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Air Quality Assessment for Chinese Industrial Regions

This project aims to provide air quality information for large industrialized regions and metropolitan areas in China through modeling and data analysis. The goal is to support policy makers, scientists, and the general public with accurate air quality assessments.

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Air Quality Assessment for Chinese Industrial Regions

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  1. FP7 MarcoPoloWP5Air Quality Assessment and ForecastingWP5 lead by DMIPartners/ Teams involved: KNMI, VITO, FMI, DUTH, and DMI 3rd Annual Meeting of the FP7 EU MarcoPolo Project 28Feb 2017, Beijing, China

  2. WP5 Main Goal To provide air quality information for selected Chinese largely industrialized regions and metropolitan areas by running models at different spatial scales The aim of the MarcoPolo service is to provide air quality information to the end-users (policy makers, scientists and general public) - interested in actual situation and in assessments over certain time periods

  3. WP5 Objectives O1 – to develop a modelling chain (regional-urban-city scale) with setup, testing, and validation using remote sensing and ground-based observations; O2 – downscaling air quality modelling chain as a service for East China (regional), Beijing-Tianjin-Hebei region, Yangtze and Pearl Rivers deltas (urban) and Shanghai, Beijing, Pearl River Delta metropolitan areas (urban/city scales); O3 – to study relationships, interactions and two-way feedbacks between pollution and meteorology/climate for selected Chinese regions.

  4. WP5 Timeline, Resources & Tasks Start – M06 -> End – M36+ Total Person-Months – 36 all spent Task 5.1: Regional air quality forecasting (KNMI) Task 5.2: Urban air quality modelling (VITO) Task 5.3:City/urban-scale air quality modelling (DMI & FMI) Task 5.4:Relationship between air pollution and meteorology (DMI & DUTH)

  5. WP 5 Deliverables D5.1 - Operational model and forecast results on a regional scale for East-China (Resp - KNMI, Other/ Public, completed) D5.2 - Assessment by modelling on an urban scale for the Yangtze River delta region (Resp - VITO, Report / Public, internal review) D5.3 - Urban/City scale modelling for metropolitan areas of Shanghai, Beijing, and Pearl River Delta (Resp - DMI, Other/Short Report/ Public, internal review) D5.4 - Relationship between air pollution and meteorology/ climate (Resp - DMI, Report / Public, completed)

  6. WP5 Presentations • Operational model and forecast results on a regional scale for East-China • B. Mijling, J. Ding, Fei Liu, R. van der A • for Task 5.1. & Del 5.1 • Urban Air Quality Modelling • Hans Hooyberghs, N. Veldeman, B. Maiheu • for Task 5.2 & Del 5.2 • Air quality assessment and forecasts in Asia with System for Integrated modeLling of AtmoshericcoMposition (SILAM) • M.Sofiev, RostislavKouznetsov, J.Vira, M.Prank, J.Soares, V.Tarvainen • for Tasks 5.3 (&5.1) & Del 5.3 (& 5.1) • Enviro-HIRLAM Downscaling for China: operational forecasting & HARMONIE aerosol experiments • Alexander Mahura, B. Amstrup, R. Nuterman, K.Nielsen, X. Yang, A. Baklanov • for Tasks 5.3 (&5.4) and Dels 5.3 (& 5.4) • Satellite investigation of aerosol-cloud relations • K. Kourtidis, ArisGeorgoulias, S. Stathopoulos • for Task 5.4 & Del 5.4

  7. WP 5 E-mail List Bas Mijling KNMI [mijling@knmi.nl] Hans Hooyberghs VITO [Hans.Hooyberghs@vito.be] Nele Veldeman VITO [Nele.Veldeman@vito.be] Peter Viaene VITO [Peter.Viaene@vito.be] Lisa Blyth VITO ‎[Lisa.Blyth@vito.be]‎‎ Alexander Mahura DMI [ama@dmi.dk] Kristian P. Nielsen DMI [kpn@dmi.dk] Xiaohua Yang DMI [xx@dmi.dk] Mikhail Sofiev FMI [Mikhail.Sofiev@fmi.fi] Julius Vira FMI [Julius.Vira@fmi.fi] Rostislav Kouznetsov FMI [Rostislav.Kouznetsov@fmi.fi] Konstantinos Kourtidis DUTH [kourtidi@env.duth.gr] Aristeidis Georgoulias DUTH [ageor@auth.gr] Stavros Stathopoulos DUTH [sstathop@env.duth.gr]

  8. WP5 Presentations • VITO has identified the user needs for urban‐scale, high resolution modelling. Local authorities want to identify the hotspots within their city, and they want to know which sector causes the pollution and where it (geographically) comes from. • Three case study cities (Shijiazhuang, Tianjin and Chengdu) have been studied using a prototype model chain, which combines a local Gaussian dispersion model (IFDM) with a background estimate based on measurements. • Results for Shijiazhuang have been compared with local particulate matter measurements. The validation points at successes (correct time series) and shortcomings (deviations of the spatial pattern caused by unknown emissions), and identifies potential improvements.

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