A　Gaussian-box　modeling　approach　was　presented　in　this　paper　to　examine　the　urban　air　quality　due　to　multiple　point-　and　area-source　emissions　in　the　northern　Chinese　city　of　Fengnan,　which　is　associated　with　a　deteriorated　air　quality　as　a　consequence　of　industrialization　and　rapid　urban　growth.　A　3-D　multi-box　(3DMB)　air　quality　model　was　developed　to　predict　air　quality　due　to　area-source　emissions.　It　improved　upon　the　conventional　box　models　by　allowing　consideration　of　more　details　in　spatial　variations　of　emission　sources　and　meteorological　conditions.　The　modeling　domain　was　divided　into　various　layers　within　the　mixing　height,　while　each　layer　was　associated　with　a　number　of　sub-boxes.　A　multi-source　and　multi-grid　Gaussian　modeling　approach　was　then　applied　to　predict　the　air　quality　in　different　sub-boxes　that　are　associated　with　multiple　point-source　emissions.　Thus　the　Gaussian-box　modeling　approach　could　effectively　simulate　impacts　of　both　area-　and　point-source　emissions　but　also　reflect　more　details　of　the　spatial　variations　in　source　distributions　and　meteorological　conditions.　This　modeling　approach　was　employed　to　predict　daily　average　SO2,　TSP　and　PM10　concentrations　for　each　sub-box　during　the　heating　and　non-heating　seasons,　respectively.　The　analysis　of　the　mean　normalized　error　of　the　modeling　results　demonstrates　the　feasibility　and　applicability　of　the　developed　method,　and　the　presented　method　could　provide　more　useful　and　scientific　bases　for　developing　effective　urban　air　quality　control　and　management　strategies.