Development of the MEGAN3 BVOC Emission Model for Use with the SILAM Chemical Transport Model

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http://urn.fi/URN:NBN:fi-fe201804208685
Title: Development of the MEGAN3 BVOC Emission Model for Use with the SILAM Chemical Transport Model
Author: Foreback, Benjamin
Contributor: University of Helsinki, Faculty of Science, Department of Physics
Publisher: Helsingin yliopisto
Date: 2018
Language: eng
URI: http://urn.fi/URN:NBN:fi-fe201804208685
http://hdl.handle.net/10138/273490
Thesis level: master's thesis
Abstract: This project has aimed to investigate and propose improvements to the methods used in the System for Integrated ModeLing of Atmospheric coMposition (SILAM) model for simulating biogenic volatile organic compound (BVOC) emissions. The goal is to study an option in SILAM to use the Model for Emission of Gases and Aerosols in Nature, Version 3 (MEGAN3) as an alternative to SILAM’s existing BVOC calculation algorithm, which is a more simplified approach. SILAM is an atmospheric chemical transport, dispersion, and deposition modelling system owned and continuously developed by the Finnish Meteorological Institute (FMI). The model’s most well-known use is in forecasting air quality in Europe and southeast Asia. Although traffic and other urban emissions are important when modelling air quality, accurate modelling of biogenic emissions is also very important when developing a comprehensive, high-quality regional and sub-regional scale model. One of the motivations of this project is that if BVOC emission simulation in SILAM were improved, the improvements would be passed into subsequent atmospheric chemistry algorithms which form the molecules responsible to produce secondary organic aerosols (SOA). SOA have significant impacts on local and regional weather, climate, and air quality. The development in this project will therefore offer the potential for future improvement of air quality forecasting in the SILAM model. Because SILAM requires meteorological forecast as input boundary conditions, this study used output generated by the Environment-High Resolution Limited Area Model (Enviro-HIRLAM), developed by the HIRLAM Consortium in collaboration with universities in Denmark, Finland, the Baltic States, Ukraine, Russia, Turkey, Kazakhstan, and Spain. Enviro-HIRLAM includes multiple aerosol modes, which account for the effects of aerosols in the meteorological forecast. Running SILAM with and without the aerosol effects included in the Enviro-HIRLAM meteorological output showed that aerosols likely caused a minor decrease in BVOC emission rate. This project has focused on the boreal forest of Hyytiälä, southern Finland, the site of the Station for Measuring Ecosystem-Atmosphere Relations - II (SMEAR-II, 61.847°N, 24.294°E) during a one day trial on July 14, 2010. After performing a test run over the Hyytiälä region in July 2010 for analysis, it was found that SILAM significantly underestimates BVOC emission rates of both isoprene and monoterpene, likely because of an oversimplified approach used in the model. The current approach in SILAM, called ‘Guenther Modified’, uses only a few equations from MEGAN and can be classified as a strongly simplified MEGAN version, with selected assumptions. It references a land cover classification map and lookup table, taking into account only three parameters (air temperature, month, and solar radiation) when performing the calculations. It does not take into account several other important parameters, which affect the BVOC emission rates. Based on qualitative analysis, this appears to be a simplified but limited approach. Therefore, based on these findings, the next step to improve SILAM simulations is to propose a full implementation of MEGAN as a replacement to the current logic in SILAM, which is to use land classification and a lookup table for BVOC emission estimates. MEGAN, which is a much more comprehensive model for simulating BVOC emissions from terrestrial ecosystems. MEGAN includes additional input parameters, such as Leaf Area Index (LAI), relative humidity, CO2 concentration, land cover, soil moisture, soil type, and canopy height. Furthermore, this study found that in the future, simulations involving BVOCs could also potentially be improved in SILAM by adding modern schemes for chemical reactions and SOA formation in future development of SILAM. After gaining in-depth understanding of the strengths and limitations of BVOC in the SILAM model, as practical result, some recommendations for improvements to the model are proposed.


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