Estimating　exposure　to　PM2.5　within　urban　areas　has　important　implications　for　human　health.　Satellite　remote　sensing　provides　an　effective　means　to　retrieve　spatial　coverage　of　PM2.5　concentrations.　Using　the　monitoring　network　established　by　the　local　government　in　2014,　this　study　developed　a　linear　mixed　effects　model　that　integrates　aerosol　optical　depth　(AOD)　measurements　(spatial　resolution:　3　km)　from　MODIS　and　meteorological　data　from　GEOS-FP　meteorological　fields　as　predictors　to　derive　daily　estimations　of　ground-level　PM2.5　concentrations　in　Fuzhou　(SE　China).　A　10-fold　cross　validation　method　was　employed　to　examine　the　performance　of　the　mixed　effects　model.　The　cross　validation　yielded　a　R-2　value　of　0.72,　and　a　root　mean　square　error　value　of　9.2　mu　g/m(3)　for　the　mixed　effects　model.　Furthermore,　the　monthly/seasonal　average　PM2.5　estimated　by　the　mixed　effects　model　was　highly　correlated　with　those　of　in　situ　measurements.　The　results　also　revealed　the　spatial　differences　in　the　PM2.5　distribution　across　the　study　area,　i.e.,　higher　concentrations　in　the　urban　center　and　lower　values　in　suburban　to　rural　areas.　The　results　suggest　that　the　mixed　effects　model　using　MODIS　3　km　AOD　together　with　meteorological　data　could　be　effective　for　the　estimation　of　PM2.5　concentrations　in　the　Fuzhou　area.