Beijing-Tianjin-Hebei　Economic　Zone　is　one　of　the　most　polluted　areas　in　northern　China.　In　recent　years,　pollution　has　become　one　of　the　most　severe　the　environmental　problems　in　that　region,　posing　huge　impact　on　the　urban　traffic　and　threatening　the　public　health　greatly.　Understanding　the　spatio-temporal　variability　and　their　mechanisms　is　important　for　the　monitoring　and　control　of　regional　air　pollution.　This　study　employed　the　Mann-Kendall　test,　statistical　methods,　geographical　spatial　analysis,　aiming　to　explore　the　characteristics　of　air　quality　and　its　main　controlling　factors　in　this　region.　Temporal　analysis　was　conducted　in　four　largest　cities　to　indicate　the　variation　trend　of　air　quality　and　identify　the　influence　of　meteorological　factors,　while　spatial　analysis　was　conducted　based　on　all　13　cities　of　the　region　to　clarify　the　socioeconomic　controls　on　air　quality.　The　results　from　trend　analysis　indicate　an　improving　trend　in　air　quality.　Temperature,　air　pressure　and　wind　speed　are　the　main　meteorological　factors　controlling　air　quality　in　the　four　large　cities,　which　impose　important　influence　on　the　migration,　diffusion　or　settlement　of　pollutants.　Agglomeration　degree　and　distribution　characteristics　of　AQI　and　six　pollutants　show　great　spatial　heterogeneity,　which　is　determined　by　topography,　land-sea　position,　physicochemical　properties　of　pollutants　and　socioeconomic　factors.　Principal　component　analysis　(PCA)　indicate　that　economic　development　benefits　the　improvement　of　air　quality,　while　industrialization　and　traffic　construction　aggravate　air　pollution.　The　air　quality　is　less　dependent　on　the　level　of　urbanization.　About　55　%　of　the　spatial　AQI　changes　can　be　explained　by　the　socioeconomic　factors,　suggesting　the　leading　contribution　of　human　activities　to　air　quality.　This　study　will　help　deeply　understand　the　main　sources　of　air　pollution　in　Beijing-Tianjin-Hebei　region,　and　provides　insights　for　urban　planning　and　rational　policy　formulation　that　are　conducive　to　air　pollution　control.