Diesel　pallet　trucks,　a　type　of　heavy-duty　diesel　trucks　(HDDTs),　have　historically　been　a　vital　component　in　logistics　and　transport　due　to　their　high　payload　capacity.　However,　they　also　present　significant　challenges,　particularly　in　terms　of　emissions　which　contribute　substantially　to　urban　air　pollution.　Traditional　HDDTs　emission　measurement　methods,　such　as　engine　bench　tests　and　those　used　in　laboratory　settings,　often　fail　to　capture　real-world　emission　behaviors　accurately.　This　study　specifically　examines　the　real-world　emission　characteristics　of　diesel　pallet　trucks　exceeding　30　t　under　varying　loads　(unloaded,　half　loaded,　and　fully　loaded)　and　different　road　conditions　(urban,　suburban,　and　high-speed).　Considering　that　data　quality　is　the　key　to　the　accuracy　of　the　scheme,　this　research　utilized　a　portable　emission　measurement　system　(PEMS)　to　capture　real-time　emissions　data　of　carbon　dioxide　(CO2),　carbon　monoxide　(CO),　nitrogen　oxides　(NOX),　and　total　hydrocarbons　(THC).　Key　findings　demonstrate　a　direct　correlation　between　vehicle　load　and　emission　factors,　with　the　emission　factors　for　CO2,　CO,　and　NOX　increasing　by　39.5%,　105.4%,　and　22.7%,　respectively,　from　unloaded　to　fully　loaded　states　under　comprehensive　operating　conditions.　Regression　analyses　further　provide　an　emission　factor　prediction　model　for　HDDPTs,　underscoring　the　continuous　relationship　between　speed,　load,　and　emission　rates.　These　findings　provide　a　scientific　basis　for　pollution　control　strategies　for　diesel　trucks.