Rapid　urbanization　has　increased　carbon　dioxide　(CO2)　emissions,　exacerbating　ecological　issues　and　prompting　global　shift　towards　low-carbon　development.　However,　current　studies　at　the　county-level　face　challenges　such　as　incomplete　monitoring　systems　and　insufficient　statistical　granularity,　which　restrict　the　detailed　analysis　of　carbon　emission　spatial　distribution　and　driving　mechanisms.　To　address　this,　the　study　utilized　high-resolution　Luojia1-01　nighttime　light　(NTL)　data　combined　with　the　optimal　parameters-based　geographical　detector　(OPGD)　model,　taking　Fuzhou,　a　typical　＂furnace　city＂　as　a　case　study　to　reveal　the　spatial　differentiation　characteristics　and　driving　mechanisms　of　carbon　emissions　at　the　county-level.　The　results　indicate　that　carbon　emissions　in　Fuzhou　exhibit　a　＂core-edge＂　spatial　differentiation　pattern,　with　the　central　urban　areas　having　higher　emissions　than　the　surrounding　counties,　and　a　positive　spatial　correlation　was　observed;　the　proportion　of　the　tertiary　production　(PTP),　the　proportion　of　the　primary　production　(PTP),　the　urbanization　rate　(UR),　and　the　level　of　social　capital　(SC)　are　core　driving　factors　of　carbon　emissions,　with　dual-factor　interactions　exhibiting　significant　bilinear　enhancement　effects.　Based　on　the　carbon　emission　differentiation　characteristics,　the　study　proposes　a　＂five-zone　differentiated＂　governance　strategy,　which　includes　low-carbon　transformation　of　the　service　industry　in　the　core　urban　areas,　green　industrial　upgrading　in　high-emission　zones,　and　strengthening　the　carbon　sink　function　in　ecological　protection　areas.　This　study　provides　methodological　support　and　decision-making　guidance　for　refined　carbon　emission　management　and　low-carbon　development　planning　at　the　county-level.