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综合美国数据库和模型,研究乙醇混合对规定的排气管排放的影响。

Comprehensive US database and model for ethanol blend effects on regulated tailpipe emissions.

机构信息

Environmental Health & Engineering, Inc., Newton, MA, USA.

Environmental Health & Engineering, Inc., Newton, MA, USA; The Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA.

出版信息

Sci Total Environ. 2022 Mar 15;812:151426. doi: 10.1016/j.scitotenv.2021.151426. Epub 2021 Nov 6.

Abstract

Particulate matter (PM), oxides of nitrogen (NOx), carbon monoxide (CO), and total hydrocarbons (THC) in gasoline exhaust affect atmospheric quality, and hence human health. Ethanol produced from corn grain is a renewable resource with favorable anti-knock properties for gasoline blending. Refiners alter petroleum composition to produce a finished blend that meets specifications. Ethanol blending affects emissions from market fuels both directly and indirectly since aromatics are typically removed from the BOB as ethanol is added to reach a constant octane rating. Numerous studies have been conducted to assess the effect of ethanol blending on light duty vehicle emissions. However, few studies have examined market fuel blends directly and small studies yield insufficient information to be generally applicable. If blending of fuels for a study does not yield gasoline that adequately resembles the composition of a market blend, the generalizability of study results may be impacted by nonlinear blending effects. Most vehicle-based fuel effect studies employed fuel formulations that either facilitate examination of several fuel variables or blend ethanol into a baseline gasoline (splash blending). Such study results do not support direct quantification of emissions inventory effects. To examine real world blending implications on regulated emissions [PM, NOx, CO, THC], we compiled a comprehensive database of US emission studies, developed regression models based on fuel and vehicle properties, and used those models to estimate differences in emissions from expected market fuel compositions. We addressed nonlinear responses to ethanol composition by modeling both low (up to 10% ethanol by volume) and mid blends (split models). We used the Federal Test Procedure (FTP) and Unified Cycle (LA92) driving schedule data, with the cold-start eliciting the highest emissions. PM cold-start emissions were lower with higher ethanol content, and more so at higher blend levels but hot-running emissions showed no differences with respect to ethanol level. For all emissions, the effects differed between port fuel injection (PFI) and gasoline direct injection (GDI) powered vehicles and for NOx, CO and THC there were differences between comphrehensive and split models. NOx results varied over blend levels and THC results were scattered for the higher blends. CO emissions were lower with higher ethanol content in nearly all cases for PFI but only the hot-running GDI. Results did not differ between summer regular and premium fuels. To the extent that PFI and GDI models differ, an emissions inventory calculation should treat them separately. There is uncertainty directly associated with the regression process, and with model inputs since study methods vary and compositions are reported differently between laboratories and test methods. Small changes in modeled emissions should be considered in this light.

摘要

颗粒物 (PM)、氮氧化物 (NOx)、一氧化碳 (CO) 和汽油废气中的总碳氢化合物 (THC) 会影响大气质量,从而影响人类健康。由谷物制成的乙醇是一种可再生资源,具有良好的抗爆性能,可用于汽油调合。炼油商改变石油成分,以生产符合规格的成品调合油。乙醇调合会直接和间接影响市场燃料的排放,因为随着乙醇的添加以达到恒定的辛烷值,芳烃通常会从 BOB 中去除。已经进行了许多研究来评估乙醇调合对轻型车辆排放的影响。然而,很少有研究直接检查市场燃料调合,而小规模研究提供的信息不足以普遍适用。如果研究中的燃料调合不能产生足够类似于市场调合组成的汽油,则研究结果的可推广性可能会受到非线性调合效应的影响。大多数基于车辆的燃料效应研究采用的燃料配方要么便于检查几个燃料变量,要么将乙醇混入基础汽油中(飞溅混合)。这种研究结果不能支持对排放清单效应的直接量化。为了研究实际的混合对法规排放[PM、NOx、CO、THC]的影响,我们编制了一份美国排放研究的综合数据库,基于燃料和车辆特性开发了回归模型,并使用这些模型估计了预期市场燃料成分差异的排放。我们通过对低(体积比最高可达 10%的乙醇)和中混合(分裂模型)进行建模来解决对乙醇成分的非线性响应。我们使用联邦测试程序 (FTP) 和统一循环 (LA92) 驾驶周期数据,冷启动会引发最高排放。随着乙醇含量的增加,PM 的冷启动排放降低,在更高的混合水平下更是如此,但热运行排放与乙醇水平无关。对于所有排放物,端口燃油喷射 (PFI) 和汽油直接喷射 (GDI) 车辆之间的影响不同,对于 NOx、CO 和 THC,综合和分裂模型之间存在差异。NOx 结果随混合水平而变化,THC 结果在较高的混合水平上分散。对于 PFI,几乎所有情况下乙醇含量较高的 CO 排放量都较低,但只有热运行的 GDI 排放量较高。夏季普通汽油和优质汽油的结果没有差异。在 PFI 和 GDI 模型存在差异的情况下,排放清单计算应将它们分开处理。回归过程直接存在不确定性,模型输入也存在不确定性,因为研究方法不同,实验室和测试方法之间的成分报告也不同。在这种情况下,应考虑模型排放量的微小变化。

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