Urban Agglomerations In China Research Articles

Urbanization intensifies the imbalance between human development and biodiversity conservation: Insights from the coupling analysis of human activities and habitat quality

AbstractIntensified human activities have been seriously threatening the structure and ecological processes of ecosystems, resulting in habitat degradation. Therefore, coordinating the coupling between human activities and habitat quality (HQ) is crucial for high‐quality sustainable regional development and human well‐being. This study evaluated the human activities and HQ in the Pearl River Delta (PRD) urban agglomeration in China from 2000 to 2020 using the human footprint index (HFI) and the integrated valuation of ecosystem services and tradeoffs model. Then, we employed bivariate spatial autocorrelation and a coupling coordination degree (CCD) model to explore the synergistic relationship between human activities and HQ. The results show that spatial changes in HQ were predominantly driven by human activities. The gradual outward urban expansion resulted in significant HQ degradation. Slight HQ improvement by ecological restoration in urban outskirts cannot offset HQ losses caused by urbanization. During the study period, high‐HQ low‐HFI clusters decreased by 1.02%, while low‐HQ high‐HFI clusters increased by 4.67%, the two main clustering types in the PRD. Despite the CCD between HFI and HQ increased after 2010, the continuous changes of CCD characteristics from the HFI significantly lagged type to the HQ lagged. HFI showed an inverted U‐shaped relationship with CCD. The CCD peaks during 2000–2020 corresponded to HFI decreasing from 0.711 to 0.566. This indicates that the risk of decoupling between human activities and HQ gradually increased. Furthermore, CCD levels and characteristics in different bivariate clusters exhibited varying changes over time. These results reveal that the spatiotemporal dislocation between urbanization and ecological restoration induced the spatial nonstationarity of the coupling relationship between human activities and HQ. Urbanization exacerbates the imbalance between human development and biodiversity conservation. Therefore, we suggest reasonably delimiting urban boundaries, controlling the scale of urban sprawl, and strengthening biodiversity protection in areas undergoing rapid urbanization. In addition, we advocate for the division of ecological barrier zones, urban development buffer zones, and urban built‐up areas, each with tailored management and protection measures. Our findings can provide an important reference for the ecological restoration of urban agglomerations.

Differences in carbon sink potential between urban agglomerations are decreasing: Evidence from China

In the context of global warming, effectively reducing carbon emissions is crucial for the sustainable development of human society. Enhancing carbon sink potential offers an efficient and economical method to reduce carbon emissions. Urban agglomerations, as significant sources and carbon sinks, play a pivotal role in optimizing carbon sink potential. This study examines 19 urban agglomerations in China, employing the improved CRITIC method, Dagum's Gini coefficient, and its decomposition, and the spatial convergence model to assess the carbon sink potential level, identify disparities and their origins, and analyze the convergence mechanism within these urban agglomerations. The findings reveal: (1) Driven by policy support and technological progress, China's urban agglomerations have improved carbon sink potential, with low-level areas diminishing and medium- to high-level areas growing consistently. (2) The variation in carbon sink potential across regions primarily stems from differences among urban agglomerations, suggesting that reducing these disparities could further enhance carbon sink potential. (3) There is a trend of convergence in carbon sink potential among urban agglomerations, indicating that disparities are narrowing over time, moving towards long-term equilibrium. This study extends carbon sink research into urban ecosystems, offering comparative analyses across temporal and spatial dimensions. It enriches the current body of research and provides empirical guidance for China and similar developing countries in pursuing an equilibrium between low-carbon development and economic growth.

Occurrence and health risk assessment of organic amine pesticides in drinking water of the Yangtze River delta urban agglomeration

Organic amine pesticides (OAPs) are widely used in modern agriculture and these compounds can contaminate drinking water sources in different ways. However, there is a lack of data on the occurrence of OAPs in drinking water and their potential human health risks. In this study, tap water (TW) and bottled water (BW) samples were collected from eight cities in the Yangtze River Delta urban agglomeration in China, and their OAP levels were analyzed using high-throughput organic analysis testing coupled with high-volume solid-phase extraction (Hi- throat/Hi-volume SPE techniques). This study is the first to systematically characterize the trace levels of OAPs in drinking water in China. Our findings indicated that the total concentration of OAPs (∑OAPs) in TW (average 11.06 ± 4.99 ng/L) was 29.4% higher than in BW (average 8.55 ± 3.98 ng/L) and fewer kinds (7) of OAPs were detected in BW. Furthermore, the long-term intake of TW in some areas was linked to carcinogenic risks even at an acceptable OAP range, particularly in males, with molinate being the major contributor (61.3%) to OAP exposure. Further analysis revealed that the occurrence and health risks of OAPs in drinking water were mainly influenced by the quality of water sources and the technologies adopted in drinking water treatment plants (DWTPs). Furthermore, our findings demonstrated that advanced treatment technologies such as nanofiltration could more effectively remove OAPs in raw water (up to 87.5%). Therefore, our findings highlighted the importance of selecting appropriate advanced treatment technologies in DWTPs.

Does settlement land expansion necessarily induce the decrease of cultivated land? Differences in national scale and local counties of China

With the extensive industrialization and urbanization taking place in China during the recent decades, land use throughout the country has experienced profound changes influenced not only by the demand for population growth and living standard improvement but also by the constraints of series of land use policies. However, whether the conflict between the expansion of settlement land (SL) and the loss of cultivated land (CL) have been resolved at the national scale or transferred between the local regions remains unclear. Based on yearly ESA CCI land use and land cover products from 1992 to 2020, the long-term trends of quantity and spatial pattern of SL expansion and CL change in China from national and local views were investigated using trend statistic methods, and finally a comprehensive zoning framework was proposed to recognize the trade-off and synergies relationships between SL expansion and CL change. There are a continuous expansion of SL with global linear trends showing three breakpoints in 2000, 2005, and 2012, and a fluctuation decline of CL presented with four breakpoints in 1997, 2002, 2006, and 2013. Aggregation and dispersion tendencies with linear characteristics of SL expansion and CL change were found with breakpoints in 2001, 2008, 2012, and 2016 and breakpoints in 2001 and 2010, respectively. A spotty spatial pattern of SL was shown spatially coincident with urban agglomerations in China while the planar continuous characteristic was found for CL. Local counties were classified into five tradeoff and synergies zones (TSZs), where general synergies (G-S) and decoupling (D) of SL expansion and CL change were rare cases and the different change in quantity and trend of SL expansion and CL change in local counties was concealed by the national trend. A few scattered counties were belonging to G-S and D TSZs, while most of the counties in the central-east and western China were in General-Tradeoff (G-T) and Superior-Tradeoff (S-T) TSZs. Counties in south and north China with higher percentages of CL were more prevalent in Superior-Synergy (S–S) TSZ. Our findings explicated the complex relationships between SL expansion and CL change of China at the national scale and in local counties, which pointed out the differences of unified land use management activities across scales and could provide insights for future policy-making and management measures of land use to both ensure the national food security and promote regional sustainable development more synchronously.

Temporal and Spatial Analysis of Coupling Coordination in Beijing–Tianjin–Hebei Urban Agglomeration: Ecology, Environment and Economy

With the rapid growth and development of urban areas, the economy has often been prioritized at the expense of the environment and ecological systems. However, it is essential to delve deeper into the relationship between the economy and the ecological environment. Therefore, this study introduces a comprehensive evaluation system that encompasses economic, ecological, and environmental factors in the Beijing–Tianjin–Hebei urban agglomeration in China. The Criteria Importance Through Inter-criteria Correlation (CRITIC) method is utilized to determine the weights of various indicators, and coupling as well as coupling coordination models are employed to investigate the spatiotemporal trends and interrelationships of the three factors. The results indicate that the economic development index has displayed a consistent uptrend since 2000, with the economic development index from 2015–2020 increasing by approximately four times compared to 2000–2005. The ecological status index has also increased in the last five years, with a rise of about 0.05 from 2015–2020 compared to 2000–2005. The environmental status index has fluctuated but generally increased, with a rise of approximately 5.6 times from 2015–2020 compared to 2000–2005. The coupling degree of the Beijing–Tianjin–Hebei urban agglomeration is relatively high, with intense coupling from 2005–2020, and moderate coupling from 2000–2005. Furthermore, the coupling coordination has continuously improved from mild maladjustment to barely coordinated from 2000 to 2020, indicating the enhancement of the coupling coordination of the three factors. It is crucial to acknowledge that there exists spatial heterogeneity in both the coupling degree and coupling coordination degree. This heterogeneity stems from the uneven progress in economic development, ecological conditions, and environmental status across various cities. Additional endeavors are required to foster the harmonized advancement of these factors across the entire region.

Spatiotemporal distribution, sources, and ecological risk of soil polycyclic aromatic hydrocarbons in Chinese urban agglomerations from 2000 to 2020

To investigate the spatial and temporal distribution, sources, and ecological risk of soil polycyclic aromatic hydrocarbons (PAHs) in China’s urban agglomerations from 2000 to 2020, a comprehensive search strategy was employed using the keywords “soil”, “PAHs”, and “city”. A total of 122 relevant studies that provided information on individual PAH content during the specified time period were collected. These studies encompassed 20 urban agglomerations in China, which were further categorized into two distinct periods: 2000 to 2010 and 2011 to 2020. The diagnostic ratio method and principal component analysis were employed to identify the sources of PAHs, and a risk quotient model was used to evaluate the soil ecological risk. The results revealed the average PAH content in the 20 urban agglomerations in China from 2011 to 2020 was 2,439 ± 4,633 ng·g-1, which exceeded the severe pollution level cut-off (> 1,000 ng·g-1). The soil PAH content in the period from 2011 to 2020 decreased by 28% compared to the soil PAH content in the period from 2000 to 2010. Soil PAH pollution was more severe in the northern urban agglomerations than in the southern urban agglomerations. Diagnostic ratios and principal component analysis demonstrated that the principal sources in most urban agglomerations in China were traffic and coal combustion. GeoDetector found that coal and fuel oil consumption were the main factors affecting the spatial differentiation of PAHs. The ecological risk quotient showed that approximately 80% of the urban agglomerations were at a medium-high ecological risk from 2000 to 2010, compared with 72% from 2011 to 2020. Thus, it is necessary to deepen energy structure reform to alleviate the threat of serious pollution caused by coal and fuel oil in urban agglomerations.

Spatiotemporal effect and influencing factors of the total factor energy efficiency: Evidence from the urban agglomerations in China

Amidst the ongoing global energy quandary, the imperative to augment energy efficiency emerges as a strategic response to counteract energy profligacy and propel sustainable development initiatives. This study aims to assist policymakers in gaining a more accurate understanding of the temporal and spatial complexity and dominant variables of total factor energy efficiency at the urban agglomeration level, thereby providing empirical insights for promoting a comprehensive improvement of the existing energy development framework. Based on the dynamic DEA model, this article utilizes an improved common frontier dynamic super-efficiency SBM model to conduct a quantitative analysis of total factor energy efficiency across 19 urban agglomerations in China. The influence factors of total factor energy efficiency are analyzed using spatial kernel density and geographical detectors at both temporal and factor levels. The research findings indicate that: (1) Total factor energy efficiency primarily fluctuates at a mid to low level, with a general decline to below 0.5 after 2018; (2) Significant regional heterogeneity is evident among Chinese urban agglomerations, displaying a “high in the northwest, low in the southeast” regional characteristic; (3) With time lag, the negative spatial spillover effect among regions further intensifies, becoming heterogeneous when the total factor energy efficiency of local urban agglomerations reaches 1.5 or above; (4) The singular and interactive effects of research funding become the main influencing factors of regional differentiation, and the integration of multiple factors is a key driver for enhancing total factor energy efficiency in the new era.

Measurement and spatial correlation analysis of high-quality development Level: A case study of the Yangtze River Delta urban agglomeration in China

Against the backdrop of slowing economic growth and increasing environmental pressure, the Yangtze River Delta city cluster, as one of the largest city clusters in the world, has become more driven in its pursuit of high-quality development. We constructed a system of 24 evaluation indexes and used entropy-weighted TOPSIS to calculate and study the high-quality development index of urban agglomerations in the region. First, the level of high quality development (HQD) of the Yangtze River Delta city cluster generally improved from 2010 to 2021, with 2017 was the best year, while 2010 was the worst year. Second, in the multidimensional evaluation of HQD, Jiangsu excels in innovation and people's livelihood with 0.524 and 0.534, respectively; Shanghai (0.531) excels in coordinated development; Zhejiang excels in green and economic development with 0.557 and 0.484, respectively; and Anhui lags behind in all aspects. Third, the development process of HQD in the Yangtze River Delta region is uneven, and the level of HQD development varies greatly among the city clusters in the province. The measurement results show that Shanghai (0.511) has the highest score, followed by Zhejiang (0.484), Jiangsu (0.440) and Anhui (0.435). Fourth, spatial correlation analysis shows that Shanghai and Jiangsu are mainly distributed in the double-high region, Zhejiang is distributed in the high-low region, while Anhui is concentrated in the low-low region. The results of this study help us understand more deeply the characteristics and challenges of high-quality development in the Yangtze River Delta urban agglomerations and provide a scientific basis for more precise urban development policies.

Feasibility of Urban–Rural Temperature Difference Method in Surface Urban Heat Island Analysis under Non-Uniform Rural Landcover: A Case Study in 34 Major Urban Agglomerations in China

The urban–rural temperature difference is widely used in measuring surface urban heat island intensity (SUHII), where the accurate determination of rural background is crucial. However, traditionally, the entire permeable rural surface has been selected to represent the background temperature, leaving uncertainty about the impact of non-uniform rural surfaces with multiple land covers on the accuracy of SUHII quantification. In this study, we proposed two quantifications of SUHII derived from the primary (SUHII1) and secondary (SUHII2) land types, respectively, which successively occupy over 40–50% of whole rural regions. The spatial integration and temporal variation of SUHII1 and SUHII2 were compared with the result from whole rural regions (SUHII) within 34 urban agglomerations (UAs) in China. The results showed that the SUHII1 and SUHII2 differed slightly with SUHII, and the correlation coefficients of SUHII and SUHII1/SUHII2 are generally above 0.9 in most (32) UAs. Regarding the long-term SUHII between 2003 and 2019, the three methods demonstrated similar seasonal patterns, although SUHII1 (or SUHII2) tended to overestimate or underestimate compared to SUHII. As for the multi-year integration at the regional scale, the day–night cycle and monthly variations of SUHII1 and SUHII were found to be identical for each geographical division separately, indicating that the spatiotemporal pattern revealed by SUHII is minimally affected by the diversity of rural landcover types. The findings confirmed the viability of the urban–rural LST difference method for measuring long-term regional SUHII patterns under non-uniform rural land cover types.

The confrontation and symbiosis of green and development: Coupling coordination analysis between carbon emissions and spatial development in urban agglomerations of China

Chinese cities face challenges of uneven development, high carbon emission intensity, and low efficiency in urbanization processes. Achieving harmonization and equilibrium between urban development and carbon emissions is crucial for sustainable development. This paper analyzes the development trajectory from 2013 to 2021 of four urban agglomerations in China: Northeast China (NEC), Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD). It identifies and calculates the urban spatial development patterns and carbon emissions, comparing the spatial-temporal variations in carbon emissions under different urban development patterns. The study also explores the coupling coordination relationship between these two aspects at various stages. The findings suggest that urban spatial development and carbon emissions are often uncoordinated in shrinking cities. In terms of coordination within urban agglomerations, BTH and NEC show suboptimal development, characterized by overall lag and polarization; YRD exhibits the best development, being consistently stable and balanced; PRD is generally improving, though with some cities lagging. Planning departments should revise urban and environmental policies to optimize spatial structures and infrastructure, aligning with regional development and promoting synergy in urban agglomerations. This research provides theoretical and empirical support for China to formulate relevant policies aimed at green, coordinated, and sustainable urban development.

Do New Urbanization Policies Promote Sustainable Urbanization? Evidence from China’s Urban Agglomerations

China’s urbanization has received as much attention as its economic growth in recent years. While rapid urbanization has promoted modernization and wealth creation, it has also brought many problems and challenges. So, since 2014, the Chinese government has implemented a new urbanization policy nationwide. However, few researchers have examined whether China’s new urbanization policies promote sustainable urbanization. This paper evaluates the sustainable urbanization of 19 urban agglomerations in China using the elastic coefficient. The results indicate a significant increase in the number of cities achieving sustainable urbanization since the implementation of China’s new urbanization policy. The number has risen from 46 in the period of 2010–2015 to 71 in the period of 2015–2021. Considering the impact of the new coronavirus on economy, there would have been even more cities entering sustainable urbanization during the latter period. This indicates that the new urbanization policy has a positive influence on the sustainable urbanization of China’s urban agglomerations. The sustainable urbanization status is not static and changes with different policies that are implemented in different time periods. Therefore, it is important to find useful policies that can guide and enhance the urbanization process in these cities. In addition, cities that have a sustainable urbanization status are not perfect. To address this issue, it is important to categorize and implement targeted policies for cities experiencing both sustainable and non-sustainable urbanization. Changes in a city’s size or urbanization rates are not related to the city’s sustainable urbanization status. A larger city size does not indicate sustainable urbanization, and, similarly, cities with faster urbanization rates do not exhibit a higher level of urbanization sustainability.

Spatial-temporal differentiation of urban eco-efficiency and its driving factors: A comparison of five major urban agglomerations in China.

This paper utilizes an improved undesirable output DEA model to measure the eco-efficiency of cities in five major urban agglomerations in China during 2006-2020. It employs the Theil Index and Geodetector to investigate the spatial-temporal distribution differentiation characteristics and driving factors of urban eco-efficiency. The main findings are as follows. Firstly, the eco-efficiency of all urban agglomerations showed a fluctuating upward trend, but the eco-efficiency performance of different urban agglomerations in China shows a stratification characteristic. Specifically, the Pearl River Delta urban agglomeration consistently ranks first in China, while the mean values of the Yangtze River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration, and Chengdu-Chongqing urban agglomeration are lower than the national average. Secondly, the overall differences in the urban eco-efficiency of all sample cities show a consistently fluctuating downward trend. The factor that affects the level differences of eco-efficiency in different cities is the intra-regional differences. Last but not least, the top three factors affecting the spatial distribution difference of urban eco-efficiency in the whole sample are environmental pollution control investments, innovation level, and environmental infrastructure investments. In the end, this paper proposes that reducing the intra-regional differences is the primary task to achieve the coordinated improvement of urban eco-efficiency in urban agglomerations, and then puts forward some policy suggestions to improve eco-efficiency for the five major urban agglomerations.

Assessment the urbanization sustainability and its driving factors in Chinese urban agglomerations: An urban land expansion - Urban population dynamics perspective

Achieving urbanization sustainability is considered to be both an important component of the Sustainable Development Goals and a key way to address the conflict between limited resource constraints and urban continued growth. Regarding the urbanization sustainability, the impact of ecological environment and resource consumption has been widely discussed, while the holistic effect of urban land expansion and urban population dynamics is under-researched. This paper evaluated the urbanization sustainability of 15 urban agglomerations in China from 2000 to 2020, and applied the Geodetector model to investigate its impact mechanism. The results show that at the national level, the level of urbanization sustainability exhibited a trend of first increasing and then decreasing, accompanied by significant spatial differentiation. Spatially, the level of urbanization sustainability in urban agglomerations located in the northeast regions had strong variability during the study period. In contrast, urban agglomerations located in the central region had a lower level of urbanization sustainability due to the unrestricted expansion of urban land. In addition, urbanization sustainability varied according to the development stage of urban agglomerations. Specifically, urbanization sustainability showed a downward trend in the initial development stage, early growth stage and later growth stage of urban agglomeration, and upward trend in mature stage. Economic development level, foreign direct investment, industrial structure and urbanization level were the primary determinants of differences in urbanization sustainability at both national and regional levels. These findings may help to formulate the urban sustainable development planning and differentiated land use policies.

The effect of the digital economy service industry on regional economic resilience: evidence from three major urban agglomerations in China

ABSTRACT The digital economy has become an important driving force for countries to rebuild economic development during COVID-19. However, its effect on regional economic resilience is still unclear. The purpose of this paper is to study the theoretical mechanism of the digital economy service industry affecting regional economic resilience and to construct an econometric model to empirically test the overall impact of the digital economy on regional economic resilience, as well as the threshold effect of the level of manufacturing development. The study finds that (1) the digital economy service industry has a significant positive impact on regional economic resilience. (2) With improvement in the level of manufacturing development, the positive contribution of the digital economy service industry to the regional economic resilience is enhanced, and the effective coupling of the digital economy service industry and the manufacturing industry can improve the regional economic resilience to a greater extent. Therefore, this paper proposes that, to improve the resilience of the regional economy, we should not only improve the level of digital technology of the digital economy service industry, but also focus on the application of digital technology in the real economy, especially in the manufacturing industry, encourage the digital transformation of enterprises, and improve the digital governance capacity of the government.

A Dynamic Collision Risk Assessment Model for the Traffic Flow on Expressways in Urban Agglomerations in North China

Expressways in urban agglomerations are important in connecting cities, thus attracting great attention from researchers in the expressways risk assessment. However, there is a lack of safety assessment models suitable for the characteristics of expressways in Chinese urban agglomerations, and the nature and mode of dynamic risks on Chinese highways are still unclear. Therefore, this study adopts the Adaptive Neural Fuzzy Inference System (ANFIS) and the method of decision tree, combined with data from the Beijing section of the Beijing Harbin Expressway, to model the risk of accident-prone highways in urban agglomerations. To determine the optimal model, we evaluated the model’s bias at different time intervals. In addition, key factors affecting highway safety were analyzed, providing scientific support for the risk prevention of highways in urban agglomerations in China.

Spatiotemporal evolutionary characteristics and driving forces of carbon emissions in three Chinese urban agglomerations

Assessing carbon emissions in urban agglomerations has emerged as a pivotal step towards achieving carbon neutrality. In this study, panel data from 75 cities within the three largest urban agglomerations in China—the Yangtze River Delta (YRD), Beijing-Tianjin-Hebei (BTH) region, and Pearl River Delta (PRD)—were constructed to analyse the spatiotemporal evolution of carbon emissions from 2005 to 2020. An indicator system was established, and the Spatial Durbin Model (SDM) was used to investigate the driving forces of carbon emissions. The findings revealed a gradual increase in carbon emissions within these agglomerations, with a notable shift in their spatial distribution from metropolitan areas to broader urban agglomerations, exhibiting significant spatial correlation. Additionally, variations in carbon emissions were observed across different development stages. The SDM indicated that several factors, such as economic conditions, industrialization levels, and population size, influenced the carbon emissions of urban agglomerations. Nevertheless, the impact of these driving factors on carbon emissions was not constant and could be altered by other elements, including green technologies and governmental policies, indicating a decoupling effect between economic growth and carbon emissions. The insights from this study can assist policymakers in formulating strategies to curb carbon emissions and foster sustainable development.

Urbanization effects on the food-water-energy nexus within ecosystem services: A case study of the Beijing-Tianjin-Hebei urban agglomeration in China

This research centers on the necessity for synchronized management of natural resources in urban agglomerations. This study utilizes the ecosystem services theory to analyze the interplay between land use and the Food-Water-Energy (F-W-E) nexus in the Beijing-Tianjin-Hebei (B-T-H) region from 2000 to 2030. Assessment of ecosystem services is conducted using InVEST models, which include Habitat Quality (HQ), Water Yield (WY), Carbon Sequestration (CS), Soil Retention (SDR), and Food Production (FP). The findings indicate an annual increase in construction land with a concurrent notable decrease in cultivated land. Furthermore, HQ, CS, and per capita FP show an annual decline until 2020, which is expected to continue until 2030. Conversely, WY and SDR have been growing annually, albeit projected to decline by 2030. Spearman coefficient analysis uncovers synergies between HQ and CS, SDR and CS, and SDR and HQ, alongside trade-offs between CS and WY and HQ and WY. Trade-offs are also observed between FP and SDR, CS, and HQ. Applying K-means clustering analysis facilitates county-based spatial planning for the F-W-E system, providing crucial insights and suggestions for sustainable resource management.

Comparison of Different Impact Factors and Spatial Scales in PM2.5 Variation

PM2.5 particles with an aerodynamic diameter of less than 2.5 μm are receiving increasing attention in China. Understanding how complex factors affect PM2.5 particles is crucial for the prevention of air pollution. This study investigated the influence of meteorological factors and land use on the dynamics of PM2.5 concentrations in four urban agglomerations of China at different scales from 2010 to 2020, using the Durbin spatial domain model (SDM) at five different grid scales. The results showed that the average annual PM2.5 concentration in four core urban agglomerations in China generally had a downward trend, and the meteorological factors and land use types were closely related to the PM2.5 concentration. The impact of temperature on PM2.5 changed significantly with an increase in grid scale, while other factors did not lead to obvious changes. The direct and spillover effects of different factors on PM2.5 in inland and coastal urban agglomerations were not entirely consistent. The influence of wind speed on coastal urban clusters (the Pearl River urban agglomeration (PRD) and Yangtze River urban agglomeration (YRD)) was not significant among the meteorological factors, but it had a significant impact on inland urban clusters (the Beijing–Tianjin–Hebei urban agglomeration (BTH) and Chengdu–Chongqing urban agglomeration (CC)). The direct effect of land use type factors showed an obvious U-shaped change with an increase in the research scale in the YRD, and the direct effect of land use type factors was almost twice as large as the spillover effect. Among land use type factors, human factors (impermeable surfaces) were found to have a greater impact in inland urban agglomerations, while natural factors (forests) had a greater impact in coastal urban agglomerations. Therefore, targeted policies to alleviate PM2.5 should be formulated in inland and coastal urban agglomerations, combined with local climate measures such as artificial precipitation, and urban land planning should be carried out under the consideration of known impacts.

Regional integration policies and urban green innovation: Fresh evidence from urban agglomeration expansion

Climate change is a non-traditional security crisis affecting the global economy and diplomatic progress. In order to curtail carbon emissions and alleviate the perils of climate change at their roots, urban green innovation (UGI) has emerged as a pivotal technological solution. Using the expansion of the Yangtze River Delta urban agglomeration in China as a case study, this paper develops a quasi-experimental model to analyze the effects of regional integration policies on UGI. The main findings are: (1) Regional integration policies significantly enhance UGI and their impact is more pronounced with the expansion of urban agglomerations; (2) Regional integration policies contribute to the advancement of exploitative green innovation while tending to diminish exploratory green innovation; (3) The green innovation effects (GIEs) created by the expansion of regional integration policies are largely influenced by governmental mechanisms on environmental governance as well as residents’ green preferences. Based on these findings, recommendations are put forward to promote UGI from the perspective of policy implementation.

Nonlinear Variations in PM2. 5 Concentration in the Three Major Urban Agglomerations in China

ITA and Beast methods were used to quantitatively analyze the nonlinear process of a PM2.5 concentration time series based on the PM2.5 concentration data of the three major urban agglomerations in China. The results showed that： ① the degree of the PM2.5 pollution in the three major urban agglomerations had decreased， and the high-concentration areas had noticeably shrunk. The degree of spatial polarization of PM2.5 concentration was reduced， and the spatial difference was narrowed. The PM2.5 concentration in most areas showed downward trends， but the degree of change was not the same. Compared with the YRD and PRD， the concentration of PM2.5 in the BTH was still at a relatively high level. ② The concentration of PM2.5 in the three major urban agglomerations had seasonal variation characteristics that were high in winter and spring and low in summer and autumn. There were obvious differences in PM2.5 concentration between winter and summer， and the convergence of PM2.5 concentration in summer was greater than that in winter. Areas with high PM2.5 concentration also had obvious downward trends， but the downward trends of PM2.5 concentration in the PRD were not obvious compared with those in the YRD and BTH. ③ The PM2.5 concentration time series of the three major urban agglomerations all had significant downward trends： Beijing-Tianjin-Hebei （BTH） > the Yangtze River Delta （YRD） > the Pearl River Delta （PRD）. The PM2.5 concentration had the largest downward trends in winter. The higher the PM2.5 pollution level， the greater the downward trends. ④ The trend component of the PM2.5 concentration time series in the BTH had two change points， and there was one change point in the seasonal component. The trend and seasonal components of the PM2.5 concentration time series in the YRD had no change point. There was no change point in the seasonal component but one change point in the trend component of the PM2.5 concentration time series in the PRD. These results can provide scientific references for regional air pollution control.