The　rapidly-increasing　urban　transportation　contributes　to　a　number　of　externalities　such　as　congestion　and　pollution;　moreover,　environmental　uncertainties　widely　exist　and　bring　challenges　to　creating　traffic　emission　control　strategies.　To　address　these　problems,　this　paper　proposes　an　inexact　bilevel　programming　approach　under　stochastic　and　fuzzy　uncertainties　(BLP-SF)　for　a　toll　scheme　design　with　the　considerations　of　the　externalities　of　vehicular　emission　and　road　pricing　policy.　The　BLP-SF　approach　can　deal　with　multiple　environmental　uncertainties　by　(1)　specifying　the　uncertainties　as　probability　distributions　and/or　fuzzy　sets,　and　(2)　integrating　chance-constrained　programming　and　fuzzy　possibility　programming　into　the　bilevel　programming　framework.　A　road　pricing　problem　is　exemplified　under　various　policy　scenarios　to　demonstrate　the　applicability　of　the　BLP-SF　approach.　It　is　shown　that　the　proposed　BLP-SF　approach　can　achieve　optimal　charging　schemes　with　improvements　in　total　emission　reduction　and　congestion　alleviation　compared　with　traditional　models.　This　study　contributes　to　urban　transportation　management　associated　with　congestion　and　emission.