This　paper　investigates　the　time　lag　effect　of　carbon　emissions　using　a　novel　temporal　input-output　approach　(TIO).　The　sectoral　average　production　time　of　various　sectors　is　evaluated　based　on　the　turnover　rate　data　of　3394　listed　companies　in　China　&　rsquo;s　A-share　market.　Then,　a　polynomial　function　is　developed　to　fit　the　indirect　carbon　emissions　and　time　lag　at　each　consumption　stage　in　the　industrial　chains.　Finally,　an　empirical　study　is　carried　out　to　forecast　the　time　lag　effect　of　carbon　emissions　with　final　demand　fluctuations　based　on　the　latest　2017　input-output　table　for　China.　The　results　show　that　indirect　carbon　emissions　caused　by　sectoral　economic　activities　decline　stage　by　stage　in　the　industrial　chains,　and　the　decline　rate　and　time　lag　intensity　vary　significantly　among　sectors.　The　logistics　industry　has　the　highest　spread　efficiency　for　indirect　carbon　emissions　in　the　industrial　chains,　and　the　con-struction　industry　is　the　first　industry　affected　by　the　indirect　carbon　emissions　caused　by　the　manufacturing　industry.　The　power/thermal　industry　&　rsquo;s　impact　on　China　&　rsquo;s　carbon　emissions　is　the　fastest,　but　its　duration　is　the　shortest,　while　the　impact　of　the　manufacturing　and　mining　industries　are　more　stable　and　durable.　However,　considering　the　fluctuations　in　final　demand,　the　manufacturing　industry　has　replaced　the　power/thermal　industry　as　the　most　important　industry　affecting　the　time　lag　effect　of　China　&　rsquo;s　carbon　emissions.　This　study　provides　important　theoretical　and　practical　value　for　indirect　carbon　emissions　forecasting.　(c)　2021　Elsevier　Ltd.　All　rights　reserved.