Efficient　allocation　of　carbon　dioxide　(CO　2　)　emissions　allowances　is　essential　to　the　realization　of　the　emissions　reduction　goal.　Using　China　as　an　example,　this　study　applies　a　zero　sum　gains–data　envelopment　analysis　(ZSG-DEA)　model　to　translate　the　country＇s　reduction　target　into　provincial　goals　based　on　the　Chinese　government＇s　2020　reduction　goal.　To　evaluate　efficiency　scores,　we　employ　the　Epsilon-based　measure　model　that　combines　radial　and　non-radial　characteristics.　Different　from　prior　studies,　we　emphasize　the　effect　of　industrial　structure　on　CO　2　emissions　and　calculate　a　composite　gross　domestic　product　(GDP)　index　as　one　of　the　output　variables.　By　utilizing　the　ZSG-DEA　model　and　based　on　China＇s　provincial　CO　2　emissions　allowances　as　the　input　variable,　the　composite　GDP　index,　and　the　population　as　the　output　variable,　we　obtain　an　optimal　reallocation　scheme　after　four　iterations.　A　comparison　between　the　results　and　official　reduction　goals　shows　that　the　government　should　increase　CO　2　emissions　allowances　appropriately　for　most　provinces　with　high　proportions　(more　than　40%)　of　second　industry　increment　in　GDP,　thereby　carrying　implications　for　policymakers.　With　China　as　an　example,　these　findings　have　global　implications　as　regards　developing　a　more　scientific　allocation　scheme,　especially　for　regions　with　unbalanced　industrial　structures.　©　2019　Elsevier　Ltd