Hyper-local scale air quality modelling Fernando Martín & José Luis Santiago CIEMAT
What means hyperlocal-scale modelling? • “ Hyper- Local scale modelling” refers to air quality modelling at high spatial resolution (typically order of meter scale), usually focused on urban environments. • These type of applications include – Computational Fluid Dynamics (CFD) models – More simplified tools like street box models or parameterized Gaussian plume models. Urban Zone Rural Zone Local Sources Urban Background Regional Background Natural Background
History • Recently, some FAIRMODE participants expressed the need for more guidance and exchange of best practices in “hyper - local scale” AQ modelling. • Steering Group decided to investigate to what extent FAIRMODE could provide support. • 2014-2017. FAIRMODE exercises related to spatial representativeness, in which some micro-local scale modelling was applied. • Some sessions in former FAIRMODE meetings, – Athens, 2017, first contact among few interested people on CFD modelling, – Tallin, 2018, special session on CFD modelling with more than 25 people attending. CFD gained attention for practical application linked to the AQD. FAIRMODE is good for exchange ideas and best practices, provide guidance… – Warsaw, 2019, CFD is quite interesting topic but competence building and benchmarking are yet necessary • HARMO (Bologna, 2017). Meeting of the FAIRMODE people (about 5 groups involved) • Previous guidance and model comparisons: – COST ACTION 732 (microscale meteorological models), 2005-2009 – COST ES1006 (local-scale emergency) 2011-2015
Priority topics: NCP survey
Questionnaire • A short questionnaire was sent to a short group of people who previously has shown some interest in very high resolution modelling and it is well-known they are working on it. • Objective: a first step to clarify the relevance of the topic in the context of FAIRMODE with the aim to support the discussions during the technical meeting in Madrid. • Questions: 1. About relevance and purpose. 2. Tools 3. Expected support from FAIRMODE 4. Participation in this group
Results 9 responses: • VITO (Bino Maiheu), BELGIUM • IVU Umwelt GmgH (Florian Pfafflin), GERMANY • RIVM (Joost Wesseling), THE NETHERLANDS • City of Stockholm (Kristina Eneroth), SWEDEN • COWI AB (Marie Haeger Eugensson), SWEDEN • Aarhus University (Matthias Ketzel & Ulas Im), DENMARK • Government of Styria (Dietmar Oettl), AUSTRIA • University of Aveiro (Vera Rodrigues & Alexandra Monteiro), PORTUGAL • CIEMAT (Fernando Martin & Jose Luis Santiago), SPAIN
Results. Question 1. • How relevant is hyperlocal scale modelling for you in the framework of the Air Quality Directive? – YES for all. Someone said “very relevant” – Someone said: “ it is possibly even more relevant than all the other "large-scale" modelling as limit values are (mostly) exceeded at the local level (hot-spots) and all the effort in large- scale modelling often serves only to provide background concentrations for local applications ” • What is the purpose of this type of modelling applications (assessment, planning, population exposure, spatial representativeness of AQ stations…)? – Assessment. 8 – Planning. 6 – Population exposure. 6 – Spatial representativeness. 5 – Support for compliance to EU regulations. 1 – Impact of emissions on air quality. 1 – Source apportionment. 1 – Validation of sensors. 1
Results. Question 2. • What kind of modelling tools (CFD model, parametric models, street box models, others) are you using for the hyperlocal scale modelling? – Complex models: 8 groups • CFD models (Open FOAM, MISKAM, FLUENT, STAR CCM, VADIS, GRAL, …) 8 • Lagrangian models 2 – Simplified models: 6 groups • Parametric models – street box models (OSPM,…) 4 • Gaussian models (AERMOD, URBAIR, OML Multi) - Line- based models (OML Highway) 4 • Others (Dutch OSP model) 1
Results. Question 3 (1/3) • What kind of support would you expect from FAIRMODE for the hyperlocal scale modelling? – Benchmarking. Model Quality Objectives. Comparison. • Model validation. Adaptation of FAIRMODE tools (Delta) • Methodologies for compute AQ indicators (i.e. annual averages). • Spatial representativeness, planning – Collecting good practices. Recommendations. Guidance. • How to use high resolution models especially CFD. Boundary conditions, background concentrations • Model Validation • Methodologies for compute AQ indicators. Reporting exceedances • Population exposure, spatial representativeness, planning – Harmonisation • Methodologies for compute AQ indicators • Reporting exceedances
Results. Question 3 (2/3) • What kind of support would you expect from FAIRMODE for the hyperlocal scale modelling? – Discussion • Planning • Model uncertainties • Population exposure • Air quality assessment. Reporting exceedances – Providing/improving input data. Checking input data quality. • Urban morphology of the European cities; • High resolution emission data (methodologies for computing them) • Hourly meteorological data (COPERNICUS) – Hyperlocal scale composite mapping
Results. Question 3 (3/3) • To what extent is the guidance already provided by FAIRMODE (e.g. Modelling Quality Objective,…) insufficient for this type of applications? – No one answered directly this question but someone pointed it is good to review and adapt some FAIRMODE guides and tools (for example DELTA tool) – Others suggests to follow some existing guides from COST732 or national guides (Sweden)
Results. Question 4. • Would you contribute to an activity on hyperlocal scale modelling within FAIRMODE (provided that the previous questions point to a real need)? – Yes 2 – Yes, depending on activity 1 – Yes, limited by funding or personal resources 5 – Yes, but not sure 1 – No 0
Other remarks • Some people suggest to rethink the term “Hyper - Local” choosing other more known term (microscale, micro local scale, street scale, etc…) • Do we agree that an specific group on Hyper Local Scale modelling must be created in FAIRMODE? • If YES, what can we do?
Discussion Topics FAIRMODE contributions • • Modelling. Input data. Boundary Discussion conditions • Good practices • Model uncertainties & validation • Model Quality Objectives • AQ indicators estimates • Bechmarking. Comparison • AQ assessement • Recomendations. Guidance • Reporting exceedances • Providing tools and data • AQ planning • Harmonisation • Population exposure estimate • Competence building • Spatial representativeness • Mapping • Validation of sensors
Validation of sensors Mapping X Reporting X X exceedances Spatial X X representativeness Population X X Exposure AQ X X X Planning AQ assessment X AQ indicator X X X estimates validation & X X X X uncertainties Input data X X X X Boundary Conditions CONTRIBUTIONS Recommendations Providing tools TOPICS Good practices Harmonisation Benchmarking Competence FAIRMODE Discussion Guidance building & data MQO-
Discussion on work proposal Current Good Practices Discussion Modelling 1 Conclussions Validation AQ indicators What is needed to do? Specific applications MQO Recomendations 2 Benchmarking Guidance Comparison Harmonisation Input data base (urban Tools morphology, emission data,) 3 Boundary conditions
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