In the “full world” and Anthropocene, global ecological consumption is beyond natural capital’s regenerative and absorptive abilities, and ecological consumption of humanity has to be reduced to have an ecologically sustainable future. To achieve the goal of ecological sustainability, influencing factors that could reduce ecological consumption need to be explored. Based on three panel datasets for the time period 1996–2015, this paper estimates the impacts of urbanization, renewable energy consumption, service industries, and internet usage on ecological consumption for all 90 sample countries, the 42 developed countries, and the 48 developing countries. Education and income are taken as control variables in the panel regressions. As a consumption-side indicator, the ecological footprint is selected to measure ecological consumption. The estimations find that (1) urbanization has negative impacts for all sample countries and the developed countries, and it is insignificant for the developing countries, (2) renewable energy consumption and service industries have negative impacts for all of the three samples, and (3) internet usage has lagged negative impacts for all sample countries, and it is an independent and significant force of reducing ecological consumption in the developing countries rather than the developed countries. It is found that there is a positive linear relationship, an inversed U-shaped relationship, and a U-shaped relationship between ecological consumption and income in all sample countries, the developed countries, and the developing countries, respectively. The estimated results provide guidance for evidence-based policymaking on reducing ecological consumption.

Based on the grain production data of the counties (cities, districts) in Poyang Lake Basin, this paper uses the productivity index of Epsilon Based Measure of Malmquist Luenberger (EBM-ML Index) to analyse the green total factor productivity (GTFP) of grain in Poyang Lake Basin. Kernel density function and Markov analysis are used to discuss the dynamic evolution process of the distribution of GTFP of grain. The results show the following: (1) From the time dimension, the GTFP of grain is on the rise and fluctuates more frequently from 2001 to 2017, and its trend of change is determined by the combination of technical efficiency and technological progress. Moreover, from a spatial dimension, the number of counties (cities, districts) with GTFP of grain greater than 1.0 has shown an overall increase, indicating that the overall level of GTFP of grain is increasing. (2) According to the kernel density estimation results, the crest of the main peak of the kernel density curve corresponding to the GTFP of grain in Poyang Lake Basin shifts to the right, and the area formed by the right part of the GTFP of grain corresponding to the crest of the main peak of its kernel density curve gradually increases. The peak of the kernel density curve changes from “multi-peak mode” to “single-peak mode,” and the height of the main peak of the kernel density curve of GTFP of grain shows an overall decrease. Meanwhile, the right tail of the kernel density curve shows an overall extending trend. (3) According to the estimation results of the Markov chain, the GTFP of grain in Poyang Lake Basin is highly mobile from 2001 to 2017, and the counties (cities, districts) have a certain degree of agglomeration in the low, medium-low, medium-high and high levels. In other words, the long-term equilibrium state of growth of GTFP of grain remains dispersed in the state space of four level types, indicating that the divergence state of GTFP of grain in counties (cities, districts) of Poyang Lake Basin will continue for a long time in the future. The study reveals the evolution and dynamic change of GTFP of grain in Poyang Lake Basin, which has important theoretical significance and practical value for optimizing the spatial pattern and realizing the balanced development of GTFP among counties (cities, districts) of Poyang Lake Basin and consolidating China’s food security strategy.

Global material consumption needs to be reduced to be within its planetary boundary. Urbanization and human inequality are two profound economic-social phenomena, which have potential impacts on material consumption. This paper aims to empirically explore how urbanization and human inequality affect material consumption. For this aim, four hypotheses are proposed and the coefficient of human inequality and material footprint per capita are employed to measure comprehensive human inequality and consumption-based material consumption, respectively. Based on an unbalanced panel data set of around 170 countries from 2010 to 2017, the regression estimations demonstrate that: (1) urbanization reduces material consumption; (2) human inequality increases material consumption; (3) the interaction effect between urbanization and human inequality reduces material consumption; (4) urbanization reduces human inequality, which explains why the interaction effect works; (5) urbanization makes more sense for reducing material consumption if the extents of human inequality are larger and the positive impacts of human inequality on material consumption are weakened if the extents of urbanization are larger. It is concluded that promoting urbanization and reducing human inequality are compatible with both ecological sustainability and social fairness. This paper contributes to understanding and achieving the absolute decoupling between economic-social development and material consumption.

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