The　industry　sector　is　not　only　an　important　driving　force　for　economic　growth　but　also　the　largest　sector　of　resource　consumption　and　pollution　emission.　In　this　study,　we　first　constructed　a　super-slack-based　measure　(Super-SBM)　model　including　the　resource　consumption　and　undesirable　outputs,　and　estimated　the　industrial　environmental　efficiency　(IEE)　in　China　from　2007　to　2016.　Afterwards,　based　on　the　spatial　autocorrelation　test　and　the　spatial　Durbin　model,　the　spatio-temporal　evolution　and　the　influencing　factors　of　IEE　were　analyzed.　The　empirical　results　are　obtained　as　follows:　the　average　IEE　from　2007　to　2016　was　0.5176.　IEE　in　the　east　of　China　was　the　highest,　whereas　it　was　the　lowest　in　the　west.　The　spatial　autocorrelation　test　showed　that　the　regions　with　similar　levels　of　IEE　in　China　had　significant　spatial　agglomeration,　whereas　the　local　spatial　distribution　of　IEE　was　unbalanced.　The　high-high　IEE　agglomeration　areas　were　located　in　Liaoning,　Jilin,　and　Inner　Mongolia.　The　low-low　IEE　agglomeration　areas　were　concentrated　in　Gansu,　Ningxia,　and　Sichuan.　Finally,　according　to　the　spatial　Durbin　panel　model　and　spillover　effect　decomposition,　GDP,　FDI,　human　capital,　environmental　governance　investment,　research　and　development　investment,　and　urbanization　have　a　positive　impact　on　IEE.　The　industrial　and　energy　consumption　structures　have　a　negative　impact　on　IEE.　Therefore,　the　central　government　should　focus　on　balancing　IEE　of　different　provinces　and　regions,　increasing　investment　in　industrial　pollution　treatment,　and　encouraging　FDI　to　improve　IEE.