The　Chinese　government　has　explicitly　promised　to　peak　carbon　dioxide　emissions　by　2030　and　strive　to　become　carbon　neutral　by　2060.　As　the　capital　of　China,　Beijing　should　play　a　pilot　role　in　reducing　carbon　emissions.　Researching　on　the　synergistic　effect　of　air　pollutants　and　carbon　dioxide　emissions　reduction　can　be　conducive　to　the　reduction　of　carbon　and　pollution,　and　ultimately　promote　economic　growth　and　enhance　environmental　management.　Based　on　the　extended　Kaya　identity　and　the　gray　correlation　model,　this　study　analyzes　the　correlation　degree　of　the　influencing　factors　of　collaborative　emission　reduction.　The Logarithmic　Mean　Divisia　Index　method　(LMDI　model)　is　conducted　to　decompose　the　driving　effects　and　quantify　the　collaborative　emission　reduction　effects　of　main　air　pollutants　and　carbon　dioxide　in　Beijing.　The　results　showed　a　strong　correlation　(correlation　coefficient　＞　0.6)　between　carbon　dioxide　and　major　air　pollution.　The　energy　intensity　and　energy　structure　are　the　main　factors　to　promote　the　major　air　pollutants　emission　reduction　in　Beijing,　while　the　economic　output　and　population　size　increase　the　air　pollutant　emissions.　The　average　CO2　contribution　rate　to　SO2,　NOx,　and　PM10　from　2010　to　2019　was　9.60,　5.99　and　9.06%,　respectively.　In　general,　there　is　a　significant　connection　between　CO2　emissions　and　the　main　air　pollutants.　However,　the　synergistic　emission　reduction　effect　of　CO2　and　SO2　is　greater　than　that　of　CO2　and　NOx,　and　CO2　and　PM10.　Finally,　this　paper　proposes　several　countermeasures　and　suggestions　for　front-end　prevention,　middle-end　control,　and　collaborative　emission　reduction　based　on　the　findings.　Graphical　abstract:　[Figure　not　available:　see　fulltext.].　©　2023,　The　Author(s),　under　exclusive　licence　to　Springer-Verlag　GmbH　Germany,　part　of　Springer　Nature.