Spatial Econometric Models Research Articles

The Temporal and Spatial Evolution and Influencing Factors of the Coupling Coordination Degree Between the Promotion of the “Dual Carbon” Targets and Stable Economic Growth in China

Coordinating the relationship between “dual carbon” targets and stable economic growth is crucial for promoting high-quality development in China. This study utilizes the coupling coordination model, kernel density estimation, and spatial econometric models to explore the temporal and spatial evolution characteristics and influencing factors of the coupling coordination degree between the promotion of the “dual carbon” targets and stable economic growth in 287 Chinese cities from 2011 to 2021. The results indicate that, in terms of temporal evolution, the promotion of China’s “dual carbon” targets increases yearly, while stable economic growth follows a “year-on-year increase—short-term decline—sustained recovery” pattern with the coupling coordination degree fluctuating upward. Regarding spatial evolution, the coupling coordination degree between the promotion of the “dual carbon” targets and stable economic growth in China presents a “higher in the east, lower in the west” spatial pattern, with varying gradient effects and polarization across the country and its regions. Influencing factors include government intervention, environmental regulations, energy efficiency, financial development, and R&D investment intensity. These findings provide scientific insights for addressing the mutual constraints between “dual carbon” targets and stable economic growth.

Analyzing spatiotemporal features of Suzhou's old canal city: an optimized composite space syntax model based on multifaceted historical-modern data

AbstractRivers and road systems play crucial roles in urban development and in shaping the vitality of cities. The present study focuses on the spatiotemporal development patterns of canal cities. Taking Suzhou as an example, employing various spatial measurement methods combined with multidimensional spatiotemporal data, it clearly demonstrates the urban morphological patterns and societal characteristics related to the road and river network systems at different stages of urban development. Utilizing data extracted from historical and modern maps of Suzhou and employing the YOLO (You Only Look Once) algorithm, this study establishes a spatiotemporal dataset for Suzhou's ancient city, a representative Chinese canal city. An optimized space syntax algorithm for public service facilities, utilizing Python library like Geopandas, Numpy, is proposed to analyze the river and road system's impact on historical development and urban morphology. With multiple spatial econometric models applied to maps from various periods, this research explores the following findings: (1) By controlling rivers as a variable, it quantitatively confirms that rivers were crucial components of urban systems in ancient cities, playing a significant role in urban development and activities, though gradually overlooked in modern times. (2) Public service facilities of different types demonstrate patterns of Accessibility and Integration within the river-road system across various periods. (3) Changes in the distribution of public service facilities correspond to phased shifts in the center of Suzhou’s ancient city, mutually validating the authenticity of realistic paintings, historical maps, and the methodologies used in this study. This study emphasizes a broader historical and spatiotemporal perspective, augmented by quantitative research methods. It investigates the distribution and developmental characteristics of various types of public service facilities across different periods. The research aim is to understand the impact of river and road systems on urban development, as well as the morphological and social changes in historical cities that arise from urban activities.

The impact of R&D factors flow and regional absorptive capacity on China's economic growth: Theory and evidence.

Innovation is the source of economic growth. Innovation in a region comes from its own knowledge creation and knowledge spillovers from other regions. Previous studies showed that R&D factors flow benefits knowledge spillover, thereby promoting economic growth. But these studies ignored the impact of a region's knowledge-absorptive capacity on knowledge spillovers. Ignoring the impact of regional absorptive capacity means that the knowledge spillover from the same R&D factors flow is the same, clearly inconsistent with reality. This thesis analyzes the impact of R&D factors flow on economic growth and explores the moderating effect of regional absorptive capacity on the relationship between R&D factors flow and economic growth from theoretical and empirical perspectives. First, we construct a knowledge creation and diffusion model of the new economic geography, including regional absorptive capacity, and analyze the theoretical logic of the flow of R&D factors and regional absorptive capacity influencing economic growth. Second, we employ spatial econometric models to examine the impact of R&D factors flow and regional absorptive capacity on economic growth, utilizing panel data of 30 provinces in China from 2008 to 2021. The results demonstrated a spatial positive correlation between regional economic growth in China. The R&D factors flow could have significantly promoted not just a region's direct economic growth, but also the economic growth of surrounding regions via spatial spillover effects. Furthermore, the stronger the regional absorptive capacity, the greater the direct effects and spatial spillover effects of the R&D factors flow on economic growth. The novelty of this article is to introduce regional absorptive capacity into the theoretical model, refine the methodology for assessing regional absorptive capacity in empirical research, and examine its moderating effect between the inflow of R&D factors and regional economic growth. This article reveals that the positive impact of the inflow of R&D factors on spatial spillovers and economic growth varies depending on regional absorptive capacity. According to the conclusions above, enhancing regional absorptive capacity is equally important as facilitating the flow of R&D factors. Therefore, it is vital for a region to strengthen its absorptive capacity for new knowledge while promoting R&D factors flow. The study provides valuable policy insights for accelerating the flow of innovation factors, enhancing regional absorptive capacity, and consequently promoting long-term sustainable economic development in the region.

Revesting the spatial spillover effects of renewable energy in curbing carbon emissions: Evidence from China

Renewable energy is fundamental to achieving China's peak carbon and carbon neutrality targets. Despite the extremely rapid growth in the share of renewable energy generation in terms of provincial-level regions, the impact of renewable energy generation on carbon emission reduction and whether this association is spatially correlated have not been fully recognized. To address this issue, this paper explores the spatial impact effect of renewable energy applications on carbon emissions using Chinese provincial panel data from 1990 to 2020 and a multi-panel spatial econometric model. The results show that the contribution of emission reduction mainly comes from the provincial clean energy mix, while the exclusion of out-of-province power plants also helps to curb their carbon emissions. In addition, in the context of large-scale penetration of renewable energy, grid infrastructure for cross-provincial power trading will contribute to cross-provincial emission reduction. Regulators should take measures to promote coordination of emission reduction policies among provinces in a unified national carbon market, rather than simplifying the allocation of responsibilities in provincial markets. Based on the findings of this paper, there is a need to rationalize and optimize the geospatial distribution of renewable energy projects in the future, so as to maximize the potential of renewable energy to contribute to carbon emission reduction.

Urban–rural links in relaunching left-behind places: the case of Portuguese municipalities

Abstract During the last few decades, the gap between the most prosperous metropolitan areas and the rural areas has widened, especially since the 2008 crisis. This gap has been particularly relevant in relation to population and employment. However, the bi-directional links in terms of population and employment between rural places and the most urbanized areas have been partly overlooked by the literature. At the same time, recent studies have brought the plight of “left-behind” areas to the forefront, highlighting rural as well as other types of “left-behind” places as focal points of discontent. In the context of the debate on left-behind areas, and in an attempt to address the decline in population and employment that they are experiencing, this article proposes a strategy based on the spatial interactions among the different types of territories. Specifically, we develop a spatial econometric model capable of testing all interactions among different territorial typologies based on their degree of urbanization. We apply the model to 278 continental municipalities in Portugal during the period 2010–8. The model estimates have implications for understanding the dynamics of territorial interactions in Portugal, highlighting the crucial role of semi-urban municipalities. The results reveal the positive and significant connections between change in employment in semi-urban municipalities and population change in both neighboring rural and urban municipalities. The findings suggest that semi-urban/rural diffusion should be promoted as a policy approach to left-behind rural places in Portugal.

Coupling coordination mechanism between ecological protection and high quality development in the Yellow River Basin

Abstract In the issue of ecological protection and high-quality development in the Yellow River Basin, this study deeply discusses the influencing factors of the coupling and coordination level between the two systems by calculating the ecological environment protection and high-quality development, as well as the ecological protection evaluation index system, and using spatial econometric models. The results showed that the average value of the comprehensive evaluation index for ecological protection in the Yellow River Basin grew from 0.253 to 0.351 (2014–2023), and the overall coupling coordination degree was in the range of 0.496 to 0.582. This indicated that the country’s emphasis on protecting the Yellow River ecosystem and the implementation of its policies had achieved significant results, and the overall environmental condition of the system had been significantly improved. At the same time, the comprehensive evaluation index for high-quality development in the Yellow River Basin also showed a fluctuating upward tendency, indicating the mutual connection between economic development and ecological environment protection. Tests had shown that the use of oil and water resources had a negative impact on the system degree of coupling and coordination, while other factors had a positive impact. This study provides useful references for environmental protection and sustainable development, and provides guidance for policymakers to achieve ecological protection and high-quality development in the Yellow River Basin.

Impact of Short-Haul High Speed Rail Commuting on Land Use and Spatial Structure in a Multi-Centre Metropolitan Area

Owing to the enhanced accessibility afforded by high-speed rail, the relationship between megacities and their neighboring cities has grown closer. Megacities exert a significant influence on the land use of neighboring cities. This study employs a spatial econometric model to investigate the direct impact and spatial spillover effects of high-speed rail on urban land values, based on urban panel data from China’s Yangtze River Delta region (2006-2020). The results revealed that shorter commuting times and improved frequency of service had a more substantial effect. Additionally, due to alterations in land values, there is a distinct preference tendency for urban land use attributes. Therefore, the city’s spatial organization has transformed, and its center of gravity has shifted as well. This study provides crucial theoretical justifications and empirical evidence to fill the gaps left by previous research on the effects of short-haul high-speed rail commuting on urban housing prices and land use. The study also offers valuable insights for strategic planning and implementation aimed at promoting urban development and urban agglomeration construction through HSR construction.

Spatiotemporal Relationship Between Land Subsidence and Ecological Environmental Quality in Shenfu Mining Area, Loess Plateau, China

The exploitation of coal resources has caused problems such as ground deformation, affecting the ecological environment. Spatiotemporal varying characteristics between land subsidence and ecological environmental quality (EEQ) are an important research hotspot. Using the SBAS-InSAR method, 64 Sentinel-1 images were utilized to monitor land subsidence in the Shenfu mining area, one of China’s largest coal source regions. And the remote sensing ecological index (RSEI) was used to monitor and evaluate EEQ of the Shenfu mining area. Global and local spatial autocorrelation methods were used to assess the spatial aggregation degree and change patterns over time. Spatial Econometric Models were employed to explore the impacts of land subsidence on EEQ. The results showed the following: (1) The average RSEI values in the Shenfu mining area were 0.531, 0.488, and 0.523 in 2016, 2018, and 2020, respectively; there was a slight downward trend in EEQ. The permanent scatter (PS) point deformation rate ranged from −353.40 mm/year to +246.24 mm/year, with average deformation rates of 0.1642, 0.2181, and 0.2490 mm/year, respectively. (2) There was a significant correlation and spatial agglomeration effect between land surface subsidence and EEQ. Low–high, high–low, and low–low clusters were the main types of relationships, indicating that land subsidence primarily has a negative spatial impact on the ecological environment. (3) The relationship between land subsidence and EEQ varied spatially in the Shenfu mining area at 500 × 500 grid units. This research can provide scientific guidance for disaster prevention and sustainable development in mining areas by considering long-term differences in ecological environmental quality and its correlation with land subsidence.

Agglomeration externalities or network externalities? Explaining productivity in Chinese urban regions

ABSTRACT This paper explores the relative importance of agglomeration externalities and network externalities in explaining regional productivity through the lens of a polycentric development framework specific to China. Using enterprise investment data, a spatial econometric model and an instrumental variables strategy, we find that both externalities are important in explaining regional productivity. There are no interaction effects between agglomeration and network externalities, with the latter being more prominent in urban regions with higher levels of polycentricity. Compared to agglomeration externalities, which are geographically confined, network externalities can generate spatial spillovers.

Impact of environmental information disclosure on environmental regulation intensity: evidence from 113 cities in China

Presently, the driving factors for environmental regulatory intensity, especially environmental information disclosure, remain unclear. Exploring the causal relationship between the two has an important guiding value for governments to achieve sustainable development. This research empirically examines the impact of environmental information disclosure on environmental regulatory intensity, and the possible action mechanisms and boundary conditions based on panel data of 113 Chinese cities from 2010 to 2020 using fixed-effects model, quantile regression model, moderating effect model, and spatial econometric models. The conclusions suggest that, first, a 1% increase in environmental information disclosure promotes a positive increase in environmental regulatory intensity of about 0.171%. Second, The regression coefficients of environmental information disclosure in the 10th, 25th, 50th, 75th and 90th quartiles are 0.489, 0.401, 0.443, 0.365 and 0.281 respectively, showing a decreasing trend. Third, transportation infrastructure and the resident’s education level exhibit positive interactions, with interaction term regression coefficients of 0.006 and 0.070, respectively; foreign direct investment exhibits a negative interaction, with coefficient of -0.029. Fourth, both environmental regulation intensity and environmental information disclosure show positive spatial correlations, with a 1% increase in environmental regulation intensity and environmental information disclosure in neighboring cities causing an increase in environmental regulation intensity of about 0.734% and 0.026% in this city. This research demonstrates the positive effects of adopting environmental information disclosure on the realization of sustainable development and provides empirical evidence for government policy formulation.

Do affluent neighbourhoods pay more for transit access? Exploring the capitalization of employment accessibility within different housing submarkets in Vancouver

Decades of research indicate that accessibility plays a fundamental role in the urban systems of cities by influencing land markets and household location choices. Accessibility is also often positioned as a policy tool in enhancing the well-being of disadvantaged population groups. Considered together, recent research into transportation equity underscores the need to critically investigate the distribution of accessibility with their affordability impacts. To better understand this dynamic, this research assesses variability in the relationship between employment access and house prices within different neighbourhood types in Metro Vancouver. We first calculate network accessibility to employment opportunities. Next, to integrate equity, we use sociodemographic indicators from census data to establish a typology of four neighbourhoods: Affluent, Stable Middle-class, At-Risk Middle-class and Economically-disadvantaged. Finally, using real estate data, we employ spatial econometric models to estimate differences in the capitalization of accessibility in residential property prices across these neighbourhood types. Results suggest that the value of transit access does differ by neighbourhood type in Metro Vancouver. While more affluent neighbourhoods exhibit the highest marginal willingness to pay for accessibility, predicted prices are highest in disadvantaged neighbourhoods due to their higher absolute levels of access. The research offers new insight into how property price effects vary according to different accessibility and sociodemographic contexts, and highlights important implications for both policy and future research.

Evolution mechanism and improvement path of marine economy resilience in Bohai Rim Region

The marine economy resilience is one of the key attributes to measure the sustainable development of marine economy system. In this paper, the core and controlling influencing factors are systematically screened out. The cross-scale evolution mechanism of marine economy resilience of overall and inter-provincial in the Bohai Rim Region is explored by using the spatial econometric model based on the spatial effect level. Meanwhile, the feasible improvement path is proposed for each region considering the quantification utility levels of the influencing factors in each region. The results are as follows: (1) Marine industrial structure Ind and ocean-related employment Emp significantly enhance the marine economy resilience in the Bohai Rim Region, while financial development scale Fin significantly inhibits it; (2) The positive development trend of Liaoning’s marine economy resilience is mainly due to the promoting role of financial development scale Fin, marine industrial structure Ind and marine economy scale Sca; (3) The development of marine economy resilience in Tianjin-Hebei mainly depends on marine economy scale Sca and marine infrastructure Cap; (4) Financial development scale Fin, marine industrial structure Ind, marine economy scale Sca and marine infrastructure Cap have jointly promoted the rapid development of Shandong’s marine economy resilience. Therefore, the improvement path of the overall and inter-provincial marine economy resilience in the Bohai Rim Region is determined and proposed, which effectively promote the sustainable and stable development of its marine economy.

Evaluating the influence of environmental regulations on green economic growth in China: A focus on renewable energy and energy efficiency guidelines

China's status as the world's largest energy consumer highlights its pivotal role in global energy consumption and the urgency of enhancing its energy efficiency and renewable energy development. This study evaluates the influence of environmental regulations on green economic growth in China, with a focus on renewable energy and energy efficiency, from 2000 to 2023 across 30 provinces. Using the Metafrontier-Global-SBM super-efficient DEA model, the research measures green economic development through the lens of energy efficiency. An enhanced fuzzy comprehensive assessment gauges the stringency of environmental regulations. To explore non-linear impacts, regional spillover, and feedback effects, a spatial econometric model was applied. The results reveal a U-shaped non-linear relationship between environmental regulations and green economic growth, with significant spatial feedback and regional spillover effects. Environmental regulations are also shown to have a substantial positive influence on the development of renewable energy, a critical driver of green economic growth. Policy implications suggest that strengthening environmental regulations could accelerate renewable energy adoption and foster sustainable economic growth across regions in China.

How to enhance the resilience of domestic tourism?

Enhancing domestic tourism resilience (DTR) is crucial to achieving high-quality development of the tourism industry. However, owing to the vulnerability of the tourism industry during the COVID-19 pandemic, the enhancement pathways and associated mechanisms of DTR need to be further investigated. Therefore, this study measures the DTR of China's 31 provinces by creatively combining the simple harmonic motion and regime-switching vector autoregressive models and explores its characteristics to lay the foundation for an empirical analysis. Furthermore, the study empirically analyzes the enhancement pathways and associated mechanisms of DTR using a spatial econometric model. First, this study found that tourism agglomeration, specialization, and diversification determine the characteristics of dynamic response and spatial distributions of DTR. Second, from the perspective of spatial effects, DTR in one region positively impacts that in adjacent regions, and tourism agglomeration in a specific region positively impacts DTR in adjacent regions. Third, in terms of mechanisms, tourism agglomeration enhances DTR by optimizing industrial structure and improving production efficiency, whereas tourism specialization and diversification enhance DTR by improving production efficiency and optimizing industrial structure, respectively. These findings provide information for the enhancement of DTR and achievement of high-quality development of the tourism industry.

Influence mechanism of digital economy development on the supply efficiency of ecological products

Improving the supply efficiency of ecological products (EPSE) is of great significance to protect the ecological environment, promote the development of green industry and the sustainable growth of the economy. This paper focuses on constructing an evaluation index system for EPSE and exploring the relationship between the development level of the digital economy (DE) and EPSE in China. To measure the EPSE, the study employs the Undesirable Slacks-Based Measurement (SBM) Model across 30 provinces, cities and districts in China from 2011 to 2022. Furthermore, the research utilizes spatial econometric models, panel threshold effect models, and other methodologies to investigate the impact mechanism and non-linear relationship between DE and EPSE. The research shows that: (1) The overall level of EPSE in the study area is relatively low, with significant development differences observed; (2) The DE has a nota-ble spatial spillover effect on EPSE, with a significantly negative impact in neighboring areas; (3) The development of the DE promotes EPSE through the upgrading of human capital structure, industrial structure, and increases in local government fiscal revenue and corporate operating profits; (4) Heterogeneity analysis shows that the impact of DE on EPSE varies significantly across eastern, central, and western China, with positive effects pronounced in the eastern and western regions; (5) Regression results of the threshold effect indicate a significant single threshold effect on the impact of DE development level on EPSE. Specifically, when the threshold value is less than 0.1232, DE significantly contributes to the improvement of EPSE. This paper contributes new literature evidence and factual references to the understanding of the causal relationship between DE and EPSE. The findings highlight the importance of considering spatial spillover effects, impact mechanisms, and regional heterogeneity in analyzing the relationship between DE and EPSE. The research also suggests that promoting the development of the digital economy could be a viable strategy to enhance EPSE, especially in regions where the threshold value is below 0.1232

Industry spillover effects of robot applications on labor productivity: Evidence from China

This paper provides new insights into the industry spillover on labor productivity by discussing the spillover effects of robot application among industries in three spillover directions: horizontal, forward, and backward spillover. In addition, this paper measures the three spillovers with the weight matrices from the year 2012 input-output table by the Chinese National Bureau of Statistics. Using a spatial econometric model and 2000–2010 data on China's secondary industry, this paper tests three hypotheses relating to the direct effect and the spillover effects of robot applications. The main results show that the robot application of one industry can improve labor productivity significantly. Moreover, all three kinds of spillover have significant positive effects on the labor productivity of a focal industry. Among them, the forward spillover exerts the greatest impact on labor productivity. The heterogeneity effects exist due to the industry's factor intensity and technological structure etc. The findings of this study could provide several important implications for the development of a given industry and the industry chain of a country as well.

Coupling Relationships and Driving Mechanisms of Water–Energy–Food in China from the Perspective of Supply and Demand Security

The rapid increase in population and economy, coupled with accelerated urbanization, is placing immense pressure on the water–energy–food (WEF) system. In this context, the water–energy–food nexus framework has emerged, recognizing the interdependencies and interactions among water, energy, and food systems, with the aim of optimizing resource management through cross-sectoral collaboration to promote sustainable development. Understanding the spatio-temporal differentiation patterns of the WEF nexus and elucidating the driving mechanisms behind changes in their coupling relationships is essential. This knowledge is crucial for ensuring the security of each subsystem and enhancing the overall sustainability of interconnected systems through coordinated efforts. To address these challenges, this study first established evaluation indicators for water, energy, and food security to quantify their levels and spatio-temporal dynamics. Subsequently, the degrees of coupling coordination within the WEF nexus were calculated. Finally, the WEF nexus’s spatial correlations were analyzed by using a spatial autocorrelation model. Spatial econometric models then identified key factors affecting its coordination. The results revealed significant spatial heterogeneity in water, energy, and food security across mainland China’s provinces. From 2002 to 2022, water security improved substantially in 87% of the provinces, while energy security began to improve in the eastern regions following a phase of high consumption. Food security saw significant enhancements, particularly in Inner Mongolia and the northeastern provinces. The overall coupling coordination of the WEF nexus improved across 30 provinces, progressing toward primary coordination. However, Henan and Anhui provinces experienced fluctuations in WEF nexus coordination. Spatial correlation analysis showed upward trends and increased clustering in WEF nexus coordination. Factors such as economic development and population positively influenced coordination, while economic agglomeration, education, and effective irrigation area had negative effects. This study elucidates the complex interconnections and key influencing factors within the WEF nexus, providing a reference framework and practical recommendations for equitable resource management.

The consequence of the digital economy on energy efficiency in Chinese provincial and regional contexts: Unleashing the potential

The digital economy, driven by advanced technologies, is becoming a new force for economic growth and sustainable development. This study investigates how the digital economy influences energy efficiency and its spatial spillover effects across 30 Chinese provinces from 2011 to 2020 using spatial econometric models and Moran's index analysis. While prior research focused on industrial value and micro-mechanisms, this work examines geographical impacts and regional synergies overlooked previously.The findings reveal urbanization and digital economy growth significantly enhance energy efficiency. However, the effects of economic structure, education, infrastructure development, and patent activity exhibit more nuanced patterns. Notably, the spatial spillover effects of the digital economy on energy efficiency operate through a "market + geographical comprehensive mechanism" rather than direct geographic transmission between neighbors. This study contributes to the literature by uncovering the complex relationships between the digital economy, technological innovation, industrial structure, and energy efficiency while accounting for spatial dynamics. The results underscore the importance of focused policies supporting sustainable energy practices based on regional contexts. By providing insights into the intricate interplay of factors influencing energy efficiency, this research informs strategies for optimizing energy utilization and transitioning towards a sustainable, secure, and affordable energy future aligned with net-zero objectives.

Quantifying the economy-wide employment effects of coal-fired power plants: Two different cases China and the United States

Ensuring a swift transition from coal to clean energy is essential for capping global temperature increases at 1.5 °C, but it poses significant economic and social challenges in coal-dependent regions. This paper examines the economy-wide employment impacts resulting from the activities of coal-fired power plants in China and the United States, the world's largest coal consumers. By analyzing observational data on the different stages of coal power, including both expansion and reduction in the two countries, we aim to derive insights that can inform a more effective and just transition during the phase-out of coal power. We leveraged unique periods post-2010 when China was predominantly opening coal plants while the US was closing them, identifying the economy-wide employment impacts at the county level. By using both two-way fixed effects and spatial econometric models for over 10 years of panel data, covering 2875 in China and 3233 counties in the US, we addressed spillover effects and ensured robust and comprehensive results. Our findings revealed that in China, coal plant deployment increased employment both locally and in the neighboring counties. In the U.S., our findings indicate that before 2015, closing coal plants generally had a negative impact on jobs. However, after 2015, when the U.S. introduced new federal and state-level transition policies, the impact on employment became positive. While it is hard to prove these policies directly facilitate the just transition, our findings demonstrate that they do not hinder the employment aspect of a just transition focused on coal power generation at a regional scale.

Spatial-temporal characteristics of port infrastructures on sulfur-oxide concentrations of coastal port in China

Port infrastructure is an important guarantee to support the development of shipping trade and a main link to connect shipping routes, where its construction and expansion promote economic progress whereas exacerbating regional pollution. Based on the panel data of 18 above-scale coastal ports in China from 2005 to 2020, the spatial characteristics and correlation of sulfur-oxide (SOX) concentrations are first analyzed, then the spatial Durbin model (SDM) is established to evaluate the extent of port infrastructure's impact on the concentrations, further the intermediation effects of three dimensions on the concentrations are explored. From the outcome, the influences of port infrastructures on the SOX concentrations are from decreasing the SOX concentrations through improving the operational efficiencies and increasing the SOX concentrations by adding the operational equipment, which also shows significant spatial spillover effects. In addition, the mechanical dimension as a mediation makes the trade dimension have an indirect effect on the SOX concentrations. This paper employs a spatial econometric model to analyze panel data from 18 coastal ports and ports of higher tiers in China, spanning from 2005 to 2020. It uncovers the intricate mechanism by which port infrastructure influences SOX concentration, thus providing a scientific foundation and decision support for environmental protection and sustainable port development.