Header

UZH-Logo

Maintenance Infos

A Dynamic Probabilistic Material Flow Modeling Method for Environmental Exposure Assessment


Bornhöft, Nikolaus Alexander. A Dynamic Probabilistic Material Flow Modeling Method for Environmental Exposure Assessment. 2017, University of Zurich, Faculty of Economics.

Abstract

Simulation modelling is an important tool for assessing the environmental level of a pollutant. By modelling the flow of anthropogenic substances from the technosphere into the ecosphere and through several environmental compartments, the concentrations of these in air, water and soil can be estimated. These values are a fundamental requirement for any estimation of environmental hazard and risk posed by a chemical or substance. In general, the input data needed for such models is uncertain and determining reliable values for environmental stocks and flows using a mass-flow model is a challenge. That is why Material flow Analysis (MFA) needs methods and tools to deal with this uncertainty. In static cases, this can be done via Probabilistic Material Flow Analysis (PMFA). But processes including time-dynamic behaviour cannot be handled with this. Therefore, the present thesis presents Dynamic Probabilistic Material Flow Analysis (DPMFA) as a new approach to close this gap. It includes:
– a mass balanced stock and flow representation,
– time-dynamic system behaviour and discrete period based time progress, and
– explicit uncertainty representation and propagation
In DPMFA, the existing Probabilistic Material Flow Analysis (PMFA) is linked to dynamic modelling means. In PMFA a system of dependent material flows is assumed to be in equilibrium for the investigated period (e.g. a year). Incomplete system knowledge is represented as Bayesian parameter distributions. On this basis, the dependent model variables (such as environmental stocks) are derived using Monte-Carlo simulation. To introduce dynamic behaviour of a system over a longer time span, in DPMFA, the flows of subsequent periods need to be calculated and the material accumulations in the sinks have to be added up. External inflows are considered for each period individually and intermediate delays are represented as stocks with specific release functions. As a result, environmental pollutant concentrations and exposures are determined based on the absolute material amounts in stocks. In addition to the theoretical modelling approach, a respective modelling-package in Python was implemented and provided1. The tool enables application experts from different fields to develop models for their domain.
One important application field for this approach is the assessment of new substances such as engineered nano-materials (ENM), which are used in a growing number of products. At present, there are no analytic methods available to quantify environmental concentrations of ENM. Most of them are long-lasting, so they can accumulate in the ecosphere over a longer time period. This qualifies the modelling and simulation of ENM flows as suitable example of use to demonstrate the new approach.
We describe the development and application of DPMFA in the form of four scientific articles, which constitute the core of this thesis. Article I (Chapter 2) presents the specific requirements for the new modelling approach and implements a small example model using several existing modelling approaches to identify their possibilities and limitations. In article II (Chapter 3), the new approach is theoretically developed in detail and then exemplarily applied in a case-study to assess the environmental concentrations of Carbon Nanotubes (CNT) in Switzerland. The new approach is further specified in Article III (Chapter 4). In particular, the representation of incomplete knowledge from several data sources, model-robustness regarding design decisions, as well as sensitivityand uncertainty analyses are discussed and resulting implications on the model and the investigated system are highlighted. A comprehensive application of the approach was performed in a modelling study in Article IV (Chapter 5). This way, the approach has been validated by applying it to realistic cases. These are modelling the concentrations of the materials nano-TiO2, nano-ZnO, nano-Ag and CNT in the European Union. For each of the materials the concentrations in surface water, sediment, natural and urban soil, sludge treated soil and air have been estimated for the year 2014. Thereby, the appropriateness of the approach could be proved for the investigated class of exposure models.

Abstract

Simulation modelling is an important tool for assessing the environmental level of a pollutant. By modelling the flow of anthropogenic substances from the technosphere into the ecosphere and through several environmental compartments, the concentrations of these in air, water and soil can be estimated. These values are a fundamental requirement for any estimation of environmental hazard and risk posed by a chemical or substance. In general, the input data needed for such models is uncertain and determining reliable values for environmental stocks and flows using a mass-flow model is a challenge. That is why Material flow Analysis (MFA) needs methods and tools to deal with this uncertainty. In static cases, this can be done via Probabilistic Material Flow Analysis (PMFA). But processes including time-dynamic behaviour cannot be handled with this. Therefore, the present thesis presents Dynamic Probabilistic Material Flow Analysis (DPMFA) as a new approach to close this gap. It includes:
– a mass balanced stock and flow representation,
– time-dynamic system behaviour and discrete period based time progress, and
– explicit uncertainty representation and propagation
In DPMFA, the existing Probabilistic Material Flow Analysis (PMFA) is linked to dynamic modelling means. In PMFA a system of dependent material flows is assumed to be in equilibrium for the investigated period (e.g. a year). Incomplete system knowledge is represented as Bayesian parameter distributions. On this basis, the dependent model variables (such as environmental stocks) are derived using Monte-Carlo simulation. To introduce dynamic behaviour of a system over a longer time span, in DPMFA, the flows of subsequent periods need to be calculated and the material accumulations in the sinks have to be added up. External inflows are considered for each period individually and intermediate delays are represented as stocks with specific release functions. As a result, environmental pollutant concentrations and exposures are determined based on the absolute material amounts in stocks. In addition to the theoretical modelling approach, a respective modelling-package in Python was implemented and provided1. The tool enables application experts from different fields to develop models for their domain.
One important application field for this approach is the assessment of new substances such as engineered nano-materials (ENM), which are used in a growing number of products. At present, there are no analytic methods available to quantify environmental concentrations of ENM. Most of them are long-lasting, so they can accumulate in the ecosphere over a longer time period. This qualifies the modelling and simulation of ENM flows as suitable example of use to demonstrate the new approach.
We describe the development and application of DPMFA in the form of four scientific articles, which constitute the core of this thesis. Article I (Chapter 2) presents the specific requirements for the new modelling approach and implements a small example model using several existing modelling approaches to identify their possibilities and limitations. In article II (Chapter 3), the new approach is theoretically developed in detail and then exemplarily applied in a case-study to assess the environmental concentrations of Carbon Nanotubes (CNT) in Switzerland. The new approach is further specified in Article III (Chapter 4). In particular, the representation of incomplete knowledge from several data sources, model-robustness regarding design decisions, as well as sensitivityand uncertainty analyses are discussed and resulting implications on the model and the investigated system are highlighted. A comprehensive application of the approach was performed in a modelling study in Article IV (Chapter 5). This way, the approach has been validated by applying it to realistic cases. These are modelling the concentrations of the materials nano-TiO2, nano-ZnO, nano-Ag and CNT in the European Union. For each of the materials the concentrations in surface water, sediment, natural and urban soil, sludge treated soil and air have been estimated for the year 2014. Thereby, the appropriateness of the approach could be proved for the investigated class of exposure models.

Statistics

Downloads

2 downloads since deposited on 14 Feb 2018
2 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Dissertation
Referees:Hilty Lorenz, Nowack Bernd
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Date:2017
Deposited On:14 Feb 2018 15:05
Last Modified:20 Sep 2018 04:29
Number of Pages:179
OA Status:Closed
Other Identification Number:merlin-id:16019

Download