Spatial-temporal pattern of ecosystem services and sustainable development in representative mountainous cities: A case study of Chengdu-Chongqing Urban Agglomeration.

The Sustainable Development Goals (SDGs) are essential measure for preserving the balance between human well-being and natural ecosystems. The benefit of preserving ecosystems health play a crucial role in promoting the SDGs by providing stable ecosystem services (ESs). However, the ecological health of mountainous cities is vulnerable, with relative low ecological resilience. To investigate the conflict between ecosystems and sustainable development, this study takes the Chengdu-Chongqing Urban Agglomeration as the study area. The major tasks and results in this study include: (1) using the entropy weighting method and the InVEST model, we combined remote sensing, geographic, and statistical data to quantify three types of SDGs (economic, social, environmental) and four ESs (water yield, soil conservation, habitat quality, carbon storage), and establish a localized sustainable development assessment framework that is applicable to the Chengdu-Chongqing Urban Agglomeration. The results show that from 2014 to 2020, the three types of SDGs exhibited an overall upward trend, with the lowest values occurring in 2016. The gap between different counties has narrowed, but significant regional differences still remain, indicating an unbalanced development status quo. Among the 142 counties, water yield and soil conservation values show a consistent downward trend but occupies significant interannual variations, while habitat quality and carbon storage values increases consistently each year. (2) using Spearman's nonparametric correlation analysis and multiscale geographically weighted regression model to explore the temporal variation and spatial heterogeneity of correlations between county ESs and SDGs. The results showed significant heterogeneity in the spatial trade-offs and synergies between ESs and SDGs, with two pairs of synergies weakening, seven pairs of trade-offs increasing, and the strongest negative correlation between Economic Sustainable Development Goals and habitat quality. (3) we applied the self-organizing mapping neural networks to analyze the spatial clustering characteristics of ESs-SDGs. Based on the spatial clustering effects, we divides the Chengdu-Chongqing Urban Agglomeration into four zones, and different zones have different levels of ESs and SDGs. The targeted strategies should be adopted according to local conditions. This work is of great practical importance in maintaining the stability and sustainable development of the Chengdu-Chongqing Urban Agglomeration ecosystem and provides a scientific reference for the optimal regulation of mountainous cities.

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.

Spatio-temporal evolution characteristics and driving mechanisms of waterlogging in urban agglomeration from multi-scale perspective: A case study of the Guangdong-Hong Kong-Macao Greater Bay Area, China.

Understanding the characteristics of waterlogging in urban agglomeration is essential for effective waterlogging prevention and management, as well as for promoting sustainable urban development. Previous studies have predominantly focused on the driving mechanisms of waterlogging in urban agglomeration at a single scale, but urban agglomeration space has greater spatio-temporal heterogeneity, it is often difficult to fully reveal such characteristics at a single scale. Consequently, this study endeavors to explore the spatio-temporal evolution characteristics and underlying mechanisms of waterlogging incidents within urban agglomerations by adopting a multi-scale analytical approach. The results indicate that: (1) The waterlogging degree and high-density zones increase in the GBA, and the waterlogging points are spatially polycentric. However, the waterlogging point in Hong Kong is decreasing. (2) The influence of ISP and AI on waterlogging is dominant at all scales, followed by RE and Slope. ISP∩Slope and ISP∩RE are the key interactions for waterlogging. (3) The aggregation of waterlogging decreases with grid scale, and the influence of land cover factors on waterlogging increases with grid scale. Moreover, the findings at the grid scale outperformed those at the watershed scale, indicating that the grid scale is more conducive to the investigation of waterlogging in urban agglomerations. This research broadens our comprehension of the mechanisms behind waterlogging in urban agglomeration and provide references for policy decisions on waterlogging prevention and mitigation within urban agglomerations.

Hybrid life-cycle and hierarchical archimedean copula analyses for identifying pathways of greenhouse gas mitigation in domestic sewage treatment systems.

Electricity consumption and anaerobic reactions cause direct and indirect greenhouse gas (GHG) emissions within domestic sewage treatment systems (DSTSs). GHG emissions in DSTSs were influenced by the sewage quantity and the efficacy of treatment technologies. To address combined effects of these variables, this study presented an approach for identifying pathways for GHG mitigation within the DSTSs of cities under climate change and socio-economic development, through combining life cycle analysis (LCA) and the Hierarchical Archimedean copula (HAC) methods. The approach was innovative in the following aspects: 1) quantifying the GHG emissions of the DSTSs; 2) identifying the correlations among temperature changes, socioeconomic development, and domestic sewage quantity, and 3) predicting the future fluctuations in GHG emissions from the DSTSs. The effectiveness of the proposed approach was validated through its application to an urban agglomeration in the Pearl River Delta (PRD), China. To identify the potentials of GHG mitigation in the DSTSs, two pathways (i.e., general and optimized) were proposed according to the different technical choices for establishing facilities from 2021 to 2030. The results indicated that GHG emissions from the DSTS in the PRD were [3.01, 4.96] Mt CO2eq in 2021, with substantial contributions from Shenzhen and Guangzhou. Moreover, GHG emissions from the sewage treatment facilities based on Anaerobic-Anoxic-Axic (AAO) technology were higher than those based on other technologies. Under the optimized pathway, GHG emissions, contributed by the technologies of Continuous Cycle Aeration System (CASS) and Oxidation Ditch (OD), were the lowest. Through the results of correlation analysis, the impact of socioeconomic development on domestic sewage quantities was more significant than that of climate change. Domestic sewage quantities in the cities of the PRD would increase by 4.10%-28.38%, 17.14%-26.01%, and 18.15%-26.50% from 2022 to 2030 under three Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5. These findings demonstrated that the capacities of domestic sewage treatment facilities in most cities of the PRD should be substantially improved from 0.12 to 2.99 times between 2022 and 2030. Under the optimized pathway, the future GHG emissions of the CASS method would be the lowest, followed by the OD method.

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

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

Spatiotemporal evolution and driving factors of ecosystem service bundle based on multi-scenario simulation in Beibu Gulf urban agglomeration, China.

Rapid urbanization is profoundly impacting the ecological environment and landscape patterns, leading to a decline in ecosystem services (ES) and posing threats to both ecological security and human well-being. This study aimed to identify the spatial and temporal patterns of ecosystem service bundles (ESB) in the Beibu Gulf urban agglomeration from 2000 to 2030, analyze the trajectory of ESB evolution, and elucidate the drivers behind ESB formation and evolution. We utilized the Patch-generating Land Use Simulation (PLUS) model to establish baseline (BLS), carbon sequestration priority (CPS), and urbanization priority (UPS) scenarios for simulating land use patterns in 2030. Following the assessment of ecosystem service values (ESV) through the equivalent factor method, we identified the spatiotemporal distribution patterns of ESB using the K-means clustering algorithm. By employing stability mapping and landscape indices, we identified and analyzed various types of ESB evolutionary trajectories. Redundancy analysis (RDA) was employed to pinpoint the drivers of ESB formation and evolution. The results revealed that from 2000 to 2030, land use changes were primarily observed in cropland, forestland, and construction land. Between 2000 and 2020, 92.88% of the region did not experience shifts in ESB types. In UPS, the ESB pattern in the study area underwent significant changes, with only 76.68% of the region exhibiting stabilized trajectories, while the other two scenarios recorded percentages higher than 80%. Key drivers of ESB-type shifts included initial food provision services, elevation, slope, changes in the proportion of construction land, and population change. This multi-scenario simulation of ESB evolution due to land use changes aids in comprehending potential future development directions from diverse perspectives and serves as a valuable reference for formulating and changing ecological management policies and strategies.

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.

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.

Understanding the inter-city causality and regional transport of atmospheric PM2.5 pollution in winter in the Harbin-Changchun megalopolis in China: A perspective from local and regional.

Harbin-Changchun megalopolis (HCM) is the typical cold urban agglomeration in China, where PM2.5 pollution is still serious in winter against the backdrop of continuous improvement in annual air quality in China. To further understand interactions of atmospheric pollution among HCM cities, inter-city causality and regional transport of PM2.5 in the winter in the HCM were comprehensively investigated by using convergent cross mapping (CCM) and CMAQ-BFM methods. CCM analysis results suggest strong bidirectional causal relationships between cities in the HCM, and the causality during polluted episodes were significantly larger than that during clean period. In addition, the influence on local PM2.5 from the HCM western cities were larger than that from cities in the southeast. Inter-city and regional transport contributions results demonstrated that although local emission were the largest contributors among 14 sub-regions for most HCM cities, interactions among cities were strong. Regional transport (42.8%-77.4%) largely contributes to HCM cities' PM2.5 concentrations. Among three regions outside the HCM, NMG (including part of inner Mongolia and Baicheng city in Jilin, 9.1%) was the largest contributor to the PM2.5 concentration in the whole HCM, followed by JLS (including Liaoning Province, Tonghua and Baishan cities in Jilin province, 5.1%) and HLJ (including cities of Heihe, Yichun, Jiamusi, Hegang, Shuangyashan, Jixi, Qitaihe in the Heilongjiang province, 3.8%). Regional transport contribution to the most HCM cities increased significantly from excellent to heavily polluted days. Furthermore, close relationships between transport paths/intensity and wind direction/speed in studied region suggests that we can quantitatively guide the regional joint emergency prevention and control before and during heavily polluted events based on regional weather forecasts in the future.

Spatio-temporal evolution of resources and environmental carrying capacity and its influencing factors: A case study of Shandong Peninsula urban agglomeration.

Promoting ecological conservation and high-quality development in the Yellow River basin is an important objective in China's 14th Five-Year Plan. Understanding the spatio-temporal evolution of and factors affecting the resources and environmental carrying capacity (RECC) of the urban agglomerations is critical for boosting high-quality green-oriented development. We first combined the Driver-Pressure-State-Impact-Response (DPSIR) framework and the improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model to evaluate the RECC of Shandong Peninsula urban agglomeration in 2000, 2010 and 2020; we then used trend analysis and spatial autocorrelation analysis to understand the spatio-temporal evolution and distribution pattern of RECC. Furthermore, we employed Geodetector to detect the influencing factors and classified the urban agglomeration into six zones based on the weighted Voronoi diagram of RECC as well as specific conditions of the study area. The results show that the RECC of Shandong Peninsula urban agglomeration increased consistently over time, from 0.3887 in 2000 to 0.4952 in 2010 and 0.6097 in 2020, respectively. Geographically, RECC decreased gradually from the northeast coast to the southwest inland. Globally, only in 2010 the RECC presented a significant spatial positive correlation, and that in the other years were not significant. The high-high cluster was mainly located in Weifang, while the low-low cluster in Jining. Furthermore, our study reveals three key factors-advancement of industrial structure, resident consumption level, and water consumption per ten thousand yuan of industrial added value-that affected the distribution of RECC. Other factors, including the interactions between residents' consumption level and environmental regulation, residents' consumption level and advancement of industrial structure, as well as between the proportion of R&D expenditure in GDP and resident consumption level also played important roles resulting in the variation of RECC among different cities within the urban agglomeration. Accordingly, we proposed suggestions for achieving high-quality development for different zones.

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.

Spatiotemporal characteristics of air pollution in Chengdu-Chongqing urban agglomeration (CCUA) in Southwest, China: 2015-2021.

Studying the spatiotemporal characteristics of air pollutants in urban agglomerations and their response factors will help to improve the quality of urban living. In combining air quality monitoring data and wavelet analysis from the Chengdu-Chongqing urban agglomeration (CCUA), this study assessed the spatiotemporal distribution characteristics and influential factors of air pollutants on daily, monthly and annual scales. The results showed that the concentration of air pollutants in the CCUA has decreased year by year, and air quality has improved. Except for O3, pollutants in autumn and winter were higher than those in summer. The spatial distribution of air pollutants was obvious distributed in Chengdu, Chongqing, Zigong and Dazhou. Pollution incidents were mainly concentrated in winter. The 6 air pollutants and air quality index (AQI) have dominant periods on multiple time scales. AQI showed positive coherence with PM2.5 and PM10 on multiple time scales, and obvious positive coherence with SO2, CO, NO2 and O3 in the short term scale. AQI was not strongly correlated with the fire point, but exhibited obvious negative coherence in the long term scale. In addition, AQI showed an obvious positive correlation with temperature and sunshine hours in short term, and a clear negative correlation with humidity and rainfall. The research results of this paper will provide a reference for pollution prevention and control in the CCUA.

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.

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.

An improved approach for evaluating landscape ecological risks and exploring its coupling coordination with ecosystem services.

The rapid urbanization has accelerated the destruction of regional ecosystems, triggering ecological risks and threatening sustainable development. Landscape ecological risk (LER) evaluation is an effective tool to mitigate such negative impacts. However, the existing evaluation systems exhibit certain subjectivity. Therefore, an improved LER evaluation method was proposed, which incorporates ecosystem services (ESs) to characterize landscape vulnerability. The method was validated using the Pearl River Delta urban agglomeration (PRDUA) as the study area. The results showed that the optimal grain size and extent for landscape pattern analysis in the PRDUA were determined to be 150 m and 6km × 6 km, respectively. The comparison results with the traditional LER evaluation method demonstrated the improved method's superior rationality and reliability. The hotspot analysis based on the Getis-Ord Gi* method revealed that the hotspots of LER were mainly concentrated in the densely populated areas of the south-central region of the PRDUA. The coupling coordination degree (CCD) between LERs and ESs showed four different levels of development in both temporal and spatial dimensions, generally dominated by moderately balanced development and lagging ESs, reflecting the unbalanced ecological environment and socio-economic development of the PRDUA. It is recommended that the ecosystems in the PRDUA be managed and protected separately according to the delineated Ecological Protection Area (EPA), Urban Built-up Area (UBA), and Urban Ecological Boundary Area (UEBA). This study can provide an important reference for regional ecosystem conservation and management.

Heavy metals pollution of soil in central plains urban agglomeration (CPUA), China: human health risk assessment based on Monte Carlo simulation.

The present study conducted the concentration evaluation, pollution assessment, source analysis, and risk assessment of heavy metals in the soil of the CPUA, China, to contribute to the smooth construction of urban agglomeration. Elevated levels of mean concentrations of cadmium (Cd), chromium (Cr), and copper (Cu) in the soils were shown compared to background values. Cu and zinc (Zn) and also lead (Pb) and Cd exhibited spatial similarity. Manganese (Mn) and Cr exhibited point source characteristics such as the concentrations at a point much higher than the surrounding area. The potential ecological risk in the northern region belonged to the moderate risk level category. Cd contributed over 90% to the potential ecological risk. The health risk among children was higher than that among adults. The major exposure pathways were different for adults and children. Exposure, as shown using Hazard Index (HI), to adults was mainly through the skin contact route, while to children was through both the skin contact and ingestion route. The primary CR (carcinogenic risk) to adults was through the inhalation route, while that to children was through the ingestion route. In both children and adults, Cr was the main contributor to HI and CR. According to the Monte Carlo simulation results, the cumulative probability of exceeding the critical value of HI for children was approximately 2.8-3.0 times that for adults. According to the sensitivity analysis results, non-carcinogenic risk prevention should begin mainly by reducing exposure duration and skin contact. The cancer risk may be reduced primarily by decreasing the exposure duration and controlling ingestion. The PMF (Positive Matrix Factorization) source analysis revealed that Pb mainly came from transportation sources. In addition, Cu, Pb, and Mn were derived mainly from agricultural sources. Cr was derived mostly from a natural source, and Cd originated mainly from an industrial source.

Effects of production-living-ecological space changes on the ecosystem service value of the Yangtze River Delta urban agglomeration in China.

In the process of urbanization, exploring the relationship between production-living-ecological space (PLES) and ecosystem service value (ESV) is a major scientific issue in promoting regional sustainable development. The Yangtze River Delta (YRD) urban agglomeration is an ideal study area, which has the highest urbanization rate in China. Based on Landsat TM/ETM imaging data from 2005, 2010, 2015, and 2018, this study established a land use classification system of PLES. The spatial and temporal characteristics of PLES and ESV were analyzed, and the response of ESV to changes in PLES was investigated based on the elasticity formula. The results showed that from 2005 to 2018, production space and ecological space were the main types of PLES and exhibited an imbalance in transformation. Production space was the main transfer type, and living space significantly expanded. Moreover, from 2005 to 2018, the ESV of the YRD urban agglomeration showed an increasing and then decreasing trend. ESV presented a "high in the southwest and low in the northeast" spatial pattern. Furthermore, ESV was sensitive to changes in PLES, showing a trend of ecological space > production space > living space. However, the sensitivity of ESV to changes in PLES varied according to urbanization level.

Qualitative-quantitative identification and functional zoning analysis of production-living-ecological space: a case study of Urban Agglomeration in Central Yunnan, China.

Territorial space exhibits multiple functional attributes, which comprise production, living, and ecological functions usually. Optimizing the production-living-ecological space (PLES) has become the key to territorial and spatial planning; the scientific identification of the PLES lays a foundation for space optimization and has important guiding significance in territorial spatial zoning. To achieve the integration of macro-scale and micro-scale PLES, with the Urban Agglomeration in Central Yunnan as the research area in this study, the PLES functional identification systems from the administrative unit scale and the grid scale are constructed. The types of PLES are determined by integrating qualitative and quantitative evaluation results and using an improved primacy index model from a composite spatial perspective. On that basis, the division of comprehensive zoning is achieved for land use functions through kernel density analysis. As indicated by the results, the model is capable of reflecting the macro background of the PLES functions in administrative regions while characterizing the micro differences at the grid level in administrative units. There are significant differences in the production, living, and ecological functional spaces in the Urban Agglomeration. Production functions are concentrated in the central and northeastern, living functions are concentrated in the central, and ecological functions are concentrated in the western and northeastern, with significantly consistent or complementary spatial distributions of each other. The PLES of Urban Agglomeration includes production space (PS), ecological space (ES), production-living space (P-LS), production-ecological space (P-ES), living-ecological space (L-ES), and production-living-ecological space (P-L-ES), placing a focus on ES, P-ES, and P-L-ES, which marks significant differences in spatial distribution among different spatial types. The study area is divided into 24 functional zones, which are classified into 6 categories, and optimization paths are proposed. This study will provide a reference for territorial and spatial planning in spatial functional zoning, spatial pattern optimization, and land management applications.

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.

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.