DOCSLIB.ORG

Comparison of the Performance of Two Atmospheric Dispersion Models (AERMOD and ADMS) for Open Pit Mining Sources of Air Pollution

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Comparison of the Performance of Two Atmospheric Dispersion Models (AERMOD and ADMS) for Open Pit Mining Sources of Air Pollution Comparison of the performance of two atmospheric dispersion models (AERMOD and ADMS) for open pit mining sources of air pollution By Martha Nyambali Neshuku Submitted as partial fulfilment of the requirements For Masters of Science in Applied Science: Environmental Technology In the Department of Chemical Engineering Faculty of Engineering, Built Environment and Information Technology University of Pretoria 2012 © University of Pretoria Comparison of the performance of two atmospheric dispersion models (AERMOD and ADMS) for open pit mining sources of air pollution Martha Nyambali Neshuku Supervisor: Dr. Gerrit Kornelius Department: Chemical engineering Faculty: Engineering, Built Environment and Information Technology Degree: Masters of Science in Applied Science: Environmental Technology Synopsis The performance of the AERMOD and ADMS dispersion models was tested using PM10 (thoracic dust) emissions from Rössing Uranium Mine open pit in Namibia. The performance of the two models was evaluated against the observations and also against each other using various statistical measures. The models were tested under different case scenarios (cases explained in chapter 4) with the aim of evaluating their performances as well as their inter model variability. The study was undertaken from the 13 July 2009 – 14 August 2009. The results from the study showed that the performance of ADMS was superior to that of AERMOD. In general, the performance of AERMOD was very poor and simulated extremely high concentration values. AERMOD performed even more poorly during calm conditions. ADMS performance was superior to AERMOD as was evident from the values of various performance statistical measures and a conclusion reached was that ADMS is likely to be a better model to use in cases where prolonged calm conditions are experienced. Keywords: air dispersion modeling, fugitive emissions, open cast mining, particulate matters i Acknowledgements First and foremost, I would like to thank and praise the Almighty God for giving me the knowledge and energy to complete this study. Next, I thank Rössing Uranium Limited for funding my studies. My sincere gratitude goes to the Department of Chemical Engineering at the University of Pretoria for partly funding my research. I wish to extend my heartfelt gratitude to my supervisor, Dr. Gerrit Kornelius for his scholarly guidance and support. I am indebted to Neel Breitenbach and Reneé von Gruenewaldt of Airshed Planning Professionals (Pty) Ltd for their assistance in the preparation of the topographical and meteorological files. I also would like to thank Coleen De Villiers of the South African Weather Services for providing me with the meteorological data. I am grateful to the Rössing Uranium Limited employees for the support they rendered to me during the time of my study. Some of them include Aina Kadhila Amoomo, Pedru Shamba, Rabanus Shoopala, Besser Rowhan and Jacklyn Mwenze. I also would like to thank Prof Jairos Kangira for his editorial work. Last but not least, I want to thank my family and friends for their patience and moral support from the beginning of my study to the end. Thank you all. I would not have completed this study without your support. ii Dedication This thesis is dedicated to my late mother, Mrs Diina Neshuku. Despite her physical absence, she continues to be my inspiration in every respect. iii Table of Contents Synopsis ....................................................................................................................................i Acknowledgements.................................................................................................................ii Dedication............................................................................................................................... iii Table of Contents...................................................................................................................iv LIST OF FIGURES.................................................................................................................vi LIST OF TABLES..................................................................................................................vii Abbreviations and Acronyms............................................................................................. viii NOMENCLATURE.................................................................................................................xi Chapter 1: Introduction...........................................................................................................1 1.1 Background ...................................................................................................................1 1.2 Objectives of the study ................................................................................................3 1.3 The outline of the dissertation ....................................................................................4 Chapter 2: Literature Survey .................................................................................................6 2.1 Background information on Rössing Uranium Mine ...............................................6 2.1.1 Location and topography .....................................................................................7 2.1.2 Climate....................................................................................................................8 2.1.3. Mining operations.................................................................................................9 2.1.4 Other sources of dust at Rössing Mine: Processing plant and tailings ......12 2.2 Dust theory ..................................................................................................................13 2.2.1 Dust classification ...............................................................................................14 2.2.2 Impacts of dust ........................................................................................................15 Impacts on human health.............................................................................................15 Impacts on environment...............................................................................................16 Impacts on safety and productivity.............................................................................16 Impacts on operational cost.........................................................................................17 2. 3. Regulations and air quality standards for PM10 ...................................................17 2. 3.1 Ambient Air quality standards for PM10...........................................................17 2. 3.2 Occupational exposure limits for PM10 ...........................................................19 2. 4. Air dispersion modelling theory..............................................................................20 2.4. 1. Mechanisms of pollutants dispersion in the atmosphere...........................21 2.4.2. Types of models .................................................................................................23 2.4.3. Factors affecting dispersion of pollutants in the atmosphere......................27 2.5 Review of models used in the study: AERMOD and ADMS................................31 2.5.1 AERMOD..............................................................................................................31 2.5.2 ADMS....................................................................................................................33 2.6.1 AERMOD studies ................................................................................................35 2.6.2 ADMS studies ......................................................................................................36 2.7. Emission estimation ..................................................................................................39 2.7.1. Drilling and Blasting (EPA, 1998) ....................................................................40 2.7.2. Aggregate handling............................................................................................42 2.7.3. Unpaved road .....................................................................................................43 2.7.4. Wind erosion from active stockpiles................................................................46 Chapter 3: Methodology.......................................................................................................49 3.1 Data collection.............................................................................................................49 3.1.1 Monitoring.............................................................................................................49 3.1.2 Data processing...................................................................................................50 iv 3.2. Modelling methodology.............................................................................................51 3.2.1 Meteorological data.............................................................................................51 3.2.2. Topographical data ............................................................................................52 3.2.3 Source parameters and geometry....................................................................54 3.2.4. Source geometry and location .........................................................................58 3.2.4. Modelling grids and receptor locations...........................................................61
Load more

Recommended publications
  • Part II: Practical Uses of Air Modeling in Litigation And
    Air Modeling as a Tool in Environmental Law and Policy: A Guide for Communities and Environmental Groups Part II: Practical Uses of Air Modeling in Litigation and Regulatory Contexts Clean Air Council 135 South 19th Street Suite 300 Philadelphia, PA 19103 (215) 567-4004 www.cleanair.org September 16, 2016 Authors and Purpose The authors are attorneys at the Clean Air Council at its headquarters in Philadelphia, Pennsylvania. The attorneys working on this White Paper were: Augusta Wilson, Esq., Aaron Jacobs-Smith, Esq., Benjamin Hartung, Esq., Christopher D. Ahlers, Esq., and Joseph Otis Minott, Esq., Executive Director and Chief Counsel. Clean Air Council is a non-profit, 501(c)(3) corporation with headquarters in Philadelphia, Pennsylvania. Acknowledgments The Clean Air Council thanks the Colcom Foundation. This paper would not have been possible without its generous funding and support. The authors would also like to thank Jini Chatterjee, Tessa Roberts and Paul Townsend, students at the University of Pennsylvania Law School’s Environmental Law Project, who conducted invaluable research for this paper, and Sonya Shea, who supervised their work at the Environmental Law Project. Disclaimer This paper is intended as a general introduction to the law and policy of air modeling under the Clean Air Act. Nothing in this paper is intended, nor shall it be construed as creating an attorney-client relationship or providing legal advice. © 2016 Clean Air Council 135 S. 19th Street Suite 300 Philadelphia, Pennsylvania 19103 Table of Contents Introduction .................................................................................................................................1 1. Use of Air Modeling to Support Tort Claims .....................................................................2 a. Challenges to the Use of Particular Modeling Software or to Underlying Assumptions .............................................................................................................2 b.
    [Show full text]
  • On the Uses of a New Linear Scheme for Stratospheric Methane in Global Models: Water Source, Transport Tracer and Radiative Forc
    Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Atmos. Chem. Phys. Discuss., 12, 479–523, 2012 Atmospheric www.atmos-chem-phys-discuss.net/12/479/2012/ Chemistry doi:10.5194/acpd-12-479-2012 and Physics © Author(s) 2012. CC Attribution 3.0 License. Discussions This discussion paper is/has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP if available. On the uses of a new linear scheme for stratospheric methane in global models: water source, transport tracer and radiative forcing B. M. Monge-Sanz1, M. P. Chipperfield1, A. Untch2, J.-J. Morcrette2, A. Rap1, and A. J. Simmons2 1Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, UK 2European Centre for Medium-Range Weather Forecasts, Reading, UK Received: 10 October 2011 – Accepted: 5 November 2011 – Published: 6 January 2012 Correspondence to: B. M. Monge-Sanz ([email protected]) Published by Copernicus Publications on behalf of the European Geosciences Union. 479 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Abstract A new linear parameterisation for stratospheric methane (CoMeCAT) has been devel- oped and tested. The scheme is derived from a 3-D full chemistry transport model (CTM) and tested within the same chemistry model itself, as well as in an independent 5 general circulation model (GCM). The new CH4/H2O scheme is suitable for any global model and here is shown to provide realistic profiles in the 3-D TOMCAT/SLIMCAT CTM and in the ECMWF (European Centre for Medium-Range Weather Forecasts) GCM.
    [Show full text]
  • Table of Contents
    CALPUFF Modeling System Version 6 User Instructions April 2011 Section 1: Introduction Table of Contents Page 1. OVERVIEW ...................................................................................................................... 1-1 1.1 CALPUFF Version 6 Modeling System............................................................... 1-1 1.2 Historical Background .......................................................................................... 1-2 1.3 Overview of the Modeling System ....................................................................... 1-7 1.4 Major Model Algorithms and Options................................................................. 1-19 1.4.1 CALMET................................................................................................ 1-19 1.4.2 CALPUFF............................................................................................... 1-23 1.5 Summary of Data and Computer Requirements .................................................. 1-28 2. GEOPHYSICAL DATA PROCESSORS.......................................................................... 2-1 2.1 TERREL Terrain Preprocessor............................................................................. 2-3 2.2 Land Use Data Preprocessors (CTGCOMP and CTGPROC) ............................. 2-27 2.2.1 Obtaining the Data.................................................................................. 2-27 2.2.2 CTGCOMP - the CTG land use data compression program .................. 2-29 2.2.3 CTGPROC - the land use preprocessor
    [Show full text]
  • Air Dispersion Modeling Guidelines
    Air Quality Modeling Guidelines for Arizona Air Quality Permits PREPARED BY: FACILITIES EMISSIONS CONTROL SECTION AIR QUALITY DIVISION ARIZONA DEPARTMENT OF ENVIRONMENTAL QUALITY November 1, 2019 TABLE OF CONTENTS 1 INTRODUCTION.......................................................................................................... 1 1.1 Overview of Regulatory Modeling ........................................................................... 1 1.2 Purpose of an Air Quality Modeling Analysis .......................................................... 2 1.3 Authority for Modeling ............................................................................................. 3 1.4 Acceptable Models.................................................................................................... 3 1.5 Overview of Modeling Protocols and Checklists ..................................................... 4 1.6 Overview of Modeling Reports ................................................................................ 5 2 LEVELS OF MODELING ANALYSIS SOPHISTICATION .................................. 5 2.1 Screening Models or Screening Techniques ............................................................. 6 2.1.1 Screening Models for Near-Field Assessments ................................................. 6 2.1.2 Screening Techniques for Long-Range Transport Assessments ....................... 7 2.2 Refined Modeling ..................................................................................................... 8 2.2.1 AERMOD .........................................................................................................
    [Show full text]
  • University of Reading Boundary-Layer Type Classification and Pollutant Mixing
    University of Reading Department of Meteorology Boundary-layer type classification and pollutant mixing Natalie Jane Harvey A thesis submitted for the degree of Doctor of Philosophy March 2013 Declaration I confirm that this is my own work and the use of all material from other sources has been properly and fully acknowledged. Natalie Harvey Page ii Abstract In the atmospheric boundary layer the vertical distribution of heat, momentum, water and pollutants is controlled by mixing that is turbulent. This complex mixing is param- eterized in weather forecast and climate models. But are the parameterizations imple- mented in these models representative of the real world? For the first time, Doppler lidar and sonic anemometer data are used to objectively classify the observed boundary layer into nine different types based on the Met Office scheme. Examples of these types are decoupled stratocumulus cloud, cumulus capped and stable with no turbulent cloud. This method is applied to three years of data from the Chilbolton Observatory, UK, to create a climatology of boundary-layer type. This climatology exhibits clear seasonal and diurnal cycles with the most common type over the three years being a cloud-free stable boundary layer. The decoupled stratocumulus type and the cumulus cloud under a stratocumulus layer type are diagnosed 10.3% and 1.0% of the period respectively. This new observationally based boundary layer classification is used to evaluate the boundary-layer type diagnosed by the 4 km and 12 km resolution versions of the Met Office Unified Model. The model is found to predict too many decoupled stratocumulus boundary layers by a factor of 1.8, in both the stable and unstable regime.
    [Show full text]
  • Effects of Stratospheretroposphere Chemistry Coupling on Tropospheric Ozone
    JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, D00M04, doi:10.1029/2009JD013515, 2010 Effects of stratosphere‐troposphere chemistry coupling on tropospheric ozone Wenshou Tian,1,2 Martyn P. Chipperfield,2 David S. Stevenson,3 Richard Damoah,3,4 Sandip Dhomse,2 Anu Dudhia,5 Hugh Pumphrey,3 and Peter Bernath6 Received 6 November 2009; revised 23 March 2010; accepted 13 April 2010; published 17 September 2010. [1] A new, computationally efficient coupled stratosphere‐troposphere chemistry‐climate model (S/T‐CCM) has been developed based on three well‐documented components: a64‐level general circulation model from the UK Met Office Unified Model, the tropospheric chemistry transport model (STOCHEM), and the UMSLIMCAT stratospheric chemistry module. This newly developed S/T‐CCM has been evaluated with various observations, and it shows good performance in simulating important chemical species and their interdependence in both the troposphere and stratosphere. The modeled total column ozone agrees well with Total Ozone Mapping Spectrometer observations. Modeled ozone profiles in the upper troposphere and lower stratosphere are significantly improved compared to runs with the stratospheric chemistry and tropospheric chemistry models alone, and they are in good agreement with Michelson Interferometer for Passive Atmospheric Sounding satellite ozone profiles. The observed CO tape recorder is also successfully captured by the new CCM, and ozone‐CO correlations are in accordance with Atmospheric Chemistry Experiment observations. However, because of limitations in vertical resolution, intrusion of CO‐rich air in the stratosphere from the mesosphere could not be simulated in the current version of S/T‐CCM. Additionally, the simulated stratosphere‐to‐troposphere ozone flux, which controls upper tropospheric OH and O3 concentrations, is found to be more realistic in the new coupled model compared to STOCHEM.
    [Show full text]
  • Assimila Blank
    NERC NERC Strategy for Earth System Modelling: Technical Support Audit Report Version 1.1 December 2009 Contact Details Dr Zofia Stott Assimila Ltd 1 Earley Gate The University of Reading Reading, RG6 6AT Tel: +44 (0)118 966 0554 Mobile: +44 (0)7932 565822 email: [email protected] NERC STRATEGY FOR ESM – AUDIT REPORT VERSION1.1, DECEMBER 2009 Contents 1. BACKGROUND ....................................................................................................................... 4 1.1 Introduction .............................................................................................................. 4 1.2 Context .................................................................................................................... 4 1.3 Scope of the ESM audit ............................................................................................ 4 1.4 Methodology ............................................................................................................ 5 2. Scene setting ........................................................................................................................... 7 2.1 NERC Strategy......................................................................................................... 7 2.2 Definition of Earth system modelling ........................................................................ 8 2.3 Broad categories of activities supported by NERC ................................................. 10 2.4 Structure of the report ...........................................................................................
    [Show full text]
  • Review of the Global Models Used Within Phase 1 of the Chemistry–Climate Model Initiative (CCMI)
    Geosci. Model Dev., 10, 639–671, 2017 www.geosci-model-dev.net/10/639/2017/ doi:10.5194/gmd-10-639-2017 © Author(s) 2017. CC Attribution 3.0 License. Review of the global models used within phase 1 of the Chemistry–Climate Model Initiative (CCMI) Olaf Morgenstern1, Michaela I. Hegglin2, Eugene Rozanov18,5, Fiona M. O’Connor14, N. Luke Abraham17,20, Hideharu Akiyoshi8, Alexander T. Archibald17,20, Slimane Bekki21, Neal Butchart14, Martyn P. Chipperfield16, Makoto Deushi15, Sandip S. Dhomse16, Rolando R. Garcia7, Steven C. Hardiman14, Larry W. Horowitz13, Patrick Jöckel10, Beatrice Josse9, Douglas Kinnison7, Meiyun Lin13,23, Eva Mancini3, Michael E. Manyin12,22, Marion Marchand21, Virginie Marécal9, Martine Michou9, Luke D. Oman12, Giovanni Pitari3, David A. Plummer4, Laura E. Revell5,6, David Saint-Martin9, Robyn Schofield11, Andrea Stenke5, Kane Stone11,a, Kengo Sudo19, Taichu Y. Tanaka15, Simone Tilmes7, Yousuke Yamashita8,b, Kohei Yoshida15, and Guang Zeng1 1National Institute of Water and Atmospheric Research (NIWA), Wellington, New Zealand 2Department of Meteorology, University of Reading, Reading, UK 3Department of Physical and Chemical Sciences, Universitá dell’Aquila, L’Aquila, Italy 4Environment and Climate Change Canada, Montréal, Canada 5Institute for Atmospheric and Climate Science, ETH Zürich (ETHZ), Zürich, Switzerland 6Bodeker Scientific, Christchurch, New Zealand 7National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA 8National Institute of Environmental Studies (NIES), Tsukuba, Japan 9CNRM UMR 3589, Météo-France/CNRS,
    [Show full text]
  • ARCOPOL the Atlantic Regions' Coastal Pollution Response
    Airborne Pollution Propagation from water incidents: State of the art of air pollution models Activity 4 Task 4.2.1 ARCOPOL The Atlantic Regions’ Coastal Pollution Response Version: Version 2 Last updated on: 05/11/2010 Author: Meteogalicia Responsible partner: IST Involved partners: CETMAR, Meteogalicia, INTECMAR, IST, CIIMAR, EGMASA, Irish Marine Institute, Bretagne Region, Aquitaine Region Table of contents 1. Executive Summary .............................................................................................................. 3 2. Context and aims of the task ............................................................................................... 3 2.1. Summary of the 2008 Air Quality Directive ..................................................... 4 2.1.1. Concepts and definitions..................................................................................... 4 2.2. Where does the Air Quality Directive apply? .................................................. 6 2.2.1. Limits and target values for the protection of human health......................... 7 2.2.2. Limits and target values for the protection of vegetation............................... 9 2.2.3. Air quality web portals in Europe .................................................................... 9 3. Methodology........................................................................................................................ 12 3.1. When can models be used for the assessment of existing air quality? ....... 12 3.2. Combined use of measurements
    [Show full text]
  • 10.5 Development of a Wrf-Aermod Tool for Use in Regulatory Applications
    10.5 DEVELOPMENT OF A WRF-AERMOD TOOL FOR USE IN REGULATORY APPLICATIONS Toree Myers-Cook*, Jon Mallard, and Qi Mao Tennessee Valley Authority (TVA) ABSTRACT available. For rural sources, the closest representative NWS station may be greater than 50- The Tennessee Valley Authority (TVA) has developed 100 kilometers away. Furthermore, NWS data a WRF-AERMOD tool which transforms the Weather limitations - instrumentation limits, missing data, and Research and Forecasting (WRF) model output into lack of surface parameters required by AERMET - the meteorological input needed by AERMOD have motivated the EPA to explore the use of (AERMAP/AERMET/AERMOD), the EPA- prognostic meteorological models, specifically MM5 recommended model for short-range dispersion (Brode 2008), which can provide a timely and spatially modeling. The tool was used to model 2002 comprehensive meteorological dataset for input to emissions from TVA’s Allen Fossil (ALF) Plant in AERMOD. The EPA has been testing an in-house Memphis, Tennessee. Modeling using NWS data MM5-AERMOD tool for possible use in future was also performed and results were compared. regulatory applications. However, since MM5 is no Analyses of modeling results showed several longer supported by its developers and the WRF differences between the two approaches, with much (Weather Research Forecasting) model is now of the inconsistencies attributed to four main findings. considered the state-of-the-art meteorological model First, the NWS-AERMOD approach tended to stay to replace it, TVA developed a WRF-AERMOD tool more unstable in the summer and stable in the winter that takes WRF three-dimensional meteorological with unrealistically high mechanical boundary layer output (surface and upper air) and transforms it into (MBL) heights.
    [Show full text]
  • Climate Change
    TRANSPORTATION RESEARCH Number E-C271 May 2021 Critical Issues in Aviation and the Environment 2021 TRANSPORTATION RESEARCH BOARD 2020 EXECUTIVE COMMITTEE OFFICERS Chair: Carlos M. Braceras, Executive Director, Utah Department of Transportation, Salt Lake City Vice Chair: Susan A. Shaheen, Adjunct Professor, Co-Director, Transportation Sustainability Research Center, University of California, Berkeley Division Chair for NRC Oversight: Chris Hendrickson, Hamerschlag University Professor Emeritus, Carnegie Mellon University, Pittsburgh, Pennsylvania Executive Director: Neil J. Pedersen, Transportation Research Board TRANSPORTATION RESEARCH BOARD 2020–2021 TECHNICAL ACTIVITIES COUNCIL Chair: Hyun-A C. Park, President, Spy Pond Partners, LLC, Arlington, Massachusetts Technical Activities Director: Ann M. Brach, Transportation Research Board Richard Bornhorst, Principal, FACTOR, Inc., Silver Spring, Maryland, Freight Systems Group Chair Michael Griffith, Director, Office of Safety Technologies, Federal Highway Administration, Washington, D.C., Safety and Operations Group Chair George Avery Grimes, CEO Advisor, Patriot Rail Company, Denver, Colorado, Rail Group Chair Brendon Hemily, Principal, Hemily and Associates, Toronto, Ontario, Public Transportation Group Chair Nikola Ivanov, Deputy Director, Center for Advanced Transportation Technology Laboratory, University of Maryland, College Park, Young Members Council Chair Pamela Keidel-Adams, Regional Vice President, Kimley-Horn and Associates, Inc., Mesa, Arizona, Aviation Group Chair C. James
    [Show full text]
  • Atmospheric Deposition of Pcbs in the Spokane River Watershed
    Atmospheric Deposition of PCBs in the Spokane River Watershed March 2019 Publication No. 19-03-003 Publication Information This report is available on the Department of Ecology’s website at https://fortress.wa.gov/ecy/publications/SummaryPages/1903003.html. Data for this project are available at Ecology’s Environmental Information Management (EIM) website: www.ecology.wa.gov/eim/index.htm, search Study ID BERA0013. The Activity Tracker Code for this study is 16-032. Water Resource Inventory Area (WRIA) and 8-digit Hydrologic Unit Code (HUC) numbers for the study area: WRIAs HUC numbers 56 – Hangman 17010305 57 – Middle Spokane 17010306 Contact Information Publications Coordinator Environmental Assessment Program P.O. Box 47600, Olympia, WA 98504-7600 Phone: (360) 407–6764 Washington State Department of Ecology – www.ecology.wa.gov. Headquarters, Olympia (360) 407-6000 Northwest Regional Office, Bellevue (425) 649-7000 Southwest Regional Office, Olympia (360) 407-6300 Central Regional Office, Union Gap (509) 575-2490 Eastern Regional Office, Spokane (509) 329-3400 Cover photo: Atmospheric deposition samplers on the roof of the Spokane Clean Air Agency Building. Photo by Brandee Era-Miller. Any use of product or firm names in this publication is for descriptive purposes only and does not imply endorsement by the author or the Department of Ecology. Accommodation Requests: To request ADA accommodation, including materials in a format for the visually impaired, call Ecology at 360-407-6764, or visit https://ecology.wa.gov/ accessibility. People with impaired hearing may call Washington Relay Service at 711. People with speech disability may call TTY at 877-833-6341.
    [Show full text]