Abstract

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 on-board 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.

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