Management of occupational exposure to engineered nanoparticles through a chance-constrained nonlinear programming approach.

Abstract:

:Critical environmental and human health concerns are associated with the rapidly growing fields of nanotechnology and manufactured nanomaterials (MNMs). The main risk arises from occupational exposure via chronic inhalation of nanoparticles. This research presents a chance-constrained nonlinear programming (CCNLP) optimization approach, which is developed to maximize the nanaomaterial production and minimize the risks of workplace exposure to MNMs. The CCNLP method integrates nonlinear programming (NLP) and chance-constrained programming (CCP), and handles uncertainties associated with both the nanomaterial production and workplace exposure control. The CCNLP method was examined through a single-walled carbon nanotube (SWNT) manufacturing process. The study results provide optimal production strategies and alternatives. It reveal that a high control measure guarantees that environmental health and safety (EHS) standards regulations are met, while a lower control level leads to increased risk of violating EHS regulations. The CCNLP optimization approach is a decision support tool for the optimization of the increasing MNMS manufacturing with workplace safety constraints under uncertainties.

authors

Chen Z,Yuan Y,Zhang SS,Chen Y,Yang FL

doi

10.3390/ijerph10041231

subject

Has Abstract

pub_date

2013-03-26 00:00:00

pages

1231-49

issue

4

eissn

1661-7827

issn

1660-4601

pii

ijerph10041231

journal_volume

10

pub_type

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