In environmental epidemiological research, extensive non-random environmental exposures and complex confounding biases pose significant challenges when attempting causal inference. In recent years, the introduction of causal inference methods into observational studies has provided a broader range of statistical tools for causal inference research in environmental epidemiology. The instrumental variable (IV) approach, as a causal inference technique for effectively controlling unmeasured confounding factors, has gradually found application in the field of environmental epidemiological research. This article reviewed the basic principles of IV and summarized the current research progress and limitations of applying IV for causal inference in environmental epidemiology. IV application in the field of environmental epidemiology is still in the initial stage. Rational use of IV and effective integration with other causal inference methods will become the focus of the development of causal inference in environmental epidemiology. The aim of this paper is to provide a methodological reference and basis for future studies involving causal inference to target population health effects of environmental exposures in China.