Managing urban agglomeration processes in Russia in the context of agglomerative and socio-economic development

Studies on urban agglomeration typically focus on the management of urban agglomerations as special types of spatial organization. The problem of finding an adequate management model which accounts for the level of spatial connectivity and socio-economic development of a given territory remains in the background. This article identifies urban agglomeration management models in Russia which account for the agglomerative and socio-economic development of a given territory. A methodology for assessing urban agglomeration processes is presented which, unlike existing methodologies, includes an assessment of agglomeration maturity and an assessment of the socio-economic development of urban agglomerations. This methodology is based on conceptual platforms within spatial development theory; new economic geography; and agglomeration theory and cluster development. The methodology was tested on the data of Chelyabinsk Region agglomerations. The study determined that the Chelyabinsk and Gorniy Ural agglomerations are socio-economically developed and highly agglomerated, while the Magnitogorsk agglomeration shows high socio-economic development and low agglomeration. The conurbations are underdeveloped in both areas. The paper gives several recommendations on methods for choosing urban agglomeration management models. The developed methodology can be used to assess agglomerations across Russia and to choose the most adequate management model for a territory depending on its agglomerative and socio-economic development.

A new perspective on anthropogenic nitrogen loss mitigation strategies: Integrated control via sustainable regional integration

Unregulated regional integrated development disrupts the reactive nitrogen (Nr) cycle, adding complexity to anthropogenic Nr environmental losses. The objective of this study was to establish a framework for mitigating anthropogenic Nr loss through a new regional integration perspective by analyzing anthropogenic Nr loss and integrated control strategies in the Yangtze River Delta (YRD) region from 2011 to 2020. The results revealed that the total Nr loss in the YRD ranged from 1780.7 to 1972.0 Gg N yr-1. Re-linking cropland and livestock is crucial for reducing Nr loss, as they act as the main sources of Nr loss. Spatial analysis at the regional scale revealed that regional integration has led to a dispersion of Nr loss, while uneven development among cities has resulted in a westward shift of 8.6 km in the Nr loss centroid, suggesting the need for the implementation of collaborative governance and integrated environmental regulation in the YRD. At the city scale, 27 cities were clustered into six types based on the similarity of Nr loss structural characteristics, allowing for the development of targeted reduction policies based on the specific Nr structural characteristics of each city. The results of driver and mitigation potential analysis indicated the feasibility of achieving the shared goal of sustainable regional integration and the application of optimal mitigation strategies in different cities and the YRD. Overall, the new-perspective framework established in this study provides valuable references for sustainable Nr management in the context of regional integration.

Research on the coupling mechanism and influencing factors of digital economy and green technology innovation in Chinese urban agglomerations

This paper examines the coupling coordination degree between digital economy and green technology innovation in 19 urban agglomerations across China from 2011 to 2020. Through the analysis of the coupling coordination degree model, spatial autocorrelation, multi-distance spatial clustering analysis, kernel density analysis and grey correlation model, this study uncovers the mechanism of coupling between digital economy and green technology in Chinese urban agglomerations. Data analysis revealed a significant increase in the coupling coordination between the digital economy and green technology innovation within urban agglomerations. However, there are noticeable spatial imbalances in this trend. Additionally, the multi-distance spatial distance analysis highlights a shift from a random distribution to a clustered distribution of spatial characteristics. The polarization features vary among each urban agglomeration and exhibit a significant positive spatial correlation. Factors such as economic sustainability, creative talent, policy support, digital impetus, and technological support will affect the coupling mechanism of green technology innovation and the digital economy in China's urban agglomerations. Policy recommendations are proposed to foster the development of the digital economy, promote coordinated growth within and beyond urban clusters, and ultimately build a digital ecological civilization that is both green and intelligent.

An urban metabolism framework purpose to assess the dynamics of linear alkylbenzenes (LABs) discharge flows and driving forces at the city level in Guangdong province, China

Linear alkylbenzenes (LABs) are a class of molecular markers derived from anthropogenic activities. A comprehensive understanding of the mechanism that determines their entry into anthroposphere, in terms of magnitude and pathway, is the prerequisite to establish effective mitigation measures. This study develops a methodology framework to analyze the source-sink interactions and driving factors of the direct and indirect LAB discharges from production and living activities in Guangdong Province, China from 2004 to 2017. Results indicated that the total LAB discharges of Guangdong into the environment were averaged at 2.9 kt yr-1, of which 61.9% originated from the Pearl River Delta (PRD) urban agglomeration. An average proportion of 76.0% was discharged into water bodies with the remaining released into land bodied. From 2014 to 2017, the LAB discharges increased by seven times, resulting from the steady increase of urban residential sources, while contribution from industrial sources continuously declined during the studied period. Meanwhile, the discharging hotspots expanded from Guangzhou city to other super-cities around it, including Shenzhen and Dongguan. The other cities exhibited a decreasing trend in discharges as a function of distance from these hotspot cities. The multisectoral sources of LABs differed considerably among cities, and the source contribution of each city changed significantly with progressive urbanization. The factor decomposition analysis indicated that LAB discharges in PRD cities primarily contributed by the pollutant concentration and reflected the treatment structure, while peripheral cities of the PRD mainly contributed by the per capita consumption and pollutant discharge per unit of GDP. Overall, our results provide a scientific database and supports for the regional co-remediation of anthropogenic pollution.

Threshold effect of ecosystem services in response to human activity in China's urban agglomeration: a perspective on quantifying ecological resilience

Ecological resilience reflects the role of human activity intensity (HMI) on regional ecosystem services (ESs), and resilience improvement is crucial for the high-quality development of urban agglomeration areas. However, a theoretical framework for ecological resilience needs to be developed based on ES thresholds under human activities. Based on the threshold index, we used threshold regression model to determine of the nonlinear dominant factors affecting ESs and to identify the priority areas for ecological restoration. The results suggest that (1) CS, HQ, and TES declined, while FP increased. The spatial distribution of each ES showed higher values in the central region and lower values in the surrounding areas. HMI showed a significant upward trend, with expanding high-HMI areas. There is a threshold effect in the relationship between HMI and ESs, leading to variations in their positive, non-monotonic, or non-linear interactions. (2) HMI positively and significantly affects ESs, especially at low threshold levels. The effect of HMI on ESs is negative in counties with higher threshold levels rather than in lower-level grids. (3) The critical area of artificial potential ecological restoration was 712 km2, primarily concentrated around urban; the critical area of natural restoration was 490 km2. Therefore, the threshold in the relationship between HMI and ESs should be given more attention. This study serves as a guide for picking out key regions for territorial ecological restoration.

Thriving arid oasis urban agglomerations: Optimizing ecosystem services pattern under future climate change scenarios using dynamic Bayesian network

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide.

Do urban agglomeration planning policies promote the discharge reduction of industrial wastewater: Evidence from the Yellow River Basin in China

The environmental effects of the urban agglomeration planning policy (UAPP) are an exploration by rapidly developing China and a concern for countries seeking development and urban reform around the world. This paper takes the three regional urban agglomerations in the Yellow River Basin (YRB) as the research object and collects the panel data of 106 prefecture-level cities from 2006 to 2019 to study the reduction effects of UAPP on the industrial wastewater discharge (IWD). The empirical results from Difference-in-Differences models indicate that UAPP can significantly inhibit IWD. UAPP reduces IWD by promoting green innovation, and the development of service industries can strengthen this effect. UAPP shows a stronger IWD reduction effect in the northeast YRB than that in the southwest region. Compared to urban agglomerations with a single provincial jurisdiction, UAPP exerts stronger IWD reduction effects on urban agglomerations with multiple jurisdictions. Moreover, there exist spatial spillover effects of UAPP on IWD. These findings provide support and references for urban reform and the development of green cities in countries around the world, especially in developing countries.

Decomposition and decoupling analysis of carbon emissions in the Yellow River Basin: evidence from urban agglomerations

A comprehensive understanding of carbon emission reduction and decoupling in urban agglomerations of the Yellow River Basin (YRB) has significant theoretical and practical value for formulating precise carbon reduction policies and achieving ecological conservation and high-quality development in the region. This study utilized a generalized Divisia index decomposition model to identify the primary driving factors behind carbon emission changes in urban agglomerations of the YRB. Based on this, a model measuring decoupling efforts was constructed to systematically investigate the decoupling relationship between carbon emissions. The research findings indicate that technological progress and output scale are two primary drivers of carbon emission increases in the YRB and its urban agglomerations, whereas technological carbon intensity, output carbon intensity, and energy carbon intensity play key roles in reducing carbon emissions. Except for a few years, the YRB and Jiziwan metropolitan area (JWMA) did not exhibit decoupling effects on carbon emissions. The Shandong Peninsula Urban Agglomeration (SPUA) and Central Plains Urban Agglomeration (CPUA) showed strong decoupling effects from 2016 to 2019. The Guanzhong Plain Urban Agglomeration (GPUA) demonstrated a strong decoupling effect from 2013 to 2019 (except from 2016 to 2017). The Lanxi Urban Agglomeration (LXUA) exhibited a strong decoupling effect from 2014 to 2019. Technological carbon intensity plays a decisive role in the transition from non-decoupling to decoupling. Therefore, the government must increase investments in green and low-carbon technologies and strictly implement carbon reduction measures. Thus, the YRB and its urban agglomerations have considerable potential for carbon emission reduction and strong decoupling effects.

Urban resilience in China's eight urban agglomerations: evolution trends and driving factors

Improving urban resilience (UR) and enhancing urban anti-risk ability are important foundations for promoting the high-quality development of new urbanization. This research employs the time-varying entropy method to evaluate the resilience level of 138 cities within China's eight urban agglomerations (UAs) between 2005 and 2019. Additionally, the Dagum Gini coefficient and the kernel density estimation method are utilized to examine the spatial disparities and distribution dynamics of UR across the eight UAs. The results of this investigation indicate that (1) the collective UR performance of the eight UAs has experienced an upward trend. However, a notable spatial disparity exits, which is primarily attributed to the differences among the UAs. (2) The overall UR development of the eight UAs has a certain gradient effect, and the UR within each UA has different degrees of polarization characteristics. (3) For the eight UAs as a whole, per capita savings deposits, capitalization of foreign capital, and per capita fiscal expenditure are the three most important driving factors. Within each UA, there was heterogeneity in the main influencing factors. The interplay between any two factors amplifies their individual driving effects on the spatial differentiation of UR.

Comprehensive evaluation of urban waterlogging prevention resilience based on the fuzzy VIKOR method: a case study of the Beijing-Tianjin-Hebei urban agglomeration

The Beijing-Tianjin-Hebei urban agglomeration was used to construct a comprehensive evaluation index system for urban waterlogging prevention and control resilience from five aspects: social resilience, economic resilience, ecological resilience, infrastructure resilience, and institutional resilience. The fuzzy VIKOR method was used to evaluate urban waterlogging prevention and control resilience. The results were analyzed at temporal and spatial scales to reveal regional differences and constraints in urban waterlogging prevention toughness and efficiently locate vulnerable urban areas. The resilience level in most of the Beijing-Tianjin-Hebei region increased during 2015-2019, while that of Beijing, Tianjin, Qinhuangdao, and Handan slightly decreased, indicating that the capacity of these cities to manage waterlogging disasters needs strengthening. The spatial difference in urban waterlogging prevention toughness was significant: Beijing, Tianjin, Handan, Tangshan, Langfang, and Shijiazhuang showed medium and high levels of urban waterlogging prevention toughness; other cities showed low levels. How the expansion speed of the urban scale matches the construction speed of urban waterlogging prevention and control directly affects resilience at all levels. These results support urban waterlogging control and regional integration construction for Beijing-Tianjin-Hebei.

Investigation of spatial association network features of construction waste in major Chinese urban agglomeration

The illegal dumping of construction waste (CW) poses an increasingly serious environmental pollution problem with the accelerated rate of urbanization. As CW disposal capacity struggles to match municipal needs, some CW is being diverted to higher resource endowment cities rather than recycled. To address this situation, it is necessary to obtain reliable information on the characteristics and evolution of CW generation networks in China. This study combines a modified gravity model with Social Network Analysis (SNA) to analyze the spatial association networks of CW generation in four Chinese urban agglomerations between 2000 and 2020. Results reveal the evolution characteristics of the CW generation network, including increasing density and correlation and decreasing network efficiency. Furthermore, the Quality Assurance Procedure (QAP) indicates that urbanization level and population size are positively correlated with CW generations, whereas distance plays a negative role, but resources are insignificant for network formation. The findings provide insight into current patterns of waste distribution and a theoretical basis for government policy formulation in the future.

Impact of industry-university-research collaboration and convergence on economic development: Evidence from chengdu-chongqing economic circle in China

Collaboration among industry, universities, and research is crucial for building an innovative nation. Although industry-university-research collaborative innovation (IURCI) and time-space convergence can drive innovation, increase productivity, and spur economic development, their effects on the regional economy have not been thoroughly examined in existing literature. Therefore, this study investigates the impact of industry-university-research collaborative innovation (IURCI) and time-space convergence on economic development in China. Specifically, we focus on local-level cities in the Chengdu-Chongqing Economic Circle (CCEC) and construct an evaluation index system and time-space convergence model to measure the effects of IURCI and time-space convergence on economic development from 2007 to 2021. Our findings indicate that the efficacy of IURCI on economic development in China follows an inverted U-shaped curve, meaning that the marginal impact of IURC may decrease as more creative funds are deployed. Furthermore, the positive marginal effect of inventive talent input may decrease when it surpasses a certain value in an open innovation environment. The spatiotemporal convergence of collaborative innovation and development levels of IURCI in the CCEC shows significant differences. Regionally, the development level of IURCI in different regions exhibits significant differences in state and speed of convergence. In the southern Sichuan urban agglomeration, the collaborative innovation level of industry, education, and research follows an evolutionary process from convergence to divergence and then to convergence. Policymakers should pay close attention to the spatial effect of high-level development of regional IURCI and promote regions with higher development to drive regions with relatively weak development levels.

Vulnerability assessment of urban agglomerations to the risk of heat waves in China since the 21st century

In the context of global warming, frequent heat wave disasters have seriously threatened the safety of human life and property. The urban agglomeration, as the main region with a high concentration of population and economy, is susceptible to heat weaves due to the existing urban heat island effect. In this study, we investigated the temporal and spatial characteristics of heat waves (heat index, HI) in China from 2000 to 2020 and assess the vulnerability of 19 urban agglomerations to heat waves from the perspective of exposure, sensitivity and adaptability. The results show that: (1) In the past 20 years, the frequency and intensity of HI (greater than 26.67 °C) both showed an upward trend. (2) Shandong Peninsula, Central Henan, Yangtze River Delta, Middle Reaches of Yangtze River, and Mid-southern Liaoning urban agglomerations always maintain a high vulnerability. (3) From 2000 to 2020, the vulnerability of Beijing-Tianjin-Hebei, Yangtze River Delta, Chengdu-Chongqing, Middle reaches of Yangtze River, Guangdong-Fujian-Zhejiang, Harbin-Changchun and Mid-southern Liaoning urban agglomerations were always dominated by exposure. The vulnerability of Shandong Peninsula, Beibu Gulf and Central Henan urban agglomeration has always been dominated by sensitivity. The vulnerability of North Tianshan Mountain, Lanzhou-Xining, Guanzhong and Hu-Bao-E-Yu urban agglomeration has always been dominated by inadequate adaptability. (4) Recently, the factors that contributed most to exposure, sensitivity and adaptability were population density, the proportion of outdoor workers and water supply, with contribution rates of 38%, 55% and 26%, respectively. This study can provide a scientific basis for the rational allocation of resources among urban agglomerations, effectively formulating policies and guiding population migration from high temperature disasters.

Spatial-temporal dynamics of land use carbon emissions and drivers in 20 urban agglomerations in China from 1990 to 2019

Urban agglomerations (UAs) are the largest carbon emitters; thus, the emissions must be controlled to achieve carbon peak and carbon neutrality. We use long time series land-use and energy consumption data to estimate the carbon emissions in UAs. The standard deviational ellipse (SDE) and spatial autocorrelation analysis are used to reveal the spatiotemporal evolution of carbon emissions, and the geodetector, geographically and temporally weighted regression (GTWR), and boosted regression trees (BRTs) are used to analyze the driving factors. The results show the following: (1) Construction land and forest land are the main carbon sources and sinks, accounting for 93% and 94% of the total carbon sources and sinks, respectively. (2) The total carbon emissions of different UAs differ substantially, showing a spatial pattern of high emissions in the east and north and low emissions in the west and south. The carbon emissions of all UAs increase over time, with faster growth in UAs with lower carbon emissions. (3) The center of gravity of carbon emissions shifts to the south (except for North China, where it shifts to the west), and carbon emissions in UAs show a positive spatial correlation, with a predominantly high-high and low-low spatial aggregation pattern. (4) Population, GDP, and the annual number of cabs are the main factors influencing carbon emissions in most UAs, whereas other factors show significant differences. Most exhibit an increasing trend over time in their impact on carbon emissions. In general, China still faces substantial challenges in achieving the dual carbon goal. The carbon control measures of different UAs should be targeted in terms of energy utilization, green and low-carbon production, and consumption modes to achieve the low-carbon and green development goals of the United Nations' sustainable cities and beautiful China's urban construction as soon as possible.

Environmental quality assessment and spatial spillover effects of three urban agglomerations in China: A Meta-EBM approach

The new development form of urban agglomeration has greatly promoted economic and social progress in recent years, but it is also facing severe environmental pollution problems. Understanding the status quo of environmental efficiency in urban agglomerations and its leading driving forces is an important prerequisite for formulating energy conservation and emission reduction policies. This research uses the Meta Epsilon Based Measure (Meta-EBM) model to measure the environmental emission efficiency of the Beijing-Tianjin-Hebei（BTH）, Yangtze River Delta (YRD) and Pearl River Delta (PRD) urban agglomerations in China from 2014 to 2018 so as to improve on the inability of traditional Data Envelopment Analysis (DEA) to combine linear and non-linear characteristics, and employs Moran's I index and spatial econometric methods to analyze their spatial dependence and main driving factors. The results demonstrate that the overall environmental efficiency of the three major urban agglomerations in the five years from 2014 to 2018 presents a wave-like development and then tends to be flat. The itemized efficiency of economic outputs has maintained a relatively high level with the environmental output index exhibiting the best efficiency for industrial wastewater, followed by industrial sulfur dioxide (SO2). The scores of the two indicators for inhalable fine particle emissions (PM2.5) and industrial smoke and dust in each urban agglomeration are not ideal, and there are obvious differences between regions. Among them, YRD and PRD are relatively inferior. From the perspective of spatial spillover effects, various indicators show diverse characteristics at different development stages of the regions. Population and Normalized Difference Vegetation Index (NDVI) have a positive effect on environmental efficiency, while both Gross Domestic Product (GDP) per capita and transportation tend to show greater negative effects on regional environmental optimization. This study proposes countermeasures as follows. Each urban agglomeration should set up measures suitable to local conditions and give full play to their location advantages. They can also use space radiation to promote sector economic development and optimize urban environmental benefits.

Do economic development and tourism heterogeneously influence ecological sustainability? Implications for sustainable development

While economic development-driven anthropogenic emissions pose challenges to ecological sustainability, the international travel and tourism sector has appeared as a hot contestant to bring sustainability to the ecological systems across varying development levels. This work investigates the diversified effects of the international travel and tourism sector and economic development on ecological deterioration, in the presence of urban agglomeration and energy use efficiency, across the development levels of China's 30 provincial units from 2002 to 2019. It contributes in two ways. (i) The stochastic estimation of environmental impacts by regression on population, affluence, and technology (STIRPAT) is modified to integrate the variables like international travel and tourism sector, urban agglomeration, and energy use efficiency. (ii) We measured an international travel and tourism sector index (ITTI) and made use of a continuously updated bias correction strategy (CUBCS) and a continuously updated fully modified strategy (CUFMS) for the long-term estimations. Besides, we used the bootstrapping-based causality technique for determining causality directions. The core results are as follows: Firstly, ITTI and economic development produced an inverse U-type association with ecological deterioration for the aggregate panels. Secondly, provinces exhibited a diverse range of links in that ITTI mitigated (boosted) the ecological deterioration in eleven (fourteen) provinces presenting diversified shapes of linkages. Economic development established the environmental Kuznets curve (EKC) theory with ecological deterioration in merely four provinces; however, the non-EKC theory is verified in twenty-four divisions. Thirdly, in China's east zone (high development scale), the ITTI revealed the ecological deterioration reduction (promotion) impact in eight (two) provinces. China's central zone (moderate development scale) exhibited ecological deterioration promotion in half of the provinces, and the other half showed a reduction impact. In China's west zone (low development scale), it promoted ecological deterioration in eight provinces. Economic development promoted (reduced) ecological deterioration in a single (nine) province(s). In China's central zone, it boosted (mitigated) the ecological deterioration in five (three) provinces. In China's west zone, it promoted (reduced) ecological deterioration in eight (two) provinces. Fourthly, urban agglomeration and energy use efficiency deteriorated and improved the environmental quality in aggregated panels, respectively; however, a diverse range of effects are observed for provinces. Finally, a unilateral bootstrap causality, from ITTI (economic development) to ecological deterioration, is revealed in twenty-four (fifteen) provinces. A bilateral causality is established in a single (thirteen) province(s). Based on empirical findings, policies are suggested.

Integrating ecosystem services and complex network theory to construct and optimize ecological security patterns: a case study of Guangdong-Hong Kong-Macao Greater Bay Area, China

The urban agglomerations' rapid expansion and population growth have led to the fragmentation of landscape patterns and the degradation of ecosystems, seriously threatening regional ecological security. Ecological security pattern (ESP) is a spatial planning approach to effectively balance the development of urbanization and ecological protection. However, previous studies have ignored the difference in the importance of ecosystem services and the spatial compactness of ecological sources. The quantitative management objectives for maintaining the resilience of ESP are also rarely discussed. In this study, taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as an example, ecological sources were identified by simulating multiple ES weight assignment scenarios through GeoSOS area optimization. Ecological corridors and strategic points were extracted by Linkage Mapper. The robustness analysis based on complex network theory was performed to quantify the management objectives of ESPs. The results showed that ESPs include 26,130.61 km² ecological sources (accounting for 46.6% of the area of GBA), 557 ecological corridors, and 112 ecological strategic points. In more detail, ecological sources are mainly distributed in the western and eastern mountainous areas, and ecological corridors primarily link peripheral edge areas of GBA in a circular radial shape. Compared with the current nature reserves, the identified ecological sources are more compact in landscape pattern. According to the robustness analysis, at least 23% of the important ecological sources should be strictly restricted from development activities to maintain the ESP's ability to resist ecological risks. This study also proposed corresponding differentiated ESPs management strategies. By optimizing the existing ESPs construction method and clarifying the ESPs management strategies, this study provides a completely scientific framework for the construction and management of ESPs in urban agglomerations.

Changes in air pollution, land surface temperature, and urban heat islands during the COVID-19 lockdown in three Chinese urban agglomerations

COVID-19 has notably impacted the world economy and human activities. However, the strict urban lockdown policies implemented in various countries appear to have positively affected pollution and the thermal environment. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and aerosol optical depth (AOD) data were selected, combined with Sentinel-5P images and meteorological elements, to analyze the changes and associations among air pollution, LST, and urban heat islands (UHIs) in three urban agglomerations in mainland China during the COVID-19 lockdown. The results showed that during the COVID-19 lockdown period (February 2020), the levels of the AOD and atmospheric pollutants (fine particles (PM_2.5), NO₂, and CO) significantly decreased. Among them, PM_2.5 and NO₂ decreased the most in all urban agglomerations, by >14 %. Notably, the continued improvement in air pollution attributed to China's strict control policies could lead to overestimation of the enhanced air quality during the lockdown. The surface temperature in all three urban agglomerations increased by >1 °C during the lockdown, which was mainly due to climate factors, but we also showed that the lockdown constrained positive LST anomalies. The decrease in the nighttime urban heat island intensity (UHIInight) in the three urban agglomerations was greater than that in the daytime quantity by >25 %. The reduction in surface UHIs at night was mainly due to the reduced human activities and air pollutant emissions. Although strict restrictions on human activities positively affected air pollution and UHIs, these changes were quickly reverted when lockdown policies were relaxed. Moreover, small-scale lockdowns contributed little to environmental improvement. Our results have implications for assessing the environmental benefits of city-scale lockdowns.

Spatial association network of PM2.5 and its influencing factors in the Beijing-Tianjin-Hebei urban agglomeration

In this paper, we empirically study the spatial association network of PM_2.5 and the factors influencing those correlations using the gravity model, social network analysis (SNA), and the quadratic assignment procedure (QAP) based on data from the Beijing-Tianjin-Hebei urban agglomeration (BTHUA) in China from 2005 to 2018. We draw the following conclusions. First, the spatial association network of PM_2.5 exhibits relatively typical network structure characteristics: the network density and network correlations are highly sensitive to efforts to control air pollution, and there are obvious spatial correlations within the network. Second, cities in the center of the BTHUA have large network centrality values, while cities in the peripheral region have small centrality values. Tianjin is a core city in the network, and the spillover effect of PM_2.5 pollution in Shijiazhuang and Hengshui is the most noticeable. Third, the 14 cities can be divided into four plates, with each plate having obvious geographical location characteristics and linkage effects. The cities in the association network are divided into three tiers. Beijing, Tianjin, and Shijiazhuang are located in the first tier, and a considerable number of PM_2.5 connections are completed through these cities. Fourth, differences in geographical distance and urbanization are the main drivers of the spatial correlations of PM_2.5. The greater the urbanization differences, the more likely the generation of PM_2.5 links is, while the opposite is true for differences in geographical distance.

What role does digital finance play in low-carbon development? Evidence from five major urban agglomerations in China

In the epoch of the digital economy, digital finance (DF) has become an indispensable engine driving the high-quality development of the Chinese economy. The issues of how DF can be used to alleviate environmental pressure and how a long-term governance mechanism for carbon emissions reduction be formed have become particularly important. Based on the panel data of five national urban agglomerations in China from 2011 to 2020, this study utilizes the panel double fixed-effects model and chain mediation model to verify the impact mechanism of DF on carbon emissions efficiency (CEE). Some valuable findings are drawn below. First, the overall CEE of the urban agglomerations has potential for improvement, and the CEE and DF development level of each urban agglomeration have regional heterogeneity. Second, a U-shaped correlation is observed between DF and CEE. Technological innovation and industrial structure upgrading have a chain mediating effect in DF affecting CEE. In addition, the breadth and depth of DF have a notable negative impact on CEE, and the digitalization degree of DF shows a significant positive correlation with CEE. Third, the influencing factors of CEE have regional heterogeneity. Finally, this study provides relevant suggestions based on the empirical conclusions and analysis.

A factorial-based dynamic distributive model for virtual-water management in multi-urban agglomerations - A case study of Yangtze River Economic Belt

The economic development, population growth and rapid urbanization in the Yangtze River Economic Belt (YREB) have resulted in an imbalance between socio-economic development and available water resources of adjacent urban agglomerations. Exploring the virtual water flow (VWF) of adjacent urban agglomerations in YREB is crucial for the collaborative management of water resources. In this study, a factorial-based dynamic distributive model (FDDM) is first developed to analyze the variations in virtual water transfers and inter/inner-sectoral relationships within multi-urban agglomerations, and expound the spatiotemporal diffusion effects of multiple water policy alternatives (and their combinations) for virtual water. The FDDM is applied in YREB's urban agglomerations covering Yangtze River Delta (YRDA), Middle Reach of Yangtze River (MRA) and Chengyu Urban Agglomeration (CYA). The FDDM is capable of i) quantifying the dynamic evolution of direct/indirect virtual water volume and virtual water transfer direction/path between and within urban agglomerations; ii) demonstrating the spatiotemporal changes of the control/dependent relationship within sectors in sub-urban agglomerations, as well as the evolution of utility relationship within the system; iii) evaluating the interactions of different water policies (and their combinations) within each sub-urban agglomeration/key sectors on the direct and indirect virtual water consumption of the system. Our major findings are: (i) YRDA always has the largest direct and indirect water consumption as well as the water consumption intensities from 2007 to 2017; (ii) The three national urban agglomerations have evolved in the direction of benign development; (iii) the interactions between YRDA and MRA, YRDA_FLF (sector of farming, forest, livestock, and fishery in YRDA) and MRA_FTO (sector of food and tobacco processing in MRA) on VWF are obvious. These results will provide a new insight for balancing urban agglomeration development and water resource utilization in YREB.

Impact assessment of urbanization on vegetation net primary productivity: A case study of the core development area in central plains urban agglomeration, China

Rapid urbanization process has a negative or positive impact on vegetation growth. Net primary productivity (NPP) is an effective indicator to characterize vegetation growth status. Taking the core development area of the Central Plains urban agglomeration as the study area, we estimated the NPP and its change trend in the past four decades using the Carnegie-Ames-Stanford Approach (CASA) model and statistical analysis based on meteorological and multi-source remote sensing data. Meanwhile, combined with the urbanization impact framework, we further analyzed urbanization's direct and indirect impact on NPP. The results showed that the urban area increased by 2688 km² during a high-speed urbanization process from 1983 to 2019. As a result of the intense urbanization process, a continuous NPP decrease (direct impact) can be seen, which aggravated along with the acceleration of the urban expansion, and the mean value of direct impact was 130.84 g C·m^-2·a^-1. Meanwhile, urbanization also had a positive impact on NPP (indirect impact). The indirect impact showed an increasing trend during urbanization with a mean value of 10.91 g C·m^-2·a^-1. The indirect impact was mainly related to temperature in climatic factors. The indirect impact has a seasonal heterogeneity, and high-temperature environments of urban areas are more effective in promoting vegetation growth in autumn and winter than in summer. Among different cities, high-speed development cities have higher indirect impact values than medium's and low's because of better ecological construction. This study is of great significance for understanding the impact of urbanization on vegetation growth in the Central Plains urban agglomeration area, supporting urban greening plans, and building sustainable and resilient urban agglomerations.

Regional characteristics and spatial correlation of haze pollution: Interpretative system analysis in cities of Fenwei Plain in China

Urban agglomeration is an important model for promoting global economic development and has made important contributions to global economic integration. However, as the core area of urbanization and industrialization, urban agglomerations also contribute to air pollutant emissions primarily due to the agglomeration of population and industry. The mutual influence of air pollution between different cities in urban agglomerations has brought significant challenges to global environmental governance. The Fenwei Plain is one of the most severely polluted areas in China. We collected daily average PM_2.5 concentration data of 11 cities in the Fenwei Plain, China in 2019. We then developed an interpretive structural model to statistically analyze the spatial correlation and hierarchical transmission of haze pollution between the 11 cities. The results showed that haze pollution has a strong systematic correlation between the 11 cities, and a regional haze pollution community has formed throughout the region. Haze pollution also exhibits evident transmission and spatial correlations between the cities. The transmission starts from Baoji and ends at Sanmenxia, with mutual interactions between the cities of Xi'an, Xianyang, Weinan, Tongchuan, Jinzhong, Lvliang, Linfen, Yuncheng, and Luoyang. Thus, air pollution prevention and control in the Fenwei Plain should consider the spatial correlation of haze pollution between different cities, especially in autumn and winter, and should rationally be implemented in key urban cluster areas. We recommend building a coordinated governance between cities to improve the overall air quality. Our findings shed a light for coordinated pollution management in urban agglomerations worldwide.

The impact of traffic control measures on the spread of COVID-19 within urban agglomerations based on a modified epidemic model

With the spatial structure of urban agglomerations, well-developed transportation networks and close economic ties can increase the risk of intercity transmission of infectious diseases. To reveal the epidemic transmission mechanism in urban agglomerations and to explore the effectiveness of traffic control measures, this study proposes an Urban-Agglomeration-based Epidemic and Mobility Model (UAEMM) based on the reality of urban transportation networks and population mobility factors. Since the model considers the urban population inflow, along with the active intracity population, it can be used to estimate the composition of urban cases. The model was applied to the Chang-Zhu-Tan urban agglomeration, and the results show that the model can better simulate the transmission process of the urban agglomeration for a certain scale of epidemic. The number of cases within the urban agglomeration is higher than the number of cases imported into the urban agglomeration from external cities. The composition of cases in the core cities of the urban agglomeration changes with the adjustment of prevention and control measures. In contrast, the number of cases imported into the secondary cities is consistently greater than the number of cases transmitted within the cities. A traffic control measures discount factor is introduced to simulate the development of the epidemic in the urban agglomeration under the traffic control measures of the first-level response to major public health emergency, traffic blockades in infected areas, and public transportation shutdowns. If none of those traffic control measures had been taken after the outbreak of COVID-19, the number of cases in the urban agglomeration would theoretically have increased to 3879, which is 11.61 times the actual number of cases that occurred. If only one traffic control measure had been used alone, each of the three measures would have reduced the number of cases in the urban agglomeration to 30.19 %-57.44 % of the theoretical values of infection cases, with the best blocking effect coming from the first-level response to major public health emergency. Traffic control measures have a significant effect in interrupting the spread of COVID-19 in urban agglomerations. The methodology and main findings presented in this paper are of general interest and can also be used in studies in other countries for similar purposes to help understand the spread of COVID-19 in urban agglomerations.

Analysis of influencing factors and prediction of carbon emissions of typical urban agglomerations in China: a case study of Beijing-Tianjin-Hebei region

Achieving the "double carbon" goal is a major task and challenge facing China. The emission reduction actions in typical urban agglomerations are of great significance. Based on the consideration of the impact of regional coordinated development, this study analyzed influencing factors and conducted prediction of carbon emissions from terminal energy consumption in the Beijing-Tianjin-Hebei (BTH) region. Firstly, the factors affecting carbon emissions were screened through the STIRPAT model. Then, the paper designs different scenarios and finally uses the genetic algorithm extreme learning machine (GA-ELM) algorithm to predict the carbon emissions of the BTH region, with and without considering the impact of the coordinated development strategy. The research shows that the increase in energy intensity and the improvement of energy consumption structure have the largest promotion effect on carbon emission reduction. At the same time, the significant role of the coordinated development strategy in promoting regional carbon emission reduction was verified. Therefore, the BTH region should adhere to the path of coordinated development, innovate low-carbon technology, and deepen the concept of green consumption to promote the realization of regional carbon emission reduction goals.

"Dark under the lamp": ecological equity of urban agglomeration from the perspective of natural capital in China

Although equity is an important aspect of sustainable development, equity research has mainly focused on income and economics while paying insufficient attention to ecological equity. Therefore, aiming to improve our understanding of equity and promote environmental protection, this study introduced natural capital to measure regional ecological equity and analyze its driving factors. Based on ecological footprint (EF) and ecosystem service value (ESV), we constructed evaluation indexes and drew an "ecological Lorentz curve bundle" to analyze ecological equity in the Jing-Jin-Ji urban agglomeration (JUA) from 2009 to 2020. The results showed that economic development in JUA resulted in the severe depletion of natural capital, especially biological and energy resources, and the supply and demand of natural capital was in a low-level equilibrium state. Based on JUA's population base, natural capital utilization in the region had exceeded ecological equity, and the Gini coefficient of EF based on population was close to the international warning value of 0.4. Although economic development in JUA has promoted economic equity, it has also led to environmental inequity. Large cities such as Beijing and Tianjin, as well as industrial cities such as Tangshan and Handan, have had the greatest effects on ecological equity. Moreover, the excessive consumption of natural capital stock and energy-dependent industrial structures threaten ecological equity.

Does urban agglomeration aggravate regional haze pollution? Empirical evidence from urban agglomerations in the middle reaches of the Yangtze River in China

Under China's "new normal," urban agglomeration (UA) has become a new direction for urbanization and regional coordinated development. The urban agglomeration in the middle reaches of the Yangtze River (MRYR-UA) is one of the locations where the haze concentration surpasses the Chinese standard. This study analyzes panel data from 284 Chinese prefecture-level cities from 2005 to 2018 to undertake an empirical investigation based on the MRYR-UA as a quasi-natural experiment for its development planning strategy. The results show that the establishment of the MRYR-UA greatly reduced regional haze pollution. In this paper, social, economic, and natural factors are considered: industrial structure, human capital, and population density can reduce haze pollution, while openness exacerbates urban pollution, confirming the pollution haven hypothesis. The increase in wind speed and rainfall can reduce the concentration of haze. The mediating effect test shows that economic, technological, and structural effects can alleviate haze pollution in the MRYR-UA. The heterogeneity analysis reveals that the number of enterprises decreased in core cities but significantly increased in edge cities, indicating that core cities transferred industrial enterprises to edge cities under the pressure of environmental regulation, resulting in the internal transfer of pollution.

Sustainable development of urban agglomeration based on material metabolism: a case study on Fujian Delta, China

As highly concentrated urbanized areas, urban agglomerations bear increasing resource depletion and environmental pressures, which threaten the regional sustainable development. Resource and environmental problems arising from the process of urbanization can be attributed to the dislocation or maladjustment of material metabolism in time or space. Conducting research on material metabolism at the level of urban agglomerations is helpful in finding the root causes of environmental problems to provide support for the reduction of regional resource consumption and pollution emissions. The material metabolism characteristics of the urban agglomeration and internal cities of the Fujian Delta Urban Agglomeration (FDUA) in China are evaluated using the material flow analysis. The following results are observed. (1) The economic development of the FDUA is still at risk of resource consumption, and a large proportion of hidden flow (HF > 80%) drags down the overall metabolic efficiency and sustainable development. (2) The discharge of various pollutants in the FDUA generally shows a downward trend. Improving metabolic efficiency, delayed MCI growth, and improved overall regional environmental quality are observed. (3) Cities that have relatively scarce land resources but are economically developed, such as Xiamen, still bear a relatively heavy ecological burden (ECdmc > 1). (4) Regional collaboration is conducive to the sustainable development of multiple regions. On the one hand, the results of this study provide decision-making basis for the sustainable development of the national ecological civilization demonstration area. On the other hand, this work guides the establishment of a comprehensive industrial linkage and cooperation mechanism for the same type of small- and medium-sized urban agglomerations.

Microplastics in rivers along an urban-rural gradient in an urban agglomeration: Correlation with land use, potential sources and pathways

Microplastics are ubiquitous and affect all environments, including rivers. In recent years the number of studies about microplastics in rivers has strongly increased. But still many questions exist regarding sources, pathways, and the role of land use patterns. In this study the relationship between microplastics abundance and anthropogenic factors (population density, urbanization, land use types), as well as the potential role of storm sewers as pathways in tributaries of the Wu River in Taichung, central Taiwan, were studied. Two river catchments of the Dali River were studied in greater detail to investigate the influence of land use on microplastics abundance along an urban-rural gradient, and to observe the change of microplastics abundance in the transition from rural to urban areas. Samples were taken from 41 different locations in urban and rural areas using a manta net with a mesh size of 0.3 mm. Results show abundances ranging from 0 pcs/m³ in unpopulated rural areas up to 230 pcs/m³ in densely populated urban centers, and are positively correlated with population density. Remarkably, a sharp increase in microplastics abundance was observed at the transition from rural to urban areas, which coincides with the appearance of storm sewers. Land use analysis revealed that microplastics abundance positively correlates with the size of industrial, residential and traffic areas in the catchment areas, and negatively correlates with the size of forest areas. Source areas for microplastics in the studied rivers are likely residential and commercial areas. Furthermore, the results of this study show that correlations between microplastics abundances and population density or land use patterns along urban-rural gradients are not trivial. Strength of correlations can depend on local factors or how well urban-rural gradients are developed. Absence of correlations need to be considered carefully, as existing correlations might be masked by the above-mentioned factors.

Environmental collaborative governance of urban agglomeration in China: influencing factors and drivers

This study attempts to examine how urban agglomerations establish sustainable environmental collaborative governance. To achieve this goal, the qualitative comparative analysis method is used to explore the conditions and models for urban agglomerations to establish environmental collaborative governance, with 12 urban agglomerations approved by the Chinese authorities as examples. Based on the collaborative governance framework, this paper proposes six starting conditions that affect the establishment of urban agglomeration collaboration: vertical intervention, horizontal cooperation, leadership attention, governance capacity, initial pollution, and economic governance. The interaction of these conditions was tested in the practice of environmental cooperation in urban agglomerations. The results show that horizontal cooperation, leadership attention, and economic governance are necessary conditions for the establishment of urban agglomeration cooperation. The authority-driven mode, capability-driven mode, and pressure-driven mode can promote cooperation. Vertical intervention, governance capacity, and initial pollution constitute the external and internal driving forces of urban agglomeration cooperation. These findings supplement the literature on urban agglomeration collaboration and provide policy makers with insight into sustainable urban agglomeration collaborative environmental governance.

Occurrence, spatial distribution and ecological risks of antibiotics in soil in urban agglomeration

Antibiotics in soil environment are regarded as emerging pollutants and have introduced increasing risks to soil ecosystem and human health in rapid urbanization areas. Identifying the occurrence and spatial variability of antibiotics in soils is an urgent issue in sustaining soil security. In this study, antibiotics in soils were investigated and analyzed in Beijing-Tianjin-Hebei urban agglomeration. The occurrence, spatial distribution, and related affecting factors of antibiotics in soils were identified and ecological risks of antibiotics in soil environment were assessed. Results showed that (1) The mean concentration of soil antibiotics in Beijing-Tianjin-Hebei urban agglomeration was 21.79 µg/kg. Land use substantially affected the occurrence and concentration of antibiotics in soils. Concentrations of antibiotics in cropland and orchard soils were 2-3 times higher than the other land use types. (2) The concentrations of antibiotics in soils in Beijing-Tianjin-Hebei urban agglomeration presented a spatial pattern of high values in southeast, and low values in northwest. Spatial variability of antibiotics in soils was closely related to the application of organic fertilizer and wastewater irrigation as well as topographical features. Furthermore, soil properties and land management policy had substantial influences on soil antibiotics, and soil heavy metals may aggravate the accumulation of antibiotics in soils. (3) Ecological risks assessment of antibiotics in soils demonstrated that erythromycin (ERY), sulfamethoxazole (SMX), and doxycycline (DOX) may introduce high risks to soil ecosystem health, and more attention should be paid to the areas with intensive human activities that had potential high risk to soil ecosystem health. This study suggests that scientific land and soil management should be considered to prevent soil antibiotic pollution and sustain soil security in urban agglomeration.

Causality and dynamic spillover effects of megacities on regional industrial pollution reduction

Regional economic power and local environmental policies have a substantial impact on pollution reduction in urban agglomerations (UAs); however, whether megacities in UAs exert spillover effects of pollution reduction on surrounding cities remains unknown. This study presents a causal analytic framework to evaluate the spillover effects of megacities on regional industrial pollution reduction in three major UAs in China between 2005 and 2016. The interaction between industrial pollution reduction and infrastructure investment indicators was also examined. Results indicated a good fit for spatial spillover of sulfur dioxide reduction (SR) in the Pearl River Delta (PRD) and Yangtze River Delta (YRD) but not in the Beijing-Hebei-Tianjin cluster (JJJ). Spatial spillover of dust reduction (DR) was evident in the PRD and JJJ but not the YRD. Spatial analysis showed that infrastructure investment indicators, at megacity and UA levels, had short-term spillover effects on surrounding cities for DR but not SR. However, spatial spillover effects, at both the city and UA levels, were substantial over the long term. In addition, the results of the spatial-time lag analysis suggest a linear relationship between pollution control-related infrastructure investment indicators and long-term pollution reduction. This study provides new information regarding the spatial spillover effects of megacities on regional industrial pollution reduction in UAs.

Study on the impact of digital economy development on carbon emission intensity of urban agglomerations and its mechanism

Using fixed, mediating, and moderating effect models, we explored the impact of the digital economy on carbon emission intensity and its mechanisms based on panel data of 100 cities in 6 Chinese urban agglomerations from 2011 to 2019. The results show that (1) the digital economy development in the urban agglomerations can significantly reduce carbon emission intensity. (2) The digital economy in the urban agglomerations can indirectly reduce carbon emission intensity through the channels of green technology innovation and the information communications technology (ICT) industry. Furthermore, a higher degree of marketization in the urban agglomerations leads to a more pronounced effect of the digital economy on reducing carbon emission intensity. (3) The impact of the digital economy on the carbon emission intensity in the urban agglomerations is regionally heterogeneous. When the carbon emission intensity is at different quantiles, the effects of the digital economy on reducing carbon emission intensity are different. (4) The digital economy development has different impacts on carbon emission intensity when different urban agglomerations are approved. The digital economy development in the urban agglomerations can better reduce carbon emission intensity than that in other cities. Currently, China is in a significant period of rapid digital economy development and energy conservation and emission reduction. We revealed some new features of the digital economy and carbon emission intensity in urban agglomerations, providing a reference for promoting the construction of urban agglomerations, developing the digital economy, and reducing carbon emission intensity.

A novel EKC perspective: do agricultural production, energy transition, and urban agglomeration achieve ecological sustainability?

We aim to analyze the existence of a novel agricultural production-augmented environmental Kuznets curve (EKC-AP) theory for energy transition, urban agglomeration, and financial depth. To conduct this research, we use a global panel of selected 54 countries belonging to low, medium, and high levels of economic development from 1971 to 2017. Since our data are distributed into three development levels, it is highly likely to face cross-sectional dependence across the countries within and between the development levels, which may provide biased empirical results. To outpace such possibility, we employ advanced econometric strategies, which are robust to cross-sectional dependence and slope heterogeneity issues. We found that agricultural production, energy transition, urban agglomeration, financial depth, and ecological degradation experience a long-term cointegrating equilibrium association. We also confirm that exists an EKC-AP linkage of agricultural production with ecological degradation in highly developed economies, while those at the low and medium levels of development reveal a positive exponential and monotonic impact, respectively, of agricultural production on ecological degradation. The energy transition is found to promote ecological sustainability in developed countries through technique impact, while it deteriorates the ecological quality in countries at the medium development level. Moreover, urban agglomeration adversely impacts the ecological quality in the economies at low and medium development levels, whereas it improves the ecological sustainability in developed economies. Besides, financial depth proves harmful to ecological sustainability, with less subtle effects in developed economies. Based on our findings, for countries at low and medium levels of development, we propose advancing farming techniques using ecologically friendly technologies, promoting green energy transition, expanding the share of the services sector, and providing green financial systems to support green investment projects to achieve the Sustainable Development agenda of the United Nations.

Increased diurnal difference of NO2 concentrations and its impact on recent ozone pollution in eastern China in summer

Nitrogen dioxide (NO₂) is a key tropospheric O₃ precursor. Since 2013, efforts to decrease air pollution in China have driven substantial declines in annual NO₂ concentrations, whereas ozone (O₃) concentrations have increased. Based on nationwide NO₂ observations and a regional air quality model (WRF-CMAQ), we analyzed trends in the diurnal difference (DD, the difference between nighttime and daytime concentrations) of NO₂ concentrations across eastern China and in five national urban agglomerations (UAs) from 2014 to 2021, and explored the factors underlying such changes and the potential impacts on O₃ pollution. We found that the observed DD of NO₂ has increased in most cities and UAs, and that this trend can be primarily attributed to changes in anthropogenic emissions, based on comparison with DDs simulated with fixed anthropogenic emissions, which generally showed much weaker trends and little interannual variation. A sensitivity analysis using the WRF-CMAQ model was conducted to investigate the impact of a modified diurnal cycle of nitrogen oxides (NO_x) emissions on O₃ concentrations. The result revealed that enhancing the DD of NO₂ would increase O₃ concentrations in the morning and the daily maximum 8-h O₃ concentrations in the cities with high NO_x concentrations, as well as downwind areas of cities, indicating that greater DDs in NO₂ is one of the reasons that have led to the enhanced China's O₃ pollution in recent years.

Evolution and improvement options of ecological environmental quality in the world's largest emerging urban green heart as revealed by a new assessment framework

Large ecological green spaces in cities are often designated as Urban Green Hearts (GHs) to support the ecological and recreational needs of urbanites. While GHs protection and sustainable development have been a high priority for urban planning and management, ecological environment quality (EEQ) of GHs has rarely been monitored and assessed. Here, we proposed a comprehensive assessment framework for EEQ based on entropy weights and rank-sum ratios methods, and applied the framework to the world's largest GH, Changsha-Zhuzhou-Xiangtan urban agglomeration Green Heart (CZT-GH), and its 5 km and 10 km buffer zones to examine the spatial-temporal dynamics of its EEQ from 2000 to 2019. Compared with the buffer zones, the EEQ in the CZT-GH was the best, with an annual average of 44.92 % of the area being High-grades EEQ. The restoration trend of EEQ was most conspicuous in only 8.4 % of CZT-GH, a small fraction compared with 25.1 % and 66.5 % of the CZT-GH showing deterioration trend and no change, respectively. Five factors were identified that calls for management attention: land use and cover change, spatial heterogeneity in vegetation restoration, temporal fluctuation in air quality improvement, comprehensive EEQ assessment and restoration, and capacity to cope with ecological risks. The approach, issues identified, and management measures proposed in this study should be applicable to GHs in general. The generic EEQ assessment framework and approaches developed in this study are generic and objective and therefore can be easily adapted to other regions; the procedures used to quantify the spatial and temporal changes of EEQ and identify underlying management issues provide essential information for formulating adaptive management measures of EEQ in general. SYNOPSIS: Taking the largest urban Green Heart as a case study, we established and applied a new general ecological environment quality (EEQ) evaluation system to monitor EEQ changes, identify issues, and propose management options.

An improved hybrid model on source-risk of polycyclic aromatic hydrocarbon in soils of the Yangtze River Delta urban agglomeration

The source, exposure and risks of polycyclic aromatic hydrocarbons (PAHs) in soil environments are of great importance to evaluate soil quality. However, understanding the risks of specific sources of PAHs in soils remains poorly understood. In this study, we determined the source, exposure and risks of PAHs in the Yangtze River Delta urban agglomeration. The source analysis receptor model combined with land use types significantly increased the identification of pollution sources and improved the prediction accuracy of PAH concentrations. There is a strong correlation between the measured and predicted values of high ring PAH. The correlations of BbF, InP and Pyr are 0.947, 0.896 and 0.906 respectively, which is significantly higher than the unmodified model. By combining the ecological risk assessment and health risk assessment models of PAHs, we established an improved mixed source-risk model. The PAHs in urban soils had the highest ecological risk and health risk, with risk probabilities of 56.3 % and 28.2 %, respectively. The average contamination severity index values of PAHs caused by oil combustion sources, coal combustion sources, coking furnace sources, and fuel (biomass, petroleum, and diesel) combustion sources were 0.13, 0.10, 0.16 and 0.17, respectively. The average noncarcinogenic risks of PAHs from oil combustion sources, coal combustion sources, coking furnace sources and biomass, petroleum volatilization and diesel combustion sources to children were 0.12, 0.11, 0.08 and 0.13, respectively. Approximately half of the PAH pollution risk in forestland and grassland soil were associated with the combustion of petroleum fossil fuels. This study quantitatively analyzed the contribution of different PAHs pollution sources in different land types of soils, further calculated the risks of each pollution source to the ecological environment and human health, and proposed corresponding treatment measures, which provided scientific and systematic methods and technologies for soil pollution management in other regions of the world.

Further mitigating carbon footprint pressure in urban agglomeration by enhancing the spatial clustering

The increasing environmental pressure of anthropogenic CO₂ emissions is impeding the sustainability of urban agglomerations (UAs). Recent research has shown that the spatial clustering of UA elements reduces CO₂ emissions but underestimates its impact on vegetation carbon sequestration. Using an extended IPAT equation analysis framework and the Logarithmic Mean Divisia Index decomposition approach, this study revealed the positive effects of the economy and population spatial clustering on carbon footprint pressure (CFP) mitigation. Specifically, improving economic spatial clustering mitigated the rise in UA's CFP caused by affluence and population growth. Furthermore, population clustering in core cities effectively mitigated CFP in neighboring cities. Additionally, we found that the efficiency improvement, i.e., the decrease in the ratio of carbon emissions and gross domestic product, should be the dominant driver of CFP mitigation, followed by improved vegetation carbon sequestration. However, these drivers have limited future potential. We believe that by improving UA's spatial clustering of the economy and population, future urban environmental pressures and climate risks will be mitigated.

Is China approaching the inflection point of the ecological Kuznets curve? Analysis based on ecosystem service value at the county level

Accounting for the ecosystem service values (ESVs) and discussing the relationship between the ESVs and economic development can help achieve sustainable ecological development. Therefore, this paper evaluates the county-level ESVs of various land types in China, and depicts the distribution of ESVs in various urban agglomerations. In addition, the nonlinear relationship between ESVs and economic development is revealed. The main findings are as follows: (1) From 2000 to 2018, the ESVs in China decreased, and the decline rate of ESVs in urban agglomerations is much higher than that of China as a whole. (2) The decline rate of ESVs in core cities is much higher than in urban agglomerations, and the decline rate of ESVs is higher in areas close to core cities and lower in areas far from core cities. (3) The ecological Kuznets curve of China has a positive "U" shape, and the ecological Kuznets curve of urban agglomerations has an "N" shape; the ecological Kuznets curve of core cities has a positive "U" shape, while the ESVs of other cities decreases monotonically with the increase of the economic level.

Tracking long-term population exposure risks to PM2.5 and ozone in urban agglomerations of China 2015-2021

China has experienced severe air pollution in the past decade, especially PM2.5 and emerging ozone pollution recently. In this study, we comprehensively analyzed long-term population exposure risks to PM2.5 and ozone in urban agglomerations of China during 2015-2021 regarding two-stage clean-air actions based on the Ministry of Ecology and the Environment (MEE) air monitoring network. Overall, the ratio of the population living in the regions exceeding the Chinese National Ambient Air Quality Standard (35 μg/m3) decreases by 29.9 % for PM2.5 from 2015 to 2021, driven by high proportions in the Middle Plain (MP, 42.3 %) and Lan-Xi (35.0 %) regions. However, this ratio almost remains unchanged for ozone and even increases by 1.5 % in the MP region. As expected, the improved air quality leads to 234.7 × 103 avoided premature mortality (ΔMort), mainly ascribed to the reduction in PM2.5 concentration. COVID-19 pandemic may influence the annual variation of PM2.5-related ΔMort as it affects the shape of the population exposure curve to become much steeper. Although all eleven urban agglomerations share stroke (43.6 %) and ischaemic heart disease (IHD, 30.1 %) as the two largest contributors to total ΔMort, cause-specific ΔMort is highly regional heterogeneous, in which ozone-related ΔMort is significantly higher (21 %) in the Tibet region than other urban agglomeration. Despite ozone-related ΔMort being one order of magnitude lower than PM2.5-related ΔMort from 2015 to 2021, ozone-related ΔMort is predicted to increase in major urban agglomerations initially along with a continuous decline for PM2.5-related ΔMort from 2020 to 2060, highlighting the importance of ozone control. Coordinated controls of PM2.5 and O3 are warranted for reducing health burdens in China during achieving carbon neutrality.

Structure characteristics and influencing factors of China's carbon emission spatial correlation network: A study based on the dimension of urban agglomerations

China faces enormous pressure to reduce carbon emissions. Since the agglomeration and driving effect of urban agglomerations have continued to increase, relying on the network relationship within urban agglomerations to coordinate emission reduction becomes an effective way. This paper combines the modified Gravity model and Social Network Analysis method to measure the structure characteristics of carbon emission spatial correlation network of the seven urban agglomerations as a whole and each urban agglomeration in China, analyzes the interaction mechanism between cities and between urban agglomerations, and finally explores the influencing factors of carbon emission spatial correlation through the QAP analysis method. The results are as follows: (1) As for the overall network, overall scale was increasing, but the hierarchical structure had a certain firmness. YRD and PRD urban agglomerations were at the center of the network and received the spillover relationship of MRYR, CC, CP, and HC urban agglomerations. (2) As for the networks of urban agglomerations, the allocation of low-carbon resource elements still needed to be optimized, especially BTH urban agglomeration. Beijing, Shanghai, Nanjing, Wuxi, etc. were at the center of the network. The influencing factors and degree of carbon emission spatial correlation in each urban agglomeration were different.

Quantifying microplastic stocks and flows in the urban agglomeration based on the mass balance model and source-pathway-receptor framework: Revealing the role of pollution sources, weather patterns, and environmental management practices

Microplastics are widely present in global ecosystems, threatening both marine and freshwater species. Given this problem, it is vital to research where land-based microplastics originate and how they are transmitted to receiving waters in urban agglomerations. Research results should inform systemic mitigation efforts to prevent future contamination. This study established the multi-directional transmission network of a microplastic mass balance system using a source-pathway-receptor framework, and involving annual source stocks and pathway flows with considerable variations under dry and wet weather patterns. Details of a baseline scenario quantifying the occurrence and spread of microplastics in an urban agglomeration were also determined in the context of current environmental management practices. We demonstrated that the total stock of the six major pollution sources amounted to 5317.7 ± 2175.3 and 3320.1 ± 953.6 tons/a in dry and wet weather, respectively; and 2347.8 ± 766.9 and 1991.8 ± 701.8 tons/a flows directly entered the sewer system and receiving water in Shanghai, China, respectively. Prominent microplastic stocks were found in atmospheric fallout, industrial wastewater, and domestic sewage. These stocks were much higher compared to crop farming wastewater, aquacultural wastewater, and livestock and poultry breeding wastewater. Total microplastic flows entering receiving water reached 3207.4 ± 1071.6 tons/a; the largest contributions were from wet weather overflow (23.7%), direct atmospheric fallout (21.7%), wastewater treatment plant effluent (14.2%), industrial wastewater (14.1%), and surface runoff (10.4%). Weather patterns led to divergent microplastic transmission pathways and mass flows, revealing a lagging timeline mode and illustrating the basic spatiotemporal features of microplastic contamination in urban agglomerations. Terminal disposal practices retained about two-fifths of the microplastic flows that would have otherwise been transmitted into receiving water. Of these, land surface sweep contributed half of the retained flow. Improvements in WWTP removal efficiency, storm sewage interception rate, industrial wastewater collection rate, and sewer sediment dredge rate could further enhance the systemic benefits.

Flows and connections of metabolic nodes in Beijing-Tianjin-Hebei Region and its cities: A study at two scales

The metabolic processes of cities and their embedded regions have received great attention, but it is still unclear how the metabolic processes change at the scale from cities to urban agglomerations. In view of the lack of multi-scale research in the field of urban metabolism, this study took Beijing-Tianjin-Hebei region, one of the urban agglomerations with largest economic scales in China, as a case to construct metabolic network models at two scales of city and urban agglomeration. The material transfers between nodes were calculated, and the connection degree index was put forward in the ecological network analysis to quantify the influence of a single node on the network when multi-level transfers were considered. On this basis, the similarities and differences of metabolic nodes at the two scales were analyzed. The results showed that nearly 97% of the volume of material transfers in the urban agglomeration was concentrated within the cities, among which the transfer volumes of Tangshan, Handan, and Shijiazhuang were more than 600 Mt. Manufacturing and environment were the major contributors to material transfers. The connection degrees of nodes had both commonness and differences at the two scales. In general, the connection degrees at the urban scale were relatively homogeneous, while their difference was large at the urban agglomeration scale. The connection degrees of nodes in Langfang were prominent at the urban agglomeration scale. The connection degrees of environment and manufacturing ranked top 3 at both scales. Meanwhile, the connection degree of energy conversion at the urban scale was relatively high, while its influence was replaced by mining sector at the urban agglomeration scale. The analysis of material metabolic nodes in Beijing-Tianjin-Hebei region can provide theoretical supports to position the key points in the process of material utilization in the cities or the urban agglomeration, and help to identify the breakthrough points for subsequent regulatory.

Unraveling the dynamics, heterogeneity, determinants of eco-efficiency in Beijing-Tianjin-Hebei urban agglomeration, China

Eco-efficiency has been considered a valuable gauge for evaluating how efficient economic activities are in regard to resource inputs and eco-environmental pressures. Even though Ecosystem services (ESs) are inseparable from sustainable eco-environment, a paucity of literature has considered ESs in eco-efficiency research lines. Therefore, this study aims to construct a novel eco-efficiency evaluation framework by integrating ESs as natural capital input and measure it utilizing the Epsilon-based measure model for the county-level cities in Beijing-Tianjin-Hebei urban agglomeration (BTHUA) during the period 2005-2015. The spatial econometric technique is further performed to acquire quantitative evidence about whether ESs and other determinants impact eco-efficiency. The results revealed that eco-efficiency increased continuously in the whole BTHUA and BTHUA's optimized development functional areas, whereas eco-efficiency of BTHUA's sub-regions showed a significant temporal diversity. The average eco-efficiency values of cities in key development functional areas and restricted development functional areas showed the V-shaped trend (declining before 2010 and then rising). Interestingly, this study found that ESV economic loss may result in eco-efficiency decline for cities located in key development functional areas. From the spatial heterogeneity perspective, the city with high EE is mainly located in eastern BTHUA, whereas cities in the northern plateau areas, southwestern, and western BTHUA have relatively low EE. Furthermore, there existed a significant spatial autocorrelation and a spatial agglomeration heterogeneity, which suggests that the low-low correlation regions gradually being the most dominant spatial pattern. The results of spatial econometric model verified that water yield has the strongest positive effect on EE while soil erosion will lead to declining EE. This paper potentially provides new insights for future policy design of urban agglomeration sustainable deployment.

Integrating water-related disaster and environment risks for evaluating spatial-temporal dynamics of water security in urban agglomeration

Water security is a compound concept coupling multi-dimensional perspectives, such as resource utilization, environmental protection, and disaster prevention. With this concern, this study focuses on the spatial-temporal dynamics of water security with considering water disaster risk index (WDRI), water environment risk index (WERI), and water supply-demand. WERI centers on risk source's hazard, control effectiveness, and risk receptor's vulnerability. Indices related to hazard, exposure, and vulnerability are used for evaluating WDRI. A multi-objective fuzzy membership function is presented for determining the indices' weight, and the distribution pattern of water security is illustrated based on cluster analysis. A real-world case study of Beijing-Tianjin-Hebei urban agglomeration (BTHUA) is given for verifying availability of the evaluation framework. Results indicate the general water security in BTHUA with a critical safe state yet a downward trend. Opposite change characteristics of water security exist between its southern and northern cities. WDRI and WERI show the trends of increasing (with a growth rate of 0.48%) and decline (with an average decrement rate of 0.56%), respectively. Beijing has high-value WDRI and WERI, and the order of WDRI and WERI is presented as follows: Beijing (0.67) > Tianjin (0.54) > Hebei (0.33) and Beijing (0.69) > Tianjin (0.58) > Hebei (0.16), respectively. Cluster analysis reveals a poor match relation between water security and regional socio-economic development. Areas with high-level economic development (e.g., Beijing and Tianjin) have poor environmental performances, with WDRI and WERI of 0.54 ~ 0.68 and 0.57 ~ 0.70, respectively. Additionally, water resources overload index of BTHUA is 8.513, which is higher than Chengdu-Chongqing urban agglomeration (1.431), Triangle of Central China (0.228), and Yangtze River Delta urban agglomeration (0.742). Findings can provide a theoretical reference for promoting sustainable utilization of water resources in BTHUA and the other areas with prominent water problems.

Spatiotemporal heterogeneity of PM2.5 and its driving difference comparison associated with urbanization in China's multiple urban agglomerations

The development of urban agglomeration further deteriorates the air pollution status arising from urbanization. However, disparities in the urbanization process across different urban agglomerations may shape unique regional air pollution characters, and further complicate its driving mechanism. In this study, 11 urban agglomerations with different urbanization levels in China thus were chosen as the case study areas, to explore the spatiotemporal heterogeneity of PM2.5 and its potential driving difference related to the urbanization process from a multi-urban agglomeration perspective. The ground-monitored PM2.5 data and socioeconomic panel data (2015-2018) were processed using multiple statistical analysis methods, and the main findings of this study can be generated as followed: (1) significant spatial heterogeneity characteristics of PM2.5 pollution were recognized across the study area. And even though obvious improvement in the air quality during the study period, PM2.5 concentration remains at a high level for most of the urban agglomerations. (2) Urbanization process has a substantial contribution to regional PM2.5 pollution, and significant differences of the urbanization factors on PM2.5 concentration across the urban agglomerations assigned with various urbanization levels were emphasized. The significance of this study is to provide insight into the relationship of the urbanization process on PM2.5 pollution in different urban agglomerations and to offer a scientific basis for regional cooperation for air pollution regulation among multiple urban agglomerations.

Testing the impact of first-mover advantage on household energy-related carbon emissions: an exploratory study from six urban agglomerations in China

The household sector has become the second-largest source of energy consumption and CO₂ emissions in China. It is important to understand the trends and changing mechanisms of household energy-related CO₂ emissions (HECEs) in different social stages for mitigating the impact of climate change. However, the existing trends in HECEs and whether they are congruent with the expectation that HECEs in later developed areas are lower than those in priority areas under the same economic level are unclear. Here, we compared the per capita HECEs (PHECEs) of urban agglomerations under the same economic standards and analyzed the causes of the comparative results. We find that (1) HECEs increased rapidly from 3.65 × 10⁸ t to 12.42 × 10⁸ t during 1995-2017, with an average annual growth rate of 14.19%; (2) urban agglomerations that developed earlier do not have higher PHECEs. The PHECEs of urban agglomerations with moderate and later development do not decrease under increased social, technological, and cognitive conditions; (3) carbon intensity (CI), energy intensity (EI), and per capita regional gross domestic product (PCG) have a positive impact on PHECEs, and the potential impact of EI on PHECEs reduction is greater; (4) the effects of CI, EI, and PCG on PHECEs in different urban agglomerations are various. However, these effects are similar within urban agglomerations. Our study provides a reference for reducing CO₂ emissions in the household sector and for the green development of urban agglomerations and emphasizes that the growth of HECE at a reasonable level is necessary when technology does not meet sufficient constraints.

Inequality of pollutant discharge in an urban agglomeration and nonurban agglomeration-evidence from a new Theil-DEA model

Under the goal of carbon neutralization, the prevention and control of pollution emissions are very meaningful. Different levels of urban economic development correspond to different pollutant discharges. An assessment of pollution inequality among cities can quantitatively explain regional differences in pollution treatment. This paper proposes a new paradigm to measure pollution inequality within the Yangtze River Delta Economic Zone of China and aims to compare the inequality of pollutant discharge of urban agglomerations and nonurban agglomerations from 2001 to 2017. The findings reveal that the overall pollutant discharge shows a slight upward trend and gradually changes from a "two polarization" distribution in 2001 to a "centralized" distribution in 2017. However, the inequality of pollutant discharge declines during this period, whereby the pattern of the within-group inequality component is similar to the overall inequality, while the inequality of nonurban agglomeration pollution is more severe than that of urban agglomeration pollution. Further decomposition indicates that the difference in pollution intensity is the most critical factor leading to the inequality of pollution discharge, and reducing the gap in energy intensity is the most rapid way to reduce the inequality of pollution discharge. To measure the total driving force that leads to their inequality and to predict the degree of inequality of pollutant discharge, we use a new Theil-DEA model. Based on the empirical results, we anticipate that the imbalance of pollutant discharge will either temporarily maintain the status quo or worsen. Finally, we briefly discuss policy recommendations and special issues.

Quantifying the human disturbance intensity of ecosystems and its natural and socioeconomic driving factors in urban agglomeration in South China

The impact of human activities on terrestrial ecosystems is becoming more intense than ever in history. Human disturbance analyses play important roles in appropriately managing the human-environment relationship. In this study, a human disturbance index (HDI) that uses land use and land cover data from 1980, 2000, 2010, and 2018 is proposed to assess the human disturbance of ecosystems in the Guangdong-Hong Kong-Macao Greater Bay Area. The HDI is first calculated by classifying the human disturbance intensity into seven levels and 13 categories from weak to strong in ecosystems. Then the driving factors of the HDI spatial pattern change are explored using a geographically weighted regression (GWR) model. The results showed that the spatial pattern of the HDI was high in the middle and low in the surrounding areas. The intensity of human disturbance increased, and the medium and high disturbance areas expanded during 1980-2018, especially in Guangzhou, Foshan, Shenzhen, and Dongguan. Human disturbance displayed an obvious spatial heterogeneity. The GWR model had a better explanation effect of the analysis of the HDI change drivers. The driving effect of the socioeconomic conditions was significantly stronger than that of the natural environmental. This study assists in understanding the distribution and change characteristics of the ecological environment in areas with strong human activities and provides a reference for related studies.

Spatiotemporal patterns and driving forces of remotely sensed urban agglomeration heat islands in South China

Rapid urbanization and increasing population have widely caused the urban heat island effect. Due to the decreasing distance between cities, there is an urgent need to reevaluate regional heat island intensity (RHII) in an urban agglomeration scale by considering all cities together instead of from conventional single city perspective. Using cropland land surface temperature as the reference temperature, we assessed the diurnal and seasonal RHII variations in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) urban agglomeration in South China. The boosted regression trees (BRT) method was then used to analyze the relative influence and marginal effect of possible drivers to disentangle their underlying driving mechanisms. Results showed that the daytime RHII spatial patterns averaged over the period 2003-2017 illustrated higher intensity and greater heterogeneity than their nighttime counterparts, especially for the stronger RHII in the central GBA around the estuary area. Seasonal dynamics of daytime RHII displayed a generally descending trend from summer to winter, but the opposite for night. BRT analyses indicated that at both annual and seasonal scales, vegetation fraction and background temperature had a dominant influence on RHII in daytime and nighttime, respectively. RHII variations were also considerably attributed to other drivers for different seasons. For daytime RHII, the other influential drivers included anthropogenic heat emissions and precipitation in summer, anthropogenic heat emissions and terrain in the transition season, and temperature and albedo in winter. For nighttime RHII, anthropogenic heat emissions for all seasons, vegetation activities for summer and the transition season, and precipitation for winter also had important contributions. The marginal effects detected the different nonlinear responses of diurnal and seasonal RHII to potential drivers, suggesting contrasting driving mechanisms. Results of this study highlight more targeted and informed strategies for RHII mitigation in the GBA and provide helpful insights into RHI evaluation in other urban agglomerations.