Yangtze River Delta Region Research Articles

Drivers of industrial carbon emissions in the Yangtze River Delta region, China: A combination of decoupling and LMDI models

ABSTRACT The expansion of the industrial economy has resulted in high carbon emissions (CE) from the Yangtze River Delta (YRD) region. Industrial CE reduction is a non-negligible way to achieve green and low-carbon development. In this paper, we aim to study the decoupling effect of industrial CE and its socio-economic influencing factors in the YRD region from 2005 to 2020. First, the decoupling relationship between industrial CE and industrial output in the YRD region is measured. Then, using the LMDI method, the variation of industrial CE is decomposed into six factors: energy structure ( Δ c s ), energy intensity ( Δ c i ), economic scale ( Δ c e ), labor structure ( Δ c l ), urbanization rate ( Δ c u ) and population size ( Δ c p ) effect. Subsequently, by combining with the decoupling and LMDI models, the contribution of each factor to the decoupling of industrial CE is studied, and the elasticity of each factor is expressed by η s , η i , η e , η l , η u , and η p . The main findings show that: (1) There are two states of weak and strong decoupling between industrial CE and the industrial economy in the YRD. (2) Δ c e is the most powerful factor in promoting industrial CE, while Δ c i and Δ c l are the factors that inhibit industrial CE in the YRD. (3) η i and η l have promoted the decoupling of industrial CE from economic advancement in the YRD and its three provinces and one city, while η e has consistently been the largest obstacle to the decoupling process. Finally, the policy recommendations proposed in this paper aim to help policy-makers and practitioners in the YRD region achieve a win-win balance between industrial CE and industrial output, and inspire further research on the decoupling and decomposition of industrial CE from an academic perspective.

A long-term Doppler wind LiDAR study of heavy pollution episodes in western Yangtze River Delta region, China

Previous studies are primarily based on surface air pollution for a single event, leaving research on the temporal characteristics of aerosols and wind fields in the atmospheric boundary layer (ABL) and their associations unclear due to a lack of long-term vertical profile data. This study was the first to conduct long-term Doppler wind LiDAR measurements from Sep. 2019 to Aug. 2022 in Hefei in western Yangtze River Delta (YRD) region, China. The spatiotemporal characteristics of retrieved aerosol backscatter coefficient (β) and wind profiles were analyzed from the perspective of long-term statistics and typical heavy pollution episodes (HPEs). The seasonal profile of β showed a peak in the near-surface layer meanwhile the overall β profile (<0.5 km) was the highest in winter but lowest in summer. Combined with ground-based meteorological and air quality observations, 12 HPEs were identified and classified into dust-related events and fog-haze episodes. The results showed a consistency between hourly variations in PM10 (particulate matter smaller than 10 μm) concentration and β retrieved at 300 m during a high PM10 concentration (>150 μg/m3) period. Different roles of horizontal wind at different altitudes and its associated time delay effect on surface PM10 pollution were evaluated based on correlation coefficients (Ф) and air pollution diffusion conditions. Significant positive Ф values were noticed below 0.5 km during the entire dust-related EP4 and EP6, indicating that the higher wind speeds could exacerbate PM10 pollution. In contrast, large negative Ф values meant the removal of PM10 pollutants by strong winds below 0.8 km during 24 h after peak in EP3. Combining with backward trajectory analysis and meteorological condition, notable transboundary pollution with positive contributions from upper winds (>1.5 km) was discovered in dust-related EP1, EP4, EP7, EP9, and EP10. Time delay effect (1-h/2-h lag) of upper winds (>0.8 km) on surface PM10 pollution was explored in EP5, EP6, EP7, EP8, and EP9. In spring dust-related HPEs, surface PM10 pollution was mostly contributed by long-range transport of aerosol particles at higher altitudes (>1.5 km) from the northwest direction, driven by the Mongolian cyclone and the cold front system. Transboundary aerosols originated from the northern part of Anhui province and the YRD region in the middle altitudes (∼0.5 km) was the main contributor to fog-haze HPEs. The findings demonstrated the ability of the real-time Doppler wind LiDAR system to monitor transboundary air pollution and provided a scientific reference for policy makers.

A Spatiotemporal Evolution and Pathway Analysis of Rural Development Efficiency: A Case Study of the Yangtze River Delta

Sustainable rural development is crucial for urban–rural integration and achieving shared prosperity. This study assesses rural development efficiency (RDE) at the county level in the Yangtze River Delta (YRD) region from 2012 to 2021 using the super-slacks-based measure model (SBM). By employing the Theil index and spatial Markov chains, this study explores the spatiotemporal evolution of RDE, categorizes rural development types, and proposes differentiated developmental pathways. The findings reveal (1) an initial upward trend in overall RDE in the YRD followed by stabilization, with regional disparities narrowing yet overall efficiency levels remaining relatively low; (2) a spatial distribution pattern of RDE characterized by high efficiency in the southeast and low efficiency in the northwest, forming a “core–periphery” structure, with pure technical efficiency identified as a significant bottleneck; (3) stability and “club convergence” in RDE, with geographic spatial patterns significantly influencing the transition process and a notable spatial spillover effect; (4) the classification of rural development types into six categories based on an “input–output–efficiency” perspective, each with specific developmental pathways. This study concludes that optimizing resource allocation efficiency and defining development pathways tailored to local conditions are essential for driving sustainable rural development in the YRD.

Ecological Evaluation of Land Resources in the Yangtze River Delta Region by Remote Sensing Observation

The evaluation of land ecological security (LES) evaluates how human activity and land use affect land ecosystems. Its ultimate objective is to provide guidance and assistance for decision making in order to preserve and restore the efficacy and health of terrestrial ecosystems. The assessment model presented in this article is comprehensive and integrates the advantages of both subjective and objective weighting techniques. This study extends the “Pressure–State–Response” (PSR) model to “Driver–Pressure–State-Impact–Response” (DPSIR) and combines it with TOPSISI to determine the weights of each contributing component. Furthermore, the geographical and temporal distribution patterns of regional land ecological security levels were investigated using GIS geostatistical approaches. According to this study, (1) the Yangtze River Delta region’s LES index, with a mean value in the fairly safe range, is generally safe. The year 2019 marks an inflection point for the index, with the highest level of ecological safety on land. The primary element is the modification of environmental policies that are enacted by the government. (2) The LES status is divided into two stages during the course of this study. The Yangtze River Delta region’s LES quickly develops throughout the first stage (2012–2019), which sees a shift in the safety rating from IV to II. The second stage (2019–2023) sees a progressive improvement in the LES index and a shift in the safety category from Class II to Class I. (3) Important variables influencing the geographical distribution of LES in the Yangtze River Delta region include barrier elements, including soil and water erosion areas, flood disaster areas, grain planting areas, urban green covering areas, and effective irrigation areas of farmland.

The impact of evolving synoptic weather patterns on multi-scale transport and sources of persistent high-concentration ozone pollution event in the Yangtze River Delta, China

High-concentration ozone pollution pose threats to ecosystems and human health. However, there is limited research on the impact of the alternating evolution of synoptic weather patterns (SWPs) on the multi-scale transport processes and sources of ozone. From June 14 to 18, 2018, a rare consecutive ozone pollution plagued in Hefei and broader Yangtze River Delta region (YRD). This study investigates the meteorological factors and sources using in-situ observational data and WRF-Chem model simulations. Analysis reveals a northeastern low-pressure system moving from north to south generated a cold front. This moving cold front facilitated the vertical transport of warm air masses carrying high-concentration ozone originating from North China. Subsequently, Ozone-rich air masses (ORMs) were transported over the YRD, influenced by the eastward movement of the Mongolian high-pressure system. Based on WRF-Chem model with NOx tagging mechanisms and WRF-FLEXPART backward simulations, it is confirmed that a notable atmospheric transport originated from North China region (NCR) to Hefei, especially on June 15. As the Mongolian high-pressure weakens and shifts east-southward, it carried ORMs generated by NOx emissions from the YRD, accumulating over the sea within the range of 120°E to 126°E and 25°N to 30°N. Both WRF-chem model results and TRopospheric Ozone and Precursors from Earth System Sounding (TROPESS) Chemistry Reanalysis dataset Version 2 (TCR-2) revealed the existence of ORMs in this geographic range. Subsequently, the ORMs carried out to sea by the weakened high-pressure system were reintroduced inland, influenced by southeast winds brought about by the peripheral circulation of typhoon “Gaemi”. In summary, the alternating evolution of SWPs significantly influences multi-scale ozone transport from both the NCR and the YRD regions, making substantial contributions to this prolonged episode. These findings offer valuable insights for improving regional ozone pollution prevention and control mechanisms.

Spatial and temporal variation of PM2.5 and the influence of vegetation in the Yangtze River Delta region

With rapid urbanisation in China, PM2.5 has become a limiting factor for the sustainable development of cities. Taking the Yangtze River Delta as the experimental area, this study analysed the spatial and temporal changes of PM2.5 concentrations from 2001 to 2020. It also examined the variations, dispersion, and correlation with NDVI of PM2.5 concentrations in different vegetation zones at different temporal and spatial scales. The results showed that: (1) The PM2.5 concentration in the Yangtze River Delta showed an overall decreasing trend during 2001–2020, and the change was divided into two phases, starting with an increasing phase and entering a decreasing phase after 2013. (2) In terms of spatial distribution, PM2.5 concentrations in the Yangtze River Delta show a pattern of low in the south and high in the north, with the spatial focus shifting to the north over time. There is a concentration of high levels of particulate matter in the Hefei-Nanjing-Wuxi area. (3) The effect of natural vegetation on the reduction and stabilization of atmospheric particulate matter concentration is better than that of artificial vegetation. (4) Needleleaf forests, broadleaf forests, and shrubs in natural vegetation are more capable of reducing and stabilizing atmospheric particulate matter than grasses. The study can provide a reference for regional air pollution control and regional plant system construction.

The Influence of Emotional Response and Aesthetic Perception of Shopping Mall Facade Color on Entry Decisions—Evidence from the Yangtze River Delta Region of China

The Influence of Emotional Response and Aesthetic Perception of Shopping Mall Facade Color on Entry Decisions—Evidence from the Yangtze River Delta Region of China

The Impact of Future Land Use Change on Carbon Emission and Its Optimization Strategy

Rapidly changing climate issues and increasingly severe carbon emissions are great challenges to the carbon peaking and carbon neutrality strategy. Analyzing the impact of future land use changes on carbon emissions can provide an important basis and reference for scientifically constructing a low-carbon and sustainable territorial spatial planning, as well as realizing the goal of the dual-carbon strategy. Based on land use data, agricultural production activity data, and energy consumption statistics, this study simulated the land use changes of the Yangtze River Delta region (YRDR) from 2030 to 2060 under the natural development (ND) scenario and sustainable development (SD) scenario by using the Patch-generating Land Use Simulation (PLUS) model and analyzed the impacts of future land use changes on carbon emissions. The results showed that: (1) The land use simulation results obtained by using the PLUS model under the sustainable development scenario were highly consistent with the actual land use with an OA value of 97.0%, a Kappa coefficient of 0.952, and a FoM coefficient of 0.403; (2) Based on the simulated land use under the SD scenario from 2030 to 2060, the quantity of construction land was effectively controlled, and the spatial distributions of cropland and forests were found to dominate in the north and south of the Yangtze River, respectively; (3) Anhui Province was the major contributor (accounted for 49.5%) to the net carbon absorption by cropland while Zhejiang Province was the major contributor (accounted for 63.3%) to the net carbon absorption by forest in the YRDR during the period 2020–2060 under the SD scenario; (4) Carbon emissions from construction land were the main source of carbon emissions from land use in the YRDR during the period 2020–2060 with proportions higher than 99% under both the ND and SD development scenarios. These findings underscore the urgent need for the government to take measures to balance the relationships between cropland and ecological protection and economic development, which provides a reference for the optimization of land use structure and policy formulation in the future.

Spatial Distribution Characteristics and Driving Factors of Little Giant Enterprises in China’s Megacity Clusters Based on Random Forest and MGWR

As a representative of potential “hidden champions”, a concept originating in Germany, specialized and innovative Little Giant Enterprises (LGEs) have become exemplary models for small and medium-sized enterprises (SMEs) in China. These enterprises are regarded as crucial support for realizing the strategy of building a strong manufacturing country and addressing the weaknesses in key industrial areas. This paper begins by examining urban agglomerations, which serve as the main spatial carriers for industrial restructuring and high-quality development in manufacturing. Based on data from LGEs in the Yangtze River Delta (YRD) and Pearl River Delta (PRD) urban agglomerations from 2019 to 2023, the study employs the Random Forest (RF) and Multi-scale Geographically Weighted Regression (MGWR) methods to conduct a comparative analysis of their spatial patterns and influencing factors. The results are as follows: (1) LGEs exhibit spatial clustering in both the YRD and PRD regions. Enterprises in the YRD form a “one-axis-three-core” pattern within a distance of 65 km, while enterprises in the PRD present a “single-axis” pattern within a distance of 30 km, with overall high clustering intensity. (2) The YRD is dominated by traditional manufacturing and supplemented by high-tech services. In contrast, the PRD has a balanced development of high-tech manufacturing and services. Enterprises in different industries are generally characterized by a “multi-point clustering” characteristic, of which the YRD displays a multi-patch distribution and the PRD a point–pole distribution. (3) Factors such as industrial structure, industrial platforms, and logistics levels significantly affect enterprise clustering and exhibit scale effects differences between the two urban clusters. Factors such as industrial platforms, logistics levels, and dependence on foreign trade show positive impacts, while government fiscal expenditure shows a negative impact. Natural geographical location factors exhibit opposite effects in the two regions but are not the primary determinants of enterprise distribution. Each region should leverage its own strengths, improve urban coordination and communication mechanisms within the urban cluster, strengthen the coordination and linkage of the manufacturing industry chain upstream and downstream, and promote high-tech industries, thereby enhancing economic resilience and regional competitiveness.

Relationships between amplified quasi‐stationary waves and humid‐heat extremes in the Yangtze River Delta region

AbstractHigh humidity combined with high temperature decreases the human body's capability to dissipate heat, causing serious health issues. While increased attention has been paid to changes in humid‐heat extremes under the current climate and in the future, the causes of near‐surface humid‐heat extremes over the Yangtze River Delta region are still unclear. Here we investigate the relationships between quasi‐stationary waves (QSWs), which are atmospheric Rossby waves with phase speed close to zero, and humid‐heat extremes over the Yangtze River Delta region during the summer from 1959 to 2021. Additionally, the potential physical processes that link them are also explored. We find that the QSWs with wavenumber 1–8 present different vertical structures: Wave 1–2 are baroclinic, while Wave 3–8 are barotropic. Wave 1, 3, 5, 6, 7 and 8 show phase‐locking behaviour. When the amplitudes of Wave 1, 3, 5 and 6 are higher, the frequency of humid‐heat extremes near the surface at specific locations tends to be higher than the norm. The high‐amplitude waves in different wavenumbers modulate near‐surface temperature and/or humidity in various ways, ultimately resulting in anomalously intensive humid‐heat extremes.

The food security risks in the Yangtze River Delta of China associated with water scarcity, grain production, and grain trade

Grain production consumes a large amount of water and is affected by the degree of water scarcity and participation in the grain trade in various regions. The grain trade has changed the food security risks in regions where grain exports and imports. Therefore, it is crucial to consider regional water scarcity to understand food security risks from the grain trade network. Here, we construct a new framework for measuring regional food security risks associated with water scarcity, grain production, and grain trade based on a cross-city grain trade network combined with virtual water flows to evaluate the regional food security risks in the Yangtze River Delta region (YRD) of China in 2017. The results show that under the current domestic grain trade pattern in China, the YRD and its four provincial-level administrative regions are in a net grain import state. The grain trade within the YRD is concentrated in exports from the two major grain-producing areas of Anhui and Jiangsu to Zhejiang and Shanghai, especially from northern Jiangsu to southeastern Zhejiang. The net import results of virtual blue water in most cities indicate that the YRD has shifted its water resource pressure to other grain exporting regions in China, with Shanghai and Zhejiang being the greatest beneficiaries. Extreme risk only exists in Shanghai, and severe and moderate risks are concentrated in Jiangsu. The current grain trade has reduced the overall food security risk in the YRD by 1.3 % but increased the risks in Shanghai and Zhejiang by 2.1 % and 0.8 % respectively. This study highlights the potential risks that excessive production of food in water-scarce areas in the grain trade system may bring to a stable food supply, providing useful information for a comprehensive understanding of the food and water security situation and for future trade-offs.

Spatiotemporal Dynamics and Scenario Simulation of Regional Green Spaces in a Rapidly Urbanizing Type I Large City: A Case Study of Changzhou, China

The rapid urbanization observed in major Chinese cities has resulted in the degradation of both urban and rural environments. In response to this challenge, the concept of regional green spaces has emerged as an innovative approach to coordinate and manage green space resources across urban and rural areas. This study focuses on conducting a comprehensive analysis of the evolution, driving factors, and future scenarios of regional green spaces in Changzhou, which serves as a representative Type I large city in China. To accomplish this analysis, Landsat satellite images from 1992, 2002, 2012, and 2022 were utilized. Various methodologies, including landscape pattern indices for quantitative evaluation, the CLUE-S model, logistic regression for qualitative evaluation, and the Markov–FLUS model, were employed. The findings indicate a continuous decline in the area of regional green spaces in Changzhou, decreasing from 248.23 km2 in 1992 to 204.46 km2 in 2022. Landscape pattern analysis reveals an increase in fragmentation, complexity, irregularity, and human interference within these green spaces. Logistic regression analysis identifies key driving factors influencing regional green spaces, including elevation, urban population, and proximity to water bodies and transportation. The scenario simulations provide valuable insights into potential future trends of regional green spaces. According to the economic priority scenario, a modest increase in regional green spaces is anticipated, while the ecological priority scenario indicates substantial growth. Conversely, the inertial development scenario predicts a continued decline in regional green spaces. This research emphasizes the significance of achieving a harmonious coexistence between economic progress and environmental preservation. It emphasizes the necessity of optimizing the arrangement of green areas within a region while fostering public engagement in the conservation of these spaces. The findings contribute to the protection and sustainable development of the urban environment in the Yangtze River Delta region.

Comparison of NMHC measurements between 2010 and 2020 in Wuxi City, Yangtze River Delta region: Levels, compositions, sources, and impacts

Field observation analyses of volatile organic compounds (VOCs) have gained significant attention due to their potential explaining atmospheric temporal trends. This study measured non-methane hydrocarbons (NMHCs) in Wuxi City, located in the Yangtze River Delta (YRD) of China, in 2010 and 2020. The aim was to gain a better understanding of the ten-year change of VOCs in terms of their mixing ratios, sources, role in ozone, secondary organic aerosol (SOA) formation, and health risks. The average NMHC level 2020 was 20.67 ppbv, which indicated a 20% drop from 2010. A notable shift was observed in the chemical composition of NMHCs. The contribution of alkanes increased from 45% to 62% in 2020, while that of the aromatics decreased from 25% in 2010 to 21% in 2020. Ratio analysis and receptor modelling for 2010 and 2020 were used to identify the source changes of VOC species. The source apportionment model showed that the contribution of vehicle exhaust decreased from 34.5% to 20.9% from 2010 to 2020, and that of the solvent increased from 15.1% to 25.3%. The chemical reactivity results suggested that aromatics played significant roles in photochemical reactions in Wuxi City. The ozone formation potential (OFP) and SOA potential of VOCs also showed decreasing trends from 2010 to 2020. The total OFP of alkenes decreased by 34.0%, from 30.6 to 20.2 ppbvO3/ppbv. The total non-carcinogenic risk value for the key VOC species was 0.034 in 2010 and 0.024 in 2020. Although the carcinogenic risks for benzene have decreased significantly, the value is still above the acceptable carcinogenic risk level. The results of this study demonstrate the effectiveness of air pollution control measures in Wuxi City and highlight the positive impacts on reducing secondary pollution and health risks in this region over one decade.

The spatial spillover effects of regional integration on carbon emissions

The Yangtze River Delta (YRD) region serves as the leading economic force of the Yangtze River Economic Belt (YREB) in China. It is crucial for the region to take a leadership role in regional integration to facilitate carbon emission reduction. This paper employs a spatial econometric model to examine the impact, spatial spillover effect, and mechanisms of regional integration on carbon emissions in the Yangtze River Delta, using data from 41 cities in the region from 2008 to 2019. The results indicate that there is an inverted U-shaped relationship between the level of regional integration and carbon emissions, with emissions initially increasing before decreasing. Additionally, the impact of regional integration on carbon emissions exhibits a positive spatial spillover effect and threshold characteristics, with carbon emissions inhibited and a positive spatial spillover observed once the threshold is exceeded. Moreover, regional integration reduces carbon emissions through the upgrading of industrial structures and the innovation of green technology. Implications for carbon emission reduction include: actively integrating into the Yangtze River Delta regional integration development; strengthening cross-regional carbon emission synergistic governance; and promoting carbon emission reduction through mechanisms such as promoting industrial upgrading and low-carbonization development, as well as incentivizing technological innovation.

Analysis of regional water resources spatial pattern and allocation equity

Water scarcity is a worldwide concern, and with the impact of climate change and human activities, the imbalance in the distribution of water resources has further intensified. The equitable allocation of water resources has become a thorny issue for water resources management authorities. It is challenging to find a relatively equitable method of water resources allocation. This study aims to propose a method for evaluating the fairness of water resources allocation, which can be used both to evaluate the fairness of water resources allocation and as a basis for water resources allocation decisions. The specific approach is to first analyze the spatial pattern of regional water resources by using water resources abundance and water resources intensity, and then to conduct a comprehensive analysis of regional water resources allocation fairness by combining Lorenz curve, Gini coefficient and Theil index to form an index system that can systematically analyze the spatial pattern of water resources, allocation fairness and its changes. A real-world example study was conducted in the Yangtze River Delta region of China, and the results showed that the index system can well reflect the allocation of water resources among regions and cities within the region. The results obtained using this method can provide some reference for promoting coordinated regional development.

Spatial analysis of the digital economy’s influence on urban sustainable development: A decade-long study of Chinese prefecture-level cities

Urban Sustainable Development (USD) is crucial for social advancement, and the rise of the Digital Economy (DE) offers potential pathways to achieve it. This study has employed the DPSIR framework and an entropy-based approach to evaluate the DE and USD across 284 Chinese prefecture-level cities from 2011 to 2020. Using the Spatial Durbin Model, the results have revealed that DE significantly enhances USD and has a spatial spillover effect of up to 300 km. The eastern region, as well as the Pearl River Delta and Yangtze River Delta regions, show stronger spillover effects than the central and western regions and the Beijing-Tianjin-Hebei region. These findings have provided insights for policymakers to leverage digital advancements to promote urban sustainability.

Measurement of regional green finance development and its coordination with economic development: a study on the Yangtze River Delta region of China

The green transformation of industry and sustainable economic development both require considerable investment. In this regard, green finance that is compatible with economic development can help cope with the massive demand for capital. Taken China’s Yangtze River Delta (YRD) as an example, this study is to measure the coordination degree between green finance and economic development. First, the concept, content and scope of green finance is defined based on the new financial regulation mechanism. Second, a green finance measurement index is built to calculate the green finance index for 30 Chinese provinces by the CFA test. Third, based on the economic structure index, an economic development index is built. Testing the rationality of green financial index and the economic development index, this paper finally measures the degree of coordination between green finance and economic development in the YRD. The results reveal that, first, green finance is a financial instrument that integrates financial industry development, environmental improvement, and economic growth. The measurement of the green financial development index includes the sum of regional green credit, green investment, green securities, and green insurance. Second, after years' development, the comprehensive score of YRD’s coupling coordination degree exceeds 0.8 in 2020, which shows a high level of coordinated development between green finance and economic construction. However, there is a 2-year timing effect between the economic development and green finance index increase, which reveals that green finance development in the YRD requires further policy guidance and support. This study’s findings can provide a theoretical reference and case support for the further development of green finance and related policies in China.

Spatiotemporal Evolution Characteristics of Carbon Sources and Carbon Sinks and Carbon Balance Zoning in the Yangtze River Delta Region

Mastering the spatiotemporal evolution laws of carbon sources and sinks is of great significance to promote the coordinated development of regional low-carbon, improve the science of carbon reduction and sink increase policies, and realize the goal of "double carbon." Taking 41 cities in the Yangtze River Delta Region as the research object, this study analyzed the spatiotemporal evolution characteristics of carbon sources and sinks in the Yangtze River Delta Region from 2000 to 2020 and conducted the carbon balance zoning. The results were as follows： ① The carbon emissions increased rapidly in the Yangtze River Delta Region from 2000 to 2011 but with some fluctuations after 2011. Carbon sinks increased slowly in the Yangtze River Delta Region from 2000 to 2020. The regional differences in carbon emissions and carbon sinks were significant, and the spatial pattern was relatively stable. ② The carbon compensation rate in the Yangtze River Delta Region showed a downward trend, and the carbon productivity, energy utilization efficiency, and carbon ecological support capacity were constantly enhanced. Interregional differences were the main source of carbon compensation rate in the Yangtze River Delta Region. Both the carbon compensation rate and carbon ecological support coefficient showed a spatial pattern of "high in the west and low in the east, high in the south and low in the north." The areas with high carbon economy contributive coefficient were concentrated in the central and southern areas of the Yangtze River Delta regions, and the areas with low carbon economy contributive coefficient were concentrated in Anhui Province. ③ Based on the carbon economy contributive coefficient and the carbon ecological support coefficient, cities in the Yangtze River Delta Region were classified into low-carbon maintenance areas, economic development areas, carbon sink development areas, and comprehensive optimization areas. Recommendations were proposed for each category of cities in order to promote the coordinated development of regional low-carbon and realize the goal of "double carbon".

Establishing resilience-targeted prediction models of rainfall for transportation infrastructures for three demonstration regions in China

Rainstorm is one of the global meteorological disasters that threaten the safety of transportation infrastructure and the connectivity of transportation system. Aiming to support the resilience assessment of transportation infrastructure in three representative regions: Sichuan–Chongqing, Yangtze River Delta, and Beijing-Tianjin-Hebei-Shandong, rainfall data over 40 years in the three regions are collected, and the temporal distribution of rainfall are analyzed. Prediction equations of rainfall are established. For the purpose of this, the probabilistic density function (PDF) is assigned to the rainfall by fitting the frequency distribution histogram. Using the assigned PDF, the rainfall data are transformed into standard normal space where regression of prediction equations is performed and the prediction accuracy is tested. The results show that: (1) The frequency of rainfall in the three regions follows a lognormal distribution based on which the prediction equations of rainfall can be established in standard normal space. The error of regression shows no remarkable dependence on self-variables, and the significance analysis indicates that the equations proposed in this paper are plausible for predicting rainfalls for the three regions. (2) The Yangtze River Delta region has a higher risk of rainstorm disaster compared to the other two regions according to the frequency of rainfall and the return period of precipitation concentration. (3) Over the period of 1980–2021, the Sichuan–Chongqing region witnessed an increase in yearly rainfall but a decrease in rainstorm disasters, whereas the other two regions experienced a consistent rise in both metrics.

RESEARCH ON THE INFLUENCE OF BIG DATA ANALYTICS CAPABILITY ON AMBIDEXTROUS INNOVATION IN MANUFACTURING ENTERPRISES

This paper, based on the perspectives of dynamic capabilities theory, constructs a theoretical model to explore the mechanisms by which big data analytics capabilities influence ambidextrous innovation in manufacturing enterprises. We conducted a survey among mid- to senior-level managers of manufacturing firms in the Yangtze River Delta region of China to empirically test this model, yielding 586 valid samples. We analyzed the questionnaire data using PLS-SEM. The research results show that big data analytics capabilities have a significant positive impact on ambidextrous innovation in manufacturing firms. Additionally, resource bricolage plays a partial mediating role in the relationship between big data analytics capabilities and ambidextrous innovation. These findings provide theoretical guidance for manufacturing enterprises to promote ambidextrous innovation through the development of big data analytics capabilities.