Priority Evaluation of Bus Routes for Low Emission Vehicle Subsidy based on Mobile Source Pollution Risk Potential Indicators
|關鍵字:||移動污染源;指標;低污染公車補助;街谷模式;永續環境系統;mobile pollution source;indicator;subsidy for low emission buses;sustainable environmental systems analysis|
初選時共刪除路線75 條，再依據行駛里程選取前100 條路線進行後
染物子指標中CO 和PM10 及PM2.5 子指標間相關性頗高，其餘子指標間的
相關性則不高，單一污染物子指標可考量採用PSI 指標污染物PM10 或是
For improving ambient air quality, subsidy for low emission buses is a widely adopt policy to reduce mobile source pollution. Since the cost for replacing buses with low emission vehicles is quite high, prioritizing bus routes for increasing the effectiveness of the subsidy policy is thus desired. Therefore, this study establishes indicators to evaluate the subsidy priority of a bus route according to simulated pollutant concentration and affected population along the route. Since there are too many bus routes in the studied area, Taipei City, this study excludes those routes with obviously low pollution impact first. Then, the Operational Street Pollution Model (OSPM) is applied to simulate the mobile source pollution along each route based on estimated traffic flow, buildings on both sides, and meteorological data. Two sets of indicators are established. The first set is computed according to pollutant concentration and route length, and the other is based on the estimated pollutant intake sum by affected population. Indicators for individual pollutants are established first. For comparing the results obtained for different pollutants, the Acute Reference Exposure Level (RELA) and Air Quality Standard are applied to establish the other sets of indicators. Finally, aggregate indictors are set up by adding up all indicators for individual pollutants. The applicability of each indicator for prioritizing bus routes for subsidy is then evaluated. Seventy-five routs with obviously low pollution impact are removed during the initial screening procedure. For the rest of routes, according to the trip length of each route, the top 100 routes are selected for further analyses. The results simulated by OSPM are mainly affected by street width, building height, and traffic flow. Because the impact on affected population along a route should be considered, the intake-sum indicators are thus recommended for prioritizing bus routes. Although the CO, PM10, PM2.5 indicators are highly correlated, others are not. For individual pollutant based indicators, either the PM10, as the major PSI critical pollutant, or CO indicator is suggested. However, different pollutants have varied impacts on human, and the indicator based on one individual pollutant may not represent the overall effect from all pollutants. The aggregate indicator is therefore recommended for prioritizing bus routes for low emission vehicle subsidy.
|Appears in Collections:||Thesis|
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