Efficiency　evaluation　of　air　pollution　management　is　one　of　China＇s　most　popular　political　concerns.　Many　studies　have　been　devoted　to　developing　an　effective　efficiency　evaluation　model　for　air　pollution　management.　However,　three　challenges　must　be　addressed　and　solved.　First,　previous　studies　treated　air　pollution　data　as　real　numbers　in　efficiency　evaluation.　This　ignored　the　fluidity　and　variability　of　air　pollutants.　Second,　the　indicators　used　in　previous　studies　were　selected　based　on　experts＇　knowledge.　Accordingly,　there　was　information　loss　in　efficiency　evaluation.　Last,　many　factors　can　affect　the　efficiency　evaluation　of　air　pollution　management.　Yet,　previous　studies　neglected　to　evaluate　efficiencies　from　different　perspectives.　To　address　the　challenges　above,　the　interval　data　was　first　used　as　basic　data　to　meet　the　flow　characteristics　of　air　pollution　management.　Next,　the　interval　evidential　reasoning　(IER)　model　and　the　interval　data　envelopment　analysis　(IDEA)　model　were　employed.　Both　models　are　suitable　for　interval　data.　They　were　introduced　to　propose　a　new　efficiency　evaluation　model:　the　IER-IDEA　model.　The　main　aims　of　the　proposed　model　are　twofold:　1)　include　interval　indicator　integration　with　a　new　weight　calculation　method;　and　2)　evaluate　interval　efficiency　from　three　different　perspectives.　To　demonstrate　the　effectiveness　of　the　proposed　IER-IDEA　model,　a　case　study　was　performed　in　29　Chinese　provinces.　Its　purpose　was　to　assess　efficiency　evaluation　of　air　pollution　management.　Experimental　results　demonstrated　that　the　IER-IDEA　model　obtains　desired　efficiencies　of　air　pollution　management　under　the　consideration　of　indicator　integrity,　interval　uncertainty,　and　different　perspectives.　Moreover,　it　can　effectively　distinguish　regional　differences　in　the　efficiency　of　air　pollution　management　compared　to　some　existing　efficiency　evaluation　models.　(C)　2019　Elsevier　Ltd.　All　rights　reserved.