The natural gas vehicle market is rapidly developing throughout the world, and the majority of such vehicles operate on compressed natural gas(CNG). However, most studies on the emission characteristics of CNG vehicles rely on laboratory chassis dynamometer measurements, which do not accurately represent actual road driving conditions. To further investigate the emission characteristics of CNG vehicles, two CNG city buses and two CNG coaches were tested on public urban roads and highway sections. Our results show that when speeds of 0–10 km/hr were increased to 10–20 km/hr, the CO_2, CO, nitrogen oxide(NO_x), and total hydrocarbon(THC) emission factors decreased by(71.6 ± 4.3)%,(65.6 ± 9.5)%,(64.9 ± 9.2)% and(67.8 ± 0.3)%, respectively. In this study, The Beijing city buses with stricter emission standards(Euro Ⅳ) did not have lower emission factors than the Chongqing coaches with Euro Ⅱ emission standards. Both the higher emission factors at 0–10 km/hr speeds and the higher percentage of driving in the low-speed regime during the entire road cycle may have contributed to the higher CO_2 and CO emission factors of these city buses. Additionally, compared with the emission factors produced in the urban road tests, the CO emission factors of the CNG buses in highway tests decreased the most(by 83.2%), followed by the THC emission factors, which decreased by 67.1%. 相似文献
A total of 15 light-duty diesel vehicles(LDDVs) were tested with the goal of understanding the emission factors of real-world vehicles by conducting on-board emission measurements. The emission characteristics of hydrocarbons(HC) and nitrogen oxides(NOx) at different speeds, chemical species profiles and ozone formation potential(OFP) of volatile organic compounds(VOCs) emitted from diesel vehicles with different emission standards were analyzed. The results demonstrated that emission reductions of HC and NOxhad been achieved as the control technology became more rigorous from Stage I to Stage IV. It was also found that the HC and NOxemissions and percentage of O2 dropped with the increase of speed, while the percentage of CO2 increased. The abundance of alkanes was significantly higher in diesel vehicle emissions, approximately accounting for 41.1%–45.2%, followed by aromatics and alkenes. The most abundant species were propene,ethane, n-decane, n-undecane, and n-dodecane. The maximum incremental reactivity(MIR)method was adopted to evaluate the contributions of individual VOCs to OFP. The results indicated that the largest contributors to O3 production were alkenes and aromatics, which accounted for 87.7%–91.5%. Propene, ethene, 1,2,4-trimethylbenzene, 1-butene, and1,2,3-trimethylbenzene were the top five VOC species based on their OFP, and accounted for 54.0%-64.8% of the total OFP. The threshold dilution factor was applied to analyze the possibility of VOC stench pollution. The majority of stench components emitted from vehicle exhaust were aromatics, especially p-diethylbenzene, propylbenzene, m-ethyltoluene, and p-ethyltoluene. 相似文献
Objective: The Useful Field of View (UFOV) assessment, a measure of visual speed of processing, has been shown to be a predictive measure of motor vehicle collision (MVC) involvement in an older adult population, but it remains unknown whether UFOV predicts commercial motor vehicle (CMV) driving safety during secondary task engagement. The purpose of this study is to determine whether the UFOV assessment predicts simulated MVCs in long-haul CMV drivers.
Method: Fifty licensed CMV drivers (Mage = 39.80, SD = 8.38, 98% male, 56% Caucasian) were administered the 3-subtest version of the UFOV assessment, where lower scores measured in milliseconds indicated better performance. CMV drivers completed 4 simulated drives, each spanning approximately a 22.50-mile distance. Four secondary tasks were presented to participants in a counterbalanced order during the drives: (a) no secondary task, (b) cell phone conversation, (c) text messaging interaction, and (d) e-mailing interaction with an on-board dispatch device.
Results: The selective attention subtest significantly predicted simulated MVCs regardless of secondary task. Each 20 ms slower on subtest 3 was associated with a 25% increase in the risk of an MVC in the simulated drive. The e-mail interaction secondary task significantly predicted simulated MVCs with a 4.14 times greater risk of an MVC compared to the no secondary task condition. Subtest 3, a measure of visual speed of processing, significantly predicted MVCs in the email interaction task. Each 20 ms slower on subtest 3 was associated with a 25% increase in the risk of an MVC during the email interaction task.
Conclusions: The UFOV subtest 3 may be a promising measure to identify CMV drivers who may be at risk for MVCs or in need of cognitive training aimed at improving speed of processing. Subtest 3 may also identify CMV drivers who are particularly at risk when engaged in secondary tasks while driving. 相似文献