What drives the change in China's provincial industrial carbon unlocking efficiency? Evidence from a geographically and temporally weighted regression model.

In this paper, we propose the concept of carbon unlocking efficiency based on carbon lock-in. Supported by the "Techno-Institutional Complex" theory, we measure the industrial carbon unlocking efficiency (ICUE) of 30 Chinese provinces and analyze its spatial and temporal jump probabilities through spatial Markov chains, and finally identify and discuss the influencing factors through the GTWR model. We found that the ICUE of each province in China follows a decreasing distribution from east to central to west, with Shanghai, Beijing, and Guangdong having the highest ICUEs among all provinces and cities; although the overall ICUE converges to a higher level in the long run, there is still a certain predatory effect of developed regions on less developed regions in the short term, and the intensification of market competition may adversely affect the growth of ICUE in the lagging regions.

Coupling coordination degree and driving factors of new-type urbanization and low-carbon development in the Yangtze River Delta: based on nighttime light data.

The coordination relationship between new-type urbanization and urban low-carbon development under the goal of carbon neutrality has become a hot issue that needs to be focused on when formulating policies. Based on the estimation of urban CO emissions by night light data, this study used spatial autocorrelation, spatial Markov chain and geographically weighted regression model to measure the spatial correlation and spillover effects of the coupling coordination degree of two systems in the Yangtze River Delta urban agglomeration from 2005 to 2018 and analyzed the influencing factors. The results showed that (1) the coupling coordination degree showed an increasing trend, but the club effect was quite obvious, and the regional pattern was higher in southeast and lower in northwest; (2) the spatial spillover effect of coupling coordination degree is significant, which aggravates the long-term persistence of the imbalance pattern; (3) regional economic level, government fiscal regulation, and industrial upgrading are the main driving forces for the increase of coupling coordination degree, while over-concentration of population and low energy efficiency are the main obstacles.

Enhanced dewaterability of waste-activated sludge with zero-valent iron-activated persulfate oxidation under mild hydrothermal conditions.

A novel technique to enhance sludge dewaterability with zero-valent iron-activated persulfate (ZVI/PDS) and hydrothermal treatment (HT) under mild temperature is proposed in this study. Key operating parameters were considered to study their influences on the dewaterability of sludge. Comparative studies of organic matter, especially extracellular polymeric substances (EPS), were analyzed carefully to reveal the mechanisms involved.

Spatio-Temporal Effects of Multi-Dimensional Urbanization on Carbon Emission Efficiency: Analysis Based on Panel Data of 283 Cities in China.

Under the influence of complex urbanization, improving the carbon emission efficiency (CEE) plays an important role in the construction of low-carbon cities in China. Based on the panel data of 283 prefectural-level cities in China from 2005 to 2017, this study evaluated the CEE by the US-SBM model, and explored the spatial agglomeration evolution characteristics of CEE from static and dynamic perspectives by integrating ESDA and Spatial Markov Chains. Then, the spatial heterogeneity of the impacts of multi-dimensional urbanization on CEE were analyzed by using the Geographically and Temporally Weighted Regression (GTWR).

Exploring the Dependence and Influencing Factors of Carbon Emissions from the Perspective of Population Development.

Working towards sustainable population development is an important part of carbon mitigation efforts, and decoupling carbon emissions from population development has great significance for carbon mitigation. Based on the construction of a comprehensive population development index (PDI), this study adopts a decoupling model to explore the dependence between carbon emissions and PDI across 30 Chinese provinces from 2001 to 2017. Then, the stochastic impacts by regression on population, affluence and technology (STIRPAT) model is used to investigate the impact of population factors on carbon emissions.

Impact of uncertainty on regional carbon peak paths: an analysis based on carbon emissions accounting, modeling, and driving factors.

Regional carbon emission paths have an important impact on the realization of China's carbon emission peak target. Due to the uncertainty of future development model, the change of carbon emissions will also face uncertainty, which will make achieving the peak target challenging. Taking Shandong, Henan, and Guangdong, three of China's most populous provinces, as examples, this study analyzed the impacts of uncertainties in carbon accounting principles, driving factors, and simulation mechanism on achieving the peak target.