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Global Air Quality Forecasting and Information System (GAFIS)

Urban air pollution

Air pollution represents a serious environmental problem. Each year, 7 million premature deaths are attributed to air pollution, with huge economic consequences – estimates indicate $5 trillion in welfare losses and $255 billion in lost income (World Bank Report, 2016). Furthermore, air pollution is detrimental for ecosystems, damages property, impacts visibility and haze, and threatens food and water security. Some Pollutants such as tropospheric ozone are also climate forcers while aerosols tend to produce atmospheric cooling. 

The Global Air Quality Forecasting and Information System (GAFIS) initiative builds a platform for providers and user of air quality forecast and information systems. It will enable access to, and use of, air quality prediction and analysis products at various temporal and spatial scales and bring the atmospheric composition component to WMO’s Earth System approach for developing NWP and Climate monitoring and modelling.

GAFIS will develop harmonized standards of operations by primarily looking at existing WMO standards and in the context of the Global Data Processing and Forecasting System (GDPFS). Additionally, it will be fully inclusive, comprising operational activities as well as pre-operational and experimental ones to engage with the entire community.

GAFIS will coordinate activities to help Developing and Least Developed Countries in reaching their air quality standards and Sustainable Development Goals. GAFIS will promote that air quality related products and services freely and openly.

 

Objectives 

GAFIS is one of the emerging services that will support the health community, and society, with globally consistent air quality forecasting and information systems that operate from the global to regional to urban scale. 

The high-level objective of GAFIS is: “to enable and provide air quality forecasting and information services in a globally harmonized and standardized way tailored to the needs of society”.

 

GAFIS Steering Committee

Member List

ToRs

 

Partners 

The contributions from other partners are open. We particularly engage the WMO operational community.

APP SAG 

The GAW Scientific Advisory Group (SAG) on Modelling Applications (SAG-APPs) was established in 2016 by the WMO Congress to enhance the exchange between the GAW observational community, the modelling communities and other-end users of atmospheric composition data. Near-real-time data applications, such as air quality forecasting, need timely access to observations- in providing such services.
The main objective of the SAG-Apps is to further develop a portfolio of modelling products and services related to atmospheric composition, and more specifically to demonstrate the usefulness of exchanging chemical observational data in Near-Real-Time (NRT; i.e. hours-days) in support of monitoring and forecasting applications.

CAMS

The Copernicus Atmosphere Monitoring Service (CAMS) is one of six services that form Copernicus, the European Union's Earth observation programme which looks at our planet and its environment for the ultimate benefit of all European citizens. Copernicus offers information services based on satellite Earth observation, in situ (non-satellite) data and modelling.

GURME 

The WMO GAW Urban Research Meteorology and Environment (GURME) project arose in response to the requests for assistance by many National Meteorological Services (NMSs) dealing with urban issues, and in recognition that the management of urban environments requires special attention. GURME is an integral part of urban research and services, and its activities include:

  • defining meteorological and air quality measurements that support urban forecasting
  • providing cities access to air quality numerical prediction systems and monitoring information which serve as the basis for health-related prediction services, and
  • promoting city pilot projects for different cities to demonstrate successful expansion of MeteoServices for urban environment issues.

ICAP 

International Cooperative for Aerosol Prediction (ICAP) is an international forum for aerosol forecast centers, remote sensing data providers, and lead systems developers to share best practices and discuss pressing issues facing the operational aerosol community. While the dynamical meteorology community has a well developed protocols and near real-time observing systems to support forecasting, the aerosol community is only beginning to organize. Infrastructure and data protocols need to be developed between operational centers in order to fully support this emerging field.

MAP-AQ 

Monitoring, Analysis, and Prediction of Air Quality (MAP-AQ) is an 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) Programme of the World Meteorological Organization (WMO).
The overarching objective of MAP-AQ is to 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.

PREFIA

Air Quality Prediction and Forecasting Improvement for Africa (PREFIA) is to develop and improve air quality prediction and forecasting capabilities and related meteorological analysis for African applications through an international science and training effort.

SDS-WAS

The WMO Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) was established in 2007 in response to the intention of 40 WMO member countries to improve capabilities for more reliable sand and dust storm forecasts. Research forecasting products from atmospheric dust models may substantially contribute to risk reduction in many areas of societal benefit. It will rely on real-time delivery of products.

More than 15 organizations currently provide daily dust forecasts in different geographic regions. The SDS-WAS integrates research and user communities (e.g. medical, aeronautical, agricultural users). SDS-WAS is established as a federation of partners organized around regional nodes. At the moment two nodes are established: the Northern Africa-Middle East-Europe Node (hosted by Spain) and the Asian Node (hosted by China). The SDS-WAS mission is to achieve comprehensive, coordinated and sustained observations and modeling capabilities of sand and dust storms in order to improve the monitoring of sand and dust storms to increase the understanding of the dust processes and to enhance dust prediction capabilities.

UN Environment

The Global Environment Monitoring System for Air (GEMS Air) is the UN Environment Programme mechanism on air quality monitoring that builds and maintains collaboration amongst global stakeholders to enhance and keep the state of the quality of the world’s air quality. It builds capacity and generates services in partnership with multiple stakeholders using low cost sensors to support the development of evidence-based air quality management policies and to support actions for mitigating air pollution.

The main vision of GEMS Air is catalyzes scalable innovation using science and technology know-how, to enable developing country governments to drive transformation that improve the air their citizens breathe.

VFSP-WAS 

The WMO Vegetation Fire and Smoke Pollution Warning and Advisory System (VFSP-WAS) is an international network of research, national operational centres and users organised through regional nodes assisted by regional centres, to deal with the societal impacts of fires and smoke pollution.
The VFSP-WAS aims to enhance the ability of countries to deliver timely and quality vegetation fire and smoke pollution forecasts, observations, information and knowledge to users through an international partnership of research and operational communities. VFSP-WAS is organised as a federation of regional partners and realised through regional activity Nodes and Regional Vegetation Fire and Smoke Pollution Warning and Advisory Centres (RVFSP-WAC).

WHO

In 2018, WMO and WHO signed a Collaboration Framework on Climate, Environment and Health (i.e. Memorandum of Understanding) committing the WHO and WMO to work more closely together to protect health from the risks of extreme weather and climate events, pollution of air and water, and global climate change. Please see here for details.

Implementation 

GAFIS will serve as an international coordinating mechanism and establish and propagate consistent methods and standards for existing and upcoming air quality forecasting and monitoring services, as well as for air quality observations used for air quality forecast evaluation. The methodology is relatively mature that reliable air quality forecasts can be provided at the global, regional and urban scales by combining model simulations with information based on observations. 
To ensure the development of products and services for the variety of user communities, and also to support needed cross-cutting research activities broad application areas have been identified based on their temporal and spatial scales. They are used to streamline research and implementation strategies that build on the observations:

  • Monitoring of Atmospheric Composition
  • Forecasting Atmospheric Composition Change and their induced environmental phenomena
  • Providing Atmospheric Composition information to support services in urban and populated areas
Fig. Schematic overview of potential GAW service

Fig. Schematic overview of potential GAW service

(WMO Global Atmosphere Watch (GAW) Implementation Plan: 2016-2023)

 

Global Forecast

Daily air quality “chemical weather” forecasts at the global scale are already provided operationally by established institutions. For example, the Copernicus Atmosphere Monitoring Service provides global air quality forecast that forecast the impact of anthropogenic emissions, desert dust and wild fires on air quality at a resolution of about 40 km.  

Regional Forecast

Regional forecasts can be more accurate than the global forecast due to their capability of resolving more spatial details of the emission, the chemistry and the transport. In North America and Europe such regional models are already operational. They use global forecasts as lateral boundary conditions.
For other parts of the world, the MAP-AQ projects MarcoPolo and Panda have developed an operational air quality forecasting system which provides daily forecasts of ozone, nitrogen oxides, and fine particulate matter for the 37 largest urban areas of China. A similar forecasting system is developed for Latin America (PAPILA).

Urban Forecast

In cities both local meteorology and infrastructure including buildings determine the propagation of pollutants. Thus, pollution levels can vary tremendously between different streets. Such information may guide sustainable planning in cities, and people to use less polluted streets to protect their health. In many cities a substantial contribution to urban pollution comes from outside of the cities, hence urban scale modelling requires proper link to regional scale modelling. 

Downscaling

To obtain air quality information for a specific region, city or even street, higher spatial resolution of the forecasting model is required than the global or regional air quality forecast. Downscaling employs a higher resolution for a specified area, similar to a magnifying glass. The large scale information of the global or regional model is used as input. Urban Air quality forecasts are often produced from downscaling of global or regional forecasts.

 

Demonstration/Outcomes 

Global Products

CAMS

CAMS provides five-day forecasts of aerosols, atmospheric pollutants, greenhouse gases, stratospheric ozone and the UV-Index every day. Example is shown below and the full range of forecast charts is available here.

Fig. Aerosol optical depth at 550 nm 11 Feb 00 UTC 2020  (provided by CAMS, the Copernicus Atmosphere Monitoring Service)

Fig. Aerosol optical depth at 550 nm 11 Feb 00 UTC 2020
 (provided by CAMS, the Copernicus Atmosphere Monitoring Service)
 

WHO Global Ambient Air Quality Database

Example from WHO Global Ambient Air Quality database is shown below. Forecast and products are available here.

WHO Global Ambient Air Quality Database

UNEP Global Environmental Platform

Example from UNEP Global Environmental Platform is shown below. Forecast and products are available here.

UNEP

 

Regional Products

MarcoPolo and Panda project

Example below is obtained from MarcoPolo and Panda Project within the EU FP7 Programme  . Forecast and products are available here.

MarcoPolo and Panda project

SDS-WAS Regional Centre for Northern Africa, Middle East and Europe

Examples below is obtained from SDS-WAS NA-ME-E. Forecast and products are available here.

SDS-WAS Regional Centre for Northern Africa, Middle East and Europe

 

SDS-WAS Regional Centre for Asia 

Example below is obtained from SDS-WAS Asia. Forecast and products are available here.

SDS-WAS Regional Centre for Asia

SDS-WAS Regional Centre for Pan American

Example below is obtained from SDS-WAS Pan American Regional Centre. Forecast and products are available here.

SDS-WAS Regional Centre for Pan American

VFSP-WAS Regional Centre for Southeast Asia

Examples below is obtained from VFSP-WAS Southeast Asia Regional Centre. Forecast and products are available here.

VFSP-WAS Regional Centre for Southeast Asia

 

Urban Products

Urban Health, Air Quality and Climate: Mexico City Case Study

Examples below is obtained from Mexico City Pilot Project of the WMO GAW Urban Research Meteorology and Environment Project (GURME). Forecast and products are available here.

Urban Health, Air Quality and Climate: Mexico City Case Study

System of Air Quality forecasting and Research (SAFAR)--India

Examples below is obtained from SAFAR-India Commonwealth Games Pilot Project of the WMO GAW Urban Research Meteorology and Environment Project (GURME). Forecast and products are available here.

System of Air Quality forecasting and Research (SAFAR)--India

 

 

 

Global to Local Air Quality Forecast Inventory

As a first step of setting up GAFIS, we are performing the survey on the air quality forecasting system you operate and the products you provide. We encourage you to share this survey with your community to make sure a wide range AQ forecast is catalogued. The results of the survey will be shared with all participants and the air quality community.

The survey is available here.

We really appreciate your taking the time and providing the input!