Dynamic early warning of regional atmospheric environmental carrying capacity

Abstract

Economic development cannot exceed the maximum amount that the environment can support. Therefore, atmospheric environmental policy should be formulated based on the scientific assessment of regional atmospheric environmental carrying capacity. The establishment of an early warning model of atmospheric environmental carrying capacity can dynamically analyse regional atmospheric environmental carrying capacity, which contributes to discerning the change trend of the regional atmospheric environmental carrying capacity and the risk issue of the regional atmospheric environment. Additionally, it can provide theoretical reference for the formulation of relevant binding and restrictive policies. In this study, according to the daily monitoring data of atmospheric pollutants, we established a dynamic early warning model of regional atmospheric environmental carrying capacity based on the cloud model and Markov chain. The research results show that this model has an excellent early warning capability. Moreover, many regions in China have exceeded the atmospheric environmental carrying capacity, especially in North China and Central China. By 2020, North China and Central China for prediction of region with non-overloading are only 9.09% and 12.50%, respectively. China's regional atmospheric environmental carrying capacity is gradually improving. It is predicted that by 2024, regions with non-overloading in North China and Central China will reach 40.91% and 37.50%, respectively. From the overall aspect, there is currently no risk of serious overload in any region.

Keywords: Atmospheric environmental carrying capacity; Cloud model; Markov chain; Streaming data.