A Review of Environmental Quality Studies in China’s Petrochemical Port Cities Driven by a Semantic Ontology Data Model

Petrochemical port cities in China face the challenge of promoting industrial development and improving environmental quality. In this situation, this paper constructs a semantic ontology-based data model from the perspective of the overall classification of environmental factors to review the environmental quality of the last three years in seven major petrochemical port cities in China. The process includes three stages. Firstly, the information sources were identified, and the research team collected and screened 1858 related papers from Web of Science and the China National Knowledge Infrastructure according to the theme of the review. Secondly, the information preprocessing was carried out, and the selected literature was sorted and filtered according to different cities and environmental elements. Finally, the research team established semantic ontology data models for the atmosphere, water, soil, biology, and acoustics environment based on the preprocessed information through visualization analysis. By using these models, the research team analyzed the hotspots of pollutants and pollution sources research in different cities in various environmental domains and summarized the main pollution mitigation measures highlighted in the research. In this way, the systematic bias and structural problem of the existing environmental study were revealed. Based on the above results, the targeted governance strategies were proposed to provide theoretical support for promoting coordinated industrial and environmental development in China’s petrochemical port cities.