Feedback from Working Group

Transcription

1 Air Quality Modelling Framework: Feedback from Working Group Presentation to the Air Quality Lekgotla 13 October 2010 Limpopo Province: The Ranch Hotel Polokwane Presented by: Dr. Patience Gwaze Atmospheric Quality Information Department of Environmental Affairs

2 Purpose of workshop Sharea a common understanding On guideline strategy based on the multi stakeholders workshop held on July 30 On guideline framework based on the Working Group 1 st workshop held on August 27 Timeframe for modellingguideline guideline and regulations Annual Lekgotla workshops as needs arise Provide clarification in the application of models Solicit review of guideline from the technical and user community Identify gaps in the guideline/modelling applications Communication with stakeholders through DEA

3 Outline of presentation Brief background Feedback from workshops Multi stakeholders tkhld workshop kh July 30 Baseline assessment Guideline framework August 27 Way forward Discussion

4 Guideline objectives Recommend appropriate and acceptable techniques and datasets for regulatory AQ modelling Standardise model applications for regulatory purposes p Ensure consistency and equity in applications Procedures, possibilities and limitations Create confidence and transparency of appropriate model applications Encourage applications of the best available science in regulatory practices fit for purpose

5 1 st MSTH Workshop 30 July Attendees: 60 Government and Metro representatives Industry Environmental consultancies Invitation ti extended dto AQO in DEA dtb database

6 Outcomes 1 st MSTH Workshop 30 July A shared understanding between the DEA and stakeholders on the strategy regulated system Establishment of an Air Quality Modelling Working Group Volunteering modelling experts from government and its agencies, industries, environmental consultancies and the academia Review committee nominated Prof. Jesse Thé offered to review the final work probono

7 Guideline development process Working Group chaired by DEA Coordinated/guideline by DEA Holding quarterly workshops till end of 2011

8 Debating points from 1 st workshop Framework approach non/certified modellers Evaluation/validation of models in the modelcentred approach Capacity development component Working Group bias International and external experts reviewers SAWS and other experts participation p

9 Baseline study questionnaire responses

10 Baseline assessment (20) Organisation Dispersion models Meteorological data Emissions inventory Terrain Airshed Planning Professionals AERMOD, ADMS, CALPUFF Hawk SAWS data, Unified Model data In-house Google or as supplied by clients C&M Consulting AERMOD SAWS In-house --- Engineers Environgaka CC AERMOD, CALPUFF --- In-house DEM Esciences SCREEN3, CALPUFF SAWS, Eskom, WRF, In-house USGS TAPM Gondwana Environmental Solutions AERMOD, ADMS, CALPUFF SAWS and ARC (purchased) or Ambient AQ Network In-house GTOPO City (1km Res), SRTM SGS Consultancy Screen 3, ALOHA, Local meteorological In house, third party and Shuttle Radar AERMOD, Hawk stations, SAWS and client MM5 umoya-nilu Consulting CALPUFF, SCREEN 3, TAPM, AirQuis i SAWS, TAPM In-house from process data; Direct measurements or inventory supplied by the client. WSP Environmental SCREEN3, ADMS & SAWS, onsite In-house, direct AERMOD measurements WardKarlson Consulting Breeze AERMOD, Screen 3, DMRB and Caline SAWS, ADM Ltd (UK), Trinity Consultants (US) In-house from process data; Direct measurements or inventory supplied by the client Topography Mission (SRTM) data (90m resolution) USGS DEM, SA? ADM Ltd

11 Baseline assessment (20) Organisation Dispersion models Meteorological data Emissions inventory Terrain DEDET, Limpopo p NESCA Genii, CALPUFF, AERMOD Onsite Direct measurements -- AngloGold Ashanti AERMOD MM5 In-house In-house Eskom ADMS, CALPUFF, In-house, direct USGS TAPM measurements Impala Platinum AERMOD MM5, onsite, SAWS In-house Google Earth (Rustenburg) SASOL AERMOD, ADMS, On-site, TAPM, SAWS In-house, direct USGS CALPUFF, TAPM, SCREEN, LED, CMAx measurements Earth Resources Observation Systems Cape Town ADMS - Urban SAWS In-house with collaboration Ekhurhuleni ADMS SAWS In-house EThekwini Airquis In-house In-house Johannesburg ADMS In-house Nelson Mandela AERMOD in Enviman In-house met stations Mt Metro GIS

12 Typical modelling applications Environmentalimpact impact assessments Majority of regulatory applications on small scale, typically of < 10 km x 10 km Rarely over 100 km x 100 km Limited use of photochemical models

13 Working Group Workshop 1 August

14 Outcomes 1 st WG Workshop 27 August Attendees 20 participants from Working Group Agenda Share a common understanding on Recommended air quality models proposed Proposed guideline framework Task Teams and working procedures Task allocations

15 Recommended models Models Model Type Applications Screening Screen3 Gaussian Simple terrain CTSCREEN Gaussian Complex terrain Local to urban AERMOD Advanced Gaussian Near source <50 km CALPUFF Lagrangian puff Urban, local < 300km CAMx CMAQ Preferred models for Complex cases Eulerian photochemical O3, CO,PM2.5 long range dispersion model transport, complex pollutants transformations

16 Recommended models Public/local familiarity widely used in South Africa Capacity developments e.g., NACA courses Reasonable costs to users free source codes US EPA, Canada, Australia, New Zealand regulatory models Increased use in Europe

17 Future CALPUFF developments Improved interface with 3D data Enhanced support for WRF development SAWS Nested grid capability CALMET and CALPUFF Improved chemistry module CMAQ modules Inorganic particulate chemistry SOA formation Aqueous phase chemistry SO 2 oxidation John Si Scire, personal comm. 2010

18 Models for specialised cases Roadside modelling Fugitive dust emissions Odour cases Other specialised cases Conditions for using other models

19 Guideline framework Working Group TOC attached

20 Section 1: Introduction 1.1 Aims and Objectives of Guideline 1.2 Why Use Models? 1.3 NEMA: AQA (DEA) 1.4 Application of Models dlin Air Quality Management Environmental Impact Management Atmospheric Quality Report Other applications 1.5 Audience 1.6 Guideline Development and Review Processes 1.7 Scope and Structure of Guideline

21 1.4 Application of Models in Air Quality Suitability of models Management E.g., topo. and met complexities Level of sophistication Screening to complex model e.g., tier systems Screening guideline?? Regulatory requirements AEL, EIM Interrelationships between regulatory authorities and modellers e.g., AEL and EIA processes specialised cases, checklist

22 Section 2: Recommended Air Quality Models Summary of recommended models and their Summary of recommended models and their appropriate use

23 Section 3: Models Input Data 3. Models Input Data 3.1 Source Characterisation 3.2 Meteorological Data 3.3 Topography and Land Use Data Transparency and consistency

24 Section 3: Models Input Data 3. Models Input Data 3.1 Source Characterisation Source types Emission factors emission inventory guideline Full description of structures around source being modelled Stack, boiler, structural t parameters Operation conditions maximum emissions, upset conditions, batch processes, Background sources that might impact modelling domain Referencing of existing, approved future emissions Special attention to urban and Priority Area cases Natural sources?

25 Section 3: Models Input Data 3. Models Input Data 3.2 Meteorological Data Source of surface and upper airmeteorologicaldata SAWS, onsite data, other sources e.g., ARC QA/QC of meteorological data (e.g., missing values, averaging times etc) Length of record of meteorological data and averaging times (3 5 year complex/urban location, 1 year rural) Representativeness of meteorology to analysed domain Use of prognostic and diagnostic model outputs WRF, TAPM, UM

26 SAWS support Task Team 3 Support SAWS in the development & dissemination of met data Required data formatforthe the selected models Promote and facilitate the use of gridded MET data Long term objective for SAWS to provide gridded at a reasonable cost to users Recommendations to take up with SAWS

27 Section 4: General Modelling Considerations General Modelling Considerations 4.1 Boundary Conditions 4.2 Dispersion Coefficients 4.3 Plume Rise 4.4 Spatial and Temporal Resolutions 4.5 Building Downwash Effects 4.6 Chemical Transformation NO NO2 transformation 4.7Wetand Dry Deposition 4.8 Design concentrations Transparency and consistency

28 Section 5: Reporting Modelling Results Reporting Modelling Results 5.1 General Requirements for Reporting Standard template 5.2 Model Accuracy and Uncertainty 5.3 Use of Modelling Outputs in Combination with Monitoring Data 5.4 Compliance with NAAQS

29 Section 5: Reporting Modelling Results Reporting Modelling Results 5.1 General Requirements for Reporting Standard template Modelling protocol submission outline a checklist of requirements forreportreport writing and submission. A checklist of model inputs (Develop a template based on e.g., US EPA checklist?)

30 Section 5: Reporting Modelling Results Reporting Modelling Results 5.2 Model Accuracy and Uncertainty Use of model quality indicators (e.g., European guideline, see Borrego 2008) Quantitative indicators recommend specific statistical indicators sbased on observations o s Correlation coefficient Fractional bias Root mean square error (RMSE) Normalised mean square error (NMSE) Qualitative analysis graphic presentations Time series plots, etc.

31 Section 5: Reporting Modelling Results Reporting Modelling Results 5.3 Use of Modelling Outputs in Combination with Monitoring Data Whenever ambient data is available! How well does the model replicate maxima? How well does the model replicate the distributions of measurements?

32 Section 5: Reporting Modelling Results Reporting Modelling Results 5.4 Compliance with NAAQS Definitions of trivial criteria pollutants concentrations Identify percentile concentration of pollutants for different averaging times to relate to NAAQS Definition of compliance with a standard. Descriptions of violation of NAAQS for the different averaging times. Spatial and temporal distribution of violation e.g. based on sensitive receptors. Frequency of exceedance

33 Review and public commenting

34 Review process How far the guideline will have gone in addressing current challenges. If the proposed uses of recommended models for specific applications are appropriate/reasonable. it/ If resources required for these modelling systems exist. Ifever there willbe resources constrains imposed by the modelling systems proposed. If the regulatory officials will be capacitated to interrogate reports based on recommended systems. If there are any significant implementation issues still remain.

35 Way forward Activity Working Group 2nd workshop to finalise modelling regulations and guideline drafts. Expected Delivery Date February 2011 AQ modelling guideline e and regulations drafts presented to DEA. March2011 ac Working Group 3rd workshop to finalise modelling regulations and guideline. AQ modelling guideline and regulations presented to DEA for internal approval and commenting. AQ modelling guideline and regulations presented for public commenting and expert committee for review. May 2011 June 2011 July 2011 AQ modelling guideline and regulations final adoption and publication. October 2011.

36 Thank you!

37 Guideline long term regulatory benefits Assessment of existing air quality A supplementary, integrated or exclusive tool in evaluating AQ state, assessing impacts, exceedances Reducing monitoring cost benefits, Source apportionment Managing, mitigation and planning Effective implementation of AQ plans Exceedances mitigation Transboundary pollution (local, provincial, international) AQ forecasting