Spatial-temporal evolution and driving force analysis of eco-quality in urban agglomerations in China

Analysis of influencing factors and paths of synergistic development of water resources-economic society-ecological environment based on DIM modeling

The intersection of climate change and human activities exacerbates the prominent contradiction between environmental resources and economic development. The synergistic development of water resources, economy and society, and ecological environment is particularly urgent. Therefore, accurately identifying its influencing factors and related pathways holds significant practical importance in resolving the contradiction between resources and economic development. This study constructs a system of influencing factors for the synergistic development of "water resources, economic society and ecological environment" from three dimensions, reveals the influencing relationship between indicators through the Decision Making Trial and Evaluation Laboratory (DEMATEL), determines the hierarchical structure of the influencing factors and the related paths through the Interpretive Structural Model (ISM), and classifies the influencing factors through the Matrix Multiplication Method of Cross Influence Matrix Multiplication (MICMAC). The results show that water resource factors are important cause factors and economic, social and ecological factors are essential effect factors. The factors influencing the synergistic development of "water resources, economic society and ecological environment" can be divided into four levels, of which the total water resources, precipitation and NDVI are at the bottom and are the most fundamental factors. The percentage of groundwater supply, total water supply, water resource utilization rate and energy consumption of 10,000 yuan of GDP are the deep core elements. Total grain output, water resources per capita, and water use per capita are the direct influencing factors. Finally, taking the Central Plains Urban Agglomeration as an example, selecting the identified important influencing factors and analyzing the level of synergistic development of its coupled system found that the degree of coupling coordination increased from 0.324 in 2011 to 0.978 in 2020. The water resources system showed a fluctuating change, and it is still the key to synergistic development. Analyzing the relationship between subsystems and clarifying the key factors for synergistic development of coupled systems are important for policy formulation, improving environmental governance and promoting high-quality economic development.

Investigation of the interactions and influencing factors of the Water-Land-Energy-Carbon system in the Yellow River Basin

The survival and advancement of human society are fundamentally dependent on the availability and sustainable management of water, land, and energy resources. The development and utilisation of various energy sources and a considerable number of natural resources lead to carbon emissions. A complex interplay exists between water, land, energy, and carbon, and their correlation lies at the core of the regional "natural-social-economic" system, which is crucial for human existence and advancement. Despite its importance, research on the water-land-energy‑carbon (WLEC) nexus is limited. In this study, we employed an innovative combination of the comprehensive assessment index, coupled coordination degree, panel vector autoregressive, and random forest models to investigate the spatiotemporal evolution, internal dynamic interactions, and external influencing factors of the WLEC system in the Yellow River Basin (YRB) from 2007 to 2021. The findings revealed that the degree of coupled coordination in the WLEC system of the YRB exhibited an overall steady upward trend. The spatial agglomeration effect was continuously enhanced, and regional disparities increased. Complex interaction mechanisms exist within the water, land, energy, and carbon subsystems in the YRB. Population size, land relief, and sunshine are the prevailing factors influencing the degree of coupling coordination in the WLEC. Addressing the trade-off relationship among the subsystems of the WLEC system is a key aspect of optimising its correlation relationship. This study provides a scientific basis and relevant suggestions for achieving the Double-Carbon Goal, promoting ecological protection and high-quality development in the YRB.

Projecting LUCC dynamics and ecosystem services in an emerging urban agglomeration under SSP-RCP scenarios and their management implications

Improving our knowledge of future dynamics of ecosystem services (ESs) in the face of climate change and human activities provides a crucial foundation to navigate complex environmental challenges, which are essential to attaining sustainable development particularly in urban regions. However, an existing dearth persists in thoroughly forecasting the intricate interplay of trade-offs and synergies, as well as ecosystem services bundling under distinct future scenarios. This study adopts an integrated research framework to understand the spatiotemporal dynamics of ESs in the Changsha-Zhuzhou-Xiangtan Urban Agglomeration (CZTUA) under three Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios (i.e., SSP126, SSP245 and SSP585). Our future scenarios suggest that the core urban area of CZTUA is projected to expand at the cost of forests and croplands by 2050. Furthermore, human-induced urbanization, particularly the high-intensity LUCC along the Xiangjiang river, significantly impacts ESs, resulting in lower ESs values. The trade-off effects between ESs are primarily observed between WY (water yield) and other ESs. Ecosystem service bundles (ESB) previously dominated by WY have significantly transitioned to CS (carbon storage)-HQ (habitat quality) bundle, especially in the urban core of CZTUA, which serves as an early warning of potential challenges related to water resources. Our study utilizes the latest climate and land use change predictions to evaluate ecosystems in urban agglomerations, and adopts a layered zoning strategy based on ESs, which provides decision-makers with reproducible tools to explore ecosystem changes.

Driving forces and obstacles analysis of urban high-quality development in Chengdu

High-quality development paths in important cities are blurry and lacking. In order to explore the important engine for Chengdu high-quality development, driving forces and obstacles recognition has emerged as a pivotal technological solution. Using the Chengdu in Sichuan province of China as a research area and quantitative data from 2010 to 2019, this study has used content mining to recognize urban high-quality development (UHQD) variables, and calculated variables' weights by entropy weight method, and explored driving forces and obstacles of UHQD by the technique for order preference by similarity to ideal solution (TOPSIS) method. The main findings are: (1) there are 36 UHQD variables; (2) Chengdu high-quality development overall level soars from 2017 to 2019, only with two negative growth rates in 2011, 2015; (3) There are 3 key driving force paths: (1) improving green development by volume of industrial wastewater discharged, comprehensively utilised ratio of industrial solid wastes, harmless treatment rate of domestic garbage; (2) stressing open development by total import and export/GDP, actual use of foreign capital, number of foreign tourists/total tourists; and (3) intensifying shared development by funds for urban residents under basic provision protection. (4) 3 clearing obstacles paths can also realize Chengdu high-quality development: (1) improving innovative development level by R&D internal outlay, patent authorisations, state high-level tech enterprises; (2) optimizing coordinated development level by the proportion of tertiary industry; (3) promoting shared development level by urban basic pension insurance. According to these findings, suggestions are put forward to promote Chengdu high-quality development from the perspective of policy implementation.

Improving grassland ecosystem services for human wellbeing in the karst desertification control area: Anthropogenic factors become more important

Elucidating the spatial and temporal patterns of grassland ecosystem service value (ESV) changes under different karst geomorphic types (KGTs) is crucial for promoting regional sustainable development and enhancing human well-being. Karst ecosystems are characterized by high spatial heterogeneity. However, analyses of the drivers of spatial and temporal changes in ESV in karst grasslands at multiple scales are lacking. In this study, the South China Karst (SCK) region was selected as the focus area, the gross ecosystem product (GEP) accounting method was used to quantify the grassland ESV from 2000 to 2020, and the GeoDetector model was used to elucidate the spatial and temporal evolution of the GEP, the drivers, and their interactions in different KGTs. The results indicate the following: (1) Over the past 20 years, the grassland GEP of SCK has increased from ¥ 14,844.24 × 108 in 2000 to ¥ 17,174.90 × 108 in 2020. Among the various KGTs, the karst gorge exhibited the fastest GEP increase (24.93 %) and karst hilly depressions the slowest (6.22 %). (2) The karst grassland GEP showed a strong positive spatial correlation with significant clustering characteristics (p < 0.05). (3) There are significant differences in the factors influencing the GEP of grasslands with different KGT values, and although they are generally influenced by factors such as NPP, precipitation, and population density, anthropogenic factors are becoming increasingly important. In addition, the multifactor interaction explained GEP better than the single factor. Based on our findings, we propose targeted grassland ESV restoration approaches and management recommendations for various KGTs dominated by distinct factors. Our results provide a scientific basis for decision-making regarding karst ecosystem service enhancement and value realization.

Research on remote sensing ecological livability index based on Google Earth Engine: a case study from Urumqi-Changji-Shihezi urban cluster

The U-Chang-Shi (Urumqi-Changji-Shihezi) urban cluster, located at the heart of Xinjiang, boasts abundant natural resources. Over the past two decades, rapid urbanization, industrialization, and climate change have significantly threatened the region's ecological livability. To comprehensively, scientifically, and objectively assess the ecological livability of this area, this study leverages the Google Earth Engine (GEE) platform and multi-source remote sensing data to develop a comprehensive evaluation metric: the Remote Sensing Ecological Livability Index (RSELI). This aims to examine the changes in the ecological livability of the U-Chang-Shi urban cluster from 2000 to 2020. The findings show that despite some annual improvements, the overall trend in ecological livability is declining, indicating that the swift pace of urbanization and industrialization has placed considerable pressure on the region's ecological environment. Land use changes, driven by urban expansion and the growth in agricultural and industrial lands, have progressively encroached upon existing green spaces and water bodies, further deteriorating the ecological environment. Additionally, the region's topographical features have influenced its ecological livability; large terrain fluctuations have made soil erosion and geological disasters common. Despite the central plains' vast rivers providing ample water resources, over exploitation and ill-conceived hydrological constructions have led to escalating water scarcity. The area near the Gurbantunggut Desert in the north, with its extremely fragile ecological environment, has long been unsuitable for habitation. This study provides a crucial scientific basis for the future development of the U-Chang-Shi urban cluster and hopes to offer theoretical support and practical guidance for the sustainable development and ecological improvement of the region.

Research on the evolution characteristics, driving mechanisms and multi-scenario simulation of habitat quality in the Guangdong-Hong Kong-Macao Greater Bay based on multi-model coupling

Since the 20th century, the global urbanization has led to a series of pollution issues, posing a severe threat to the habitat quality of human habitat. The quality of habitat determines whether ecosystems can provide suitable living conditions for humans and other species. Therefore, systematic study of the habitat quality is essential for the maintenance of sustainable development. In this study, we coupled models such as SD, InVEST and PLUS with a series of indicators to analyze the characteristics of land cover and habitat quality evolution in the Guangdong-HongKong-Macao Greater Bay Area (GBA) from 2000 to 2020 and deconstruct the driving mechanisms of habitat quality. Then simulate the evolution of land cover and habitat quality under different scenarios in 2030. The results show that: 1) Over the historical research period, the GBA exhibited "rapid expansion of artificial surfaces and rapid shrinkage of ecological land". Artificial surfaces increased by approximately 4878.95km2,while ecological land, such as agricultural land, decreased by about 3095.93km2.2) The degradation of habitat quality gradually accelerated and the habitat quality was characterized by "stepwise decline from the periphery to the interior", which was directly related to the land cover changes brought about by the topographic gradient effect in the Bay Area.3) Pollution control driven by environmental investments has had a moderating effect on habitat degradation, but it has not been able to change the overall degradation trend. 4) Scenario analysis suggests that future habitat quality in the GBA will degrade to a certain extent due to the impact of artificial surface expansion. We deduce that this will affect the structure of the city's ecological network as well as the conservation function of the ecological zones. This study provides a scientific basis for understanding the historical and future trends of habitat quality in the GBA, offering new insights into the intrinsic driving mechanisms of habitat quality. It also provides a theoretical support for relevant authorities to undertake sustainable development initiatives.