Who this module is designed for?

☒ Public authorities

☐ Municipalities

☒ Research centres

☐ Impacted industries (e.g.: solar plant and electricity grid operators, health industry…)

☒ Emitting Industries (e.g.: Fracking)

☐ Emergency services

☐ Airports and flight control authorities

☐ Citizens

Geographical coverage

All countries of the world in addition to states/provinces for the largest countries (USA, Canada, Russia, China and India) for the global atlas. For the regional atlas, central and southern Chile (Chile), CONUS area (USA) and China will be available and other regions may be developed afterwards depending on the demand.

Current progress of the module

The layout of Module 1 is shown below. In the topmost part (A), the user can chose between the Global and the Regional Atlas, select the country and target city or region, the data type and the time frame and resolution. The atlases both consist of a map (B) with zooming capability for each of the pollutants, a time series and statistical analysis tools. In the Global Atlas, air quality maps of the entire world at 80 km grid resolution are shown based on historical Copernicus Atmosphere Monitoring Service (CAMS) reanalysis data, NO2 column integrated data from the satellite-based Ozone Monitoring Instrument (OMI) and aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS).
The Regional Atlas allows the user to understand and research historical and current air pollutants in a specific area. It is based on modelling data from the WRF-Chem and SILAM models, and satellite-based observations of NO2 from OMI and the TROPOspheric Monitoring Instrument (TROPOMI) and AOD from MODIS.
Below the map (C), the user can choose between a statistical summary at country level or from a manually selected area. Depending on the selection, in (D) a summary (mean, standard deviation and total relative change within the chosen time frame) and in (E) a time series for each pollutant are shown below, averaged either for the selected country or the area selected on the map.
If the Country Data tab was selected above, the next plot allows the user to relate air quality data to demographic data over time for different pollutants and different demographic variables such as gross domestic product or population density for the selected country (F). The last plot (G) sets the selected country in relation to other countries. A time series of the relative change of each pollutant since the beginning of the chosen time frame is shown. On the right side, an overview of the total change since the beginning of the chosen time frame until the end is shown for the selected country and a list of other countries.
If the Surface Data tab was chosen, polygons can be drawn on the map in (B). The Pollutant Summary graph (D) below shows then the overview of all pollutants for the selected area (mean, standard deviation and total relative change within the chosen time frame), the Pollutants Time Series graph (E) shows the absolute levels of each pollutant with time in the selected area and the Pollutants Change over Time graph (G) shows the relative levels with time for each pollutant in the selected area.
The data can be exported by clicking on the Export Data button (H) on the bottom of the page.

What does this module do ?

Module 1 presents the Global and Regional Air Quality Atlases. It allows users to easily understand the air quality and its change over time in different areas in their country or region. This will help policymakers and local authorities to take informed decisions to improve air quality, provide NGOs with necessary information to act, and grant researchers and students easy access to global and regional air quality data. It includes global and regional atlases of individual air pollutants, graphical and numerical information on the regional climatology of air pollutants based on the Copernicus CAMS model global reanalysis and regional reanalyses for three regions, the Contiguous United States (CONUS), Chile and China, as well as satellite information on AOD and NO2.

Value-chain

Global atlas of air quality indices and reports

Click on the image to enlarge it. Regional atlases of air quality indices and reports Click on the image to enlarge it.

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What does this module do ?

The purpose of this module is to provide information on various sources of air pollution and simulate potential changes in air quality in response to proposed mitigation strategies.

It allows the user to reduce the emissions of

one type of pollution source and demonstrates the effect on the pollution levels in the area. Furthermore, it provides attribution information of air pollution in regard to different sectors (e.g. agriculture, traffic, industry) and to different regional origins (e.g. countries or states, local versus transboundary), allowing more informed decisions on an air pollution mitigation strategy.

It includes two products as support for air quality policy: The product #6 providing information on the attribution of emission sources for different regions and economic sectors with emphasis on the role of agricultural emissions and the product #7 allowing the assessment of the efficiency of alternative actions to mitigate air pollution as well as the development of effective strategy options for air pollution abatement.

Who this module is designed for?

Product #6: Attribution service with focus on agricultural sources

☒ Public authorities

☒ Municipalities

☒ Research centres

☐ Impacted industries (e.g.: solar plant and electricity grid operators, health industry…)

☒ Emitting Industries (e.g.: Fracking)

☐ Emergency services

☐ Airports and flight control authorities

☒ Citizens

Product #7: Emission mitigation service

☒ Public authorities

☒ Municipalities

☒ Research centres

☐ Impacted industries (e.g.: solar plant and electricity grid operators, health industry…)

☐ Emitting Industries (e.g.: Fracking)

☐ Emergency services

☐ Airports and flight control authorities

☐ Citizens

Geographical coverage

Beijing (China), Colorado (USA), Santiago de Chile (Chile) will be available at the end of the project.
Other regions may be developed afterwards depending on the demand.

Value-chain

Attribution service with focus on agricultural sources

Click on the image to enlarge it. Emission mitigation service

Click on the image to enlarge it.

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Current progress of the module

The layout of Module 2 in shown below. In the upper most part (A) of the module the user can choose the location (Santiago de Chile, Chile; Colorado, USA; Beijing, China). Below, a map (C) shows the current level for a chosen pollutant or the change over time. On the panel left of the map (B), the user can individually reduce different emission sources (agriculture, traffic, combustion etc.). The resulting pollutionlevels are then displayed on the map. After that, the user can choose a location on the map and the followinggraphs below show the results for that location.Directly below the pollutant map, a time series (D) shows the actual concentrations as well as the simulatedconcentrations if the pollution source is reduced on the panel next to the map. When hovering over the linesin (D), a popup appears summarizing the mitigated pollutant concentrations at a certain moment in time. The “Country/Region Contribution” panel (E) indicates the contribution by various regions/countries to the concentration level of the selected pollutant at the chosen location:

• Santiago de Chile: PM, NO2 (+ possibly at a later stage SO2/ health index): Santiago, Chile, all South American countries separately, Intercontinental (from outside South America)
• Front Range, Colorado: PM, NO2 (+ possibly at a later stage SO2/ health index): Colorado, neighbouring states, other US, Canada, Mexico, other
• Front Range, Colorado CO: U.S. anthropogenic sources, U.S. biomass burning, non-U.S. fires, non-U.S.total, CO transported from Asia.

Hereby, the health indices will follow the definition of the respective countries. The “Sector Contribution” panel (F) shows the source contribution by sector for the chosen pollutant. The contribution of the following sectors will be shown:

• Santiago and Colorado (for PM and NO2): Agriculture, residential combustion, road traffic, non-road traffic, power plants, industry, mining and extraction, wildfires, marine, dust, boundary
• Front Range Colorado (CO only): Anthropogenic, fires, chemical, boundary, boundary fires
• Beijing (PM, O3, NO2): Traffic, Industry, Residential.

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What does this module do ?

The purpose of this module is to provide information on the possible impact of fracking activities (or more general oil and gas extraction activities) on the air quality in nearby and distant areas. As opposed to the other modules in the AQ-WATCH system, this module is not real-time and is rather an informational tool.

For this module, we are demonstrating the abilities of the tool for a specific region (Front Range, CO, USA) and showing the impact on neighbourhoods near the fracking and related activities and distant to them as well as on sensitive locations (e.g. hospitals, schools).

The product provides predictions of the potential impact on regional air quality (e.g., ozone levels) due to fracking and related operations and determination of the exposure of the local population to related emissions of hydrocarbons.

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Who this module is designed for?

☒ Public authorities

☒ Municipalities

☒ Research centres

☐ Impacted industries (e.g.: solar plant and electricity grid operators, health industry…)

☒ Emitting Industries (e.g.: Fracking)

☐ Emergency services

☐ Airports and flight control authorities

☐ Citizens

Geographical coverage

Colorado will be available at the end of the project.
Other regions may be developed afterwards depending on the demand.

Value-chain

Click on the image to enlarge it.

Current progress of the module

The layout of Module 4 is shown ibelow. The location can be chosen in (A). The top part of the module shows a map (B) where fracking activities are indicated and the concentration of several pollutants either with or without the fracking activities are shown. The grid resolution of the map is 4 km. The user will be able to choose between the following pollutants to be displayed:

• O3
• Benzene
• Toluene
• NOx
• Ethane
• Propane
• HCHO

Below the map a time series of each pollutant with and without the impacts of oil and gas extraction is shown based on the location that the user chooses on the map above (C). When hovering over the lines, a pop-up shows the pollutant levels with vs. without the fracking activities at the chosen point in time.
The data can be exported in (D).

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What does this module do ?

The purpose of this module is to provide information on the occurence of episodic events as it is sand and dust storms and wildfires. This product aims to help air quality and solar energy stakeholder by providing predictions of the degradation of air quality and reduction in visibility caused by sand and dust strom and wildfires.

It includes two products:

• The product #3 predicting the degradation of air quality and reduction in visibility caused by dust mobilization and impact of the presence of mineral dust on solar irradiance forecasts. The purpose of this module is to provide information on airborne mineral dust, mineral dust deposition and solar irradiance forecast products. These products are providing added-value information to assist air quality and solar energy stakeholders, for example in planning cleaning and maintenance times of solar panels.

• The product #4 predicting the degradation of air quality and reduction in visibility caused by the occurrence of wildfires and the development of a related regional alert system.
  The purpose of this module is to provide a forecast of air pollution data related to wildfires to assist stakeholders such as policymakers, local authorities and emergency services.

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Who this module is designed for?

Product #3: Dust and solar energy forecasts

☐ Public authorities

☐ Municipalities

☒ Research centres

☒ Impacted industries (e.g.: solar plant and electricity grid operators, health industry…)

☐ Emitting Industries (e.g.: Fracking)

☐ Emergency services

☐ Airports and flight control authorities

☐ Citizens

Product #4: Wildfire and Visibility Service

☒ Public authorities

☒ Municipalities

☒ Research centres

☐ Impacted industries (e.g.: solar plant and electricity grid operators, health industry…)

☐ Emitting Industries (e.g.: Fracking)

☒ Emergency services

☒ Airports and flight control authorities

☒ Citizens

Geographical coverage

China, Colorado, Northern Chile will be available at the end of the project.
Other regions may be developed afterwards depending on the demand.

Value-chain

Dust and solar energy forecasts Click on the image to enlarge it. Wildfire and Visibility Service Click on the image to enlarge it.

Current progress of the module

DUST AND FIRE MODULE The user can select the location and submodule type (i.e., dust or fire product) in (A). This module will be available for three regions in the first phase:

• Chile (78ºW – 60ºW; 32ºS – 17ºS)
• Colorado (124ºW – 102ºW; 25ºN – 46ºN)
• Beijing, China (72ºE – 128ºE; 26ºN – 52ºN

In the upper part of the module a map (B) presents the mineral dust or solar irradiance parameters on a 0.2ºx0.2º grid. The map presents one of the following:

Dust products:

• Dust concentration at the surface for different size fractions:
  • Dust PM2.5
  • Dust PM10
• Dust surface extinction at 550 nm
• Dust Optical Depth at 550 nm (Dust AOD)
• Wet dust deposition
• Dry dust deposition

Solar Radiation products:

• DNI (Direct Normal Irradiance)
• GHI (Global Horizontal Irradiance)

After the user selects a location on the map, additional graphs are presented below the map: The Dust Forecast Graph (C) presents a time series of 72 hours of forecast on an hourly time resolution and a daily refresh rate for the dust concentrations at the surface (PM2.5 and PM10) and the AOD. The Solar Radiation Graph (D) presents a time series of the 72 hours of forecast for DNI (Direct Normal Irradiance) and GHI (Global Horizontal Irradiance).
The data can be exported in (E). FIRE MODULE The user first needs to select the location and the forecast type in (A). At the top of the fire product a map (B) shows the location of fires and the distribution of air pollutants (PM2.5, PM10, AOD and fire tracers for carbon monoxide) on a grid resolution of about 10 km. A time lapse will show forecasted progress of the fire and the pollution dispersion for the next 96 hours. After the user chooses a location on the map a summary of the pollutants is presented in (C). Below the Summary Panel, the “Pollution Forecast” panel (D) shows a time series of either PM2.5, PM10, CO tracers or AOD. When hovering over the lines a pop-up appears presenting the current pollutant level and the pollutant level forecasted at that moment in time.
The data can be exported in (E).

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What does this module do ?

This module provides up to 96h of hourly forecast of air pollution at the regional scale based on different predictive models. It consists in an air quality map which allows the users to understand and research the forecasted AQ statistics in a specific area including forecast of air pollution at the regional scale.

Who this module is designed for?

☒ Public authorities

☒ Municipalities

☒ Research centres

☒ Impacted industries (e.g.: solar plant and electricity grid operators, health industry…)

☒ Emitting Industries (e.g.: Fracking)

☐ Emergency services

☐ Airports and flight control authorities

☐ Citizens

Geographical coverage

Beijing (China), Colorado (USA) and Santiago de Chile (Chile) will be available at the end of the project.
Other regions may be developed afterwards depending on the demand.

Value-chain

Click on the image to enlarge it.

Current progress of the module

Module 5 provides the user with an air quality forecast in the core regions of the AQ Watch project: Santiago de Chile, Colorado and Beijing. It gives a graphical and numerical representation of the six main air pollutants for the next 96 hours. The forecasts are based on a multi-model ensemble system. The following models contribute to Module 5: SILAM, LOTOS-EUROS, WRF-Chem-MPI, WRF-Chem-UCAR, CHIMERE-China. The air quality forecast will allow local authorities and municipalities to better plan countermeasures against air pollution, (e.g. pass emergency regulations such as bans on driving or target certain emitting industries,) or warn their citizens of upcoming air pollution events. Members of the impacted industries such as from the health care sector will have the ability to better prepare for air pollution-related emergency events.