scholarly journals Assessment of the quality of TROPOMI high-spatial-resolution NO<sub>2</sub> data products in the Greater Toronto Area

2020 ◽  
Vol 13 (4) ◽  
pp. 2131-2159 ◽  
Author(s):  
Xiaoyi Zhao ◽  
Debora Griffin ◽  
Vitali Fioletov ◽  
Chris McLinden ◽  
Alexander Cede ◽  
...  
Keyword(s):  
Air Quality ◽  
High Spatial Resolution ◽  
Forecast Model ◽  
Satellite Measurements ◽  
Data Product ◽  
Greater Toronto Area ◽  
Air Quality Forecast ◽  
Tropospheric No2 ◽  
Data Products ◽  
Regional Air Quality

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite (launched on 13 October 2017) is a nadir-viewing spectrometer measuring reflected sunlight in the ultraviolet, visible, near-infrared, and shortwave infrared spectral ranges. The measured spectra are used to retrieve total columns of trace gases, including nitrogen dioxide (NO2). For ground validation of these satellite measurements, Pandora spectrometers, which retrieve high-quality NO2 total columns via direct-sun measurements, are widely used. In this study, Pandora NO2 measurements made at three sites located in or north of the Greater Toronto Area (GTA) are used to evaluate the TROPOMI NO2 data products, including a standard Royal Netherlands Meteorological Institute (KNMI) tropospheric and stratospheric NO2 data product and a TROPOMI research data product developed by Environment and Climate Change Canada (ECCC) using a high-resolution regional air quality forecast model (in the air mass factor calculation). It is found that these current TROPOMI tropospheric NO2 data products (standard and ECCC) met the TROPOMI design bias requirement (< 10 %). Using the statistical uncertainty estimation method, the estimated TROPOMI upper-limit precision falls below the design requirement at a rural site but above in the other two urban and suburban sites. The Pandora instruments are found to have sufficient precision (< 0.02 DU) to perform TROPOMI validation work. In addition to the traditional satellite validation method (i.e., pairing ground-based measurements with satellite measurements closest in time and space), we analyzed TROPOMI pixels located upwind and downwind from the Pandora site. This makes it possible to improve the statistics and better interpret the high-spatial-resolution measurements made by TROPOMI. By using this wind-based validation technique, the number of coincident measurements can be increased by about a factor of 5. With this larger number of coincident measurements, this work shows that both TROPOMI and Pandora instruments can reveal detailed spatial patterns (i.e., horizontal distributions) of local and transported NO2 emissions, which can be used to evaluate regional air quality changes. The TROPOMI ECCC NO2 research data product shows improved agreement with Pandora measurements compared to the TROPOMI standard tropospheric NO2 data product (e.g., lower multiplicative bias at the suburban and urban sites by about 10 %), demonstrating benefits from the high-resolution regional air quality forecast model.

scholarly journals Assessment of the quality of TROPOMI high-spatial-resolution NO<sub>2</sub> data products

2019 ◽  
Author(s):  
Xiaoyi Zhao ◽  
Debora Griffin ◽  
Vitali Fioletov ◽  
Chris McLinden ◽  
Alexander Cede ◽  
...  
Keyword(s):  
Air Quality ◽  
High Spatial Resolution ◽  
Forecast Model ◽  
Research Data ◽  
Satellite Measurements ◽  
Data Product ◽  
Air Quality Forecast ◽  
Tropospheric No2 ◽  
Data Products ◽  
Regional Air Quality

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) on-board the Sentinel-5 Precursor satellite (launched on 13 October 2017) is a nadir-viewing spectrometer measuring reflected sunlight in the ultraviolet, visible, near-infrared, and shortwave infrared spectral ranges. The measured spectra are used to retrieve total columns of trace gases, including nitrogen dioxide (NO2). For ground validation of these satellite measurements, Pandora spectrometers, which retrieve high-quality NO2 total columns via direct-sun measurements, are widely used. In this study, Pandora NO2 measurements made at three sites located in or north of the Greater Toronto Area (GTA) are used to evaluate the TROPOMI NO2 data products, including standard Royal Netherlands Meteorological Institute (KNMI) tropospheric and stratospheric NO2 data product and a TROPOMI research data product developed by Environment and Climate Change Canada (ECCC) using a high-resolution regional air quality forecast model (used in the air mass factor calculation). It is found that these current TROPOMI tropospheric NO2 data products (standard and ECCC) met the TROPOMI design bias requirement. Using the statistical uncertainty estimation method, the estimated TROPOMI upper limit precision falls below the design requirement at a rural site, but above in the other two urban and suburban sites. The Pandora instruments are found to have sufficient precision to perform TROPOMI validation work. In addition to the traditional satellite validation method (i.e., pairing ground-based measurements with satellite measurements closest in time and space), we analyzed TROPOMI pixels located upwind and downwind from the Pandora site. This makes it possible to improve the statistics and better interpret the high-spatial-resolution measurements made by TROPOMI. By using this wind-based validation technique, the number of coincident measurements can be increased by about a factor of five. Using this larger number of coincident measurements, this work shows that both TROPOMI and Pandora instruments can reveal detailed spatial patterns (i.e., horizontal distributions) of local and transported NO2 emissions, which can be used to evaluate regional air quality changes. The TROPOMI ECCC NO2 research data product shows improved agreement with Pandora measurements compared to the TROPOMI standard tropospheric NO2 data product, demonstrating benefits from the high-resolution regional air quality forecast model.

Assessment of the quality of TROPOMI high-spatial-resolution NO2 data products

2020 ◽  
Author(s):  
Xiaoyi Zhao ◽  
Debora Griffin ◽  
Vitali Fioletov ◽  
Chris McLinden ◽  
Alexander Cede ◽  
...  
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Near Infrared ◽  
Forecast Model ◽  
Research Data ◽  
Data Product ◽  
Air Quality Forecast ◽  
Data Products ◽  
Regional Air Quality ◽  
Quality Forecast

&lt;p&gt;The TROPOspheric Monitoring Instrument (TROPOMI) on-board the Sentinel-5 Precursor satellite (launched on 13 October 2017) is a nadir-viewing spectrometer measuring reflected sunlight in the ultraviolet, visible, near-infrared, and shortwave infrared spectral ranges. The measured spectra are used to retrieve total columns of trace gases, including nitrogen dioxide (NO&lt;sub&gt;2&lt;/sub&gt;). In this study, Pandora NO&lt;sub&gt;2&lt;/sub&gt; measurements made at three sites located in or north of the Greater Toronto Area (GTA) are used to evaluate the TROPOMI NO&lt;sub&gt;2&lt;/sub&gt; data products, including the standard Royal Netherlands Meteorological Institute (KNMI) NO&lt;sub&gt;2&lt;/sub&gt; data product and a research data product developed by Environment and Climate Change Canada (ECCC) using a high-resolution regional air quality forecast model (used in the airmass factor calculation).&lt;/p&gt;&lt;p&gt;TROPOMI pixels located upwind and downwind from the Pandora sites were analyzed using a new wind-based validation method that increases the number of coincident measurements by about a factor of five compared to standard techniques. Using this larger number of coincident measurements, this work shows that both TROPOMI and Pandora instruments can reveal detailed spatial patterns (i.e., horizontal distributions) of local and transported NO&lt;sub&gt;2&lt;/sub&gt; emissions, which can be used to evaluate regional air quality changes. The TROPOMI ECCC NO&lt;sub&gt;2&lt;/sub&gt; research data product shows improved agreement with Pandora measurements compared to the TROPOMI standard tropospheric NO&lt;sub&gt;2&lt;/sub&gt; data product, demonstrating the benefit of using the high-resolution regional air quality forecast model to derive NO&lt;sub&gt;2&lt;/sub&gt; airmass factors.&lt;/p&gt;

scholarly journals Evaluation of a regional air quality forecast model for tropospheric NO<sub>2</sub> columns using the OMI/AURA satellite tropospheric NO<sub>2</sub> product

2009 ◽  
Vol 9 (6) ◽  
pp. 27063-27098
Author(s):  
F. L. Herron-Thorpe ◽  
J. K. Vaughan ◽  
B. K. Lamb ◽  
G. H. Mount
Keyword(s):  
Air Quality ◽  
Pacific Northwest ◽  
Urban Areas ◽  
Forecast Model ◽  
Air Quality Forecast ◽  
The Pacific ◽  
Tropospheric No2 ◽  
Regional Air Quality ◽  
Significant Model ◽  
Quality Forecast

Abstract. Results from a regional air quality forecast model, AIRPACT-3, are compared to OMI tropospheric NO2 integrated column densities for an 18 month period over the Pacific Northwest. AIRPACT column densities were well correlated with cloud-free monthly averages of tropospheric NO2 (R=0.75) to NASA retrievals for months without wildfires, but were poorly correlated with significant model overpredictions (R=0.21) for months with wildfires when OMI and AIRPACT were compared over the entire domain. AIRPACT forecasted higher NO2 in some US urban areas, and lower NO2 in many Canadian urban areas, when compared to OMI. There are significant changes in results after spatially averaging model results to the daily OMI swath. Also, it is shown that applying the averaging kernel to model results in cloudy conditions has a large effect, but applying the averaging kernel in cloud free conditions has little effect. The KNMI and NASA retrievals of tropospheric NO2 from OMI (collection 3) are compared. The NASA product is shown to be significantly different than the KNMI tropospheric NO2 product, i.e. July 2007 (R=0.60) and January 2008 (R=0.69).

scholarly journals Evaluation of a regional air quality forecast model for tropospheric NO<sub>2</sub> columns using the OMI/Aura satellite tropospheric NO<sub>2</sub> product

2010 ◽  
Vol 10 (18) ◽  
pp. 8839-8854 ◽  
Author(s):  
F. L. Herron-Thorpe ◽  
B. K. Lamb ◽  
G. H. Mount ◽  
J. K. Vaughan
Keyword(s):  
Air Quality ◽  
Pacific Northwest ◽  
Urban Areas ◽  
Forecast Model ◽  
Air Quality Forecast ◽  
The Pacific ◽  
Standard Product ◽  
Tropospheric No2 ◽  
Regional Air Quality ◽  
Quality Forecast

Abstract. Results from a regional air quality forecast model, AIRPACT-3, are compared to OMI tropospheric NO2 integrated column densities for an 18 month period over the Pacific Northwest. AIRPACT column densities are well correlated (r=0.75) to cloud-free (<35%) retrievals of tropospheric NO2 for monthly averages without wildfires, but are poorly correlated (r=0.21) with significant model over-predictions for months with wildfires when OMI and AIRPACT are compared over the entire domain. AIRPACT predicts higher NO2 in some northwestern US urban areas, and lower NO2 in the Vancouver, BC urban area, when compared to OMI. Model results are spatially averaged to the daily OMI swath. The Dutch KNMI (DOMINO) and NASA (Standard Product) retrievals of tropospheric NO2 from OMI (Collection-3) are compared. The NASA product is shown to be significantly different than the KNMI tropospheric NO2 product. The average difference in tropospheric columns, after applying the averaging kernels of the respective products to the model results, is shown to be larger in the summer (±50%) than winter (±20%).

scholarly journals Regional air-quality forecasting for the Pacific Northwest using MOPITT/TERRA assimilated carbon monoxide MOZART-4 forecasts as a near real-time boundary condition

2012 ◽  
Vol 12 (12) ◽  
pp. 5603-5615 ◽  
Author(s):  
F. L. Herron-Thorpe ◽  
G. H. Mount ◽  
L. K. Emmons ◽  
B. K. Lamb ◽  
S. H. Chung ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Air Quality ◽  
Boundary Conditions ◽  
Pacific Northwest ◽  
Forecast Model ◽  
Dynamic Boundary Conditions ◽  
Air Quality Forecast ◽  
The Pacific ◽  
Regional Air Quality ◽  
Air Quality Forecasting

Abstract. Results from a regional air quality forecast model, AIRPACT-3, were compared to AIRS carbon monoxide column densities for the spring of 2010 over the Pacific Northwest. AIRPACT-3 column densities showed high correlation (R > 0.9) but were significantly biased (~25%) with consistent under-predictions for spring months when there is significant transport from Asia. The AIRPACT-3 CO bias relative to AIRS was eliminated by incorporating dynamic boundary conditions derived from NCAR's MOZART forecasts with assimilated MOPITT carbon monoxide. Changes in ozone-related boundary conditions derived from MOZART forecasts are also discussed and found to affect background levels by ± 10 ppb but not found to significantly affect peak ozone surface concentrations.

scholarly journals Regional air-quality forecasting for the Pacific Northwest using MOPITT/TERRA assimilated carbon monoxide MOZART-4 forecasts as a near real-time boundary condition

2012 ◽  
Vol 12 (2) ◽  
pp. 3695-3730
Author(s):  
F. L. Herron-Thorpe ◽  
G. H. Mount ◽  
L. K. Emmons ◽  
B. K. Lamb ◽  
S. H. Chung ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Air Quality ◽  
Boundary Conditions ◽  
Pacific Northwest ◽  
Forecast Model ◽  
Dynamic Boundary Conditions ◽  
Air Quality Forecast ◽  
The Pacific ◽  
Regional Air Quality ◽  
Air Quality Forecasting

Abstract. Results from a regional air quality forecast model, AIRPACT-3, were compared to AIRS carbon monoxide column densities for the spring of 2010 over the Pacific Northwest. AIRPACT-3 column densities showed high correlation (R>0.9) but were significantly biased (~25 %) with significant under-predictions for spring months with significant transport from Asia. The AIRPACT-3 CO bias relative to AIRS was eliminated by incorporating dynamic boundary conditions derived from NCAR's MOZART forecasts with assimilated MOPITT carbon monoxide. Changes in ozone-related boundary conditions derived from MOZART forecasts are also discussed and found to affect background levels by ±10 ppb but not found to significantly affect peak ozone surface concentrations.

scholarly journals Assessing the Impact of Corona-Virus-19 on Nitrogen Dioxide Levels over Southern Ontario, Canada

2020 ◽  
Vol 12 (24) ◽  
pp. 4112
Author(s):  
Debora Griffin ◽  
Chris Anthony McLinden ◽  
Jacinthe Racine ◽  
Michael David Moran ◽  
Vitali Fioletov ◽  
...  
Keyword(s):  
Air Quality ◽  
Nitrogen Dioxide ◽  
Forecast Model ◽  
Activity Data ◽  
Southern Ontario ◽  
Greater Toronto Area ◽  
Air Quality Forecast ◽  
Scale Modelling ◽  
Emission Activity ◽  
The Impact

A lockdown was implemented in Canada mid-March 2020 to limit the spread of COVID-19. In the wake of this lockdown, declines in nitrogen dioxide (NO2) were observed from the TROPOspheric Monitoring Instrument (TROPOMI). A method is presented to quantify how much of this decrease is due to the lockdown itself as opposed to variability in meteorology and satellite sampling. The operational air quality forecast model, GEM-MACH (Global Environmental Multi-scale - Modelling Air quality and CHemistry), was used together with TROPOMI to determine expected NO2 columns that represents what TROPOMI would have observed for a non-COVID scenario. Applying this methodology to southern Ontario, decreases in NO2 emissions due to the lockdown were seen, with an average 40% (roughly 10 kt[NO2]/yr) in Toronto and Mississauga and even larger declines in the city center. Natural and satellite sampling variability accounted for as much as 20–30%, which demonstrates the importance of taking meteorology into account. A model run with reduced emissions (from 65 kt[NO2]/yr to 40 kt[NO2]/yr in the Greater Toronto Area) based on emission activity data during the lockdown period was found to be consistent with TROPOMI NO2 columns.

scholarly journals Description and Evaluation of the Fine Particulate Matter Forecasts in the NCAR Regional Air Quality Forecasting System

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 302
Author(s):  
Rajesh Kumar ◽  
Piyush Bhardwaj ◽  
Gabriele Pfister ◽  
Carl Drews ◽  
Shawn Honomichl ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Information Dissemination ◽  
Fine Particulate Matter ◽  
Model Errors ◽  
Air Quality Forecast ◽  
Fine Particulate ◽  
Regional Air Quality ◽  
Forecasting System ◽  
Air Quality Forecasting

This paper describes a quasi-operational regional air quality forecasting system for the contiguous United States (CONUS) developed at the National Center for Atmospheric Research (NCAR) to support air quality decision-making, field campaign planning, early identification of model errors and biases, and support the atmospheric science community in their research. This system aims to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA), not to replace them. A publicly available information dissemination system has been established that displays various air quality products, including a near-real-time evaluation of the model forecasts. Here, we report the performance of our air quality forecasting system in simulating meteorology and fine particulate matter (PM2.5) for the first year after our system started, i.e., 1 June 2019 to 31 May 2020. Our system shows excellent skill in capturing hourly to daily variations in temperature, surface pressure, relative humidity, water vapor mixing ratios, and wind direction but shows relatively larger errors in wind speed. The model also captures the seasonal cycle of surface PM2.5 very well in different regions and for different types of sites (urban, suburban, and rural) in the CONUS with a mean bias smaller than 1 µg m−3. The skill of the air quality forecasts remains fairly stable between the first and second days of the forecasts. Our air quality forecast products are publicly available at a NCAR webpage. We invite the community to use our forecasting products for their research, as input for urban scale (<4 km), air quality forecasts, or the co-development of customized products, just to name a few applications.

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