Heavy-duty　diesel　trucks　(HDDTs)　cause　serious　pollution,　and　a　high　spatiotemporal　resolution　emissions　inventory　is　a　valuable　assessment　tool　for　use　in　quantitatively　understanding　the　emissions　mechanisms　of　HDDTs　and　scientifically　developing　associated　emissions　reduction　measures.　This　study　aims　to　comprehensively　utilize　multi-source　spatiotemporal　data　on　transportation-including　fine-scale　trajectories　of　HDDTs,　road　traffic　conditions,　and　attribute　data　for　road　networks　and　HDDTs-supplemented　by　relatively　mature　vehicle　pollution　emissions　models　to　establish　a　high　spatiotemporal　resolution　emissions　inventory　for　HDDTs　in　Beijing　using　a　bottom-up　approach.　Spatial　statistical　techniques,　including　spatial　autocorrelation,　high/low　clustering,　and　outlier　analysis,　are　also　used　to　explore　the　spatiotemporal　distribution　pattern　of　pollution　emissions　in　the　city.　The　results　showed　the　following:　(1)　spatially,　nitrogen　oxide　(NOx)　and　particulate　matter　(PM)　emission　hotspots　spread　from　the　Beijing　sixth-ring　roads　to　the　fourth-ring　roads　from　daytime　to　nighttime.　The　road　segments　with　high　emissions　intensities　have　pronounced　spatial　agglomeration　effects　at　night,　but　these　are　scattered　during　daytime.　(2)　Temporally,　total　HDDT　NOx　emissions　are　consistent　with　the　traffic　volume　trends　and　are　lower　during　major　festivals.　The　highest　NOx　emissions　occur　at　intercity　highways,　and　this　reflects　the　severe　impact　that　intercity　freight　traffic　has　on　air　quality.　The　dominant　HDDT　NOx　emissions　are　from　vehicles　belonging　to　the　China　4　emissions　standard.　(3)　NOx　and　PM　emissions　have　a　significant　spatial　autocorrelation　and　exhibit　high-value　clustering　as　a　whole.　(4)　At　different　time　intervals,　the　distribution　of　High-High/Low-Low　clustering　and　outliers　of　NOx　and　PM　in　the　road　network　is　consistent　with　the　spatial　distribution　of　the　pollutant　emission　intensity.　The　High-Low　outlier　is　mainly　distributed　within　the　fourth-ring　roads,　and　the　number　gradually　reduces　between　night　and　day.　The　Low-High　outlier　is　affected　by　the　heterogeneous　distribution　of　HDDTs　and　exhibits　discontinuous　distribution　characteristics.　Our　results　effectively　evaluate　Beijing＇s　emissions　control　measures　for　HDDTs　and　provide　a　scientific　decision-making　basis　for　developing　targeted　emission　reduction　strategies　for　HDDTs.　(C)　2019　Elsevier　Ltd.　All　rights　reserved.