Atmospheric Conditions Which Affect Air Pollution
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AMOC Variability, a Key Factor in Emission Reduction Scenarios
UTRECHT UNIVERSITY MSC CLIMATE PHYSICS INSTITUTE FOR MARINE AND ATMOSPHERIC RESEARCH UTRECHT 5 AMOC variability, a key factor in emission reduction scenarios 10 Author: J.M. Valentí Muelas [6515886] Supervisor: Prof. Dr. Ir. H.A. Dijkstra 15 June 2020. Contents 1 Introduction 2 2 Methods 4 2.1 Carbon Cycle Model................................................4 5 2.2 Emission reduction pathways............................................5 2.3 Model........................................................7 2.4 Climate sensitivity & Feedbacks..........................................8 2.5 Model diagnostics.................................................. 10 3 Results 12 10 3.1 Basic variables................................................... 12 3.2 AMOC....................................................... 14 3.3 GMST-AMOC correlation............................................. 19 4 Discussion and Conclusions 21 4.1 GMST response to emission reduction....................................... 21 15 4.2 AMOC Collapse.................................................. 22 4.3 Conclusions..................................................... 24 Appendix A: Tables 28 Appendix B: Complementary figures 29 1 Abstract The climate system response to emission reduction shows time dependencies when evaluated in terms of global mean sur- face temperature (GMST). The Atlantic meridional overturning circulation (AMOC) variability may be forcing a non-linear behaviour on GMST response to emission reduction. In this study, emission reduction is evaluated with -
Referee 1 1 2 Many Thanks for the Constructive Suggestions. Our
1 Referee 1 2 3 Many thanks for the constructive suggestions. Our responses are in red text 4 below. 5 6 The paper describes PLASIM-GENIE a new intermediate-complexity 7 Atmosphere- Ocean Earth System Model, designed for simulations of millenium+ 8 length. The new model is well suited for studies of long-term climate change, its 9 simulation of present-day climate is acceptable, its formulation is mostly 10 described well, and I recommend publication subject to the following changes 11 being made. 12 13 1. It’s not 100% clear whether or not this model has a carbon cycle, and what 14 aspects of this are turned on or off. The model is described as an AOGCM 15 (suggesting no C-cycle), but section 2.1 and others do allude to the simulation of 16 different carbon pools on land, which is slightly confusing. I presume there is 17 some sort of diagnostic C-cycle which does not affect atmospheric CO2, but does 18 affect vegetation. However GENIE- 1 does contain a fully interactive C-cycle. The 19 abstract, introduction, section 2.1 and other sections have to be clearer about 20 which parts of the C-cycle are on or off. Any flexibility in the C-cycle (ie: being 21 run in a diagnostic mode to simulation terrestrial pools but without affecting the 22 ocean and atmosphere) should be noted, as potential users of this AOGCM would 23 be interested in this. 24 25 As suggested, we have added flexibility to the run the terrestrial carbon cycle in 26 diagnostic mode. -
Evaluation of Fast Atmospheric Dispersion Models in a Regular
Evaluation of fast atmospheric dispersion models in a regular street network Denise Hertwig, Lionel Soulhac, Vladimír Fuka, Torsten Auerswald, Matteo Carpentieri, Paul Hayden, Alan Robins, Zheng-Tong Xie, Omduth Coceal To cite this version: Denise Hertwig, Lionel Soulhac, Vladimír Fuka, Torsten Auerswald, Matteo Carpentieri, et al.. Eval- uation of fast atmospheric dispersion models in a regular street network. Environmental Fluid Me- chanics, Springer Verlag, 2018, 10.1007/s10652-018-9587-7. hal-01761232 HAL Id: hal-01761232 https://hal.archives-ouvertes.fr/hal-01761232 Submitted on 8 Apr 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Environ Fluid Mech manuscript No. (will be inserted by the editor) 1 Evaluation of fast atmospheric dispersion models in a regular 2 street network 3 Denise Hertwig · Lionel Soulhac · Vladim´ır 4 Fuka · Torsten Auerswald · Matteo Carpentieri · 5 Paul Hayden · Alan Robins · Zheng-Tong Xie · 6 Omduth Coceal 7 8 Received: date / Accepted: date 9 Abstract The need to balance computational speed and simulation accuracy is a key chal- 10 lenge in designing atmospheric dispersion models that can be used in scenarios where near 11 real-time hazard predictions are needed. -
Atmospheric Dispersion Modelling of Bioaerosols That Are Pathogenic to Humans and Livestock – a Review to Inform Risk Assessment Studies
Microbial Risk Analysis 1 (2016) 19–39 Contents lists available at ScienceDirect Microbial Risk Analysis journal homepage: www.elsevier.com/locate/mran Atmospheric dispersion modelling of bioaerosols that are pathogenic to humans and livestock – A review to inform risk assessment studies J.P.G. Van Leuken a,b,∗,A.N.Swarta, A.H. Havelaar a,b,c, A. Van Pul d, W. Van der Hoek a, D. Heederik b a Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands b Institute for Risk Assessment Sciences (IRAS), Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands c Emerging Pathogens Institute and Animal Sciences Department, University of Florida, Gainesville, FL, United States of America d Environment & Safety (M&V), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands article info abstract Article history: In this review we discuss studies that applied atmospheric dispersion models (ADM) to bioaerosols that Received 19 May 2015 are pathogenic to humans and livestock in the context of risk assessment studies. Traditionally, ADMs have Revised 25 June 2015 been developed to describe the atmospheric transport of chemical pollutants, radioactive matter, dust, and Accepted 17 July 2015 particulate matter. However, they have also enabled researchers to simulate bioaerosol dispersion. Availableonline26July2015 To inform risk assessment, the aims of this review were fourfold, namely (1) to describe the most im- Keywords: portant physical processes related to ADMs and pathogen transport, (2) to discuss studies that focused on Airborne the application of ADMs to pathogenic bioaerosols, (3) to discuss emission and inactivation rate parameter- Pathogens isations, and (4) to discuss methods for conversion of concentrations to infection probabilities (concerning Respiratory infections quantitative microbial risk assessment). -
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 -
Coordination of Atmospheric Dispersion Activities for the Real-Time Decision Support System RODOS
RODOS R-2-1997 RIS0-R-93O (EN) DK9700116 Coordination of Atmospheric Dispersion Activities for the Real-Time Decision Support System RODOS DECISION SUPPORT FOR NUCLEAR EMERGENCIES RODOS R-2-1997 RIS0-R-93O (EN) Coordination of Atmospheric Dispersion Activities for the Real-Time Decision Support System RODOS Torben Mikkelsen RIS0 National Laboratory Denmark July 1997 Secretariat of the RODOS Project: Forschungszentrum Karlsruhe Institut fur Neutronenphysik und Reaktortechnik P.O. Box 3640, 76021 Karlsruhe, Germany Phone: +49 7247 82 5507, Fax: +49 7247 82 5508 EMail: [email protected], Internet: http://rodos.fzk.de This work has been performed with the support of the European Commission Radiation Protection Research Action (DGXII-F-6) contract FI3P-CT92-0044 This report has been published as Report RIS0-R-93O (EN) (ISSN 0106-2840) (ISBN 87-550-2230-8) in May 1997 by RIS0 National Laboratory P.O. Box 49 DK-4000 Roskilde, Denmark Management Summary 1.1 Global Objectives: This projects task has been to coordinate activities among the RODOS Atmospheric Dispersion sub-group A participants (1) - (8), with the overall objective of developing and integrating an atmospheric transport and dispersion module for the joint European Real-time On- line DecisiOn Support system RODOS headed by FZK (formerly KfK), Germany. The projects final goal is the establishment of a fully operational, system-integrated atmospheric transport module for the RODOS system by year 2000, capable of consistent now- and forecasting of radioactive airborne spread over all types of terrain and on all scales of interest, including in particular complex terrain and the different scales of operation, such as the local, the national and the European scale. -
Technical Assistance for Improving Emissions Control the Role Of
This Project is Co-Financed by the European Union and the Republic of Turkey This Project is c This project is co-financed by the European Union and the Republic of Turkey Technical Assistance for Improving Emissions Control Service Contract No: TR0802.03-02/001 Identification No: EuropeAid/128897/D/SER/TR The Role of Emissions Dispersion Modelling in Cost Benefit Analysis Applied to Urban Air Quality Management: Part 1-the Approach (Version 2: 18 May 2012) This publication has been produced with the assistance of the European Union. The content of this publication is the sole responsibility of the Consortium led by PM Group and can in no way be taken to reflect the views of the European Union. Contracting Authority: Central Finance and Contracting Unit, Turkey Implementing Authority / Beneficiary: Ministry of Environment and Urbanisation Project Title: Improving Emissions Control Service Contract Number: TR0802.03-02/001 Identification Number: EuropeAid/128897/D/SER/TR PM Project Number: 300424 This project is co-financed by the European Union and the Republic of Turkey The Role of Emissions Dispersion Modelling in Cost Benefit Analysis Applied to Urban Air Quality Management: Part 1 – the Approach Version 2: 18 May 2012 PM File Number: 300424-06-RP-200 PM Document Number: 300424-06-205(2) CURRENT ISSUE Issue No.: 2 Date: 18/05/2012 Reason for Issue: Final Version for Client Approval Customer Approval Sign-Off Originator Reviewer Approver (if required) Scott Hamilton, Peter Print Name Russell Frost Jim McNelis Faircloth, Chris Dore Signature Date PREVIOUS ISSUES (Type Names) Issue No. Date Originator Reviewer Approver Customer Reason for Issue 1 14/03/2012 Scott Hamilton, Peter Russell Frost Jim McNelis For client review / comment Faircloth, Chris Dore CFCU / MoEU 300424-06-RP-205 (2) TA for Improving Emissions Control 18 May 2012 CONTENTS GLOSSARY OF ACRONYMS ...................................................................................... -
Predicting Air Quality Near Roadway Intersections Through the Applicat
University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2004 Predicting Air Quality Near Roadway Intersections Through The Applicat Brian Kim University of Central Florida Part of the Environmental Engineering Commons Find similar works at: https://stars.library.ucf.edu/etd University of Central Florida Libraries http://library.ucf.edu This Doctoral Dissertation (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact [email protected]. STARS Citation Kim, Brian, "Predicting Air Quality Near Roadway Intersections Through The Applicat" (2004). Electronic Theses and Dissertations, 2004-2019. 200. https://stars.library.ucf.edu/etd/200 PREDICTING AIR QUALITY NEAR ROADWAY INTERSECTIONS THROUGH THE APPLICATION OF A GAUSSIAN PUFF MODEL TO MOVING SOURCES by BRIAN Y. KIM B.S. University of California at Irvine, 1990 M.S. California Polytechnic State University at San Luis Obispo, 1996 A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Civil and Environmental Engineering in the College of Engineering and Computer Science at the University of Central Florida Orlando, Florida Fall Term 2004 ABSTRACT With substantial health and economic impacts attached to many highway-related projects, it has become imperative that the models used to assess air quality be as accurate as possible. The United States (US) Environmental Protection Agency (EPA) currently promulgates the use of CAL3QHC to model concentrations of carbon monoxide (CO) near roadway intersections. -
MARK R THEOBALD.Pdf
TESIS DOCTORAL / Ph.D THESIS An Intercomparison of Modelling Approaches for Simulating the Atmospheric Dispersion of Ammonia Emitted by Agricultural Sources Mark R. Theobald Madrid 2012 E.T.S.I. Agrónomos Universidad Politécnica de Madrid Departamento de Química y Análisis Agrícola Escuela Técnica Superior de Ingenieros Agrónomos An Intercomparison of Modelling Approaches for Simulating the Atmospheric Dispersion of Ammonia Emitted by Agricultural Sources Autor: Mark R. Theobald Licenciado en Ciencias Físicas (MPhys hons) Directores: Dr. Antonio Vallejo Garcia Doctor en Ciencias Químicas Dr. Mark A. Sutton Doctor en Ciencias Físicas Madrid 2012 Acknowledgements ACKNOWLEDGEMENTS This work was funded by the European Commission through the NitroEurope Integrated Project (Contract No. 017841 of the EU Sixth Framework Programme for Research and Technological Development). The European Science Foundation also provided additional funding through COST Action 729 for the attendance of conferences and workshops and for the collaboration with the University of Lisbon (COST-STSM-729-5799). Firstly I would like to thank my two supervisors Dr. Mark A. Sutton and Prof. Antonio Vallejo for their support and guidance throughout this work. I am grateful to Mark not only for his willingness to discuss and direct this work no matter where he was in the world or whatever time of day it was, but also for the support and encouragement I received when I was at CEH Edinburgh. I am also grateful to Antonio for guiding me through the labyrinths of University bureaucracy. I would also like to thank the other research groups with whom I have collaborated throughout this work. Thanks to all my colleagues at CEH Edinburgh with a special mention to Bill Bealey for his help developing the SCAIL model and to Sim Tang for providing the ALPHA samplers and technical support. -
Development of the Next Generation Air Quality Models for Outer Continental Shelf (OCS) Applications
Development of the Next Generation Air Quality Models for Outer Continental Shelf (OCS) Applications Final Report: Volume 2 - CALPUFF Users Guide (CALMET and Preprocessors) March 2006 Prepared For: U.S. Department of the Interior, Minerals Management Service, Herndon, VA Contract No. 1435-01-01-CT-31071 Prepared By: Earth Tech, Inc. 196 Baker Avenue Concord, Massachusetts 01742 (978) 371-4000 Contents A. OVERVIEW A-1 A.1 Background A-1 A.2 Overview of the Modeling System A-4 A.3 Major Model Algorithms and Options A-14 A.4 Summary of Data and Computer Requirements A-23 B. GEOPHYSICAL DATA PROCESSORS B-1 B.1 TERREL Terrain Preprocessor B-3 B.2 Land Use Data Preprocessors (CTGCOMP and CTGPROC) B-17 B.3 MAKEGEO B-31 B.4 NIMA DATUM REFERENCE INFORMATION B-42 C. METEOROLOGICAL DATA PROCESSORS C-1 C.1 READ62 UPPER AIR PREPROCESSOR C-1 C.2 PXTRACT PRECIPITATION DATA EXTRACT PROGRAM C-12 C.3 PMERGE PRECIPITATION DATA PREPROCESSOR C-19 C.4 SMERGE SURFACE DATA METEOROLOGICAL PREPROCESSOR C-29 C.5 BUOY OVER-WATER DATA METEOROLOGICAL PREPROCESSOR C-39 D. PROGNOSTIC METEOROLOGICAL DATA PROCESSORS D-1 D.1 CALMM5 D-1 D.2 CALETA D-25 D.3 CALRUC D-40 D.4 CALRAMS D-48 D.5 3D.DAT OUTPUT FILE D-53 E. CALMET MODEL FILES E-1 E.1 User Control File (CALMET.INP) E-5 E.2 Geophysical Data File (GEO.DAT) E-49 E.3 Upper Air Data Files (UP1.DAT, UP2.DAT,...) E-61 E.4 Surface Meteorological Data File (SURF.DAT) E-66 E.5 Overwater Data Files (SEA1.DAT, SEA2.DAT, ...) E-70 E.6 Precipitation Data File (PRECIP.DAT) E-74 E.7 Preprocessed Diagnostic Model Data File (DIAG.DAT) E-78 E.8 Prognostic Model Data File (PROG.DAT) E-82 E.9 3D Model Data Files (3D.DAT) E-84 E.10 Terrain Weighting Factor Data File (WT.DAT) E-102 E.11 CALMET Output Files E-109 Volume II & III References A. -
Wind Energy Department Annual Progress Report 2001
View metadata,Downloaded citation and from similar orbit.dtu.dk papers on:at core.ac.uk Dec 19, 2017 brought to you by CORE provided by Online Research Database In Technology Wind Energy Department annual progress report 2001 Skrumsager, Birthe; Larsen, Søren Ejling; Madsen, Peter Hauge Publication date: 2002 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Skrumsager, B., Larsen, S. E., & Madsen, P. H. (2002). Wind Energy Department annual progress report 2001. (Denmark. Forskningscenter Risoe. Risoe-R; No. 1317(EN)). General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Risø-R-1317(EN) Wind Energy Department Annual Progress Report 2001 Birthe Skrumsager, Søren E. Larsen and Peter Hauge Madsen (Eds) Risø National Laboratory, Roskilde October 2002 Abstract The report describes the work of the Wind Energy Department at Risø National Laboratory in 2001. -
Evaluation of ISC3, AERMOD, and ADMS Dispersion Models with Observations from Five Field Sites
EVALUATION OF THE ADMS, AERMOD, AND ISC3 DISPERSION MODELS WITH THE OPTEX, DUKE FOREST, KINCAID, INDIANAPOLIS, AND LOVETT FIELD DATA SETS Steven R. Hanna*, Bruce A. Egan**, John Purdum***, and Jen Wagler**** *CSI MS 5C3, George Mason Univ., Fairfax, VA 22030-4444 USA **Egan Environmental, 75 Lothrop St., Beverly, MA 01915 USA ***17 Peters Way, North Attleboro, MA 02760 USA ****URS Greiner Woodward-Clyde, 38 Chauncy St., Boston, MA 02111 USA ABSTRACT The model evaluation exercise addresses the question whether the new models, ADMS and AERMOD, produce improvements over ISC3 when compared with a range of field observations. ADMS and AERMOD have similar state-of-the-art scientific components, whereas ISC3 contains 1960s technology. The five sets of field observations used in the statistical evaluation represent a cross-section of typical scenarios encountered by modelers. The OPTEX data base concerns non-buoyant tracer releases within an oil refinery complex, and the Duke Forest data base involves non-buoyant tracer releases from area and volume sources in an open field. The Kincaid, Indianapolis, and Lovett data bases all deal with buoyant plumes from tall stacks at power plants. However, the settings are quite different, since the Kincaid plant is surrounded by flat farmland, the Indianapolis plant is located in an urban environment, and the Lovett plant is sited in a valley surrounded by complex terrain with monitors at elevations higher than the stack. Analysis of the model performance measures suggest that ISC3 typically overpredicts, has a scatter of about a factor of three, and has about 33% of its predictions within a factor of two of observations.