Heavy-duty　diesel　trucks　(HDDTs)　contribute　significantly　to　NOX　and　particulate　matter　(PM)　pollution.　Although　existing　studies　have　emphasized　that　HDDTs　play　a　dominant　role　in　vehicular　pollution,　the　spatial　distribution　pattern　of　HDDT　emissions　and　their　related　socioeconomic　factors　are　unclear.　To　fill　this　research　gap,　this　study　investigates　the　spatial　distribution　pattern　and　spatial　autocorrelation　characteristics　of　NOX,　PM,　and　SO2　emissions　from　HDDTs　in　200　districts　and　counties　of　the　Beijing–Tianjin–Hebei　(BTH)　region.　We　used　the　spatial　lag　model　to　calculate　the　significances　and　directions　of　the　pollutants　from　HDDTs　and　their　related　socioeconomic　factors,　namely,　per　capita　GDP,　population　density,　urbanization　rate,　and　proportions　of　secondary　and　tertiary　industries.　Then,　the　geographical　detector　technique　was　applied　to　quantify　the　strengths　of　the　significant　socioeconomic　factors　of　HDDT　emissions.　The　results　show　that　(1)　NOX,　PM,　and　SO2　pollutants　emitted　by　HDDTs　in　the　BTH　region　have　spatial　heterogeneity,　i.e.,　low　in　the　north　and　high　in　the　east　and　south.　(2)　The　pollutants　from　HDDTs　in　the　BTH　region　have　significant　spatial　autocorrelation　characteristics.　The　spatial　dependence　effect　was　obvious;　for　every　1%　increase　in　the　HDDT　emissions　in　the　surrounding　districts　and　counties,　the　local　HDDT　emissions　increased　by　0.39%.　(3)　Related　factors　analysis　showed　that　the　proportion　of　tertiary　industries　had　a　significant　negative　correlation,　whereas　the　proportion　of　secondary　industries　and　urbanization　rate　had　significant　positive　correlations　with　HDDT　emissions.　Population　density　and　per　capita　GDP　did　not　pass　the　significance　test.　(4)　The　order　of　effect　intensities　of　the　significant　socioeconomic　factors　was　proportion　of　tertiary　industry　＞　proportion　of　secondary　industry　＞　urbanization　rate.　This　study　guides　scientific　decision　making　for　pollution　control　of　HDDTs　in　the　BTH　region.　©　2019,　by　the　authors.　Licensee　MDPI,　Basel,　Switzerland.