The　iron　and　steel　industry,　which　discharges　a　large　amount　of　pollutants　including　SO2,　NOx,　and　PM2.5,　is　the　main　source　of　atmospheric　pollution　in　the　Beijing-Tianjin-Hebei　region.　Based　on　the　bottom-up　method,　a　high　temporal　and　spatial　resolution　emission　inventory　of　the　iron　and　steel　industry　in　the　Beijing-Tianjin-Hebei　region　was　developed,　which　took　into　account　the　multiple　air　pollutants　released　during　coking,　sintering,　pelletizing,　ironmaking,　steelmaking,　and　the　steel　rolling　process.　As　the　emission　inventory　showed,　the　total　emissions　of　SO2,　NOx,　TSP,　PM10,　PM2.5,　CO,　and　VOC　from　the　iron　and　steel　industry　in　the　Beijing-Tianjin-Hebei　region　in　2015　were　388.2,　272.3,　791.9,　531.5,　386.8,　8233.8,　and　265.3　kilotons,　respectively,　among　which,　sintering　and　pelletizing　were　the　two　processes　discharging　the　most　pollutants　(17.0%-72.0%),　followed　by　the　ironmaking　process　(4.6%-42.4%)　and　the　steel　rolling　process　(3.5%-35.7%);　the　iron　and　steel　industry　in　Tangshan　discharged　the　most　pollutants　(39.1%-63.5%)　among　those　in　all　the　13　cities.　The　impact　of　the　iron　and　steel　industry　on　the　regional　PM2.5　concentration　was　simulated　by　a　two-layer　nested　meteorology-air　quality　coupling　model　system　(WRF-CMAx)　with　Particulate　Source　Apportionment　Technology　(PSAT).　The　simulation　results　showed　that　the　iron　and　steel　industry　contributed　14.0%,　15.9%,　12.3%,　and　8.7%　of　the　PM2.5　concentrations　of　the　Beijing-Tianjin-Hebei　region　in　spring,　summer,　autumn,　and　winter,　respectively,　and　that　the　iron　and　steel　industry　had　the　most　significant　impact　on　the　PM2.5　concentrations　in　Tangshan　among　all　the　13　cities,　with　a　contribution　rate　up　to　41.2%,　followed　by　those　in　Qinhuangdao,　Shijiazhuang,　and　Handan,　with　contributions　of　19.3%,　15.3%,　and　15.1%,　respectively.　The　iron　and　steel　industry　has　an　important　impact　on　the　PM2.5　concentration　of　the　Beijing-Tianjin-Hebei　region　to　which　the　government　should　pay　more　attention,　and　take　more　effective　control　measures　to　address　this　problem.　©　2018,　Science　Press.　All　right　reserved.