The　paper　aims　to　investigate　the　influencing　factors　that　drive　the　temporal　and　spatial　differences　of　CO2　emissions　for　the　transportation　sector　in　China.　For　this　purpose,　this　study　adopts　a　Logistic　Mean　Division　Index　(LMDI)　model　to　explore　the　driving　forces　of　the　changes　for　the　transport　sector＇s　CO2　emissions　from　a　temporal　perspective　during　2000-2017　and　identifies　the　key　factors　of　differences　in　the　transport　sector＇s　CO2　emissions　of　China＇s　15　cities　in　four　key　years　(i.e.,　2000,　2005,　2010,　and　2017)　using　a　multi-regional　spatial　decomposition　model　(M-R).　Based　on　the　empirical　results,　it　was　found　that　the　main　forces　for　affecting　CO2　emissions　of　the　transport　sector　are　not　the　same　as　those　from　temporal　and　spatial　perspectives.　Temporal　decomposition　results　show　that　the　income　effect　is　the　dominant　factor　inducing　the　increase　of　CO2　emissions　in　the　transport　sector,　while　the　transportation　intensity　effect　is　the　main　factor　for　curbing　the　CO2　emissions.　Spatial　decomposition　results　demonstrate　that　income　effect,　energy　intensity　effect,　transportation　intensity　effect,　and　transportation　structure　effect　are　important　factors　which　result　in　enlarging　the　differences　in　city-level　CO2　emissions.　In　addition,　the　less-developed　cities　and　lower　energy　efficiency　cities　have　greater　potential　to　reduce　CO2　emissions　of　the　transport　sector.　Understanding　the　feature　of　CO2　emissions　and　the　influencing　factors　of　cities　is　critical　for　formulating　city-level　mitigation　strategies　of　the　transport　sector　in　China.　Overall,　it　is　expected　that　the　level　of　economic　development　is　the　main　factor　leading　to　the　differences　in　CO2　emissions　from　a　spatial-temporal　perspective.