Environmental　impact　assessment　(EIA)　problems　are　often　characterised　by　a　large　number　of　identified　environmental　factors　that　are　qualitative　in　nature　and　can　only　be　assessed　on　the　basis　of　human　judgments,　which　inevitably　involve　various　types　of　uncertainties　such　as　ignorance　and　fuzziness.　So,　EIA　problems　need　to　be　modelled　and　analysed　using　methods　that　can　handle　uncertainties.　The　evidential　reasoning　(ER)　approach　provides　such　a　modelling　framework　and　analysis　method.　In　this　paper　the　ER　approach　will　be　applied　to　conduct　EIA　analysis　for　the　first　time.　The　environmental　impact　consequences　are　characterized　by　a　set　of　assessment　grades　that　are　assumed　to　be　collectively　exhaustive　and　mutually　exclusive.　All　assessment　information,.　quantitative　or　qualitative,　complete　or　incomplete,　and　precise　or　imprecise,　is　modelled　using　a　unified　framework　of　a　belief　structure.　The　original　ER　approach　with　a　recursive　ER　algorithm　will　be　introduced　and　a　new　analytical　ER　algorithm　will　be　investigated　which　provides　a　means　for　using　the　ER　approach　in　decision　situations　where　an　explicit　ER　aggregation　function　is　needed　such　as　in　optimisation　problems.　The　ER　approach　will　be　used　to　aggregate　multiple　environmental　factors,　resulting　in　an　aggregated　distributed　assessment　for　each　alternative　policy.　A　numerical　example　and　its　modified　version　are　studied　to　illustrate　the　detailed　implementation　process　of　the　ER　approach　and　demonstrate　its　potential　applications　in　EIA.　(c)　2005　Elsevier　B.V.　All　rights　reserved.