This　study　explores　the　carbon　emission　reduction　effect　of　the　transportation　structure　adjustment　from　the　perspectives　of　transportation　structure　optimization　and　transportation　mode　shift.　A　multi-objective　optimization　model　of　China＇s　transportation　structure　is　constructed,　and　the　transportation　structure　is　then　adjusted　by　combing　the　multi-objective　particle　swarm　optimization　(MOPSO)　algorithm　and　compromise　programming　technique.　Under　the　premise　of　ensuring　the　economic　and　social　effects,　the　largest　carbon　emission　reduction　effect　of　the　transportation　structure　is　acquired.　The　results　indicate　that　the　transportation　structure　optimization　reduces　carbon　emissions　by　12.70%.　Optimization　in　the　western　region　has　the　largest　carbon　emission　reduction　effect,　followed　by　that　of　the　central　and　eastern　regions.　Furthermore,　the　carbon　emission　reduction　effect　of　the　shift　mode　＂road　to　rail＂　increases　uninhibitedly　with　the　increase　in　the　shift　range.　However,　the　same　effect　of　＂road　to　water＂　has　an　upper　limit.　＂Road　to　rail＂　is　found　to　be　more　effective　in　the　eastern　region,　whereas　＂road　to　water＂　is　more　effective　in　the　central　and　western　regions.