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Characterizing particulate matter emitted from on-road motor vehicles.

机译:表征公路机动车辆排放的颗粒物。

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Recent epidemiological studies have found a correlation between mortality and ambient fine particulate matter (PM) levels. In urban areas, motor vehicles are a major source of fine and ultrafine PM. In order to aid in better understanding the contribution of the motor vehicle sector as a whole and to derive mass and number emission factors from individual classes of vehicles and the mechanisms contributing to them, the research presented in this dissertation was undertaken. A multi-lag linear regression approach was developed to calculate PM emission factors from on-road motor vehicles and two source attribution techniques were applied to apportion total PM emissions to specific mechanisms including tailpipe, resuspended road dust, tire-wear, and brake-wear. In order to characterize the size distribution of emitted particles and the particle number emission rates, a quantitative approach was also developed.; The findings of the source attribution component of the study revealed that the motor vehicles sector contributes 20% to 76% and 35% to 93% of the observed ambient PM10 and PM2.5 in seven urban areas, respectively. Using the multi-lag linear regression approach, on-road PM 10 emission factors were determined and ranged from 530 to 9,100 mg/km and from 90 to 850 mg/km for HDD and LDSI vehicles, respectively. PM 2.5 emission factors ranged from 120 to 170 mg/km and from 10 to 90 mg/km for HDD and LDSI vehicles, respectively. The PM contributing to the above mass emission factors was found to be associated with resuspended road dust, tailpipe emissions, and brake-wear. No tire-wear was observed.; Vehicle particle size distributions were determined using an SMPS. Each measured size distribution consisted of two modes: a nucleation mode with midpoint diameter less than 20 nm and an accumulation mode with midpoint diameter less than 100 nm. The nucleation and accumulation components in some distributions exhibited second maxima, which may imply that such particle size distributions are superpositions of two particle size distributions: one attributed to the HDD vehicles and another attributed to either a different class of HDD vehicles or to LDSI vehicles. This decomposing technique enabled us to estimate particle production rates of 1.8 × 1013 and 2.8 × 10 14 particles per vehicle-km for LDSI and HDD vehicles, respectively.
机译:最近的流行病学研究发现死亡率与周围细颗粒物(PM)水平之间存在相关性。在城市地区,机动车辆是PM和超细PM的主要来源。为了帮助更好地理解整个汽车行业的贡献,并从各个类别的车辆及其产生机理中推导出质量和数量排放因子,本文进行了研究。开发了一种多延迟线性回归方法来计算公路机动车辆的PM排放因子,并应用了两种来源归因技术将PM的总排放分配给特定的机制,包括排气管,重悬的道路灰尘,轮胎磨损和刹车磨损。 。为了表征所排放颗粒的尺寸分布和颗粒数量的排放速率,还开发了一种定量方法。该研究的来源归因部分的发现表明,机动车部门贡献了所观察到的环境PM 10 和PM 2.5 分别位于七个市区。使用多重滞后线性回归方法,确定了道路PM 10 排放因子,HDD和LDSI车辆的排放因子分别为530至9,100 mg / km和90至850 mg / km。 HDD和LDSI车辆的PM 2.5 排放因子分别为120至170 mg / km和10至90 mg / km。发现造成上述大量排放因子的颗粒物与道路重悬的粉尘,尾气排放和制动磨损有关。没有观察到轮胎磨损。使用SMPS确定载体粒度分布。每种测量的尺寸分布均由两种模式组成:中点直径小于20 nm的成核模式和中点直径小于100 nm的累积模式。在某些分布中的成核和累积成分表现出第二个最大值,这可能意味着这种粒度分布是两个粒度分布的叠加:一个归因于HDD载具,另一个归因于不同类别的HDD载具或LDSI载具。这种分解技术使我们能够估计LDSI和HDD车辆每车辆每公里km的颗粒产生率分别为1.8×10 13 和2.8×10 13

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