Carbon dioxide emission and climatic variation have a detrimental influence on the atmosphere as well as on agriculture production. The key aim of the present study was to investigate the influence of carbon dioxide emission on livestock, cereal crops production, rainfall, and temperature in China by utilizing the vector autoregressive model and Granger causality test for the period 1988–2017. Variables stationarity was verified by using ADF, P-P, and KPSS unit root tests. The outcomes through long-run dynamics exposed that agriculture value-added and rainfall have a positive influence on carbon dioxide emission, while cereal crops production, livestock production, and temperature have an adverse interaction with carbon dioxide emission. Similarly, the results of the short-run analysis also demonstrate that agriculture value-added, cereal crops production, livestock production, rainfall, and temperature have a significant influence on carbon dioxide emission with their p-values (0.0488), (0.0885), (0.0263), (0.0096) and (0.5141) respectively. Furthermore, the Granger causality test outcomes also exposed a unidirectional linkage amid the variables. In order to improve agricultural productivity, the Chinese government should take potential steps to minimize the carbon dioxide emission from various industries that trigger climate change.