The influence of renewable energy integration and service value-added on carbon dioxide emissions in China

Renewable energy is the key factor in limiting carbon intensity and mitigating climate change. The present study examines the effect of economic growth (Y, GDP), service sector (SVA), and renewable and non-renewable energy consumption (RE, NRE) on environmental quality (CO₂, E) and the dynamic interdependence among them for China spanning the period 1980–2021 using the linear and non-linear autoregressive distributed lags (ARDL, NARDL) techniques. Granger causality tests are employed to check for causalities among the underlying variables. The main results showed for the ARDL model the existence of unidirectional causality from GDP to SVA and bidirectional causality between RE and NRE and RE and CO₂ in the short term. However, there is no short-run causality between NRE, E, GDP, and SVA. According to the NARDL, the results of the empirics mentioned a one-way causality running from RE⁺ to all the variables and a one-way causality from SVA to RE⁺. Granger shows bidirectional causality between RE⁺ and CO₂ and between RE⁺ and NRE in the short run. Nevertheless, a negative shock in renewable energy negatively affects CO₂ emissions in the long term. China's policymakers will increase the share of non-fossil fuels in primary energy and invest more technology in the service sector, including buildings and transport. To reduce environmental pollution, the government, policymakers, and regulatory agencies will place more of their attention on less energy-intensive and polluting industrial output, moving from more polluting activities to a less polluting services sector. As a result, mitigating climate change.