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Chemical Property Estimation Techniques for Environmental Modeling

机译:用于环境建模的化学性质估算技术

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Mathematical modeling of chemical fate provides an excellent framework for sorting out massive quantities of environmental data in an organized way. Parameters in a model may be varied to gain an understanding as to what processes are most important in determining the environmental behavior of a chemical. One of the most useful modeling approaches integrates data on physical-chemical properties of the compound in question with hydrodynamic or aerodynamic transport models. The approach employs the results of such laboratory measurements as aqueous solubility, saturation vapor pressure, liquid and vapor molecular diffusivity, Henry's law constant, UV-adsorption spectra, octanol-water partition coefficient, photolysis rate, microbial degradation rate, etc. These data are then incorporated into various steady-state or time dependent fate models. In recent applications of these models to simulate the environmental behavior of PCBs, PCDDs, PCDFs, and other chlorinated aromatic hydrocarbons (CAHs) in the Great Lakes, it quickly became obvious that much of the aforementioned data are lacking. While property estimation techniques have been used extensively in the fields of chemical engineering and pharmacology, the data base for the CAHs has not been of sufficient quality and quantity to test these procedures. However, recent work has produced high quality and self consistent data on aqueous solubilities, saturation vapor pressures, and octanol-water partition coefficients for the CAHs. In this paper we present a summary of some of the more useful estimation techniques for aqueous solubilities and vapor pressures. This is followed by an examination as to how well these techniques work for compounds whose aqueous solubilities and saturation vapor pressures range down to10^{-13}M and10^{-10}atm.
机译:化学结局的数学建模为以有组织的方式整理出大量环境数据提供了一个极好的框架。可以更改模型中的参数以了解哪些过程对确定化学品的环境行为最重要。一种最有用的建模方法是将有关化合物的物理化学性质的数据与流体动力学或空气动力学传输模型集成在一起。该方法采用实验室测量的结果,例如水溶性,饱和蒸气压,液体和蒸气分子扩散率,亨利定律常数,紫外线吸收光谱,辛醇-水分配系数,光解速率,微生物降解率等。这些数据是然后结合到各种稳态或时间相关的命运模型中。在这些模型的最新应用中,以模拟五大湖地区的PCBs,PCDDs,PCDFs和其他氯化芳烃(CAHs)的环境行为,很快就很明显缺少上述数据。尽管属性估计技术已在化学工程和药理学领域广泛使用,但CAH的数据库仍没有足够的质量和数量来测试这些程序。但是,最近的工作已经获得了有关CAHs的水溶性,饱和蒸汽压和辛醇-水分配系数的高质量且自洽的数据。在本文中,我们对水溶解度和蒸气压的一些更有用的估算技术进行了总结。接下来是对这些技术对水溶解度和饱和蒸气压低至 10 ^ {-13} M和 10 ^ {-10} < / tex> atm。

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