Evaluating real-world CO2 and NOX emissions for public transit buses using a remote wireless on-board diagnostic (OBD) approach

The challenge to mitigate real-world emissions from vehicles calls for powerful in-use compliance supervision. The remote on-board diagnostic (OBD) approach, with wireless data communications, is one of the promising next-generation monitoring methods. We collected second-by-second profiles of carbon dioxide (CO2) and nitrogen oxides (NOX) emissions, driving conditions and engine performance for three conventional diesel and three hybrid diesel buses participating in a remote OBD pilot program in Nanjing, China. Our results showed that the average CO2 emissions for conventional diesel and hybrid diesel buses were 816 83 g km(-1) and 627 54 g km(-1), respectively, under a typical driving pattern. An operating mode binning analysis indicated that CO2 emissions reduction by series-parallel hybrid technology was largely because of the significant benefits of the technology under the modes of low speed and low power demand. However, significantly higher CO2 emissions were observed for conventional diesel buses during rush hours, higher than 1200 g km(-1). The OBD data suggested no improvement in NOX emission reduction for hybrid buses compared with conventional buses; both were approximately 12 g km(-1) because of poor performance of the selective catalyst reduction (SCR) systems in the real world. Speed-dependent functions for real-world CO2 and NOX emissions were also constructed. The CO2 emissions of hybrid buses were much less sensitive to the average speed than conventional buses. If the average speed decreased from 20 km h(-1) to 10 km h(-1), the estimated CO2 emission factor for conventional buses would be increased by 34%. Such a change in speed would increase NOX emissions for conventional and hybrid buses by 38% and 56%, respectively. This paper demonstrates the useful features of the remote OBD system and can inform policy makers how to take advantage of these features in monitoring in-use vehicles. (C) 2016 Elsevier Ltd. All rights reserved.