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Sensitivity analysis of an ammonium salt formation model applied to pollutant removal in marine diesel exhaust gases
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Process Technology.ORCID iD: 0000-0001-6842-7543
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Process Technology.ORCID iD: 0000-0002-6326-4084
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Process Technology.ORCID iD: 0000-0001-5886-415X
(English)Manuscript (preprint) (Other academic)
Abstract [en]

This study presents the sensitivity analysis of the aerosol model for ammonium salt particle formation from NOx and SOx pollutants for low-temperature gas cleaning applications developed by Olenius et al. (2021). Starting from the acid gases derived from NOx and SOx (i.e. HNO3 and H2SO4), the numerical model simulates different particle growth phenomena as the acids react with ammonia (NH3). In the present study, the aerosol model uncertainty is analyzed systematically for the first time through a global sensitivity analysis employing the Sobol' method. The first- and total-order effects of five different input variables on model outputs such as particle size distribution, pollutant removal effectiveness, ammonia slip, and total run time are reported. Furthermore, the range of input parameters for which the model is tested is made to emulate the realistic operations experienced by low-speed two-stroke marine diesel engine ships burning fuel with high sulfur content. The sources of uncertainty are reviewed in detail to provide a holistic yet more complete view of the knowledge gaps in the particle conversion process.

National Category
Chemical Process Engineering
Identifiers
URN: urn:nbn:se:kth:diva-311571OAI: oai:DiVA.org:kth-311571DiVA, id: diva2:1654949
Note

QC 20220503

Submitted to Environmental Modelling & Software

Available from: 2022-04-29 Created: 2022-04-29 Last updated: 2023-07-19Bibliographically approved
In thesis
1. In pursuit of clean air through numerical simulations of no-waste pollutant removal
Open this publication in new window or tab >>In pursuit of clean air through numerical simulations of no-waste pollutant removal
2022 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

As epidemiological evidence continues to mount, it has become undeniable that exposure to high levels of airborne pollutants such as SOx and NOx are detrimental to human health. In recent years, millions of premature deaths by stroke, coronary heart disease, and lung cancer worldwide have been linked to poor outdoor air quality.

Unfortunately, not all polluting industries have faced the same stringent regulations. For instance, restrictions on harmful pollutant emissions from road vehicles have remained higher than those from marine transport. This discrepancy between sectors is expected to shrink as an increasing number of industries come into the spotlight of regulators. In this rapidly changing landscape, the demand for effective and innovative pollution abatement solutions is rising.

In the present work, our focus is on investigating the viability of a novel airborne pollutant removal concept. In this no-waste design, SOx and NOx are trapped into ammonium salt particles that can be then sold as an agricultural fertilizer. The gaseous pollutants are first oxidized by ozone, which is then mixed with ammonia in humid air to allow the ammonium particles to form and grow.

The study of this system requires analyzing the interplay between chemical reactions and the turbulent fluid dynamics that enables them through efficient mixing. To this end, numerical simulations are an invaluable tool that facilitates uncovering detailed knowledge where experimental studies may be intractable. Here, we leverage the use of high-fidelity large-eddy simulations to study reactive and non-reactive flow conditions relevant to this multi-pollutant removal solution. These investigations are supplemented by reactor modeling approaches to analyze specific key chemical processes. Finally, we implement and employ state-of-the-art data-driven methods that provide enhanced insight into our numerical datasets. For this purpose, we apply proper orthogonal decomposition, a machine-learning workflow for automated region identification, and global sensitivity analysis.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2022. p. 309
Series
TRITA-SCI-FOU ; 2022:11
Keywords
Air quality, SOx and NOx removal, Ozone oxidation, Aerosol particle formation, Large-eddy simulations, Reactive flows, Proper orthogonal decomposition, Machine learning, Sensitivity analysis
National Category
Mechanical Engineering
Research subject
Engineering Mechanics
Identifiers
urn:nbn:se:kth:diva-311573 (URN)978-91-8040-209-5 (ISBN)
Public defence
2022-05-23, https://kth-se.zoom.us/j/61833102899, H1, Teknikringen 33, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 220502

Available from: 2022-05-02 Created: 2022-04-29 Last updated: 2022-06-25Bibliographically approved

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Rovira, MarcEngvall, KlasDuwig, Christophe

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