Spatiotemporal dynamic decoupling states of eco-environmental quality and land-use carbon emissions: A case study of Qingdao City, China

Abstract

Spatiotemporal dynamic association between eco-environmental quality and land-use carbon emissions (LCE) is an indispensable part of regional and city planning and land management and a necessary condition for maintaining sustainable development. With the increasing awareness of the importance of sustainable development, quantifying the relationship between eco-environmental quality and LCE needs to be improved. Based on raster datasets of carbon emissions from fossil fuels, remotely sensed environmental variables, and land-use and land-cover change, this study aimed to combine an improved model of LCE, remote sensing ecological index (RSEI), and decoupling theory along with the help of the Google Earth Engine (GEE) and geographical information system platforms to explore the spatiotemporal patterns and trends of the eco-environmental quality and LCE over Qingdao City in the coastal economic belt of China for 2005–2019. There are three significant findings in this study. First, during 2005–2019, RSEI in the study area showed an overall upward trend (0.4365 in 2005 and 0.5378 in 2019), with a significant difference in the spatial distribution. Second, during 2005–2019, the total LCE value showed an increasing trend (4.028 million tonnes (Mt) in 2005 and 7.929 Mt. in 2019), with the study area acting as a carbon source. Third, the study area exhibited the four decoupling states of mainly weak decoupling (WD), expansive negative decoupling (END), strong decoupling (SD), and strong negative decoupling (SND). Finally, space management policies should be formulated based on different spatiotemporal characteristics and decoupling states to achieve carbon emission reductions and high-quality development.