Chapter 9 Profiles of Operational and Research Forecasting of Smoke and Air Quality Around the World Susan M. O'Neill, Susan M. O'Neill Pacific Northwest Research Station, United States Forest Service, Seattle, Washington, USASearch for more papers by this authorPeng Xian, Peng Xian United States Naval Research Laboratory, Marine Meteorology Division, Monterey, California, USASearch for more papers by this authorJohannes Flemming, Johannes Flemming European Centre for Medium-Range Weather Forecasts, Reading, United KingdomSearch for more papers by this authorMartin Cope, Martin Cope CSIRO Climate Science Centre, Aspendale, Victoria, AustraliaSearch for more papers by this authorAlexander Baklanov, Alexander Baklanov World Meteorological Organization, Geneva, SwitzerlandSearch for more papers by this authorNarasimhan K. Larkin, Narasimhan K. Larkin Pacific Northwest Research Station, United States Forest Service, Seattle, Washington, USASearch for more papers by this authorJoseph K. Vaughan, Joseph K. Vaughan Department of Civil and Environmental Engineering, Washington State University, Pullman, Washington, USASearch for more papers by this authorDaniel Tong, Daniel Tong Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, Virginia, USASearch for more papers by this authorRosie Howard, Rosie Howard Earth, Ocean and Atmospheric Sciences Department, The University of British Columbia, Vancouver, British Columbia, CanadaSearch for more papers by this authorRoland Stull, Roland Stull Earth, Ocean and Atmospheric Sciences Department, The University of British Columbia, Vancouver, British Columbia, CanadaSearch for more papers by this authorDidier Davignon, Didier Davignon Environment and Climate Change Canada, Dorval, Quebec City, CanadaSearch for more papers by this authorRavan Ahmadov, Ravan Ahmadov CIRES, University of Colorado Boulder, Boulder, Colorado, USA NOAA Global Systems Laboratory, Boulder, Colorado, USASearch for more papers by this authorM. Talat Odman, M. Talat Odman School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USASearch for more papers by this authorJohn Innis, John Innis EPA Tasmania, Hobart, Tasmania, AustraliaSearch for more papers by this authorMerched Azzi, Merched Azzi Department of Planning and Environment, Government of New South Wales, Sydney, AustraliaSearch for more papers by this authorChristopher Gan, Christopher Gan Centre for Climate Research Singapore, Meteorological Service Singapore, SingaporeSearch for more papers by this authorRadenko Pavlovic, Radenko Pavlovic Environment and Climate Change Canada, Dorval, Quebec City, CanadaSearch for more papers by this authorBoon Ning Chew, Boon Ning Chew Centre for Climate Research Singapore, Meteorological Service Singapore, SingaporeSearch for more papers by this authorJeffrey S. Reid, Jeffrey S. Reid United States Naval Research Laboratory, Marine Meteorology Division, Monterey, California, USASearch for more papers by this authorEdward J. Hyer, Edward J. Hyer United States Naval Research Laboratory, Marine Meteorology Division, Monterey, California, USASearch for more papers by this authorZak Kipling, Zak Kipling European Centre for Medium-Range Weather Forecasts, Reading, United KingdomSearch for more papers by this authorAngela Benedetti, Angela Benedetti European Centre for Medium-Range Weather Forecasts, Reading, United KingdomSearch for more papers by this authorPeter R. Colarco, Peter R. Colarco NASA Goddard Space Flight Center, Greenbelt, Maryland, USASearch for more papers by this authorArlindo Da Silva, Arlindo Da Silva NASA Goddard Space Flight Center, Greenbelt, Maryland, USASearch for more papers by this authorTaichu Tanaka, Taichu Tanaka Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, JapanSearch for more papers by this authorJeffrey McQueen, Jeffrey McQueen NOAA National Centers for Environmental Prediction, College Park, Maryland, USASearch for more papers by this authorPartha Bhattacharjee, Partha Bhattacharjee I. M. Systems Group, NWS/NCEP/EMC, College Park, Maryland, USASearch for more papers by this authorJonathan Guth, Jonathan Guth Météo-France, Toulouse, FranceSearch for more papers by this authorNicole Asencio, Nicole Asencio Météo-France, Toulouse, FranceSearch for more papers by this authorOriol Jorba, Oriol Jorba Barcelona Supercomputing Center, Barcelona, SpainSearch for more papers by this authorCarlos Pérez García-Pando, Carlos Pérez García-Pando Barcelona Supercomputing Center, Barcelona, Spain Catalan Institution for Research and Advanced Studies, Barcelona, SpainSearch for more papers by this authorRostislav Kouznetsov, Rostislav Kouznetsov Atmospheric Composition Unit, Finnish Meteorological Institute, Helsinki, FinlandSearch for more papers by this authorMikhail Sofiev, Mikhail Sofiev Atmospheric Composition Unit, Finnish Meteorological Institute, Helsinki, FinlandSearch for more papers by this authorMelissa E. Brooks, Melissa E. Brooks Met Office, Exeter, United KingdomSearch for more papers by this authorJack Chen, Jack Chen Environment and Climate Change Canada, Ottawa, Ontario, CanadaSearch for more papers by this authorEric James, Eric James CIRES, University of Colorado Boulder, Boulder, Colorado, USA NOAA Global Systems Laboratory, Boulder, Colorado, USASearch for more papers by this authorFabienne Reisen, Fabienne Reisen CSIRO Climate Science Centre, Aspendale, Victoria, AustraliaSearch for more papers by this authorAlan Wain, Alan Wain Australian Bureau of Meteorology, Melbourne, Victoria, AustraliaSearch for more papers by this authorKerryn McTaggart, Kerryn McTaggart Department of Environment, Land, Water and Planning, Government of Victoria, Melbourne, Victoria, AustraliaSearch for more papers by this authorAngus MacNeil, Angus MacNeil Forest Practices Authority, Hobart, Tasmania, AustraliaSearch for more papers by this author Susan M. O'Neill, Susan M. O'Neill Pacific Northwest Research Station, United States Forest Service, Seattle, Washington, USASearch for more papers by this authorPeng Xian, Peng Xian United States Naval Research Laboratory, Marine Meteorology Division, Monterey, California, USASearch for more papers by this authorJohannes Flemming, Johannes Flemming European Centre for Medium-Range Weather Forecasts, Reading, United KingdomSearch for more papers by this authorMartin Cope, Martin Cope CSIRO Climate Science Centre, Aspendale, Victoria, AustraliaSearch for more papers by this authorAlexander Baklanov, Alexander Baklanov World Meteorological Organization, Geneva, SwitzerlandSearch for more papers by this authorNarasimhan K. Larkin, Narasimhan K. Larkin Pacific Northwest Research Station, United States Forest Service, Seattle, Washington, USASearch for more papers by this authorJoseph K. Vaughan, Joseph K. Vaughan Department of Civil and Environmental Engineering, Washington State University, Pullman, Washington, USASearch for more papers by this authorDaniel Tong, Daniel Tong Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, Virginia, USASearch for more papers by this authorRosie Howard, Rosie Howard Earth, Ocean and Atmospheric Sciences Department, The University of British Columbia, Vancouver, British Columbia, CanadaSearch for more papers by this authorRoland Stull, Roland Stull Earth, Ocean and Atmospheric Sciences Department, The University of British Columbia, Vancouver, British Columbia, CanadaSearch for more papers by this authorDidier Davignon, Didier Davignon Environment and Climate Change Canada, Dorval, Quebec City, CanadaSearch for more papers by this authorRavan Ahmadov, Ravan Ahmadov CIRES, University of Colorado Boulder, Boulder, Colorado, USA NOAA Global Systems Laboratory, Boulder, Colorado, USASearch for more papers by this authorM. Talat Odman, M. Talat Odman School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USASearch for more papers by this authorJohn Innis, John Innis EPA Tasmania, Hobart, Tasmania, AustraliaSearch for more papers by this authorMerched Azzi, Merched Azzi Department of Planning and Environment, Government of New South Wales, Sydney, AustraliaSearch for more papers by this authorChristopher Gan, Christopher Gan Centre for Climate Research Singapore, Meteorological Service Singapore, SingaporeSearch for more papers by this authorRadenko Pavlovic, Radenko Pavlovic Environment and Climate Change Canada, Dorval, Quebec City, CanadaSearch for more papers by this authorBoon Ning Chew, Boon Ning Chew Centre for Climate Research Singapore, Meteorological Service Singapore, SingaporeSearch for more papers by this authorJeffrey S. Reid, Jeffrey S. Reid United States Naval Research Laboratory, Marine Meteorology Division, Monterey, California, USASearch for more papers by this authorEdward J. Hyer, Edward J. Hyer United States Naval Research Laboratory, Marine Meteorology Division, Monterey, California, USASearch for more papers by this authorZak Kipling, Zak Kipling European Centre for Medium-Range Weather Forecasts, Reading, United KingdomSearch for more papers by this authorAngela Benedetti, Angela Benedetti European Centre for Medium-Range Weather Forecasts, Reading, United KingdomSearch for more papers by this authorPeter R. Colarco, Peter R. Colarco NASA Goddard Space Flight Center, Greenbelt, Maryland, USASearch for more papers by this authorArlindo Da Silva, Arlindo Da Silva NASA Goddard Space Flight Center, Greenbelt, Maryland, USASearch for more papers by this authorTaichu Tanaka, Taichu Tanaka Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, JapanSearch for more papers by this authorJeffrey McQueen, Jeffrey McQueen NOAA National Centers for Environmental Prediction, College Park, Maryland, USASearch for more papers by this authorPartha Bhattacharjee, Partha Bhattacharjee I. M. Systems Group, NWS/NCEP/EMC, College Park, Maryland, USASearch for more papers by this authorJonathan Guth, Jonathan Guth Météo-France, Toulouse, FranceSearch for more papers by this authorNicole Asencio, Nicole Asencio Météo-France, Toulouse, FranceSearch for more papers by this authorOriol Jorba, Oriol Jorba Barcelona Supercomputing Center, Barcelona, SpainSearch for more papers by this authorCarlos Pérez García-Pando, Carlos Pérez García-Pando Barcelona Supercomputing Center, Barcelona, Spain Catalan Institution for Research and Advanced Studies, Barcelona, SpainSearch for more papers by this authorRostislav Kouznetsov, Rostislav Kouznetsov Atmospheric Composition Unit, Finnish Meteorological Institute, Helsinki, FinlandSearch for more papers by this authorMikhail Sofiev, Mikhail Sofiev Atmospheric Composition Unit, Finnish Meteorological Institute, Helsinki, FinlandSearch for more papers by this authorMelissa E. Brooks, Melissa E. Brooks Met Office, Exeter, United KingdomSearch for more papers by this authorJack Chen, Jack Chen Environment and Climate Change Canada, Ottawa, Ontario, CanadaSearch for more papers by this authorEric James, Eric James CIRES, University of Colorado Boulder, Boulder, Colorado, USA NOAA Global Systems Laboratory, Boulder, Colorado, USASearch for more papers by this authorFabienne Reisen, Fabienne Reisen CSIRO Climate Science Centre, Aspendale, Victoria, AustraliaSearch for more papers by this authorAlan Wain, Alan Wain Australian Bureau of Meteorology, Melbourne, Victoria, AustraliaSearch for more papers by this authorKerryn McTaggart, Kerryn McTaggart Department of Environment, Land, Water and Planning, Government of Victoria, Melbourne, Victoria, AustraliaSearch for more papers by this authorAngus MacNeil, Angus MacNeil Forest Practices Authority, Hobart, Tasmania, AustraliaSearch for more papers by this author Book Editor(s):Tatiana V. Loboda, Tatiana V. LobodaSearch for more papers by this authorNancy H. F. French, Nancy H. F. FrenchSearch for more papers by this authorRobin C. Puett, Robin C. PuettSearch for more papers by this author First published: 20 October 2023 https://doi.org/10.1002/9781119757030.ch9Book Series:Geophysical Monograph Series AboutPDFPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShareShare a linkShare onEmailFacebookTwitterLinkedInRedditWechat Summary Biomass burning has shaped many of the ecosystems of the planet and for millennia humans have used it as a tool to manage the environment. When widespread fires occur, the health and daily lives of millions of people can be affected by the smoke leading to a range of health consequences such as respiratory issues, cardiovascular issues, and mortality. It is critical to include smoke and its consequences in atmospheric modeling systems to meet needs such as informing and protecting the public during smoke episodes. This chapter profiles many of the global and regional smoke prediction systems available. It is not an exhaustive list, but rather a profile of many of the systems to give examples of the creativity and complexity needed to simulate the phenomenon of smoke. The global smoke prediction systems are advanced, and many are self-organizing into a powerful ensemble. Regional and national systems are being developed independently for example in Europe (11 systems), North America (7 systems), and Australia (3 systems). Finally, the World Meteorological Organization is bringing together global and regional systems to form an ensemble to support countries with smoke issues and who lack resources. For each system we discuss how fire activity information is obtained, how fire emissions are calculated, and how atmospheric transport and chemical transformation of the smoke plume is treated. REFERENCES Adams , C. , McLinden , C. A. , Shephard , M. W. , Dickson , N. , Dammers , E. , Chen , J. , et al. ( 2019 ). Satellite-derived emissions of carbon monoxide, ammonia, and nitrogen dioxide from the 2016 Horse River wildfire in the Fort McMurray area . Atmospheric Chemistry and Physics , 19 ( 4 ), 2577 – 2599 . Ahmadov , R. , Grell , G. , James , E. , Csiszar , I. , Tsidulko , M. , Pierce , B. , et al. ( 2017 ). Using VIIRS fire radiative power data to simulate biomass burning emissions, plume rise and smoke transport in a real-time air quality modeling system . Paper presented at the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Akagi , S. K. , Yokelson , R. J. , Wiedinmyer , C. , Alvarado , M. J. , Reid , J. S. , Karl , T. , et al. ( 2011 ). Emission factors for open and domestic biomass burning for use in atmospheric models . Atmospheric Chemistry and Physics , 11 ( 9 ), 4039 – 4072 . Al Mahmud , A. A. ( 2005 ). Evaluation of the AIRPACT2 air quality forecast system for the Pacific Northwest . 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The WMO Vegetation Fire and Smoke Pollution Warning Advisory and Assessment System (VFSP-WAS): Concept, current capabilities, research and development challenges and the way ahead . Biodiversidade Brasileira: BioBrasil ( 2 ), 179 – 201 . https://doi.org/10.37002/biobrasil.v11i2.1738 Barna , M. , Lamb , B. , O'Neill , S. , Westberg , H. , Figueroa-Kaminsky , C. , Otterson , S. , et al. ( 2000 ). Modeling ozone formation and transport in the Cascadia region of the Pacific northwest . Journal of Applied Meteorology , 39 ( 3 ), 349 – 366 . https://journals.ametsoc.org/view/journals/apme/39/3/1520-0450_2000_039_0349_mofati_2.0.co_2.xml Benedetti , A. , Morcrette , J. J. , Boucher , O. , Dethof , A. , Engelen , R. J. , Fisher , M. , et al. ( 2009 ). Aerosol analysis and forecast in the European centre for Medium-Range Weather Forecasts Integrated Forecast System: 2. Data assimilation . Journal of Geophysical Research , 114 ( D13 ). Benedetti , A. , Reid , J. S. , & Colarco , P. R. ( 2011 ). International cooperative for aerosol prediction workshop on aerosol forecast verification . Bulletin of the American Meteorological Society , 92 ( 11 ), ES48–ES53 . Benjamin , S. G. , Weygandt , S. S. , Brown , J. M. , Hu , M. , Alexander , C. R. , Smirnova , T. G. , et al. ( 2016 ). A North American hourly assimilation and model forecast cycle: The rapid refresh . Monthly Weather Review , 144 ( 4 ), 1669 – 1694 . BOM ( 2020a ). Special climate statement 73: Extreme heat and fire weather in December 2019 and January 2020 . http://www.bom.gov.au/climate/current/statements/scs73.pdf BOM ( 2020b ). State of the climate 2020 . http://www.bom.gov.au/state-of-the-climate/documents/State-of-the-Climate-2020.pdf Bowman , D. M. J. S. , Balch , J. K. , Artaxo , P. , Bond , W. J. , Carlson , J. M. , Cochrane , M. A. , et al. ( 2009 ). Fire in the Earth system . Science , 324 ( 5926 ), 481 – 484 . https://www.ncbi.nlm.nih.gov/pubmed/19390038 Bowman , D. M. J. S. , Kolden , C. A. , Abatzoglou , J. T. , Johnston , F. H. , van der Werf , G. R. , & Flannigan , M. ( 2020 ). Vegetation fires in the Anthropocene . Nature Reviews Earth and Environment , 1 ( 10 ), 500 – 515 . Bowman , D. M. J. S. , Williamson , G. J. , Gibson , R. K. , Bradstock , R. A. , & Keenan , R. J. ( 2021 ). The severity and extent of the Australia 2019–20 eucalyptus forest fires are not the legacy of forest management . Nature Ecology and Evolution. https://www.ncbi.nlm.nih.gov/pubmed/33972737 Briggs , G. A. ( 1969 ). Plume rise: A critical survey (No. TID-25075). Air Resources Atmospheric Turbulence and Diffusion Lab ., Oak Ridge, TN . https://www.osti.gov/servlets/purl/4743102 Briggs , G. A. ( 1972 ). Chimney plumes in neutral and stable surroundings . Atmospheric Environment (1967) , 6 ( 7 ), 507 – 510 . Briggs , G. A. ( 1982 ). Plume rise predictions . In Lectures on air pollution and environmental impact analyses . Boston : American Meteorological Society . Brown , T. , Clements , C. , Larkin , N. K. , Anderson , K. , Butler , B. , Goodrick , S. , et al. ( 2014 ). Validating the next generation of wildland fire and smoke models for operational and research use: A national plan . Final report to the Joint Fire Science Program, Project #13-S-1-1. http://www.firescience.gov Byun , D. , & Schere , K. L. ( 2006 ). Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system . Applied Mechanics Reviews , 59 ( 2 ). Campbell , S. L. , Jones , P. J. , Williamson , G. J. , Wheeler , A. J. , Lucani , C. , Bowman , D. M. J. S. , et al. ( 2020 ). Using digital technology to protect health in prolonged poor air quality episodes: A case study of the AirRater app during the Australian 2019–20 fires . Fire , 3 ( 3 ). Chang , L. T.-C. , Barthelemy , X. , Watt , S. , Jiang , N. , Riley , M. , & Azzi , M. ( 2021 ). The use of HYSPLIT in NSW in air quality Management and forecasting . Paper presented at the Clean Air Society of Australia and New Zealand (CASANZ) Conference, Online. Chang , L. T.-C. , Duc , H. , Scorgie , Y. , Trieu , T. , Monk , K. , & Jiang , N. ( 2018 ). Performance evaluation of CCAM-CTM regional airshed modelling for the New South Wales Greater Metropolitan Region . Atmosphere , 9 ( 12 ), 486 . http://www.mdpi.com/2073-4433/9/12/486 Chen , H. ,

O fogo na vegetação, incluindo a aplicação do fogo no uso da terra e na mudança de uso da terra, assim como os incêndios florestais, afetam o funcionamento do sistema terrestre e impõem ameaças significativas à saúde e segurança públicas. Este documento apresenta o conceito de um Sistema de Avaliação e Alerta de Poluição causada por Fumaça decorrente do Fogo na Vegetação (VFSP-WAS, na sigla em inglês). Apresenta-se o fundamento científico do sistema e diretrizes para abordar as questões de fogo na vegetação e poluição por fumaça, indicando-se os principais desafios para a pesquisa. O artigo propõe o estabelecimento de centros regionais VFSP-WAS e mostra exemplos potenciais do conceito VFSP-WAS em duas regiões (sudeste da Ásia e América do Norte), onde centros regionais VFSP-WAS trabalham em parceria com Centros Regionais de Monitoramento de Fogo/Manejo de fogo.

We have investigated the impact of reduced emissions due to COVID-19 lockdown measures in spring 2020 on air quality in Canada’s four largest cities: Toronto, Montreal, Vancouver, and Calgary. Observed daily concentrations of NO2, PM2.5, and O3 during a “pre-lockdown” period (15 February–14 March 2020) and a “lockdown” period (22 March–2 May 2020), when lockdown measures were in full force everywhere in Canada, were compared to the same periods in the previous decade (2010–2019). Higher-than-usual seasonal declines in mean daily NO2 were observed for the pre-lockdown to lockdown periods in 2020. For PM2.5, Montreal was the only city with a higher-than-usual seasonal decline, whereas for O3 all four cities remained within the previous decadal range. In order to isolate the impact of lockdown-related emission changes from other factors such as seasonal changes in meteorology and emissions and meteorological variability, two emission scenarios were performed with the GEM-MACH air quality model. The first was a Business-As-Usual (BAU) scenario with baseline emissions and the second was a more realistic simulation with estimated COVID-19 lockdown emissions. NO2 surface concentrations for the COVID-19 emission scenario decreased by 31 to 34% on average relative to the BAU scenario in the four metropolitan areas. Lower decreases ranging from 6 to 17% were predicted for PM2.5. O3 surface concentrations, on the other hand, showed increases up to a maximum of 21% close to city centers versus slight decreases over the suburbs, but Ox (odd oxygen), like NO2 and PM2.5, decreased as expected over these cities.

The GEM-MACH air quality model has been used by Environment and Climate Change Canada in its operational Regional Air Quality Deterministic Prediction System (RAQDPS) since November 2009. The RAQDPS is run twice daily to produce 48-h forecasts of hourly surface O3, NO2, and PM2.5 concentration fields over North America. In the past decade there have been 20 upgrades of varying magnitude made to the RAQDPS, and it is now possible to examine the evolution of RAQDPS performance skill over the near-decadal period from January 2010 to June 2019. A set of quality-controlled near-real-time hourly measurements of O3, NO2, and PM2.5 surface concentrations for North America has been used for this evaluation. Results of three selected analyses that focus on time trends in performance skill are presented in this study along with a discussion of the impacts of some of the major model upgrades.

Vegetation fires - including the application of fire in land use, land-use change and uncontrolled wildfire - affect the functioning of the Earth System and impose significant threats to health and security. This paper presents the concept of a Vegetation Fire and Smoke Pollution Warning Advisory and Assessment System (VFSP-WAS). It describes the scientific rationale for the system and provides guidance for addressing the issues of vegetation fire and smoke pollution, including key research challenges. The paper proposes the establishment of VFSP-WAS regional centers and describes potential examples of this VFSP-WAS concept from two regions in (Southeast Asia and North America) where regional centers will partner with Regional Fire Monitoring/Fire Management Resource Centers

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015–2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015–2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples’ mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015–2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015–2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO2 + O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.

Environment and Climate Change Canada has initiated the production of a 1980–2018, 10 km, North American precipitation and surface reanalysis. ERA-Interim is used to initialize the Global Deterministic Reforecast System (GDRS) at a 39 km resolution. Its output is then dynamically downscaled to 10 km by the Regional Deterministic Reforecast System (RDRS). Coupled with the RDRS, the Canadian Land Data Assimilation System (CaLDAS) and Precipitation Analysis (CaPA) are used to produce surface and precipitation analyses. All systems used are close to operational model versions and configurations. In this study, a 7-year sample of the reanalysis (2011–2017) is evaluated. Verification results show that the skill of the RDRS is stable over time and equivalent to that of the current operational system. The impact of the coupling between RDRS and CaLDAS is explored using an early version of the reanalysis system which was run at 15 km resolution for the period 2010–2014, with and without the use of CaLDAS. Significant improvements are observed with CaLDAS in the lower troposphere and surface layer, especially for the 850 hPa dew point and absolute temperatures in summer. Precipitation is further improved through an offline precipitation analysis which allows the assimilation of additional observations of 24 h precipitation totals. The final dataset should be of particular interest for hydrological applications focusing on transboundary and northern watersheds, where existing products often show discontinuities at the border and assimilate very few – if any – precipitation observations.

Vegetation fires – including the application of fire in land use, land-use change and uncontrolled wildfire – affect the functioning of the Earth System and impose significant threats to public health and security. This paper presents the concept of a Vegetation Fire and Smoke Pollution Warning Advisory and Assessment System (VFSP-WAS*). It describes the scientific rationale for the system and provides guidance for addressing the issues of vegetation fire and smoke pollution, including key research challenges. The paper proposes the establishment of VFSP-WAS regional centers and describes Potential examples of this VFSP-WAS concept are described from two regions in (South-East Asia and North America) where regional centers will partner with Regional Fire Monitoring / Fire Management Resource Centers. *) https://community.wmo.int/activity-areas/gaw/science/modelling-applications/vfsp-was

Smoke from wildfires contains many air pollutants of concern and epidemiological studies have identified associations between exposure to wildfire smoke PM2.5 and mortality and respiratory morbidity, and a possible association with cardiovascular morbidity. For this study, a retrospective analysis of air quality modelling was performed to quantify the exposure to wildfire-PM2.5 across the Canadian population. The model included wildfire emissions from across North America for a 5-month period from May to September (i.e. wildfire season), between 2013 and 2015 and 2017-2018. Large variations in wildfire-PM2.5 were noted year-to-year, geospatially, and within fire season. The model results were then used to estimate the national population health impacts attributable to wildfire-PM2.5 and the associated economic valuation. The analysis estimated annual premature mortalities ranging from 54-240 premature mortalities attributable to short-term exposure and 570-2500 premature mortalities attributable to long-term exposure, as well as many non-fatal cardiorespiratory health outcomes. The economic valuation of the population health impacts was estimated per year at $410M-$1.8B for acute health impacts and $4.3B-$19B for chronic health impacts for the study period. The health impacts were greatest in the provinces with populations in close proximity to wildfire activity, though health impacts were also noted across many provinces indicating the long-range transport of wildfire-PM2.5. Understanding the population health impacts of wildfire smoke is important as climate change is anticipated to increase wildfire activity in Canada and abroad.

A lockdown was implemented in Canada mid-March 2020 to limit the spread of COVID-19. In the wake of this lockdown, declines in nitrogen dioxide (NO2) were observed from the TROPOspheric Monitoring Instrument (TROPOMI). A method is presented to quantify how much of this decrease is due to the lockdown itself as opposed to variability in meteorology and satellite sampling. The operational air quality forecast model, GEM-MACH (Global Environmental Multi-scale - Modelling Air quality and CHemistry), was used together with TROPOMI to determine expected NO2 columns that represents what TROPOMI would have observed for a non-COVID scenario. Applying this methodology to southern Ontario, decreases in NO2 emissions due to the lockdown were seen, with an average 40% (roughly 10 kt[NO2]/yr) in Toronto and Mississauga and even larger declines in the city center. Natural and satellite sampling variability accounted for as much as 20–30%, which demonstrates the importance of taking meteorology into account. A model run with reduced emissions (from 65 kt[NO2]/yr to 40 kt[NO2]/yr in the Greater Toronto Area) based on emission activity data during the lockdown period was found to be consistent with TROPOMI NO2 columns.

Canadian Air Quality Forecasting and Information SystemsEnvironment and Climate Change Canada (ECCC) has been in charge of the national air quality program for more than 20 years. As of today, air pollution remains one of the most important environmental risk factors to health, in addition to hazardous effects on climate change, ecosystems, properties, and food and water chain.Currently, Canadian air quality forecasting and information systems with observational and modeling components are a key element for policy and mitigation measures, which are used to reduce the negative impacts of air pollution. The operational ECCC’s air quality program provides immediate adaptive measures based on early warning services. In addition to this operational service, the air quality scenario and policy modelling is essential for implementing cost-effective emission reduction strategies and local planning to ensure compliance with air quality standards.Canadian air quality forecasting and information systems also enable access to air quality data at different temporal and spatial scales. This is done through coordination of national activities to facilitate seamless provision of atmospheric composition information at various scales. This work will present Canadian air quality forecasting and information systems, components, collaboration, application and data streaming, as an example that can be helpful in building the WMO GAFIS initiative.

North American air quality (AQ) forecasts made by the Environment and Climate Change Canada (ECCC) operational regional AQ prediction system since 2015 have used input emissions files based on Canadian, U.S., and Mexican national emissions inventories for base years 2010, 2011, and 1999, respectively. Since 2010, however, emissions of many criteria air pollutants have declined in both Canada and the U.S.. We recently tested new input emissions files based on a 2013 Canadian inventory, a projected 2017 U.S. inventory, and a 2008 Mexican inventory in the ECCC regional AQ prediction system. For Canada, the switch from the 2010 inventory to the 2013 inventory reduced SO2, NOx, and VOC annual anthropogenic emissions by 12%, 2%, and 4%, respectively. For the continental U.S., adoption of the projected 2017 inventory reduced SO2, NOx, and VOC annual anthropogenic emissions relative to the 2011 inventory by 65%, 33%, and 11%, respectively, suggesting the importance of emissions base-year representativeness for AQ forecasting. Moreover, the use of these new input emissions fields for 2016 and 2017 test periods improved AQ forecasts in comparison to the operational model for Canada and the U.S., in particular for summertime ozone forecasts over the eastern U.S.. A new version of the ECCC forecast system that uses these updated input emissions files was accepted for operational implementation in mid 2018.

The authors compare modeling system predictions of PM2.5, O3, and NO2 against routine surface measurement sites from 3 different forecasting systems: 1) a system with no wildfire, 2) the existing version of the Canadian forecasting system, and 3) the newly updated Canadian forecasting system. Simulations 2 and 3 include wildfire emissions, which are treated differently in each system. Multiple enhancements to simulating wildfire emissions were implemented in the new forecasting system compared to the existing system including emission factors, plume height, and vertical distribution of smoke emissions within the plume.

Abstract. Biomass burning activities can produce large quantities of smoke and result in adverse air quality conditions in regional environments. In Canada, Environment and Climate Change Canada's (ECCC) operational FireWork air quality forecast system incorporates near-real-time biomass burning emissions to forecast smoke plumes from fire events. The system is based on the ECCC operational Regional Air Quality Deterministic Prediction System (RAQDPS) augmented with near-real-time wildfire emissions using inputs from the Canadian Forest Service's (CFS) Canadian Wildland Fire Information System (CWFIS). Recent improvements to the representation of fire behaviour and fire emissions have been incorporated into the CFS Canadian Forest Fire Emissions Prediction System (CFFEPS). This is a bottom-up system linked to CWFIS in which hourly changes in biomass fuel consumption are parameterized with hourly forecasted meteorology at fire locations. CFFEPS has now also been connected to FireWork. In addition, a plume-rise parameterization based on fire energy thermodynamics is used to define the smoke injection height and the distribution of emissions within a model vertical column. The new system, FireWork-CFFEPS, has been evaluated over North America for July–September 2017 and June–August 2018, both periods when western Canada experienced historical levels of fire activity with poor air quality conditions in several cities as well as other fires affecting northern Canada and Ontario. Forecast results were evaluated against hourly surface measurements for the three pollutant species used to calculate the Canadian Air Quality Health Index (AQHI), namely PM2.5, O3, and NO2, and benchmarked against the operational FireWork system (FireWork-Ops). This comparison shows improved forecast performance and predictive skills for the FireWork-CFFEPS system. Modelled fire plume injection heights from CFFEPS based on fire energy thermodynamics show higher plume injection heights and larger variability. The changes in predicted fire emissions and injection height reduced the consistent over-predictions of PM2.5 and O3 seen in FireWork-Ops. On the other hand, there were minimal fire emission contributions to surface NO2, and results from FireWork-CFFEPS do not degrade NO2 forecast skill compared to the RAQDPS. Model performances statistics are slightly better for Canada than for the U.S., with lower errors and biases. The new system is still unable to capture the hourly variability of the observed values for PM2.5, but it captured the observed hourly variability for O3 concentration adequately. FireWork-CFFEPS also improves upon FireWork-Ops categorical scores for forecasting the occurrence of elevated air pollutant concentrations in terms of false alarm ratio (FAR), and critical success index (CSI).

Since the last ITM in October 2016, the Canadian operational Regional Air Quality Deterministic Prediction System (RAQDPS) has been ported to a new high-performance computing system and has been updated to use a new meteorological initialization method, a new meteorological “piloting” model, a new and faster version of the GEM-MACH code, and a new set of input emissions files and to produce an expanded set of output fields. These updates are briefly described and some examples are given of their impact on RAQDPS forecast performance, including improved NO2 forecasts and a large reduction (~10 ppbv) in summertime ozone overpredictions for the eastern United States.

FireWork is an on-line, one-way coupled meteorology–chemistry model based on near-real-time wildfire emissions. It was developed by Environment and Climate Change Canada to deliver operational real-time forecasts of biomass-burning pollutants, in particular fine particulate matter (PM2.5), over North America. Such forecasts provide guidance for early air quality alerts that could reduce air pollution exposure and protect human health. A multi-year (2013–2016) analysis of FireWork forecasts over a five-month period (May to September) was conducted. This work used an archive of FireWork outputs to quantify wildfire contributions to total PM2.5 surface concentrations across North America. Different concentration thresholds (0.2 to 28 µg/m3) and averaging periods (24 h to five months) were considered. Analysis suggested that, on average over the fire season, 76% of Canadians and 69% of Americans were affected by seasonal wildfire-related PM2.5 concentrations above 0.2 µg/m3. These effects were particularly pronounced in July and August. Futhermore, the analysis showed that fire emissions contributed more than 1 µg/m3 of daily average PM2.5 concentrations on more than 30% of days in the western USA and northwestern Canada during the fire season.