO2, 80% for PM2.5, 72% for VOCs, and 66% for NH3 emissions. Air pollution control policies could mitigate premature deaths by 19 600, while carbon reduction policies could potentially lower them by 50 800. The health inequality coefficient among provinces stands at 0.19, primarily attributable to significantly higher mortality rates in Hebei and Shandong. These findings yield valuable insights for crafting synergistic abatement strategies in similarly imbalanced developmental regions grappling with comparable environmental challenges.

Do Tradable Green Certificates Promote Regional Carbon Emissions Reduction for Sustainable Development? Evidence from China

The tradable green certificate (TGC) scheme is an important approach for mitigating carbon emissions within the context of a renewable energy development strategy and regional sustainable development. However, studies investigating the role of TGCs in encouraging carbon emissions reduction in China are limited and inconclusive due to ignoring the interference of other renewable energy policies and little distinguishing the impact of different green certificates. Using Chinese provincial data from 2013 to 2023, this study employs a difference-in-differences strategy to estimate the effect of the TGC policy on regional carbon emissions. The results reveal that the TGC policy significantly reduces provincial carbon emissions, and this reduction is predominantly contributed by certificate-electricity integration green certificates rather than certificate-electricity separation certificates. A 1% increase in the provincial trade volume of certificate-electricity integration green certificates can reduce total provincial carbon emissions by 0.8–1.3%. These findings hold across a series of rigorous robustness tests. This study also explains the different effects between certificate-electricity integration and certificate-electricity separation green certificates by the concept of additionality. To effectively reduce carbon emissions in the future, the TGC system must meet the requirement of additionality. These insights can provide reference for the improvement of TGC policy to better achieve the carbon reduction objective and sustainable development.

Process evaluation of an mHealth-based school education program to reduce salt intake scaling up in China (EduSaltS): a mixed methods study using the RE-AIM framework

BackgroundAn mHealth-based school health education platform (EduSaltS) was promoted in real-world China to reduce salt intake among children and their families. This progress evaluation explores its implementation process and influencing factors using mixed methods.MethodsThe mixed-methods process evaluation employed the RE-AIM framework. Quantitative data were collected from a management website monitoring 54,435 third-grade students across two cities. Questionnaire surveys (n = 27,542) assessed pre- and post-education effectiveness. Mixed-effects models were used to control cluster effects. Qualitative interviews (23 individuals and 8 focus groups) identified program performance, facilitators, and barriers. Findings were triangulated using the RE-AIM framework.ResultsThe program achieved 100% participation among all the third-grade classes of the 208 invited primary schools, with a 97.7% registration rate among all the 54,435 families, indicating high "Reach." Qualitative interviews revealed positive engagement from children and parents through the "small hands leading big hands" strategy. The high completion rate of 84.9% for each health cloud lesson and the significant improvement in salt reduction knowledge and behaviors scores from 75.0 (95%CI: 74.7–75.3) to 80.9 (95%CI: 80.6–81.2) out of 100 demonstrated the "Effect" of EduSaltS. The program's "Adoption" and "Implementation" were supported by attractive materials, reduced workload via auto-delivered lessons/activities and performance evaluation, and high fidelity to recommended activities, with medians 3.0 (IQR: 2.0–8.0)/class and 9.0 (IQR: 5.0–14.0)/school. Stable course completion rates (79.4%-93.4%) over one year indicated promising "Maintenance." Apart from the facilitating features praised by the interviewees, government support was the basis for the scaling up of EduSaltS. Barriers included the lack of smartphone skills among some parents and competing priorities for schools. Unhealthy off-campus environments, such as excessive use of salt in pre-packaged and restaurant foods, also hindered salt reduction efforts. The program's scalability was evident through its integration into existing health education, engagement of local governments and adaptation across various mobile devices.ConclusionsThe mHealth-based school health education program is scalable and effective for public salt reduction in China. Identified barriers and facilitators can inform future health program scale-ups. The program's successful implementation demonstrates its potential for broader application in public health initiatives aimed at reducing dietary salt intake.

The effects of green finance on pollution and carbon reduction: Evidence from China’s industrial firms

Reducing pollution and carbon emissions is important but requires a large amount of capital. Green finance is becoming an important market-based instrument. Few literatures have focused on the direct impact of green finance on corporate environmental performance. This study investigates the effects of green finance on air pollution and carbon reduction in China’s industrial firms from 2008 to 2015. Results show that green finance promotes CO2 and air pollution reduction. Moreover, green finance has a synergistic effect on SO2 and carbon reduction, but not on reduction of dust and carbon emissions. Our findings suggest that green finance reduces emissions by improving corporate energy utilization efficiency. Furthermore, we find that the effects of green finance on emission reduction are more significant among non-state and non-listed firms. These findings have important implications for the development of green finance and synergistic reduction of air pollutants and carbon.

Potential and Pathways of Carbon Emission Reduction in China’s Beef Production from the Supply Chain Perspective

Potential and Pathways of Carbon Emission Reduction in China’s Beef Production from the Supply Chain Perspective

Can industrial intelligence promote carbon emission efficiency? --empirical research based on the Yangtze River Economic Belt

The rapid development of intelligent technology characterized by robots under the fourth scientific and technological revolution provides a favorable opportunity for the accurate decision-making of urban pollution control and the effective achievement of the goal of carbon emission reduction in China. This research uses the robot penetration rate as a representative and characteristic index of industrial intelligence development, based on panel data from 108 cities in the Yangtze River Economic Belt (YEB) from 2006 to 2020. It then uses panel quantile regression, spatial measurement, and threshold effect models to provide a more thorough theoretical and empirical discussion of the impact, mechanism, and spatial effect of industrial intelligence development on urban carbon emission efficiency (CEE). Urban CEE may be greatly increased with the use of industrial intelligence, and this finding remains true even after endogeneity and robustness tests are controlled; From an action mechanism perspective, industrial intelligence advances technology, optimizes industrial structure, and ultimately enhances regional CEE; There is a Matthew effect on the degree of development of carbon emission efficiency, and the impact of industrial intelligence on CEE is more pronounced in non-resource-based cities and the lower portions of YEB; Urban CEE increases positively with the spatial spillover impact of industrial intelligence development. The ability for regional sustainable development will be significantly increased if cross-regional cooperative prevention and control of environmental governance can be successfully achieved. This study verifies the enabling effect of industrial intelligence development on the improvement of urban CEE, and provides enlightenment for China to improve industrial intelligence development strategies and policies to achieve regional high-quality development.

Characterization and sources of carbonaceous aerosol in ambient PM1 in Qingdao, a coastal megacity of northern China from 2017 to 2022

Organic carbon (OC) and elemental carbon (EC) are major chemical constituents of ambient submicron particles (PM1) and have substantial implications for air quality, climate dynamics, and human health. Long-term observations of daily mean mass concentrations of OC and EC in PM1 were conducted in Qingdao, a typical coastal megacity in northern China, in autumn and winter from Nov. 2017 to Jan. 2023. The variety in OC and EC concentrations under the active emission reduction policies of long-term carbon reduction in China, combined with the impact of the COVID-19 pandemic, were analyzed. OC and EC concentrations decreased noticeably from 8.28 ± 4.59 μg m−3 and 2.00 ± 1.17 μg m−3 during pre-COVID-19 pandemic to 6.34 ± 3.82 μg m−3 and 1.87 ± 1.01 μg m−3 during post-COVID-19 pandemic, respectively. The XGBoost-SHAP model indicated that emission sources had the most significant effect on OC and EC concentrations, followed by meteorological factors. Unfavorable meteorological conditions and a substantial increase in emissions are responsible for the increase of OC and EC concentration in winter. Potential source contribution function results indicated that the southern, eastern, and central Shandong regions were the primary source areas for transporting high concentrations of carbonaceous components. Positive matrix factorization analysis suggested that carbonaceous aerosols in Qingdao predominantly originated from coal/biomass combustion (54.75%–81.78%) and local vehicle emissions (8.72%–28.73%). Compared with that before COVID-19, coal/biomass combustion's contribution to OC and EC decreased by 19% after the COVID-19 pandemic. The contribution of vehicles increased by 110%, possibly due to the increase in motor vehicles and the rapid recovery in diesel consumption in freight transportation. Prohibiting biomass burning, such as open burning of straw, and measures such as promoting low-carbon and clean production of coal-fired industrial furnaces might have played a key role in reducing OC and EC levels. These results contribute to a deeper understanding of the concentration levels and sources of carbonaceous components in PM1 and provide theoretical guidance for environmental management.

Plant-level green transformation strategy in China's cement industry: Considering energy conservation and emission reduction co-benefits

The green transformation strategy is critical for achieving the emission mitigation targets in China's cement study. However, previous studies have focused on the nationwide industry level and overlooked the significant differences in the cement plants, remaining the risk of difficulties in implementing the proposed strategy. To overcome this problem, this study proposes a framework for plant-level green transformation strategy based on the industry-level emission mitigation pathway and a plant-level cement database. The strategy indicates the cement plants that need to be shut down, be retrofitted, and promote technologies. Results show that 1005 clinker and 3706 cement production plants should be shut down or retrofitted, while 60%+ of the plants should take denitrification and dust removal technologies in 2019–2035. The plant-level strategy can achieve energy conservation and CO2, SO2, NOx, and PM reductions by 40.0–79.9%, demonstrating the existence of the co-benefits. As only 4.1%–25.0% of the plants contribute half of the energy conservation and emission reduction effects, the plant-level strategy leads to significant spatial heterogeneity of the co-benefits. For example, the energy conservation and emission reduction potential in the five largest cement producer cities varies from over 30%. In addition, the total fixed investment is 99.6 billion Chinese Yuan (CNY) and the highest cost is 12.8 billion CNY/a, which will not cause heavy economic burdens to the industry. This study bridges the industrial-level planning and plant-level implementation of the green transformation strategy, whose methodology supports the synergic energy conservation and emission reduction in China's cement industry and beyond.

Impact of green innovation on carbon reduction in China

Green innovation directly encompasses the two major concepts of green and innovation in the new development concepts, which provides a powerful driving force to support Chinese-style modernisation. This paper empirically tests the relationship between green innovation and carbon emission intensity using a double fixed effects model. Based on the panel data of 30 provinces in China, the mediation effect model of “green innovation-big data-carbon emission” is constructed. The result shows that green innovation has a noticeable direct negative effect on urban carbon emission intensity. The conclusions are robust after considering measurement errors and endogenous problems. Furthermore, it is found that big data plays a significant role in strengthening the relationship between green innovation and carbon emission intensity. The findings in this study not only advance the study on green innovation and carbon emissions but also provide a new perspective on the role of big data.

Does internet usage drive antibiotic reduction in China's livestock industry? Evidence from Chinese duck farmers

The reduction of antibiotics in livestock farming is of great significance for ensuring the safety of meat-derived food and reducing farming pollution. Agricultural technology extension can precisely, efficiently, and cost-effectively provide frontline concepts and technologies for antibiotic reduction to farmers. However, there is still a lack of empirical evidence on the impact of Internet usage on antibiotic reduction among farmers. Based on survey data from 1005 duck farmers in 9 provinces across China, this study empirically analyzes the impact of Internet usage on the reduction of antibiotics among duck farmers and its underlying mechanisms. The results indicate that Internet usage significantly affects antibiotic reduction among farmers, a conclusion that holds true after endogeneity testing and robustness testing. Cognition of ecological benefits and cognition of health benefits are crucial pathways for promoting antibiotic reduction in farming, and Internet usage significantly enhances farmers' cognition of ecological and health benefits. Regarding information effectiveness, technical training exhibits complementary effects on Internet usage. The marginal effects of Internet usage on antibiotic reduction among farmers are significantly enhanced when the quantity and quality of family labor are at a medium level or higher. Internet usage has a substantial impact on antibiotic reduction among farmers when the quantity of family labor is at a medium level or higher, and information effectiveness can effectively promote antibiotic reduction in farming. There is no apparent heterogeneity in the impact of information effectiveness on antibiotic reduction among farmers of different quality groups.

Impacts of the pilot policy for carbon emissions trading on pollution reduction in China

Global environmental problems are worsening. Among various regulatory measures, market-oriented approaches are most favored by governments worldwide. Using provincial panel data from 2004 to 2020, a multi-period DID model was hereby constructed to empirically study the pollution reduction effects of the pilot policy for carbon emissions trading in China. Findings of this paper could be listed as follows: (1) The pilot policy has achieved notable reductions in waste gas and solid waste, although its effect on wastewater pollutants has been less pronounced; (2) Pollution reduction in the pilot regions can be achieved by optimizing the energy consumption structure; (3) Significant variations in pollution reduction effects are observed between the Northern and Southern pilot regions, with notably stronger policy effects in the north across various pollutants compared to the south. Overall, this paper offers pertinent policy recommendations to aid the Chinese government in enhancing its carbon market.

Poverty or pollution: The environmental cost of E-commerce for poverty reduction in China

Pro-poor policies can have economic benefits, but they may also have environmental costs. This paper examines the impact of China's “E-commerce into Countryside” project (the ECC project), one of the world's largest targeted poverty alleviation strategies, on local air quality. The project covers approximately 100 million poor people. Using a set of difference-in-differences identification strategies, we find that the pro-poor ECC policy has consistently and significantly contributed to local air pollution, despite its role in fighting poverty. The decline in local air quality is primarily caused by the increase in rural enterprises, destruction of vegetation, and traffic pollution resulting from the intention to sell more agricultural products to the city. Pro-poor policymakers face the challenge of balancing poverty reduction with environmental protection during the process of sustainable development. When making policy decisions, it is important to consider local environmental regulations, ecological vulnerability, and potential adaptation strategies in order to weigh economic benefits against environmental costs.

Global health benefits of shipping emission reduction in early 2020

The impact of COVID-19 lockdown on the absolute concentration of air pollutant has been widely investigated, whereas the impact of lockdown on global shipping-related air pollutants still remained poorly understood because the contribution of individual source cannot be observed directly. In our study, we employed an efficient chemical transport model (GEOS-Chem) to quantify the shipping-related PM2.5, NO2, and O3 levels in early 2019 and 2020, and assessed the impact of COVID-19 lockdown on global shipping-related air pollutants and health effects. The result suggested that shipping-related global PM2.5, NO2, and O3 levels reduced by 14%, 85%, and 1%, respectively. Furthermore, the decreasing ratios of air pollutants in difference regions often suffered from large spatial discrepancy. PM2.5 and NO2 levels in China, India, Europe, and the United States decreased by 6.5% (NO2: 9%), 7.4% (8%), 11% (8.6%), and 15% (10%), which could be caused by dense shipping activities during the non-lockdown period. For O3 concentrations, the shipping-related concentrations in China, India, Europe, and the United States showed 0.7%, −12.9%, 16.6%, and −4.8% during lockdown period, respectively. The relatively slight O3 reduction might be linked with more significant decrease of NOx emission than VOCs. The changes of air pollutant concentrations inevitably led to the variations of health benefits. Globally, the all-cause mortalities caused by shipping-related PM2.5 exposures reached 40,464 (95% CI: 26,546, 54,382) and 39,035 (95% CI: 25,135, 52,935) cases in early 2019 and 2020, respectively. The combined health benefits of PM2.5, NO2, and O3 linked with shipping emission reduction in China, India, Europe, and the United States reached 476 (95% CI: 131, 822), 3341 (95% CI: 3,177, 3505), 2194 (95% CI: −970, 5358), and 311 (95% CI: 242, 379), respectively. Our study confirms the potentially considerable effects of shipping emission on multiple air pollutants and health impacts, which could provide valuable information for air quality management.