A generic approach to construct pseudo components for oil weathering models

A generic approach to construct pseudo components for oil weathering models
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构建石油风化模型伪组件的通用方法

DOI:
10.1016/j.jhazmat.2023.132160
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发表时间:
2023
影响因子:
13.6
通讯作者:
Lee, Kenneth
Lee, Kenneth
中科院分区:
环境科学与生态学1区
文献类型:
--
作者:
Geng, Xiaolong;Barker, Christopher H.;MacFadyen, Amy;Boufadel, Michel C.;Thrift-Viveros, Dalina L.;Jones, Robert K.;O’Connor, Caitlin;Lee, Kenneth

文献摘要

相似文献

溢油风化模型是预测溢油在环境中行为的基础。大多数模型使用“伪组分”(PC)方法来表示石油产品中发现的各种化合物。在该方法中,不是对油中的每个单独的化合物进行建模,而是开发了代表整个化合物类别的可管理数量的PC。然而,以前的研究主要集中在传统的原油,并没有开发出一种通用的方法来创建一个最佳的PC集的各种油。在开发更新的NOAA石油风化模型,我们在这里提出了一个通用的方法来构建PC使用石油蒸馏数据来捕捉石油蒸发风化的复杂性。我们用来自溢油自动数据查询(ADIOS)油库的899种油验证了我们的方法,并发现应使用16台PC的最佳设置。这些PC包括两个低沸点(低于144 °C),一个高沸点(高于400 °C),以及十三个在中间沸点范围内构建的温度分辨率为20 °C。我们的模拟测试表明,这一套十六个PC充分表征各种各样的油的油蒸发过程。
Oil weathering models are essential for predicting the behavior of spilled oil in the environment. Most models use a “Pseudo Component” (PC) approach to represent the wide range of compounds found in petroleum products. Within the approach, rather than modeling each individual compound in an oil, a manageable number of PCs are developed that represent whole classes of compounds. However, previous studies focused mainly on traditional crude oils and did not develop a generic approach to create an optimal set of PCs for a variety of oils. In developing the updates to the NOAA oil weathering model, we propose herein a generic approach to construct PCs using oil distillation data to capture the complexity of oil evaporative weathering. We validated our approach with 899 oils from the Automated Data Inquiry for Oil Spills (ADIOS) oil library and found that an optimal set of sixteen PCs should be used. These PCs include two with low boiling point (below 144 °C), one with a high boiling point (above 400 °C), and thirteen constructed within a middle range of boiling points with a temperature resolution of 20 °C. Our simulation tests suggested that this set of sixteen PCs adequately characterizes oil evaporation processes for a wide variety of oils.