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Urban agglomeration, which is an organism with distinct organizational characteristics, differs from a single city. In its policy-level environmental impact assessment, the ecological and health risks need to be addressed in a unified manner, because multiple cities interact and influence each other, and the environmental risks have multiple elements, multiple processes, and multiple effect interaction and superposition. To this end, this study proposed a regional-level cumulative risk assessment framework coupling a relative risk model (RRM) with a multi-media fugacity model (MFM). The RRM translated the risk causal relations into four city-differentiated matrices, which consisted of normalized factors (NFs), ranging from 0 to 1, that were indicative of the impact intensity and possibility. The MFM was embedded into the RRM to generate the NFs. The NFs were multiplied for each city-source-endpoint combination to get the overall risk score, and the score provided policy references. This framework was applied to Guangdong Province of China (GD). As heavy metal contamination is one of the GD's major concerns, this study analyzed their cumulative risks due to industrialization for the year 2020 and compared the city level and industrial level risk scores. The results showed that the central part of GD was under the highest risk, with Guangzhou, Foshan, and Jiangmen having the highest risk. From the perspective of the risk pressure sources, Pb and Cd were the biggest stressors. Non-ferrous/ferrous metals mining and processing and metal products manufacturing were the major threats. As these industries gain greater footholds in the GD's ecologically susceptible region, the relevant policies should be elaborately designed before new entrants commence their operations. • Fugacity simulation was integrated into a relative risk model for city cluster planning. • The risk ranking rationale was increased by considering the chemical multi-media persistency. • Step-by-step analysis was conducted of the regional long-term environmental risks. • Comparable risk scores among cities/industries were generated for policy references. [ABSTRACT FROM AUTHOR]