Synergic Control Strategies Of Air Pollutants And CO₂ Emissions For Lightduty Vehicles In China

As the rapid economic development and the improved consumption level in China, the population of light-duty vehicles is developing fast and has become largest, so air pollutants emissions of light-duty vehicles need to be concerned. China has implemented increasingly stringent light-duty vehicle emission standards as well as national fuel consumption standards, emission control technologies have been adopted to reduce vehicle pollution. However, not all control technologies can meet both emission limits and fuel consumption targets effectively. Further research on synergic air pollutants and CO₂ emission of light-duty vehicles is important to develope cost-effective emission control technology strategies.In order to mitigate fuel consumption and emissions, additional technologies beyond the traditional multipoint fuel injection（MPFI） technology path need to be considered such as the gasoline direct injection（GDI） technology path and advanced diesel technology path and gasoline hybrid technology path for the future light-duty passenger vehicles（LDPVs）, and related technology cost database has been built. In the study, based on cost-effectiveness assessment of representative technology paths in use cycle and reduction-effectiveness evaluation of fleet scenarios. We evaluate cost-effectiveness of each technology path in terms of environment, energy consumption and costs by monetization of emissions and sensitivity analysis. Also, we estimate fleet emissions of air pollutants, fuel economy and technology costs under different scenarios to analyse reduction-effectiveness of the new LDPV fleet with different technology penetration rates. Suggestions on synergic control technology strategies are then proposed for future LDPVs.Social cost of PM2.5 emission and CO₂ emission per vehicle, and technology cost in ten-year use cycle under each representative LDPV technology path have been calculated. Use the costs of China 4 MPFI as reference, we estimate the net cost-effectiveness of environment and energy consumption for each technology path. The results indicate that under China 5 emission standard, Diesel has highest cost-effectiveness for its high fuel economy; GDI comes next with a 7% variation from Diesel; MPFI is the third; HEV has the lowest net cost-effectiveness because of its high technology cost, in spite of its low air pollutants emissions and high fuel economy. When it comes to China 6, net cost-effectiveness of GDI technology path ranks first as it uses aftertreatment device to control particles; Diesel then has 17% less net cost-effectiveness than GDI; with reduction of technology cost, net cost-effectiveness of HEV is nearly the same as MPFI, and is 27% lower compard to GDI.We design three scenarios（Referece Scenario BAU, Market Scenario PC0 and Linear Planning Scenario PC1） with various penetration rates of MPFI, GDI, diesel and HEV engines for the new LDPVs in Beijing through 2030. The results show that diesel technology path has no market share by linear planning as the high emissions of NOX and PM2.5. As the penetration rate of GDI is getting higher, air pollutants of PC0 and PC1 have positive reduction-effectiveness in 2020 compared to BAU, but NOX.emissions of both scenarios are slightly higher than BAU. In 2030, HC and PM2.5 reductioneffectiveness of PC0 and PC1 go down relatively because incremental technology cost is higher than emissions reduction, while NOx reduction-effectiveness has been improved with the penetration of HEV. Reduction-effectiveness of fuel consumption under two scenarios has similar trend with HC reduction-effectiveness. In conclusion, diesel technology path is still inappropriate for China’s LDPVs, and the control technology strategy would be the combination development of MPFI, GDI and HEV. Specifically, GDI technology path will become highest in the market share of new gasoline LDPVs, and the penetration rate of HEV will develope gradually, while MPFI will have fewer and fewer market share relatively in the future.