| 英文摘要 |
1. Mobile source emissions estimation
Based on the 2019 annual traffic big data, the transportation demand model is calibrated, and the mobile source emissions are estimated in combination with the EPA source emission factor. The analysis shows that the emissions of major pollutants are CO (29,418 tons), NOX (15,677 metric tons), THC (11,161 metric tons), and emissions in 2019 are slightly lower than in 2018. This study draws a 2019 City mobile source emission map with the road network and grid format.
According to the simulation results of the odd/even license number restricted control for passenger cars in Banqiao District, the SOX reduction has the most significant effect, with a decrease of about 13%~16%, followed by a decrease of 9%~11% for PM10 and 9%~10% for PM2.5.
2. High pollution motorcycle identification
The installation of 10 license plate recognizers for the motorcycle in New Taipei City was operated in Jan. 2020. There were about 33.9 million motorcycle trips have been collected (the correct rate is between 81.54% and 85.82%). A Comparison of high-pollution motorcycle data shows that 8,888 two-stroke scooters/motorcycles license plates were obtained between January and November of 2020.
3. Air quality model development and air quality event day simulation
This project has integrated meteorological, environmental observation data ,and transportation demand model to build the air quality model to conduct PM2.5 analysis which refined the spatial scale resolution to 150m 150m.
On 2020/1/6, the daily observation of the air quality was carried out, and the main sources of PM2.5 pollution were assessed as factories and mobile sources. After further evaluation and adoption of the traffic improvement strategy, the measured value of PM2.5 at the observation station can be reduced by 0.01 μg/m3.
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