Production–living–ecological space (PLES) is a recent research hotspot on land planning and regional sustainable development in China. Taking the Yangtze River Delta agglomerations as a case study, this paper establishes a spatial-conflict index to identify the PLES conflicts, and then builds a cellular-automaton (CA) Markov model to simulate the PLES pattern in 2030 and to evaluate the influence on PLES conflicts under two scenarios. Results showed that the ecological space (ES) and the living–productive space (LPS) of the Yangtze River Delta agglomerations showed a descending tendency in 2010–2015, whereas ecological–productive space (EPS) and productive–ecological space (PES) reflected a small increase. EPS and PES had squeezed ES and LPS with urbanization and industrial development in this region. Meanwhile, the spatial conflicts of PLES worsened during the period, with the average of the spatial-conflict index (SCI) shifting from 0.283 to 0.522, and seemed to gain momentum. On the basis of scenario analysis for 2030, it was concluded that the “ecological red line policy”, appropriate restriction of urban expansion, and ecological management of the bank of the Yangtze River are helpful in alleviating PLES conflicts, and contribute to spatial structure and harmonizing. The results of this study are expected to provide valuable implications for spatial planning and sustainable development in the Yangtze River delta agglomerations.

In the pursuit of China’s dual carbon goals, identifying spatio-temporal changes in industrial carbon emission efficiency and their influencing factors in cities at different stages of development is the key to effective formulation of countermeasures to promote the low-carbon transformation of Chinese national industry and achieve high-quality economic development. In this study, we used balanced panel data of 270 Chinese cities from 2005 to 2020 as a research object: (1) to show spatio-temporal evolution patterns in urban industrial carbon emission efficiency; (2) to analyze the aggregation characteristics of industrial carbon emission efficiency in Chinese cities using Global Moran’s I statistics; and (3) to use the hierarchical regression model for panel data to assess the non-linear impact of the digital economy on the industrial carbon emission efficiency of cities. The results show the following: (1) the industrial carbon emission efficiency of Chinese cities exhibited an upward trend from 2005 to 2020, with a spatial distribution pattern of high in the south and low in the north; (2) China’s urban industrial carbon emission efficiency is characterized by significant spatial autocorrelation, with increasing and stabilizing correlation, and a relatively fixed pattern of spatial agglomeration; (3) there is a significant inverted-U-shaped relationship between the digital economy and the industrial carbon emission efficiency of cities. The digital economy increases carbon emissions and inhibits industrial carbon emission efficiency in the early stages of development but inhibits carbon emissions and promotes industrial carbon emission efficiency in mature developmental stages. Therefore, cities at all levels should reduce pollution and carbon emissions from high-energy-consuming and high-polluting enterprises, gradually reduce carbon-intensive industries, and accelerate the digital transformation and upgrading of enterprises. Western, central, and eastern regions especially should seek to promote the sharing of innovation resources, strengthen exchanges and interactions relating to scientific and technological innovation, and jointly explore coordinated development routes for the digital economy.

Urban development and coal extraction have caused conflicts regarding production, living, and ecological lands in the Yellow River basin. Here, a coupled genetic algorithm–patch generating land use simulation InVEST model was constructed to optimize land use/land cover (LULC) and simulate carbon storage changes. This study shows that the LULC changed dramatically from 2010 to 2020 in an area that accounts for 31.96% of the area of the Yellow River basin. Inappropriate land use conversion and encroachment have reduced carbon storage by 2.92 × 10⁶ t, destroying the stability of the ecosystem. The development of cities has encroached on cultivated land, which may have affected the region’s food security. Following LULC optimization, ecological and cultivated lands are gradually being restored, and the transition between the different lands tends to be orderly, resulting in an increase of 24.84 × 10⁶ t in carbon storage. The relationship between LULC and carbon storage shows that the high carbon intensity of woodland, grassland, and cultivated land is crucial to ensuring regional carbon balance. For the Yellow River basin, necessary environmental protection measures are the key to achieving high-quality economic development. This study can provide guidance for decision-makers in formulating ecosystem restoration plans.

Influenced by historical background, regional economic development, and the frequent occurrence of armed conflict, the human–earth relationship in the Central and Southern Peninsula, which is located in a “fragmented zone”, is characteristic of the region. The Indochina Peninsula has now become an area of interest for the study of spatial changes in production–living–ecological spaces (PLES). Taking the Indochina Peninsula as the study area, this paper explores the evolution of the spatiotemporal patterns of PLES and its driving mechanism in the Indochina Peninsula, from 2010 to 2020, based on a grid scale. Methods such as the land-use transition matrix, land-use dynamics index, and geographically and temporally weighted regression (GTWR) were used in our model, which will provide the basic data and reference for sustainable development planning across the Indochina Peninsula. Our results show that, from 2010 to 2020, ecological space dominated the PLES pattern on the Indochina Peninsula, but its area gradually decreased, accompanied by a sharp increase in the areas of productive and living spaces. The area of PLES interconversion on the Indochina Peninsula in 2010–2020 was 212,818.70 km², and the intertransfer of production and ecological spaces was distributed in a networklike manner throughout the Indochina Peninsula, while the transfer of living space was distributed in a pointlike manner. The migration path of the center of gravity of PLES on the Indochina Peninsula demonstrated a significant directional difference, and the direction and extent of the standard deviation ellipse distribution of the ecological space was similar to that of the production space. The PLES’s pattern evolution was affected by the degree of multiple factors, with a significant spatial and temporal heterogeneity. The positive and negative feedback effects of the factors were distributed in different areas and in different transfer directions.

The enormous potential of the photovoltaic (PV) sector has aided in the faster attainment of China's “dual-carbon” aim. However, due to a scarcity of land resources and intermittent fluctuations in solar energy, it has been difficult to build large-scale PV bases, and existing PV systems also suffer from unstable power generation and seasonal fluctuations and are unable to be directly connected to the grid for use. However, abandoned mines with huge surface collapse zones and a large underground mining area offer a potential possibility for constructing photovoltaic-pumped hydro storage (PV-PHS) systems and limiting PV variations. Based on the abandoned mine pumbed hydro storage (AMPHS) potential assessment model and the optimized discrete wavelet decomposition algorithm, this study proposes a dynamic cycle optimization method for the PHS regulation capacity in an abandoned mine PV-PHS hybrid system. This approach is able to determine the optimal regulation capacity of AMPHS on a daily scale while limiting the volatility of the PV-PHS hybrid system. The method was applied to an abandoned mine PV-PHS hybrid system in Zaozhuang City, Shandong Province, and the optimal regulation capacity of the AMPHS was determined to be 88 MWh and 100 % elimination of PV generation volatility was achieved. This also reduces the economic cost by roughly 1.94 × 10⁸ CNY. In addition, it is possible to store an average of 2.32 % of the PV power generated and to extend the power generation time by approximately 2.5 h per day. This research is critical for boosting the resource use of abandoned mines, and establishing the comprehensive usage model of new energy and abandoned mine resources.

In the pursuit of China’s dual carbon goals, identifying spatio-temporal changes in industrial carbon emission efficiency and their influencing factors in cities at different stages of development is the key to effective formulation of countermeasures to promote the low-carbon transformation of Chinese national industry and achieve high-quality economic development. In this study, we used balanced panel data of 270 Chinese cities from 2005 to 2020 as a research object: (1) to show spatio-temporal evolution patterns in urban industrial carbon emission efficiency; (2) to analyze the aggregation characteristics of industrial carbon emission efficiency in Chinese cities using Global Moran's I statistics; and (3) to use the hierarchical regression model for panel data to assess the non-linear impact of the digital economy on the industrial carbon emission efficiency of cities. The results show the following: (1) the industrial carbon emission efficiency of Chinese cities exhibited an upward trend from 2005 to 2020, with a spatial distribution pattern of high in the south and low in the north; (2) China's urban industrial carbon emission efficiency is characterized by significant spatial autocorrelation, with increasing and stabilizing correlation, and a relatively fixed pattern of spatial agglomeration; (3) there is a significant inverted-U-shaped relationship between the digital economy and the industrial carbon emission efficiency of cities. The digital economy increases carbon emissions and inhibits industrial carbon-emission efficiency in the early stages of development, but inhibits carbon emissions and promotes industrial carbon emission efficiency in mature developmental stages. Therefore, cities at all levels should reduce pollution and carbon emissions from high-energy-consuming and high-polluting enterprises, gradually reduce carbon-intensive industries, and accelerate the digital transformation and upgrading of enterprises. Western, central and eastern regions especially should seek to promote the sharing of innovation resources, strengthen exchanges and interactions relating to scientific and technological innovation, and jointly explore coordinated development routes for the digital economy.