Yangtze River Delta Urban Agglomeration Research Articles

Spatial and Temporal Variations of Vegetation Phenology and Its Response to Land Surface Temperature in the Yangtze River Delta Urban Agglomeration

In the Yangtze River Delta urban agglomeration, which is the region with the highest urbanization intensity in China, the development of cities leads to changes in land surface temperature (LST), while vegetation phenology varies with LST. To investigate the spatial and temporal changes in vegetation phenology and its response to LST in the study area, this study reconstructed the time series of the enhanced vegetation index (EVI) based on the MODIS EVI product and extracted the vegetation phenology indicators in the study area from 2002 to 2020, including the start of the growing season (SOS), the end of the growing season (EOS), and the growing season length (GSL), and analyzed the temporal–spatial patterns of vegetation phenology and LST in the study area, as well as the correlation between them. The results show that (1) SOS was advanced, EOS was postponed, and GSL was extended in the study area from 2002 to 2020, and there were obvious differences in the vegetation phenology indicators under different land covers and cities; (2) LST was higher in the southeast than in the northwest of the study area from 2002 to 2020, with an increasing trend; and (3) there are differences in the response of vegetation phenology to LST across land covers and cities, and SOS responds differently to LST at different times of the year. EOS shows a significant postponement trend with the annual mean LST increase. Overall, we found differences in vegetation phenology and its response to LST under different land covers and cities, which is important for scholars to understand the response of vegetation phenology to urbanization.

Analysis of dynamic evolution characteristics and driving factors of regional synergistic effect of reducing carbon and saving water: the case of Yangtze River Delta Urban Agglomerations, China.

Carbon emissions and water consumption are both important factors affecting sustainable development. Therefore, it is necessary to put them in the same research framework and investigate the synergy. In this study, the dynamic evolution characteristics of the synergistic effect of reducing carbon and saving water (RCSW) were analyzed. Then, taking the Yangtze River Delta Urban Agglomerations (YRDUA) as the research object, the influencing factors and specific paths of the synergistic effect were clarified. The results showed that the low-carbon emission efficiency (LCEE) had a stable synergy with the intensive utilization efficiency of water resources (IUEWR) in the YRDUA. Government financial expenditure, actual use of foreign capital, and population density were the most significant driving forces for the synergistic effect of RCSW, with q values of 0.561, 0.363, and 0.240, respectively. In addition, most of the interactions of the driving factors were nonlinear enhancement and double-factor enhancement.

Digital Economy and Green and Low-Carbon Transformation of Land Use: Spatial Effects and Moderating Mechanisms

The green and low-carbon transformation of land use (GLTLU) is a pressing global issue that requires urgent attention. The digital economy has emerged as a new driver for the GLTLU. However, current research mainly focuses on the measurement and environmental effects of the digital economy, with less exploration of how the digital economy influences the spatial effects and regulatory mechanisms of GLTLU, particularly regarding the differential impacts and specific mechanisms at the regional level. This study uses panel data from 283 cities in China from 2011 to 2019, employing the spatial Durbin model (SDM) and the panel threshold model to examine the spatial and regulatory mechanisms of the digital economy’s impact on GLTLU. The findings reveal that digital economy promotes GLTLU not only within cities but also in surrounding regions. Robustness analyses support this conclusion. Notably, the digital economy’s positive impact on GLTLU in surrounding areas is confined to the central region of China. In contrast, the Yangtze River Delta urban agglomeration experiences a significant negative impact on GLTLU in nearby regions due to the digital economy. The study also identifies that the positive spatial spillover effect of the digital economy on GLTLU reaches its peak at a distance of 450 km. Additionally, the digital economy’s ability to promote GLTLU is contingent upon financial agglomeration levels exceeding 9.1728. Moreover, the local government’s emphasis on the digital economy and intellectual property protection enhances the digital economy’s impact on GLTLU. The promotion effect is maximized when these factors surpass the thresholds of 27.8054 and 3.5189, respectively. Overall, this study contributes to the understanding of how the digital economy influences sustainable land development, highlighting the critical role of regional factors and regulatory mechanisms in amplifying the digital economy’s positive effects on GLTLU.

Insights from land sparing and land sharing frameworks for land productivity degradation governance in the Yangtze River Delta urban agglomeration, China

AbstractLand degradation due to mismanagement is widespread globally and may threaten the achievement of several UN Sustainable Development Goals. Yet the differences in land productivity degradation under various land management patterns (land sparing vs. land sharing) are poorly known. In this research, we used remote sensing data to develop a machine learning model for assessing the risk of land productivity degradation and interpreted the model using state‐of‐the‐art interpretable artificial intelligence techniques. In 2018, the risk level of land productivity degradation in the agricultural production space of the Yangtze River Delta urban agglomeration (YRD) was 0.230. More than half of the area was at low risk (68.19% of the area), mainly in mountainous and hilly areas. The degradation risk of the land sharing management pattern is lower than that of the land sparing pattern, but there are significant differences among provinces/municipalities. The four most influential factors for land productivity degradation in YRD were Normalized Vegetation Difference Index, nighttime light, elevation, and nitrogen deposition, which together explained 72.75% of the degradation risk. This study provides a methodological framework for land degradation governance in emerging urban agglomerations. It strongly recommends that policymakers explore locally appropriate land management patterns based on regional contexts.

Does policy integration promote water–energy–food coordination? A quasi-natural experiment in the Yangtze River Delta Urban Agglomeration

Does policy integration promote water–energy–food coordination? A quasi-natural experiment in the Yangtze River Delta Urban Agglomeration

Relationship between Green Space and Mortality in the Cities of the Yangtze River Delta Urban Agglomeration

Relationship between Green Space and Mortality in the Cities of the Yangtze River Delta Urban Agglomeration

Exploring the spatial effects and influencing mechanism of ozone concentration in the Yangtze River Delta urban agglomerations of China.

Ground-level ozone (O3) pollution has emerged as a significant concern impacting air quality in urban agglomerations, primarily driven by meteorological conditions and social-economic factors. However, previous studies have neglected to comprehensively reveal the spatial distribution and driving mechanism of O3 pollution. Based on the O3 monitoring data of 41 cities in the Yangtze River Delta (YRD) from 2014 to 2021, a comprehensive analysis framework of spatial analysis-spatial econometric regression was constructed to reveal the driving mechanism of O3 pollution. The results revealed the following: (1) O3 concentrations in the YRD exhibited a general increasing and then decreasing trend, indicating an improvement in pollution levels. The areas with higher O3 concentration are mainly the cities concentrated in central and southern Jiangsu, Shanghai, and northern Zhejiang. (2) The change of O3 concentration and distribution is the result of various factors. The effect of urbanization on O3 concentrations followed an inverted U-shaped curve, which implies that achieving higher quality urbanization is essential for effectively controlling urban O3 pollution. Traffic conditions and energy consumption have significant direct positive influences on O3 concentrations and spatial spillover effects. The indirect pollution contribution, considering economic weight, accounted for about 35%. Thus, addressing overall regional energy consumption and implementing traffic source regulations are crucial paths for O3 pollution control in the YRD. (3) Meteorological conditions play a certain role in regulating the O3 concentration. Higher wind speed will promote the diffusion of O3 and increase the O3 concentration in the surrounding city. These findings provide valuable insights for designing effective policies to improve air quality and mitigate ozone pollution in urban agglomeration area.

Regional integration, agricultural production, and their heterogeneous interaction in the classic urban agglomeration of China

Regional integration, a global trend covering multiple aspects of cities that constitute an urban agglomeration, is poised to reallocate limited resources and reshape regional production pattern. While its effects on urban economic efficiency and environmental emissions have been investigated, the agricultural system, which plays a pivotal role in ensuring food security, remains an underexplored domain. To address this, this study commences by discussing the possible influence of regional integration on agricultural production drawing from literature and practical evidence. Then the regional integration level of the Yangtze River Delta Urban Agglomeration (YRDUA) from 2005 to 2019 was evaluated, which is a facet that has received limited quantitative scrutiny hitherto. Subsequently, the agricultural production efficiency (APE) that integrates the composite inputs and outputs information was analyzed to assess the utility of rural production. The interconnection between these two systems was then explored by panel Tobit Model. The findings reveal that (1) regional integration in the YRDUA has exhibited fluctuation across different developmental stages and is presently converging toward a state of stability. (2) The APE appears better performance characterized by weakened spatial heterogeneity and long-term growth. (3) The APE presents an increase in response to the improved integration levels within the gradients, and the model results suggest a positive relationship between them. The discovery of this study implied the potential of macro-regulation promoted through regional integration to enhance APE, underscoring its dual welfares, impacting not only urban development but also extending its spilled-beneficial effects to rural overall production. It provides insights to help find solutions to food security and regional equilibrium under the worldwide tendency of regional integration.

Impact of urban space on PM2.5 distribution: A multiscale and seasonal study in the Yangtze River Delta urban agglomeration

Despite concerted efforts in emission control, air pollution control remains challenging. Urban planning has emerged as a crucial strategy for mitigating PM2.5 pollution. What remains unclear is the impact of urban form and their interactions with seasonal changes. In this study, base on the air quality monitoring stations in the Yangtze River Delta urban agglomeration, the relationship between urban spatial indicators (building morphology and land use) and PM2.5 concentrations was investigated using full subset regression and variance partitioning analysis, and seasonal differences were further analysed. Our findings reveal that PM2.5 pollution exhibits different sensitivities to spatial scales, with higher sensitivity to the local microclimate formed by the three-dimensional structure of buildings at the local scale, while land use exerts greater influence at larger scales. Specifically, land use indicators contributed sustantially more to the PM2.5 prediction model as buffer zone expand (from an average of 2.41% at 100 m range to 47.30% at 5000 m range), whereas building morphology indicators display an inverse trend (from an average of 13.84% at 100 m range to 1.88% at 5000 m range). These results enderscore the importance of considering building morphology in local-scale urban planning, where the increasing building height can significantly enhance the disperion of PM2.5 pollution. Conversely, large-scale urban planning should prioritize the mixed use of green spaces and construction lands to mitigate PM2.5 pollution. Moreover, the significant seasonal differences in the ralationship between urban spatical indicatiors and PM2.5 pollution were observed. Particularly moteworthy is the heightened association between forest, water indicators and PM2.5 concentrations in summer, indicating the urban forests may facilitate the formation of volatile compunds, exacerbating the PM2.5 pollution. Our study provides a theoretical basis for addressing scale-related challenges in urban spatial planning, thereby forstering the sustainable development of cities.

Assessing Urban Water–Energy–Food Security: A Case of Yangtze River Delta Urban Agglomeration

Assessing Urban Water–Energy–Food Security: A Case of Yangtze River Delta Urban Agglomeration

Monitoring public perceptions of contaminated sites based on social media

Contaminated sites have a negative impact on human health and the ecological environment, which can potentially lead to major pollution incidents, and frequently receive complaints and reports from the public. Therefore, monitoring public perceptions of contaminated sites is crucial for risk management. However, methods based on traditional questionnaire surveys are limited in terms of time, cost, and target audience size. The purpose of this study was to establish a method using social media to monitor public perceptions of contaminated sites in the Yangtze River Delta urban agglomeration. Thus, 6802 public opinions were collected from social media (mainly microblogs in China) and topic modeling and pollution and spatial mining techniques were employed. The topic modeling results indicated that public perceptions of contaminated sites mainly focused on the construction of prevention and control systems, law enforcement work, developments and challenges applicable to the coal industry, environmental public interest litigation (pertaining to pollution), pollution inspection and rectification, and green development and ecological governance, with intensities of 7.9%, 7.8%, 7.1%, 6.1%, 5.9%, and 4.8%, respectively. Three communities resulting from public opinions in the study area included “environment and pollution,” “enterprises,” and “environmental protection,” with proportions of 37.68%, 34.78%, and 27.54%, respectively. The field investigation results indicated that approximately 90% of the tweets in three typical cities (i.e., Taizhou City in Zhejiang Province and Wuxi and Changzhou Cities in Jiangsu Province) involved key industrial enterprises or contaminated sites located within 1 km of the surrounding areas. The emotional analysis indicated that >3401 tweets dealt with a pollution probability (i.e., the possibility of potentially contaminated sites mentioned in social media becoming contaminated sites) exceeding 0.90 for the period 2011–2021. This finding suggests that the pollution probability for the sites involved in these tweets was high. Our study provides methodological references for monitoring public perceptions of contaminated sites for large-scale, long-term, and high-resolution studies.

Evaluating the spatiotemporal dynamics of ecosystem service supply-demand risk from the perspective of service flow to support regional ecosystem management: A case study of yangtze river delta urban agglomeration

The inappropriate spatio-temporal distribution of natural capital during rapid urbanization has increased ecosystem service supply-demand (ESSD) risks, posing great challenges to the sustainable growth of human well-being, especially in urban agglomerations. Although methods focusing on the spatial match or temporal dynamics of ESSD in risk assessment have been established, a comprehensive understanding of the spatial dynamics underlying ecosystem service flows (ESF) is still missing. Due to the spatiotemporal heterogeneity of various ESSD risks within urban agglomerations, incorporating these elements into a unified spatial planning framework is still difficult. This study integrated the spatio-temporal analysis method of ESSD considering ESF and the spatial clustering method to propose an ESSD risk assessment and management framework: evaluating ES supply, demand and flow, incorporating ESF to quantify ESSD across various timeframes, assessing ESSD risks based on the current status and dynamic trends, and using Self-Organizing Map to identify optimal ESSD risk bundles (ESSDR_Bs). The results showed high ESSD risks of high temperature regulation, nitrogen purification, phosphorus purification, and food production in Yangtze River Delta urban agglomeration. While the ESSD risks of biodiversity conservation, carbon sequestration, soil retention, water yield, and tourism culture were relatively low, a concerning trend of decreasing surpluses was observed in general. In addition, six ESSDR_Bs were identified, and differentiated ecological management strategies were proposed for each bundle. This study provided a novel perspective for efficiently understanding and regulating the ESSD risks in urban agglomerations.

Contrasting Effects of Urban Land Cover Change and Anthropogenic Heat on Summer Precipitation Over the Yangtze River Delta of China: Analyses From an Atmospheric Moisture Budget Perspective

AbstractBoth urban land cover (ULC) change and anthropogenic heat (AH) emission are important causes of urban heat island, but their relative contributions to the changes in urban precipitation and the related mechanism remain unclear. Based on numerical simulations utilizing the latest realistic urban fraction and AH data over the Yangtze River Delta urban agglomeration, we found that ULC and AH resulted in nearly opposite effects on precipitation. Various dynamical and thermodynamic processes were involved according to the atmospheric moisture budget analyses. AH increased precipitation particularly during afternoon, and the increases were stronger during heavy precipitation events because of the enhanced moisture convergence effect together with the release of moisture storage previously accumulated in the atmosphere. Differently, ULC reduced mean precipitation mainly due to suppressed evaporation. During weak precipitation events, the suppressed evaporation was largely balanced by the intensified moisture convergence, but during heavy events, ULC caused more pronounced precipitation reduction because the moisture convergence response disappeared and failed to offset the evaporation effect. The relative contributions of different dynamical and thermodynamic processes such as those related to circulation, moisture gradient, and background moisture availability to the temporal variation in the total moisture convergence were further quantified. Overall, our results help better understand the relative roles of different aspects of urbanization on precipitation, and suggest that compared to ULC, reduction in AH emission that is tightly related to the energy consumption structure could be more efficient for mitigating the risk of extreme precipitation.

Evaluation and influencing factors of green transformation in three major urban agglomerations in China

Since the 21st century, the world has increasingly focused on the issue of sustainable development, and the green transformation issues have become a new hot topic worldwide. Green and low-carbon transformation has become an international consensus. Urban agglomerations are important connections between urban development and regional coordination, as well as important spatial carriers for economic activities. They are not only the main source of carbon emissions, but also the main battlefield for energy conservation and emission reduction. As an important field for carbon reduction, the green transformation of cities is crucial for achieving the “dual carbon” goals. This article focuses on 48 cities in the three most mature and influential urban agglomerations in China from 2011 to 2019, namely, the Beijing-Tianjin-Hebei urban agglomeration, the Yangtze River Delta urban agglomeration, and the Pearl River Delta urban agglomeration. The three-stage DEA model and Malmquist index model are used to measure the green transformation efficiency of the three urban agglomerations from both dynamic and static perspectives, and a Tobit regression model is constructed to explore the influencing factors of green transformation efficiency in urban agglomerations. Research has found that: 1) From a static perspective, the overall efficiency of green transformation in the three major urban agglomerations is at a high level, but from a temporal perspective, it shows a downward trend. The Pearl River Delta urban agglomeration is known for its green development, with the highest average efficiency of green transformation, followed by the Yangtze River Delta urban agglomeration. The Beijing-Tianjin-Hebei urban agglomeration has the lowest level of green transformation; 2) From a dynamic perspective, technological progress is the main driving factor for improving the efficiency of green transformation in the three major urban agglomerations. Therefore, the government should pay special attention to the progressiveness of technology when formulating relevant policies to promote urban green transformation; 3) From the perspective of spatiotemporal differences, there are significant differences in the spatiotemporal characteristics of green transformation among the three major urban agglomerations, and there are significant differences in green transformation strategies among different urban agglomerations. Eliminating environmental factors and random interference is necessary for accurately measuring the efficiency of green transformation in urban agglomerations; 4) From the perspective of influencing factors, factors such as industrial structure upgrading, green innovation level, and environmental regulation intensity jointly affect the efficiency of green transformation in urban agglomerations. Based on this, we should pay attention to the differences between urban agglomerations and implement policies tailored to local conditions; Strengthen the network system of urban agglomerations and avoid conflicts between cities; Encourage green technology innovation, accelerate industrial structure upgrading, and so on. This article focuses on the issue of green transformation in urban agglomerations, and conducts research from three perspectives: efficiency measurement, influencing factors, and implementation mechanisms. A relatively systematic theoretical framework for green transformation in urban agglomerations is formed, and an evaluation index system for green transformation efficiency in urban agglomerations is constructed and optimized. The composition mechanism of the five dimensional evaluation system for transformation efficiency is analyzed, and the bottleneck and breakthrough direction of the three major urban agglomerations in China in the development process are grasped. It has a good demonstration effect on the green transformation of other urban agglomerations.

Effects of internal migrants' health on economic resilience in China's Yangtze River Delta urban agglomeration: moderating effects of basic public health services.

Internal migrants constitute a significant generality in the socioeconomic development of developing countries. With the frequent occurrence of major public health emergencies, obstacles to labor supply due to health issues among internal migrants not only affect their livelihood stability but also urban economic resilience. Moreover, the design of basic public health service systems tends to favor local residents over internal migrants, further exacerbating the health and employment risks of internal migrants. As a result, urban economic resilience faces significant challenges. The objective of this study was to deconstruct economic resilience into economic resistance and recovery abilities, investigate the net effect and its heterogeneity of internal migrants' health on economic resilience in China's Yangtze River Delta urban agglomeration (CYRD), and the mediating effect from labor participation rate and labor time supply, as well as the moderating effect of basic public health services. Based on the China Migrants Dynamic Survey data (CMDS), the study empirically estimated the effects of internal migrants' health on economic resilience in CYRD through microeconometric analysis methods, mediating and moderating effect model. Our findings indicate that internal migrants' health has a positive effect on economic resilience in CYRD. For each unit increase in migrants' health, it will drive up the average economic resistance ability by 0.0186 and the average recovery ability by 0.0039. Secondly, the net effects of migrants' health on economic resilience show significant structural differences, industry and city heterogeneity. The effect of migrants' health on economic resistance ability is significantly higher than that on economic recovery ability; The effect of migrants' health on economic resilience of the secondary industry is higher than that of the tertiary industry; The cities with high economic resistance and recovery abilities have more prominent positive effect from migrants' health. Thirdly, migrants' health not only has a direct effect on the economic resistance and recovery abilities, but also has a mediating effect on which through labor participation rate and labor time supply. Enhancing the accessibility and quality of basic public health services is beneficial for enhancing the positive effects of internal migrants' health on economic resilience.

Identifying building function using multisource data: A case study of China's three major urban agglomerations

As crucial geographical components shaping urban landscapes, defining the functions of buildings plays one of the pivotal roles in planning urban development and facilitating socio-economic human activities. Existing studies in large-scale mapping mainly ignore the environment around buildings, leading to insufficient meeting the demands of large-scale building-level mapping in certain disciplines. To abridge this gap, this article calculates the geometric characteristics of building footprint, the distances from buildings to adjacent objects, and the kernel densities of Point-of-Interest (POIs) to identify building main functions in three Chinese urban agglomerations (Beijing-Tianjin-Hebei Urban Agglomeration, Yangtze River Delta Urban Agglomeration, and Pearl River Delta Urban Agglomeration). Leveraging XGBoost, our models attained accuracies of 0.936, 0.934, and 0.940 in the three urban agglomerations, accompanied by kappa coefficients of 0.883, 0.868, and 0.891 respectively, suggesting their capability of identifying building functions in large-scale mapping. Furthermore, the conducted experiments on varying feature combinations and transferability highlight the significance of the built environment in enhancing classification accuracy. Additionally, the analysis of the classification results of buildings in the three urban agglomerations shows harmonized development strategies for Yangtze River Delta Urban Agglomeration and Pearl River Delta Urban Agglomeration, while cities within the Beijing-Tianjin-Hebei Urban Agglomeration do not show the same development strategies. All results demonstrate the feasibility of employing multi-source accessible data to efficiently categorize building functions over large areas in a cost-effective manner. This methodology can be replicated in China and even on a larger scale to offer insights into complex urban spaces and to help urban planners provide policy support such as old city renovations and new city planning.

China’s urbanisation evolution and metropolitan area expansion, based on the Prolonged Artificial Nighttime-light Dataset (PANDA, 1984–2020)

ABSTRACT China’s massive urbanisation development will undoubtedly serve as a global reference. Due to the uncertainty of statistical data, nighttime light (NTL) data have emerged as alternative data for urbanisation evaluation. Here, the application of the Prolonged Artificial NTL Dataset of China (1984–2020) has been newly expanded. Total-value statistical, complex NTL index (CNLI), NTL concentration degree, rank-size rule, and Markov transfer matrix were used to systematically mine information about urban change from multiple perspectives. China’s urbanisation exhibited rapid growth and outwards expansion. The total percentage increase in NTL brightness and NTL area was 409.38% and 302.58%, respectively. The Yangtze River Delta urban agglomeration of East China had the fastest urbanisation (CNLI Trend = 0.0057/a, p < 0.01). Low NTL areas transitioned to medium NTL areas, and high and extremely-high NTL areas diffused to medium NTL areas. The cities in Eastern China and Southern China typically exhibited extremely-high type NTL areas, whereas other cities primarily exhibited medium NTL areas. The gaps between city sizes decreased over time (q Trend = – 0.0200/a, p < 0.01). Lowest-ranked cities exhibited the highest stability (>95%) in city size type transition. The spatiotemporal changes in NTL obtained were of great significance for monitoring urban expansion patterns, making government decisions, and quantifying China’s sustainable development.

Decrypting resilience: The spatiotemporal evolution and driving factors of ecological resilience in the Yangtze River Delta Urban Agglomeration

Can a system be reconstructed for greater resilience to complex disturbances? We provide answers to this question by demystifying ecological resilience (ER). We innovatively constructed a “resistant, absorptive, and restorative capacity” framework based on evolutionary resilience theory, the Dagum Gini coefficient, and the panel Tobit model to systematically determine what ER is and how to enhance it. The results indicate that during 2005–2021, minimal longitudinal changes with significant horizontal variations occurred in the ER of the Yangtze River Delta Urban Agglomeration (YRDUA). ER showed an “east strong, west weak” pattern, with average values from 0.124 to 0.665. The ER of Southern Jiangsu ranked high, while that of the seven cities in Anhui ranked low. The inequity of ER showed an initial increase followed by a fluctuating decreasing trend; the overall average Gini coefficient was 0.262. The intra-regional differences showed Zhejiang > Jiangsu > Anhui, with a contribution rate of 55.46%. Green patents and the proportion of cultivated land were the most significant positive and negative driving forces for ER, respectively. Additionally, when these factors worked together, they increased the explanatory power of ER, primarily via nonlinear enhancement. Urbanization rate and green patents enhanced the joint action of driving forces. The contribution of our study is to compensate for the lack of theoretical traceability in previous studies and provide an inspiring analytical framework for ER.

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

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

A novel framework for urban flood resilience assessment at the urban agglomeration scale

With global climate change and continuous urbanization exacerbating floods, urban flood resilience (UFR) has become a key to cope with floods. However, few studies target frameworks of UFR assessment at the urban agglomeration scale over a longer time span. This study, taking the Yangtze River Delta urban agglomeration as a case study, developed an evaluation framework to detail the building of a final evaluation index system of UFR, to analyze UFR's driving factors and spatiotemporal features based on the SSA-PP-KL-TOPSIS (projection pursuit based on sparrow search algorithm-Kullback-Leibler-technique for order of preference by similarity to ideal solution) model. From the perspectives of comparing numerical values and spatial distribution results, the evaluation indicators and method proposed in this article perform better. The case results showed that UFR displayed an overall growth trend and significant spatial heterogeneities. The economic, social, and infrastructure resilience showed a similar growth trend, while the environmental resilience demonstrated a decreasing trend. Environmental resilience has become a weak link in improving resilience. Higher resilience levels were concentrated in the central metropolis, provincial capitals, and industrial cities. The findings could be of use to researchers and practitioners, and the framework presented would be of reference to other flood-stricken areas.