Monitoring, Analysis, and Prediction of Air Quality (MAP-AQ)

Overarching Objective:

Develop and implement a global air pollution monitoring, analysis, and prediction system for air quality with downscaling capability in regions of the world affected by high levels of atmospheric pollutants, in particular in Asia, Latin America, and Africa.

Description:

MAP-AQ stands for Monitoring, Analysis, and Prediction of Air Quality. This is a new international initiative that has been endorsed as an emerging activity of the International Global Atmospheric Chemistry (IGAC) project and a contributing activity to the Global Atmosphere Watch (GAW) program of the WMO. MAP-AQ focuses on a number of activities listed below.

  • To constitute and develop a consortium of expert groups to coordinate and enhance research and services that will help mitigate air pollution, specifically in regions of the world where high concentrations of pollutants are observed.
  • To develop and implement a global air pollution monitoring, analysis, and prediction system with downscaling capability in regions of the world that are affected by high levels of atmospheric pollutants, particularly in the low and middle-income countries.
  • To combine an ensemble of state-of-the-art multi-scale chemical transport models, high-resolution emission inventories, space observaions, surface measurements and post-processing techniques to provide near-real-time forecasts and analyses of air pollution and its effect at the global to regional and local scales.
  • To co-design and co-develop with users and other stakeholders relevant products and services, and transfer air quality related information to the public.
  • To co-design and co-develop with policymakers emission control strategies to reduce air pollution in the long-term.
  • To create collaborative efforts for the application of the system to urban planning.
  • To develop educational activities in support of the capacity building.

 

MAP-AQ co-Chairs:

Guy P Brasseur (NCAR/Max Planck Institute for Meteorology) brasseur@ucar.edu
Rajesh Kumar (NCAR) rkumar@ucar.edu

MAP-AQ Steering committee:

Vincent-Henri Peuch (European Center for Medium Range Weather Forecasting (ECMWF), UK), Vincent-Henri.Peuch@ecmwf.int
James H. Crawford (National Aeronautics and Space Administration (NASA), USA), james.h.crawford@nasa.gov  
Nicolas Huneeus (University of Santiago, Chile), nhuneeus@dgf.uchile.cl
Rebecca Garland (Council for Scientific and Industrial Research, South Africa),  RGarland@csir.co.za
Manish Naja (Aryabhatta Research Institute of Observational Sciences, India), manish@aries.res.in
Xuemei Wang (Jinan University, China), eciwxm@jnu.edu.cn  
Yvonne Scorgie (Office of Environment and Heritage, Australia), Yvonne.Scorgie@environment.nsw.gov.au 
Ashraf Zakey (The Egyptian Meteorological Authority, Egypt), ashzakey@gmail.com  

Ex-Officio:
Alexander Baklanov (World Meteorological Organization (WMO), Geneva), abaklanov@wmo.int
Judith Hoelzemann (International Global Atmospheric Chemistry (IGAC)), judith.hoelzemann@ccet.ufrn.br 

Projects led by MAP-AQ members:

1. Partnership with China on Space Data (PANDA): This project has developed an operational multi-model air quality forecasting system based on nine different chemistry transport models and provides daily forecasts of ozone, nitrogen oxides, and fine particulate matter for the 37 largest urban areas of China. The forecasts are disseminated through a publicly accessible website: http://www.marcopolo-panda.eu, Funding Agency: EU, Principal Investigator: Guy P. Brasseur

2. Prediction of Air Pollution in Latin America (PAPILA): This project is developing an operational multi-model air quality forecasting system for Latin America similar to the MarcoPolo-PANDA system developed for China., Funding Agency: EU, Principal Investigator: Guy P. Brasseur

3. AirQuip Project (https://wiki.met.no/airquip/start): This project has developed a downscaling tool and is providing daily operational air quality forecasts for all Norwegian municipalities and the general public (https://luftkvalitet.miljostatus.no/). High-resolution air quality forecasts are generated using EMEP model runs which in turn use CAMS global boundary conditions, bridging all scales from global to 50 meters. Funding Agency: Research Council of Norway, Principal Investigator: Michael Gauss

Publications led by MAP-AQ members:

1. Kumar, R., Peuch, V.-H., Crawford, J., and Brasseur, G. P.: Five steps to improve air-quality forecasts, Nature, 561, 27-29, 2018.
 
2. Brasseur, G. P., Xie, Y., Petersen, A. K., Bouarar, I., Flemming, J., Gauss, M., Jiang, F., Kouznetsov, R., Kranenburg, R., Mijling, B., Peuch, V.-H., Pommier, M., Segers, A., Sofiev, M., Timmermans, R., van der A, R., Walters, S., Xu, J., and Zhou, G.: Ensemble forecasts of air quality in eastern China – Part 1: Model description and implementation of the MarcoPolo–Panda prediction system, version 1, Geosci. Model Dev., 12, 33-67, https://doi.org/10.5194/gmd-12-33-2019, 2019.
 
3. Petersen, A. K., Brasseur, G. P., Bouarar, I., Flemming, J., Gauss, M., Jiang, F., Kouznetsov, R., Kranenburg, R., Mijling, B., Peuch, V.-H., Pommier, M., Segers, A., Sofiev, M., Timmermans, R., van der A, R., Walters, S., Xie, Y., Xu, J., and Zhou, G.: Ensemble Forecasts of Air Quality in Eastern China – Part 2. Evaluation of the MarcoPolo-Panda Prediction System, Version 1, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-234, in review, 2018. 

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