利用IVE模型进行公交车尾气排放分析

介绍了IVE尾气排放模型并与MOBILE模型进行了比较分析。使用GPS对上海市公交车多条运行线路进行了实时运行速度测量,得到上海公交车运行模式的BIN分布,对上海市CNG公交车和柴油公交车的尾气排放进行了模拟计算。结果表明使用CNG公交车代替柴油公交车后,NOX和PM的排放均有显著的降低,但采用不同技术的CNG公交车尾气排放仍有很大的差异,无催化转化和尾气再循环的CNG公交车的CO排放量远高于同类型柴油公交车的排放量。认为IVE模型的模拟结果具有较好的可靠性,其计算模式适用于我国机动车尾气排放清单分析的研究。     

燃料电池汽车氢源生命周期分析

运用生命周期评价方法对使用不同氢源的燃料电池汽车进行了分析.经过目的与范围的确定、清单分析、影响评价和结果解释,表明电解制氢方案的污染排放明显高于甲醇重整和汽油重整方案,而甲醇重整和汽油重整方案又高于天然气制氢和煤制氢方案,对于相同的制氢方案,液氢方案的排放略高于气氢方案.      

柴油车排气微粒后处理器的研究

通过同种典型微粒过滤器的比选试验,表明高效袋式消烟器微粒捕集效率最高.其结构简单,成本低,耐热性好,因此具有很好的推广价值.如果应用在公路隧道中,能降低隧道内能见度的影响,具有较大的开发前景.      

北京地区土壤对柴油的吸附及影响因素研究

通过静态吸附实验,研究了北京地区土壤对柴油的吸附行为,考察了溶液pH和添加乙醇对柴油吸附的影响. 结果表明,6种不同土样对柴油的吸附等温线均较好地符合Langmuir吸附方程,其吸附系数(K)分别为0.193, 0.218, 0.203, 0.199, 0.211和0.182 L/mg,6种土样吸附能力依次为轻壤土>轻粘土>中壤土>砂壤土>重壤土>紧砂土,这主要是由于6种土样的pH,有机质含量和机械组成不同所致;溶液pH的升高,不利于柴油在土壤中的吸附,pH从4升高到10,柴油在1～6号土样中的吸附量分别从1　012, 1　800, 1　377, 1　272, 1　601和862 μg/g降低到114, 236, 163, 150, 201和85 μg/g;向柴油中添加乙醇会减小柴油的吸附量,并且吸附量随添加乙醇量的增大而降低,这有利于柴油的向下运移.      

广州市移动源现状及其污染控制管理对策

通过对广州市机动车辆构成状况和发展趋势、车流变化与氮氧化物变化关系以及各类车型污染排放分担率的分析,结果表明:在排放污染物的移动源中,小型车(出租车及其他小型车)和摩托车是一氧化碳、碳氢化合物的主要排放源;公共汽车等大型车是氮氧化物的主要排放源之一。并提出对广州市机动车污染控制应着重控制摩托车、小型车(特别是轿车,包括出租车)、公共汽车的污染排放。      

Providing the Spark: Impact of financial incentives on battery electric vehicle adoption

To overcome adoption barriers and promote battery electric vehicles (BEVs) as an energy efficient consumer transportation option, a number of states offer subsidies to consumers for BEVs. We use a national data set of vehicle registrations and state-level financial incentives to assess the impact of vehicle purchase subsidies on adoption using both difference-in-differences and synthetic controls methods. We find that incentives offered as direct purchase rebates generate increased levels of new BEV registrations at a rate of approximately 8 percent per thousand dollars of incentive offered. Between 2011 and 2015, vehicle rebate incentives are associated with an increase in overall BEV registrations of approximately 11 percent. Our findings indicate incentives offered as state income tax credits do not have a statistically significant effect on BEV adoptions, though we caution this may be a result of limited temporal variation in BEV incentives across our sample. Responses to rebate incentives do not differ significantly by the make of the vehicle purchased (i.e., Tesla and non-Tesla vehicles). We combine our results with recent assessments of marginal environmental costs of electric vehicle charging and measure net welfare effects of BEV subsidy programs. Our analysis indicates these programs are not welfare-improving if only considering benefits associated with avoided emissions. Additional benefits associated with long-term market growth, production cost savings, network externalities, or accelerated innovation could substantially impact the net welfare outcomes.     

腐殖酸钠和表面活性剂对黄土中石油污染物解吸增溶作用

选用十二烷基苯磺酸钠(LAS)、十二烷基硫酸钠(SDS)和十二烷基磺酸钠(SAS)对污染的土壤进行解吸实验,研究了这3种阴离子表面活性剂和腐殖酸钠对黄土中柴油类污染物的协同增溶作用.结果表明,腐殖酸钠和3种阴离子表面活性剂对黄土中柴油的解吸均有显著增溶作用,使柴油的解吸量明显增加,柴油的去除率最高可达63%.SDS对柴油的解吸量随腐殖酸钠浓度增大呈线性增加关系;但腐殖酸钠浓度增加对 LAS和SAS的解吸曲线有突越点,超过此浓度后反而会抑制解吸作用.     

汽油机排气颗粒粒径分布特征试验研究

对汽油机排气中颗粒的数浓度和粒径分布特征进行了测试.在测试工况下,汽油机排气中的颗粒呈包含核模态粒子(10 nm＜DP＜50 nm)和积聚模态粒子(50 nm＜DP＜487 nm)的双峰分布,排气颗粒的总数和总质量浓度分别为4.2×105-7.9×106个·cm-3和0.02-0.27 mg·m-3.汽油机在开环控制状态下(车速不低于90 km·h-1时)的颗粒数量排放明显高于闭环控制状态(车速不高于70 km·h-1),总颗粒质量浓度随车速的增大显著增加.随车速增大,积聚模态粒子的平均粒径先减小后增大,核模态粒子的几何平均粒径先增大后减小,低车速时,有大量10-20 nm的核模态粒子生成.柴油机和汽油机排气颗粒中核模态粒子通常占有大的数量百分比,为75%-95%,而其质量百分比仅为5%-25%.汽油机的总颗粒、核模态粒子和积聚模态粒子的数量和质量排放均远低于柴油机.     

深圳市纯电动泥头车减污降碳协同效益评价研究

新能源汽车替代传统燃油车是减缓能源与环境压力并如期实现“双碳”目标的重要途径,但在重型车辆、工程车等领域推广较为缓慢. 深圳市自2019年开始推广使用纯电动泥头车,并计划到2025年新能源环卫、泥头车数量达到8000辆.为深入探究纯电动泥头车替代柴油泥头车所产生的减污降碳协同效益,本研究基于一手调研数据,采用生命周期评价方法并结合GREET模型,对比分析了两类泥头车在燃料周期、 车辆周期和配套设施周期3个周期内的能耗、主要空气污染物及碳排放情况.结果表明,纯电动泥头车全生命周期内能耗较柴油泥头车可减少36.2%,主要污染物如NO_x、SO₂、VOC和PM_2.5降幅分别达81.3%、37.8%、29.0%和25.9%;温室气体（GHGs）排放强度减少14.4%,基准情境下2030年和2050年推广纯电动泥头车GHGs累计减排量分别为71.4万t和258.5万t.尽管节能减排效果显著,但其初始购置和售后维保成本 过高是制约其推广的最主要因素,通过降低车辆及电池生产制造成本、提高充换电设施数量及售后维保能力等有望加快泥头车纯电动化.     

Relating meteorological variables and trends in motor vehicle emissions to monthly urban carbon monoxide concentrations

A model which quantifies the relationship between the monthly time series for CO emissions, the monthly time series in ambient CO concentration, and meteorologically driven dispersion was developed. Fifteen cities representing a wide range of geographical and climatic conditions were selected. An eight-year time series (1984–1991 inclusive) of monthly averaged data were examined in each city. A new method of handling missing ambient concentration values which is designed to calculate city-wide average concentrations that follow the trend seen at individual monitor sites is presented. This method is general and can be used in other applications involving missing data. The model uses emissions estimates along with two meteorological variables (wind speed and mixing height) to estimate monthly averages of ambient air pollution concentrations. The model is shown to have a wide range of applicability; it works equally well for a wide range of cities that have very different temporal CO distributions. The model is suited for assessing long-term trends in ambient air pollutants and can also be used for estimating seasonal variations in concentration, estimation of trends in emissions, and for filling in gaps in the ambient concentration record.