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

China's petrochemical port cities are confronted with the dual challenges of fostering industrial development and enhancing environmental quality. In this context, this paper establishes a semantic ontology-based data model from a comprehensive environmental factor classification perspective to thoroughly review the environmental quality over the past three years in seven major petrochemical port cities in China. The process consists of three main phases: First, information sources were identified, with the research team conducting extensive statistics and screening of 1,858 relevant papers from Web of Science and the China National Knowledge Infrastructure based on the review’s thematic focus. Next, information preprocessing was carried out, in which the selected literature was categorized and filtered according to different cities and environmental elements. Finally, visual analysis was performed using the preprocessed data to construct semantic ontology-based models for the atmospheric, water, soil, biological, and acoustic environments. These models facilitated the identification of research hotspots regarding pollutants and pollution sources across different cities and environmental domains, as well as the extraction of predominant pollution mitigation measures proposed in existing studies. The outcomes provide theoretical support for achieving coordinated development between industry and the environment in petrochemical port cities in China.