| 英文摘要 |
This project focuses on the estimation of the total emissions of major air pollutants from mobile sources in 2015 and 2016. To renew the parameter source of mobile pollutants emission estimation model, we evaluate the accuracy of activity intensity, which is calculated by fuel consumption, and zero mileage degradation rate. Furthermore, in order to analyze the impact of mobile pollution sources on air quality, we use the photochemical station hourly data and Positive Matrix Factorization (PMF) model to estimate the source contributions of mobile pollution, and discuss the relationship between mobile source and distribution of PM2.5. The Real-world on-road measurements and data analysis of various types of vehicles on different road grades were completed. The Real-world on-road measurement results were also compared to emission factors of Mobile Taiwan 2.0. On the other hand, this project also focuses on mobile pollution control strategy, including the analysis of domestic and foreign mobile pollution control strategies, related reduction scenarios and the feasibility of implementation.
1. The estimation of the total emissions of major air pollutants from mobile sources in 2015 and 2016 was completed. The results show (that) emissions of TSP, PM10, PM2.5, SOx, NOx, THC, NMHC, CO in 2016 were slightly reduced compared with 2015. This reduction, which was associated with activity intensity and emission factors, shows significantly on NMHC and CO by 6.26% and 6.24%. The primary cause of this reduction is 20% decrease of two Stroke Cycle Scooters in calculation of activity intensity.
2. Air quality analysis we investigated the difference of percentage of mobile source contributions between “high PM2.5 episode” and “non-high PM2.5 episode” through analyzing monitoring data collected from Wanhua air quality monitoring station (AQMS). After applied statistical analysis, we found that there was no significant difference between the two episodes. Besides, we also analyzed the high PM2.5 episode occurring on February 5th in 2015. We infer that the PM2.5 level was not only mainly affected by mobile sources but also other factors on that day.
3. According to the results obtained from Pearson correlation analysis and cluster analysis, we found that CO, which is a monitoring item of AQMSs, has the most similar temporal variation to mobile sources temporal variation. Furthermore, we also investigate the PM2.5 variation of Puli and Zhudong station from 2014 to 2016. The results showed that the decrease of PM2.5 of Puli station in 2016 may have a lower correlation with mobile sources but higher correlation with meteorological factors. We also applied CMAQ model to simulate the impact from mobile sources to PM2.5 level in Puli area. We infer that the decrease of PM2.5 of Puli station in 2016 may have a lower correlation with mobile sources as well.
4. In the past project, Portable Emission Measurement System (PEMS) tests were performed in order to investigate the impact of road grade on on-road exhaust emissions of passenger vehicles. The results show road grade was found to have a significant impact on vehicle exhaust emissions, especially, have higher emission factors of CO2 and FC of gasoline passenger cars on urban road, when speed lower than 30km/h. Furthermore, the real world emissions of CO, HC and NOx shows highest emission factors from Euro 3 gasoline passenger cars. The HC and NOx emission factors of diesel passenger cars were higher than gasoline passenger cars.
5. Real-world on-road measurements for gasoline cars were performed. Comparisons between Real-world on-road measurements and Mobile Taiwan 2.0 emission factors shows that of the Euro 3 and Euro 4 gasoline cars are similar to MT-2.0 model. But significant differences were found in emission factors of NOx for several speed ranges.
6. The result showed that the Air Quality Areas still use the large number of diesel vehicles which before 1999 and have a higher emissions proportion of PM2.5 and NOx by analyzing the changes of the mobile emission proportion in each Air Quality Areas from 2013 to 2016. We further estimate if eliminating all the old diesel vehicles will reduce the emissions of PM2.5 and NOx by more than 20% in all air quality areas. Otherwise, we already assembled the control strategy of mobile sources control of the domestic and international agencies; complete the estimation of mobile strategic reduction scenarios and the feasibility of implementing and possible impact assessment for the relevant strategies. According to the principle of trading the mobile source’s offsets to the Stationary air pollution in the Cap and Trade plan, we put forward suggestions for amendment and foreign references for the way of providing operation. The report also presented a calculation for the emission reduction targets of mobile sources control in the second phase of the plan which is made of the mobile source’s offsets that can be exchanged for them. TSP is 22 tons/year, NOx is 306 tons/year, and VOC is 356 tons/year.
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