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Investigation and Prediction of Heavy-Duty Diesel Passenger Bus Emissions in Hainan Using a COPERT Model

机译:使用Copert模型对海南重型柴油乘客总线排放的调查与预测

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摘要

To investigate the emission status and predict the future trends of heavy-duty diesel passenger buses in Hainan Province, the technical level distribution, activity characteristics, and operating conditions of heavy-duty diesel passenger buses were statistically analyzed. The emissions of CO, CO2, NOX, and PM of the province’s heavy-duty diesel passenger buses in 2017 were calculated by the COPERT model. The Portable Emission Measurement System was applied to the calibration of emission factors calculated by the model to improve the accuracy of emission predictions. The prediction of emission trends sets three different scenarios: baseline scenarios (BAS), emission reduction standard scenario (ERS), and emission reduction standard and replacement by electric vehicle scenario (ERS and REV). The gray model was used to predict the number of heavy-duty diesel passenger buses in the three scenarios and combined with the calibrated emission factors to predict the emission trends under different scenarios. Results show that the ERS will reduce CO, CO2, NOX, and PM emissions by approximately 23%, 12%, 23%, and 46% respectively, in 2025 compared with BAS. ERS and REV will reduce CO, CO2, NOX, and PM emissions by approximately 38%, 33%, 38%, and 50% for the three emissions, compared with the BAS.
机译:为了调查排放状态并预测海南省重型柴油乘客公共汽车的未来趋势,统计分析了重型柴油乘客公共汽车的技术水平分布,活动特性和运行条件。 2017年全省重型柴油乘用车的CO,CO2,NOX和PM的排放量由Copert模型计算。便携式发射测量系统应用于由模型计算的排放因子的校准,以提高排放预测的准确性。排放趋势的预测设定了三种不同的场景:基线情景(BAS),减排标准场景(ERS),减排标准和电动车辆场景(ERS和REV)更换。灰色模型用于预测三种情况中的重型柴油乘客总线的数量,并结合校准的排放因子,以预测不同情景下的排放趋势。结果表明,与BAS相比,2025分别将分别减少CO,CO2,NOX和PM排放约23%,12%,23%和46%。与BAS相比,ERS和REV将减少CO,CO2,NOX和PM排放约38%,33%,38%和50%。

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