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用于工程纳米材料库存和释放流的动态模型。

Dynamic Model for the Stocks and Release Flows of Engineered Nanomaterials.

机构信息

Bren School of Environmental Science and Management, University of California , Santa Barbara, California 93106-5131, United States.

出版信息

Environ Sci Technol. 2017 Nov 7;51(21):12424-12433. doi: 10.1021/acs.est.7b01907. Epub 2017 Oct 25.

Abstract

Most existing life-cycle release models for engineered nanomaterials (ENM) are static, ignoring the dynamics of stock and flows of ENMs. Our model, nanoRelease, estimates the annual releases of ENMs from manufacturing, use, and disposal of a product explicitly taking stock and flow dynamics into account. Given the variabilities in key parameters (e.g., service life of products and annual release rate during use) nanoRelease is designed as a stochastic model. We apply nanoRelease to three ENMs (TiO, SiO and FeO) used in paints and coatings through seven product applications, including construction and building, household and furniture, and automotive for the period from 2000 to 2020 using production volume and market projection information. We also consider model uncertainties using Monte Carlo simulation. Compared with 2016, the total annual releases of ENMs in 2020 will increase by 34-40%, and the stock will increase by 28-34%. The fraction of the end-of-life release among total release flows will increase from 11% in 2002 to 43% in 2020. As compared to static models, our dynamic model predicts about an order of magnitude lower values for the amount of ENM released from this sector in the near-term while stock continues to build up in the system.

摘要

大多数现有的工程纳米材料 (ENM) 生命周期释放模型都是静态的,忽略了 ENM 的库存和流动的动态变化。我们的模型 nanoRelease 明确考虑了库存和流动动态,从制造、使用和产品处置中估算 ENM 的年排放量。鉴于关键参数的可变性(例如,产品的使用寿命和使用期间的年释放率),nanoRelease 被设计为随机模型。我们使用生产数量和市场预测信息,将 nanoRelease 应用于 2000 年至 2020 年期间在建筑和建筑、家庭和家具以及汽车等七种产品应用中使用的三种纳米材料(TiO、SiO 和 FeO)。我们还使用蒙特卡罗模拟考虑模型不确定性。与 2016 年相比,2020 年 ENM 的年总排放量将增加 34-40%,存量将增加 28-34%。使用寿命结束时的释放量在总释放流中的份额将从 2002 年的 11%增加到 2020 年的 43%。与静态模型相比,我们的动态模型预测在短期内,该行业释放的 ENM 数量要低一个数量级,而系统中的库存仍在不断增加。

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