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Over the last three decades, the world has been facing the phenomenon of the ecological deficit as the ecological footprint is continuously rising due to the persistent decline of the per-capita bio-capacity. Moreover, there is a substantial increase in globalization and electricity consumption for the same period, and transportation is contributing to economic prosperity at the cost of environmental sustainability. Understanding the determinants of ecological footprint is thus critical for suggesting appropriate policies for environmental sustainability. As a result, this study analyzes the impacts of economic globalization, transportation, coal rents, and electricity consumption in ecological footprint in the context of the USA over the period 1995 to 2018. The data have been extracted from “Global Footprint Network,” “Swiss Economic Institute,” and “World Development Indicators.” The current study has also applied the flexible Fourier form nonlinear unit root test to examine the stationarity among variables. For the empirical estimation, a novel technique, the “quantile auto-regressive distributive lag model,” is applied in the study to deal with the nonlinear associations of the variables and to evaluate the long-term stability of variables across quantiles. The study’s findings indicate that coal rents, transportation, and globalization significantly and positively contribute to the deterioration of ecological footprints at different quantile ranges in the short and long run. Electricity consumption is found to have a positive and significant impact at lower quantile ranges in the long run but not have a significant impact in the short run. The study suggested that lowering the dependence of the transport sector on fossil fuels, more use of hydroelectricity, and stringent strategies to curb coal consumption would be helpful to reduce the positive influence of these variables on ecological footprints in the USA. Graphical abstract

In order to realize the optimization of urban spatial patterns in the Yellow River Basin, a study on the inefficient use of urban land in the Yellow River Basin was carried out. In this study, Dali County and Hancheng County in Weinan City are selected as the research areas. Firstly, the analytic hierarchy process is used to build a comprehensive evaluation system for the identification of inefficient land in stock; secondly, the standard deviation ellipse method and spatial kernel density estimation method are used to quantitatively analyze the spatial distribution characteristics of inefficient land. Thirdly, the contribution model is used to analyze the influencing factors of inefficient land use. Finally, corresponding redevelopment suggestions are given for each type of inefficient land. The results show that Dali had the smallest area of inefficient land; second is Xincheng Street in Hancheng City; and Longmen Town, Hancheng City has the largest area. The distribution of inefficient land in Dali and Longmen Town in Hancheng City is relatively balanced, while the distribution of all kinds of inefficient land in Xincheng Street in Hancheng City is not concentrated. The density of the road network is the most important contributing factor to inefficient land use in the study area. This paper comprehensively uses the methods of economics and geography to study inefficient land use, quantifies the spatial-temporal characteristics and influencing factors of land use units, explores the spatial patterns of land use and enriches the research into relevant theories.