| Literature DB >> 28855647 |
Xuan Zheng1, Ye Wu2,3, Shaojun Zhang4, Jingnan Hu5, K Max Zhang6, Zhenhua Li1, Liqiang He1,5, Jiming Hao1,7.
Abstract
Particulate polycyclic aromatic hydrocarbons (p-PAHs) emitted from diesel vehicles are of concern because of their significant health impacts. Laboratory tests, road tunnel and roadside experiments have been conducted to measure p-PAH emissions. While providing valuable information, these methods have limited capabilities of characterizing p-PAH emissions either from individual vehicles or under real-world conditions. We employed a portable emissions measurement (PEMS) to measure real-world emission factors of priority p-PAHs for diesel vehicles representative of an array of emission control technologies. The results indicated over 80% reduction in p-PAH emission factors comparing the China V and China II emission standard groups (113 μg kg-1 vs. 733 μg kg-1). The toxicity abatement in terms of Benzo[a]pyrene equivalent emissions was substantial because of the large reductions in highly toxic components. By assessing real traffic conditions, the p-PAH emission factors on freeways were lower than on local roads by 52% ± 24%. A significant correlation (R2~0.85) between the p-PAH and black carbon emissions was identified with a mass ratio of approximately 1/2000. A literature review indicated that diesel p-PAH emission factors varied widely by engine technology, measurement methods and conditions, and the molecular diagnostic ratio method for source apportionment should be used with great caution.Entities:
Year: 2017 PMID: 28855647 PMCID: PMC5577249 DOI: 10.1038/s41598-017-09822-w
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Average p-PAH emission factors for the tested HDDVs according to the emission standard category, engine type and road type, respectively.
Figure 2Average distance-based emission factors for each p-PAH component according to the engine type.
Figure 3Correlation between p-PAH emission factors and BC emission factors from simultaneous test profiles of nine HDDVs.
Figure 4Comparison of the p-PAH emissions from HDDVs determined in this study with those determined in (a) dynamometer studies and (b) tunnel and roadside studies. Emission factors of each p-PAH compound (left axis) measured in this study are presented in the form of five-number boxplot to reflect inter-vehicle variations, which consists of the minimum, first quartile, median, third quartile, and maximum values. Mean values of emission factors reported in previous studies are marked with the literature sources. Total p-PAHs emission factors (right axis) represent the sum of the fifteen p-PAH compounds detected from each study. Note: (I) dynamometer study of two vehicles with MI engines under steady conditions[10]; (II) dynamometer study of two in-use diesel trucks (model year earlier than 1996) under FTP conditions[11]; (III) dynamometer study of a diesel fleet under transit conditions[14]; (IV) dynamometer study of a diesel fleet under cruising conditions[14]; (V) dynamometer study of vehicles with EI engines under UDDS conditions[15]; (VI) tunnel study at the Caldecott Tunnel[46]; (VII) tunnel study at the Caldecott Tunnel[17]; (VIII) tunnel study at the Caldecott Tunnel[47]; (IX) roadside study near the I-710; (X) tunnel study at the Caldecott Tunnel for ultrafine mode particles[16]; (XI) tunnel study at the Caldecott Tunnel for accumulation mode particles[16].
Molecular diagnostic ratios (MDRs) to infer source characteristics.
| Test method | Sources and conditions | Flu/Pyr + Flu | Ant/Phe + Ant | BaA/Chr + BaA |
|---|---|---|---|---|
| PEMS (this study) | MI engines on freeways | 0.40 ± 0.04 | 0.12 ± 0.03 | 0.28 ± 0.07 |
| MI engines on local roads | 0.44 ± 0.13 | 0.09 ± 0.03 | 0.34 ± 0.12 | |
| EI engines on freeways | 0.37 ± 0.04 | 0.10 ± 0.02 | 0.34 ± 0.08 | |
| EI engines on local roads | 0.38 ± 0.08 | 0.10 ± 0.02 | 0.37 ± 0.08 | |
| Overall | 0.40 ± 0.03 | 0.10 ± 0.02 | 0.33 ± 0.09 | |
| Dynamometers | Rogge | 0.37 | 0.12 | 0.36 |
| Shah | 0.28, 0.26 and 0.26 | 0.07, 0.05 and 0.03 | 0.53, 0.50, and 0.51 | |
| Riddle | 0.31 ± 0.04 and 0.31 ± 0.06 | 0.05 and 0.25 | ||
| Schauer | 0.39 | 0.19 | 0.33 | |
| Laroo | 0.64 and 0.31 | 0.15 and 0.07 | 0.34 and 0.48 | |
| Pabkin | 0.22 and 0.26 | 0.20 and 0.21 | 0.44 and 0.41 | |
| Tunnels and roadsides | Miguel | 0.41 | 0.68 | |
| Marr | 0.43 | 0.56 | ||
| Phuleria | 0.38 and 0.36 | 0.50 and 0.56 | ||
| Ning | 0.41 | 0.57 | ||
| Characteristic MDRs to infer emissions sources by previous studies | Katsoyiannis | <0.4 for petroleum sources, and >0.4 for combustion sources; 0.4~0.5 for fuel combustion, and >0.5 for coal and biomass burning; | <0.1 for petroleum sources, and >0.1 for combustion sources; | <0.2 for petroleum sources, and >0.35 for combustion sources; |
| Yunker | Petroleum sources: 0.26 ± 0.16 for diesel, 0.22 ± 0.07 for crude oil, 0.46 for kerosene, and 0.29 lubricating oil; Combustion sources: 0.39 ± 0.11 for diesel, 0.44 for gasoline, 0.50 for kerosene, and over 0.5 for coal and biomass burning; | |||
| Ravindra | >0.5 for diesel and <0.5 for gasoline | 0.50 for diesel and 073 for gasoline |
Figure 5Schematic diagram of the PEMS platform.