Greenhouse　gases　(GHG)　from　human　activities　are　the　main　contributor　to　climate　change　since　the　mid-20th　century.　Reducing　the　release　of　GHG　emissions　is　becoming　a　thematic　research　topic　in　many　research　disciplines.　In　the　reliability　research　community,　there　are　research　papers　relating　to　reliability　and　maintenance　for　systems　in　power　generation　farms　such　as　offshore　farms.　Nevertheless,　there　is　sparse　research　that　aims　to　optimise　maintenance　policies　for　reducing　the　GHG　emissions　from　systems　such　as　automotive　vehicles　or　building　service　systems.　To　fill　up　this　gap,　this　paper　optimises　replacement　policies　for　systems　that　age　and　degrade　and　that　produce　GHG　emissions　(i.e.,　exhaust　emissions)　including　the　initial　manufacturing　GHG　emissions　produced　during　the　manufacturing　stage　and　the　emissions　generated　during　the　operational　stage.　Both　the　exhaust　emissions　process　and　the　failure　process　are　considered　as　functions　of　two　time　scales　(i.e.,　age　and　accumulated　usage),　respectively.　Other　factors　that　may　affect　the　two　processes　such　as　ambient　temperature　and　road　conditions　are　depicted　as　random　effects.　Under　these　settings,　the　decision　problem　is　a　nonlinear　programming　problem　subject　to　several　constraints.　Replacement　policies　are　then　developed.　Numerical　examples　are　provided　to　illustrate　the　proposed　methods.　©　2022　The　Author(s)