Advances in operational air quality and aerosol prediction at NOAA/National Weather Service

2020 ◽  
Author(s):  
Ivanka Stajner ◽  
Keyword(s):  
Air Quality ◽  
Satellite Data ◽  
Weather Prediction ◽  
Satellite Observations ◽  
Atmospheric Composition ◽  
Forecast System ◽  
National Weather Service ◽  
Aerosol Composition ◽  
Fire Emissions ◽  
Weather Service

<p>NOAA is developing the Unified Forecast System (UFS) (https://ufscommunity.org/) as the source system for operational numerical weather prediction applications.  The UFS will be a coupled, comprehensive Earth modeling system with community contributions. The UFS is designed to streamline and simplify NOAA/National Weather Service operational modeling suite.  Integration of air quality predictions into the UFS began with testing of the Community Multiscale Air Quality modeling system (CMAQ) predictions driven by the operational version of the Global Forecast System (GFS), which includes the Finite-Volume Cubed-Sphere (FV3) dynamical core since June 2019.  In addition to system integration, this testing allows us to extend ozone and PM2.5 predictions to 72 hours (from 48 hours that operational predictions currently cover).  Integration of global aerosol prediction based on the Goddard Chemistry Aerosol Radiation and Transport (GOCART) scheme into the UFS begun by including it into one member of the Global Ensemble Forecast System (GEFS-Aerosol). GEFS-Aerosol predictions demonstrate a substantial improvement for both composition and variability of aerosol distributions over those from the currently operational standalone global aerosol prediction system.</p><p>The use of satellite observations in atmospheric composition and air quality predictions is increasing at NOAA.  Real-time estimates of biomass burning emissions for predictions are based on satellite data.  Challenges for these emissions involve detection of fires, the strength and composition of the emissions, altitude of the plume rise, temporal distribution of the emissions and the uncertainty in persistence or change of emissions during the forecast period. Representation of changing fire emissions in the model becomes more important with increasing prediction length.  Assimilation of Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) observations is under development to constrain aerosol distribution in the global system. Initial testing shows promise for improvement of predictions as well as limitations indicating a need for refinements in quality control, data assimilation impacts on aerosol composition and vertical distribution, as well as a need for bias correction of satellite observations.   Plans for the next-generation regional system include assimilation of satellite retrievals of VIIRS AOD and Sentinel-5 Precursor Tropospheric Ozone Monitoring Instrument (S5P TROPOMI) NO2. Satellite data also play an important role in verification of aerosol predictions. Additional uses of satellite data include verification and evaluation of model predictions such as aerosol vertical profile with TROPOMI aerosol layer height product as well as efforts to constrain and update anthropogenic emissions.</p><p>This presentation will overview advances and challenges in model development and the use of satellite data for operational atmospheric composition and air quality predictions at NOAA.</p>

scholarly journals Monitoring emissions from the 2015 Indonesian fires using CO satellite data

2018 ◽  
Vol 373 (1760) ◽  
pp. 20170307 ◽  
Author(s):  
Narcisa Nechita-Banda ◽  
Maarten Krol ◽  
Guido R. van der Werf ◽  
Johannes W. Kaiser ◽  
Sudhanshu Pandey ◽  
...  
Keyword(s):  
Satellite Data ◽  
El Niño ◽  
El Nino ◽  
Air Pollutant ◽  
Satellite Observations ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Burned Area ◽  
Fire Emissions ◽  
The Impact

Southeast Asia, in particular Indonesia, has periodically struggled with intense fire events. These events convert substantial amounts of carbon stored as peat to atmospheric carbon dioxide (CO 2 ) and significantly affect atmospheric composition on a regional to global scale. During the recent 2015 El Niño event, peat fires led to strong enhancements of carbon monoxide (CO), an air pollutant and well-known tracer for biomass burning. These enhancements were clearly observed from space by the Infrared Atmospheric Sounding Interferometer (IASI) and the Measurements of Pollution in the Troposphere (MOPITT) instruments. We use these satellite observations to estimate CO fire emissions within an inverse modelling framework. We find that the derived CO emissions for each sub-region of Indonesia and Papua are substantially different from emission inventories, highlighting uncertainties in bottom-up estimates. CO fire emissions based on either MOPITT or IASI have a similar spatial pattern and evolution in time, and a 10% uncertainty based on a set of sensitivity tests we performed. Thus, CO satellite data have a high potential to complement existing operational fire emission estimates based on satellite observations of fire counts, fire radiative power and burned area, in better constraining fire occurrence and the associated conversion of peat carbon to atmospheric CO 2 . A total carbon release to the atmosphere of 0.35–0.60 Pg C can be estimated based on our results. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

scholarly journals Comparisons of aerosol optical depth provided by seviri satellite observations and CAMx air quality modelling

2015 ◽  
Vol XL-7/W3 ◽  
pp. 187-193 ◽  
Author(s):  
A. Fernandes ◽  
M. Riffler ◽  
J. Ferreira ◽  
S. Wunderle ◽  
C. Borrego ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Satellite Data ◽  
Spatial Variations ◽  
Transport Processes ◽  
Satellite Observations ◽  
High Temporal Resolution ◽  
Vertical Column ◽  
Air Pollution Modelling ◽  
Spatial Coverage

Satellite data provide high spatial coverage and characterization of atmospheric components for vertical column. Additionally, the use of air pollution modelling in combination with satellite data opens the challenging perspective to analyse the contribution of different pollution sources and transport processes. The main objective of this work is to study the AOD over Portugal using satellite observations in combination with air pollution modelling. For this purpose, satellite data provided by Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-9 satellite on AOD at 550 nm and modelling results from the Chemical Transport Model (CAMx - Comprehensive Air quality Model) were analysed. The study period was May 2011 and the aim was to analyse the spatial variations of AOD over Portugal. In this study, a multi-temporal technique to retrieve AOD over land from SEVIRI was used. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and high spatial resolution. <br><br> CAMx provides the size distribution of each aerosol constituent among a number of fixed size sections. For post processing, CAMx output species per size bin have been grouped into total particulate sulphate (PSO4), total primary and secondary organic aerosols (POA + SOA), total primary elemental carbon (PEC) and primary inert material per size bin (CRST_1 to CRST_4) to be used in AOD quantification. The AOD was calculated by integration of aerosol extinction coefficient (Qext) on the vertical column. The results were analysed in terms of temporal and spatial variations. The analysis points out that the implemented methodology provides a good spatial agreement between modelling results and satellite observation for dust outbreak studied (10th -17th of May 2011). A correlation coefficient of r=0.79 was found between the two datasets. This work provides relevant background to start the integration of these two different types of the data in order to improve air pollution assessment.

scholarly journals Impact of Mexico City emissions on regional air quality from MOZART-4 simulations

2010 ◽  
Vol 10 (2) ◽  
pp. 3457-3498 ◽  
Author(s):  
L. K. Emmons ◽  
E. C. Apel ◽  
J.-F. Lamarque ◽  
P. G. Hess ◽  
M. Avery ◽  
...  
Keyword(s):  
Air Quality ◽  
Mexico City ◽  
Production Efficiency ◽  
Transport Model ◽  
Ozone Production ◽  
Atmospheric Composition ◽  
Chemical Transport Model ◽  
Model Calculations ◽  
Fire Emissions ◽  
Regional Air Quality

Abstract. An extensive set of measurements was made in and around Mexico City as part of the MILAGRO (Megacity Initiative: Local and Global Research Observations) experiments in March 2006. Simulations with the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4), a global chemical transport model, have been used to provide a regional context for these observations and assist in their interpretation. These MOZART-4 simulations reproduce the aircraft observations generally well, but some differences in the modeled volatile organic compounds (VOCs) from the observations result from incorrect VOC speciation assumed for the emission inventories. The different types of CO sources represented in the model have been "tagged" to quantify the contributions of regions outside Mexico, as well as the various emissions sectors within Mexico, to the regional air quality of Mexico. This analysis indicates open fires have some, but not a dominant, impact on the atmospheric composition in the region around Mexico City, when averaged over the month. However, considerable variation in the fire contribution (2–15% of total CO) is seen during the month. The transport and photochemical aging of Mexico City emissions were studied using tags of CO emissions for each day, showing that typically the air near Mexico City was a combination of many ages. Ozone production in MOZART-4 is shown to agree well with the net production rates from box model calculations constrained by the MILAGRO aircraft measurements. Ozone production efficiency derived from the ratio of Ox to NOz is higher in MOZART-4 than in the observations for moderately polluted air. OH reactivity determined from the MOZART-4 results shows the same increase in relative importance of oxygenated VOCs downwind of Mexico City as the reactivity inferred from the observations. The amount of ozone produced by emissions from Mexico City and surrounding areas has been quantified in the model by tracking NO emissions, showing little influence beyond Mexico's borders, and also relatively minor influence from fire emissions on the monthly average tropospheric ozone column.

scholarly journals Improving regional air quality predictions in the Indo-Gangetic Plain – case study of an intensive pollution episode in November 2017

2021 ◽  
Vol 21 (4) ◽  
pp. 2837-2860 ◽  
Author(s):  
Behrooz Roozitalab ◽  
Gregory R. Carmichael ◽  
Sarath K. Guttikunda
Keyword(s):  
Air Quality ◽  
Boundary Conditions ◽  
Infrared Imaging ◽  
Central India ◽  
Aerosol Composition ◽  
Gangetic Plain ◽  
Back Trajectories ◽  
Fire Emissions ◽  
Pollution Episode ◽  
Indo Gangetic Plain

Abstract. The Indo-Gangetic Plain (IGP) experienced an intensive air pollution episode during November 2017. Weather Research and Forecasting model coupled to Chemistry (WRF-Chem), a coupled meteorology–chemistry model, was used to simulate this episode. In order to capture PM2.5 peaks, we modified input chemical boundary conditions and biomass burning emissions. The Community Atmosphere Model with Chemistry (CAM-chem) and Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) global models provided gaseous and aerosol chemical boundary conditions, respectively. We also incorporated Visible Infrared Imaging Radiometer Suite (VIIRS) active fire points to fill in missing fire emissions in the Fire INventory from NCAR (FINN) and scaled by a factor of 7 for an 8 d period. Evaluations against various observations indicated the model captured the temporal trend very well although missed the peaks on 7, 8, and 10 November. Modeled aerosol composition in Delhi showed secondary inorganic aerosols (SIAs) and secondary organic aerosols (SOAs) comprised 30 % and 27 % of total PM2.5 concentration, respectively, during November, with a modeled OC/BC ratio of 2.72. Back trajectories showed agricultural fires in Punjab were the major source for extremely polluted days in Delhi. Furthermore, high concentrations above the boundary layers in vertical profiles suggested either the plume rise in the model released the emissions too high or the model did not mix the smoke down fast enough. Results also showed long-range-transported dust did not affect Delhi's air quality during the episode. Spatial plots showed averaged aerosol optical depth (AOD) of 0.58 (±0.4) over November. The model AODs were biased high over central India and low over the eastern IGP, indicating improving emissions in the eastern IGP can significantly improve the air quality predictions. We also found high ozone concentrations over the domain, which indicates ozone should be considered in future air quality management strategies alongside particulate matter.

Investigating chemical composition of the troposphere over the Russian Arctic using the "Optik" Tu-134 aircraft laboratory

2020 ◽  
Author(s):  
Boris D. Belan ◽  
Pavel N. Antokhin ◽  
Mikhail Yu. Arshinov ◽  
Sergey B. Belan ◽  
Denis K. Davydov ◽  
...  
Keyword(s):  
Satellite Data ◽  
Land Surface ◽  
General Scheme ◽  
Water Area ◽  
Kara Sea ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Aerosol Composition ◽  
The Impact

&lt;p&gt;The need to undertake a comprehensive investigation of the atmospheric composition over the Russian segment of the Arctic is caused by a serious lack and irregularity in obtaining observational data from this regio of the Earth. In addition, a comparison of the aircraft in-situ measurements with satellite data retrieved for the Kara Sea region in 2017 revealed large uncertainties in determining the vertical distribution of greenhouse gas concentrations using remote sensing methods. The development and improvement of the last ones needs at least their periodic verification by means of undertaking precise in-situ aircraft measurements.&lt;/p&gt;&lt;p&gt;The general scheme of the proposed experiment is as follows (map is attached): flight from Novosibirsk to Naryan-Mar via Sabetta. From Naryan-Mar, flight to a water area of the Bering Sea (up to 1000 km). Flight from Naryan-Mar to Sabetta. From here, flight to a water area of the Kara Sea (up to 1000 km). Then, flight to Tiksi. Flight from Tiksi to a water area of the Laptev Sea (up to 1000 km). Flight to Chokurdakh or Chersky. From there, flight to a water area of the East Siberian Sea (up to 1000 km). Flight to Cape Schmidt. Flight to a water area of the Chukchi Sea (up to 1000 km). Return route: Cape Shmidt&amp;#8211;Chersky (or Chokurdah)&amp;#8211;Yakutsk&amp;#8211;Bratsk&amp;#8211;Novosibirsk. It will take about 100 hours of flying time to implement the entire aircraft campaign. Campaign period is about 2-3 weeks. It is better to undertake the campaign during summer when the ocean is open. Flights over the land surface are assumed to be undertaken from 0.5 km to 11 km above ground level while above the sea from 0.2 km to 11 km. The flight profile is variable from the maximum possible height to the minimum allowed one. Vertical profiles of gas and aerosol composition will be obtained, including black carbon and organic components, as well as basic meteorological quantities.&lt;/p&gt;&lt;p&gt;Satellite data will be verified that do not yet provide acceptable accuracy. For the first time, unique information will be obtained over the least explored region of the Arctic, which is crucial for the whole planet in terms of climate formation and the impact of global warming.&lt;/p&gt;

scholarly journals Historic global biomass burning emissions based on merging satellite observations with proxies and fire models (1750–2015)

2017 ◽  
Author(s):  
Margreet J. E. van Marle ◽  
Silvia Kloster ◽  
Brian I. Magi ◽  
Jennifer R. Marlon ◽  
Anne-Laure Daniau ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Satellite Data ◽  
Carbon Emissions ◽  
Data Representation ◽  
Atmospheric Composition ◽  
Full Time ◽  
Fire Emissions ◽  
Fire Models ◽  
Time Period ◽  
In Fire

Abstract. Fires have influenced atmospheric composition and climate since the rise of vascular plants, and satellite data has shown the overall global extent of fires. Our knowledge of historic fire emissions has progressively improved over the past decades due mostly to the development of new proxies and the improvement of fire models. Currently there is a suite of proxies including sedimentary charcoal records, measurements of fire-emitted trace gases and black carbon stored in ice and firn, and visibility observations. These proxies provide opportunities to extrapolate emissions estimates based on satellite data starting in 1997 back in time, but each proxy has strengths and weaknesses regarding, for example, the spatial and temporal extents over which they are representative. We developed a new historic biomass burning emissions dataset starting in 1750 that merges the satellite record with several existing proxies, and uses the average of six models from the Fire Model Intercomparison Project (FireMIP) protocol to estimate emissions when the available proxies had limited coverage. According to our approach, global biomass burning emissions were relatively constant with 10-year averages varying between 1.8 and 2.3 Pg C year−1. Carbon emissions increased only slightly over the full time period and peaked during the 1990s after which they decreased gradually. There is substantial uncertainty in these estimates and patterns varied depending on choices regarding data representation, especially on regional scales. The observed pattern in fire carbon emissions is for a large part driven by African fires, which accounted for 58 % of global fire carbon emissions. African fire emissions declined since about 1950 due to conversion of savanna to cropland, and this decrease is partially compensated for by increasing emissions in deforestation zones of South America and Asia. These global fire emissions estimates are mostly suited for global analyses and will be used in the IPCC CMIP simulations.

scholarly journals Air quality simulations of wildfires in the Pacific Northwest evaluated with surface and satellite observations during the summers of 2007 and 2008

2014 ◽  
Vol 14 (22) ◽  
pp. 12533-12551 ◽  
Author(s):  
F. L. Herron-Thorpe ◽  
G. H. Mount ◽  
L. K. Emmons ◽  
B. K. Lamb ◽  
D. A. Jaffe ◽  
...  
Keyword(s):  
Air Quality ◽  
Pacific Northwest ◽  
Sparse Matrix ◽  
Surface Ozone ◽  
The United States ◽  
Satellite Observations ◽  
Fire Emissions ◽  
The Pacific ◽  
Aqua Satellite ◽  
Total Column

Abstract. Evaluation of a regional air quality forecasting system for the Pacific Northwest was carried out using a suite of surface and satellite observations. Wildfire events for the 2007 and 2008 fire seasons were simulated using the Air Information Report for Public Access and Community Tracking v.3 (AIRPACT-3) framework utilizing the Community Multi-scale Air Quality (CMAQ) model. Fire emissions were simulated using the BlueSky framework with fire locations determined by the Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation (SMARTFIRE). Plume rise was simulated using two different methods: the Fire Emission Production Simulator (FEPS) and the Sparse Matrix Operator Kernel Emissions (SMOKE) model. Predicted plume top heights were compared to the Cloud-Aerosol LIDAR with Orthogonal Polarization (CALIOP) instrument aboard the Cloud Aerosol LIDAR and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. Carbon monoxide predictions were compared to the Atmospheric InfraRed Sounder (AIRS) instrument aboard the Aqua satellite. Horizontal distributions of column aerosol optical depth (AOD) were compared to retrievals by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua satellite. Model tropospheric nitrogen dioxide distributions were compared to retrievals from the Ozone Monitoring Instrument (OMI) aboard the Aura satellite. Surface ozone and PM2.5 predictions were compared to surface observations. The AIRPACT-3 model captured the location and transport direction of fire events well, but sometimes missed the timing of fire events and overall underestimated the PM2.5 impact of wildfire events at surface monitor locations. During the 2007 (2008) fire period, the fractional biases (FBs) of AIRPACT-3 for various pollutant observations included: average 24 h PM2.5 FB = −33% (−27%); maximum daily average 8 h ozone FB = −8% (+1%); AOD FB = −61% (−53%); total column CO FB = −10% (−5%); and tropospheric column NO2 FB = −39% (−28%). The bias in total column CO is within the range of expected error. Fractional biases of AIRPACT-3 plume tops were found to be −46% when compared in terms of above mean sea level, but only −28% when compared in terms of above ground level, partly due to the under-estimation of AIRPACT-3 ground height in complex terrain that results from the 12 km grid-cell smoothing. We conclude that aerosol predictions were too low for locations greater than ~100–300 km downwind from wildfire sources and that model predictions are likely under-predicting secondary organic aerosol (SOA) production, due to a combination of very low volatile organic compound (VOC) emission factors used in the United States Forest Service Consume model, an incomplete speciation of VOC to SOA precursors in SMOKE, and under-prediction by the SOA parameterization within CMAQ.

scholarly journals Air quality simulations of wildfires in the Pacific Northwest evaluated with surface and satellite observations during the summers of 2007 and 2008

2014 ◽  
Vol 14 (8) ◽  
pp. 11103-11152
Author(s):  
F. L. Herron-Thorpe ◽  
G. H. Mount ◽  
L. K. Emmons ◽  
B. K. Lamb ◽  
D. A. Jaffe ◽  
...  
Keyword(s):  
Air Quality ◽  
Pacific Northwest ◽  
Sparse Matrix ◽  
Surface Ozone ◽  
Satellite Observations ◽  
Orthogonal Polarization ◽  
Fire Emissions ◽  
The Pacific ◽  
Aqua Satellite ◽  
The Impact

Abstract. Evaluation of a regional air quality forecasting system for the Pacific Northwest was carried out for the 2007 and 2008 fire seasons using suite of surface and satellite observations. Wildfire events in the Pacific Northwest during the summers of 2007 and 2008 were simulated using the Air Information Report for Public Access and Community Tracking v.3 (AIRPACT-3) framework utilizing the Community Multi-scale Air Quality (CMAQ) model. Fire emissions were simulated using the BlueSky framework with fire locations determined by the Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation (SMARTFIRE). Plume rise was simulated using two different methods: the Fire Emission Production Simulator (FEPS) and the Sparse Matrix Operator Kernel Emissions (SMOKE) model. Predicted plume top heights were compared to the Cloud-Aerosol LIDAR with Orthogonal Polarization (CALIOP) instrument aboard the Cloud Aerosol LIDAR and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. Carbon monoxide predictions were compared to the Atmospheric InfraRed Sounder (AIRS) instrument aboard the Aqua satellite. Horizontal distributions of column aerosol optical depth (AOD) were compared to retrievals by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua satellite. Model tropospheric nitrogen dioxide distributions were compared to retrievals from the Ozone Monitoring Instrument (OMI) aboard the Aura satellite. Surface ozone and PM2.5 predictions were compared to surface observations. The AIRPACT-3 model captured the location and transport direction of fire events well, but sometimes missed the timing of fire events and overall underestimated the impact of wildfire events at regional surface monitor locations. During the 2007 fire period the fractional biases of AIRPACT-3 for average 24 h PM2.5, maximum daily average 8 h Ozone, AOD, total column CO, and tropospheric column NO2 were found to be −33%, −8%, −61%, −10%, and −39%, respectively; while during the 2008 fire period the fractional biases were −27%, +1%, −53%, −5%, and −28%, respectively. Fractional biases of AIRPACT-3 plume tops were found to be −46% above mean sea level (a.m.s.l.), but only −28% above ground level (a.g.l.), partly due to the under-estimation of AIRPACT-3 elevation in complex terrain that results from the 12 km grid-cell smoothing.

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