The　latest　China　VI　emission　standard　has　introduced　a　remote　monitoring　rule　for　regulating　in-use　emissions　of　heavy-duty　diesel　vehicles　(HDDVs).　Real-time　data　regarding　engine　and　aftertreatment　operating　conditions　and　tailpipe　nitrogen　oxides　(NOx)　concentrations　are　required　to　be　collected　through　electronic　control　unit　and　on-board　NOx　sensors　by　vehicle　original　equipment　manufacturers　(OEMs),　and　then　transmitted　to　environmental　authorities.　Beijing　has　developed　a　local　standard　that　requires　OEMs　to　design　China　VI-like　onboard　monitoring　(OBM)　systems　for　new　China　V　HDDVs　since　September　2018.　Additionally,　Beijing　has　been　a　pioneer　in　retrofitting　in-use　China　IV　and　China　V　HDDVs　with　OBM　systems　since　2017.　This　paper　contains　a　timely　technical　and　policy　assessment　for　the　state-of-the-art　OBM　programs　in　China　with　a　focus　on　the　recent　progress　in　Beijing.　Both　OEM-performed　and　retrofitted　OBM　data　were　collected　from　a　fleet　of　OBM-instrumented　vehicles.　First,　our　assessment　shows　high　data　integrity　and　quality　of　OEM-performed　OBM　systems.　In　contrast,　a　considerable　fraction　of　HDDVs　equipped　with　retrofitted　OBM　systems　did　not　completely　report　NOx　concentrations,　intake　mass　air　flow　and　other　parameters.　Next,　eight　OBM-instrumented　HDDVs　were　tested　on　road　by　portable　emissions　measurement　systems　(PEMSs)　to　examine　the　reliability　of　sensor-based　NOx　concentrations.　The　majority　(6　of　8)　shows　a　good　agreement　between　OBM　and　PEMS　results　with　an　average　relative　error　of　approximately-15%.　Furthermore,　calculation　of　NOx　mass　emissions,　inter-trip　variability,　and　alternative　methods　of　enforcing　in-use　emissions　management　(e.g.,　to　develop　concentration　metric-based　emission　limits)　are　discussed.　This　early-stage　assessment　suggests　the　OBM　approach　has　the　potential　to　play　a　central　role　in　in-use　emission　inspections　for　HDDVs　in　China.　The　regulatory　agency　should　focus　more　attention　to　the　data　integrity　and　the　reliability　of　NOx　sensors　by　developing　effective　verification　processes.　(C)　2018　Elsevier　B.V.　All　rights　reserved.