scholarly journals The Korea–United States Air Quality (KORUS-AQ) field study

Elem Sci Anth ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
James H. Crawford ◽  
Joon-Young Ahn ◽  
Jassim Al-Saadi ◽  
Limseok Chang ◽  
Louisa K. Emmons ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
South Korea ◽  
Field Study ◽  
The United States ◽  
Environmental Research ◽  
Test Bed ◽  
Perspective View ◽  
Air Quality Forecast ◽  
Synthesis Report

The Korea–United States Air Quality (KORUS-AQ) field study was conducted during May–June 2016. The effort was jointly sponsored by the National Institute of Environmental Research of South Korea and the National Aeronautics and Space Administration of the United States. KORUS-AQ offered an unprecedented, multi-perspective view of air quality conditions in South Korea by employing observations from three aircraft, an extensive ground-based network, and three ships along with an array of air quality forecast models. Information gathered during the study is contributing to an improved understanding of the factors controlling air quality in South Korea. The study also provided a valuable test bed for future air quality–observing strategies involving geostationary satellite instruments being launched by both countries to examine air quality throughout the day over Asia and North America. This article presents details on the KORUS-AQ observational assets, study execution, data products, and air quality conditions observed during the study. High-level findings from companion papers in this special issue are also summarized and discussed in relation to the factors controlling fine particle and ozone pollution, current emissions and source apportionment, and expectations for the role of satellite observations in the future. Resulting policy recommendations and advice regarding plans going forward are summarized. These results provide an important update to early feedback previously provided in a Rapid Science Synthesis Report produced for South Korean policy makers in 2017 and form the basis for the Final Science Synthesis Report delivered in 2020.

Linking the Eta Model with the Community Multiscale Air Quality (CMAQ) Modeling System to Build a National Air Quality Forecasting System

2005 ◽  
Vol 20 (3) ◽  
pp. 367-384 ◽  
Author(s):  
Tanya L. Otte ◽  
George Pouliot ◽  
Jonathan E. Pleim ◽  
Jeffrey O. Young ◽  
Kenneth L. Schere ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Environmental Protection Agency ◽  
Rural Areas ◽  
Numerical Models ◽  
The United States ◽  
Air Quality Forecast ◽  
Eta Model ◽  
State And Local ◽  
Air Quality Forecasting

Abstract NOAA and the U.S. Environmental Protection Agency (EPA) have developed a national air quality forecasting (AQF) system that is based on numerical models for meteorology, emissions, and chemistry. The AQF system generates gridded model forecasts of ground-level ozone (O3) that can help air quality forecasters to predict and alert the public of the onset, severity, and duration of poor air quality conditions. Although AQF efforts have existed in metropolitan centers for many years, this AQF system provides a national numerical guidance product and the first-ever air quality forecasts for many (predominantly rural) areas of the United States. The AQF system is currently based on NCEP’s Eta Model and the EPA’s Community Multiscale Air Quality (CMAQ) modeling system. The AQF system, which was implemented into operations at the National Weather Service in September of 2004, currently generates twice-daily forecasts of O3 for the northeastern United States at 12-km horizontal grid spacing. Preoperational testing to support the 2003 and 2004 O3 forecast seasons showed that the AQF system provided valuable guidance that could be used in the air quality forecast process. The AQF system will be expanded over the next several years to include a nationwide domain, a capability for forecasting fine particle pollution, and a longer forecast period. State and local agencies will now issue air quality forecasts that are based, in part, on guidance from the AQF system. This note describes the process and software components used to link the Eta Model and CMAQ for the national AQF system, discusses several technical and logistical issues that were considered, and provides examples of O3 forecasts from the AQF system.

Air Quality Forecast Verification Using Satellite Data

2008 ◽  
Vol 47 (2) ◽  
pp. 425-442 ◽  
Author(s):  
S. Kondragunta ◽  
P. Lee ◽  
J. McQueen ◽  
C. Kittaka ◽  
A. I. Prados ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Long Range ◽  
Regional Scale ◽  
The United States ◽  
Long Range Transport ◽  
Forecast Performance ◽  
Air Quality Forecast ◽  
Time Period ◽  
Range Transport

Abstract NOAA’s operational geostationary satellite retrievals of aerosol optical depths (AODs) were used to verify National Weather Service developmental (research mode) particulate matter (PM2.5) predictions tested during the summer 2004 International Consortium for Atmospheric Research on Transport and Transformation/New England Air Quality Study (ICARTT/NEAQS) field campaign. The forecast period included long-range transport of smoke from fires burning in Canada and Alaska and a regional-scale sulfate event over the Gulf of Mexico and the eastern United States. Over the 30-day time period for which daytime hourly forecasts were compared with observations, the categorical (exceedance defined as AOD > 0.55) forecast accuracy was between 0% and 20%. Hourly normalized mean bias (forecasts − observations) ranged between −50% and +50% with forecasts being positively biased when observed AODs were small and negatively biased when observed AODs were high. Normalized mean errors are between 50% and 100% with the errors on the lower end during the 18–22 July 2004 time period when a regional-scale sulfate event occurred. Spatially, the errors are small over the regions where sulfate plumes were present. The correlation coefficient also showed similar features (spatially and temporally) with a peak value of ∼0.6 during the 18–22 July 2004 time period. The dominance of long-range transport of smoke into the United States during the summer of 2004, neglected in the model predictions, skewed the model forecast performance. Enhanced accuracy and reduced normalized mean errors during the time period when a sulfate event prevailed show that the forecast system has skill in predicting PM2.5 associated with urban/industrial pollution events.

scholarly journals Assessment of NO<sub>2</sub> observations during DISCOVER-AQ and KORUS-AQ field campaigns

2020 ◽  
Vol 13 (5) ◽  
pp. 2523-2546 ◽  
Author(s):  
Sungyeon Choi ◽  
Lok N. Lamsal ◽  
Melanie Follette-Cook ◽  
Joanna Joiner ◽  
Nickolay A. Krotkov ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
A Priori ◽  
Reduction Process ◽  
Remote Sensing Data ◽  
The United States ◽  
Environmental Research ◽  
Ozone Monitoring Instrument ◽  
In Situ Data

Abstract. NASA's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011–2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea–United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori profiles) but mostly to OMI's large footprint (>312 km2).

scholarly journals Assessment of NO<sub>2</sub> observations during DISCOVER-AQ and KORUS-AQ field campaigns

2019 ◽  
Author(s):  
Sungyeon Choi ◽  
Lok N. Lamsal ◽  
Melanie Follette-Cook ◽  
Joanna Joiner ◽  
Nickolay A. Krotkov ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
A Priori ◽  
Reduction Process ◽  
Remote Sensing Data ◽  
The United States ◽  
Environmental Research ◽  
Ozone Monitoring Instrument ◽  
In Situ Data

Abstract. NASA’s Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea-United States Air Quality Study (KORUS-AQ) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with a goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique data sets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a-priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 33.3 %. These show even larger differences with Pandora, reaching up to 53.1 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of two lower in these highly polluted environments, due in part to inaccurate retrieval assumptions (e.g., a priori profiles), but mostly to OMI’s areal (> 312 km2) averaging.

Impact of Domain Size on Modeled Ozone Forecast for the Northeastern United States

2008 ◽  
Vol 47 (2) ◽  
pp. 443-461 ◽  
Author(s):  
Pius Lee ◽  
Daiwen Kang ◽  
Jeff McQueen ◽  
Marina Tsidulko ◽  
Mary Hart ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
The United States ◽  
Skill Score ◽  
Northeastern United States ◽  
Forecast System ◽  
Air Quality Forecast ◽  
Model Domain ◽  
The Impact ◽  
The U.S

Abstract This study investigates the impact of model domain extent and the specification of lateral boundary conditions on the forecast quality of air pollution constituents in a specific region of interest. A developmental version of the national Air Quality Forecast System (AQFS) has been used in this study. The AQFS is based on the NWS/NCEP Eta Model (recently renamed the North American Mesoscale Model) coupled with the U.S. Environmental Protection Agency Community Multiscale Air Quality (CMAQ) model. This coupled Eta–CMAQ modeling system provided experimental air quality forecasts for the northeastern region of the United States during the summers of 2003 and 2004. The initial forecast over the northeastern United States was approved for operational deployment in September 2004. The AQFS will provide forecast coverage for the entire United States in the near future. In a continuing program of phased development to extend the geographical coverage of the forecast, the developmental version of AQFS has undergone two domain expansions. Hereinafter, this “developmental” domain-expanded forecast system AQFS will be dubbed AQFS-β. The current study evaluates the performance of AQFS-β for the northeastern United States using three domain sizes. Quantitative comparisons of forecast results with compiled observation data from the U.S. Aerometric Information Retrieval Now (AIRNOW) network were performed for each model domain, and interdomain comparisons were made for the regions of overlap. Several forecast skill score measures have been employed. Based on the categorical statistical metric of the critical success index, the largest domain achieved the highest skill score. This conclusion should catapult the implementation of the largest domain to attain the best forecast performance whenever the operational resource and criteria permit.

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