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In the context of climate change and rapid urbanization, there have been unparalleled changes in land use and land cover (LULC), resulting in substantial impacts on the surrounding habitat quality (HQ), particularly in ecologically vulnerable arid regions. However, previous studies on the influencing mechanisms of HQ in arid urban agglomerations and future multi‐scenario simulations remain limited. To fill this knowledge gap, this study aimed to reveal the influencing mechanisms in HQ changes and to develop a multi‐scenario HQ assessment framework within arid urban agglomerations. We assessed the spatiotemporal variations in HQ using the InVEST model and three periods of LULC data for the urban agglomeration on the northern slope of the Tianshan Mountains (UANSTM), and the partial least squares structural equation model was introduced to explore the interactions between natural and non‐natural factors and their impacts on HQ. Additionally, we coupled multi‐objective programming and PLUS models to predict the LULC under different optimization scenarios (natural development scenario (NDS), ecological protection scenario (EPS), ecological–economic coordinated scenario, and economic development scenario) for the UANSTM in 2030, and to assess HQ. Results show that (1) the HQ index of the UANSTM was 0.507, 0.520, and 0.495 in 2000, 2010, and 2020 respectively, with a spatial distribution pattern of high values in the west, low values in the east, and high in the central and low in the north and south; (2) geomorphic, climatic, and LULC factors have direct positive effects on HQ, while socio‐economic factors have a direct negative effect on HQ. In addition, geomorphic, socio‐economic, and climatic factors also influence HQ through potential indirect paths. Climatic and LULC factors enhance the positive effect of geomorphic on HQ while counteracting the direct negative effect of socio‐economic factors on HQ. Climatic factors have the largest negative effect on HQ through their influence on LULC; (3) according to the four scenarios in 2030, the highest HQ index (increased by 0.13%) was found under the EPS, which also aligns more closely with SDGs. Conversely, NDS showed the lowest HQ index (declined by 2.59%). The research results could provide a scientific basis for promoting sustainable land management and ecological conservation for the UANSTM. [ABSTRACT FROM AUTHOR]

Promoting the high-quality development of the marine economy is an inevitable choice for building a maritime power, and technological innovation can provide strong impetus for the high-quality development of the marine economy. Therefore, it is urgent to clarify the impact mechanism of technological innovation on the high-quality development of the marine economy, and promote the high-quality development of the marine economy. This study employs panel data from 11 coastal provinces and municipalities (autonomous regions) in China, spanning the years 2006 to 2020. The objective is to empirically evaluate the mechanism through which scientific and technical innovation impacts the high-quality development of the marine economy. This is achieved by utilizing the PVAR model and the mediation effect model. The research findings indicate that there is a noteworthy impact of enhancing scientific and technological innovation on the marine economy of China. Moreover, there exists a significant reciprocal relationship between scientific and technological innovation and the pursuit of high-quality development in the marine economy. It is observed that scientific and technological innovation not only has a positive influence on the high-quality development of the marine economy by enhancing green total factor productivity and optimizing the industrial structure, but it also facilitates the advancement of the marine economy through the chain mediation path of "improving green total factor productivity and optimizing industrial structure". [ABSTRACT FROM AUTHOR]

Nowadays, the challenges of energy depletion, environmental pollution and food security caused by extensive agriculture development are attracting global attention. In China, the construction of ecological farms is a key initiative to effectuate the goal of peaking carbon dioxide emissions and achieving carbon neutrality, contributing to high-quality agricultural development. Based on this, this study selects the national-level ecological farms directories issued by the Ministry of Agriculture and Rural Affairs (MARA) of China in 2021 and 2022, and collects the corresponding economic, social and physical geographic data for GIS spatial analysis and Geodetector. The results are as follows: (1) The distribution of ecological farms in various provinces of China is uneven and spatially clustered. It generally presents a 'high in the east and low in the west with concentrated cores' pattern. The construction scope significantly expanded over time, and the high-value areas of nuclear density are concentrated in East China, with the development core transitioned from East China to Central China. (2) Environmental conditions, industrial foundation, economic and social development level, science and technology level and financial support all significantly affect the spatial distribution of ecological farms in China, among which the science and technology level has the most significant enhancement effect on other factors. (3) Environmental conditions provide the construction basis for ecological farms, while economic and social development level and financial support determine the number of ecological farms. The industrial foundation affects the scale of ecological farms in China, while the level of science and technology eliminates the restrictions of other factors to a certain extent. This study provides a reference for optimizing the spatial distribution pattern of ecological farms in China and promoting ecological agriculture. In addition, it presents a viable approach to safeguarding food security. [ABSTRACT FROM AUTHOR]

Research framework for the mechanism of the influence of residents' income on residential building carbon emissions. [Display omitted] • The Environmental Kuznets Curve (EKC) hypothesis is confirmed. • Residents' income affects RBCE through direct and indirect effects. • Residential floor space and household appliance use are both mediating variables. • Moderating role of energy structure and environmental awareness are confirmed. The residential building sector, with its significant potential for carbon reduction, is crucial in China's pursuit of carbon emission peaks and neutrality. Using the Stochastic Impacts by Regression on Population, Affluence, and Technology model and Environmental Kuznets Curve hypothesis, this study explores the nonlinear relationship between income and residential building carbon emissions (RBCE) by examining the underlying mechanisms at play. Utilizing panel data for 30 Chinese provinces from 2010 to 2020, we conducted an empirical analysis by employing mediating and moderating models. The results showed that (1) Over the study period, China's RBCE per person rose from 0.73 to 0.95 tons, and disposable income per capita increased from 12,520 to 32,189 CNY. (2) An inverted U-shaped relationship between income and RBCE was observed. However, almost all provinces are yet to traverse the inflection point of this curve, emphasizing the ongoing challenge of mitigating emissions. (3) Residents' income affects RBCE by influencing residential floor space and household appliances use. Energy structure and environmental awareness act as moderators, regulating the extent to which income affects RBCE. Our study provides empirical evidence for carbon reduction goals and highlights the importance of low-carbon lifestyles for sustainable development amidst economic progress. [ABSTRACT FROM AUTHOR]

Nowadays, the challenges of energy depletion, environmental pollution and food security caused by extensive agriculture development are attracting global attention. In China, the construction of ecological farms is a key initiative to effectuate the goal of peaking carbon dioxide emissions and achieving carbon neutrality, contributing to high-quality agricultural development. Based on this, this study selects the national-level ecological farms directories issued by the Ministry of Agriculture and Rural Affairs (MARA) of China in 2021 and 2022, and collects the corresponding economic, social and physical geographic data for GIS spatial analysis and Geodetector. The results are as follows: (1) The distribution of ecological farms in various provinces of China is uneven and spatially clustered. It generally presents a ‘high in the east and low in the west with concentrated cores’ pattern. The construction scope significantly expanded over time, and the high-value areas of nuclear density are concentrated in East China, with the development core transitioned from East China to Central China. (2) Environmental conditions, industrial foundation, economic and social development level, science and technology level and financial support all significantly affect the spatial distribution of ecological farms in China, among which the science and technology level has the most significant enhancement effect on other factors. (3) Environmental conditions provide the construction basis for ecological farms, while economic and social development level and financial support determine the number of ecological farms. The industrial foundation affects the scale of ecological farms in China, while the level of science and technology eliminates the restrictions of other factors to a certain extent. This study provides a reference for optimizing the spatial distribution pattern of ecological farms in China and promoting ecological agriculture. In addition, it presents a viable approach to safeguarding food security.

Air pollution is the environmental issue of greatest concern in China, especially the PM2.5 pollution in the Beijing–Tianjin–Hebei urban agglomeration (BTHUA). Based on sustainable development, it is of interest to study the spatiotemporal distribution of PM2.5 and its influencing mechanisms. This study reveals the temporal evolution and spatial clustering characteristic of PM2.5 pollution from 2015 to 2019, and quantifies the drivers of its natural and socioeconomic factors on it by using a geographical temporal weighted regression model. Results show that PM2.5 concentrations reached their highest level in 2015 before decreasing in the following years. The monthly averages all present a U-shaped change trend. Relative to the traditional high concentrations in the northern part of the BTHUA domain in 2015, the gap in pollution between the north and south has reduced since 2018. The obvious spatial heterogeneity was demonstrated in both the strength and direction of the variables. This study may help identify reasons for high PM2.5 concentrations and suggest appropriate targeted control and prevention measures. [ABSTRACT FROM AUTHOR]

• A comprehensive indicator system is constructed to evaluate green development. • Urbanization shows nonlinear effects on urban green development. • Spatial disparities exist in the impact of urbanization on green development. • Green technology innovation, green life consumption and infrastructure construction form crucial mechanisms. The process of rapid urbanization has exerted immense pressure on the ecological environment of cities. Consequently, achieving green development during urbanization has emerged as the new focal point. Based on 2011–2020 panel data of 110 cities at the prefecture level and above in the Yangtze River Economic Belt (YREB), this study aims to investigate the impact of urbanization on urban green development. Specifically, this study analyzes the spatial and temporal evolution patterns of urbanization and urban green development, and examines the spatial disparities and influencing mechanisms of urbanization on urban green development with the help of panel econometric model and mediation model. The results verify that the urbanization and urban green development levels in the YREB have generally improved, but there are significant differences across cities in terms of their aggregate level and growth rate. The relationship between urbanization and urban green development in the YREB follows a "U" shaped curve, where urbanization initially hinders green development but later facilitates it. Spatially, cities located in the middle and lower reaches, as well as urban agglomerations, benefit from location and organization advantages that amplify the effect of urbanization on urban green development. Conversely, cities in the upper reaches and non-urban agglomerations, with their advantages in late development, have the great potential to promote urban green development at a lower threshold. Moreover, Urbanization influences urban green development through non-linear mediating effects. As the level of urbanization increases, green life consumption (GLC) and green technology innovation (GTI) gradually replace infrastructure construction (IC) as the primary mechanisms driving urban green development in the YREB. [ABSTRACT FROM AUTHOR]

Improving green economic efficiency (GEE) contributes to the sustainable development of China's economy. The market-oriented reform of fossil energy prices is yet incomplete, resulting in distortions which have significant implications for China's GEE. This study measures different types of fossil energy price distortions and GEE based on panel data, and also analyzes how these fossil energy price distortions affect GEE using the System-GMM model. Additionally, potential influencing mechanisms are explored. The main results show that (1) all fossil energy prices are distorted, with coal and oil having larger distortions. Additionally, regional energy price distortions are characterized as low in eastern China and high in the central and western regions. (2) Fossil energy price distortions exhibit significant negative impacts on GEE from a national perspective. The sub-group analysis also shows negative effects on GEE but different regions have heterogeneous impacts. (3) Mechanism analysis illustrates that negative fossil energy price distortions further hinder GEE by inhibiting technological innovation and impeding the optimization of the energy consumption structure. It is necessary to improve market-based energy pricing mechanism and develop differentiated regional energy pricing policies for the realization of China's green economy. • Different types of fossil energy price distortions are measured. • Green economic efficiency (GEE) of provinces in China is calculated. • Energy price distortions negatively affect GEE at both national and regional levels. • Fossil energy price distortions exhibit heterogeneous effects on regional GEE. • The influencing mechanisms of energy price distortions are further explored. [ABSTRACT FROM AUTHOR]

In the recent years, the existence of a large amount of old residential neighborhoods has become the concentrated expressions of the unbalanced development in China. The studies related to neighborhood renewal are mostly focused on its renewal methods and contents. However, to make a significant contribution to the long-term neighborhood development, sustainable renewal for the old residential neighborhoods is crucial. This study aims to identify critical barriers to sustainable neighborhood renewal in China and explore their related interactive mechanisms. To this end, 19 barriers were identified from comprehensive literature review and interviews with the experts. The relationships between the barriers are testified by fuzzy-DEMATEL method. The results revealed thirteen critical barriers, and among which lack of effective supporting policies is considered as the root cause of unsustainable neighborhood renewal. Besides, lack of public-private corporation mechanism, unequal and opaque information between stakeholders, lack of public participation, low profits of the private sectors, and immature law and regulations are all proved to be important causes. Accordingly, proper countermeasures are suggested to be adopted for future neighborhood renewal projects with the identified influencing paths. The study provides a theoretical basis and approach to prevent unsustainable renewal and pursuit of sustainable development in old neighborhoods. • Barriers to sustainable renewal of old neighborhood in China are identified. • A fuzzy-DEMATEL method is developed to explore the causality and influencing mechanism between identified barriers. • Lack of effective supporting policies is proved to be the root cause of unsustainable neighborhood renewal. • Suggestions to improve sustainability of ONR are provided. [ABSTRACT FROM AUTHOR]