This paper investigates whether energy consumption, population density, and exports are the main factors causing environmental damage in China. Using annual data from 1971–2018, unit root tests are applied for the stationarity analyses, and Autoregressive Distributed Lag (ARDL) bounds tests are used for the long-run relationships between the variables. A Vector Error Correction Model (VECM) Granger approach is employed to examine the causal relationships amongst the variables. Our findings show that the selected variables are cointegrated, and that energy consumption and economic growth are identified as the main reasons for CO2 emissions in both the shortrun and long-run. In contrast, exports reduce CO2 emissions in the long-run. Short-run unidirec-tional Granger causality is found from economic growth to energy consumption, CO2 emissions and exports, and from CO2 emissions to energy consumption and exports. Moreover, long-run causal links exist between CO2 emissions and exports. Five policy recommendations are made following the obtained results.