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.

scholarly journals The contribution of marine organics to the air quality of the western United States

2010 ◽  
Vol 10 (15) ◽  
pp. 7415-7423 ◽  
Author(s):  
B. Gantt ◽  
N. Meskhidze ◽  
A. G. Carlton
Keyword(s):  
United States ◽  
Air Quality ◽  
San Francisco ◽  
Atmospheric Chemistry ◽  
Environmental Protection Agency ◽  
Regional Scale ◽  
The United States ◽  
Coastal Areas ◽  
Western United States ◽  
The Us

Abstract. The contribution of marine organic emissions to the air quality in coastal areas of the western United States is studied using the latest version of the US Environmental Protection Agency (EPA) regional-scale Community Multiscale Air Quality (CMAQv4.7) modeling system. Emissions of marine isoprene, monoterpenes, and primary organic matter (POM) from the ocean are implemented into the model to provide a comprehensive view of the connection between ocean biology and atmospheric chemistry and air pollution. Model simulations show that marine organics can increase the concentration of PM2.5 by 0.1–0.3 μg m−3 (up to 5%) in some coastal cities such as San Francisco, CA. This increase in the PM2.5 concentration is primarily attributed to the POM emissions, with small contributions from the marine isoprene and monoterpenes. When marine organic emissions are included, organic carbon (OC) concentrations over the remote ocean are increased by up to 50% (25% in coastal areas), values consistent with recent observational findings. This study is the first to quantify the air quality impacts from marine POM and monoterpenes for the United States, and it highlights the need for inclusion of marine organic emissions in air quality models.

scholarly journals Development and application of a United States-wide correction for PM<sub>2.5</sub> data collected with the PurpleAir sensor

2021 ◽  
Vol 14 (6) ◽  
pp. 4617-4637
Author(s):  
Karoline K. Barkjohn ◽  
Brett Gantt ◽  
Andrea L. Clements
Keyword(s):  
United States ◽  
Air Quality ◽  
Reference Method ◽  
Ambient Air ◽  
The United States ◽  
Global Network ◽  
Raw Data ◽  
The Us ◽  
State And Local ◽  
Multiplicative Models

Abstract. PurpleAir sensors, which measure particulate matter (PM), are widely used by individuals, community groups, and other organizations including state and local air monitoring agencies. PurpleAir sensors comprise a massive global network of more than 10 000 sensors. Previous performance evaluations have typically studied a limited number of PurpleAir sensors in small geographic areas or laboratory environments. While useful for determining sensor behavior and data normalization for these geographic areas, little work has been done to understand the broad applicability of these results outside these regions and conditions. Here, PurpleAir sensors operated by air quality monitoring agencies are evaluated in comparison to collocated ambient air quality regulatory instruments. In total, almost 12 000 24 h averaged PM2.5 measurements from collocated PurpleAir sensors and Federal Reference Method (FRM) or Federal Equivalent Method (FEM) PM2.5 measurements were collected across diverse regions of the United States (US), including 16 states. Consistent with previous evaluations, under typical ambient and smoke-impacted conditions, the raw data from PurpleAir sensors overestimate PM2.5 concentrations by about 40 % in most parts of the US. A simple linear regression reduces much of this bias across most US regions, but adding a relative humidity term further reduces the bias and improves consistency in the biases between different regions. More complex multiplicative models did not substantially improve results when tested on an independent dataset. The final PurpleAir correction reduces the root mean square error (RMSE) of the raw data from 8 to 3 µg m−3, with an average FRM or FEM concentration of 9 µg m−3. This correction equation, along with proposed data cleaning criteria, has been applied to PurpleAir PM2.5 measurements across the US on the AirNow Fire and Smoke Map (https://fire.airnow.gov/, last access: 14 May 2021) and has the potential to be successfully used in other air quality and public health applications.

scholarly journals Development and Application of a United States wide correction for PM<sub>2.5</sub> data collected with the PurpleAir sensor

2020 ◽  
Author(s):  
Karoline K. Barkjohn ◽  
Brett Gantt ◽  
Andrea L. Clements
Keyword(s):  
United States ◽  
Air Quality ◽  
Reference Method ◽  
Ambient Air ◽  
The United States ◽  
Global Network ◽  
Raw Data ◽  
State And Local ◽  
Multiplicative Models ◽  
The U.S

Abstract. PurpleAir sensors which measure particulate matter (PM) are widely used by individuals, community groups, and other organizations including state and local air monitoring agencies. PurpleAir sensors comprise a massive global network of more than 10,000 sensors. Previous performance evaluations have typically studied a limited number of PurpleAir sensors in small geographic areas or laboratory environments. While useful for determining sensor behavior and data normalization for these geographic areas, little work has been done to understand the broad applicability of these results outside these regions and conditions. Here, PurpleAir sensors operated by air quality monitoring agencies are evaluated in comparison to collocated ambient air quality regulatory instruments. In total, almost 12,000 24-hour averaged PM2.5 measurements from collocated PurpleAir sensors and Federal Reference Method (FRM) or Federal Equivalent Method (FEM) PM2.5 measurements were collected across diverse regions of the United States (U.S.), including 16 states. Consistent with previous evaluations, under typical ambient and smoke impacted conditions, the raw data from PurpleAir sensors overestimate PM2.5 concentrations by about 40 % in most parts of the U.S. A simple linear regression reduces much of this bias across most U.S. regions, but adding a relative humidity term further reduces the bias and improves consistency in the biases between different regions. More complex multiplicative models did not substantially improve results when tested on an independent dataset. The final PurpleAir correction reduces the root mean square error (RMSE) of the raw data from 8 µg m−3 to 3 µg m−3 with an average FRM or FEM concentration of 9 µg m−3. This correction equation, along with proposed data cleaning criteria, has been applied to PurpleAir PM2.5 measurements across the U.S. in the AirNow Fire and Smoke Map (fire.airnow.gov) and has the potential to be successfully used in other air quality and public health applications.

scholarly journals What Do Economists Have to Say about the Clean Air Act 50 Years after the Establishment of the Environmental Protection Agency?

2019 ◽  
Vol 33 (4) ◽  
pp. 3-26 ◽  
Author(s):  
Janet Currie ◽  
Reed Walker
Keyword(s):  
United States ◽  
Air Quality ◽  
Environmental Protection ◽  
Environmental Protection Agency ◽  
Clean Air Act ◽  
The United States ◽  
Economic Research ◽  
Protection Agency ◽  
The Past ◽  
Clean Air

Air quality in the United States has improved dramatically over the past 50 years in large part due to the introduction of the Clean Air Act and the creation of the Environmental Protection Agency to enforce it. This article is a reflection on the 50-year anniversary of the formation of the Environmental Protection Agency, describing what economic research says about the ways in which the Clean Air Act has shaped our society—in terms of costs, benefits, and important distributional concerns. We conclude with a discussion of how recent changes to both policy and technology present new opportunities for researchers in this area.

Bicyclist Crash Types on National, State, and Local Levels: A New Look

2019 ◽  
Vol 2673 (6) ◽  
pp. 664-676 ◽  
Author(s):  
Libby Thomas ◽  
Krista Nordback ◽  
Rebecca Sanders
Keyword(s):  
United States ◽  
Rural Areas ◽  
Urban Areas ◽  
The United States ◽  
Fatal Crash ◽  
Serious Injury ◽  
State And Local ◽  
Crash Types ◽  
Serious Injuries ◽  
The City

This paper presents an overview of prevalent bicyclist crash types in the United States, providing insights for practitioners that may be useful in planning safer networks and taking other proactive and risk-based approaches to treatment. The study compares fatal bicyclist crash types from national data with serious injury and all-severity bicyclist collisions from the state of North Carolina (NC) and the city of Boulder, Colorado. Overall, bicyclist fatalities in the United States are more prevalent in urban areas (69%) than rural areas (29%). Though the majority of all-severity crashes are at intersections, most fatal and disabling injury bicyclist crashes occur at non-intersection locations, including nearly one-third of bicyclists who die from collisions involving overtaking motorists. Top intersection crash types across national fatal and all-severity crashes in NC and Boulder include bicyclists failing to yield and motorists turning across a bicyclist’s path. However, many of the top all-severity types in the two jurisdictions differ from the top fatal crash types nationwide. These comparisons provide a fresh look at bicyclist crash type trends and have potential importance with respect to planning safer networks for Vision Zero communities, since a key finding is that locations and crash types most prevalent among fatal and serious injuries may differ from the most prevalent types for all-severity crashes. The findings could be useful to agencies lacking their own resources for risk-based assessment, but also suggest it is important to analyze higher severity crash types and jurisdiction-specific data when possible.

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 &gt; 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.

The new smoke management

2001 ◽  
Vol 10 (4) ◽  
pp. 415 ◽  
Author(s):  
Allen R. Riebau ◽  
Douglas Fox
Keyword(s):  
United States ◽  
Air Quality ◽  
Environmental Protection Agency ◽  
Agricultural Land ◽  
Wildland Fire ◽  
The United States ◽  
Atmospheric Particulate Matter ◽  
Management Tool ◽  
Smoke Management ◽  
Ozone Precursor

This paper was presented at the conference ‘Integrating spatial technologies and ecological principles for a new age in fire management’, Boise, Idaho, USA, June 1999 The United States Environmental Protection Agency (EPA) will implement new regulations for the management of atmospheric particulate matter 2.5 µm and less in diameter (PM2.5), tropospheric ozone, and regional haze in the next few years. These three air quality issues relate directly to forest and agriculture burning. Fire generates PM2.5 and ozone precursor gases that reduce visibility. Hence, wild and agricultural land managers will be subject to these air quality regulations much as industrial and mobile sources have been for the past 25 years. In addition, these new regulations come at a time when private as well as public land managers throughout the United States are developing plans to increase their application of fire as a management tool. Prescribed fire will remain viable as a tool for land managers with these new regulations but only under a responsible smoke management paradigm. This paradigm will include formal ‘state-approved’ Smoke Management Programs and will require the use of new and ‘approved’ technologies that have been subjected to public and stakeholder scrutiny as regulatory tools. These programs will acknowledge that wildland fire is different from conventional human-caused air pollution sources. They will recognize that the managed use of fire is a superior option to wildfire from public safety and health perspectives. But they will also require greater utilization of non-burning alternatives in all circumstances, especially where fire is used for economic rather than ecological reasons. Through better smoke management and greater use of non-burning alternatives, steadily reduced smoke emissions will likely result.

A quasi-operational air quality forecasting system for the contiguous United States (CONUS) 

2021 ◽  
Author(s):  
Rajesh Kumar ◽  
Gabriele Pfister ◽  
Piyush Bhardwaj
Keyword(s):  
United States ◽  
Air Quality ◽  
Information Dissemination ◽  
Surface Ozone ◽  
High Surface ◽  
Model Errors ◽  
Grid Spacing ◽  
Air Quality Forecast ◽  
Forecasting System ◽  
Air Quality Forecasting

&lt;p&gt;We present a research system for regional air quality forecasting over&amp;#160; the contiguous United States (CONUS). This system has been developed at the National Center for Atmospheric Research (NCAR) to support community model development, allow early identification of model errors and biases, and support the atmospheric science community in their research. At the same time, it assists field campaign planning and air quality decision-making. The forecasts aim to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA) and 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. Our forecasting system has been producing a 48-h forecast every day at 12 km x 12 km grid spacing over the entire CONUS since June 2019 and at 4 km x 4 km grid spacing in Colorado since June 2020. Here, we will report on the performance of our air quality forecasting system in simulating meteorology, PM2.5, ozone, and NOx for the period of 1 June 2019 to 31 December 2020. Our system showed excellent skill in capturing hourly to daily variations in temperature, surface pressure, relative humidity, water vapor mixing ratios, and wind direction but showed, in parts, relatively larger errors in wind speed. The model captured the seasonal cycle of surface PM2.5 and ozone very well in different regions of CONUS and at different types of sites (urban, suburban, and rural) but generally overestimates summertime surface ozone and fails to capture very high surface PM2.5 events. These shortcomings are being addressed in current work. 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 https://www.acom.ucar.edu/firex-aq/forecast.shtml and we invite the community to use our forecasting products for their research, as input for urban scale (&lt; 4 km) air quality forecasts, or the co-development of customized products just to name a few applications.&lt;/p&gt;

scholarly journals The impact of marine organics on the air quality of the western United States

2010 ◽  
Vol 10 (3) ◽  
pp. 6257-6278 ◽  
Author(s):  
B. Gantt ◽  
N. Meskhidze ◽  
A. G. Carlton
Keyword(s):  
United States ◽  
Air Quality ◽  
Atmospheric Chemistry ◽  
Environmental Protection Agency ◽  
Regional Scale ◽  
The United States ◽  
Coastal Areas ◽  
Western United States ◽  
The Us ◽  
The Impact

Abstract. The impact of marine organic emissions to the air quality in coastal areas of the western United States is studied using the latest version of the US Environmental Protection Agency (EPA) regional-scale Community Multiscale Air Quality (CMAQv4.7) modeling system. Emissions of marine isoprene, monoterpenes, and primary organic matter (POM) from the ocean are implemented into the model to provide a comprehensive view of the connection between ocean biology and atmospheric chemistry and air pollution. Model simulations show that marine organics can increase the concentration of PM2.5 by 0.1–0.3 μg m−3 (up to 5%) in coastal cities. This increase in the PM2.5 concentration is primarily attributed to the POM emissions, with small contributions from the marine isoprene and monoterpenes. When marine organic emissions are included, organic carbon (OC) concentrations over the remote ocean are increased by up to 50% (25% in coastal areas), values consistent with recent observational findings. This study is the first to quantify the air quality impacts from marine POM and monoterpenes for the United States, and highlights the need for inclusion of marine organic emissions in air quality models.

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.

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