APPLICATION OF A NEW LAND-SURFACE, DRY DEPOSITION, AND PBL MODEL IN THE MODELS-3 COMMUNITY MULTI-SCALE AIR QUALITY (CMAQ) MODEL SYSTEM

EPA Science Inventory

Like most air quality modeling systems, CMAQ divides the treatment of meteorological and chemical/transport processes into separate models run sequentially. A potential drawback to this approach is that it creates the illusion that these processes are minimally interdependent an...

Community Multiscale Air Quality Modeling System (CMAQ)

EPA Pesticide Factsheets

CMAQ is a computational tool used for air quality management. It models air pollutants including ozone, particulate matter and other air toxics to help determine optimum air quality management scenarios.

Incremental Testing of the Community Multiscale Air Quality (CMAQ) Modeling System Version 4.7

EPA Science Inventory

This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to obse...

Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system

EPA Science Inventory

A new windblown dust emission treatment was incorporated in the Community Multiscale Air Quality (CMAQ) modeling system. This new model treatment has been built upon previously developed physics-based parameterization schemes from the literature. A distinct and novel feature of t...

Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modeled processes were examined and enhanced to suitably represent the extended space and timesca...

Annual Application and Evaluation of the Online Coupled WRF‐CMAQ System over North America under AQMEII Phase 2

EPA Science Inventory

We present an application of the online coupled WRF-CMAQ modeling system to two annual simulations over North America performed under Phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII). Operational evaluation shows that model performance is comparable t...

Sensitivity of an Integrated Mesoscale Atmosphere and Agriculture Land Modeling System (WRF/CMAQ-EPIC) to MODIS Vegetation and Lightning Assimilation

EPA Science Inventory

The combined meteorology and air quality modeling system composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ) model is an important decision support tool that is used in research and regulatory decisions related to emissions, meteo...

WHAT'S NEW IN MCIP2?

EPA Science Inventory

An update to CMAQ's Meteorology/Chemistry Interface Processor Version 2 (MCIP2) will be released in August 2004 in conjunction with the next public release of the CMAQ model. MCIP2 is the pre-processor in the CMAQ system that is typically used to perform off-line linkage between...

PREMAQ: A NEW PRE-PROCESSOR TO CMAQ FOR AIR-QUALITY FORECASTING

EPA Science Inventory

A new pre-processor to CMAQ (PREMAQ) has been developed as part of the national air-quality forecasting system. PREMAQ combines the functionality of MCIP and parts of SMOKE in a single real-time processor. PREMAQ was specifically designed to link NCEP's Eta model with CMAQ, and...

WRF-CMAQ Two-way Coupled System with Aerosol Feedback: Software Development and Preliminary Results

EPA Science Inventory

Air quality models such as the EPA Community Multiscale Air Quality (CMAQ) require meteorological data as part of the input to drive the chemistry and transport simulation. The Meteorology-Chemistry Interface Processor (MCIP) is used to convert meteorological data into CMAQ-ready...

Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

PubMed Central

Mathur, Rohit; Xing, Jia; Gilliam, Robert; Sarwar, Golam; Hogrefe, Christian; Pleim, Jonathan; Pouliot, George; Roselle, Shawn; Spero, Tanya L.; Wong, David C.; Young, Jeffrey

2018-01-01

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modelled processes were examined and enhanced to suitably represent the extended space and time scales for such applications. Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting (WRF) model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. The expansion of CMAQ to simulate the hemispheric scales provides a framework to examine interactions between atmospheric processes occurring at various spatial and temporal scales with physical, chemical, and dynamical consistency. PMID:29681922

MODELS-3/CMAQ APPLICATIONS WHICH ILLUSTRATE CAPABILITY AND FUNCTIONALITY

EPA Science Inventory

The Models-3/CMAQ developed by the U.S. Environmental Protections Agency (USEPA) is a third generation multiscale, multi-pollutant air quality modeling system within a high-level, object-oriented computer framework (Models-3). It has been available to the scientific community ...

Recent Enhancements to the Community Multiscale Air Quality Model (CMAQ)

EPA Science Inventory

This presentation overviews recent updates to the CMAQ modeling system. The presentation will be given as part of the information exchange session on Regional Air Pollution Modeling at the UK-US Collaboration Meeting on Air Pollution Exposure Science.

NEW DEVELOPMENTS IN THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL

EPA Science Inventory

CMAQ model research and development is currently following two tracks at the Atmospheric Modeling Division of the USEPA. Public releases of the community model system for research and policy analysis is continuing on an annual interval with the latest release scheduled for Augus...

ASSESSMENT OF ETA-CMAQ FORECASTS OF PARTICULATE MATTER DISTRIBUTIONS THROUGH COMPARISONS WITH SURFACE NETWORK AND SPECIALIZED MEASUREMENTS

EPA Science Inventory

An air-quality forecasting (AQF) system based on the National Weather Service (NWS) National Centers for Environmental Prediction's (NCEP's) Eta model and the U.S. EPA's Community Multiscale Air Quality (CMAQ) Modeling System is used to simulate the distributions of tropospheric ...

SIMULATIONS OF AEROSOLS AND PHOTOCHEMICAL SPECIES WITH THE CMAQ PLUME-IN-GRID MODELING SYSTEM

EPA Science Inventory

A plume-in-grid (PinG) method has been an integral component of the CMAQ modeling system and has been designed in order to realistically simulate the relevant processes impacting pollutant concentrations in plumes released from major point sources. In particular, considerable di...

A framework for expanding aqueous chemistry in the ...

EPA Pesticide Factsheets

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ordinary differential equations (ODEs) that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry. Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the US reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM − KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from bio

APPLICATION OF FINE SCALE AIR TOXICS MODELING WITH CMAQ TO HAPEM5

EPA Science Inventory

This paper provides a preliminary demonstration of the EPA neighborhood scale modeling paradigm for air toxics by linking concentration from the Community Multiscale Air Quality (CMAQ) modeling system to the fifth version of the Hazardous Pollutant Exposure Model (HAPEM5). For t...

EPA RESEARCH HIGHLIGHTS -- MODELS-3/CMAQ OFFERS COMPREHENSIVE APPROACH TO AIR QUALITY MODELING

EPA Science Inventory

Regional and global coordinated efforts are needed to address air quality problems that are growing in complexity and scope. Models-3 CMAQ contains a community multi-scale air quality modeling system for simulating urban to regional scale pollution problems relating to troposphe...

Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States

NASA Astrophysics Data System (ADS)

Hogrefe, Christian; Liu, Peng; Pouliot, George; Mathur, Rohit; Roselle, Shawn; Flemming, Johannes; Lin, Meiyun; Park, Rokjin J.

2018-03-01

This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global-scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental US for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ process analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couples fluctuations in free-tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry - Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), the Goddard Earth Observing System model coupled to chemistry (GEOS-Chem), and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the middle and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8 h average ozone on individual days. In contrast, the differences between the C-IFS-, GEOS-Chem-, and H-CMAQ-driven regional-scale CMAQ simulations are typically smaller. Comparing simulated surface ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.

Model Representation of Secondary Organic Aerosol in CMAQ v4.7

EPA Science Inventory

Numerous scientific upgrades to the representation of secondary organic aerosol (SOA) are incorporated into the Community Multiscale Air Quality (CMAQ) modeling system. Additions include several recently identified SOA precursors: benzene, isoprene, and sesquiterpenes; and pathwa...

Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF–CMAQ: model description, development, evaluation and regional analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, S.; Mathur, R.; Pleim, J.

This study implemented first, second and glaciation aerosol indirect effects (AIE) on resolved clouds in the two-way coupled Weather Research and Forecasting Community Multiscale Air Quality (WRF–CMAQ) modeling system by including parameterizations for both cloud drop and ice number concentrations on the basis of CMAQ-predicted aerosol distributions and WRF meteorological conditions. The performance of the newly developed WRF–CMAQ model, with alternate Community Atmospheric Model (CAM) and Rapid Radiative Transfer Model for GCMs (RRTMG) radiation schemes, was evaluated with observations from the Clouds and the See http://ceres.larc.nasa.gov/. Earth's Radiant Energy System (CERES) satellite and surface monitoring networks (AQS, IMPROVE, CASTNET, STN,more » and PRISM) over the continental US (CONUS) (12 km resolution) and eastern Texas (4 km resolution) during August and September of 2006. The results at the Air Quality System (AQS) surface sites show that in August, the normalized mean bias (NMB) values for PM 2.5 over the eastern US (EUS) and the western US (WUS) are 5.3% (-0.1%) and 0.4% (-5.2%) for WRF–CMAQ/CAM (WRF–CMAQ/RRTMG), respectively. The evaluation of PM 2.5 chemical composition reveals that in August, WRF–CMAQ/CAM (WRF–CMAQ/RRTMG) consistently underestimated the observed SO 4 2- by -23.0% (-27.7%), -12.5% (-18.9%) and -7.9% (-14.8%) over the EUS at the Clean Air Status Trends Network (CASTNET), Interagency Monitoring of Protected Visual Environments (IMPROVE) and Speciated Trends Network (STN) sites, respectively. Both configurations (WRF–CMAQ/CAM, WRF–CMAQ/RRTMG) overestimated the observed mean organic carbon (OC), elemental carbon (EC) and and total carbon (TC) concentrations over the EUS in August at the IMPROVE sites. Both configurations generally underestimated the cloud field (shortwave cloud forcing, SWCF) over the CONUS in August due to the fact that the AIE on the subgrid convective clouds was not considered when the model simulations were run at the 12 km resolution. This is in agreement with the fact that both configurations captured SWCF and longwave cloud forcing (LWCF) very well for the 4 km simulation over eastern Texas, when all clouds were resolved by the finer resolution domain. The simulations of WRF–CMAQ/CAM and WRF–CMAQ/RRTMG show dramatic improvements for SWCF, LWCF, cloud optical depth (COD), cloud fractions and precipitation over the ocean relative to those of WRF default cases in August. The model performance in September is similar to that in August, except for a greater overestimation of PM 2.5 due to the overestimations of SO 4 2-, NH 4 +, NO 3 -, and TC over the EUS, less underestimation of clouds (SWCF) over the land areas due to the lower SWCF values, and fewer convective clouds in September. Finally, this work shows that inclusion of indirect aerosol effect treatments in WRF–CMAQ represents a significant advancement and milestone in air quality modeling and the development of integrated emissions control strategies for air quality management and climate change mitigation.« less

COMPARISON OF SPATIAL PATTERNS OF POLLUTANT DISTRIBUTION WITH CMAQ PREDICTIONS

EPA Science Inventory

To evaluate the Models-3/Community Multiscale Air Quality (CMAQ) modeling system in reproducing the spatial patterns of aerosol concentrations over the country on timescales of months and years, the spatial patterns of model output are compared with those derived from observation...

Strong influence of deposition and vertical mixing on secondary organic aerosol concentrations in CMAQ and CAMx

NASA Astrophysics Data System (ADS)

Shu, Qian; Koo, Bonyoung; Yarwood, Greg; Henderson, Barron H.

2017-12-01

Differences between two air quality modeling systems reveal important uncertainties in model representations of secondary organic aerosol (SOA) fate. Two commonly applied models (CMAQ: Community Multiscale Air Quality; CAMx: Comprehensive Air Quality Model with extensions) predict very different OA concentrations over the eastern U.S., even when using the same source data for emissions and meteorology and the same SOA modeling approach. Both models include an option to output a detailed accounting of how each model process (e.g., chemistry, deposition, etc.) alters the mass of each modeled species, referred to as process analysis. We therefore perform a detailed diagnostic evaluation to quantify simulated tendencies (Gg/hr) of each modeled process affecting both the total model burden (Gg) of semi-volatile organic compounds (SVOC) in the gas (g) and aerosol (a) phases and the vertical structures to identify causes of concentration differences between the two models. Large differences in deposition (CMAQ: 69.2 Gg/d; CAMx: 46.5 Gg/d) contribute to significant OA bias in CMAQ relative to daily averaged ambient concentration measurements. CMAQ's larger deposition results from faster daily average deposition velocities (VD) for both SVOC (g) (VD,cmaq = 2.15 × VD,camx) and aerosols (VD,cmaq = 4.43 × Vd,camx). Higher aerosol deposition velocity would be expected to cause similar biases for inert compounds like elemental carbon (EC), but this was not seen. Daytime low-biases in EC were also simulated in CMAQ as expected but were offset by nighttime high-biases. Nighttime high-biases were a result of overly shallow mixing in CMAQ leading to a higher fraction of EC total atmospheric mass in the first layer (CAMx: 5.1-6.4%; CMAQ: 5.6-6.9%). Because of the opposing daytime and nighttime biases, the apparent daily average bias for EC is reduced. For OA, there are two effects of reduced vertical mixing: SOA and SVOC are concentrated near the surface, but SOA yields are reduced near the surface by nighttime enhancement of NOx. These results help to characterize model processes in the context of SOA and provide guidance for model improvement.

Evaluation of the Community Multiscale Air Quality (CMAQ) ...

EPA Pesticide Factsheets

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In the fall of 2016, CMAQ version 5.1.1 will be released. This new version of CMAQ will contain important bug fixes to several issues that were identified in CMAQv5.1 (the current public release version of the CMAQ model), and additionally include updates to other portions of the code. Some specific model updates include a new implementation of the wind-blown dust calculation in CMAQv5.1.1 which fixes several bugs that were identified in the current implementation of wind-blown dust in CMAQv5.1. Several other major updates to the model include an update to the calculation of aerosols; implementation of full halogen chemistry (CMAQv5.1 contains a partial implementation of halogen chemistry), which is particularly important for hemispheric applications of the CMAQ model, as halogen chemistry is need to accurately simulation the destruction of ozone over the ocean; and the new carbon bond 6 (CB6) chemical mechanism. Several annual, and numerous episodic, CMAQv5.1.1 simulations will be performed to assess the impact of these

Diagnostic Analysis of Ozone Concentrations Simulated by Two Regional-Scale Air Quality Models

EPA Science Inventory

Since the Community Multiscale Air Quality modeling system (CMAQ) and the Weather Research and Forecasting with Chemistry model (WRF/Chem) use different approaches to simulate the interaction of meteorology and chemistry, this study compares the CMAQ and WRF/Chem air quality simu...

Recent Advances in Modeling of the Atmospheric Boundary Layer and Land Surface in the Coupled WRF-CMAQ Model

EPA Science Inventory

Advances in the land surface model (LSM) and planetary boundary layer (PBL) components of the WRF-CMAQ coupled meteorology and air quality modeling system are described. The aim of these modifications was primarily to improve the modeling of ground level concentrations of trace c...

A Hemispheric Version of the Community Multiscale Air Quality (CMAQ) Modeling System

EPA Science Inventory

This invited presentation will be given at the 4th Biannual Western Modeling Workshop in the Plenary session on Global model development, evaluation, and new source attribution tools. We describe the development and application of the hemispheric version of the CMAQ to examine th...

Description and evaluation of the Community Multiscale Air ...

EPA Pesticide Factsheets

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O3) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM2. 5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O3 mixing ratios, primarily due to reduced

Evaluation of the Community Multi-scale Air Quality (CMAQ) ...

EPA Pesticide Factsheets

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In the fall of 2015, CMAQ version 5.1 was released. This new version of CMAQ will contain important bug fixes to several issues that were identified in CMAQv5.0.2 and additionally include updates to other portions of the code. Several annual, and numerous episodic, CMAQv5.1 simulations were performed to assess the impact of these improvements on the model results. These results will be presented, along with a base evaluation of the performance of the CMAQv5.1 modeling system against available surface and upper-air measurements available during the time period simulated. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, proces

LINKING AIR TOXIC CONCENTRATIONS FROM CMAQ TO THE HAPEM5 EXPOSURE MODEL AT NEIGHORHOOD SCALES FOR THE PHILADELPHIA AREA

EPA Science Inventory

This paper provides a preliminary demonstration of the EPA neighborhood scale modeling paradigm for air toxics by linking concentration from the Community Multi-scale Air Quality (CMAQ) modeling system to the fifth version of the Hazardous Pollutant Exposure Model (HAPEM5). For ...

RESULTS OF PHOTOCHEMICAL SIMULATIONS OF SUBGRID SCALE POINT SOURCE EMISSIONS WITH THE MODELS-3 CMAQ MODELING SYSTEM

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) / Plume-in-Grid (PinG) model was applied on a domain encompassing the greater Nashville, Tennessee region. Model simulations were performed for selected days in July 1995 during the Southern Oxidant Study (SOS) field study program wh...

Application and Evaluation of MODIS LAI, FPAR, and Albedo Products in the WRF/CMAQ System

EPA Science Inventory

MODIS vegetation and albedo products provide a more realistic representation of surface conditions for input to the WRF/CMAQ modeling system. However, the initial evaluation of ingesting MODIS data into the system showed mixed results, with increased bias and error for 2-m temper...

Application and Evaluation of MODIS LAI, FPAR, and Albedo ...

EPA Pesticide Factsheets

MODIS vegetation and albedo products provide a more realistic representation of surface conditions for input to the WRF/CMAQ modeling system. However, the initial evaluation of ingesting MODIS data into the system showed mixed results, with increased bias and error for 2-m temperature and reduced bias and error for 2-m mixing ratio. Recently, the WRF/CMAQ land surface and boundary laywer processes have been updated. In this study, MODIS vegetation and albedo data are input to the updated WRF/CMAQ meteorology and air quality simulations for 2006 over a North American (NA) 12-km domain. The evaluation of the simulation results shows that the updated WRF/CMAQ system improves 2-m temperature estimates over the pre-update base modeling system estimates. The MODIS vegetation input produces a realistic spring green-up that progresses through time from the south to north. Overall, MODIS input reduces 2-m mixing ration bias during the growing season. The NA west shows larger positive O3 bias during the growing season because of reduced gas phase deposition resulting from lower O3 deposition velocities driven by reduced vegetation cover. The O3 bias increase associated with the realistic vegetation representation indicates that further improvement may be needed in the WRF/CMAQ system. The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment. AMAD’s rese

Evaluation of the two-way coupled WRF-CMAQ modeling system to the 2011 DISCOVER-AQ campaign at 12-km, 4-km and 1-km resolutions

EPA Science Inventory

At the 12th Annual CMAS Conference initial results from the application of the coupled WRF-CMAQ modeling system to the 2011 Baltimore-Washington D.C. DISCOVER-AQ campaign were presented, with the focus on updates and new methods applied to the WRF modeling for fine-scale applicat...

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

NASA Astrophysics Data System (ADS)

Fahey, Kathleen M.; Carlton, Annmarie G.; Pye, Havala O. T.; Baek, Jaemeen; Hutzell, William T.; Stanier, Charles O.; Baker, Kirk R.; Wyat Appel, K.; Jaoui, Mohammed; Offenberg, John H.

2017-04-01

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM - KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ordinary differential equations (ODEs) that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry. Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the US reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM - KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from biogenic epoxides (AQCHEM - KMTI), normalized mean error and bias statistics are slightly improved for 2-methyltetrols and 2-methylglyceric acid at the Research Triangle Park measurement site in North Carolina during the Southern Oxidant and Aerosol Study (SOAS) period. The added in-cloud chemistry leads to a monthly average increase of 11-18 % in cloud SOA at the surface in the eastern United States for June 2013.

APPLICATION OF BIAS AND ADJUSTMENT TECHNIQUES TO THE ETA-CMAQ AIR QUALITY FORECAST

EPA Science Inventory

The current air quality forecast system, based on linking NOAA's Eta meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, consistently overpredicts surface ozone concentrations, but simulates its day-to-day variability quite well. The ability of bias cor...

Recent Enhancements to the Community Multiscale Air Quality Modeling System (CMAQ)

EPA Science Inventory

EPA’s Office of Research and Development, Computational Exposure Division held a webinar on January 31, 2017 to present the recent scientific and computational updates made by EPA to the Community Multi-Scale Air Quality Model (CMAQ). Topics covered included: (1) Improveme...

ATMOSPHERIC MERCURY SIMULATION USING THE CMAQ MODEL: FORMULATION DESCRIPTION AND ANALYSIS OF WET DEPOSITION RESULTS

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) modeling system has recently been adapted to simulate the emission, transport, transformation and deposition of atmospheric mercury in three distinct forms; elemental mercury gas, reactive gaseous mercury, and particulate mercury. Emis...

Application, evaluation and sensitivity analysis of the coupled WRF-CMAQ system from regional to urban scales

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science chemical transport model (CTM) capable of simulating the emission, transport and fate of numerous air pollutants. Similarly, the Weather Research and Forecasting (WRF) model is a state-of-the-science mete...

Examination of the Community Multiscale Air Quality (CMAQ) Model Performance over the North American and European Domains

EPA Science Inventory

The CMAQ modeling system has been used to simulate the air quality for North America and Europe for the entire year of 2006 as part of the Air Quality Model Evaluation International Initiative (AQMEII) and the operational model performance of O₃, fine particulate matte...

Overview and Evaluation of the Community Multiscale Air Quality (CMAQ) Modeling System Version 5.2

EPA Science Inventory

A new version of the Community Multiscale Air Quality (CMAQ) model, version 5.2 (CMAQv5.2), is currently being developed, with a planned release date in 2017. The new model includes numerous updates from the previous version of the model (CMAQv5.1). Specific updates include a new...

Development and evaluation of the Screening Trajectory Ozone Prediction System (STOPS, version 1.0)

NASA Astrophysics Data System (ADS)

Czader, B. H.; Percell, P.; Byun, D.; Choi, Y.

2014-11-01

A hybrid Lagrangian-Eulerian modeling tool has been developed using the Eulerian framework of the Community Multiscale Air Quality (CMAQ) model. It is a moving nest that utilizes saved original CMAQ simulation results to provide boundary conditions, initial conditions, as well as emissions and meteorological parameters necessary for a simulation. Given that these file are available, this tool can run independently from the CMAQ whole domain simulation and it is designed to simulate source - receptor relationship upon changes in emissions. In this tool, the original CMAQ's horizontal domain is reduced to a small sub-domain that follows a trajectory defined by the mean mixed-layer wind. It has the same vertical structure and physical and chemical interactions as CMAQ except advection calculation. The advantage of this tool compared to other Lagrangian models is its capability of utilizing realistic boundary conditions that change with space and time as well as detailed chemistry treatment. The correctness of the algorithms and the overall performance was evaluated against CMAQ simulation results. Its performance depends on the atmospheric conditions occurring during the simulation period with the comparisons being most similar to CMAQ results under uniform wind conditions. The mean bias varies between -0.03 and -0.78 and the slope is between 0.99 and 1.01 for different analyzed cases. For complicated meteorological condition, such as wind circulation, the simulated mixing ratios deviate from CMAQ values as a result of Lagrangian approach of using mean wind for its movement, but are still close, with the mean varying between 0.07 and -4.29 and slope varying between 0.95 and 1.063 for different analyzed cases. For historical reasons this hybrid Lagrangian - Eulerian tool is named the Screening Trajectory Ozone Prediction System (STOPS) but its use is not limited to ozone prediction as similarly to CMAQ it can simulate concentrations of many species, including particulate matter and some toxic compounds, such as formaldehyde and 1,3-butadiene.

Fertilizer Emission Scenario Tool for crop management system scenarios

EPA Pesticide Factsheets

The Fertilizer Emission Scenario Tool for CMAQ is a high-end computer interface that simulates daily fertilizer application information for any gridded domain. It integrates the Weather Research and Forecasting model and CMAQ.

Application and evaluation of high-resolution WRF-CMAQ with simple urban parameterization.

EPA Science Inventory

The 2-way coupled WRF-CMAQ meteorology and air quality modeling system is evaluated for high-resolution applications by comparing to a regional air quality field study (Discover-AQ). The model was modified to better account for the effects of urban environments. High-resolution...

Extending the Applicability of the Community Multiscale Air Quality Model to Hemispheric Scales: Motivation, Challenges, and Progress

EPA Science Inventory

The adaptation of the Community Multiscale Air Quality (CMAQ) modeling system to simulate O₃, particulate matter, and related precursor distributions over the northern hemisphere is presented. Hemispheric simulations with CMAQ and the Weather Research and Forecasting (...

Application and evaluation of high-resolution WRF-CMAQ with simple urban parameterization

EPA Science Inventory

The 2-way coupled WRF-CMAQ meteorology and air quality modeling system is evaluated for high-resolution applications by comparing to a regional air quality field study (Discover-AQ). The model was modified to better account for the effects of urban environments. High-resolution...

A NASA Lightning Parameterization for CMAQ

NASA Technical Reports Server (NTRS)

Koshak, William; Khan, Maudood; Biazar, Arastoo; Newchurch, Mike; McNider, Richard

2009-01-01

Many state and local air quality agencies use the U.S. Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) modeling system to determine compliance with the National Ambient Air Quality Standards (NAAQS). Because emission reduction scenarios are tested using CMAQ with an aim of determining the most efficient and cost effective strategies for attaining the NAAQS, it is very important that trace gas concentrations derived by CMAQ are accurate. Overestimating concentrations can literally translate into billions of dollars lost by commercial and government industries forced to comply with the standards. Costly health, environmental and socioeconomic problems can result from concentration underestimates. Unfortunately, lightning modeling for CMAQ is highly oversimplified. This leads to very poor estimates of lightning-produced nitrogen oxides "NOx" (= NO + NO2) which directly reduces the accuracy of the concentrations of important CMAQ trace gases linked to NOx concentrations such as ozone and methane. Today it is known that lightning is the most important NOx source in the upper troposphere with a global production rate estimated to vary between 2-20 Tg(N)/yr. In addition, NOx indirectly influences our climate since it controls the concentration of ozone and hydroxyl radicals (OH) in the atmosphere. Ozone is an important greenhouse gas and OH controls the oxidation of various greenhouse gases. We describe a robust NASA lightning model, called the Lightning Nitrogen Oxides Model (LNOM) that combines state-of-the-art lightning measurements, empirical results from field studies, and beneficial laboratory results to arrive at a realistic representation of lightning NOx production for CMAQ. NASA satellite lightning data is used in conjunction with ground-based lightning detection systems to assure that the best representation of lightning frequency, geographic location, channel length, channel altitude, strength (i.e., channel peak current), and number of strokes per flash are accounted for. LNOM combines all of these factors in a straightforward approach that is easily implemented into CMAQ. We anticipate that future applications of LNOM will produce significant and important changes in CMAQ trace gas concentrations for various regions and times. We also anticipate that these changes will have a direct impact on decision makers responsible for NAAQS attainment.

COMPUTATIONAL ASPECTS OF THE AIR QUALITY FORECASTING VERSION OF CMAQ (CMAQ-F)

EPA Science Inventory

The air quality forecast version of the Community Modeling Air Quality (CMAQ) model (CMAQ-F) was developed from the public release version of CMAQ (available from http://www.cmascenter.org), and is running operationally at the National Weather Service's National Centers for Envir...

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

EPA Science Inventory

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used t...

Assessment of the contribution of traffic emissions to the mobile vehicle measured PM2.5 concentration by means of WRF-CMAQ simulations.

DOT National Transportation Integrated Search

2012-03-01

The Alaska adapted version of the Weather Research and Forecasting and the Community Modeling and Analysis Quality (WRF-CMAQ) modeling : systems was used to assess the contribution of traffic to the PM2.5-concentration in the Fairbanks nonattainment ...

Evaluation of the Community Multiscale Air Quality (CMAQ) modeling system against size-resolved measurements of inorganic particle composition across sites in North America

EPA Science Inventory

This work evaluates particle size-composition distributions simulated by the Community Multiscale Air Quality (CMAQ) model using Micro-Orifice Uniform Deposit Impactor (MOUDI) measurements at 18 sites across North America. Size-resolved measurements of particulate SO₄<...

Human-model hybrid Korean air quality forecasting system.

PubMed

Chang, Lim-Seok; Cho, Ara; Park, Hyunju; Nam, Kipyo; Kim, Deokrae; Hong, Ji-Hyoung; Song, Chang-Keun

2016-09-01

The Korean national air quality forecasting system, consisting of the Weather Research and Forecasting, the Sparse Matrix Operator Kernel Emissions, and the Community Modeling and Analysis (CMAQ), commenced from August 31, 2013 with target pollutants of particulate matters (PM) and ozone. Factors contributing to PM forecasting accuracy include CMAQ inputs of meteorological field and emissions, forecasters' capacity, and inherent CMAQ limit. Four numerical experiments were conducted including two global meteorological inputs from the Global Forecast System (GFS) and the Unified Model (UM), two emissions from the Model Intercomparison Study Asia (MICS-Asia) and the Intercontinental Chemical Transport Experiment (INTEX-B) for the Northeast Asia with Clear Air Policy Support System (CAPSS) for South Korea, and data assimilation of the Monitoring Atmospheric Composition and Climate (MACC). Significant PM underpredictions by using both emissions were found for PM mass and major components (sulfate and organic carbon). CMAQ predicts PM2.5 much better than PM10 (NMB of PM2.5: -20~-25%, PM10: -43~-47%). Forecasters' error usually occurred at the next day of high PM event. Once CMAQ fails to predict high PM event the day before, forecasters are likely to dismiss the model predictions on the next day which turns out to be true. The best combination of CMAQ inputs is the set of UM global meteorological field, MICS-Asia and CAPSS 2010 emissions with the NMB of -12.3%, the RMSE of 16.6μ/m(3) and the R(2) of 0.68. By using MACC data as an initial and boundary condition, the performance skill of CMAQ would be improved, especially in the case of undefined coarse emission. A variety of methods such as ensemble and data assimilation are considered to improve further the accuracy of air quality forecasting, especially for high PM events to be comparable to for all cases. The growing utilization of the air quality forecast induced the public strongly to demand that the accuracy of the national forecasting be improved. In this study, we investigated the problems in the current forecasting as well as various alternatives to solve the problems. Such efforts to improve the accuracy of the forecast are expected to contribute to the protection of public health by increasing the availability of the forecast system.

Performance Summary of the 2006 Community Multiscale Air Quality (CMAQ) Simulation for the AQMEII Project: North American Application

EPA Science Inventory

The CMAQ modeling system has been used to simulate the CONUS using 12-km by 12-km horizontal grid spacing for the entire year of 2006 as part of the Air Quality Model Evaluation International initiative (AQMEII). The operational model performance for O₃ and PM_2.5<...

Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.1

EPA Science Inventory

The AMAD will performed two CMAQ model simulations, one with the current publically available version of the CMAQ model (v5.0.2) and the other with the new version of the CMAQ model (v5.1). The results of each model simulation are compared to observations and the performance of t...

EVALUATION OF THE CMAQ - AIM MODEL AGAINST SIZE AND CHEMICALLY-RESOLVED IMPACTOR DATA AT A COASTAL URBAN SITE

EPA Science Inventory

CMAQ-UCD (formerly known as CMAQ-AIM), is a fully dynamic, sectional aerosol model which has been coupled to the Community Multiscale Air Quality (CMAQ) host air quality model. Aerosol sulfate, nitrate, ammonium, sodium, and chloride model outputs are compared against MOUDI data...

Methods for Improving Fine-Scale Applications of the WRF-CMAQ Modeling System

EPA Science Inventory

Presentation on the work in AMAD to improve fine-scale (e.g. 4km and 1km) WRF-CMAQ simulations. Includes iterative analysis, updated sea surface temperature and snow cover fields, and inclusion of impervious surface information (urban parameterization).

Development and evaluation of the Screening Trajectory Ozone Prediction System (STOPS, version 1.0)

NASA Astrophysics Data System (ADS)

Czader, B. H.; Percell, P.; Byun, D.; Kim, S.; Choi, Y.

2015-05-01

A hybrid Lagrangian-Eulerian based modeling tool has been developed using the Eulerian framework of the Community Multiscale Air Quality (CMAQ) model. It is a moving nest that utilizes saved original CMAQ simulation results to provide boundary conditions, initial conditions, as well as emissions and meteorological parameters necessary for a simulation. Given that these files are available, this tool can run independently of the CMAQ whole domain simulation, and it is designed to simulate source-receptor relationships upon changes in emissions. In this tool, the original CMAQ's horizontal domain is reduced to a small sub-domain that follows a trajectory defined by the mean mixed-layer wind. It has the same vertical structure and physical and chemical interactions as CMAQ except advection calculation. The advantage of this tool compared to other Lagrangian models is its capability of utilizing realistic boundary conditions that change with space and time as well as detailed chemistry treatment. The correctness of the algorithms and the overall performance was evaluated against CMAQ simulation results. Its performance depends on the atmospheric conditions occurring during the simulation period, with the comparisons being most similar to CMAQ results under uniform wind conditions. The mean bias for surface ozone mixing ratios varies between -0.03 and -0.78 ppbV and the slope is between 0.99 and 1.01 for different analyzed cases. For complicated meteorological conditions, such as wind circulation, the simulated mixing ratios deviate from CMAQ values as a result of the Lagrangian approach of using mean wind for its movement, but are still close, with the mean bias for ozone varying between 0.07 and -4.29 ppbV and the slope varying between 0.95 and 1.06 for different analyzed cases. For historical reasons, this hybrid Lagrangian-Eulerian based tool is named the Screening Trajectory Ozone Prediction System (STOPS), but its use is not limited to ozone prediction as, similarly to CMAQ, it can simulate concentrations of many species, including particulate matter and some toxic compounds, such as formaldehyde and 1,3-butadiene.

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

EPA Science Inventory

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosen...

Application and evaluation of the WRF-CMAQ modeling system to the 2011 DISCOVER-AQ Baltimore-Washington D.C. study

NASA Astrophysics Data System (ADS)

Appel, W.; Gilliam, R. C.; Pouliot, G. A.; Godowitch, J. M.; Pleim, J.; Hogrefe, C.; Kang, D.; Roselle, S. J.; Mathur, R.

2013-12-01

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in urban areas using satellite, aircraft, vertical profiler and ground based measurements (http://discover-aq.larc.nasa.gov). In July 2011, the DISCOVER-AQ project conducted intensive air quality measurements in the Baltimore, MD and Washington, D.C. area in the eastern U.S. To take advantage of these unique data, the Community Multiscale Air Quality (CMAQ) model, coupled with the Weather Research and Forecasting (WRF) model is used to simulate the meteorology and air quality in the same region using 12-km, 4-km and 1-km horizontal grid spacings. The goal of the modeling exercise is to demonstrate the capability of the coupled WRF-CMAQ modeling system to simulate air quality at fine grid spacings in an urban area. Development of new data assimilation techniques and the use of higher resolution input data for the WRF model have been implemented to improve the meteorological results, particularly at the 4-km and 1-km grid resolutions. In addition, a number of updates to the CMAQ model were made to enhance the capability of the modeling system to accurately represent the magnitude and spatial distribution of pollutants at fine model resolutions. Data collected during the 2011 DISCOVER-AQ campaign, which include aircraft transects and spirals, ship measurements in the Chesapeake Bay, ozonesondes, tethered balloon measurements, DRAGON aerosol optical depth measurements, LIDAR measurements, and intensive ground-based site measurements, are used to evaluate results from the WRF-CMAQ modeling system for July 2011 at the three model grid resolutions. The results of the comparisons of the model results to these measurements will be presented, along with results from the various sensitivity simulations examining the impact the various updates to the modeling system have on the model estimates.

Comparative evaluation of the impact of GRAPES and MM5 meteorology on CMAQ prediction over Pearl River Delta, China

NASA Astrophysics Data System (ADS)

Deng, T.; Chen, Y.; Wan, Q.

2017-12-01

The Community Multiscale Air Quality (CMAQ) model was utilized for forecasting air quality over the Pearl River Delta (PRD) region from December 2013 to January 2014. The pollution forecasting performance of CMAQ coupled with the two different meteorological models, the Global/Regional Assimilation and Prediction System (GRAPES) and the 5th-generation Mesoscale Model (MM5), was assessed by combining observational data. The effect of meteorological factors and physical-chemical processes on forecast results was discussed through process analysis. The results showed that both models have similar good performance with better performance by GRAPES-CMAQ. GRAPES was superior in predicting the overall meteorological element variation tendencies but showed large deviations in atmospheric pressure and wind speed. It contributed to higher correlation coefficients of the pollutants with GRAPES-CMAQ, but with greater deviation. The underestimations of nitrate and ammonium salt contributed to the underestimations of Particle Matter (PM) and extinction coefficients. Surface layer SO2, CO and NO source emissions made the sole positive contribution. O3 originated mainly from horizontal and vertical transport and chemical processes were the main consumption item. On the contrary, NO2 derived mainly from chemical production.

Dynamic evaluation of CMAQ part I: Separating the effects of changing emissions and changing meteorology on ozone levels between 2002 and 2005 in the eastern US

EPA Science Inventory

A dynamic evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.1 was conducted to evaluate the model's ability to predict changes in ozone levels between 2002 and 2005, a time period characterized by emission reductions associated with the EPA's N...

Use of a Process Analysis Tool for Diagnostic Study on Fine Particulate Matter Predictions in the U.S.-Part II: Analysis and Sensitivity Simulations

EPA Science Inventory

Following the Part I paper that described an application of the U.S. EPA Models-3/Community Multiscale Air Quality (CMAQ) modeling system to the 1999 Southern Oxidants Study episode, this paper presents results from process analysis (PA) using the PA tool embedded in CMAQ and s...

Intercomparison of the community multiscale air quality model and CALGRID using process analysis.

PubMed

O'Neill, Susan M; Lamb, Brian K

2005-08-01

This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit greater fluctuations in the CMAQ cases than in the CALGRID cases, which lead to different placement of the urban ozone plumes. The CALGRID cases, which rely on the SAPRC97 chemical mechanism, exhibited a greater diurnal production/loss cycle of ozone concentrations per hour compared to either the RADM2 or CBIV chemical mechanisms in the CMAQ cases. These results demonstrate the need for specialized process field measurements to confirm whether we are modeling ozone with valid processes.

“Fine-Scale Application of the coupled WRF-CMAQ System to ...

EPA Pesticide Factsheets

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in urban areas using satellite, aircraft, vertical profiler and ground based measurements (http://discover-aq.larc.nasa.gov). In July 2011, the DISCOVER-AQ project conducted intensive air quality measurements in the Baltimore, MD and Washington, D.C. area in the eastern U.S. To take advantage of these unique data, the Community Multiscale Air Quality (CMAQ) model, coupled with the Weather Research and Forecasting (WRF) model is used to simulate the meteorology and air quality in the same region using 12-km, 4-km and 1-km horizontal grid spacings. The goal of the modeling exercise is to demonstrate the capability of the coupled WRF-CMAQ modeling system to simulate air quality at fine grid spacings in an urban area. Development of new data assimilation techniques and the use of higher resolution input data for the WRF model have been implemented to improve the meteorological results, particularly at the 4-km and 1-km grid resolutions. In addition, a number of updates to the CMAQ model were made to enhance the capability of the modeling system to accurately represent the magnitude and spatial distribution of pollutants at fine model resolutions. Data collected during the 2011 DISCOVER-AQ campa

HIGH TIME-RESOLVED COMPARISONS FOR IN-DEPTH PROBING OF CMAQ FINE-PARTICLE AND GAS PREDICTIONS

EPA Science Inventory

Input errors affect model predictions. The diurnal behavior of two inputs NHx, which partitions in the inorganic system between gas and particle, and EC, a nonreactive emitted specie, is compared for CMAQ predictions and observations. A monthly average diurnal profile based on ho...

RECENT DEVELOPMENTS IN THE CMAQ MODEL AEROSOL MODULE

EPA Science Inventory

This poster describes changes that were made to the aerosol module between CMAQ v4.4 and v4.5, as well as the effects of these changes on CMAQ model results. New aerosol diagnostic tools released with CMAQ v4.5 are also described and some illustrative results are provided

CMAQ Model Output

EPA Pesticide Factsheets

CMAQ and CMAQ-VBS model outputThis dataset is associated with the following publication:Woody , M., K. Baker , P. Hayes, J. Jimenez, B. Koo, and H. Pye. Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 16: 4081-4100, (2016).

Model development of dust emission and heterogeneous chemistry within the Community Multiscale Air Quality modeling system and its application over East Asia

NASA Astrophysics Data System (ADS)

Dong, Xinyi; Fu, Joshua S.; Huang, Kan; Tong, Daniel; Zhuang, Guoshun

2016-07-01

The Community Multiscale Air Quality (CMAQ) model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust. The default parameterization of initial threshold friction velocity constants are revised to correct the double counting of the impact of soil moisture in CMAQ by the reanalysis of field experiment data; source-dependent speciation profiles for dust emission are derived based on local measurements for the Gobi and Taklamakan deserts in East Asia; and dust heterogeneous chemistry is also implemented. The improved dust module in the CMAQ is applied over East Asia for March and April from 2006 to 2010. The model evaluation result shows that the simulation bias of PM10 and aerosol optical depth (AOD) is reduced, respectively, from -55.42 and -31.97 % by the original CMAQ to -16.05 and -22.1 % by the revised CMAQ. Comparison with observations at the nearby Gobi stations of Duolun and Yulin indicates that applying a source-dependent profile helps reduce simulation bias for trace metals. Implementing heterogeneous chemistry also results in better agreement with observations for sulfur dioxide (SO2), sulfate (SO42-), nitric acid (HNO3), nitrous oxides (NOx), and nitrate (NO3-). The investigation of a severe dust storm episode from 19 to 21 March 2010 suggests that the revised CMAQ is capable of capturing the spatial distribution and temporal variation of dust. The model evaluation also indicates potential uncertainty within the excessive soil moisture used by meteorological simulation. The mass contribution of fine-mode particles in dust emission may be underestimated by 50 %. The revised CMAQ model provides a useful tool for future studies to investigate the emission, transport, and impact of wind-blown dust over East Asia and elsewhere.

Improving short-term air quality predictions over the U.S. using chemical data assimilation

NASA Astrophysics Data System (ADS)

Kumar, R.; Delle Monache, L.; Alessandrini, S.; Saide, P.; Lin, H. C.; Liu, Z.; Pfister, G.; Edwards, D. P.; Baker, B.; Tang, Y.; Lee, P.; Djalalova, I.; Wilczak, J. M.

2017-12-01

State and local air quality forecasters across the United States use air quality forecasts from the National Air Quality Forecasting Capability (NAQFC) at the National Oceanic and Atmospheric Administration (NOAA) as one of the key tools to protect the public from adverse air pollution related health effects by dispensing timely information about air pollution episodes. This project funded by the National Aeronautics and Space Administration (NASA) aims to enhance the decision-making process by improving the accuracy of NAQFC short-term predictions of ground-level particulate matter of less than 2.5 µm in diameter (PM2.5) by exploiting NASA Earth Science Data with chemical data assimilation. The NAQFC is based on the Community Multiscale Air Quality (CMAQ) model. To improve the initialization of PM2.5 in CMAQ, we developed a new capability in the community Gridpoint Statistical Interpolation (GSI) system to assimilate Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals in CMAQ. Specifically, we developed new capabilities within GSI to read/write CMAQ data, a forward operator that calculates AOD at 550 nm from CMAQ aerosol chemical composition and an adjoint of the forward operator that translates the changes in AOD to aerosol chemical composition. A generalized background error covariance program called "GEN_BE" has been extended to calculate background error covariance using CMAQ output. The background error variances are generated using a combination of both emissions and meteorological perturbations to better capture sources of uncertainties in PM2.5 simulations. The newly developed CMAQ-GSI system is used to perform daily 24-h PM2.5 forecasts with and without data assimilation from 15 July to 14 August 2014, and the resulting forecasts are compared against AirNOW PM2.5 measurements at 550 stations across the U. S. We find that the assimilation of MODIS AOD retrievals improves initialization of the CMAQ model in terms of improved correlation coefficient and reduced bias. However, we notice a large bias in nighttime PM2.5 simulations which is primarily associated with very shallow boundary layer in the model. The developments and results will be discussed in detail during the presentation.

Modeling natural emissions in the Community Multiscale Air Quality (CMAQ) Model-I: building an emissions data base

NASA Astrophysics Data System (ADS)

Smith, S. N.; Mueller, S. F.

2010-05-01

A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions processing system) currently estimates non-methane volatile organic compound (NMVOC) emissions from biogenic sources, nitrogen oxide (NOx) emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, windblown dust particulate, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide), 44% of total NOx, 80% of reactive carbonaceous gases (NMVOCs and carbon monoxide), 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride), and 84% of fine particles (i.e., those smaller than 2.5 μm in size) released into the atmosphere. The seasonality and relative importance of the various natural emissions categories are described.

Modeling natural emissions in the Community Multiscale Air Quality (CMAQ) model - Part 1: Building an emissions data base

NASA Astrophysics Data System (ADS)

Smith, S. N.; Mueller, S. F.

2010-01-01

A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions processing system) currently estimates volatile organic compound (VOC) emissions from biogenic sources, nitrogen oxide (NOx) emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as windblown dust and sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide), 44% of total NOx, 80% of reactive carbonaceous gases (VOCs and carbon monoxide), 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride), and 84% of fine particles (i.e., those smaller than 2.5 μm in size) released into the atmosphere. The seasonality and relative importance of the various natural emissions categories are described.

The interconnection of wet and dry deposition and the response of deposition to incorporation of new process understanding in regional models.

EPA Science Inventory

Process level improvements in the CMAQ system have been made to WRF meteorology, lightning NO production, national ammonia emission profiles, and CMAQ ammonia air-surface exchange. An incremental study was conducted to quantify the impact of individual and combined changes on mo...

Evaluation of CMAQ Coupled With a State-of-the-Art Mercury Chemical Mechanism (CMAQ-newHg-Br)

NASA Astrophysics Data System (ADS)

Ye, Zhuyun; Mao, Huiting; Driscoll, Charles T.; Wang, Yan; Zhang, Yanxu; Jaeglé, Lyatt

2018-03-01

Most regional three-dimensional chemical transport models neglect gaseous elemental mercury (GEM) oxidation by bromine (Br) radicals and Br chemistry. In this study, the Community Multiscale Air Quality model with its default mercury module (CMAQ-Hg) was modified by implementing a state-of-the-art algorithm depicting Hg reactions coupled with Br chemistry (CMAQ-newHg-Br). Using CMAQ-newHg-Br with initial and boundary concentrations (ICs and BCs) from global model output, we conducted simulations for the northeastern United States over March-November 2010. Simulated GEM mixing ratios were predominantly influenced by BCs and hence reflected significant seasonal variation that was captured in the global model output as opposed to a lack of seasonal variation using CMAQ-Hg's default constant BCs. Observed seasonal percentage changes (i.e., seasonal amplitude [=maximum - minimum] in percentage of the seasonal average) of gaseous oxidized mercury (GOM) and particulate bound mercury (PBM) were 76% and 39%, respectively. CMAQ-newHg-Br significantly improved the simulated seasonal changes in GOM and PBM to 43% and 23%, respectively, from 18% and 16% using CMAQ-Hg. CMAQ-newHg-Br reproduced observed Hg wet deposition with a remarkably low fractional bias (FB; 0.4%) as opposed to a -56% to 19% FB for CMAQ-Hg simulations. Simulated Hg dry deposition using CMAQ-newHg-Br excluding the GEM + OH reaction agreed well with studies using inferential methods and litterfall/throughfall measurements, and the discrepancy varied over 13%-42%. This study demonstrated the promising capability of CMAQ-newHg-Br to reproduce observed concentrations and seasonal variations of GEM, GOM and PBM, and Hg wet and dry deposition fluxes.

A Novel Approach of Understanding and Incorporating Error of Chemical Transport Models into a Geostatistical Framework

NASA Astrophysics Data System (ADS)

Reyes, J.; Vizuete, W.; Serre, M. L.; Xu, Y.

2015-12-01

The EPA employs a vast monitoring network to measure ambient PM2.5 concentrations across the United States with one of its goals being to quantify exposure within the population. However, there are several areas of the country with sparse monitoring spatially and temporally. One means to fill in these monitoring gaps is to use PM2.5 modeled estimates from Chemical Transport Models (CTMs) specifically the Community Multi-scale Air Quality (CMAQ) model. CMAQ is able to provide complete spatial coverage but is subject to systematic and random error due to model uncertainty. Due to the deterministic nature of CMAQ, often these uncertainties are not quantified. Much effort is employed to quantify the efficacy of these models through different metrics of model performance. Currently evaluation is specific to only locations with observed data. Multiyear studies across the United States are challenging because the error and model performance of CMAQ are not uniform over such large space/time domains. Error changes regionally and temporally. Because of the complex mix of species that constitute PM2.5, CMAQ error is also a function of increasing PM2.5 concentration. To address this issue we introduce a model performance evaluation for PM2.5 CMAQ that is regionalized and non-linear. This model performance evaluation leads to error quantification for each CMAQ grid. Areas and time periods of error being better qualified. The regionalized error correction approach is non-linear and is therefore more flexible at characterizing model performance than approaches that rely on linearity assumptions and assume homoscedasticity of CMAQ predictions errors. Corrected CMAQ data are then incorporated into the modern geostatistical framework of Bayesian Maximum Entropy (BME). Through cross validation it is shown that incorporating error-corrected CMAQ data leads to more accurate estimates than just using observed data by themselves.

Community Multiscale Air Quality (CMAQ) Modeling for Regional and Hemispheric Scales

EPA Science Inventory

The CMAQ model is a Eulerian model that produces gridded values of atmospheric concentration and deposition. Recent updates to the model are highlighted that impact estimates of dry and wet deposition of nitrogen, sulfur and base cations. Output from the CMAQ model is used in t...

Application of OMI NO2 for Regional Air Quality Model Evaluation

NASA Astrophysics Data System (ADS)

Holloway, T.; Bickford, E.; Oberman, J.; Scotty, E.; Clifton, O. E.

2012-12-01

To support the application of satellite data for air quality analysis, we examine how column NO2 measurements from the Ozone Monitoring Instrument (OMI) aboard the NASA Aura satellite relate to ground-based and model estimates of NO2 and related species. Daily variability, monthly mean values, and spatial gradients in OMI NO2 from the Netherlands Royal Meteorological Institute (KNMI) are compared to ground-based measurements of NO2 from the EPA Air Quality System (AQS) database. Satellite data is gridded to two resolutions typical of regional air quality models - 36 km x 36 km over the continental U.S., and 12 km x 12 km over the Upper Midwestern U.S. Gridding is performed using the Wisconsin Horizontal Interpolation Program for Satellites (WHIPS), a publicly available software to support gridding of satellite data to model grids. Comparing daily OMI retrievals (13:45 daytime local overpass time) with ground-based measurements (13:00), we find January and July 2007 correlation coefficients (r-values) generally positive, with values higher in the winter (January) than summer (July) for most sites. Incidences of anti-correlation or low-correlation are evaluated with model simulations from the U.S. EPA Community Multiscale Air Quality Model version 4.7 (CMAQ). OMI NO2 is also used to evaluate CMAQ output, and to compare performance metrics for CMAQ relative to AQS measurements. We compare simulated NO2 across both the U.S. and Midwest study domains with both OMI NO2 (total column CMAQ values, weighted with the averaging kernel) and with ground-based observations (lowest model layer CMAQ values). 2007 CMAQ simulations employ emissions from the Lake Michigan Air Directors Consortium (LADCO) and meteorology from the Weather Research and Forecasting (WRF) model. Over most of the U.S., CMAQ is too high in January relative to OMI NO2, but too low in January relative to AQS NO2. In contrast, CMAQ is too low in July relative to OMI NO2, but too high relative to AQS NO2. These biases are used to evaluate emission sources (and the importance of missing sources, such as lightning NOx), and to explain model performance for related secondary species, especially nitrate aerosol and ozone.

CMAQ Model Evaluation Framework

EPA Pesticide Factsheets

CMAQ is tested to establish the modeling system’s credibility in predicting pollutants such as ozone and particulate matter. Evaluation of CMAQ has been designed to assess the model’s performance for specific time periods and for specific uses.

USING MM5 VERSION 2 WITH CMAQ AND MODELS-3, A USER'S GUIDE AND TUTORIAL

EPA Science Inventory

Meteorological data are important in many of the processes simulated in the Community Multi-Scale Air Quality (CMAQ) model and the Models-3 framework. The first meteorology model that has been selected and evaluated with CMAQ is the Fifth-Generation Pennsylvania State University...

Model development of dust emission and heterogeneous chemistry within the Community Multiscale Air Quality modeling system and its application over East Asia

NASA Astrophysics Data System (ADS)

Dong, X.; Fu, J. S.; Huang, K.; Tong, D.

2015-12-01

The Community Multiscale Air Quality (CMAQ) model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust aerosols. The default parameterization of threshold friction velocity constants in the CMAQ are revised to avoid double counting of the impact of soil moisture based on the re-analysis of field experiment data; source-dependent speciation profiles for dust emission are derived based on local measurements for the Gobi and Taklamakan deserts in East Asia; and dust heterogeneous chemistry is implemented to simulate the reactions involving dust aerosol. The improved dust module in the CMAQ was applied over East Asia for March and April from 2006 to 2010. Evaluation against observations has demonstrated that simulation bias of PM10 and aerosol optical depth (AOD) is reduced from -55.42 and -31.97 % in the original CMAQ to -16.05 and -22.1 % in the revised CMAQ, respectively. Comparison with observations at the nearby Gobi stations of Duolun and Yulin indicates that applying a source-dependent profile helps reduce simulation bias for trace metals. Implementing heterogeneous chemistry is also found to result in better agreement with observations for sulfur dioxide (SO2), sulfate (SO42-), nitric acid (HNO3), nitrous oxides (NOx), and nitrate (NO3-). Investigation of a severe dust storm episode from 19 to 21 March 2010 suggests that the revised CMAQ is capable of capturing the spatial distribution and temporal variations of dust aerosols. Model evaluation indicates potential uncertainties within the excessive soil moisture fraction used by meteorological simulation. The mass contribution of fine mode aerosol in dust emission may be underestimated by 50 %. The revised revised CMAQ provides a useful tool for future studies to investigate the emission, transport, and impact of wind-blown dust over East Asia and elsewhere.

EVALUATION OF ETA- CMAQ O3 FORECAST OVER DIFFERENT REGIONS OF THE CONTINENTAL US AND USING NEW CATEGORICAL EVALUATION METRICS

EPA Science Inventory

Developmental forecasts simulations with the Eta-CMAQ modeling system over the continental U.S. were initiated in 2005. This paper presents an evaluation of surface O₃ forecast over different regions of the continental U.S. In addition, to the traditional operational e...

Browse CMAQ Applications

EPA Pesticide Factsheets

The CMAQ system has been used to address major environmental issues. Below are examples of how the CMAQ system provides information to help communities, states and countries determine the most effective strategies for reducing exposure to pollution.

COMMUNITY MULTISCALE AIR QUALITY ( CMAQ ) MODEL - QUALITY ASSURANCE AND VERSION CONTROL

EPA Science Inventory

This presentation will be given to the EPA Exposure Modeling Workgroup on January 24, 2006. The quality assurance and version control procedures for the Community Multiscale Air Quality (CMAQ) Model are presented. A brief background of CMAQ is given, then issues related to qual...

Preliminary Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.1

EPA Science Inventory

The AMAD will perform two annual CMAQ model simulations, one with the current publically available version of the CMAQ model (v5.0.2) and the other with the beta version of the new model (v5.1). The results of each model simulation will then be compared to observations and the pe...

Improvement of PM concentration predictability using WRF-CMAQ-DLM coupled system and its applications

NASA Astrophysics Data System (ADS)

Lee, Soon Hwan; Kim, Ji Sun; Lee, Kang Yeol; Shon, Keon Tae

2017-04-01

Air quality due to increasing Particulate Matter(PM) in Korea in Asia is getting worse. At present, the PM forecast is announced based on the PM concentration predicted from the air quality prediction numerical model. However, forecast accuracy is not as high as expected due to various uncertainties for PM physical and chemical characteristics. The purpose of this study was to develop a numerical-statistically ensemble models to improve the accuracy of prediction of PM10 concentration. Numerical models used in this study are the three dimensional atmospheric model Weather Research and Forecasting(WRF) and the community multiscale air quality model (CMAQ). The target areas for the PM forecast are Seoul, Busan, Daegu, and Daejeon metropolitan areas in Korea. The data used in the model development are PM concentration and CMAQ predictions and the data period is 3 months (March 1 - May 31, 2014). The dynamic-statistical technics for reducing the systematic error of the CMAQ predictions was applied to the dynamic linear model(DLM) based on the Baysian Kalman filter technic. As a result of applying the metrics generated from the dynamic linear model to the forecasting of PM concentrations accuracy was improved. Especially, at the high PM concentration where the damage is relatively large, excellent improvement results are shown.

Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS

EPA Science Inventory

Community Multiscale Air Quality (CMAQ) model simulations utilizing the traditional organic aerosol (OA) treatment (CMAQ-AE6) and a volatility basis set (VBS) treatment for OA (CMAQ-VBS) were evaluated against measurements collected at routine monitoring networks (Chemical Specia...

Application and evaluation of two air quality models for particulate matter for a southeastern U.S. episode.

PubMed

Zhang, Yang; Pun, Betty; Wu, Shiang-Yuh; Vijayaraghavan, Krish; Seigneur, Christian

2004-12-01

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29-July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O3), particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 microm (PM10) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O3 and PM than CMAQ. Both models tend to predict O3 values that are higher than those observed. For observed O3 values above 60 ppb, O3 performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O3 values above 40 ppb. Both models predict similar amounts of sulfate (SO4(2-)) and organic matter, and both predict SO4(2-) to be the largest contributor to PM2.5. PMCAMx generally predicts higher amounts of ammonium (NH4+), nitrate (NO3-), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO3-, NH4+, and BC than observed, which degrades its performance. For PM10 and PM2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37-43% and -33-4% for CMAQ and 50-59% and 7-30% for PMCAMx. Both models predict the largest MNGEs for NO3- (98-104% for CMAQ 138-338% for PMCAMx). The inaccurate NO3- predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.

EVALUATION OF THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL VERSION 4.5: UNCERTAINTIES AND SENSITIVITIES IMPACTING MODEL PERFORMANCE: PART II - PARTICULATE MATTER

EPA Science Inventory

This paper presents an analysis of the CMAQ v4.5 model performance for particulate matter and its chemical components for the simulated year 2001. This is part two is two part series of papers that examines the model performance of CMAQ v4.5.

USING CMAQ-AIM TO EVALUATE THE GAS-PARTICLE PARTITIONING TREATMENT IN CMAQ

EPA Science Inventory

The Community Multi-scale Air Quality model (CMAQ) aerosol component utilizes a modal representation, where the size distribution is represented as a sum of three lognormal modes. Though the aerosol treatment in CMAQ is quite advanced compared to other operational air quality mo...

Evaluation of Observation-Fused Regional Air Quality Model Results for Population Air Pollution Exposure Estimation

PubMed Central

Chen, Gang; Li, Jingyi; Ying, Qi; Sherman, Seth; Perkins, Neil; Rajeshwari, Sundaram; Mendola, Pauline

2014-01-01

In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O3 (as well as NOx) monitoring networks in the HRR regions are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses. PMID:24747248

A Multi-Resolution Assessment of the Community Multiscale Air Quality (CMAQ) Model v4.7 Wet Deposition Estimates for 2002 - 2006

EPA Science Inventory

This paper examines the operational performance of the Community Multiscale Air Quality (CMAQ) model simulations for 2002 - 2006 using both 36-km and 12-km horizontal grid spacing, with a primary focus on the performance of the CMAQ model in predicting wet deposition of sulfate (...

Visual Environment for Rich Data Interpretation (VERDI) program for environmental modeling systems

EPA Pesticide Factsheets

VERDI is a flexible, modular, Java-based program used for visualizing multivariate gridded meteorology, emissions and air quality modeling data created by environmental modeling systems such as the CMAQ model and WRF.

APPLICATION AND EVALUATION OF CMAQ IN THE UNITED STATES: AIR QUALITY FORECASTING AND RETROSPECTIVE MODELING

EPA Science Inventory

Presentation slides provide background on model evaluation techniques. Also included in the presentation is an operational evaluation of 2001 Community Multiscale Air Quality (CMAQ) annual simulation, and an evaluation of PM_2.5 for the CMAQ air quality forecast (AQF) ...

A BAYESIAN STATISTICAL APPROACHES FOR THE EVALUATION OF CMAQ

EPA Science Inventory

This research focuses on the application of spatial statistical techniques for the evaluation of the Community Multiscale Air Quality (CMAQ) model. The upcoming release version of the CMAQ model was run for the calendar year 2001 and is in the process of being evaluated by EPA an...

Towards the Next Generation Air Quality Modeling System ...

EPA Pesticide Factsheets

The community multiscale air quality (CMAQ) model of the U.S. Environmental Protection Agency is one of the most widely used air quality model worldwide; it is employed for both research and regulatory applications at major universities and government agencies for improving understanding of the formation and transport of air pollutants. It is noted, however, that air quality issues and climate change assessments need to be addressed globally recognizing the linkages and interactions between meteorology and atmospheric chemistry across a wide range of scales. Therefore, an effort is currently underway to develop the next generation air quality modeling system (NGAQM) that will be based on a global integrated meteorology and chemistry system. The model for prediction across scales-atmosphere (MPAS-A), a global fully compressible non-hydrostatic model with seamlessly refined centroidal Voronoi grids, has been chosen as the meteorological driver of this modeling system. The initial step of adapting MPAS-A for the NGAQM was to implement and test the physics parameterizations and options that are preferred for retrospective air quality simulations (see the work presented by R. Gilliam, R. Bullock, and J. Herwehe at this workshop). The next step, presented herein, would be to link the chemistry from CMAQ to MPAS-A to build a prototype for the NGAQM. Furthermore, the techniques to harmonize transport processes between CMAQ and MPAS-A, methodologies to connect the chemis

A mechanistic modeling system for estimating large scale emissions and transport of pollen and co-allergens

PubMed Central

Efstathiou, Christos; Isukapalli, Sastry

2011-01-01

Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQ-pollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002, during their corresponding peak pollination periods (April for birch and September for ragweed). The model simulations were driven by previously evaluated meteorological model outputs and emissions inventories for the eastern United States for the simulation period. A semi-quantitative evaluation of CMAQ-pollen was performed using tree and ragweed pollen counts in Newark, NJ for the same time periods. The peak birch pollen concentrations were predicted to occur within two days of the peak measurements, while the temporal patterns closely followed the measured profiles of overall tree pollen. For the case of ragweed pollen, the model was able to capture the patterns observed during September 2002, but did not predict an early peak; this can be associated with a wider species pollination window and inadequate spatial information in current land cover databases. An additional sensitivity simulation was performed to comparatively evaluate the dispersion patterns predicted by CMAQ-pollen with those predicted by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, which is used extensively in aerobiological studies. The CMAQ estimated concentration plumes matched the equivalent pollen scenario modeled with HYSPLIT. The novel pollen modeling approach presented here allows simultaneous estimation of multiple airborne allergens and other air pollutants, and is being developed as a central component of an integrated population exposure modeling system, the Modeling Environment for Total Risk studies (MENTOR) for multiple, co-occurring contaminants that include aeroallergens and irritants. PMID:21516207

A mechanistic modeling system for estimating large-scale emissions and transport of pollen and co-allergens

NASA Astrophysics Data System (ADS)

Efstathiou, Christos; Isukapalli, Sastry; Georgopoulos, Panos

2011-04-01

Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQ-pollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002, during their corresponding peak pollination periods (April for birch and September for ragweed). The model simulations were driven by previously evaluated meteorological model outputs and emissions inventories for the eastern United States for the simulation period. A semi-quantitative evaluation of CMAQ-pollen was performed using tree and ragweed pollen counts in Newark, NJ for the same time periods. The peak birch pollen concentrations were predicted to occur within two days of the peak measurements, while the temporal patterns closely followed the measured profiles of overall tree pollen. For the case of ragweed pollen, the model was able to capture the patterns observed during September 2002, but did not predict an early peak; this can be associated with a wider species pollination window and inadequate spatial information in current land cover databases. An additional sensitivity simulation was performed to comparatively evaluate the dispersion patterns predicted by CMAQ-pollen with those predicted by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, which is used extensively in aerobiological studies. The CMAQ estimated concentration plumes matched the equivalent pollen scenario modeled with HYSPLIT. The novel pollen modeling approach presented here allows simultaneous estimation of multiple airborne allergens and other air pollutants, and is being developed as a central component of an integrated population exposure modeling system, the Modeling Environment for Total Risk studies (MENTOR) for multiple, co-occurring contaminants that include aeroallergens and irritants.

Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS

NASA Astrophysics Data System (ADS)

Woody, Matthew C.; Baker, Kirk R.; Hayes, Patrick L.; Jimenez, Jose L.; Koo, Bonyoung; Pye, Havala O. T.

2016-03-01

Community Multiscale Air Quality (CMAQ) model simulations utilizing the traditional organic aerosol (OA) treatment (CMAQ-AE6) and a volatility basis set (VBS) treatment for OA (CMAQ-VBS) were evaluated against measurements collected at routine monitoring networks (Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE)) and those collected during the 2010 California at the Nexus of Air Quality and Climate Change (CalNex) field campaign to examine important sources of OA in southern California. Traditionally, CMAQ treats primary organic aerosol (POA) as nonvolatile and uses a two-product framework to represent secondary organic aerosol (SOA) formation. CMAQ-VBS instead treats POA as semivolatile and lumps OA using volatility bins spaced an order of magnitude apart. The CMAQ-VBS approach underpredicted organic carbon (OC) at IMPROVE and CSN sites to a greater degree than CMAQ-AE6 due to the semivolatile POA treatment. However, comparisons to aerosol mass spectrometer (AMS) measurements collected at Pasadena, CA, indicated that CMAQ-VBS better represented the diurnal profile and primary/secondary split of OA. CMAQ-VBS SOA underpredicted the average measured AMS oxygenated organic aerosol (OOA, a surrogate for SOA) concentration by a factor of 5.2, representing a considerable improvement to CMAQ-AE6 SOA predictions (factor of 24 lower than AMS). We use two new methods, one based on species ratios (SOA/ΔCO and SOA/Ox) and another on a simplified SOA parameterization, to apportion the SOA underprediction for CMAQ-VBS to slow photochemical oxidation (estimated as 1.5 × lower than observed at Pasadena using -log(NOx : NOy)), low intrinsic SOA formation efficiency (low by 1.6 to 2 × for Pasadena), and low emissions or excessive dispersion for the Pasadena site (estimated to be 1.6 to 2.3 × too low/excessive). The first and third factors are common to CMAQ-AE6, while the intrinsic SOA formation efficiency for that model is estimated to be too low by about 7 × . From source-apportioned model results, we found most of the CMAQ-VBS modeled POA at the Pasadena CalNex site was attributable to meat cooking emissions (48 %, consistent with a substantial fraction of cooking OA in the observations). This is compared to 18 % from gasoline vehicle emissions, 13 % from biomass burning (in the form of residential wood combustion), and 8 % from diesel vehicle emissions. All "other" inventoried emission sources (e.g., industrial, point, and area sources) comprised the final 13 %. The CMAQ-VBS semivolatile POA treatment underpredicted AMS hydrocarbon-like OA (HOA) + cooking-influenced OA (CIOA) at Pasadena by a factor of 1.8 compared to a factor of 1.4 overprediction of POA in CMAQ-AE6, but it did capture the AMS diurnal profile of HOA and CIOA well, with the exception of the midday peak. Overall, the CMAQ-VBS with its semivolatile treatment of POA, SOA from intermediate volatility organic compounds (IVOCs), and aging of SOA improves SOA model performance (though SOA formation efficiency is still 1.6-2 × too low). However, continued efforts are needed to better understand assumptions in the parameterization (e.g., SOA aging) and provide additional certainty to how best to apply existing emission inventories in a framework that treats POA as semivolatile, which currently degrades existing model performance at routine monitoring networks. The VBS and other approaches (e.g., AE6) require additional work to appropriately incorporate IVOC emissions and subsequent SOA formation.

Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS

DOE PAGES

Woody, Matthew C.; Baker, Kirk R.; Hayes, Patrick L.; ...

2016-03-29

In this paper, Community Multiscale Air Quality (CMAQ) model simulations utilizing the traditional organic aerosol (OA) treatment (CMAQ-AE6) and a volatility basis set (VBS) treatment for OA (CMAQ-VBS) were evaluated against measurements collected at routine monitoring networks (Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE)) and those collected during the 2010 California at the Nexus of Air Quality and Climate Change (CalNex) field campaign to examine important sources of OA in southern California. Traditionally, CMAQ treats primary organic aerosol (POA) as nonvolatile and uses a two-product framework to represent secondary organic aerosol (SOA) formation. CMAQ-VBS insteadmore » treats POA as semivolatile and lumps OA using volatility bins spaced an order of magnitude apart. The CMAQ-VBS approach underpredicted organic carbon (OC) at IMPROVE and CSN sites to a greater degree than CMAQ-AE6 due to the semivolatile POA treatment. However, comparisons to aerosol mass spectrometer (AMS) measurements collected at Pasadena, CA, indicated that CMAQ-VBS better represented the diurnal profile and primary/secondary split of OA. CMAQ-VBS SOA underpredicted the average measured AMS oxygenated organic aerosol (OOA, a surrogate for SOA) concentration by a factor of 5.2, representing a considerable improvement to CMAQ-AE6 SOA predictions (factor of 24 lower than AMS). We use two new methods, one based on species ratios (SOA/ΔCO and SOA/O x) and another on a simplified SOA parameterization, to apportion the SOA underprediction for CMAQ-VBS to slow photochemical oxidation (estimated as 1.5 × lower than observed at Pasadena using -log(NO x:NO y)), low intrinsic SOA formation efficiency (low by 1.6 to 2 × for Pasadena), and low emissions or excessive dispersion for the Pasadena site (estimated to be 1.6 to 2.3 × too low/excessive). The first and third factors are common to CMAQ-AE6, while the intrinsic SOA formation efficiency for that model is estimated to be too low by about 7 ×. From source-apportioned model results, we found most of the CMAQ-VBS modeled POA at the Pasadena CalNex site was attributable to meat cooking emissions (48 %, consistent with a substantial fraction of cooking OA in the observations). This is compared to 18 % from gasoline vehicle emissions, 13 % from biomass burning (in the form of residential wood combustion), and 8 % from diesel vehicle emissions. All "other" inventoried emission sources (e.g., industrial, point, and area sources) comprised the final 13 %. The CMAQ-VBS semivolatile POA treatment underpredicted AMS hydrocarbon-like OA (HOA) + cooking-influenced OA (CIOA) at Pasadena by a factor of 1.8 compared to a factor of 1.4 overprediction of POA in CMAQ-AE6, but it did capture the AMS diurnal profile of HOA and CIOA well, with the exception of the midday peak. Overall, the CMAQ-VBS with its semivolatile treatment of POA, SOA from intermediate volatility organic compounds (IVOCs), and aging of SOA improves SOA model performance (though SOA formation efficiency is still 1.6–2 × too low). However, continued efforts are needed to better understand assumptions in the parameterization (e.g., SOA aging) and provide additional certainty to how best to apply existing emission inventories in a framework that treats POA as semivolatile, which currently degrades existing model performance at routine monitoring networks. Finally, the VBS and other approaches (e.g., AE6) require additional work to appropriately incorporate IVOC emissions and subsequent SOA formation.« less

Application of Watershed Deposition Tool to Estimate from CMAQ Simulations of the Atmospheric Deposition of Nitrogen to Tampa Bay and Its Watershed

EPA Science Inventory

The USEPA has developed Watershed Deposition Tool (WDT) to calculate from the Community Multiscale Air Quality (CMAQ) model output the nitrogen, sulfur, and mercury deposition rates to watersheds and their sub-basins. The CMAQ model simulates from first principles the transport, ...

TTI CM/AQ evaluation model user`s guide and workshop training materials. Interim research report, September 1993-August 1996

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1995-08-01

The TTI CM/AQ Evaluation Model evaluates potential projects based on the following criteria: eligibility, travel impacts, emission impacts, and cost-effectiveness. To compare independent projects within a region during the decision process for CM/AQ funding, each project evaluated with this model is given an overall score based on the project`s effects for the criteria listed above. Training workshops were held by TTI in the first quarter of 1995 to teach metropolitan planning organization, state department of transportation, and regional air quality organization staff how to use this model. Basics of sketch-planning applications were also taught. The DRCOG and TTI CM/AQ Evaluationmore » Models represent significant steps toward the development of analytical methodologies for selecting projects for CM/AQ funding. Because the needs of nonattainment and attainment areas change over time, this model is particularly useful as key evaluation criteria can be modified to reflect the changing needs of a metropolitan area.« less

CMAQ's Support of EPA's Mission

EPA Pesticide Factsheets

At Federal, State, and Local agencies, CMAQ is often used when developing regulatory policies because it represents the state-of-the-science in air quality modeling. See how CMAQ supports the EPA mission of protecting human health and the environment.

LINKING ETA MODEL WITH THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODELING SYSTEM: OZONE BOUNDARY CONDITIONS

EPA Science Inventory

A prototype surface ozone concentration forecasting model system for the Eastern U.S. has been developed. The model system is consisting of a regional meteorological and a regional air quality model. It demonstrated a strong prediction dependence on its ozone boundary conditions....

Evaluation of CMAQ and CAMx Ensemble Air Quality Forecasts during the 2015 MAPS-Seoul Field Campaign

NASA Astrophysics Data System (ADS)

Kim, E.; Kim, S.; Bae, C.; Kim, H. C.; Kim, B. U.

2015-12-01

The performance of Air quality forecasts during the 2015 MAPS-Seoul Field Campaign was evaluated. An forecast system has been operated to support the campaign's daily aircraft route decisions for airborne measurements to observe long-range transporting plume. We utilized two real-time ensemble systems based on the Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Comprehensive Air quality Model with extensions (CAMx) modeling framework and WRF-SMOKE- Community Multi_scale Air Quality (CMAQ) framework over northeastern Asia to simulate PM10 concentrations. Global Forecast System (GFS) from National Centers for Environmental Prediction (NCEP) was used to provide meteorological inputs for the forecasts. For an additional set of retrospective simulations, ERA Interim Reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF) was also utilized to access forecast uncertainties from the meteorological data used. Model Inter-Comparison Study for Asia (MICS-Asia) and National Institute of Environment Research (NIER) Clean Air Policy Support System (CAPSS) emission inventories are used for foreign and domestic emissions, respectively. In the study, we evaluate the CMAQ and CAMx model performance during the campaign by comparing the results to the airborne and surface measurements. Contributions of foreign and domestic emissions are estimated using a brute force method. Analyses on model performance and emissions will be utilized to improve air quality forecasts for the upcoming KORUS-AQ field campaign planned in 2016.

Performance and diagnostic evaluation of ozone predictions by the Eta-Community Multiscale Air Quality Forecast System during the 2002 New England Air Quality Study.

PubMed

Yu, Shaocai; Mathur, Rohit; Kang, Daiwen; Schere, Kenneth; Eder, Brian; Pleim, Jonathan

2006-10-01

A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within +/- 20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites. The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64-77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations.

Implementation of a WRF-CMAQ Air Quality Modeling System in Bogotá, Colombia

NASA Astrophysics Data System (ADS)

Nedbor-Gross, R.; Henderson, B. H.; Pachon, J. E.; Davis, J. R.; Baublitz, C. B.; Rincón, A.

2014-12-01

Due to a continuous economic growth Bogotá, Colombia has experienced air pollution issues in recent years. The local environmental authority has implemented several strategies to curb air pollution that have resulted in the decrease of PM10 concentrations since 2010. However, more activities are necessary in order to meet international air quality standards in the city. The University of Florida Air Quality and Climate group is collaborating with the Universidad de La Salle to prioritize regulatory strategies for Bogotá using air pollution simulations. To simulate pollution, we developed a modeling platform that combines the Weather Research and Forecasting Model (WRF), local emissions, and the Community Multi-scale Air Quality model (CMAQ). This platform is the first of its kind to be implemented in the megacity of Bogota, Colombia. The presentation will discuss development and evaluation of the air quality modeling system, highlight initial results characterizing photochemical conditions in Bogotá, and characterize air pollution under proposed regulatory strategies. The WRF model has been configured and applied to Bogotá, which resides in a tropical climate with complex mountainous topography. Developing the configuration included incorporation of local topography and land-use data, a physics sensitivity analysis, review, and systematic evaluation. The threshold, however, was set based on synthesis of model performance under less mountainous conditions. We will evaluate the impact that differences in autocorrelation contribute to the non-ideal performance. Air pollution predictions are currently under way. CMAQ has been configured with WRF meteorology, global boundary conditions from GEOS-Chem, and a locally produced emission inventory. Preliminary results from simulations show promising performance of CMAQ in Bogota. Anticipated results include a systematic performance evaluation of ozone and PM10, characterization of photochemical sensitivity, and air quality predictions under proposed regulatory scenarios.

Sensitivity of air quality simulation to smoke plume rise

Treesearch

Yongqiang Liu; Gary Achtemeier; Scott Goodrick

2008-01-01

Plume rise is the height smoke plumes can reach. This information is needed by air quality models such as the Community Multiscale Air Quality (CMAQ) model to simulate physical and chemical processes of point-source fire emissions. This study seeks to understand the importance of plume rise to CMAQ air quality simulation of prescribed burning to plume rise. CMAQ...

The air quality forecast in Beijing with Community Multi-scale Air Quality Modeling (CMAQ) System: model evaluation and improvement

NASA Astrophysics Data System (ADS)

Wu, Q.

2013-12-01

The MM5-SMOKE-CMAQ model system, which is developed by the United States Environmental Protection Agency(U.S. EPA) as the Models-3 system, has been used for the daily air quality forecast in the Beijing Municipal Environmental Monitoring Center(Beijing MEMC), as a part of the Ensemble Air Quality Forecast System for Beijing(EMS-Beijing) since the Olympic Games year 2008. In this study, we collect the daily forecast results of the CMAQ model in the whole year 2010 for the model evaluation. The results show that the model play a good model performance in most days but underestimate obviously in some air pollution episode. A typical air pollution episode from 11st - 20th January 2010 was chosen, which the air pollution index(API) of particulate matter (PM10) observed by Beijing MEMC reaches to 180 while the prediction of PM10-API is about 100. Taking in account all stations in Beijing, including urban and suburban stations, three numerical methods are used for model improvement: firstly, enhance the inner domain with 4km grids, the coverage from only Beijing to the area including its surrounding cities; secondly, update the Beijing stationary area emission inventory, from statistical county-level to village-town level, that would provide more detail spatial informance for area emissions; thirdly, add some industrial points emission in Beijing's surrounding cities, the latter two are both the improvement of emission. As the result, the peak of the nine national standard stations averaged PM10-API, which is simulated by CMAQ as daily hindcast PM10-API, reach to 160 and much near to the observation. The new results show better model performance, which the correlation coefficent is 0.93 in national standard stations average and 0.84 in all stations, the relative error is 15.7% in national standard stations averaged and 27% in all stations. The time series of 9 national standard in Beijing urban The scatter diagram of all stations in Beijing, the red is the forecast and the blue is new result.

COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (ONE ATMOSPHERE)

EPA Science Inventory

This task supports ORD's strategy by providing responsive technical support of EPA's mission and provides credible state of the art air quality models and guidance. This research effort is to develop and improve the Community Multiscale Air Quality (CMAQ) modeling system, a mu...

Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework

EPA Science Inventory

The work here complements the overview analysis of the modelling systems participating in the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3) by focusing on the performance for hourly surface ozone by two modelling systems, Chimere for Europe an...

Improved meteorology from an updated WRF/CMAQ modeling ...

EPA Pesticide Factsheets

Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) that employs the Pleim-Xiu land surface model (PX LSM). Recently, PX LSM WRF/CMAQ has been updated in vegetation, soil, and boundary layer processes resulting in improved 2 m temperature (T) and mixing ratio (Q), 10 m wind speed, and surface ozone simulations across the domain compared to the previous version for a period around August 2006. Yearlong meteorology simulations with the updated system demonstrate that MODIS input helps reduce bias of the 2 m Q estimation during the growing season from April to September. Improvements follow the green-up in the southeast from April and move toward the west and north through August. From October to March, MODIS input does not have much influence on the system because vegetation is not as active. The greatest effects of MODIS input include more accurate phenology, better representation of leaf area index (LAI) for various forest ecosystems and agricultural areas, and realistically sparse vegetation coverage in the western drylands. Despite the improved meteorology, MODIS input causes higher bias for the surface O3 simulation in April, August, and October in areas where MODIS LAI is much less than the base LAI. Thus, improvement

Performance characteristics of MM5-SMOKE-CMAQ for a summer photochemical episode in southeast England, United Kingdom

NASA Astrophysics Data System (ADS)

Yu, Y.; Sokhi, R. S.; Kitwiroon, N.; Middleton, D. R.; Fisher, B.

In this study a modelling system consisting of Mesoscale Model (MM5), Sparse Matrix Operator Kernel Emissions (SMOKE) and Community Multiscale Air Quality (CMAQ) model has been applied to a summer photochemical period in southeast England, UK. Ozone (O 3), nitrogen dioxide (NO 2) and particulate matter (PM 2.5) concentrations modelled with different horizontal grid resolutions (9 and 3 km) were evaluated against available ground-level observations from the UK Automatic Urban and Rural Network (AURN) and London Air Quality Network (LAQN) for the period of 24-28 June 2001 with a focus on O 3 predictions. This effort, which represents the first comprehensive performance evaluation of the modelling system over a UK domain, reveals that CMAQ's ability to reproduce surface O 3 observations varies with O 3 concentrations. It underpredicts O 3 mixing ratios on high-O 3 days and overpredicts the maximum and minimum hourly O 3 values for most low-O 3 days. Model sensitivity analysis with doubled anthropogenic NO x or volatile organic compounds (VOC) emissions and analysis of the daylight-averaged levels of OX (sum of O 3 and NO 2) as a function of NO x revealed that the undereprediction of peak O 3 concentrations on high-O 3 days is caused by the underprediction of regional contribution and to a lesser extent local production, which might be related to the underestimation of European emissions in EMEP inventory and the lacked reactivity of the modelled atmosphere. CMAQ systematically underpredicts hourly NO 2 mixing ratios but captures the temporal variations. The normalized mean bias for hourly NO 2, although much larger than that for O 3, falls well within the generally accepted range of -20% to -50%. CMAQ with both resolutions (9 and 3 km) significantly underpredicts PM 2.5 mass concentrations and fails to reproduce its temporal variations. While model performance for O 3 and PM 2.5 are not very sensitive to model grid resolutions, a better agreement between modelled and measured hourly NO 2 mixing ratios was achieved with higher resolution. Further investigation into the uncertainties in meteorological input, uncertainties in emissions, as well as representation of physical and chemical processes (e.g. chemical mechanism) in the model is needed to identify the causes for the discrepancies between observations and predictions.

The Lightning Nitrogen Oxides Model (LNOM): Status and Recent Applications

NASA Technical Reports Server (NTRS)

Koshak, William; Khan, Maudood; Peterson, Harold

2011-01-01

Improvements to the NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) are discussed. Recent results from an August 2006 run of the Community Multiscale Air Quality (CMAQ) modeling system that employs LNOM lightning NOx (= NO + NO2) estimates are provided. The LNOM analyzes Lightning Mapping Array (LMA) data to estimate the raw (i.e., unmixed and otherwise environmentally unmodified) vertical profile of lightning NOx. The latest LNOM estimates of (a) lightning channel length distributions, (b) lightning 1-m segment altitude distributions, and (c) the vertical profile of NOx are presented. The impact of including LNOM-estimates of lightning NOx on CMAQ output is discussed.

Multi-year downscaling application of two-way coupled WRF v3.4 and CMAQ v5.0.2 over east Asia for regional climate and air quality modeling: model evaluation and aerosol direct effects

NASA Astrophysics Data System (ADS)

Hong, Chaopeng; Zhang, Qiang; Zhang, Yang; Tang, Youhua; Tong, Daniel; He, Kebin

2017-06-01

In this study, a regional coupled climate-chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM) and the regional two-way coupled Weather Research and Forecasting - Community Multi-scale Air Quality (WRF-CMAQ) model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over east Asia for a multi-year climatological application during 2006-2010, driven with CESM downscaling data under Representative Concentration Pathways 4.5 (RCP4.5), along with a short-term air quality application in representative months in 2013 that was driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the two-way coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2 m temperature (T2) in this study (with a mean bias of -0.6 °C) compared with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2. 5 in winter (with a normalized mean bias (NMB) of 6.4 % in 2013) and O3 in summer (with an NMB of 18.2 % in 2013) in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2. 5 concentrations in China, WRF-CMAQ was able to capture the high PM2. 5 concentrations in urban areas. In general, the two-way coupled WRF-CMAQ model performed well for both climatological and air quality applications. The coupled modeling system with direct aerosol feedbacks predicted aerosol optical depth relatively well and significantly reduced the overprediction in downward shortwave radiation at the surface (SWDOWN) over polluted regions in China. The performance of cloud variables was not as good as other meteorological variables, and underpredictions of cloud fraction resulted in overpredictions of SWDOWN and underpredictions of shortwave and longwave cloud forcing. The importance of climate-chemistry interactions was demonstrated via the impacts of aerosol direct effects on climate and air quality. The aerosol effects on climate and air quality in east Asia (e.g., SWDOWN and T2 decreased by 21.8 W m-2 and 0.45 °C, respectively, and most pollutant concentrations increased by 4.8-9.5 % in January over China's major cities) were more significant than in other regions because of higher aerosol loadings that resulted from severe regional pollution, which indicates the need for applying online-coupled models over east Asia for regional climate and air quality modeling and to study the important climate-chemistry interactions. This work established a baseline for WRF-CMAQ simulations for a future period under the RCP4.5 climate scenario, which will be presented in a future paper.

Modeling of air pollutant removal by dry deposition to urban trees using a WRF/CMAQ/i-Tree Eco coupled system.

PubMed

Cabaraban, Maria Theresa I; Kroll, Charles N; Hirabayashi, Satoshi; Nowak, David J

2013-05-01

A distributed adaptation of i-Tree Eco was used to simulate dry deposition in an urban area. This investigation focused on the effects of varying temperature, LAI, and NO2 concentration inputs on estimated NO2 dry deposition to trees in Baltimore, MD. A coupled modeling system is described, wherein WRF provided temperature and LAI fields, and CMAQ provided NO2 concentrations. A base case simulation was conducted using built-in distributed i-Tree Eco tools, and simulations using different inputs were compared against this base case. Differences in land cover classification and tree cover between the distributed i-Tree Eco and WRF resulted in changes in estimated LAI, which in turn resulted in variations in simulated NO2 dry deposition. Estimated NO2 removal decreased when CMAQ-derived concentration was applied to the distributed i-Tree Eco simulation. Discrepancies in temperature inputs did little to affect estimates of NO2 removal by dry deposition to trees in Baltimore. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multiple Sensitivity Testing for Regional Air Quality Model in summer 2014

NASA Astrophysics Data System (ADS)

Tang, Y.; Lee, P.; Pan, L.; Tong, D.; Kim, H. C.; Huang, M.; Wang, J.; McQueen, J.; Lu, C. H.; Artz, R. S.

2015-12-01

The NOAA Air Resources laboratory leads to improve the performance of the U.S. Air Quality Forecasting Capability (NAQFC). It is operational in NOAA National Centers for Environmental Prediction (NCEP) which focuses on predicting surface ozone and PM2.5. In order to improve its performance, we tested several approaches, including NOAA Environmental Modeling System Global Aerosol Component (NGAC) simulation derived ozone and aerosol lateral boundary conditions (LBC), bi-direction NH3 emission and HMS(Hazard Mapping System)-BlueSky emission with the latest U.S. EPA Community Multi-scale Air Quality model (CMAQ) version and the U.S EPA National Emission Inventory (NEI)-2011 anthropogenic emissions. The operational NAQFC uses static profiles for its lateral boundary condition (LBC), which does not impose severe issue for near-surface air quality prediction. However, its degraded performance for the upper layer (e.g. above 3km) is evident when comparing with aircraft measured ozone. NCEP's Global Forecast System (GFS) has tracer O3 prediction treated as 3-D prognostic variable (Moorthi and Iredell, 1998) after being initialized with Solar Backscatter Ultra Violet-2 (SBUV-2) satellite data. We applied that ozone LBC to the CMAQ's upper layers and yield more reasonable O3 prediction than that with static LBC comparing with the aircraft data in Discover-AQ Colorado campaign. NGAC's aerosol LBC also improved the PM2.5 prediction with more realistic background aerosols. The bi-direction NH3 emission used in CMAQ also help reduce the NH3 and nitrate under-prediction issue. During summer 2014, strong wildfires occurred in northwestern USA, and we used the US Forest Service's BlueSky fire emission with HMS fire counts to drive CMAQ and tested the difference of day-1 and day-2 fire emission estimation. Other related issues were also discussed.

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2

EPA Pesticide Factsheets

The uploaded data consists of the BRACE Na aerosol observations paired with CMAQ model output, the updated model's parameterization of sea salt aerosol emission size distribution, and the model's parameterization of the sea salt emission factor as a function of sea surface temperature. This dataset is associated with the following publication:Gantt , B., J. Kelly , and J. Bash. Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 8: 3733-3746, (2015).

THE EMISSION PROCESSING SYSTEM FOR THE ETA/CMAQ AIR QUALITY FORECAST SYSTEM

EPA Science Inventory

NOAA and EPA have created an Air Quality Forecast (AQF) system. This AQF system links an adaptation of the EPA's Community Multiscale Air Quality Model with the 12 kilometer ETA model running operationally at NOAA's National Center for Environmental Predication (NCEP). One of th...

Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS

NASA Astrophysics Data System (ADS)

Woody, M. C.; Baker, K. R.; Hayes, P. L.; Jimenez, J. L.; Koo, B.; Pye, H. O. T.

2015-10-01

Community Multiscale Air Quality (CMAQ) model simulations utilizing the volatility basis set (VBS) treatment for organic aerosols (CMAQ-VBS) were evaluated against measurements collected at routine monitoring networks (Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE)) and those collected during the 2010 California at the Nexus of Air Quality and Climate Change (CalNex) field campaign to examine important sources of organic aerosol (OA) in southern California. CMAQ-VBS (OA lumped by volatility, semivolatile POA) underpredicted total organic carbon (OC) at CSN (-25.5 % Normalized Median Bias (NMdnB)) and IMPROVE (-63.9 % NMdnB) locations and total OC was underpredicted to a greater degree compared to the CMAQ-AE6 (9.9 and -55.7 % NMdnB, respectively; semi-explicit OA treatment, SOA lumped by parent hydrocarbon, nonvolatile POA). However, comparisons to aerosol mass spectrometer (AMS) measurements collected at Pasadena, CA indicated that CMAQ-VBS better represented the diurnal profile and the primary/secondary split of OA. CMAQ-VBS secondary organic aerosol (SOA) underpredicted the average measured AMS oxygenated organic aerosol (OOA, a surrogate of SOA) concentration by a factor of 5.2 (4.7 μg m-3 measured vs. 0.9 μg m-3 modeled), a considerable improvement to CMAQ-AE6 SOA predictions, which were approximately 24× lower than the average AMS OOA concentration. We use two new methods, based on species ratios and on a simplified SOA parameterization from the observations, to apportion the SOA underprediction for CMAQ-VBS to too slow photochemical oxidation (estimated as 1.5× lower than observed at Pasadena using - log (NOx: NOy)), low intrinsic SOA formation efficiency (low by 1.6 to 2× for Pasadena), and too low emissions or too high dispersion for the Pasadena site (estimated to be 1.6 to 2.3× too low/high). The first and third factors will be similar for CMAQ-AE6, while the intrinsic SOA formation efficiency for that model is estimated to be too low by about 7×. For CMAQ-VBS, 90 % of the anthropogenic SOA mass formed was attributed to aged secondary semivolatile vapors (70 % originating from volatile organic compounds (VOCs) and 20 % from intermediate volatility compounds (IVOCs)). From source-apportioned model results, we found most of the CMAQ-VBS modeled POA at the Pasadena CalNex site was attributable to meat cooking emissions (48 %, and consistent with a substantial fraction of cooking OA in the observations), compared to 18 % from gasoline vehicle emissions, 13 % from biomass burning (in the form of residential wood combustion), and 8 % from diesel vehicle emissions. All "other" inventoried emission sources (e.g. industrial/point sources) comprised the final 13 %. The CMAQ-VBS semivolatile POA treatment underpredicted AMS hydrocarbon-like OA (HOA) + cooking-influenced OA (CIOA) at Pasadena by a factor of 1.8 (1.16 μg m-3 modeled vs. 2.05 μg m-3 observed) compared to a factor of 1.4 overprediction of POA in CMAQ-AE6, but did well to capture the AMS diurnal profile of HOA and CIOA, with the exception of the midday peak. We estimated that using the National Emission Inventory (NEI) POA emissions without scaling to represent SVOCs underestimates SVOCs by ~1.7×.

EMISSIONS PROCESSING FOR THE ETA/ CMAQ AIR QUALITY FORECAST SYSTEM

EPA Science Inventory

NOAA and EPA have created an Air Quality Forecast (AQF) system. This AQF system links an adaptation of the EPA's Community Multiscale Air Quality Model with the 12 kilometer ETA model running operationally at NOAA's National Center for Environmental Predication (NCEP). One of the...

EMISSION AND SURFACE EXCHANGE PROCESS

EPA Science Inventory

This task supports the development, evaluation, and application of emission and dry deposition algorithms in air quality simulation models, such as the Models-3/Community Multiscale Air Quality (CMAQ) modeling system. Emission estimates influence greatly the accuracy of air qual...

A Five-Year CMAQ PM2.5 Model Performance for Wildfires and Prescribed Fires

NASA Astrophysics Data System (ADS)

Wilkins, J. L.; Pouliot, G.; Foley, K.; Rappold, A.; Pierce, T. E.

2016-12-01

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. Two components of the biomass burning inventory, wildfires and prescribed fires are routinely estimated in the national emissions inventory. However, there is a large amount of uncertainty in the development of these emission inventory sectors. We have completed a 5 year set of CMAQ model simulations (2008-2012) in which we have simulated regional air quality with and without the wildfire and prescribed fire inventory. We will examine CMAQ model performance over regions with significant PM2.5 and Ozone contribution from prescribed fires and wildfires. We will also review plume rise to see how it affects model bias and compare CMAQ current fire emissions input to an hourly dataset from FLAMBE.

Analyzing the Effects of Horizontal Resolution on Long-Term Coupled WRF-CMAQ Simulations

EPA Science Inventory

The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. To this end, WRF-CMAQ simulations over the co...

MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL AEROSOL COMPONENT 1: MODEL DESCRIPTION

EPA Science Inventory

The aerosol component of the Community Multiscale Air Quality (CMAQ) model is designed to be an efficient and economical depiction of aerosol dynamics in the atmosphere. The approach taken represents the particle size distribution as the superposition of three lognormal subdis...

Updates to In-Line Calculation of Photolysis Rates

EPA Science Inventory

How photolysis rates are calculated affects ozone and aerosol concentrations predicted by the CMAQ model and the model?s run-time. The standard configuration of CMAQ uses the inline option that calculates photolysis rates by solving the radiative transfer equation for the needed ...

Assessment of the effects of horizontal grid resolution on long-term air quality trends using coupled WRF-CMAQ simulations

EPA Science Inventory

The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental Uni...

Regionalized PM2.5 Community Multiscale Air Quality model performance evaluation across a continuous spatiotemporal domain.

PubMed

Reyes, Jeanette M; Xu, Yadong; Vizuete, William; Serre, Marc L

2017-01-01

The regulatory Community Multiscale Air Quality (CMAQ) model is a means to understanding the sources, concentrations and regulatory attainment of air pollutants within a model's domain. Substantial resources are allocated to the evaluation of model performance. The Regionalized Air quality Model Performance (RAMP) method introduced here explores novel ways of visualizing and evaluating CMAQ model performance and errors for daily Particulate Matter ≤ 2.5 micrometers (PM2.5) concentrations across the continental United States. The RAMP method performs a non-homogenous, non-linear, non-homoscedastic model performance evaluation at each CMAQ grid. This work demonstrates that CMAQ model performance, for a well-documented 2001 regulatory episode, is non-homogeneous across space/time. The RAMP correction of systematic errors outperforms other model evaluation methods as demonstrated by a 22.1% reduction in Mean Square Error compared to a constant domain wide correction. The RAMP method is able to accurately reproduce simulated performance with a correlation of r = 76.1%. Most of the error coming from CMAQ is random error with only a minority of error being systematic. Areas of high systematic error are collocated with areas of high random error, implying both error types originate from similar sources. Therefore, addressing underlying causes of systematic error will have the added benefit of also addressing underlying causes of random error.

The Effect of Lateral Boundary Values on Atmospheric Mercury Simulations with the CMAQ Model

EPA Science Inventory

Simulation results from three global-scale models of atmospheric mercury have been used to define three sets of initial condition and boundary condition (IC/BC) data for regional-scale model simulations over North America using the Community Multi-scale Air Quality (CMAQ) model. ...

Modeling and Measurements to Improve Bidirectional Exchange in CMAQ

EPA Science Inventory

Ammonia, NH3, is an emerging atmospheric pollutant of interest. It is an aerosol precursor and growing constituent of nitrogen deposition. In this presentation, the bidirectional exchange model for NH¬3 in the Community Multiscale Air Quality (CMAQ) model will be reviewed and...

ONE ATMOSPHERE MODELING FOR AIR QUALITY: BUILDING PARTNERSHIPS THAT TRANSITION RESEARCH INTO APPLICATIONS

EPA Science Inventory

The Community Miultiscale Air Quality (CMAQ) modeling system is a "one atmosphere" chemical transport model that simulates the transport and fate of air pollutants from urban to continental scales and from daily to annual time intervals.

“Application and evaluation of the two-way coupled WRF ...

EPA Pesticide Factsheets

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in urban areas using satellite, aircraft, vertical profiler and ground based measurements (http://discover-aq.larc.nasa.gov). In July 2011, the DISCOVER-AQ project conducted intensive air quality measurements in the Baltimore, MD and Washington, D.C. area in the eastern U.S. To take advantage of these unique data, the Community Multiscale Air Quality (CMAQ) model, coupled with the Weather Research and Forecasting (WRF) model is used to simulate the meteorology and air quality in the same region using 12-km, 4-km and 1-km horizontal grid spacings. The goal of the modeling exercise is to demonstrate the capability of the coupled WRF-CMAQ modeling system to simulate air quality at fine grid spacings in an urban area. Development of new data assimilation techniques and the use of higher resolution input data for the WRF model have been implemented to improve the meteorological results, particularly at the 4-km and 1-km grid resolutions. In addition, a number of updates to the CMAQ model were made to enhance the capability of the modeling system to accurately represent the magnitude and spatial distribution of pollutants at fine model resolutions. Data collected during the 2011 DISCOVER-AQ campa

NOAA's National Air Quality Prediction and Development of Aerosol and Atmospheric Composition Prediction Components for NGGPS

NASA Astrophysics Data System (ADS)

Stajner, I.; McQueen, J.; Lee, P.; Stein, A. F.; Wilczak, J. M.; Upadhayay, S.; daSilva, A.; Lu, C. H.; Grell, G. A.; Pierce, R. B.

2017-12-01

NOAA's operational air quality predictions of ozone, fine particulate matter (PM2.5) and wildfire smoke over the United States and airborne dust over the contiguous 48 states are distributed at http://airquality.weather.gov. The National Air Quality Forecast Capability (NAQFC) providing these predictions was updated in June 2017. Ozone and PM2.5 predictions are now produced using the system linking the Community Multiscale Air Quality model (CMAQ) version 5.0.2 with meteorological inputs from the North American Mesoscale Forecast System (NAM) version 4. Predictions of PM2.5 include intermittent dust emissions and wildfire emissions from an updated version of BlueSky system. For the latter, the CMAQ system is initialized by rerunning it over the previous 24 hours to include wildfire emissions at the time when they were observed from the satellites. Post processing to reduce the bias in PM2.5 prediction was updated using the Kalman filter analog (KFAN) technique. Dust related aerosol species at the CMAQ domain lateral boundaries now come from the NEMS Global Aerosol Component (NGAC) v2 predictions. Further development of NAQFC includes testing of CMAQ predictions to 72 hours, Canadian fire emissions data from Environment and Climate Change Canada (ECCC) and the KFAN technique to reduce bias in ozone predictions. NOAA is developing the Next Generation Global Predictions System (NGGPS) with an aerosol and gaseous atmospheric composition component to improve and integrate aerosol and ozone predictions and evaluate their impacts on physics, data assimilation and weather prediction. Efforts are underway to improve cloud microphysics, investigate aerosol effects and include representations of atmospheric composition of varying complexity into NGGPS: from the operational ozone parameterization, GOCART aerosols, with simplified ozone chemistry, to CMAQ chemistry with aerosol modules. We will present progress on community building, planning and development of NGGPS.

Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

AN AGGREGATION AND EPISODE SELECTION SCHEME FOR EPA'S MODELS-3 CMAQ

EPA Science Inventory

The development of an episode selection and aggregation approach, designed to support distributional estimation for use with the Models-3 Community Multiscale Air Quality (CMAQ) model, is described. The approach utilized cluster analysis of the 700 hPa u and v wind field compo...

EVALUATION TECHNIQUES AND TOOL DEVELOPMENT FOR FY 08 CMAQ RELEASE

EPA Science Inventory

In this task, research efforts are outlined that relate to the AMD Model Evaluation Program element and support CMAQ releases within the FY05-FY08 time period. Model evaluation serves dual purposes; evaluation is necessary to characterize the accuracy of model predictions, and e...

MODEL DEVELOPMENT AND TESTING FOR SEMI-VOLATILES (ATRAZINE)

EPA Science Inventory

The Community Multi-Scale Air Quality (CMAQ) model, air quality model within EPA's Models-3 system, can be adapted to simulate the fate of semi-volatile compounds that are emitted into the atmosphere. "Semi-volatile" refers to compounds that partition their mass between two ph...

Regional Background Fine Particulate Matter

EPA Science Inventory

A modeling system composed of the global model GEOS-Chem providing hourly lateral boundary conditions to the regional model CMAQ was used to calculate the policy relevant background level of fine particulate: matter. Simulations were performed for the full year of 2004 over the d...

AQMEII Phase 2: Overview and WRF/CMAQ Application over North America

EPA Science Inventory

In this study, we provide an overview of the second phase of the Air Quality Model Evaluation International Initiative (AQMEII). Activities in this phase are focused on the application and evaluation of coupled meteorologychemistry models. Participating modeling systems are being...

ESTABLISHMENT OF A COMMUNITY MODELING AND ANALYSIS SUPPORT MECHANISM

EPA Science Inventory

During the fall of 2001, a Cooperative Research Agreement between the U.S. Environmental Protection Agency and MCNC began a Community Modeling and Analysis System (CMAS) center. The CMAS will foster development, distribution, and use of the Models-3/CMAQ (Community Multiscale ...

Estimating the agricultural fertilizer NH3 emission in China based on the bi-directional CMAQ model and an agro-ecosystem model

NASA Astrophysics Data System (ADS)

Wang, S.

2014-12-01

Atmospheric ammonia (NH3) plays an important role in fine particle formation. Accurate estimates of ammonia can reduce uncertainties in air quality modeling. China is one of the largest countries emitting ammonia with the majority of NH3 emissions coming from the agricultural practices, such as fertilizer applications and animal operations. The current ammonia emission estimates in China are mainly based on pre-defined emission factors. Thus, there are considerable uncertainties in estimating NH3 emissions, especially in time and space distribution. For example, fertilizer applications vary in the date of application and amount by geographical regions and crop types. In this study, the NH3 emission from the agricultural fertilizer use in China of 2011 was estimated online by an agricultural fertilizer modeling system coupling a regional air-quality model and an agro-ecosystem model, which contains three main components 1) the Environmental Policy Integrated Climate (EPIC) model, 2) the meso-scale meteorology Weather Research and Forecasting (WRF) model and 3) the CMAQ air quality model with bi-directional ammonia fluxes. The EPIC output information about daily fertilizer application and soil characteristics would be the input of the CMAQ model. In order to run EPIC model, much Chinese local information is collected and processed. For example, Crop land data are computed from the MODIS land use data at 500-m resolution and crop categories at Chinese county level; the fertilizer use rate for different fertilizer types, crops and provinces are obtained from Chinese statistic materials. The system takes into consideration many influencing factors on agriculture ammonia emission, including weather, the fertilizer application method, timing, amount, and rate for specific pastures and crops. The simulated fertilizer data is compared with the NH3 emissions and fertilizer application data from other sources. The results of CMAQ modeling are also discussed and analyzed with field measurements. The estimated agricultural fertilizer NH3 emission in this study is about 3Tg in 2011. The regions with the highest emission rates are located in the North China Plain. Monthly, the peak ammonia emissions occur in April to July.

IMPACT OF AN UPDATED CARBON BOND MECHANISM ON PREDICTIONS FROM THE CMAQ MODELING SYSTEM: PRELIMINARY ASSESSMENT

EPA Science Inventory

An updated and expanded Carbon Bond mechanism (CB05) has been incorporated into the Community Multiscale Air Quality modeling system to more accurately simulate wintertime, pristine, and high altitude situations. The CB05 mechanism has nearly twice the number of reactions compare...

A Reduced Form Model for Ozone Based on Two Decades of CMAQ Simulations for the Continental United States

EPA Science Inventory

A Reduced Form Model (RFM) is a mathematical relationship between the inputs and outputs of an air quality model, permitting estimation of additional modeling without costly new regional-scale simulations. A 21-year Community Multiscale Air Quality (CMAQ) simulation for the con...

"Advances in Coupled Air Quality, Farm Management and ...

EPA Pesticide Factsheets

A cropland farm management modeling system for regional air quality and field-scale applications of bi-directional ammonia exchange was presented at ITM XXI. The goal of this research is to improve estimates of nitrogen deposition to terrestrial and aquatic ecosystems and ambient ammonium aerosol particle concentrations injurious to human health. These concepts have been implemented and have been released as options in CMAQ 5.01. This presentation will summarize the integration of these two models and will present model performance results relative to wet deposition measurements, ambient ammonium aerosol and ambient ammonia observations. Results indicate a shift in the timing of current U.S. agricultural emission inventories and improved CMAQ model performance. Comparison to annual wet deposition observations suggests remaining bias may be attributable primarily to precipitation model errors. Preliminary results of CMAQ deposition and ambient ammonia response to interannual variability in farm management activities will also be presented. The USEPA Office of Air and Radiation is currently considering the recommendation of the coupled model for use in standard setting activities and applications are being developed in collaboration with USEPA Office of Water and Regional Offices. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the envi

Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.1

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Modeling the Influence of Hemispheric Transport on Trends in O3 Distributions

EPA Science Inventory

We describe the development and application of the hemispheric version of the CMAQ to examine the influence of long-range pollutant transport on trends in surface level O3 distributions. The WRF-CMAQ model is expanded to hemispheric scales and multi-decadal model simulations were...

Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

EFFECTS OF VERTICAL-LAYER STRUCTURE AND BOUNDARY CONDITIONS ON CMAQ-V4.5 AND V4.6 MODELS

EPA Science Inventory

This work is aimed at determining whether the increased vertical layers in CMAQ provides substantially improved model performance and assess whether using the spatially and temporally varying boundary conditions from GEOS-CHEM offer improved model performance as compared to the d...

CMAQ MODELING FOR AIR TOXICS AT FINE SCALES: A PROTOTYPE STUDY

EPA Science Inventory

Toxic air pollutants (TAPs) or hazardous air pollutants (HAPs) exhibit considerable spatial and temporal variability across urban areas. Therefore, the ability of chemical transport models (CTMs), e.g. Community Multi-scale Air Quality (CMAQ), to reproduce the spatial and tempor...

THE 2006 CMAQ RELEASE AND PLANS FOR 2007

EPA Science Inventory

The 2006 release of the Community Multiscale Air Quality (CMAQ) model (Version 4.6) includes upgrades to several model components as well as new modules for gas-phase chemistry and boundary layer mixing. Capabilities for simulation of hazardous air pollutants have been expanded ...

A Comparison of Modeled Pollutant Profiles With MOZAIC Aircraft Measurements

EPA Science Inventory

In this study, we use measurements performed under the MOZAIC program to evaluate vertical profiles of meteorological parameters, CO, and ozone that were simulated for the year 2006 with several versions of the WRF/CMAQ modeling system. Model updates, including WRF nudging strate...

Development , Implementation and Evaluation of a Physics-Base Windblown Dust Emission Model

EPA Science Inventory

A physics-based windblown dust emission parametrization scheme is developed and implemented in the CMAQ modeling system. A distinct feature of the present model includes the incorporation of a newly developed, dynamic relation for the surface roughness length, which is important ...

Update of NOx emission temporal profiles using CMAQ-HDDM

NASA Astrophysics Data System (ADS)

Bae, C.; Lee, J. B.; Kim, H. C.; Kim, B. U.; Kim, S.

2017-12-01

This study demonstrates the impact of revised temporal profiles of NOx emissions on air quality simulations in the Seoul Metropolitan Area (SMA), South Korea. Air pollutants such as ozone and nitrogen oxides can be harmful to the human body even with short-term exposure. Since most of air quality models use predefined temporal profiles which are often outdated or taken from different chemical environment, providing accurate temporal variation of emissions are challenging in prediction of correct local air quality. Considering secondary formation of pollutants are important in mega cities and temporal variations of emissions are not coincident with those of resultant concentrations, we utilized CMAQ-HDDM to link emissions and consequential concentrations from different time steps. Base simulations were conducted using WRF, SMOKE, and CMAQ modeling frame using CREATE 2015 and CAPSS 2013 emissions inventories for East Asia and South Korea, respectively. With current modeling system, modeled NOx concentrations underestimate 4% in the daytime (10-16 LST), but overestimate 30% in the nighttime during May to August 2015. Applying revised temporal profiles based on HDDM sensitivities, model performance was improved significantly. We conclude that the proposed temporal allocation method can be useful to reduce the model-observation discrepancies when the activity data for emission sources are difficult to obtain with a bottom-up approach.

Toward verifying fossil fuel CO2 emissions with the CMAQ model: motivation, model description and initial simulation.

PubMed

Liu, Zhen; Bambha, Ray P; Pinto, Joseph P; Zeng, Tao; Boylan, Jim; Huang, Maoyi; Lei, Huimin; Zhao, Chun; Liu, Shishi; Mao, Jiafu; Schwalm, Christopher R; Shi, Xiaoying; Wei, Yaxing; Michelsen, Hope A

2014-04-01

Motivated by the question of whether and how a state-of-the-art regional chemical transport model (CTM) can facilitate characterization of CO2 spatiotemporal variability and verify CO2 fossil-fuel emissions, we for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate CO2. This paper presents methods, input data, and initial results for CO2 simulation using CMAQ over the contiguous United States in October 2007. Modeling experiments have been performed to understand the roles of fossil-fuel emissions, biosphere-atmosphere exchange, and meteorology in regulating the spatial distribution of CO2 near the surface over the contiguous United States. Three sets of net ecosystem exchange (NEE) fluxes were used as input to assess the impact of uncertainty of NEE on CO2 concentrations simulated by CMAQ. Observational data from six tall tower sites across the country were used to evaluate model performance. In particular, at the Boulder Atmospheric Observatory (BAO), a tall tower site that receives urban emissions from Denver CO, the CMAQ model using hourly varying, high-resolution CO2 fossil-fuel emissions from the Vulcan inventory and Carbon Tracker optimized NEE reproduced the observed diurnal profile of CO2 reasonably well but with a low bias in the early morning. The spatial distribution of CO2 was found to correlate with NO(x), SO2, and CO, because of their similar fossil-fuel emission sources and common transport processes. These initial results from CMAQ demonstrate the potential of using a regional CTM to help interpret CO2 observations and understand CO2 variability in space and time. The ability to simulate a full suite of air pollutants in CMAQ will also facilitate investigations of their use as tracers for CO2 source attribution. This work serves as a proof of concept and the foundation for more comprehensive examinations of CO2 spatiotemporal variability and various uncertainties in the future. Atmospheric CO2 has long been modeled and studied on continental to global scales to understand the global carbon cycle. This work demonstrates the potential of modeling and studying CO2 variability at fine spatiotemporal scales with CMAQ, which has been applied extensively, to study traditionally regulated air pollutants. The abundant observational records of these air pollutants and successful experience in studying and reducing their emissions may be useful for verifying CO2 emissions. Although there remains much more to further investigate, this work opens up a discussion on whether and how to study CO2 as an air pollutant.

Multiscale Modeling of Multi-Decadal Trends in Air Pollutant Concentrations & Radiative Properties: The Role of Models in an Integrated Observing System

EPA Science Inventory

EPA’s coupled WRF-CMAQ modeling system is applied over a domain encompassing the northern hemisphere for the period spanning 1990-2010. This period has witnessed significant reductions in anthropogenic emissions in North America and Europe as a result of implementation of c...

Community Multiscale Air Quality Model

EPA Science Inventory

The U.S. EPA developed the Community Multiscale Air Quality (CMAQ) system to apply a “one atmosphere” multiscale and multi-pollutant modeling approach based mainly on the “first principles” description of the atmosphere. The multiscale capability is supported by the governing di...

FIRST RESULTS FROM OPERATIONAL TESTING OF THE U.S. EPA MODELS-3 COMMUNITY MULTISCALE MODEL FOR AIR QUALITY (CMAQ)

EPA Science Inventory

The Models 3 / Community Multiscale Model for Air Quality (CMAQ) has been designed for one-atmosphere assessments for multiple pollutants including ozone (O3), particulate matter (PM10, PM2.5), and acid / nutrient deposition. In this paper we report initial results of our evalu...

EVALUATION OF THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL VERSION 4.5: UNCERTAINTIES AND SENSITIVITIES IMPACTING MODEL PERFORMANCE: PART I - OZONE

EPA Science Inventory

This study examines ozone (O₃) predictions from the Community Multiscale Air Quality (CMAQ) model version 4.5 and discusses potential factors influencing the model results. Daily maximum 8-hr average O₃ levels are largely underpredicted when observed O_...

On the Use of Principal Component and Spectral Density Analysis to Evaluate the Community Multiscale Air Quality (CMAQ) Model

EPA Science Inventory

A 5 year (2002-2006) simulation of CMAQ covering the eastern United States is evaluated using principle component analysis in order to identify and characterize statistically significant patterns of model bias. Such analysis is useful in that in can identify areas of poor model ...

Verification of CMAQ modeling with Discover-AQ campaigns against measurements and efficacy of emission inversion modeling

NASA Astrophysics Data System (ADS)

Lee, P.; Tang, Y.; Pan, L.; Szykman, J.; Plessel, T.; Tong, D.; Liu, Q.

2015-12-01

NASA has led a few DISCOVER-AQ campaigns in recent years: (1) Baltimore/Washington in July 2011, (2) Central valley, CA in January - February 2013, (3) Houston, TX in September 2013, and co-led with NCAR (4) Front Range, CO in July - August 2014. NOAA Air Resources Laboratory has participated in all these campaigns in the role of air quality forecasting support. For some of these campaigns post analyses were performed with the possible help of after-the-fact observed data from satellite retrieved radiances to constrain emissions through the Community Radiative Transfer Model (CRTM) developed at the Joint Center for Satellite Data Assimilation. It is our experience that despite the vastly different chemical regime, season, terrain, and meteorological conditions of the domain for the campaigns, we found that the emissions input and the U.S. EPA Community Air Quality model (CMAQ), the forecasting chemical transport model used to generate the forecast had severely under-estimated formaldehyde (HCHO), and carbon monoxide (CO) aloft between surface and the middle of the free troposphere - 500 hPa. Post analyses point to two strong suspects of these deficiencies: (a) emission projection fed into CMAQ, and/or (b) erroneously fast removal of the species. We investigate both of these potential deficiencies and for the former possible reason we looked into data assimilation and possible inverse modeling to adjust emission projection for CMAQ. We will elaborate more on the CRTM which plays a critical role in this aspect of remedying erroneous inputs to CMAQ. In addition, we will utilize some satellite products to improve initial fields of aerosols and CO for air quality forecasting. Suomi NPP VIIRS aerosol optical depth (AOD) environmental data record (EDR) delivers global aerosol information daily. The Unique CrIS/ATMS Processing System (NUCAPS) operationally generates vertical profiles of atmospheric carbonate EDRs (CO, CO2, and CH4) and ozone during day and night. The AOD can be assimilated by using the CRTM. The carbonate EDRs and ozone EDR can be directly assimilated.

A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

EPA Science Inventory

This paper discusses a framework for fine-scale CFD modeling that may be developed to complement the present Community Multi-scale Air Quality (CMAQ) modeling system which itself is a computational fluid dynamics model. A goal of this presentation is to stimulate discussions on w...

PARADIGM USING JOINT DETERMINISTIC GRID MODELING AND SUB-GRID VARIABILITY STOCHASTIC DESCRIPTION AS A TEMPLATE FOR MODEL EVALUATION

EPA Science Inventory

The goal of achieving verisimilitude of air quality simulations to observations is problematic. Chemical transport models such as the Community Multi-Scale Air Quality (CMAQ) modeling system produce volume averages of pollutant concentration fields. When grid sizes are such tha...

Probabilistic Predictions of PM2.5 Using a Novel Ensemble Design for the NAQFC

NASA Astrophysics Data System (ADS)

Kumar, R.; Lee, J. A.; Delle Monache, L.; Alessandrini, S.; Lee, P.

2017-12-01

Poor air quality (AQ) in the U.S. is estimated to cause about 60,000 premature deaths with costs of 100B-150B annually. To reduce such losses, the National AQ Forecasting Capability (NAQFC) at the National Oceanic and Atmospheric Administration (NOAA) produces forecasts of ozone, particulate matter less than 2.5 mm in diameter (PM2.5), and other pollutants so that advance notice and warning can be issued to help individuals and communities limit the exposure and reduce air pollution-caused health problems. The current NAQFC, based on the U.S. Environmental Protection Agency Community Multi-scale AQ (CMAQ) modeling system, provides only deterministic AQ forecasts and does not quantify the uncertainty associated with the predictions, which could be large due to the chaotic nature of atmosphere and nonlinearity in atmospheric chemistry. This project aims to take NAQFC a step further in the direction of probabilistic AQ prediction by exploring and quantifying the potential value of ensemble predictions of PM2.5, and perturbing three key aspects of PM2.5 modeling: the meteorology, emissions, and CMAQ secondary organic aerosol formulation. This presentation focuses on the impact of meteorological variability, which is represented by three members of NOAA's Short-Range Ensemble Forecast (SREF) system that were down-selected by hierarchical cluster analysis. These three SREF members provide the physics configurations and initial/boundary conditions for the Weather Research and Forecasting (WRF) model runs that generate required output variables for driving CMAQ that are missing in operational SREF output. We conducted WRF runs for Jan, Apr, Jul, and Oct 2016 to capture seasonal changes in meteorology. Estimated emissions of trace gases and aerosols via the Sparse Matrix Operator Kernel (SMOKE) system were developed using the WRF output. WRF and SMOKE output drive a 3-member CMAQ mini-ensemble of once-daily, 48-h PM2.5 forecasts for the same four months. The CMAQ mini-ensemble is evaluated against both observations and the current operational deterministic NAQFC products, and analyzed to assess the impact of meteorological biases on PM2.5 variability. Quantification of the PM2.5 prediction uncertainty will prove a key factor to support cost-effective decision-making while protecting public health.

VERIFICATION OF SURFACE LAYER OZONE FORECASTS IN THE NOAA/EPA AIR QUALITY FORECAST SYSTEM IN DIFFERENT REGIONS UNDER DIFFERENT SYNOPTIC SCENARIOS

EPA Science Inventory

An air quality forecast (AQF) system has been established at NOAA/NCEP since 2003 as a collaborative effort of NOAA and EPA. The system is based on NCEP's Eta mesoscale meteorological model and EPA's CMAQ air quality model (Davidson et al, 2004). The vision behind this system is ...

Application and Evaluation of MODIS LAI, fPAR, and Albedo Products in the WRFCMAQ System

EPA Science Inventory

Leaf area index (LAI), vegetation fraction (VF), and surface albedo are important parameters in the land surface model (LSM) for meteorology and air quality modeling systems such as WRF/CMAQ. LAI and VF control not only leaf to canopy level evapotranspiration flux scaling but al...

The WRF-CMAQ Integrated On-Line Modeling System: Development, Testing, and Initial Applications

EPA Science Inventory

Traditionally, atmospheric chemistry-transport and meteorology models have been applied in an off-line paradigm, in which archived output on the dynamical state of the atmosphere simulated using the meteorology model is used to drive transport and chemistry calculations of atmos...

MODELING THE FORMATION OF SECONDARY ORGANIC AEROSOL WITHIN A COMPREHENSIVE AIR QUALITY MODEL SYSTEM

EPA Science Inventory

The aerosol component of the CMAQ model is designed to be an efficient and economical depiction of aerosol dynamics in the atmosphere. The approach taken represents the particle size distribution as the superposition of three lognormal subdistributions, called modes. The proces...

Representing the Effects of Long-Range Transport and Lateral Boundary Conditions in Regional Air Pollution Models

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) modeling system was applied to a domain covering the northern hemisphere; meteorological information was derived from the Weather Research and Forecasting (WRF) model run on identical grid and projection configuration, while the emissio...

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model

EPA Science Inventory

Sea spray aerosols (SSA) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. In this study, the Community Multiscale Air Quality (CMAQ) model is updated to enhance fine mode SSA emissions,...

USING CMAQ FOR EXPOSURE MODELING AND CHARACTERIZING THE SUB-GRID VARIABILITY FOR EXPOSURE ESTIMATES

EPA Science Inventory

Atmospheric processes and the associated transport and dispersion of atmospheric pollutants are known to be highly variable in time and space. Current air quality models that characterize atmospheric chemistry effects, e.g. the Community Multi-scale Air Quality (CMAQ), provide vo...

Cloud processing of gases and aerosols in the Community Multiscale Air Quality (CMAQ) model: Impacts of extended chemistry

EPA Science Inventory

Clouds and fogs can significantly impact the concentration and distribution of atmospheric gases and aerosols through chemistry, scavenging, and transport. This presentation summarizes the representation of cloud processes in the Community Multiscale Air Quality (CMAQ) modeling ...

Final Report: Fourth Peer Review of the CMAQ Model

EPA Science Inventory

The CMAQ Model External Peer Review Panel conducted a two and a half day review view on June 27, 28, and 29, 2011. This report summarizes its findings, and follows other reviews conducted in 2004, 2005, and 2006 [Amar et al., 2004; 2005 and 2007].

INTERDEPENDENCIES OF MULTI-POLLUTANT CONTROL SIMULATIONS IN AN AIR QUALITY MODEL

EPA Science Inventory

In this work, we use the Community Multi-Scale Air Quality (CMAQ) modeling system to examine the effect of several control strategies on simultaneous concentrations of ozone, PM_2.5, and three important HAPs: formaldehyde, acetaldehyde and benzene.

Recent Advances in WRF Modeling for Air Quality Applications

EPA Science Inventory

The USEPA uses WRF in conjunction with the Community Multiscale Air Quality (CMAQ) for air quality regulation and research. Over the years we have added physics options and geophysical datasets to the WRF system to enhance model capabilities especially for extended retrospective...

Sensitivity of the Community Multiscale Air Quality (CMAQ) Model v4.7 Results for the Eastern United States to MM5 and WRF Meteorological Drivers

EPA Science Inventory

This paper presents a comparison of the operational performance of two Community Multiscale Air Quality (CMAQ) model v4.7 simulations that utilize input data from the 5th generation Mesoscale Model MM5 and the Weather Research and Forecasting (WRF) meteorological models.

Validation of the WRF-CMAQ Two-Way Model with Aircraft Data and High Resolution MODIS Data in the CA 2008 Wildfire Case

EPA Science Inventory

A new WRF-CMAQ two-way coupled model was developed to provide a pathway for chemical feedbacks from the air quality model to the meteorological model. The essence of this interaction is focused on the direct radiative effects of scattering and absorbing aerosols in the tropospher...

Dynamic evaluation of CMAQ part I: Separating the effects of ...

EPA Pesticide Factsheets

A dynamic evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.1 was conducted to evaluate the model's ability to predict changes in ozone levels between 2002 and 2005, a time period characterized by emission reductions associated with the EPA's Nitrogen Oxides State Implementation Plan as well as significant reductions in mobile source emissions. Model results for the summers of 2002 and 2005 were compared to simulations from a previous version of CMAQ to assess the impact of model updates on predicted pollutant response. Changes to the model treatment of emissions, meteorology and chemistry had substantial impacts on the simulated ozone concentrations. While the median bias for high summertime ozone decreased in both years compared to previous simulations, the observed decrease in ozone from 2002 to 2005 in the eastern US continued to be underestimated by the model. Additional “cross” simulations were used to decompose the model predicted change in ozone into the change due to emissions, the change due to meteorology and any remaining change not explained individually by these two components. The decomposition showed that the emission controls led to a decrease in modeled high summertime ozone close to twice as large as the decrease attributable to changes in meteorology alone. Quantifying the impact of retrospective emission controls by removing the impacts of meteorology during the control period can be a valuable approac

Estimating the deposition of urban atmospheric NO2 to the urban forest in Portland-Vancouver USA

NASA Astrophysics Data System (ADS)

Rao, M.; Gonzalez Abraham, R.; George, L. A.

2016-12-01

Cities are hotspots of atmospheric emissions of reactive nitrogen oxides, including nitrogen dioxide (NO2), a US EPA criteria pollutant that affects both human and environmental health. A fraction of this anthropogenic, atmospheric NO2 is deposited onto the urban forest, potentially mitigating the impact of NO2 on respiratory health within cities. However, the role of the urban forest in removal of atmospheric NO2 through deposition has not been well studied. Here, using an observationally-based statistical model, we first estimate the reduction of NO2 associated with the urban forest in Portland-Vancouver, USA, and the health benefits accruing from this reduction. In order to assess if this statistically observed reduction in NO2 associated with the urban forest is consistent with deposition, we then compare the amount of NO2 removed through deposition to the urban forest as estimated using a 4km CMAQ simulation. We further undertake a sensitivity analysis in CMAQ to estimate the range of NO2removed as a function of bulk stomatal resistance. We find that NO2 deposition estimated by CMAQ accounts for roughly one-third of the reduction in NO2 shown by the observationally-based statistical model (Figure). Our sensitivity analysis shows that a 3-10 fold increase in the bulk stomatal resistance parameter in CMAQ would align CMAQ-estimated deposition with the statistical model. The reduction of NO2 by the urban forest in the Portland-Vancouver area may yield a health benefit of at least $1.5 million USD annually, providing strong motivation to better understand the mechanism through which the urban forest may be removing air pollutants such as NO2and thus helping create healthier urban atmospheres. Figure: Comparing the amount of NO2 deposition as estimated by CMAQ and the observationally-based statistical model (LURF). Each point corresponds to a single 4 x 4km CMAQ grid cell.

SENSITIVITY OF THE CMAQ MERCURY MODEL TO GAS-PHASE OXIDATION CHEMISTRY

EPA Science Inventory

Simulations of the Community Multi-scale Air Quality (CMAQ) model for mercury have shown the vast majority of the mercury deposited in the United States to be in the form of oxidized mercury. However, most of this simulated oxidized mercury was the result of atmospheric oxidatio...

AN ANNUAL EVALUATION OF THE 2005 RELEASE OF MODELS-3 CMAQ

EPA Science Inventory

An annual operation performance evaluation of the 2005 release of Models-3 CMAQ v4.5 has been performed. The poster presented results from the winter and summer season for sulfate, nitrate, ammonium, elemental carbon, organic carbon, PM2.5 mass and AQS 8-hr maximum ozone. Stati...

“Assessment of the two-way Coupled WRF-CMAQ Model with Observations from the CARES”

EPA Science Inventory

The main goal of this assessment is to evaluate the improved aerosol component of two-way coupled WRF-CMAQ model particularly in representing aerosol physical and optical properties by utilizing observations from the Carbonaceous Aerosol and Radiative Effects Study (CARES) in May...

IMPLEMENTATION OF AN URBAN CANOPY PARAMETERIZATION IN MM5 FOR MESO-GAMMA-SCALE AIR QUALITY MODELING APPLICATIONS

EPA Science Inventory

The U.S. Environmental Protection Agency (U.S. EPA) is extending its Models-3/Community Multiscale Air Quality (CMAQ) Modeling System to provide detailed gridded air quality concentration fields and sub-grid variability characterization at neighborhood scales and in urban areas...

Towards the Next Generation Air Quality Modeling System: Current Progress on Implementing Chemistry into MPAS-A

EPA Science Inventory

The community multiscale air quality (CMAQ) model of the U.S. Environmental Protection Agency is one of the most widely used air quality model worldwide; it is employed for both research and regulatory applications at major universities and government agencies for improving under...

The NASA Lightning Nitrogen Oxides Model (LNOM): Recent Updates and Applications

NASA Technical Reports Server (NTRS)

Koshak, William; Peterson, Harold; Biazar, Arastoo; Khan, Maudood; Wang, Lihua; Park, Yee-Hun

2011-01-01

Improvements to the NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) and its application to the Community Multiscale Air Quality (CMAQ) modeling system are presented. The LNOM analyzes Lightning Mapping Array (LMA) and National Lightning Detection Network(tm) (NLDN) data to estimate the raw (i.e., unmixed and otherwise environmentally unmodified) vertical profile of lightning NOx (= NO + NO2). Lightning channel length distributions and lightning 10-m segment altitude distributions are also provided. In addition to NOx production from lightning return strokes, the LNOM now includes non-return stroke lightning NOx production due to: hot core stepped and dart leaders, stepped leader corona sheath, K-changes, continuing currents, and M-components. The impact of including LNOM-estimates of lightning NOx for an August 2006 run of CMAQ is discussed.

A PERFORMANCE EVALUATION OF THE ETA- CMAQ AIR QUALITY FORECAST SYSTEM FOR THE SUMMER OF 2005

EPA Science Inventory

This poster presents an evaluation of the Eta-CMAQ Air Quality Forecast System's experimental domain using O₃ observations obtained from EPA's AIRNOW program and a suite of statistical metrics examining both discrete and categorical forecasts.

DEVELOPMENT AND ANALYSIS OF AIR QUALITY MODELING SIMULATIONS FOR HAZARDOUS AIR POLLUTANTS

EPA Science Inventory

The concentrations of five hazardous air pollutants were simulated using the Community Multi Scale Air Quality (CMAQ) modeling system. Annual simulations were performed over the continental United States for the entire year of 2001 to support human exposure estimates. Results a...

Characterizing the Influence of Hemispheric Transport on Regional Air Pollution

EPA Science Inventory

Expansion of the coupled WRF-CMAQ modeling system to hemispheric scales is pursued to enable the development of a robust modeling framework in which the interactions between atmospheric processes occurring at various spatial and temporal scales can be examined in a consistent man...

Examining Air Quality-Meteorology Interactions on Regional to Hemispheric Scales

EPA Science Inventory

This presentation provides motivation for coupling the atmospheric dynamics and chemistry calculations in air pollution modeling systems, provides an overview of how this coupling is achieved in the WRF-CMAQ 2-way coupled model, presents results from various applications of the m...

LARGE-SCALE PREDICTIONS OF MOBILE SOURCE CONTRIBUTIONS TO CONCENTRATIONS OF TOXIC AIR POLLUTANTS

EPA Science Inventory

This presentation shows concentrations and deposition of toxic air pollutants predicted by a 3-D air quality model, the Community Multi Scale Air Quality (CMAQ) modeling system. Contributions from both on-road and non-road mobile sources are analyzed.

MODELING AIR TOXICS AND PM 2.5 CONCENTRATION FIELDS AS A MEANS FOR FACILITATING HUMAN EXPOSURE ASSESSMENTS

EPA Science Inventory

The capability of the US EPA Models-3/Community Multiscale Air Quality (CMAQ) modeling system is extended to provide gridded ambient air quality concentration fields at fine scales. These fields will drive human exposure to air toxics and fine particulate matter (PM2.5) models...

CMAQ Application to the Southern Oxidant and Aerosol Study (SOAS)

EPA Pesticide Factsheets

CMAQ was used to simulate conditions during the the Southern Oxidant and Aerosol Study (SOAS) in the summer of 2013. Data collected as part of this study have been used to perform diagnostic model evaluation.

Moving Towards Air Quality Models with Chemistry Linked to the Master Chemical Mechanism: CRI Performance in U.S. Regional Models

EPA Science Inventory

This presentation described implementation of the Common Representative Intermediate (CRI) atmospheric chemistry in CMAQ, a short analysis of its performance in CMAQ relative to other mechanisms and an example of the additional detail it gives us for understanding atmospheric che...

Statistical Properties of Differences between Low and High Resolution CMAQ Runs with Matched Initial and Boundary Conditions

EPA Science Inventory

The difficulty in assessing errors in numerical models of air quality is a major obstacle to improving their ability to predict and retrospectively map air quality. In this paper, using simulation outputs from the Community Multi-scale Air Quality Model (CMAQ), the statistic...

Correlation Between Hierarchical Bayesian and Aerosol Optical Depth PM2.5 Data and Respiratory-Cardiovascular Chronic Diseases

EPA Science Inventory

Tools to estimate PM2.5 mass have expanded in recent years, and now include: 1) stationary monitor readings, 2) Community Multi-Scale Air Quality (CMAQ) model estimates, 3) Hierarchical Bayesian (HB) estimates from combined stationary monitor readings and CMAQ model output; and, ...

Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States (2017 CMAS)

EPA Science Inventory

Weather Research and Forecasting (WRF)–Community Multi-scale Air Quality (CMAQ) model over the contiguous United States is conducted to assess how well the changes in observed ozone air quality are simulated by the model. The changes induced by variations in meteorology and...

CHANGES TO THE CHEMICAL MECHANISMS FOR HAZARDOUS AIR POLLUTANTS IN CMAQ VERSION 4.6

EPA Science Inventory

The extended abstract describes a presentation to the 2006 conference of the Community Modeling and Analysis System. The presentation introduces two new mechanisms for the atmospheric photochemistry of Hazardous Air Pollutants (HAPs) to be used in regional air quality models. It ...

15th Anniversary of CMAS

EPA Pesticide Factsheets

The EPA recently celebrated the 15th anniversary of its partnership with the Community Modeling and Analysis System (CMAS) Center. CMAS provides training and support for the CMAQ community, and they host an annual workshop dedicated to exchanging ideas.

"Updates to Model Algorithms & Inputs for the Biogenic Emissions Inventory System (BEIS) Model"

EPA Science Inventory

We have developed new canopy emission algorithms and land use data for BEIS. Simulations with BEIS v3.4 and these updates in CMAQ v5.0.2 are compared these changes to the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and evaluated the simulations against observatio...

Development of an Agricultural Fertilizer Modeling System for Bi-Directional Ammonia Fluxes in the Community Multiscale Air Quality (CMAQ) Model

EPA Science Inventory

Atmospheric ammonia (NH₃) plays an important role in fine-mode aerosol formation. Accurate estimates of ammonia from both human and natural emissions can reduce uncertainties in air quality modeling. The majority of ammonia anthropogenic emissions come from the agricul...

Multiscale Modeling of Multi-decadal Trends in Ozone and Precursor Species Across the Northern Hemisphere and the United States

EPA Science Inventory

Multi-decadal model calculations for the 1990-2010 period are performed with the coupled WRF-CMAQ modeling system over a domain encompassing the northern hemisphere and a nested domain over the continental U.S. Simulated trends in ozone and precursor species concentrations acros...

Development and evaluation of a physics-based windblown ...

EPA Pesticide Factsheets

A new windblown dust emission treatment was incorporated in the Community Multiscale Air Quality (CMAQ) modeling system. This new model treatment has been built upon previously developed physics-based parameterization schemes from the literature. A distinct and novel feature of this scheme, however, is the incorporation of a newly developed dynamic relation for the surface roughness length relevant to small-scale dust generation processes. Through this implementation, the effect of nonerodible elements on the local flow acceleration, drag partitioning, and surface coverage protection is modeled in a physically based and consistent manner. Careful attention is paid in integrating the new windblown dust treatment in the CMAQ model to ensure that the required input parameters are correctly configured. To test the performance of the new dust module in CMAQ, the entire year 2011 is simulated for the continental United States, with particular emphasis on the southwestern United States (SWUS) where windblown dust concentrations are relatively large. Overall, the model shows good performance with the daily mean bias of soil concentrations fluctuating in the range of ±1 µg m−3 for the entire year. Springtime soil concentrations are in quite good agreement (normalized mean bias of 8.3%) with observations, while moderate to high underestimation of soil concentration is seen in the summertime. The latter is attributed to the issue of representing the convective dust sto

DIAGNOSTIC EVALUATION OF NUMBERICAL AIR QUALITY MODELS WITH SPECIALIZED AMBIENT OBSERVATIONS: TESTING THE COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (CMAQ) AT SELECTED SOS 95 GROUND SITES

EPA Science Inventory

Three probes for diagnosing photochemical dynamics are presented and applied to specialized ambient surface-level observations and to a numerical photochemical model to better understand rates of production and other process information in the atmosphere and in the model. Howeve...

Implementing subgrid-scale cloudiness into the Model for Prediction Across Scales-Atmosphere (MPAS-A) for next generation global air quality modeling

EPA Science Inventory

A next generation air quality modeling system is being developed at the U.S. EPA to enable seamless modeling of air quality from global to regional to (eventually) local scales. State of the science chemistry and aerosol modules from the Community Multiscale Air Quality (CMAQ) mo...

A COMPARISON OF CMAQ-BASED AEROSOL PROPERTIES WITH IMPROVE, MODIS, AND AERONET DATA

EPA Science Inventory

We compare select aerosol Properties derived from the Community Multiscale Air Quality (CMAQ) model-simulated aerosol mass concentrations with routine data from the National Aeronautics and Space Administration (NASA) satellite-borne Moderate Resolution Imaging Spectro-radiometer...

Comparison of Spatial and Temporal Rainfall Characteristics in WRF-Simulated Precipitation to Gauge and Radar Observations

EPA Science Inventory

Weather Research and Forecasting (WRF) meteorological data are used for USEPA multimedia air and water quality modeling applications, within the CMAQ modeling system to estimate wet deposition and to evaluate future climate and land-use scenarios. While it is not expected that hi...

Incorporating Lightning Flash Data into the WRF-CMAQ Modeling System: Algorithms and Evaluations

EPA Science Inventory

We describe the use of lightning flash data from the National Lightning Detection Network (NLDN) to constrain and improve the performance of coupled meteorology-chemistry models. We recently implemented a scheme in which lightning data is used to control the triggering of conve...

The NASA Lightning Nitrogen Oxides Model (LNOM): Application to Air Quality Modeling

NASA Technical Reports Server (NTRS)

Koshak, William; Peterson, Harold; Khan, Maudood; Biazar, Arastoo; Wang, Lihua

2011-01-01

Recent improvements to the NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) and its application to the Community Multiscale Air Quality (CMAQ) modeling system are discussed. The LNOM analyzes Lightning Mapping Array (LMA) and National Lightning Detection Network(TradeMark)(NLDN) data to estimate the raw (i.e., unmixed and otherwise environmentally unmodified) vertical profile of lightning NO(x) (= NO + NO2). The latest LNOM estimates of lightning channel length distributions, lightning 1-m segment altitude distributions, and the vertical profile of lightning NO(x) are presented. The primary improvement to the LNOM is the inclusion of non-return stroke lightning NOx production due to: (1) hot core stepped and dart leaders, (2) stepped leader corona sheath, K-changes, continuing currents, and M-components. The impact of including LNOM-estimates of lightning NO(x) for an August 2006 run of CMAQ is discussed.

Toward Verifying Fossil Fuel CO2 Emissions with the CMAQ Model: Motivation, Model Description and Initial Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Zhen; Bambha, Ray P.; Pinto, Joseph P.

2014-03-14

Motivated by the urgent need for emission verification of CO2 and other greenhouse gases, we have developed regional CO2 simulation with CMAQ over the contiguous U.S. Model sensitivity experiments have been performed using three different sets of inputs for net ecosystem exchange (NEE) and two fossil fuel emission inventories, to understand the roles of fossil fuel emissions, atmosphere-biosphere exchange and transport in regulating the spatial and diurnal variability of CO2 near the surface, and to characterize the well-known ‘signal-to-noise’ problem, i.e. the interference from the biosphere on the interpretation of atmospheric CO2 observations. It is found that differences in themore » meteorological conditions for different urban areas strongly contribute to the contrast in concentrations. The uncertainty of NEE, as measured by the difference among the three different NEE inputs, has notable impact on regional distribution of CO2 simulated by CMAQ. Larger NEE uncertainty and impact are found over eastern U.S. urban areas than along the western coast. A comparison with tower CO2 measurements at Boulder Atmospheric Observatory (BAO) shows that the CMAQ model using hourly varied and high-resolution CO2 emission from the Vulcan inventory and CarbonTracker optimized NEE reasonably reproduce the observed diurnal profile, whereas switching to different NEE inputs significantly degrades the model performance. Spatial distribution of CO2 is found to correlate with NOx, SO2 and CO, due to their similarity in emission sources and transport processes. These initial results from CMAQ demonstrate the power of a state-of-the art CTM in helping interpret CO2 observations and verify fossil fuel emissions. The ability to simulate CO2 in CMAQ will also facilitate investigations of the utility of traditionally regulated pollutants and other species as tracers to CO2 source attribution.« less

Organic aerosol sources an partitioning in CMAQv5.2

EPA Science Inventory

We describe a major CMAQ update, available in version 5.2, which explicitly treats the semivolatile mass transfer of primary organic aerosol compounds, in agreement with available field and laboratory observations. Until this model release, CMAQ has considered these compounds to ...

A PERFORMANCE EVALUATION OF THE 2004 RELEASE OF MODELS-3 CMAQ

EPA Science Inventory

This performance evaluation compares a full annual simulation (2001) of CMAQ (Version4.4) covering the contiguous United States against monitoring data from four nationwide networks. This effort, which represents one of the most spatially and temporally comprehensive performance...

A photosynthesis-based two-leaf canopy stomatal conductance model for meteorology and air quality modeling with WRF/CMAQ PX LSM

NASA Astrophysics Data System (ADS)

Ran, Limei; Pleim, Jonathan; Song, Conghe; Band, Larry; Walker, John T.; Binkowski, Francis S.

2017-02-01

A coupled photosynthesis-stomatal conductance model with single-layer sunlit and shaded leaf canopy scaling is implemented and evaluated in a diagnostic box model with the Pleim-Xiu land surface model (PX LSM) and ozone deposition model components taken directly from the meteorology and air quality modeling system - WRF/CMAQ (Weather Research and Forecast model and Community Multiscale Air Quality model). The photosynthesis-based model for PX LSM (PX PSN) is evaluated at a FLUXNET site for implementation against different parameterizations and the current PX LSM approach with a simple Jarvis function (PX Jarvis). Latent heat flux (LH) from PX PSN is further evaluated at five FLUXNET sites with different vegetation types and landscape characteristics. Simulated ozone deposition and flux from PX PSN are evaluated at one of the sites with ozone flux measurements. Overall, the PX PSN simulates LH as well as the PX Jarvis approach. The PX PSN, however, shows distinct advantages over the PX Jarvis approach for grassland that likely result from its treatment of C3 and C4 plants for CO2 assimilation. Simulations using Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) rather than LAI measured at each site assess how the model would perform with grid averaged data used in WRF/CMAQ. MODIS LAI estimates degrade model performance at all sites but one site having exceptionally old and tall trees. Ozone deposition velocity and ozone flux along with LH are simulated especially well by the PX PSN compared to significant overestimation by the PX Jarvis for a grassland site.

Vegetation Exposure to Ozone over the Continental United States: Assessment of Exposure Indices by the Eta-CMAQ Air Quality Forecast Model

EPA Science Inventory

This study presents the first evaluation of the performance of the Eta-CMAQ air quality forecast model to predict a variety of widely used seasonal mean and cumulative O₃ exposure indices associated with vegetation using the U.S. AIRNow O₃ observations.

A STUDY OF PROCESS CONTRIBUTIONS TO OZONE FORMATION DURING THE 2004 ICARTT PERIOD USING THE ETA-CMAQ FORECAST MODEL OVER THE NORTHEASTERN U.S.

EPA Science Inventory

First, this study evaluates the Eta-CMAQ forecast model performances for O₃, and related chemical species with the observational data from the aircraft (NOAA P-3 and NASA DC-8) flights, Lidar and ozonesonde during the 2004 International Consortium for Atmospheric Resea...

A STUDY OF PROCESS CONTRIBUTIONS TO OZONE FORMATION DURING THE 2004 ICARTT PERIOD USING THE ETA- CMAQ FORECAST MODEL OVER THE NORTHEASTERN U.S.

EPA Science Inventory

First, this study evaluates the Eta-CMAQ forecast model performances for O₃, and related chemical species with the observational data from the aircraft (NOAA P-3 and NASA DC-8) flights, Lidar and ozonesonde during the 2004 International Consortium for Atmospheric Resea...

Comparative Evaluation of the Impact of WRF-NMM and WRF-ARW Meteorology on CMAQ Simulations for O3 and Related Species During the 2006 TexAQS/GoMACCS Campaign

EPA Science Inventory

In this paper, impact of meteorology derived from the Weather, Research and Forecasting (WRF)– Non–hydrostatic Mesoscale Model (NMM) and WRF–Advanced Research WRF (ARW) meteorological models on the Community Multiscale Air Quality (CMAQ) simulations for ozone and its related prec...

AN OPERATIONAL EVALUATION OF THE ETA - CMAQ AIR QUALITY FORECAST MODEL

EPA Science Inventory

The National Oceanic and Atmospheric Administration (NOAA), in partnership with the United States Environmental Protection Agency (EPA), are developing an operational, nationwide Air Quality Forecasting (AQF) system. An experimental phase of this program, which couples NOAA's Et...

AN OPERATIONAL EVALUATION OF THE ETA-CMAQ AIR QUALITY FORECAST MODEL

EPA Science Inventory

The National Oceanic and Atmospheric Administration (NOAA), in collaboration with the Environmental Protection Agency (EPA), are developing an Air Quality Forecasting Program that will eventually result in an operational Nationwide Air Quality Forecasting System. The initial pha...

Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin

PubMed Central

Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

2017-01-01

Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency’s model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes. PMID:29162976

Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin.

PubMed

Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

2017-01-01

Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency's model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes.

TESTING PHYSICS AND CHEMISTRY SENSITIVITIES IN THE U.S. EPA COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (CMAQ)

EPA Science Inventory

Uncertainties in key elements of emissions and meteorology inputs to air quality models (AQMs) can range from 50 to 100% with some areas of emissions uncertainty even higher (Russell and Dennis, 2000). Uncertainties in the chemical mechanisms are thought to be smaller (Russell an...

Real-Time Bias-Adjusted O3 and PM2.5 Air Quality Index Forecasts and their Performance Evaluations over the Continental United States

EPA Science Inventory

The National Air Quality Forecast Capacity (NAQFC) system, which links NOAA's North American Mesoscale (NAM) meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, provided operational ozone (O₃) and experimental fine particular matter (PM_2...

Examining the Impact of Nitrous Acid Chemistry on Ozone and PM over the Pearl River Delta Region

EPA Science Inventory

The impact of nitrous acid (HONO) chemistry on regional ozone and particulate matter in Pearl River Delta region was investigated using the community multiscale air quality (CMAQ) modeling system and the CB05 mechanism. Model simulations were conducted for a ten-day period in Oct...

Introducing Subgrid-scale convective cloud and aerosol interactions to the WRF-CMAQ integrated modeling system

EPA Science Inventory

Many regional and global climate models include aerosol indirect effects (AIE) on grid-scale/resolved clouds. However, the interaction between aerosols and convective clouds remains highly uncertain, as noted in the IPCC AR4 report. The objective of this work is to help fill in ...

Modeling of air pollutant removal by dry deposition to urban trees using a WRF/CMAQ/i-Tree Eco coupled system

Treesearch

Maria Theresa I. Cabaraban; Charles N. Kroll; Satoshi Hirabayashi; David J. Nowak

2013-01-01

A distributed adaptation of i-Tree Eco was used to simulate dry deposition in an urban area. This investigation focused on the effects of varying temperature, LAI, and NO2 concentration inputs on estimated NO2 dry deposition to trees in Baltimore, MD. A coupled modeling system is described, wherein WRF provided temperature...

A BAYESIAN STATISTICAL APPROACH FOR THE EVALUATION OF CMAQ

EPA Science Inventory

Bayesian statistical methods are used to evaluate Community Multiscale Air Quality (CMAQ) model simulations of sulfate aerosol over a section of the eastern US for 4-week periods in summer and winter 2001. The observed data come from two U.S. Environmental Protection Agency data ...

Advanced Land Surface Processes in the Coupled WRF/CMAQ with MODIS Input

EPA Science Inventory

Land surface modeling (LSM) is important in WRF/CMAQ for simulating the exchange of heat, moisture, momentum, trace atmospheric chemicals, and windblown dust between the land surface and the atmosphere.? Vegetation and soil treatments are crucial in LSM for surface energy budgets...

Advances in Support of the CMAQ Bidirectional Science Option for the Estimation of Ammonia Flux from Agricultural cropland

EPA Science Inventory

Proposed Session: Emissions Inventories, Models and processes: Last year a new CMAQ bidirectional option for the estimation of ammonia flux (emission and deposition) was released. This option essentially replaces NEI crop ammonia emissions with emissions calculated dynamically...

A Study of the Ozone Formation by Ensemble Back Trajectory-process Analysis Using the Eta-CMAQ Forecast Model over the Northeastern U.S. During the 2004 ICARTT Period

EPA Science Inventory

The integrated process rates (IPR) estimated by the Eta-CMAQ model at grid cells along the trajectory of the air mass transport path were analyzed to quantitatively investigate the relative importance of physical and chemical processes for O₃ formation and evolution ov...

New Particle Formation & Growth in CMAQ-NPF: Application of Comprehensive Model Methods to Observations during CalNex & CARES

EPA Science Inventory

The formation and growth of new atmospheric ultrafine particles are exceedingly complex processes and recent scientific efforts have grown our understanding of them tremendously. This presentation describes the effort to apply this new knowledge to the CMAQ chemical transport mod...

DIAGNOSTIC STUDY ON FINE PARTICULATE MATTER PREDICTIONS OF CMAQ IN THE SOUTHEASTERN U.S.

EPA Science Inventory

In this study, the authors use the process analysis tool embedded in CMAQ to examine major processes that govern the fate of key pollutants, identify the most influential processes that contribute to model errors, and guide the diagnostic and sensitivity studies aimed at improvin...

Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States

EPA Science Inventory

Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)– Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to ...

Dynamic Evaluation of Two Decades of CMAQ Simulations over the Continental United States

EPA Science Inventory

This presentation focuses on the dynamic evaluation of the CMAQ model over the continental United States using multi-decadal simulations for the period from 1990 to 2010 to examine how well the changes in observed ozone air quality induced by variations in meteorology and/or emis...

Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States

EPA Science Inventory

Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)– Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to assess...

Modeling Analysis of Multi-Decadal Trends in Ozone and Precursor Species across the Northern Hemisphere and the United States

EPA Science Inventory

The WRF-CMAQ modeling system was applied over a domain encompassing the northern hemisphere and a nested domain over the U.S. Model simulations for the 1990-2010 were performed to examine trends in various air pollutant concentrations. Trends in O3 mixing ratios over the U.S. are...

Evaluation of the Community Multiscale Air Quality (CMAQ) ...

EPA Pesticide Factsheets

This work evaluates particle size-composition distributions simulated by the Community Multiscale Air Quality (CMAQ) model using Micro-Orifice Uniform Deposit Impactor (MOUDI) measurements at 18 sites across North America. Size-resolved measurements of particulate SO4+, with the model ranging from an underestimation to overestimation of both the peak diameter and peak particle concentration across the sites. Computing PM2.5 from the modeled size distribution parameters rather than by summing the masses in the Aitken and a

A STUDY OF PROCESS CONTRIBUTION TO PM 2.5 FORMATION DURING THE 2004 ICARTT PERIOD USING THE ETA-CMAQ FORECAST MODEL OVER THE NORTHEASTERN U.S.

EPA Science Inventory

In this study, first, we evaluate the Eta-CMAQ forecast model performance for the chemical components (SO₄^2-, NO₃^-, and NH₄⁺) of PM_2.5 with the observational data from aircraft flights during the 2004 In...

A COMPREHENSIVE EVALUATION OF THE ETA-CMAQ FORECAST MODEL PERFORMANCE FOR O3, ITS RELATED PRECURSORS, AND METEOROLOGICAL PARAMETERS DURING THE 2004 ICARTT STUDY

EPA Science Inventory

In this study, the ability of the Eta-CMAQ forecast model to represent the vertical profiles of O3, related chemical species (CO, NO, NO₂, H₂O₂, CH₂O, HNO₃, SO₂, PAN, isoprene, toluene), and meteorological paramete...

"Advances in Linked Air Quality, Farm Management and Biogeochemistry Models to Address Bidrectional Ammonia Flux in CMAQ"

EPA Science Inventory

Recent increases in anthropogenic inputs of nitrogen to air, land and water media pose a growing threat to human health and ecosystems. Modeling of air-surface N flux is one area in need of improvement. Implementation of a linked air quality and cropland management system is de...

ADAPTATION AND APPLICATION OF THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODELING SYSTEM FOR REAL-TIME AIR QUALITY FORECASTING DURING THE SUMMER OF 2004

EPA Science Inventory

The ability to forecast local and regional air pollution events is challenging since the processes governing the production and sustenance of atmospheric pollutants are complex and often non-linear. Comprehensive atmospheric models, by representing in as much detail as possible t...

Advances in Linked Air Quality, Farm Management and Biogeochemistry Models to Address Bidirectional Ammonia Flux in CMAQ

EPA Science Inventory

Recent increases in anthropogenic inputs of nitrogen to air, land and water media pose a growing threat to human health and ecosystems. Modeling of air-surface N flux is one area in need of improvement. Implementation of a linked air quality and cropland management system is de...

How Clean is your Local Air? Here's an app for that

NASA Astrophysics Data System (ADS)

Maskey, M.; Yang, E.; Christopher, S. A.; Keiser, K.; Nair, U. S.; Graves, S. J.

2011-12-01

Air quality is a vital element of our environment. Accurate and localized air quality information is critical for characterizing environmental impacts at the local and regional levels. Advances in location-aware handheld devices and air quality modeling have enabled a group of UAHuntsville scientists to develop a mobile app, LocalAQI, that informs users of current conditions and forecasts of up to twenty-four hours, of air quality indices. The air quality index is based on Community Multiscale Air Quality Modeling System (CMAQ). UAHuntsville scientists have used satellite remote sensing products as inputs to CMAQ, resulting in forecast guidance for particulate matter air quality. The CMAQ output is processed to compute a standardized air quality index. Currently, the air quality index is available for the eastern half of the United States. LocalAQI consists of two main views: air quality index view and map view. The air quality index view displays current air quality for the zip code of a location of interest. Air quality index value is translated into a color-coded advisory system. In addition, users are able to cycle through available hourly forecasts for a location. This location-aware app defaults to the current air quality of user's location. The map view displays color-coded air quality information for the eastern US with an ability to animate through the available forecasts. The app is developed using a cross-platform native application development tool, appcelerator; hence LocalAQI is available for iOS and Android-based phones and pads.

Updates to the CMAQ Post Processing and Evaluation Tools for 2016

EPA Science Inventory

In the spring of 2016, the evaluation tools distributed with the CMAQ model code were updated and new tools were added to the existing set of tools. Observation data files, compatible with the AMET software, were also made available on the CMAS website for the first time with the...

Assessment of long-term WRF–CMAQ simulations for understanding direct aerosol effects on radiation "brightening" in the United States

EPA Science Inventory

Long-term simulations with the coupled WRF–CMAQ (Weather Research and Forecasting–Community Multi-scale Air Quality) model have been conducted to systematically investigate the changes in anthropogenic emissions of SO2 and NOx over the past 16 years (1995–2010) ...

“Nitrogen Budgets for the Mississippi River Basin using the linked EPIC-CMAQ-NEWS Models”

EPA Science Inventory

Presentation on the results from the 3 linked models, EPIC (USDA), CMAQ and NEWS to analyze a scenario of increased corn production related to biofuels together with Clean Air Act emission reductions across the US and the resultant effect on nitrogen loading to the Gulf of Mexico...

Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States (2017 MAC-MAQ Conference Presentation)

EPA Science Inventory

Dynamic evaluation of two decades of ozone simulations performed with the fully coupled Weather Research and Forecasting (WRF)–Community Multi-scale Air Quality (CMAQ) model over the contiguous United States is conducted to assess how well the changes in observed ozone air ...

Dynamic Evaluation of Two Decades of CMAQ Simulations over the Continental United States (book chapter)

EPA Science Inventory

This paper focuses on dynamic evaluation of the CMAQ model over the continental United States using multi-decadal simulations for the period from 1990 to 2010 to examine how well the changes in observed ozone air quality induced by variations in meteorology and/or emissions are s...

Utility of NCEP Operational and Emerging Meteorological Models for Driving Air Quality Prediction

NASA Astrophysics Data System (ADS)

McQueen, J.; Huang, J.; Huang, H. C.; Shafran, P.; Lee, P.; Pan, L.; Sleinkofer, A. M.; Stajner, I.; Upadhayay, S.; Tallapragada, V.

2017-12-01

Operational air quality predictions for the United States (U. S.) are provided at NOAA by the National Air Quality Forecasting Capability (NAQFC). NAQFC provides nationwide operational predictions of ozone and particulate matter twice per day (at 06 and 12 UTC cycles) at 12 km resolution and 1 hour time intervals through 48 hours and distributed at http://airquality.weather.gov. The NOAA National Centers for Environmental Prediction (NCEP) operational North American Mesoscale (NAM) 12 km weather prediction is used to drive the Community Multiscale Air Quality (CMAQ) model. In 2017, the NAM was upgraded in part to reduce a warm 2m temperature bias in Summer (V4). At the same time CMAQ was updated to V5.0.2. Both versions of the models were run in parallel for several months. Therefore the impact of improvements from the atmospheric chemistry model versus upgrades with the weather prediction model could be assessed. . Improvements to CMAQ were related to improvements to improvements in NAM 2 m temperature bias through increasing the opacity of clouds and reducing downward shortwave radiation resulted in reduced ozone photolysis. Higher resolution operational NWP models have recently been introduced as part of the NCEP modeling suite. These include the NAM CONUS Nest (3 km horizontal resolution) run four times per day through 60 hours and the High Resolution Rapid Refresh (HRRR, 3 km) run hourly out to 18 hours. In addition, NCEP with other NOAA labs has begun to develop and test the Next Generation Global Prediction System (NGGPS) based on the FV3 global model. This presentation also overviews recent developments with operational numerical weather prediction and evaluates the ability of these models for predicting low level temperatures, clouds and capturing boundary layer processes important for driving air quality prediction in complex terrain. The assessed meteorological model errors could help determine the magnitude of possible pollutant errors from CMAQ if used for driving meteorology. The NWP models will be evaluated against standard and mesonet fields averaged for various regions during the summer 2017. An evaluation of meteorological fields important to air quality modeling (eg: near surface winds, temperatures, moisture and boundary layer heights, cloud cover) will be reported on.

The Community Multi-scale Air Quality (CMAQ) Modeling System: Past, Recent Developments, and New Directions

EPA Science Inventory

Every year since 1966 the NCAR/ASP has hosted a summer colloquium designed for graduate students favoring subjects that represent new or rapidly developing areas of atmospheric science research. The NCAR/ASP Summer Colloquium brings together lecturers and graduate students for tw...

A Five- Year CMAQ Model Performance for Wildfires and ...

EPA Pesticide Factsheets

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. Two components of the biomass burning inventory, wildfires and prescribed fires are routinely estimated in the national emissions inventory. However, there is a large amount of uncertainty in the development of these emission inventory sectors. We have completed a 5 year set of CMAQ model simulations (2008-2012) in which we have simulated regional air quality with and without the wildfire and prescribed fire inventory. We will examine CMAQ model performance over regions with significant PM2.5 and Ozone contribution from prescribed fires and wildfires. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Development and Evaluation of the Biogenic Emissions Inventory System (BEIS) Model v3.6

EPA Science Inventory

We have developed new canopy emission algorithms and land use data for BEIS v3.6. Simulations with BEIS v3.4 and BEIS v3.6 in CMAQ v5.0.2 are compared these changes to the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and evaluated the simulations against observati...

Greenhouse Gas Source Attribution: Measurements Modeling and Uncertainty Quantification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Zhen; Safta, Cosmin; Sargsyan, Khachik

2014-09-01

In this project we have developed atmospheric measurement capabilities and a suite of atmospheric modeling and analysis tools that are well suited for verifying emissions of green- house gases (GHGs) on an urban-through-regional scale. We have for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate atmospheric CO 2 . This will allow for the examination of regional-scale transport and distribution of CO 2 along with air pollutants traditionally studied using CMAQ at relatively high spatial and temporal resolution with the goal of leveraging emissions verification efforts for both air quality and climate. We have developedmore » a bias-enhanced Bayesian inference approach that can remedy the well-known problem of transport model errors in atmospheric CO 2 inversions. We have tested the approach using data and model outputs from the TransCom3 global CO 2 inversion comparison project. We have also performed two prototyping studies on inversion approaches in the generalized convection-diffusion context. One of these studies employed Polynomial Chaos Expansion to accelerate the evaluation of a regional transport model and enable efficient Markov Chain Monte Carlo sampling of the posterior for Bayesian inference. The other approach uses de- terministic inversion of a convection-diffusion-reaction system in the presence of uncertainty. These approaches should, in principle, be applicable to realistic atmospheric problems with moderate adaptation. We outline a regional greenhouse gas source inference system that integrates (1) two ap- proaches of atmospheric dispersion simulation and (2) a class of Bayesian inference and un- certainty quantification algorithms. We use two different and complementary approaches to simulate atmospheric dispersion. Specifically, we use a Eulerian chemical transport model CMAQ and a Lagrangian Particle Dispersion Model - FLEXPART-WRF. These two models share the same WRF assimilated meteorology fields, making it possible to perform a hybrid simulation, in which the Eulerian model (CMAQ) can be used to compute the initial condi- tion needed by the Lagrangian model, while the source-receptor relationships for a large state vector can be efficiently computed using the Lagrangian model in its backward mode. In ad- dition, CMAQ has a complete treatment of atmospheric chemistry of a suite of traditional air pollutants, many of which could help attribute GHGs from different sources. The inference of emissions sources using atmospheric observations is cast as a Bayesian model calibration problem, which is solved using a variety of Bayesian techniques, such as the bias-enhanced Bayesian inference algorithm, which accounts for the intrinsic model deficiency, Polynomial Chaos Expansion to accelerate model evaluation and Markov Chain Monte Carlo sampling, and Karhunen-Lo %60 eve (KL) Expansion to reduce the dimensionality of the state space. We have established an atmospheric measurement site in Livermore, CA and are collect- ing continuous measurements of CO 2 , CH 4 and other species that are typically co-emitted with these GHGs. Measurements of co-emitted species can assist in attributing the GHGs to different emissions sectors. Automatic calibrations using traceable standards are performed routinely for the gas-phase measurements. We are also collecting standard meteorological data at the Livermore site as well as planetary boundary height measurements using a ceilometer. The location of the measurement site is well suited to sample air transported between the San Francisco Bay area and the California Central Valley.« less

Enhanced Representation of Soil NO Emissions in the Community Multiscale Air Quality (CMAQ) Model Version 5.0.2

NASA Technical Reports Server (NTRS)

Rasool, Quazi Z.; Zhang, Rui; Lash, Benjamin; Cohan, Daniel S.; Cooter, Ellen J.; Bash, Jesse O.; Lamsal, Lok N.

2016-01-01

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.

Two Methods to Derive Ground-level Concentrations of PM2.5 with Improved Accuracy in the North China, Calibrating MODIS AOD and CMAQ Model Predictions

NASA Astrophysics Data System (ADS)

Lyu, Baolei; Hu, Yongtao; Chang, Howard; Russell, Armistead; Bai, Yuqi

2016-04-01

Reliable and accurate characterizations of ground-level PM2.5 concentrations are essential to understand pollution sources and evaluate human exposures etc. Monitoring network could only provide direct point-level observations at limited locations. At the locations without monitors, there are generally two ways to estimate the pollution levels of PM2.5. One is observations of aerosol properties from the satellite-based remote sensing, such as Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD). The other one is from deterministic atmospheric chemistry models, such as the Community Multi-Scale Air Quality Model (CMAQ). In this study, we used a statistical spatio-temporal downscaler to calibrate the two datasets to monitor observations to derive fine-scale ground-level concentrations of PM2.5 with improved accuracy. We treated both MODIS AOD and CMAQ model predictions as biased proxy estimations of PM2.5 pollution levels. The downscaler proposed a Bayesian framework to model the spatially and temporally varying coefficients of the two types of estimations in the linear regression setting, in order to correct biases. Especially for calibrating MODIS AOD, a city-specific linear model was established to fill the missing AOD values, and a novel interpolation-based variable, i.e. PM2.5 Spatial Interpolator, was introduced to account for the spatial dependence among grid cells. We selected the heavy polluted and populated North China as our study area, in a grid setting of 81×81 12-km cells. For the evaluation of calibration performance for retrieved MODIS AOD, the R2 was 0.61 by the full model with PM2.5 Spatial Interpolator being presented, and was 0.48 with PM2.5 Spatial Interpolator not being presented. The constructed AOD values effectively predicted PM2.5 concentrations under our model structure, with R2=0.78. For the evaluation of calibrated CMAQ predictions, the R2 was 0.51, a little less than that of calibrated AOD. Finally we obtained two sets of calibrated estimations of ground-level PM2.5 concentrations with complete spatial coverage. By comparing the two datasets, we found that the prediction from AOD have a little smoother texture than that from CMAQ. The former also predicted larger heavy pollution area in the southern Hebei province than the latter, but in a small margin. In general, they have pretty similar spatial patterns, indicating the reliability of our data fusion method. In summary, the statistical spatio-temporal downscaler could provide improvements on MODIS AOD and CMAQ's predictions on PM2.5 pollution levels. Future work would focus on fusing three datasets, as aforementioned monitor observations, MODIS AOD and CMAQ predictions, to derive predictions of ground-level PM2.5 pollution levels with even increased accuracy.

Evaluating commercial marine emissions and their role in air quality policy using observations and the CMAQ model

NASA Astrophysics Data System (ADS)

Ring, Allison M.; Canty, Timothy P.; Anderson, Daniel C.; Vinciguerra, Timothy P.; He, Hao; Goldberg, Daniel L.; Ehrman, Sheryl H.; Dickerson, Russell R.; Salawitch, Ross J.

2018-01-01

We investigate the representation of emissions from the largest (Class 3) commercial marine vessels (c3 Marine) within the Community Multiscale Air Quality (CMAQ) model. In present emissions inventories developed by the United States Environmental Protection Agency (EPA), c3 Marine emissions are divided into off-shore and near-shore files. Off-shore c3 Marine emissions are vertically distributed within the atmospheric column, reflecting stack-height and plume rise. Near-shore c3 Marine emissions, located close to the US shoreline, are erroneously assumed to occur only at the surface. We adjust the near-shore c3 Marine emissions inventory by vertically distributing these emissions to be consistent with the off-shore c3 Marine inventory. Additionally, we remove near-shore c3 Marine emissions that overlap with off-shore c3 Marine emissions within the EPA files. The CMAQ model generally overestimates surface ozone (O3) compared to Air Quality System (AQS) site observations, with the largest discrepancies occurring near coastal waterways. We compare modeled O3 from two CMAQ simulations for June, July, and August (JJA) 2011 to surface O3 observations from AQS sites to examine the efficacy of the c3 Marine emissions improvements. Model results at AQS sites show average maximum 8-hr surface O3 decreases up to ∼6.5 ppb along the Chesapeake Bay, and increases ∼3-4 ppb around Long Island Sound, when the adjusted c3 Marine emissions are used. Along with the c3 Marine emissions adjustments, we reduce on-road mobile NOX emissions by 50%, motivated by work from Anderson et al. 2014, and reduce the lifetime of the alkyl nitrate species group from ∼10 days to ∼1 day based on work by Canty et al. 2015, to develop the ;c3 Science; model scenario. Simulations with these adjustments further improve model representation of the atmosphere. We calculate the ratio of column formaldehyde (HCHO) and tropospheric column nitrogen dioxide (NO2) using observations from the Ozone Monitoring Instrument and CMAQ model output to investigate the photochemical O3 production regime (VOC or NOX-limited) of the observed and modeled atmosphere. Compared to the baseline, the c3 Science model scenario more closely simulates the HCHO/NO2 ratio calculated from OMI data. Model simulations for JJA 2018 using the c3 Science scenario show a reduction of surface O3 by as much as ∼13 ppb for areas around the Chesapeake Bay and ∼2-3 ppb at locations in NY and CT downwind of New York City. These reductions are larger in 2018 than in 2011 due to a change in the photochemical O3 production regime in the Long Island Sound region and the projected decline of other (non-c3 Marine) sources of O3 precursors, highlighting the importance of proper representation of c3 Marine emissions in future modeling scenarios.

Analyses of the long-range transport of nitrogeneous species through the atmosphere from the Asian continent using observational data at Cape Hedo, Okinawa, and CMAQ postanalyses

NASA Astrophysics Data System (ADS)

Sadanaga, Y.; Bandow, H.; Uno, I.; Sera, T.; Yuba, A.; Takenaka, N.; Takami, A.; Kurokawa, J.; Hatakeyama, S.

2010-12-01

The long-term monitoring of air quality has been continuing at the Cape Hedo Atmosphere and Aerosol Monitoring Station (CHAAMS) in Okinawa, Japan in terms of assessing the environmental impact and biogeochemical effect to the marine-surface activities by the economic growth of Asian continent. Among the monitoring data, total odd nitrogen oxides (NOy), HNO3, particulate nitrate (NO3-(p)), NH3, NH4+ and SO42- were analyzed for the period from 16 March to 13 April 2008 as well as the postanalyses of those species by the Community Muti-scale Air Quality model (CMAQ) of those species. NOy and total nitrate (TN = HNO3 + NO3-(p)) concentrations from China (CH) air mass origin were high during the observational period in both observed and model-calculated result. The long-range transport of odd nitrogen species from the Asian continent is supported with respect to both the CMAQ postanalyses and the observations. HNO3 and NO3-(p) concentrations from CH air mass origin were also high during the observational period. However, the HNO3 diurnal variation with daytime peak and nighttime lows suggests that HNO3 around the CHAAMS forms photochemically in situ or in areas relatively close to the CHAAMS. The maximum and minimum concentrations of NH3 were observed at Pacific Ocean (PO) and Middle China air mass origins, respectively, and the observed NH3 concentrations from PO air mass origin were highest. NH3 concentration calculated by the CMAQ failed to reproduce observed variation, this is because the horizontal resolution of CMAQ (-20km) is not sufficient to allocate the land surface/vegetation base NH3 emission. NH4+ and SO42- concentrations from CH air mass origin were high during the observational period for both the observation and the CMAQ calculation. As well as the case of NOy and TN, the long-range transport of ammonium and sulfur compounds from the Asian continent is also supported in terms of both the CMAQ postanalyses and the observations.

CMAQ Emissions Calculator Toolkit

DOT National Transportation Integrated Search

2017-10-27

CMAQ: A Quick Overview - Congestion Mitigation and Air Quality Improvement (CMAQ) Program - Established in 1991 under ISTEA (23 U.S.C. Section 149) The CMAQ program is established for transportation projects that contribute to the attainment or maint...

Fine-scale application of the WRF-CMAQ modeling system to the 2013 DISCOVER-AQ San Joaquin Valley study

EPA Science Inventory

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in ...

Improvements to the WRF-CMAQ modeling system for fine-scale air quality simulations

EPA Science Inventory

Despite significant reductions in atmospheric pollutants such as ozone (O₃) and fine particulate matter (PM_2.5) over the past several decades, air pollution continues to pose a threat to the health of humans and sensitive ecosystems. A number of areas across...

ASSESSMENT OF THE WINTER-TIME PERFORMANCE OF DEVELOPMENTAL PARTICULATE MATTER FORECASTS WITH THE ETA-CMAQ MODELING SYSTEM

EPA Science Inventory

It is desirable for local air quality agencies to accurately forecast tropospheric PM_2.5 concentrations to alert the sensitive population of the onset, severity and duration of unhealthy air, and to encourage the public and industry to reduce emissions-producing activi...

ETA-CMAQ MODELING SYSTEM'S CAPABILITY TO PROVIDE PM 2.5 AND AEROSOL OPTICAL THICKNESS FORECAST

EPA Science Inventory

In 2003, NOAA and the U.S. EPA signed a Memorandum of Agreement to work together to develop a National Air Quality Forecasting (AQF) capability. To meet this goal, NOAA's National Weather Service (NWS), the Office of Atmospheric Research (OAR) and the U.S. EPA developed and eval...

NOAA's National Air Quality Predictions and Development of Aerosol and Atmospheric Composition Prediction Components for the Next Generation Global Prediction System

NASA Astrophysics Data System (ADS)

Stajner, I.; Hou, Y. T.; McQueen, J.; Lee, P.; Stein, A. F.; Tong, D.; Pan, L.; Huang, J.; Huang, H. C.; Upadhayay, S.

2016-12-01

NOAA provides operational air quality predictions using the National Air Quality Forecast Capability (NAQFC): ozone and wildfire smoke for the United States and airborne dust for the contiguous 48 states at http://airquality.weather.gov. NOAA's predictions of fine particulate matter (PM2.5) became publicly available in February 2016. Ozone and PM2.5 predictions are produced using a system that operationally links the Community Multiscale Air Quality (CMAQ) model with meteorological inputs from the North American mesoscale forecast Model (NAM). Smoke and dust predictions are provided using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Current NAQFC focus is on updating CMAQ to version 5.0.2, improving PM2.5 predictions, and updating emissions estimates, especially for NOx using recently observed trends. Wildfire smoke emissions from a newer version of the USFS BlueSky system are being included in a new configuration of the NAQFC NAM-CMAQ system, which is re-run for the previous 24 hours when the wildfires were observed from satellites, to better represent wildfire emissions prior to initiating predictions for the next 48 hours. In addition, NOAA is developing the Next Generation Global Prediction System (NGGPS) to represent the earth system for extended weather prediction. NGGPS will include a representation of atmospheric dynamics, physics, aerosols and atmospheric composition as well as coupling with ocean, wave, ice and land components. NGGPS is being developed with a broad community involvement, including community developed components and academic research to develop and test potential improvements for potentially inclusion in NGGPS. Several investigators at NOAA's research laboratories and in academia are working to improve the aerosol and gaseous chemistry representation for NGGPS, to develop and evaluate the representation of atmospheric composition, and to establish and improve the coupling with radiation and microphysics. Additional efforts may include the improved use of predicted atmospheric composition in assimilation of observations and the linkage of full global atmospheric composition predictions with national air quality predictions.

TESTING CMAQ CHEMISTRY SENSITIVITIES IN BASE CHASE AND EMISSION CONTROL RUNS AT SEARCH AND SOS 99 SURFACE SITES IN THE SOUTHEASTERN UNITED STATES

EPA Science Inventory

CMAQ was run to simulate urban conditions in the southeastern U.S. in July 1999 at 32, 8, and 2 km grid spacings. Runs were made with two older mechanisms, Carbon Bond IV (CB4) and the Regional Acid Deposition Model, version 2 (RADM2), and with the more recent California Statewid...

Evaluating ammonia (NH3) predictions in the NOAA National Air Quality Forecast Capability (NAQFC) using in-situ aircraft and satellite measurements from the CalNex2010 campaign

NASA Astrophysics Data System (ADS)

Bray, Casey D.; Battye, William; Aneja, Viney P.; Tong, Daniel; Lee, Pius; Tang, Youhua; Nowak, John B.

2017-08-01

Atmospheric ammonia (NH3) is not only a major precursor gas for fine particulate matter (PM2.5), but it also negatively impacts the environment through eutrophication and acidification. As the need for agriculture, the largest contributing source of NH3, increases, NH3 emissions will also increase. Therefore, it is crucial to accurately predict ammonia concentrations. The objective of this study is to determine how well the U.S. National Oceanic and Atmospheric Administration (NOAA) National Air Quality Forecast Capability (NAQFC) system predicts ammonia concentrations using their Community Multiscale Air Quality (CMAQ) model (v4.6). Model predictions of atmospheric ammonia are compared against measurements taken during the NOAA California Nexus (CalNex) field campaign that took place between May and July of 2010. Additionally, the model predictions were also compared against ammonia measurements obtained from the Tropospheric Emission Spectrometer (TES) on the Aura satellite. The results of this study showed that the CMAQ model tended to under predict concentrations of NH3. When comparing the CMAQ model with the CalNex measurements, the model under predicted NH3 by a factor of 2.4 (NMB = -58%). However, the ratio of the median measured NH3 concentration to the median of the modeled NH3 concentration was 0.8. When compared with the TES measurements, the model under predicted concentrations of NH3 by a factor of 4.5 (NMB = -77%), with a ratio of the median retrieved NH3 concentration to the median of the modeled NH3 concentration of 3.1. Because the model was the least accurate over agricultural regions, it is likely that the major source of error lies within the agricultural emissions in the National Emissions Inventory. In addition to this, the lack of the use of bidirectional exchange of NH3 in the model could also contribute to the observed bias.

Dynamic Evaluation of Two Decades of CMAQ Simulations ...

EPA Pesticide Factsheets

This presentation focuses on the dynamic evaluation of the CMAQ model over the continental United States using multi-decadal simulations for the period from 1990 to 2010 to examine how well the changes in observed ozone air quality induced by variations in meteorology and/or emissions are simulated by the model. We applied spectral decomposition of the ozone time-series using the KZ filter to assess the variations in the strengths of synoptic (weather-induced variations) and baseline (long-term variation) forcings, embedded in the simulated and observed concentrations. The results reveal that CMAQ captured the year-to-year variability (more so in the later years than the earlier years) and the synoptic forcing in accordance with what the observations are showing. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Modeling Emissions and Vertical Plume Transport of Crop Residue Burning Experiments in the Pacific Northwest

NASA Astrophysics Data System (ADS)

Zhou, L.; Baker, K. R.; Napelenok, S. L.; Pouliot, G.; Elleman, R. A.; ONeill, S. M.; Urbanski, S. P.; Wong, D. C.

2017-12-01

Crop residue burning has long been a common practice in agriculture with the smoke emissions from the burning linked to negative health impacts. A field study in eastern Washington and northern Idaho in August 2013 consisted of multiple burns of well characterized fuels with nearby surface and aerial measurements including trace species concentrations, plume rise height and boundary layer structure. The chemical transport model CMAQ (Community Multiscale Air Quality Model) was used to assess the fire emissions and subsequent vertical plume transport. The study first compared assumptions made by the 2014 National Emission Inventory approach for crop residue burning with the fuel and emissions information obtained from the field study and then investigated the sensitivity of modeled carbon monoxide (CO) and PM2.5 concentrations to these different emission estimates and plume rise treatment with CMAQ. The study suggests that improvements to the current parameterizations are needed in order for CMAQ to reliably reproduce smoke plumes from burning. In addition, there is enough variability in the smoke emissions, stemming from variable field-specific information such as field size, that attempts to model crop residue burning should use field-specific information whenever possible.

Operational air quality forecast guidance for the United States

NASA Astrophysics Data System (ADS)

Stajner, Ivanka; Lee, Pius; Tong, Daniel; Pan, Li; McQueen, Jeff; Huang, Jinaping; Djalalova, Irina; Wilczak, James; Huang, Ho-Chun; Wang, Jun; Stein, Ariel; Upadhayay, Sikchya

2016-04-01

NOAA provides operational air quality predictions for ozone and wildfire smoke over the United States (U.S.) and predictions of airborne dust over the contiguous 48 states at http://airquality.weather.gov. These predictions are produced using U.S. Environmental Protection Agency (EPA) Community Model for Air Quality (CMAQ) and NOAA's HYSPLIT model (Stein et al., 2015) with meteorological inputs from the North American Mesoscale Forecast System (NAM). The current efforts focus on improving test predictions of fine particulate matter (PM2.5) from CMAQ. Emission inputs for ozone and PM2.5 predictions include inventory information from the U.S. EPA and recently added contributions of particulate matter from intermittent wildfires and windblown dust that rely on near real-time information. Current testing includes refinement of the vertical grid structure in CMAQ and inclusion of contributions of dust transport from global sources into the U.S. domain using the NEMS Global Aerosol Capability (NGAC). The addition of wildfire smoke and dust contributions in CMAQ reduced model underestimation of PM2.5 in summertime. Wintertime overestimation of PM2.5 was reduced by suppressing emissions of soil particles when the terrain is covered by snow or ice. Nevertheless, seasonal biases and biases in the diurnal cycle of PM2.5 are still substantial. Therefore, a new bias correction procedure based on an analog ensemble approach was introduced (Djalalova et al., 2015). It virtually eliminates biases in monthly means or in the diurnal cycle, but it also reduces day-to-day variability in PM2.5 predictions. Refinements to the bias correction procedure are being developed. Upgrades for the representation of wildfire smoke emissions within the domain and from global sources are in testing. Another area of active development includes approaches to scale emission inventories for nitrogen oxides in order to reproduce recent changes observed by the AirNow surface monitoring network and by satellite instruments (Tong et al., 2015) and to use these updated emissions to improve ozone predictions (Pan et al., 2015). An overview of the impacts of these recent and ongoing efforts to improve predictions of ozone, smoke and PM2.5 will be presented. Djalalova, I. et al., 2015: PM2.5 analog forecast and Kalman filter post-processing for the Community Multiscale Air Quality (CMAQ) model. Atmospheric Environment, doi:10.1016/j.atmosenv.2015.05.057. Pan L. et al., 2014: Assessment of NOx and O3 forecasting performances in the U.S. National Air Quality Forecasting Capability before and after the 2012 major emissions updates. Atmospheric Environment, doi: 10.1016/j.atmosenv.2014.06.020. Stein, A. et al., 2015: NOAA's HYSPLIT atmospheric transport and dispersion modeling system. Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-14-00110.1. Tong, D.Q. et al., 2015: Long-term NOx trends over large cities in the United States during the great recession: Comparison of satellite retrievals, ground observations, and emission inventories. Atmospheric Environment, doi:10.1016/j.atmosenv.2015.01.035.

Impacts of different plant functional types on ambient ozone predictions in the Seoul Metropolitan Areas (SMA), Korea

NASA Astrophysics Data System (ADS)

Kim, H.-K.; Woo, J.-H.; Park, R. S.; Song, C. H.; Kim, J.-H.; Ban, S.-J.; Park, J.-H.

2013-09-01

Plant functional type (PFT) distributions affect the results of biogenic emission modeling as well as O3 and PM simulations using chemistry-transport models (CTMs). This paper analyzes the variations of both surface biogenic VOC emissions and O3 concentrations due to changes in the PFT distributions in the Seoul Metropolitan Areas, Korea. Also, this paper attempts to provide important implications for biogenic emissions modeling studies for CTM simulations. MM5-MEGAN-SMOKE-CMAQ model simulations were implemented over the Seoul Metropolitan Areas in Korea to predict surface O3 concentrations for the period of 1 May to 31 June 2008. Starting from MEGAN biogenic emissions analysis with three different sources of PFT input data, US EPA CMAQ O3 simulation results were evaluated by surface O3 monitoring datasets and further considered on the basis of geospatial and statistical analyses. The three PFT datasets considered were "(1)KORPFT", developed with a region specific vegetation database; (2) CDP, adopted from US NCAR; and (3) MODIS, reclassified from the NASA Terra and Aqua combined land cover products. Comparisons of MEGAN biogenic emission results with the three different PFT data showed that broadleaf trees (BT) are the most significant contributor, followed by needleleaf trees (NT), shrub (SB), and herbaceous plants (HB) to the total biogenic volatile organic compounds (BVOCs). In addition, isoprene from BT and terpene from NT were recognized as significant primary and secondary BVOC species in terms of BVOC emissions distributions and O3-forming potentials in the study domain. Multiple regression analyses with the different PFT data (δO3 vs. δPFTs) suggest that KORPFT can provide reasonable information to the framework of MEGAN biogenic emissions modeling and CTM O3 predictions. Analyses of the CMAQ performance statistics suggest that deviations of BT areas can significantly affect CMAQ isoprene and O3 predictions. From further evaluations of the isoprene and O3 prediction results, we explored the PFT area-loss artifact that occurs due to geographical disparity between the PFT and leaf area index distributions, and can cause increased bias in CMAQ O3. Thus, the PFT-loss artifact must be a source of limitation in the MEGAN biogenic emission modeling and the CTM O3 simulation results. Time changes of CMAQ O3 distributions with the different PFT scenarios suggest that hourly and local impacts from the different PFT distributions on occasional inter-deviations of O3 are quite noticeable, reaching up to 10 ppb. Exponentially diverging hourly BVOC emissions and O3 concentrations with increasing ambient temperature suggest that the use of representative PFT distributions becomes more critical for O3 air quality modeling (or forecasting) in support of air quality decision-making and human health studies.

Secondary organic aerosol from sesquiterpene and monoterpene emissions in the United States.

PubMed

Sakulyanontvittaya, Tanarit; Guenther, Alex; Helmig, Detlev; Milford, Jana; Wiedinmyer, Christine

2008-12-01

Emissions of volatile organic compounds (VOC) from vegetation are believed to be a major source of secondary organic aerosol (SOA), which in turn comprises a large fraction of fine particulate matter in many areas. Sesquiterpenes are a class of biogenic VOC with high chemical reactivity and SOA yields. Sesquiterpenes have only recently been quantified in emissions from a wide variety of plants. In this study, a new sesquiterpene emission inventory is used to provide input to the Models-3 Community Multiscale Air Quality (CMAQ) model. CMAQ is used to estimate the contribution of sesquiterpenes and monoterpenes to SOA concentrations over the contiguous United States. The gas-particle partitioning module of CMAQ was modified to include condensable products of sesquiterpene oxidation and to update values of the enthalpy of vaporization. The resulting model predicts July monthly average surface concentrations of total SOA in the eastern U.S. ranging from about 0.2-0.8 microg m(-3). This is roughly double the amount of SOA produced in this region when sesquiterpenes are not included. Even with sesquiterpenes included, however, the model significantly underpredicts surface concentrations of particle-phase organic matter compared to observed values. Treating all SOA as capable of undergoing polymerization increases predicted monthly average surface concentrations in July to 0.4-1.2 microg m(-3), in closer agreement with observations. Using the original enthalpy of vaporization value in CMAQ in place of the values estimated from the recent literature results in predicted SOA concentrations of about 0.3-1.3 microg m(-3).

CMAQ modeling of near-ground ozone pollution during the CAREBeijing-2006 campaign in Beijing, China

NASA Astrophysics Data System (ADS)

Wang, Xuesong; Song, Yu; Zhang, Yuanhang; Hu, Min; Zeng, Limin; Zhu, Tong

2010-05-01

The Community Multiscale Air Quality (CMAQ) modeling system, a 3-D regional chemical transport model, was used to simulate the O3 episodes during the Campaign of Air Quality Research in Beijing and surrounding areas in 2006 (CAREBeijing-2006). The model reproduced the temporal and spatial variations of the observed ozone and precursors well during the campaign. The modeling results showed the evolution of near ground O3 and the feature of vertical O3 profile on pollution days with different meteorological conditions. Process analysis was applied to investigate the contributions of local production and regional transport, and found different relative importance at different locations of Beijing. O3-NOx-VOCs sensitivity was also addressed with different precursor emission scenarios. The Beijing downtown area and downwind urban plume were usually in VOC-limited regime, whereas the upwind regions and northern mountain areas were generally characterized by NOx-sensitive chemistry. Ozone production efficiency of NOx was also calculated based on simulation results and compared with that derived from observations. For reducing O3 levels in Beijing, the above results suggest a regional emission control strategy with more emphasis on VOCs reduction in Beijing urban areas.

Eta-CMAQ Air Quality Forecasts for O3 and Related Species Using Three Different Photochemical Mechanisms (CB4, CB05, SAPRC-99): Comparisons with Measurements During the 2004 ICARTT Study

EPA Science Inventory

In this study, we compare the CB4, CB05 and SAPRC-99 mechanisms by examining the impact of these different chemical mechanisms on the Eta-CMAQ air quality forecast model simulations for O₃ and its related precursors over the eastern US through comparisons with the inte...

One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system

NASA Astrophysics Data System (ADS)

Hu, Jianlin; Chen, Jianjun; Ying, Qi; Zhang, Hongliang

2016-08-01

China has been experiencing severe air pollution in recent decades. Although an ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research and Forecasting (WRF) model and the Community Multi-scale Air Quality (CMAQ) model was conducted to provide detailed temporal and spatial information of ozone (O3), total PM2.5, and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O3 generally occurs at low concentration range while underprediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in southern China than in northern China, central China, and Sichuan Basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of the CMAQ model to reproduce severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.

Remote Sensing Characterization of the Urban Landscape for Improvement of Air Quality Modeling

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Khan, Maudood

2005-01-01

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, in moderating ground-level ozone and air temperature, compared to "business as usual" simulations in which heat island mitigation strategies are not applied. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data has been found to better characterize low densityhburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for fiture scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the state Environmental Protection agency to evaluate how these transportation plans will affect fbture air quality.

Chemical transport model simulations of organic aerosol in ...

EPA Pesticide Factsheets

Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we updated the organic aerosol module and organic emissions inventory of a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ), using recent, experimentally derived inputs and parameterizations for mobile sources. The updated model included a revised volatile organic compound (VOC) speciation for mobile sources and secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOCs). The updated model was used to simulate air quality in southern California during May and June 2010, when the California Research at the Nexus of Air Quality and Climate Change (CalNex) study was conducted. Compared to the Traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted organic aerosol (OA) mass concentrations but did substantially improve predictions of OA sources and composition (e.g., POA–SOA split), as well as ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performed similar to a recently released research version of CMAQ (Woody et al., 2016) that did not include the updated VOC and IVOC emissions and SOA data

“Application and evaluation of the two-way coupled WRF-CMAQ modeling system to the 2011 DISCOVER-AQ campaign in the Baltimore-Washington D.C. area.”

EPA Science Inventory

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in ...

Molecular view modeling of atmospheric organic particulate matter: Incorporating molecular structure and co-condensation of water

NASA Astrophysics Data System (ADS)

Pankow, James F.; Marks, Marguerite C.; Barsanti, Kelley C.; Mahmud, Abdullah; Asher, William E.; Li, Jingyi; Ying, Qi; Jathar, Shantanu H.; Kleeman, Michael J.

2015-12-01

Most urban and regional models used to predict levels of organic particulate matter (OPM) are based on fundamental equations for gas/particle partitioning, but make the highly simplifying, anonymized-view (AV) assumptions that OPM levels are not affected by either: a) the molecular characteristics of the condensing organic compounds (other than simple volatility); or b) co-condensation of water as driven by non-zero relative humidity (RH) values. The simplifying assumptions have allowed parameterized chamber results for formation of secondary organic aerosol (SOA) (e.g., ;two-product; (2p) coefficients) to be incorporated in chemical transport models. However, a return towards a less simplistic (and more computationally demanding) molecular view (MV) is needed that acknowledges that atmospheric OPM is a mixture of organic compounds with differing polarities, water, and in some cases dissolved salts. The higher computational cost of MV modeling results from a need for iterative calculations of the composition-dependent gas/particle partition coefficient values. MV modeling of OPM that considered water uptake (but not dissolved salts) was carried out for the southeast United States for the period August 29 through September 7, 2006. Three model variants were used at three universities: CMAQ-RH-2p (at PSU), UCD/CIT-RH-2p (at UCD), and CMAQ-RH-MCM (at TAMU). With the first two, MV structural characteristics (carbon number and numbers of functional groups) were assigned to each of the 2p products used in CMAQv.4.7.1 such that resulting predicted Kp,i values matched those in CMAQv.4.7.1. When water uptake was allowed, most runs assumed that uptake occurred only into the SOA portion, and imposed immiscibility of SOA with primary organic aerosol (POA). (POA is often viewed as rather non-polar, while SOA is commonly viewed as moderately-to-rather polar. Some runs with UCD/CIT-RH-2p were used to investigate the effects of POA/SOA miscibility.) CMAQ-RH-MCM used MCM to generate oxidation products, and assumed miscibility of SOA and POA. In a ∼500 km wide band from Louisiana through to at least North Carolina, CMAQ-RH-2p and UCD/CIT-RH-2p predicted that water uptake can increase SOA levels by as much as 50-100% (from a range of ∼1-2 μg m-3 to a range of ∼1-4 μg m-3). CMAQ-RH-MCM predicted much lower effects of water uptake on SOA levels (<10% increase). The results from CMAQ-RH-2p and UCD/CIT-RH-2p are considered more reflective of reality. In the Alabama/Georgia hotspot, both CMAQ-RH-2p and UCD/CIT-RH-2p predicted aerosol water levels that are up to nearly half the predicted SOA levels, namely ∼0.5-2 μg m-3. Such water levels in SOA will affect particle optical properties, viscosity, gas/particle partitioning times, and rates of hydrolysis and water elimination reactions.

Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework

NASA Astrophysics Data System (ADS)

Solazzo, Efisio; Hogrefe, Christian; Colette, Augustin; Garcia-Vivanco, Marta; Galmarini, Stefano

2017-09-01

The work here complements the overview analysis of the modelling systems participating in the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3) by focusing on the performance for hourly surface ozone by two modelling systems, Chimere for Europe and CMAQ for North America. The evaluation strategy outlined in the course of the three phases of the AQMEII activity, aimed to build up a diagnostic methodology for model evaluation, is pursued here and novel diagnostic methods are proposed. In addition to evaluating the base case simulation in which all model components are configured in their standard mode, the analysis also makes use of sensitivity simulations in which the models have been applied by altering and/or zeroing lateral boundary conditions, emissions of anthropogenic precursors, and ozone dry deposition. To help understand of the causes of model deficiencies, the error components (bias, variance, and covariance) of the base case and of the sensitivity runs are analysed in conjunction with timescale considerations and error modelling using the available error fields of temperature, wind speed, and NOx concentration. The results reveal the effectiveness and diagnostic power of the methods devised (which remains the main scope of this study), allowing the detection of the timescale and the fields that the two models are most sensitive to. The representation of planetary boundary layer (PBL) dynamics is pivotal to both models. In particular, (i) the fluctuations slower than ˜ 1.5 days account for 70-85 % of the mean square error of the full (undecomposed) ozone time series; (ii) a recursive, systematic error with daily periodicity is detected, responsible for 10-20 % of the quadratic total error; (iii) errors in representing the timing of the daily transition between stability regimes in the PBL are responsible for a covariance error as large as 9 ppb (as much as the standard deviation of the network-average ozone observations in summer in both Europe and North America); (iv) the CMAQ ozone error has a weak/negligible dependence on the errors in NO2, while the error in NO2 significantly impacts the ozone error produced by Chimere; (v) the response of the models to variations of anthropogenic emissions and boundary conditions show a pronounced spatial heterogeneity, while the seasonal variability of the response is found to be less marked. Only during the winter season does the zeroing of boundary values for North America produce a spatially uniform deterioration of the model accuracy across the majority of the continent.

Responses of future air quality to emission controls over North Carolina, Part I: Model evaluation for current-year simulations

NASA Astrophysics Data System (ADS)

Liu, Xiao-Huan; Zhang, Yang; Olsen, Kristen M.; Wang, Wen-Xing; Do, Bebhinn A.; Bridgers, George M.

2010-07-01

The prediction of future air quality and its responses to emission control strategies at national and state levels requires a reliable model that can replicate atmospheric observations. In this work, the Mesoscale Model (MM5) and the Community Multiscale Air Quality Modeling (CMAQ) system are applied at a 4-km horizontal grid resolution for four one-month periods, i.e., January, June, July, and August in 2002 to evaluate model performance and compare with that at 12-km. The evaluation shows skills of MM5/CMAQ that are overall consistent with current model performance. The large cold bias in temperature at 1.5 m is likely due to too cold soil initial temperatures and inappropriate snow treatments. The large overprediction in precipitation in July is due likely to too frequent afternoon convective rainfall and/or an overestimation in the rainfall intensity. The normalized mean biases and errors are -1.6% to 9.1% and 15.3-18.5% in January and -18.7% to -5.7% and 13.9-20.6% in July for max 1-h and 8-h O 3 mixing ratios, respectively, and those for 24-h average PM 2.5 concentrations are 8.3-25.9% and 27.6-38.5% in January and -57.8% to -45.4% and 46.1-59.3% in July. The large underprediction in PM 2.5 in summer is attributed mainly to overpredicted precipitation, inaccurate emissions, incomplete treatments for secondary organic aerosols, and model difficulties in resolving complex meteorology and geography. While O 3 prediction shows relatively less sensitivity to horizontal grid resolutions, PM 2.5 and its secondary components, visibility indices, and dry and wet deposition show a moderate to high sensitivity. These results have important implications for the regulatory applications of MM5/CMAQ for future air quality attainment.

Aerosol Optical Depth over Europe: Evaluation of the CALIOPE air quality modelling system with direct-sun AERONET observations

NASA Astrophysics Data System (ADS)

Basart, Sara; Pay, María. Teresa; Pérez, Carlos; Cuevas, Emilio; Jorba, Oriol; Piot, Matthias; María Baldasano, Jose

2010-05-01

In the frame of the CALIOPE project (Baldasano et al., 2008), the Barcelona Supercomputing Center (BSC-CNS) currently operates a high-resolution air quality forecasting system based on daily photochemical forecasts in Europe (12km x 12km resolution) with the WRF-ARW/HERMES/CMAQ modelling system (http://www.bsc.es/caliope) and desert dust forecasts over Southern Europe with BSC-DREAM8b (Pérez et al., 2006; http://www.bsc.es/projects/earthscience/DREAM). High resolution simulations and forecasts are possible through their implementation on MareNostrum supercomputer at BSC-CNS. As shown in previous air quality studies (e.g. Rodríguez et al., 2001; Jiménez-Guerrero et al., 2008), the contribution of desert dust on particulate matter levels in Southern Europe is remarkable due to its proximity to African desert dust sources. When considering only anthropogenic emissions (Baldasano et al., 2008) and the current knowledge about aerosol physics and chemistry, chemistry-transport model simulations underestimate the PM10 concentrations by 30-50%. As a first approach, the natural dust contribution from BSC-DREAM8b is on-line added to the anthropogenic aerosol output of CMAQ. The aim of the present work is the quantitative evaluation of the WRF-ARW/HERMES/ CMAQ/BSC-DREAM8b forecast system to simulate the Aerosol Optical Depth (AOD) over Europe. The performance of the modelled AOD has been quantitatively evaluated with discrete and categorical (skill scores) statistics by a comparison to direct-sun AERONET observations for 2004. The contribution of different types of aerosols will be analyzed by means of the O'Neill fine mode AOD products (O'Neill et al., 2001). A previous aerosol characterization of AERONET data was performed (Basart et al., 2009) in order to discriminate the different aerosol source contributions within the study region. The results indicate a remarkable improvement in the discrete and skill-scores evaluation (accuracy, critical success index and probability of detection) of AOD when using CMAQ+DREAM8b compared to CMAQ-alone simulations. An accurate analysis of the relative contributions of anthropogenic aerosols and desert dust to AOD over Europe and their seasonality will be also presented. References: Baldasano J.M, P. Jiménez-Guerrero, O. Jorba, C. Pérez, E. López, P. Güereca, F. Martin, M. García-Vivanco, I. Palomino, X. Querol, M. Pandolfi, M.J. Sanz and J.J. Diéguez: "CALIOPE: An operational air quality forecasting system for the Iberian Peninsula, Balearic Islands and Canary Islands- First annual evaluation and ongoing developments", Adv. Sci. and Res., 2: 89-98, 2008. Baldasano J.M., L. P. Güereca, E. López, S. Gassó, P. Jimenez-Guerrero. "Development of a high resolution (1 km x 1 km, 1 h) emission model for Spain: the High-Elective Resolution Modelling Emission System (HERMES)". Atmospheric Environment, 42: 7215-7233 doi: 10.1016/j.atmosenv.2008.07.026, 2008. Basart, S., Pérez, C., Cuevas, E., Baldasano, J. M. and Gobbi, G. P. "Aerosol characterization in Northern Africa, Northeastern Atlantic, Mediterranean Basin and Middle East from direct-sun AERONET observations", Atmos. Chem. Phys.., 9, 7707-7745, 2009. Jiménez-Guerrero, P., Pérez, C., Jorba, O. and Baldasano, J. M. "Contribution of Saharan dust in an integrated air quality system and its on-line assessment", Geophys. Res. Lett., 35(3), 2008. O'Neill, N. T., Dubovik, O., and Eck, T. F.: A modified Angstrom coefficient for the characterization of sub-micron aerosols, App. Opt., 40(14), 2368-2375, 2001. Pérez, C., Nickovic, S., Pejanovic, G., Baldasano, J. M. and Ozsoy, E. "Interactive dust-radiation modeling: A step to improve weather forecasts", Geophys. Res., 11(D16206),doi:10.1029/2005JD006717, 2006. Rodríguez, S., Querol, X., Alastuey, A., Kallos, G. and Kakaliagou, O. "Saharan dust contributions to PM10 and TSP levels in Southern and Eastern Spain", Atmos. Environ., 35, 2433-2447, 2001.

Utilizing Operational and Improved Remote Sensing Measurements to Assess Air Quality Monitoring Model Forecasts

NASA Astrophysics Data System (ADS)

Gan, Chuen-Meei

Air quality model forecasts from Weather Research and Forecast (WRF) and Community Multiscale Air Quality (CMAQ) are often used to support air quality applications such as regulatory issues and scientific inquiries on atmospheric science processes. In urban environments, these models become more complex due to the inherent complexity of the land surface coupling and the enhanced pollutants emissions. This makes it very difficult to diagnose the model, if the surface parameter forecasts such as PM2.5 (particulate matter with aerodynamic diameter less than 2.5 microm) are not accurate. For this reason, getting accurate boundary layer dynamic forecasts is as essential as quantifying realistic pollutants emissions. In this thesis, we explore the usefulness of vertical sounding measurements on assessing meteorological and air quality forecast models. In particular, we focus on assessing the WRF model (12km x 12km) coupled with the CMAQ model for the urban New York City (NYC) area using multiple vertical profiling and column integrated remote sensing measurements. This assessment is helpful in probing the root causes for WRF-CMAQ overestimates of surface PM2.5 occurring both predawn and post-sunset in the NYC area during the summer. In particular, we find that the significant underestimates in the WRF PBL height forecast is a key factor in explaining this anomaly. On the other hand, the model predictions of the PBL height during daytime when convective heating dominates were found to be highly correlated to lidar derived PBL height with minimal bias. Additional topics covered in this thesis include mathematical method using direct Mie scattering approach to convert aerosol microphysical properties from CMAQ into optical parameters making direct comparisons with lidar and multispectral radiometers feasible. Finally, we explore some tentative ideas on combining visible (VIS) and mid-infrared (MIR) sensors to better separate aerosols into fine and coarse modes.

Delivery of Forecasted Atmospheric Ozone and Dust for the New Mexico Environmental Public Health Tracking System - An Open Source Geospatial Solution

NASA Astrophysics Data System (ADS)

Hudspeth, W. B.; Sanchez-Silva, R.; Cavner, J. A.

2010-12-01

New Mexico's Environmental Public Health Tracking System (EPHTS), funded by the Centers for Disease Control (CDC) Environmental Public Health Tracking Network (EPHTN), aims to improve health awareness and services by linking health effects data with levels and frequency of environmental exposure. As a public health decision-support system, EPHTS systems include: state-of-the-art statistical analysis tools; geospatial visualization tools; data discovery, extraction, and delivery tools; and environmental/public health linkage information. As part of its mandate, EPHTS issues public health advisories and forecasts of environmental conditions that have consequences for human health. Through a NASA-funded partnership between the University of New Mexico and the University of Arizona, NASA Earth Science results are fused into two existing models (the Dust Regional Atmospheric Model (DREAM) and the Community Multiscale Air Quality (CMAQ) model) in order to improve forecasts of atmospheric dust, ozone, and aerosols. The results and products derived from the outputs of these models are made available to an Open Source mapping component of the New Mexico EPHTS. In particular, these products are integrated into a Django content management system using GeoDjango, GeoAlchemy, and other OGC-compliant geospatial libraries written in the Python and C++ programming languages. Capabilities of the resultant mapping system include indicator-based thematic mapping, data delivery, and analytical capabilities. DREAM and CMAQ outputs can be inspected, via REST calls, through temporal and spatial subsetting of the atmospheric concentration data across analytical units employed by the public health community. This paper describes details of the architecture and integration of NASA Earth Science into the EPHTS decision-support system.

Spatial-temporal Variations and Source Apportionment of typical Heavy Metals in Beijing-Tianjin-Hebei (BTH) region of China Based on Localized Air Pollutants Emission Inventory and WRF-CMAQ modelling

NASA Astrophysics Data System (ADS)

Tian, H.; Liu, S.; Zhu, C.; Liu, H.; Wu, B.

2017-12-01

Abstract: Anthropogenic atmospheric emissions of air pollutants have caused worldwide concerns due to their adverse effects on human health and the ecosystem. By determining the best available emission factors for varied source categories, we established the comprehensive atmospheric emission inventories of hazardous air pollutants including 12 typical toxic heavy metals (Hg, As, Se, Pb, Cd, Cr, Ni, Sb, Mn, Co, Cu, and Zn) from primary anthropogenic activities in Beijing-Tianjin-Hebei (BTH) region of China for the period of 2012 for the first time. The annual emissions of these pollutants were allocated at a high spatial resolution of 9km × 9km grid with ArcGIS methodology and surrogate indexes, such as regional population and gross domestic product (GDP). Notably, the total heavy metal emissions from this region represented about 10.9% of the Chinese national total emissions. The areas with high emissions of heavy metals were mainly concentrated in Tangshan, Shijiazhuang, Handan and Tianjin. Further, WRF-CMAQ modeling system were applied to simulate the regional concentration of heavy metals to explore their spatial-temporal variations, and the source apportionment of these heavy metals in BTH region was performed using the Brute-Force method. Finally, integrated countermeasures were proposed to minimize the final air pollutants discharge on account of the current and future demand of energy-saving and pollution reduction in China. Keywords: heavy metals; particulate matter; emission inventory; CMAQ model; source apportionment Acknowledgment. This work was funded by the National Natural Science Foundation of China (21377012 and 21177012) and the Trail Special Program of Research on the Cause and Control Technology of Air Pollution under the National Key Research and Development Plan of China (2016YFC0201501).

Modeling green infrastructure land use changes on future air ...

EPA Pesticide Factsheets

Green infrastructure can be a cost-effective approach for reducing stormwater runoff and improving water quality as a result, but it could also bring co-benefits for air quality: less impervious surfaces and more vegetation can decrease the urban heat island effect, and also result in more removal of air pollutants via dry deposition with increased vegetative surfaces. Cooler surface temperatures can also decrease ozone formation through the increases of NOx titration; however, cooler surface temperatures also lower the height of the boundary layer resulting in more concentrated pollutants within the same volume of air, especially for primary emitted pollutants (e.g. NOx, CO, primary particulate matter). To better understand how green infrastructure impacts air quality, the interactions between all of these processes must be considered collectively. In this study, we use a comprehensive coupled meteorology-air quality model (WRF-CMAQ) to simulate the influence of planned land use changes that include green infrastructure in Kansas City (KC) on regional meteorology and air quality. Current and future land use data was provided by the Mid-America Regional Council for 2012 and 2040 (projected land use due to population growth, city planning and green infrastructure implementation). These land use datasets were incorporated into the WRF-CMAQ modeling system allowing the modeling system to propagate the changes in vegetation and impervious surface coverage on meteoro

Finely Resolved On-Road PM2.5 and Estimated Premature Mortality in Central North Carolina.

PubMed

Chang, Shih Ying; Vizuete, William; Serre, Marc; Vennam, Lakshmi Pradeepa; Omary, Mohammad; Isakov, Vlad; Breen, Michael; Arunachalam, Saravanan

2017-12-01

To quantify the on-road PM 2.5 -related premature mortality at a national scale, previous approaches to estimate concentrations at a 12-km × 12-km or larger grid cell resolution may not fully characterize concentration hotspots that occur near roadways and thus the areas of highest risk. Spatially resolved concentration estimates from on-road emissions to capture these hotspots may improve characterization of the associated risk, but are rarely used for estimating premature mortality. In this study, we compared the on-road PM 2.5 -related premature mortality in central North Carolina with two different concentration estimation approaches-(i) using the Community Multiscale Air Quality (CMAQ) model to model concentration at a coarser resolution of a 36-km × 36-km grid resolution, and (ii) using a hybrid of a Gaussian dispersion model, CMAQ, and a space-time interpolation technique to provide annual average PM 2.5 concentrations at a Census-block level (∼105,000 Census blocks). The hybrid modeling approach estimated 24% more on-road PM 2.5 -related premature mortality than CMAQ. The major difference is from the primary on-road PM 2.5 where the hybrid approach estimated 2.5 times more primary on-road PM 2.5 -related premature mortality than CMAQ due to predicted exposure hotspots near roadways that coincide with high population areas. The results show that 72% of primary on-road PM 2.5 premature mortality occurs within 1,000 m from roadways where 50% of the total population resides, highlighting the importance to characterize near-road primary PM 2.5 and suggesting that previous studies may have underestimated premature mortality due to PM 2.5 from traffic-related emissions. © 2017 Society for Risk Analysis.

CMAQ Involvement in Air Quality Model Evaluation International Initiative

EPA Pesticide Factsheets

Description of Air Quality Model Evaluation International Initiative (AQMEII). Different chemical transport models are applied by different groups over North America and Europe and evaluated against observations.

An emission processing system for air quality modelling in the Mexico City metropolitan area: Evaluation and comparison of the MOBILE6.2-Mexico and MOVES-Mexico traffic emissions.

PubMed

Guevara, M; Tena, C; Soret, A; Serradell, K; Guzmán, D; Retama, A; Camacho, P; Jaimes-Palomera, M; Mediavilla, A

2017-04-15

This article describes the High-Elective Resolution Modelling Emission System for Mexico (HERMES-Mex) model, an emission processing tool developed to transform the official Mexico City Metropolitan Area (MCMA) emission inventory into hourly, gridded (up to 1km 2 ) and speciated emissions used to drive mesoscale air quality simulations with the Community Multi-scale Air Quality (CMAQ) model. The methods and ancillary information used for the spatial and temporal disaggregation and speciation of the emissions are presented and discussed. The resulting emission system is evaluated, and a case study on CO, NO 2 , O 3 , VOC and PM 2.5 concentrations is conducted to demonstrate its applicability. Moreover, resulting traffic emissions from the Mobile Source Emission Factor Model for Mexico (MOBILE6.2-Mexico) and the MOtor Vehicle Emission Simulator for Mexico (MOVES-Mexico) models are integrated in the tool to assess and compare their performance. NO x and VOC total emissions modelled are reduced by 37% and 26% in the MCMA when replacing MOBILE6.2-Mexico for MOVES-Mexico traffic emissions. In terms of air quality, the system composed by the Weather Research and Forecasting model (WRF) coupled with the HERMES-Mex and CMAQ models properly reproduces the pollutant levels and patterns measured in the MCMA. The system's performance clearly improves in urban stations with a strong influence of traffic sources when applying MOVES-Mexico emissions. Despite reducing estimations of modelled precursor emissions, O 3 peak averages are increased in the MCMA core urban area (up to 30ppb) when using MOVES-Mexico mobile emissions due to its VOC-limited regime, while concentrations in the surrounding suburban/rural areas decrease or increase depending on the meteorological conditions of the day. The results obtained suggest that the HERMES-Mex model can be used to provide model-ready emissions for air quality modelling in the MCMA. Copyright © 2017 Elsevier B.V. All rights reserved.

The Impact of Iodide-Mediated Ozone Deposition and ...

EPA Pesticide Factsheets

The air quality of many large coastal areas in the United States is affected by the confluence of polluted urban and relatively clean marine airmasses, each with distinct atmospheric chemistry. In this context, the role of iodide-mediated ozone (O3) deposition over seawater and marine halogen chemistry accounted for in both the lateral boundary conditions and coastal waters surrounding the continental U.S. is examined using the Community Multiscale Air Quality (CMAQ) model. Several nested simulations are conducted in which these halogen processes are implemented separately in the continental U.S. and hemispheric CMAQ domains, the latter providing lateral boundary conditions for the former. Overall, it is the combination of these processes within both the continental U.S. domain and from lateral boundary conditions that lead to the largest reductions in modeled surface O3 concentrations. Predicted reductions in surface O3 concentrations occur mainly along the coast where CMAQ typically has large overpredictions. These results suggest that a realistic representation of halogen processes in marine regions can improve model prediction of O3 concentrations near the coast. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and

Evaluation of gas-particle partitioning in a regional air quality model for organic pollutants

NASA Astrophysics Data System (ADS)

Efstathiou, Christos I.; Matejovičová, Jana; Bieser, Johannes; Lammel, Gerhard

2016-12-01

Persistent organic pollutants (POPs) are of considerable concern due to their well-recognized toxicity and their potential to bioaccumulate and engage in long-range transport. These compounds are semi-volatile and, therefore, create a partition between vapour and condensed phases in the atmosphere, while both phases can undergo chemical reactions. This work describes the extension of the Community Multiscale Air Quality (CMAQ) modelling system to POPs with a focus on establishing an adaptable framework that accounts for gaseous chemistry, heterogeneous reactions, and gas-particle partitioning (GPP). The effect of GPP is assessed by implementing a set of independent parameterizations within the CMAQ aerosol module, including the Junge-Pankow (JP) adsorption model, the Harner-Bidleman (HB) organic matter (OM) absorption model, and the dual Dachs-Eisenreich (DE) black carbon (BC) adsorption and OM absorption model. Use of these descriptors in a modified version of CMAQ for benzo[a]pyrene (BaP) results in different fate and transport patterns as demonstrated by regional-scale simulations performed for a European domain during 2006. The dual DE model predicted 24.1 % higher average domain concentrations compared to the HB model, which was in turn predicting 119.2 % higher levels compared to the baseline JP model. Evaluation with measurements from the European Monitoring and Evaluation Programme (EMEP) reveals the capability of the more extensive DE model to better capture the ambient levels and seasonal behaviour of BaP. It is found that the heterogeneous reaction of BaP with O3 may decrease its atmospheric lifetime by 25.2 % (domain and annual average) and near-ground concentrations by 18.8 %. Marginally better model performance was found for one of the six EMEP stations (Košetice) when heterogeneous BaP reactivity was included. Further analysis shows that, for the rest of the EMEP locations, the model continues to underestimate BaP levels, an observation that can be attributed to low emission estimates for such remote areas. These findings suggest that, when modelling the fate and transport of organic pollutants on large spatio-temporal scales, the selection and parameterization of GPP can be as important as degradation (reactivity).

LAYER DEPENDENT ADVECTION IN CMAQ

EPA Science Inventory

The advection methods used in CMAQ require that the Courant-Friedrichs-Lewy (CFL) condition be satisfied for numerical stability and accuracy. In CMAQ prior to version 4.3, the ADVSTEP algorithm established CFL-safe synchronization and advection timesteps that were uniform throu...

3D Air Quality and the Clean Air Interstate Rule: Lagrangian Sampling of CMAQ Model Results to Aid Regional Accountability Metrics

NASA Technical Reports Server (NTRS)

Fairlie, T. D.; Szykman, Jim; Pierce, Robert B.; Gilliland, A. B.; Engel-Cox, Jill; Weber, Stephanie; Kittaka, Chieko; Al-Saadi, Jassim A.; Scheffe, Rich; Dimmick, Fred;

Effect of aerosol feedback in the Korea Peninsula using WRF-CMAQ two-way coupled model

NASA Astrophysics Data System (ADS)

Yoo, J.; Jeon, W.; Lee, H.; Lee, S.

2017-12-01

Aerosols influence the climate system by scattering and absorption of the solar radiation by altering the cloud radiative properties. For the reason, consideration of aerosol feedback is important numerical weather prediction and air quality models. The purpose of this study was to investigate the effect of aerosol feedback on PM10 simulation in Korean Peninsula using the Weather Research and Forecasting (WRF) and the community multiscale air quality (CMAQ) two-way coupled model. Simulations were conducted with the aerosol feedback (FB) and without (NFB). The results of the simulated solar radiation in the west part of Korea decreased due to the aerosol feedback effect. The feedback effect was significant in the west part of Korea Peninsula, showing high Particulate Matter (PM) estimates due to dense emissions and its long-range transport from China. The decrease of solar radiation lead to planetary boundary layer (PBL) height reduction, thereby dispersion of air pollutants such as PM is suppressed, and resulted in higher PM concentrations. These results indicate that aerosol feedback effects can play an important role in the simulation of meteorology and air quality over Korea Peninsula.

A Reduced Form Model for Ozone Based on Two Decades of ...

EPA Pesticide Factsheets

A Reduced Form Model (RFM) is a mathematical relationship between the inputs and outputs of an air quality model, permitting estimation of additional modeling without costly new regional-scale simulations. A 21-year Community Multiscale Air Quality (CMAQ) simulation for the continental United States provided the basis for the RFM developed in this study. Predictors included the principal component scores (PCS) of emissions and meteorological variables, while the predictand was the monthly mean of daily maximum 8-hour CMAQ ozone for the ozone season at each model grid. The PCS form an orthogonal basis for RFM inputs. A few PCS incorporate most of the variability of emissions and meteorology, thereby reducing the dimensionality of the source-receptor problem. Stochastic kriging was used to estimate the model. The RFM was used to separate the effects of emissions and meteorology on ozone concentrations. by running the RFM with emissions constant (ozone dependent on meteorology), or constant meteorology (ozone dependent on emissions). Years with ozone-conducive meteorology were identified, and meteorological variables best explaining meteorology-dependent ozone were identified. Meteorology accounted for 19% to 55% of ozone variability in the eastern US, and 39% to 92% in the western US. Temporal trends estimated for original CMAQ ozone data and emission-dependent ozone were mostly negative, but the confidence intervals for emission-dependent ozone are much

Impacts of Oil and Gas Production on Winter Ozone Pollution in the Uintah Basin Using Model Source Apportionment

NASA Astrophysics Data System (ADS)

Tran, H. N. Q.; Tran, T. T.; Mansfield, M. L.; Lyman, S. N.

2014-12-01

Contributions of emissions from oil and gas activities to elevated ozone concentrations in the Uintah Basin - Utah were evaluated using the CMAQ Integrated Source Apportionment Method (CMAQ-ISAM) technique, and were compared with the results of traditional budgeting methods. Unlike the traditional budgeting method, which compares simulations with and without emissions of the source(s) in question to quantify its impacts, the CMAQ-ISAM technique assigns tags to emissions of each source and tracks their evolution through physical and chemical processes to quantify the final ozone product yield from the source. Model simulations were performed for two episodes in winter 2013 of low and high ozone to provide better understanding of source contributions under different weather conditions. Due to the highly nonlinear ozone chemistry, results obtained from the two methods differed significantly. The growing oil and gas industry in the Uintah Basin is the largest contributor to the elevated zone (>75 ppb) observed in the Basin. This study therefore provides an insight into the impact of oil and gas industry on the ozone issue, and helps in determining effective control strategies.

Investigation of the air pollutant distribution over Northeast Asia using Models-3/CMAQ

NASA Astrophysics Data System (ADS)

Kim, J. Y.; Ghim, Y. S.; Won, J.-G.; Yoon, S.-C.; Woo, J.-H.

2003-04-01

Northeast Asia is one of the most densely populated areas in the world. Huge amount of air pollutants emitted in the area is transported to the east along with prevailing westerlies. In spring of Northeast Asia, migratory anticyclones are frequent. Transport and distribution of air pollutants can be substantially altered according to the locations of anticyclones. In this work, two different synoptic meteorological conditions associated with different locations of anticyclones in May 1999 were identified. The distributions of gaseous and particulate pollutants in these meteorological conditions were predicted and compared. Models-3/CMAQ (USEPA Models-3/Community Multi-scale Air Quality) and MM5 (PSU/NCAR Mesoscale Modeling System) were used to predict air quality and meteorology, respectively. The modeling domain was 5,184 km x 3,456 km centering on the Korean Peninsula (130o N, 40o E). The grid size was 108 km x 108 km and the number of grids was 48 in the west-east direction and 32 in the south-north direction. The number of layers in the vertical direction was six to the height of 500 hPa. Emission data were taken from the Center for Global and Regional Environmental Research, University of Iowa for anthropogenic emissions and from GEIA (Global Emissions Inventory Activity) for biogenic emissions. The GDAPS (Global Data Assimilation and Prediction System) data of six-hour intervals were used for initial and boundary conditions of MM5.

Implementation of marine halogen chemistry into the Community Multiscale Air Quality (CMAQ) model

NASA Astrophysics Data System (ADS)

Gantt, B.; Sarwar, G.

2017-12-01

In two recent studies (Sarwar et al, 2015 and Gantt et al., 2017), the impact of marine halogen (bromine and iodine) chemistry on air quality has been evaluated using the Community Multiscale Air Quality (CMAQ) model. We found that marine halogen chemistry not only has the expected effect of reducing marine boundary layer ozone concentrations, but also reduces ozone in the free troposphere and inland from the coast. In Sarwar et al. (2015), the impact of the halogen chemistry without and with photochemical reactions of higher iodine oxides over the Northern Hemisphere was examined using the coarse horizontal grids of a hemispheric domain. Halogen chemistry without and with the photochemical reactions of higher iodine oxides reduces ozone over seawater by 15% and 48%, respectively. Using the results of the chemistry without the photochemical reactions of higher iodine oxides, we developed a simple first order ozone loss rate and implemented it into the public version of CMAQv52. In Gantt et al. (2017), the impact of the simple first order loss rate as well as the full halogen chemistry without photochemical reactions of higher iodine oxides over the continental United States was examined using finer horizontal grids of the regional domain and boundary conditions from the hemispheric domain with and without marine halogen chemistry. The boundary conditions obtained with the halogen chemistry as well as the simple halogen chemistry reduces ozone along the coast where CMAQ typically overpredicts the concentrations. Development of halogen chemistry in CMAQ has continued with the implementation of several heterogeneous reactions of bromine and iodine species, revised reactions of higher iodine oxides, and a refined marine halogen emissions inventory. Our latest version of halogen chemistry with photochemical reactions of higher iodine oxides reduces ozone by 23% over the seawater. This presentation will discuss the previous and ongoing implementation of revised halogen chemistry in CMAQ and its impacts on air quality.

A new physically-based windblown dust emission ...

EPA Pesticide Factsheets

Dust has significant impacts on weather and climate, air quality and visibility, and human health; therefore, it is important to include a windblown dust emission module in atmospheric and air quality models. In this presentation, we summarize our efforts in development of a physics-based windblown dust emission scheme and its implementation in the CMAQ modeling system. The new model incorporates the effect of the surface wind speed, soil texture, soil moisture, and surface roughness in a physically sound manner. Specifically, a newly developed dynamic relation for the surface roughness length in this model is believed to adequately represent the physics of the surface processes involved in the dust generation. Furthermore, careful attention is paid in integrating the new windblown dust module within the CMAQ to ensure that the required input parameters are correctly configured. The new model is evaluated for the case studies including the continental United States and the Northern hemisphere, and is shown to be able to capture the occurrence of the dust outbreak and the level of the soil concentration. We discuss the uncertainties and limitations of the model and briefly describe our path forward for further improvements. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based

Comparison of CMAQ Modeling Study with Discover-AQ 2014 Aircraft Measurements over Colorado

NASA Astrophysics Data System (ADS)

Tang, Y.; Pan, L.; Lee, P.; Tong, D.; Kim, H. C.; Artz, R. S.

2014-12-01

NASA and NCAR jointly led a recent multiple platform-based (space, air and ground) measurement intensive to study air quality and to validate satellite data. The Discover-AQ/FRAPPE field experiment took place along the Colorado Front Range in July and August, 2014. The air quality modeling team of the NOAA Air Resources Laboratory was one of the three teams that provided real-time air quality forecasting for the campaign. The U.S. EPA Community Multi-scale Air Quality (CMAQ) Model was used with emission inventories based on the data set used by the NOAA National Air Quality Forecasting Capacity (NAQFC). By analyzing the forecast results calculated using aircraft measurements, it was found that CO emissions tended to be overestimated, while ethane emissions were underestimated. Biogenic VOCs were also underpredicted. Due to their relatively high altitude, ozone concentrations in Denver and the surrounding areas are affected by both local emissions and transported ozone. The modeled ozone was highly dependent on the meteorological predictions over this region. The complex terrain over the Rocky Mountains also contributed to the model uncertainty. This study discussed the causes of model biases, the forecast performance under different meteorology, and results from using different model grid resolutions. Several data assimilation techniques were further tested to improve the "post-analysis" performance of the modeling system for the period.

A coupled modeling system for connecting prescribed fire activity data through CMAQ for simulating regional scale air quality

Treesearch

Gary L. Achtemeier; Scott Goodrick; Yongqiang Liu

2005-01-01

The southeastern United Stats - states extending from Virginia to Texas and from the Ohio River southward - (hereafter called the "South") compromise one of the most productive forested areas in the United States. Although the South represents only 24 percent of the U.S. land area, approximately 200 million acres (81 million ha) or 40 percent of the Nation...

CMAQ in the states : a preliminary assessment of the CMAQ program's contribution toward meeting ozone standards

DOT National Transportation Integrated Search

1998-01-08

The Congestion Mitigation and Air Quality Improvement (CMAQ) program provides funds to states for projects designed to help metropolitan areas attain and maintain the national ambient air quality standards (NAAQS). The objective of this analysis is t...

Identification of biased sectors in emission data using a combination of chemical transport model and receptor model

NASA Astrophysics Data System (ADS)

Uranishi, Katsushige; Ikemori, Fumikazu; Nakatsubo, Ryohei; Shimadera, Hikari; Kondo, Akira; Kikutani, Yuki; Asano, Katsuyoshi; Sugata, Seiji

2017-10-01

This study presented a comparison approach with multiple source apportionment methods to identify which sectors of emission data have large biases. The source apportionment methods for the comparison approach included both receptor and chemical transport models, which are widely used to quantify the impacts of emission sources on fine particulate matter of less than 2.5 μm in diameter (PM2.5). We used daily chemical component concentration data in the year 2013, including data for water-soluble ions, elements, and carbonaceous species of PM2.5 at 11 sites in the Kinki-Tokai district in Japan in order to apply the Positive Matrix Factorization (PMF) model for the source apportionment. Seven PMF factors of PM2.5 were identified with the temporal and spatial variation patterns and also retained features of the sites. These factors comprised two types of secondary sulfate, road transportation, heavy oil combustion by ships, biomass burning, secondary nitrate, and soil and industrial dust, accounting for 46%, 17%, 7%, 14%, 13%, and 3% of the PM2.5, respectively. The multiple-site data enabled a comprehensive identification of the PM2.5 sources. For the same period, source contributions were estimated by air quality simulations using the Community Multiscale Air Quality model (CMAQ) with the brute-force method (BFM) for four source categories. Both models provided consistent results for the following three of the four source categories: secondary sulfates, road transportation, and heavy oil combustion sources. For these three target categories, the models' agreement was supported by the small differences and high correlations between the CMAQ/BFM- and PMF-estimated source contributions to the concentrations of PM2.5, SO42-, and EC. In contrast, contributions of the biomass burning sources apportioned by CMAQ/BFM were much lower than and little correlated with those captured by the PMF model, indicating large uncertainties in the biomass burning emissions used in the CMAQ simulations. Thus, this comparison approach using the two antithetical models enables us to identify which sectors of emission data have large biases for improvement of future air quality simulations.

Modeling the Influence of Hemispheric Transport on Trends in ...

EPA Pesticide Factsheets

We describe the development and application of the hemispheric version of the CMAQ to examine the influence of long-range pollutant transport on trends in surface level O3 distributions. The WRF-CMAQ model is expanded to hemispheric scales and multi-decadal model simulations were recently performed for the period spanning 1990-2010 to examine changes in hemispheric air pollution resulting from changes in emissions over this period. Simulated trends in ozone and precursor species concentrations across the U.S. and the northern hemisphere over the past two decades are compared with those inferred from available measurements during this period. Additionally, the decoupled direct method (DDM) in CMAQ is used to estimate the sensitivity of O3 to emissions from different source regions across the northern hemisphere. The seasonal variations in source region contributions to background O3 is then estimated from these sensitivity calculations and will be discussed. A reduced form model combining these source region sensitivities estimated from DDM with the multi-decadal simulations of O3 distributions and emissions trends, is then developed to characterize the changing contributions of different source regions to background O3 levels across North America. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas

Fine Particulate Matter and Cardiovascular Disease ...

EPA Pesticide Factsheets

Background Adverse cardiovascular events have been linked with PM2.5 exposure obtained primarily from air quality monitors, which rarely co-locate with participant residences. Modeled PM2.5 predictions at finer resolution may more accurately predict residential exposure; however few studies have compared results across different exposure assessment methods. Methods We utilized a cohort of 5679 patients who had undergone a cardiac catheterization between 2002–2009 and resided in NC. Exposure to PM2.5 for the year prior to catheterization was estimated using data from air quality monitors (AQS), Community Multiscale Air Quality (CMAQ) fused models at the census tract and 12 km spatial resolutions, and satellite-based models at 10 km and 1 km resolutions. Case status was either a coronary artery disease (CAD) index >23 or a recent myocardial infarction (MI). Logistic regression was used to model odds of having CAD or an MI with each 1-unit (μg/m3) increase in PM2.5, adjusting for sex, race, smoking status, socioeconomic status, and urban/rural status. Results We found that the elevated odds for CAD>23 and MI were nearly equivalent for all exposure assessment methods. One difference was that data from AQS and the census tract CMAQ showed a rural/urban difference in relative risk, which was not apparent with the satellite or 12 km-CMAQ models. Conclusions

METEOROLOGICAL AND TRANSPORT MODELING

EPA Science Inventory

Advanced air quality simulation models, such as CMAQ, as well as other transport and dispersion models, require accurate and detailed meteorology fields. These meteorology fields include primary 3-dimensional dynamical and thermodynamical variables (e.g., winds, temperature, mo...

Effects of emissions change, climate change and long-range transport on regional modeling of future U.S. particulate matter pollution and speciation

NASA Astrophysics Data System (ADS)

He, Hao; Liang, Xin-Zhong; Wuebbles, Donald J.

2018-04-01

This study investigates the future U.S. PM2.5 pollution under multiple emissions scenarios, climate states, and long-range transport (LRT) effects using the regional Community Multi-scale Air Quality (CMAQ) model integrated with a regional climate model. CMAQ with fixed chemical lateral boundary conditions (LBCs) successfully reproduces the present-day PM2.5 pollution and its major species in rural and suburban areas, but has some discrepancies in urban areas such as the Los Angeles Basin, where detailed emissions and meteorology conditions cannot be resolved by the 30 km grid. Its performance is slightly worsened when using dynamic chemical LBCs from global chemical transport model (CTM) simulations, which provide cleaner conditions into the CMAQ lateral boundaries. Under future Intergovernmental Panel on Climate Change (IPCC) emission scenarios, CMAQ projects large PM2.5 reductions (∼40% for A1B and ∼20% for A1Fi scenario) in the eastern United States, but slight to moderate increases (∼5% for A1B and ∼10% for A1Fi) in the western United States. The projected increases are particularly large (up to 30%) near the Mexico-U.S. border, suggesting that Mexico is a major source for future U.S. PM2.5 pollution. The effect from climate change alone is estimated to increase PM2.5 levels ubiquitously (∼5% for both A1B and A1Fi) over the United States, except for a small decrease in the Houston, Texas area, where anthropogenic non-methane volatile organic compounds (NMVOCs) emissions dominate. This climate penalty, however, is substantially smaller than effects of emissions change, especially in the eastern United States. Future PM2.5 pollution is affected substantially (up to -20%) by changes in SO2 emissions and moderately (3-5%) by changes in NOx and NH3 emissions. The long-range transport (LRT) effects, which are estimated by comparing CMAQ simulations with fixed and dynamic LBCs, are regional dependent, causing up to 10-20% decrease over the western United States in future summertime PM2.5 pollution. Therefore, it is important to consider the relative contributions of emissions scenarios, climate conditions, and LRT to the major PM2.5 components in future U.S. air quality regulation.

US EPA 2012 Air Quality Fused Surface for the Conterminous U.S. Map Service

EPA Pesticide Factsheets

This web service contains a polygon layer that depicts fused air quality predictions for 2012 for census tracts in the conterminous United States. Fused air quality predictions (for ozone and PM2.5) are modeled using a Bayesian space-time downscaling fusion model approach described in a series of three published journal papers: 1) (Berrocal, V., Gelfand, A. E. and Holland, D. M. (2012). Space-time fusion under error in computer model output: an application to modeling air quality. Biometrics 68, 837-848; 2) Berrocal, V., Gelfand, A. E. and Holland, D. M. (2010). A bivariate space-time downscaler under space and time misalignment. The Annals of Applied Statistics 4, 1942-1975; and 3) Berrocal, V., Gelfand, A. E., and Holland, D. M. (2010). A spatio-temporal downscaler for output from numerical models. J. of Agricultural, Biological,and Environmental Statistics 15, 176-197) is used to provide daily, predictive PM2.5 (daily average) and O3 (daily 8-hr maximum) surfaces for 2012. Summer (O3) and annual (PM2.5) means calculated and published. The downscaling fusion model uses both air quality monitoring data from the National Air Monitoring Stations/State and Local Air Monitoring Stations (NAMS/SLAMS) and numerical output from the Models-3/Community Multiscale Air Quality (CMAQ). Currently, predictions at the US census tract centroid locations within the 12 km CMAQ domain are archived. Predictions at the CMAQ grid cell centroids, or any desired set of locations co

Characteristics of New CMAQ Deposition Series of 2002 to 2011 for Critical Loads

EPA Science Inventory

The new CMAQ deposition time series from 2002 to 2011 of wet and dry nitrogen and sulfur deposition is characterized and evaluated in this presentation. The time series examines annual deposition across regions of the continental US. The CMAQ version with bi-directional ammonia...

AN EXAMINATION OF THE CMAQ SIMULATIONS OF THE WET DEPOSITION OF AMMONIUM FROM A BAYESIAN PERSPECTIVE

EPA Science Inventory

The objective of this study is to ascertain the effects of precipitation simulations and emissions on CMAQ simulations of deposition. In both seasons, CMAQ tends to underpredict the deposition amounts. Based on the co-located measurements of ammonium wet deposition and precipita...

CMAQ and NPS : exploring the applicability of the Congestion Mitigation and Air Quality Improvement program to NPS transit

DOT National Transportation Integrated Search

2014-03-06

The Congestion Mitigation and Air Quality Improvement (CMAQ) Program is a funding program that was most recently : re-authorized in Moving Ahead for Progress in the 21st Century. CMAQ offers a potential funding opportunity for NPS park units : with e...

Comparison of exposure estimation methods for air pollutants: ambient monitoring data and regional air quality simulation.

PubMed

Bravo, Mercedes A; Fuentes, Montserrat; Zhang, Yang; Burr, Michael J; Bell, Michelle L

2012-07-01

Air quality modeling could potentially improve exposure estimates for use in epidemiological studies. We investigated this application of air quality modeling by estimating location-specific (point) and spatially-aggregated (county level) exposure concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM(2.5)) and ozone (O(3)) for the eastern U.S. in 2002 using the Community Multi-scale Air Quality (CMAQ) modeling system and a traditional approach using ambient monitors. The monitoring approach produced estimates for 370 and 454 counties for PM(2.5) and O(3), respectively. Modeled estimates included 1861 counties, covering 50% more population. The population uncovered by monitors differed from those near monitors (e.g., urbanicity, race, education, age, unemployment, income, modeled pollutant levels). CMAQ overestimated O(3) (annual normalized mean bias=4.30%), while modeled PM(2.5) had an annual normalized mean bias of -2.09%, although bias varied seasonally, from 32% in November to -27% in July. Epidemiology may benefit from air quality modeling, with improved spatial and temporal resolution and the ability to study populations far from monitors that may differ from those near monitors. However, model performance varied by measure of performance, season, and location. Thus, the appropriateness of using such modeled exposures in health studies depends on the pollutant and metric of concern, acceptable level of uncertainty, population of interest, study design, and other factors. Copyright © 2012 Elsevier Inc. All rights reserved.

Simulation of the Indirect Radiative Forcing of Climate Due to Aerosols by the Two-Way Coupled WRF-CMAQ over the Eastern United States

EPA Science Inventory

In this study, the shortwave cloud forcing (SWCF) and longwave cloud forcing (LWCF) are estimated with the newly developed two-way coupled WRF-CMAQ over the eastern United States. Preliminary indirect aerosol forcing has been successfully implemented in WRF-CMAQ. The comparisons...

Evaluation of biogenic emission flux and its impact on oxidants and inorganic aerosols in East Asia

NASA Astrophysics Data System (ADS)

Han, K. M.; Song, C. H.; Park, R. S.; Woo, J.; Kim, H.

2010-12-01

As a major precursor during the summer season, biogenic species are of primary importance in the ozone and SOAs (secondary organic aerosols) formations. Isoprene and mono-terpene also influence the level of inorganic aerosols (i.e. sulfate and nitrate) by controlling OH radicals. However, biogenic emission fluxes are highly uncertain in East Asia. While isoprene emission fluxes from the GEIA (Global Emissions Inventory Activity) and POET (Precursors of Ozone and their Effects in the Troposphere) inventories estimate approximately 20 Tg yr-1 in East Asia, those from the MEGAN (Model of Emissions of Gases and Aerosols from Nature) and MOHYCAN (MOdel for Hydrocarbon emissions by the CANopy) estimate approximately 10 Tg yr-1 and 5 Tg yr-1, respectively. In order to evaluate and/or quantify the magnitude of biogenic emission fluxes over East Asia, the tropospheric HCHO columns obtained from the GOME (Global Ozone Monitoring Experiment) observations were compared with the HCHO columns from the CMAQ (Community Multi-scale Air Quality) simulations over East Asia. In this study, US EPA Models-3/CMAQ v4.5.1 model simulation using the ACE-ASIA (Asia Pacific Regional Aerosol Characterization Experiment) emission inventory for anthropogenic pollutants and GEIA, POET, MEGAN, and MOHYCAN emission inventories for biogenic species was carried out in conjunction with the Meteorological fields generated from the PSU/NCAR MM5 (Pennsylvania state University/National Center for Atmospheric Research Meso-scale Model 5) model for the summer episodes of the year 2002. In addition to an evaluation of the biogenic emission flux, we investigated the impact of the uncertainty in biogenic emission inventory on inorganic aerosol formations and variations of oxidants (OH, O3, and H2O2) in East Asia. In this study, when the GEIA and POET emission inventories are used, the CMAQ-derived HCHO columns are highly overestimated over East Asia, particularly South China compared with GOME-derived HCHO columns. The CMAQ-derived HCHO columns using the MOHYCAN emission inventory have similar values with the GOME-derived HCHO columns over East Asia. Also, differences in biogenic emission fluxes lead to changes in the levels of nitrates by changing the OH radical concentrations.

Impacts of updated emission inventories on source apportionment of fine particle and ozone over the southeastern U.S.

NASA Astrophysics Data System (ADS)

Zhang, Yang; Wang, Wei; Wu, Shiang-Yuh; Wang, Kai; Minoura, Hiroaki; Wang, Zifa

2014-05-01

As the U.S. Environmental Protection Agency updates the National Emission Inventory (NEI), the source contributions (SC) of major source sectors to major pollutants based on source apportionment techniques should be periodically reassessed to reflect changes in SCs due to changes in emissions. This work assesses emission updates from the 1999 NEI version 2 (NEI99v2) and the 2005 NEI (NEI05) and the resulting differences in SCs using the two inventories. Large differences exist in the emissions of nitrogen oxide, formaldehyde, ammonia, terpene, and primary PM2.5 between NEI99v2 and NEI05. Differences in emissions lead to differences in model performance and source appointment. SCs of ten major source categories to fine particulate matter (PM2.5) are estimated using the Community Multiscale Air Quality modeling system with the Brute Force Method (CMAQ/BFM) andNEI05and compared with those obtained previously using CMAQ/BFM with NEI99v2. In January, compared to CMAQ/BFM (NEI99v2), CMAQ/BFM (NEI05) shows that miscellaneous areas, biomass burning, and coal combustion remain the top three contributors to PM2.5 but with different ranking and higher SCs (17.7%, 16.0%, and 14.1% for NEI05 vs. 11.8%, 13.7%, and 10.8% for NEI99v2, respectively). In July, coal combustion, miscellaneous areas, and industrial processes remain the top three with higher SCs (41.9%, 14.1%, and 8.8% for NEI05 vs.30.8%, 8.9%, and 6.9% for NEI99v2, respectively). Those changes in SCs are attributed to increased primary PM2.5 (PPM) emissions in NEI05 and increases in relative contributions of miscellaneous areas and coal combustion to the emissions of PPM, NH3, and SO2.SCs from diesel and gasoline vehicles decrease in both months, due to decreased contributions of gasoline vehicles to SO2 and NH3 emissions and those of diesel vehicles to NOx and PPM emissions. Compared with CMAQ/BFM (NEI99v2), SCs from other combustion and biomass burning are higher in Florida, due to substantial increases in formaldehyde and PPM emissions in NEI05, resulting from higher wildfire emissions and state emission updates. SCs from industrial processes increase and those from diesel and gasoline vehicles decrease in urban areas. SCs of O3 from most sources in both months increase due to a large increase in their contributions to NOx emissions, except for diesel vehicles in July, which decreases over domainwide due to a relative decrease in NOx emissions. These results provide valuable information for policy makers to formulate and adjust emission control strategies as the NEI is continuously updated.

Bulgarian emergency responce system for release of hazardous pollutants - design and first test of the preparedness mode

NASA Astrophysics Data System (ADS)

Ganev, Kostadin; Todorova, Angelina; Jordanov, Georgi; Gadzhev, Georgi; Syrakov, Dimiter; Miloshev, Nikolai; Prodanova, Maria

2010-05-01

The NATO SfP N 981393 project aims at developing of a unified Balkan region oriented modelling system for operational response to accidental releases of harmful gases in the atmosphere, which would be able to: 1.Perform highly acurate and reliable risk analysis and assessment for selected "hot spots"; 2.Support the emergency fast decisions with short-term regional scale forecast of the propagation of harmful gasesin case of accidental release; 3.Perform, in an off-line mode, a more detailed and comprehensive analysis of the possible longer-term impacts on the environment and human health and make the results available to the authorities and the public. The present paper describes the set up and the testing of the system, mainly focusing on the risk analysis mode. The modeling tool used in the system is the US EPA Models-3 System: WRF, CMAQ and SMOKE (partly). The CB05 toxic chemical mechanism, including chlorine reactions, is employed. The emission input exploits the high-resolution TNO emission inventory. The meteorological pre-processor WRF is driven by NCAR Final Reanalysis data and performs calculations in 3 nested domains, covering respectively the regions of South-Eastern Europe, Bulgaria, and the area surrounding the particular site. The risk assessment for the region of "Vereja Him" factory, Jambol, Bulgaria is performed on the basis of one-year long model calculations. The calculations with CMAQ chemical transport model are performed for the two inner domains. An ammount of 25 tons of chlorine is released two times daily in the innermost domain, and sepаrate calculations are performed for every release. The results are averaged over one year in order to evaluate the probability of exceeding some regulatory treshold value in each grid point. The completion of this task in a relatively short period of time was made possible by using the newly developed Grid computational environment, which allows for shared use of facilities in the research community.

A Spectral Method for Spatial Downscaling

PubMed Central

Reich, Brian J.; Chang, Howard H.; Foley, Kristen M.

2014-01-01

Summary Complex computer models play a crucial role in air quality research. These models are used to evaluate potential regulatory impacts of emission control strategies and to estimate air quality in areas without monitoring data. For both of these purposes, it is important to calibrate model output with monitoring data to adjust for model biases and improve spatial prediction. In this article, we propose a new spectral method to study and exploit complex relationships between model output and monitoring data. Spectral methods allow us to estimate the relationship between model output and monitoring data separately at different spatial scales, and to use model output for prediction only at the appropriate scales. The proposed method is computationally efficient and can be implemented using standard software. We apply the method to compare Community Multiscale Air Quality (CMAQ) model output with ozone measurements in the United States in July 2005. We find that CMAQ captures large-scale spatial trends, but has low correlation with the monitoring data at small spatial scales. PMID:24965037

The Use of AMET & Automated Scripts for Model Evaluation

EPA Science Inventory

Brief overview of EPA’s new CMAQ website to be launched publically in June, 2017. Details on the upcoming release of the Atmospheric Model Evaluation Tool (AMET) and the creation of automated scripts for post-processing and evaluating air quality model data.

URBAN MORPHOLOGY FOR HOUSTON TO DRIVE MODELS-3/CMAQ AT NEIGHBORHOOD SCALES

EPA Science Inventory

Air quality simulation models applied at various horizontal scales require different degrees of treatment in the specifications of the underlying surfaces. As we model neighborhood scales ( 1 km horizontal grid spacing), the representation of urban morphological structures (e....

AIR QUALITY FORECAST DATABASE AND ANALYSIS

EPA Science Inventory

In 2003, NOAA and EPA signed a Memorandum of Agreement to collaborate on the design and implementation of a capability to produce daily air quality modeling forecast information for the U.S. NOAA's ETA meteorological model and EPA's Community Multiscale Air Quality (CMAQ) model ...

Evolution of Air Quality Model at the US EPA

EPA Science Inventory

At the US EPA, we have developed an air quality model, CMAQ, in the past 20+ years. Throughout the years, the model has been upgraded with respect to advancement of science. We have extended the model from regional to hemispheric. We have coupled it with meteorological model, WR...

Impact of WRF model PBL schemes on air quality simulations over Catalonia, Spain.

PubMed

Banks, R F; Baldasano, J M

2016-12-01

Here we analyze the impact of four planetary boundary-layer (PBL) parametrization schemes from the Weather Research and Forecasting (WRF) numerical weather prediction model on simulations of meteorological variables and predicted pollutant concentrations from an air quality forecast system (AQFS). The current setup of the Spanish operational AQFS, CALIOPE, is composed of the WRF-ARW V3.5.1 meteorological model tied to the Yonsei University (YSU) PBL scheme, HERMES v2 emissions model, CMAQ V5.0.2 chemical transport model, and dust outputs from BSC-DREAM8bv2. We test the performance of the YSU scheme against the Assymetric Convective Model Version 2 (ACM2), Mellor-Yamada-Janjic (MYJ), and Bougeault-Lacarrère (BouLac) schemes. The one-day diagnostic case study is selected to represent the most frequent synoptic condition in the northeast Iberian Peninsula during spring 2015; regional recirculations. It is shown that the ACM2 PBL scheme performs well with daytime PBL height, as validated against estimates retrieved using a micro-pulse lidar system (mean bias=-0.11km). In turn, the BouLac scheme showed WRF-simulated air and dew point temperature closer to METAR surface meteorological observations. Results are more ambiguous when simulated pollutant concentrations from CMAQ are validated against network urban, suburban, and rural background stations. The ACM2 scheme showed the lowest mean bias (-0.96μgm -3 ) with respect to surface ozone at urban stations, while the YSU scheme performed best with simulated nitrogen dioxide (-6.48μgm -3 ). The poorest results were with simulated particulate matter, with similar results found with all schemes tested. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Integrating Measurement Based New Knowledge on Wildland Fire Emissions and Chemistry into the AIRPACT Air Quality Forecasting for the Pacific Northwest

NASA Astrophysics Data System (ADS)

Nergui, T.; Lee, Y.; Chung, S. H.; Lamb, B. K.; Yokelson, R. J.; Barsanti, K.

2017-12-01

A number of chamber and field measurements have shown that atmospheric organic aerosols and their precursors produced from wildfires are significantly underestimated in the emission inventories used for air quality models for various applications such as regulatory strategy development, impact assessments of air pollutants, and air quality forecasting for public health. The AIRPACT real-time air quality forecasting system consistently underestimates surface level fine particulate matter (PM2.5) concentrations in the summer at both urban and rural locations in the Pacific Northwest, primarily result of errors in organic particulate matter. In this work, we implement updated chemical speciation and emission factors based on FLAME-IV (Fourth Fire Lab at Missoula Experiment) and other measurements in the Blue-Sky fire emission model and the SMOKE emission preprocessor; and modified parameters for the secondary organic aerosol (SOA) module in CMAQ chemical transport model of the AIRPACT modeling system. Simulation results from CMAQ version 5.2 which has a better treatment for anthropogenic SOA formation (as a base case) and modified parameterization used for fire emissions and chemistry in the model (fire-soa case) are evaluated against airborne measurements downwind of the Big Windy Complex Fire and the Colockum Tarps Fire, both of which occurred in the Pacific Northwest in summer 2013. Using the observed aerosol chemical composition and mass loadings for organics, nitrate, sulfate, ammonium, and chloride from aircraft measurements during the Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS) and the Biomass Burning Observation Project (BBOP), we assess how new knowledge gained from wildfire measurements improve model predictions for SOA and its contribution to the total mass of PM2.5 concentrations.

WRF-CMAQ simulations of Aerosol Direct Effects

EPA Pesticide Factsheets

CMAQ and WRF output filesThis dataset is associated with the following publication:Gan, C., J. Pleim , R. Mathur , C. Hogrefe , C.N. Long, J. Xing, D. Wong , R. Gilliam , and C. Wei. Assessment of long-term WRF–CMAQ simulations for understanding direct aerosol effects on radiation "brightening" in the United States. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 15: 12193-12209, (2015).

A FAST BAYESIAN METHOD FOR UPDATING AND FORECASTING HOURLY OZONE LEVELS

EPA Science Inventory

A Bayesian hierarchical space-time model is proposed by combining information from real-time ambient AIRNow air monitoring data, and output from a computer simulation model known as the Community Multi-scale Air Quality (Eta-CMAQ) forecast model. A model validation analysis shows...

Simulation of atmospheric oxidation capacity in Houston, Texas

EPA Science Inventory

Air quality model simulations are performed and evaluated for Houston using the Community Multiscale Air Quality (CMAQ) model. The simulations use two different emissions estimates: the EPA 2005 National Emissions Inventory (NEI) and the Texas Commission on Environmental Quality ...

Dynamic evaluation of two decades of WRF-CMAQ ozone ...

EPA Pesticide Factsheets

Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)– Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to assess how well the changes in observed ozone air quality are simulated by the model. The changes induced by variations in meteorology and/or emissions are also evaluated during the same timeframe using spectral decomposition of observed and modeled ozone time series with the aim of identifying the underlying forcing mechanisms that control ozone exceedances and making informed recommendations for the optimal use of regional-scale air quality models. The evaluation is focused on the warm season's (i.e., May–September) daily maximum 8-hr (DM8HR) ozone concentrations, the 4th highest (4th) and average of top 10 DM8HR ozone values (top10), as well as the spectrally-decomposed components of the DM8HR ozone time series using the Kolmogorov-Zurbenko (KZ) filter. Results of the dynamic evaluation are presented for six regions in the U.S., consistent with the National Oceanic and Atmospheric Administration (NOAA) climatic regions. During the earlier 11-yr period (1990–2000), the simulated and observed trends are not statistically significant. During the more recent 2000–2010 period, all trends are statistically significant and WRF-CMAQ captures the observed trend in most regions. Given large n

MODEL DEVELOPMENT FOR FY08 CMAQ RELEASE

EPA Science Inventory

This task provides credible state of the art air quality models and guidance for use in implementation of National Ambient Air Quality Standards for ozone and PM. This research effort is to develop and improve air quality models, such as the Community Multiscale Air Quality (CMA...

WILDLAND FIRE EMISSION MODELING FOR CMAQ: AN UPDATE

EPA Science Inventory

This paper summarizes recent efforts to improve the methods used for modeling wild land fire emissions both for retrospective modeling and real-time forecasting. These improvements focus on the temporal and spatial resolution of the activity data as well as the methods to estimat...

STOCHASTIC DESCRIPTION OF SUBGRID POLLUTANT VARIABILITY IN CMAQ

EPA Science Inventory

This paper describes a tool for investigating and describing fine scale spatial variability in model concentration fields with the goal of improving the use of air quality models for driving exposure modeling to assess human risk to hazardous air pollutants or air toxics. Region...

COMPARISONS OF SPATIAL PATTERNS OF WET DEPOSITION TO MODEL PREDICTIONS

EPA Science Inventory

The Community Multiscale Air Quality model, (CMAQ), is a "one-atmosphere" model, in that it uses a consistent set of chemical reactions and physical principles to predict concentrations of primary pollutants, photochemical smog, and fine aerosols, as well as wet and dry depositi...

COMPARISON OF SPATIAL PATTERNS OF POLLUTANT DISTRIBUTION WITH CMAQ PREDICTIONS

EPA Science Inventory

One indication of model performance is the comparison of spatial patterns of pollutants, either as concentration or deposition, predicted by the model with spatial patterns derived from measurements. If the spatial patterns produced by the model are similar to the observations i...

Impacts of Lateral Boundary Conditions on U.S. Ozone Modeling Analyses

EPA Science Inventory

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, we perform annual simulations over North America with chemical boundary conditions prepared from two global models (GEOS-CHEM and Hemispheric CMAQ). Results indicate that the impac...

Simulation of summer ozone episodes in Southeast Louisiana during 2006-2015

NASA Astrophysics Data System (ADS)

Guo, H.; Zhang, H.

2017-12-01

Southeast Louisiana experiences high ozone (O3) events due to immense emissions from industrial and urban sources and unique meteorology conditions of high temperatures, intensive solar radiation and land-sea breeze circulation. The Community Multi-scale Air Quality (CMAQ) model with modified photochemical mechanism is used to investigate the contributions of regional transport to ozone (O3) and its precursors to Southeast Louisiana in summer months from 2006 to 2015. The meteorological and CMAQ model performance are validated. Spatial and temporal variations of O3 are investigated during summer episodes in 10 years. Contributions of different source types and regions to 1 hour O3 are also quantified. Changes in the contributions of different source types and regions are also obtained to help design intelligent control measures.

A proof-of-concept for linking the global meteorological model, MPAS-A with the air quality model, CMAQ

EPA Science Inventory

Researchers who perform air quality modeling studies usually do so on a regional scale. Typically, the boundary conditions are generated by another model which might have a different chemical mechanism, spatial resolution, and/or map projection. Hence, a necessary conversion/inte...

An Analysis of Simulated Wet Deposition of Mercury from the North American Mercury Model Intercomparison Study

EPA Science Inventory

A previous intercomparison of atmospheric mercury models in North America has been extended to compare simulated and observed wet deposition of mercury. Three regional-scale atmospheric mercury models were tested; CMAQ, REMSAD and TEAM. These models were each employed using thr...

Global and Regional Modeling of Long-Range Transport and Intercontinental Source-Receptor Linkages

EPA Science Inventory

In this study, we compare air quality over North America simulated by the C-IFS global model and the CMAQ regional model driven by boundary conditions from C-IFS against surface and upper air observations. Results indicate substantial differences in model performance for surface ...

“Modeling Trends in Air Pollutant Concentrations over the Northern Hemisphere Using the Coupled WRF-CMAQ Model”

EPA Science Inventory

Regional model calculations over annual cycles have pointed to the need for accurately representing impacts of long-range transport. Linking regional and global scale models have met with mixed success as biases in the global model can propagate and influence regional calculatio...

A photosynthesis-based two-leaf canopy stomatal conductance model for meteorology and air quality modeling with WRF/CMAQ PX LSM

EPA Science Inventory

A coupled photosynthesis-stomatal conductance model with single-layer sunlit and shaded leaf canopy scaling is implemented and evaluated in a diagnostic box model with the Pleim-Xiu land surface model (PX LSM) and ozone deposition model components taken directly from the meteorol...

Impact of Lightning-NO Emissions on Summertime U.S. Photochemistry as Determined Using the CMAQ Model with NLDN-Constrained Flash Rates

NASA Technical Reports Server (NTRS)

Allen, Dale; Pickering, Kenneth; Pinder, Robert; Koshak, William; Pierce, Thomas

2011-01-01

Lightning-NO emissions are responsible for 15-30 ppbv enhancements in upper tropospheric ozone over the eastern United States during the summer time. Enhancements vary from year to year but were particularly large during the summer of 2006, a period during which meteorological conditions were particularly conducive to ozone formation. A lightning-NO parameterization has been developed that can be used with the CMAQ model. Lightning-NO emissions in this scheme are assumed to be proportional to convective precipitation rate and scaled so that monthly average flash rates in each grid box match National Lightning Detection Network (NLDN) observed flash rates after adjusting for climatological intracloud to cloud-to-ground (IC/CG) ratios. The contribution of lightning-NO emissions to eastern United States NOx and ozone distributions during the summer of 2006 will be evaluated by comparing results of 12- km CMAQ simulations with and without lightning-NO emissions to measurements from the IONS field campaign and to satellite retrievals from the Tropospheric Emission Spectrometer (TES) and the Ozone Monitoring Instrument (OMI) aboard the Aura satellite. Special attention will be paid to the impact of the assumed vertical distribution of emissions on upper tropospheric NOx and ozone amounts.

COMMUNITY SCALE AIR TOXICS MODELING WITH CMAQ

EPA Science Inventory

Consideration and movement for an urban air toxics control strategy is toward a community, exposure and risk-based modeling approach, with emphasis on assessments of areas that experience high air toxic concentration levels, the so-called "hot spots". This strategy will requir...

Constraining ammonia dairy emissions during NASA DISCOVER-AQ California: surface and airborne observation comparisons with CMAQ simulations

NASA Astrophysics Data System (ADS)

Miller, D. J.; Liu, Z.; Sun, K.; Tao, L.; Nowak, J. B.; Bambha, R.; Michelsen, H. A.; Zondlo, M. A.

2014-12-01

Agricultural ammonia (NH3) emissions are highly uncertain in current bottom-up inventories. Ammonium nitrate is a dominant component of fine aerosols in agricultural regions such as the Central Valley of California, especially during winter. Recent high resolution regional modeling efforts in this region have found significant ammonium nitrate and gas-phase NH3 biases during summer. We compare spatially-resolved surface and boundary layer gas-phase NH3 observations during NASA DISCOVER-AQ California with Community Multi-Scale Air Quality (CMAQ) regional model simulations driven by the EPA NEI 2008 inventory to constrain wintertime NH3 model biases. We evaluate model performance with respect to aerosol partitioning, mixing and deposition to constrain contributions to modeled NH3 concentration biases in the Central Valley Tulare dairy region. Ammonia measurements performed with an open-path mobile platform on a vehicle are gridded to 4 km resolution hourly background concentrations. A peak detection algorithm is applied to remove local feedlot emission peaks. Aircraft NH3, NH4+ and NO3- observations are also compared with simulations extracted along the flight tracks. We find NH3 background concentrations in the dairy region are underestimated by three to five times during winter and NH3 simulations are moderately correlated with observations (r = 0.36). Although model simulations capture NH3 enhancements in the dairy region, these simulations are biased low by 30-60 ppbv NH3. Aerosol NH4+ and NO3- are also biased low in CMAQ by three and four times respectively. Unlike gas-phase NH3, CMAQ simulations do not capture typical NH4+ or NO3- enhancements observed in the dairy region. In contrast, boundary layer height simulations agree well with observations within 13%. We also address observational constraints on simulated NH3 deposition fluxes. These comparisons suggest that NEI 2008 wintertime dairy emissions are underestimated by a factor of three to five. We test sensitivity to emissions by increasing the NEI 2008 NH3 emissions uniformly across the dairy region and evaluate the impact on modeled concentrations. These results are applicable to improving predictions of ammoniated aerosol loading and highlight the value of mobile platform spatial NH3 measurements to constrain emission inventories.

Evaluation of the Community Multi-scale Air Quality Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Development and application of air quality models at the U.S. EPA

EPA Science Inventory

Overview of the development and application of air quality models at the U.S. EPA, particularly focused on the development and application of the Community Multiscale Air Quality (CMAQ) model developed within the Computation Exposure Division (CED) of the National Exposure Resear...

MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL AEROSOL COMPONENT 2. MODEL EVALUATION

EPA Science Inventory

Ambient air concentrations of particulate matter (atmospheric suspensions of solid of liquid materials, i.e., aerosols) continue to be a major concern for the U.S. Environmental Protection Agency (EPA). High particulate matter (PM) concentrations are associated not only with adv...

“AQMEII Phase 2: Overview and WRF/CMAQ Application over North America”.

EPA Science Inventory

This presentation provides an overview of the second phase of the Air Quality Model Evaluation International Initative (AQMEII). Activities in this phase are focused on the application and evaluation of coupled meteorology-chemistry models to assess how well these models can simu...

Linking Global to Regional Models to Assess Future Climate Impacts on Surface Ozone Concentrations in the United States

EPA Science Inventory

The UCD sectional aerosol model has been coupled to the CMAQ air quality model and used to simulate air quality in Tampa, Florida. Sea salt emissions are parameterized as a function of modeled wind speed and relative humidity. Modeled aerosol sulfate, nitrate, ammonium, sodium,...

Impacts of Four SO2 Oxidation Pathways on Wintertime Sulfate Concentrations

NASA Astrophysics Data System (ADS)

Sarwar, G.; Fahey, K.; Zhang, Y.; Kang, D.; Mathur, R.; Xing, J.; Wei, C.; Cheng, Y.

2017-12-01

Air quality models tend to under-estimate winter-time sulfate concentrations compared to observed data. Such under-estimations are particularly acute in China where very high concentrations of sulfate have been measured. Sulfate is produced by oxidation of sulfur dioxide (SO2) in gas-phase by hydroxyl radical and in aqueous-phase by hydrogen peroxide, ozone, etc. and most air quality models employ such typical reactions. Several additional SO2 oxidation pathways have recently been proposed. Heterogeneous reaction on dust has been suggested to be an important sink for SO2. Oxidation of SO2 on fine particles in presence of nitrogen dioxide (NO2) and ammonia (NH3) at high relative humidity has been implicated for sulfate formation in Chinese haze and London fog. Reactive nitrogen chemistry in aerosol water has also been suggested to produce winter-time sulfate in China. Specifically, high aerosol water can trap SO2 which can be subsequently oxidized by NO2 to form sulfate. Aqueous-phase (in-cloud) oxidation of SO2 by NO2 can also produce sulfate. Here, we use the hemispheric Community Multiscale Air Quality (CMAQ) modeling system to examine the potential impacts of these SO2 oxidation pathways on sulfate formation. We use anthropogenic emissions from the Emissions Database for Global Atmospheric Research and biogenic emissions from Global Emissions InitiAtive. We performed simulations without and with these SO2 oxidation pathways for October-December of 2014 using meteorological fields obtained from the Weather Research and Forecasting model. The standard CMAQ model contains one gas-phase chemical reaction and five aqueous-phase chemical reactions for SO2 oxidation. We implement four additional SO2 oxidation pathways into the CMAQ model. Our preliminary results suggest that the dust chemistry enhances mean sulfate over parts of China and Middle-East, the in-cloud SO2 oxidation by NO2 enhances sulfate over parts of western Europe, oxidation of SO2 by NO2 and NH3 on fine particles enhances sulfate only over parts of China, and SO2 oxidation by NO2 in aerosol water enhances sulfate only over parts of China by >5%. We will present a detailed analysis of the results and a comparison of model predictions with available observed data.

STATUS AND PROGRESS IN PARTICULATE MATTER FORECASTING: INITIAL APPLICATION OF THE ETA- CMAQ FORECAST MODEL

EPA Science Inventory

This presentation reviews the status and progress in forecasting particulate matter distributions. The shortcomings in representation of particulate matter formation in current atmospheric chemistry/transport models are presented based on analyses and detailed comparisons with me...

REVISED TREATMENT OF N2 O5 HYDROLYSIS IN CMAQ

EPA Science Inventory

In this presentation, revised treatment of homogeneous and heterogeneous hydrolysis of dinitrogen pentoxide in the Community Multiscale Air Quality model version 4.6 are described. A series of model sensitivity tests are conducted and compared with observations of total atmosphe...

Optimal interpolation schemes to constrain pmPM2.5 in regional modeling over the United States

NASA Astrophysics Data System (ADS)

Sousan, Sinan Dhia Jameel

This thesis presents the use of data assimilation with optimal interpolation (OI) to develop atmospheric aerosol concentration estimates for the United States at high spatial and temporal resolutions. Concentration estimates are highly desirable for a wide range of applications, including visibility, climate, and human health. OI is a viable data assimilation method that can be used to improve Community Multiscale Air Quality (CMAQ) model fine particulate matter (PM2.5) estimates. PM2.5 is the mass of solid and liquid particles with diameters less than or equal to 2.5 µm suspended in the gas phase. OI was employed by combining model estimates with satellite and surface measurements. The satellite data assimilation combined 36 x 36 km aerosol concentrations from CMAQ with aerosol optical depth (AOD) measured by MODIS and AERONET over the continental United States for 2002. Posterior model concentrations generated by the OI algorithm were compared with surface PM2.5 measurements to evaluate a number of possible data assimilation parameters, including model error, observation error, and temporal averaging assumptions. Evaluation was conducted separately for six geographic U.S. regions in 2002. Variability in model error and MODIS biases limited the effectiveness of a single data assimilation system for the entire continental domain. The best combinations of four settings and three averaging schemes led to a domain-averaged improvement in fractional error from 1.2 to 0.97 and from 0.99 to 0.89 at respective IMPROVE and STN monitoring sites. For 38% of OI results, MODIS OI degraded the forward model skill due to biases and outliers in MODIS AOD. Surface data assimilation combined 36 × 36 km aerosol concentrations from the CMAQ model with surface PM2.5 measurements over the continental United States for 2002. The model error covariance matrix was constructed by using the observational method. The observation error covariance matrix included site representation that scaled the observation error by land use (i.e. urban or rural locations). In theory, urban locations should have less effect on surrounding areas than rural sites, which can be controlled using site representation error. The annual evaluations showed substantial improvements in model performance with increases in the correlation coefficient from 0.36 (prior) to 0.76 (posterior), and decreases in the fractional error from 0.43 (prior) to 0.15 (posterior). In addition, the normalized mean error decreased from 0.36 (prior) to 0.13 (posterior), and the RMSE decreased from 5.39 µg m-3 (prior) to 2.32 µg m-3 (posterior). OI decreased model bias for both large spatial areas and point locations, and could be extended to more advanced data assimilation methods. The current work will be applied to a five year (2000-2004) CMAQ simulation aimed at improving aerosol model estimates. The posterior model concentrations will be used to inform exposure studies over the U.S. that relate aerosol exposure to mortality and morbidity rates. Future improvements for the OI techniques used in the current study will include combining both surface and satellite data to improve posterior model estimates. Satellite data have high spatial and temporal resolutions in comparison to surface measurements, which are scarce but more accurate than model estimates. The satellite data are subject to noise affected by location and season of retrieval. The implementation of OI to combine satellite and surface data sets has the potential to improve posterior model estimates for locations that have no direct measurements.

Spatio-temporal PM and AOD estimations over Northeast Asia during DRAGON NE-Asia campaign

NASA Astrophysics Data System (ADS)

Park, M.; Song, C.; Kim, J.

2013-12-01

Particulate matter (PM) is closely related to human health, air quality, and climate changes. It has been directly measured on the surface level. However, ground-based measurements have a limitation in spatial coverage of PM concentrations. In order to overcome this spatial limitation of ground measurements, AOD, which is considered as a proxy to PM concentration, was used in this study. AOD was first utilized to figure out the characteristics of PM and was then used to estimate the PM concentrations in Northeast Asia during the DRAGON Northeast-Asia campaign (March-May 2012), using CMAQ-estimated AOD, COMS/GOCI-retrieved AOD, and the AOD data from the DRAGON NE-Asia campaign. First of all, current emission inventories (MEIC and INTEX-B based emission inventories) were evaluated to improve CMAQ modeling results. Next, several algorithms to convert aerosol composition to AOD were evaluated using intensive measurement data from the DRAGON NE-Asia campaign. The accuracy of the CMAQ-estimated AOD was further evaluated with hourly observing GOCI-retrieved AOD. After the evaluation, CMAQ-calculated AOD was mathematically combined with GOCI-retrieved AOD via data assimilation. After this, AERONET AOD measured by the DRAGON NE-Asia campaign was again combined with the assimilated AOD from CMAQ and GOCI AODs to produce more accurate spatio-temporal AOD fields over Northeast Asia. Using several relationships between PM (PM10 and PM2.5) and AOD, the best surface-PM concentrations over the entire domain were calculated. It was then evaluated with ground-based PM2.5 measurements from the DRAGON NE-Asia campaign. A good agreement between estimated PM2.5 and measured PM2.5 over the domain was found. Finally, the PM and AOD information was used to investigate the effects of transboundary PM pollution from China to the Korean peninsula.

Overview and Evaluation of the Community Multiscale Air Quality Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

DIAGNOSTIC MODEL EVALUATION FOR CARBONACEOUS PM 2.5 USING ORGANIC MARKERS MEASURED IN THE SOUTHEASTERN U.S.

EPA Science Inventory

Summertime concentrations of fine particulate carbon in the southeastern United States are consistently underestimated by air quality models. In an effort to understand the cause of this error, the Community Multiscale Air Quality (CMAQ) model is instrumented to track primary org...

FINE SCALE AIR QUALITY MODELING USING DISPERSION AND CMAQ MODELING APPROACHES: AN EXAMPLE APPLICATION IN WILMINGTON, DE

EPA Science Inventory

Characterization of spatial variability of air pollutants in an urban setting at fine scales is critical for improved air toxics exposure assessments, for model evaluation studies and also for air quality regulatory applications. For this study, we investigate an approach that su...

Diagnostic Analysis of the Three-Dimensional Sulfur Distributions over the Eastern United States Using the CMAQ Model and Measurements from the ICARTT Field Experiment

EPA Science Inventory

Previous comparisons of air quality modeling results from various forecast models with aircraft measurements of sulfate aerosol collected during the ICARTT field experiment indicated that models that included detailed treatment of gas- and aqueous-phase atmospheric sulfate format...

DEVELOPMENT OF AN AGGREGATION AND EPISODE SELECTION SCHEME TO SUPPORT THE MODELS-3 COMMUNITY MULTISCALE AIR QUALITY MODEL

EPA Science Inventory

The development of an episode selection and aggregation approach, designed to support distributional estimation of use with the Models-3 Community Multiscale Air Quality (CMAQ) model, is described. The approach utilized cluster analysis of the 700-hPa east-west and north-south...

Two Decades of WRF/CMAQ simulations over the continental United States: New approaches for performing dynamic model evaluation and determining confidence limits for ozone exceedances

EPA Science Inventory

Confidence in the application of models for forecasting and regulatory assessments is furthered by conducting four types of model evaluation: operational, dynamic, diagnostic, and probabilistic. Operational model evaluation alone does not reveal the confidence limits that can be ...

Analysis of air quality with numerical simulation (CMAQ), and observations of trace gases

NASA Astrophysics Data System (ADS)

Castellanos, Patricia

Ozone, a secondary pollutant, is a strong oxidant that can pose a risk to human health. It is formed from a complex set of photochemical reactions involving nitrogen oxides (NOx) and volatile organic compounds (VOCs). Ambient measurements and air quality modeling of ozone and its precursors are important tools for support of regulatory decisions, and analyzing atmospheric chemical and physical processes. I worked on three methods to improve our understanding of photochemical ozone production in the Eastern U.S.: a new detector for NO2, a numerical experiment to test the sensitivity to the timing to emissions, and comparison of modeled and observed vertical profiles of CO and ozone. A small, commercially available cavity ring-down spectroscopy (CRDS) NO2 detector suitable for surface and aircraft monitoring was modified and characterized. The CRDS detector was run in parallel to an ozone chemiluminescence device with photolytic conversion of NO2 to NO. The two instruments measured ambient air in suburban Maryland. A linear least-squares fit to a direct comparison of the data resulted in a slope of 0.960+/-0.002 and R of 0.995, showing agreement between two measurement techniques within experimental uncertainty. The sensitivity of the Community Multiscale Air Quality (CMAQ) model to the temporal variation of four emissions sectors was investigated to understand the effect of emissions' daily variability on modeled ozone. Decreasing the variability of mobile source emissions changed the 8-hour maximum ozone concentration by +/-7 parts per billion by volume (ppbv). Increasing the variability of point source emissions affected ozone concentrations by +/-6 ppbv, but only in areas close to the source. CO is an ideal tracer for analyzing pollutant transport in AQMs because the atmospheric lifetime is longer than the timescale of boundary layer mixing. CO can be used as a tracer if model performance of CO is well understood. An evaluation of CO model performance in CMAQ was carried out using aircraft observations taken for the Regional Atmospheric Measurement, Modeling and Prediction Program (RAMMPP) in the summer of 2002. Comparison of modeled and observed CO total columns were generally in agreement within 5-10%. There is little evidence that the CO emissions inventory is grossly overestimated. CMAQ predicts the same vertical profile shape for all of the observations, i.e. CO is well mixed throughout the boundary layer. However, the majority of observations have poorly mixed air below 500 m, and well mixed air above. CMAQ appears to be transporting CO away from the surface more quickly than what is observed. Turbulent mixing in the model is represented with K-theory. A minimum Kz that scales with fractional urban land use is imposed in order to account for subgrid scale obstacles in urban areas and the urban heat island effect. Micrometeorological observations suggest that the minimum Kz is somewhat high. A sensitivity case where the minimum K z was reduced from 0.5 m2/s to 0.1 m2/s was carried out. Model performance of surface ozone observations at night increased significantly. The model better captures the observed ozone minimum with slower mixing, and increases ozone concentrations in the residual layer. Model performance of CO and ozone morning vertical profiles improves, but the effect is not large enough to bring the model and measurements into agreement. Comparison of modeled CO and O3 vertical profiles shows that turbulent mixing (as represented by eddy diffusivity) appears to be too fast, while convective mixing may be too slow.

Multiscale predictions of aviation-attributable PM2.5 for US ...

EPA Pesticide Factsheets

Aviation activities represent an important and unique mode of transportation, but also impact air quality. In this study, we aim to quantify the impact of aircraft on air quality, focusing on aviation-attributable PM2.5 at scales ranging from local (a few kilometers) to continental (spanning hundreds of kilometers) using the Community Multiscale Air Quality-Advanced Plume Treatment (CMAQ-APT) model. In our CMAQ-APT simulations, a plume scale treatment is applied to aircraft emissions from 99 major U.S. airports over the contiguous U.S. in January and July 2005. In addition to the plume scale treatment, we account for the formation of non-traditional secondary organic aerosols (NTSOA) from the oxidation of semivolatile and intermediate volatility organic compounds (S/IVOCs) emitted from aircraft, and utilize alternative emission estimates from the Aerosol Dynamics Simulation Code (ADSC). ADSC is a 1-D plume scale model that estimates engine specific PM and S/IVOC emissions at ambient conditions, accounting for relative humidity and temperature. We estimated monthly and contiguous U.S. average aviation-attributable PM2.5 to be 2.7 ng m−3 in January and 2.6 ng m−3 in July using CMAQ-APT with ADSC emissions. This represents an increase of 40% and 12% in January and July, respectively, over impacts using traditional modeling approaches (traditional emissions without APT). The maximum fine scale (subgrid scale) hourly impacts at a major airport were 133.6 μg m−

Top-Down Constraints on Air Quality Model Emissions of NH3, NOx, and SO2 using Surface, Aircraft, and Satellite Data

NASA Astrophysics Data System (ADS)

Alvarado, M. J.; Lonsdale, C. R.; Winijkul, E.; Brodowski, C. M.; Cady-Pereira, K.; Henze, D. K.; Capps, S.

2016-12-01

Accurate modeling of the formation of ozone (O3) and fine particulate matter (PM2.5) requires accurate estimates of the emissions of precursor species such as ammonia (NH3), nitrogen oxides (NOx = NO+NO2) and sulfur dioxide (SO2). Here we present an evaluation of the 2011 EPA National Emission Inventory for NH3, NOx, and SO2 using CMAQv5.0.2 and data from the 2013 NOAA Southeast Nexus (SENEX) field campaign. Model results are compared to surface and aircraft measurements during each campaign, as well as satellite NH3 observations from the NOAA Cross-track Infrared Sounder (CrIS) and satellite observations of NO2 and SO2 from the NASA Ozone Monitoring Instrument (OMI). We also present an evaluation of the California Air Resources Board (CARB) NH3 emissions for 2012 using CMAQ and the CrIS NH3 observations. We discuss the lessons learned in using CrIS NH3 observations in the southeast US, where CMAQ predicts most of the gas-phase NH3 is very close to the surface, and contrast this with the use of CrIS NH3 observations over California. We discuss the use of two methods - a mass balance approach and an approach using the CMAQ adjoint - to optimize these emissions and evaluate the improvement in model performance for gas-phase NH3, NOx, and SO2, as well as for the formation of O3 and PM2.5.

Implementation and evaluation of PM2.5 source contribution analysis in a photochemical model

EPA Science Inventory

Source culpability assessments are useful for developing effective emissions control programs. The Integrated Source Apportionment Method (ISAM) has been implemented in the Community Multiscale Air Quality (CMAQ) model to track contributions from source groups and regions to ambi...

SCIENTIFIC UNCERTAINTIES IN ATMOSPHERIC MERCURY MODELS III: BOUNDARY AND INITIAL CONDITIONS, MODEL GRID RESOLUTION, AND HG(II) REDUCTION MECHANISMS

EPA Science Inventory

In this study we investigate the CMAQ model response in terms of simulated mercury concentration and deposition to boundary/initial conditions (BC/IC), model grid resolution (12- versus 36-km), and two alternative Hg(II) reduction mechanisms. The model response to the change of g...

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2

NASA Astrophysics Data System (ADS)

Gantt, B.; Kelly, J. T.; Bash, J. O.

2015-11-01

Sea spray aerosols (SSAs) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. Model evaluations of SSA emissions have mainly focused on the global scale, but regional-scale evaluations are also important due to the localized impact of SSAs on atmospheric chemistry near the coast. In this study, SSA emissions in the Community Multiscale Air Quality (CMAQ) model were updated to enhance the fine-mode size distribution, include sea surface temperature (SST) dependency, and reduce surf-enhanced emissions. Predictions from the updated CMAQ model and those of the previous release version, CMAQv5.0.2, were evaluated using several coastal and national observational data sets in the continental US. The updated emissions generally reduced model underestimates of sodium, chloride, and nitrate surface concentrations for coastal sites in the Bay Regional Atmospheric Chemistry Experiment (BRACE) near Tampa, Florida. Including SST dependency to the SSA emission parameterization led to increased sodium concentrations in the southeastern US and decreased concentrations along parts of the Pacific coast and northeastern US. The influence of sodium on the gas-particle partitioning of nitrate resulted in higher nitrate particle concentrations in many coastal urban areas due to increased condensation of nitric acid in the updated simulations, potentially affecting the predicted nitrogen deposition in sensitive ecosystems. Application of the updated SSA emissions to the California Research at the Nexus of Air Quality and Climate Change (CalNex) study period resulted in a modest improvement in the predicted surface concentration of sodium and nitrate at several central and southern California coastal sites. This update of SSA emissions enabled a more realistic simulation of the atmospheric chemistry in coastal environments where marine air mixes with urban pollution.

Halogen Chemistry in the CMAQ Model

EPA Science Inventory

Halogens (iodine and bromine) emitted from oceans alter atmospheric chemistry and influence atmospheric ozone mixing ratio. We previously incorporated a representation of detailed halogen chemistry and emissions of organic and inorganic halogen species into the hemispheric Commun...

Regional/Urban Air Quality Modeling Assessment over China Using the Models-3/CMAQ System

NASA Astrophysics Data System (ADS)

Fu, J. S.; Jang, C. C.; Streets, D. G.; Li, Z.; Wang, L.; Zhang, Q.; Woo, J.; Wang, B.

2004-12-01

China is the world's most populous country with a fast growing economy that surges in energy comsumption. It has become the second largest energy consumer after the United States although the per capita level is much lower than those found in developed or developing countries. Air pollution has become one of the most important problems of megacities such as Beijing and Shanghai and has serious impacts on public health, causes urban and regional haze. The Models-3/CMAQ modeling application that has been conducted to simulate multi-pollutants in China is presented. The modeling domains cover East Asia (36-kmx36-km) including Japan, South Korea, Korea DPR, Indonesia, Thailand, India and Mongolia, East China (12-kmx12-km) and Beijing/Tianjing, Shanghai (4-kmx4-km). For this study, the Asian emission inventory based on the emission estimates of the year 2000 that supported the NASA TRACE-P program is used. However, the TRACE-P emission inventory was developed for a different purpose such as global modeling. TRACE-P emission inventory may not be practical in urban area. There is no China national emission inventory available. Therefore, TRACE-P emission inventory is used on the East Asia and East China domains. The 8 districts of Beijing and Shanghai local emissions inventory are used to replace TRACE-P in 4-km domains. The meteorological data for the Models-3/CMAQ run are extracted from MM5. The model simulation is performed during the period January 1-20 and July 1-20, 2001 that presented the winter and summer time for China areas. The preliminary model results are shown O3 concentrations are in the range of 80 -120 ppb in the urban area. Lower urban O3 concentrations are shown in Beijing areas, possibly due to underestimation of urban man-made VOC emissions in the TRACE-P inventory and local inventory. High PM2.5 (70ug/m3 in summer and 150ug/m3 in winter) were simulated over metropolitan & downwind areas with significant secondary constituents. More comprehensive simulations in the Beijing, Shanghai areas are presented with sensitivity analysis. A comparison against available ozone and PM measurement data in Beijing, Shanghai is presented. The local emission inventory improvement in China is to be suggested to investigate. The modeling configuration of the Beijing 4-km x 4-km domain is to demonstrate the development of cost-effective control strategies for the air pollution control such as 2008 Olympic Game air quality management plan.

Impact of RACM2, halogen chemistry, and updated ozone deposition velocity onhemispheric ozone predictions

EPA Science Inventory

We incorporate the Regional Atmospheric Chemistry Mechanism (RACM2) into the Community Multiscale Air Quality (CMAQ) hemispheric model and compare model predictions to those obtained using the existing Carbon Bond chemical mechanism with the updated toluene chemistry (CB05TU). Th...

Modeling the Role of Alkanes, Polycyclic Aromatic Hydrocarbons, and Their Oligomers in Secondary Organic Aerosol Formation

EPA Science Inventory

A computationally efficient method to treat secondary organic aerosol (SOA) from various length and structure alkanes as well as SOA from polycyclic aromatic hydrocarbons (PAHs) is implemented in the Community Multiscale Air Quality (CMAQ) model to predict aerosol concentrations ...

On Regional Modeling to Support Air Quality Policies

EPA Science Inventory

We examine the use of the Community Multiscale Air Quality (CMAQ) model in simulating the changes in the extreme values of air quality that are of interest to the regulatory agencies. Year-to-year changes in ozone air quality are attributable to variations in the prevailing mete...

“Transference Ratios” to Predict Total Oxidized Sulfur and Nitrogen Deposition – Part II, Modeling Results

EPA Science Inventory

The current study examines predictions of transference ratios and related modeled parameters for oxidized sulfur and oxidized nitrogen using five years (2002-2006) of 12-km grid cell-specific annual estimates from EPA’s Community Air Quality Model (CMAQ) for five selected sub-re...

Improvements to the Noah Land Surface Model in WRF-CMAQ, and its Application to Future Changes in the Chesapeake Bay Region

EPA Science Inventory

Regional, state, and local environmental regulatory agencies often use Eulerian meteorological and air quality models to investigate the potential impacts of climate, emissions, and land use changes on nutrient loading and air quality. The Noah land surface model in WRF could be...

Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin.

EPA Science Inventory

The Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models were used to simulate a 10 day high‐ozone episode observed during the 2013 Uinta Basin Winter Ozone Study (UBWOS). The baseline model had a large negative bias when compared to ozo...

Chemical transport model simulations of organic aerosol in southern California: model evaluation and gasoline and diesel source contributions

NASA Astrophysics Data System (ADS)

Jathar, Shantanu H.; Woody, Matthew; Pye, Havala O. T.; Baker, Kirk R.; Robinson, Allen L.

2017-03-01

Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we updated the organic aerosol module and organic emissions inventory of a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ), using recent, experimentally derived inputs and parameterizations for mobile sources. The updated model included a revised volatile organic compound (VOC) speciation for mobile sources and secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOCs). The updated model was used to simulate air quality in southern California during May and June 2010, when the California Research at the Nexus of Air Quality and Climate Change (CalNex) study was conducted. Compared to the Traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted organic aerosol (OA) mass concentrations but did substantially improve predictions of OA sources and composition (e.g., POA-SOA split), as well as ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performed similar to a recently released research version of CMAQ (Woody et al., 2016) that did not include the updated VOC and IVOC emissions and SOA data. Mobile sources were predicted to contribute 30-40 % of the OA in southern California (half of which was SOA), making mobile sources the single largest source contributor to OA in southern California. The remainder of the OA was attributed to non-mobile anthropogenic sources (e.g., cooking, biomass burning) with biogenic sources contributing to less than 5 % to the total OA. Gasoline sources were predicted to contribute about 13 times more OA than diesel sources; this difference was driven by differences in SOA production. Model predictions highlighted the need to better constrain multi-generational oxidation reactions in chemical transport models.

Preliminary evaluation of the Community Multiscale Air Quality model for 2002 over the Southeastern United States.

PubMed

Morris, Ralph E; McNally, Dennis E; Tesche, Thomas W; Tonnesen, Gail; Boylan, James W; Brewer, Patricia

2005-11-01

The Visibility Improvement State and Tribal Association of the Southeast (VISTAS) is one of five Regional Planning Organizations that is charged with the management of haze, visibility, and other regional air quality issues in the United States. The VISTAS Phase I work effort modeled three episodes (January 2002, July 1999, and July 2001) to identify the optimal model configuration(s) to be used for the 2002 annual modeling in Phase II. Using model configurations recommended in the Phase I analysis, 2002 annual meteorological (Mesoscale Meterological Model [MM5]), emissions (Sparse Matrix Operator Kernal Emissions [SMOKE]), and air quality (Community Multiscale Air Quality [CMAQ]) simulations were performed on a 36-km grid covering the continental United States and a 12-km grid covering the Eastern United States. Model estimates were then compared against observations. This paper presents the results of the preliminary CMAQ model performance evaluation for the initial 2002 annual base case simulation. Model performance is presented for the Eastern United States using speciated fine particle concentration and wet deposition measurements from several monitoring networks. Initial results indicate fairly good performance for sulfate with fractional bias values generally within +/-20%. Nitrate is overestimated in the winter by approximately +50% and underestimated in the summer by more than -100%. Organic carbon exhibits a large summer underestimation bias of approximately -100% with much improved performance seen in the winter with a bias near zero. Performance for elemental carbon is reasonable with fractional bias values within +/- 40%. Other fine particulate (soil) and coarse particular matter exhibit large (80-150%) overestimation in the winter but improved performance in the summer. The preliminary 2002 CMAQ runs identified several areas of enhancements to improve model performance, including revised temporal allocation factors for ammonia emissions to improve nitrate performance and addressing missing processes in the secondary organic aerosol module to improve OC performance.

About Us - CMAQ

EPA Pesticide Factsheets

Our team comes from all over the world, with members representing nine different countries in North America, Europe, and Asia with diverse educational backgrounds. The CMAQ team is part of the EPA's Office of Research and Development.

Exploring the Production of NOx by Lightning and Its Impact on Tropospheric Ozone

NASA Technical Reports Server (NTRS)

Gillani, Noor; Koshak, William; Biazar, Arastoo; Doty, Kevin; Mahon, Robert; Newchurch, Michael; Byun, Daewon; Emmons, Louisa

2006-01-01

Our quantitative understanding of free tropospheric (FT) chemistry is quite poor. State-of-the-art regional air quality models (e.g., US EPA's CMAQ) perform very poorly in simulating FT chemistry, with Uniform ozone around 70 ppb throughout the FT in summer, while ozonesonde data show much higher levels of ozone and much spatial-temporal structure. Such models completely neglect lightning-NOx (LNOx) emissions (the most significant source of NOx in the FT), and also contain large uncertainties in the specifications of intercontinental transport, stratosphere-troposphere exchange (STE) and PBLFT exchange (PFTE). Global air chemistry models include LNOx, but in very crude fashion, with the frequency and distribution of lightning being based on modeled cloud parameters (hence large uncertainty), lightning energetics being assumed to be constant for all flashes (literature value, while in reality there is at least a two-orders of magnitude variability from flash-to-flash), and the production of NOx in the surrounding heated air, per Joule of heating, being assumed to be constant also (literature value, while in fact it is a non-linear function of the dissipated heat and local air density, p). This situation is commonly blamed on paucity of pertinent observational data, but for the USA, there is now a wealth of surface- and satellite-based data of lightning available to permit much improved observation-based estimation of LNOx emissions. In the FT, such NOx has a long residence time, and also the ozone production efficiency from NOx there is considerably higher than in the PBL. It is, therefore, of critical importance in FT chemistry. This paper will describe the approach and data products of an ongoing NSSTC project aimed at a much-improved quantification of not only LNOx production on the scale of continental USA based on local and regional lightning observations, but also of intercontinental transport, STE and PFTE, all in upgraded simulations of tropospheric transport and chemistry. In our approach for LNOx, (a) we utilize continuous observed lightning information from the NLDN ground network and from satellite imagers (OTD and LIS) to quantify lightning frequency and distribution at the spatial-temporal scales of models such as CMAQ; (b) we develop new methodologies to quantify flash-specific lightning energy dissipation as heat (epsilon) using data from the research-grade lightning measurement facility at NASA-KSC, and to parameterize epsilon based on regional lightning monitoring data (ground- and satellite-based); and, (c) we develop a new parameterization of NOx production as a function of epsilon and rho. Based on such observation-based information, we are working to develop a gridded, episodic LNOx emissions inventory for the USA for use in models like CMAQ. We are also developing approaches for global(MOZART)- regional(CMAQ) chemistry coupling to improve intercontinental transport and STE. Finally, we are developing new methodologies for assimilation of satellite-observed (GOES) clouds into meteorological modeling (MM5), to improve PFTE and to optimize co-location of cloud convection and observed lightning. We will incorporate these improvements in CMAQ simulations over the USA to better understand FT processes and chemistry, and its impact on ground-level ozone.

Applying for and using CMAQ funds

DOT National Transportation Integrated Search

1997-01-01

This guide provides the basic concepts to aid in an alternative fuel vehicle market development program developing an application for Congestion Mitigation and Air Quality (CMAQ) Improvement Program funding. The U.S. Department of Energy's Clean Citi...

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2

EPA Science Inventory

Sea spray aerosols (SSAs) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. Model evaluations of SSA emissions have mainly focused on the global scale, but regional-scale evaluations are...

Current and estimated future atmospheric nitrogen loads to the Chesapeake Bay Watershed

EPA Science Inventory

Nitrogen deposition for CMAQ scenarios in 2011, 2017, 2023, 2028, and a 2048-2050 RCP 4.5 climate scenario will be presented for the watershed and tidal waters. Comparisons will be made with the 2017 Airshed Model to the previous 2010 Airshed Model estimates. In addition, atmosph...

WRF/CMAQ AQMEII3 Simulations of U.S. Regional-Scale Ozone: Sensitivity to Processes and Inputs

EPA Science Inventory

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, performed during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), we perform annual simulations over North America with chemical boundary con...

REGIONAL MODELING OF THE ATMOSPHERIC TRANSPORT AND DEPOSITION OF ATRAZINE

EPA Science Inventory

A version of the Community Multiscale Air Quality (CMAQ) model has been developed by the U.S. EPA that is capable of addressing the atmospheric fate, transport and deposition of some common trace toxics. An initial, 36-km rectangular grid-cell application for atrazine has been...

HIGH TIME-RESOLVED COMPARISONS FOR IN-DEPTH PROBING OF CMAQ FINE-PARTICLES AND GAS PREDICTIONS

EPA Science Inventory

Model evaluation is important to develop confidence in models and develop an understanding of their predictions. Most comparisons in the U.S. involve time-integrated measurements of 24-hours or longer. Comparisons against continuous or semi-continuous particle and gaseous measur...

CONCENTRATIONS OF TOXIC AIR POLLUTANTS IN THE U.S. SIMULATED BY AN AIR QUALITY MODEL

EPA Science Inventory

As part of the US National Air Toxics Assessment, we have applied the Community Multiscale Air Quality Model, CMAQ, to study the concentrations of twenty gas-phase, toxic, hazardous air pollutants (HAPs) in the atmosphere over the continental United States. We modified the Carbo...

AQUEOUS REDUCTION OF HG2+ TO HG0 BY HO2 IN THE CMAQ-MODEL

EPA Science Inventory

Numerical models of atmospheric mercury are formulated based on the current understanding of mercury chemistry in air and in atmospheric water. Recent evidence that significant reduction of Hg2+ by reaction with HO2 may not actually occur in natural atmospheric water has obviou...

Enhanced representation of soil NO emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2

EPA Science Inventory

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community...

Predicting Nitrogen in Streams : A Comparison of Two Estimates of Fertilizer Application

EPA Science Inventory

Decision makers frequently rely on water and air quality models to develop nutrient management strategies. Obviously, the results of these models (e.g., SWAT, SPARROW, CMAQ) are only as good as the nutrient source input data and recently the Nutrient Innovations Task Group has ca...

Modeling crop residue burning experiments and assessing the fire impacts on air quality

EPA Science Inventory

Prescribed burning is a common land management practice that results in ambient emissions of a variety of primary and secondary pollutants with negative health impacts. The community Multiscale Air Quality (CMAQ) model is used to conduct 2 km grid resolution simulations of prescr...

SIMULATING URBAN AIR TOXICS OVER CONTINENTAL AND URBAN SCALES

EPA Science Inventory

The US EPA is evaluating a version of the CMAQ model to support risk assessment for the exposure to Hazardous Air Pollutants (HAPs). The model uses a variant of the CB4 chemical mechanism to simulate ambient concentrations of twenty HAPs that exist primarily as gaseous compounds...

“Impact of RACM2, halogen chemistry, and updated ozonedeposition velocity on hemispheric ozone predictions”

EPA Science Inventory

We incorporate the Regional Atmospheric Chemistry Mechanism (RACM2) into the Community Multiscale Air Quality (CMAQ) hemispheric model and compare model predictions to those obtained using the existing Carbon Bond chemical mechanism with updated toluene chemistry (CB05TU). The RA...

On Regional Modeling to Support Air Quality Policies (book chapter)

EPA Science Inventory

We examine the use of the Community Multiscale Air Quality (CMAQ) model in simulating the changes in the extreme values of air quality that are of interest to the regulatory agencies. Year-to-year changes in ozone air quality are attributable to variations in the prevailing meteo...

Diagnostic Evaluation of Carbon Sources in CMAQ

EPA Science Inventory

Traditional monitoring networks measure only total elemental carbon (EC) and organic carbon (OC) routinely. Diagnosing model biases with such limited information is difficult. Measurements of organic tracer compounds have recently become available and allow for more detailed di...

Quantifying Co-benefits of Renewable Energy through Integrated Electricity and Air Quality Modeling

NASA Astrophysics Data System (ADS)

Abel, D.

2016-12-01

This work focuses on the coordination of electricity sector changes with air quality and health improvement strategies through the integration of electricity and air quality models. Two energy models are used to calculate emission perturbations associated with changes in generation technology (20% generation from solar photovoltaics) and demand (future electricity use under a warmer climate). Impacts from increased solar PV penetration are simulated with the electricity model GridView, in collaboration with the National Renewable Energy Laboratory (NREL). Generation results are used to scale power plant emissions from an inventory developed by the Lake Michigan Air Directors Consortium (LADCO). Perturbed emissions and are used to calculate secondary particulate matter with the Community Multiscale Air Quality (CMAQ) model. We find that electricity NOx and SO2 emissions decrease at a rate similar to the total fraction of electricity supplied by solar. Across the Eastern U.S. region, average PM2.5 is reduced 5% over the summer, with highest reduction in regions and on days of greater PM2.5. A similar approach evaluates the air quality impacts of elevated electricity demand under a warmer climate. Meteorology is selected from the North American Regional Climate Change Assessment Program (NARCCAP) and input to a building energy model, eQUEST, to assess electricity demand as a function of ambient temperature. The associated generation and emissions are calculated on a plant-by-plant basis by the MyPower power sector model. These emissions are referenced to the 2011 National Emissions Inventory to be modeled in CMAQ for the Eastern U.S. and extended to health impact evaluation with the Environmental Benefits Mapping and Analysis Program (BenMAP). All results focus on the air quality and health consequences of energy system changes, considering grid-level changes to meet climate and air quality goals.

Photochemical model evaluation of the ground-level ozone impacts on ambient air quality and vegetation health in the Alberta oil sands region: Using present and future emission scenarios

NASA Astrophysics Data System (ADS)

Vijayaraghavan, Krish; Cho, Sunny; Morris, Ralph; Spink, David; Jung, Jaegun; Pauls, Ron; Duffett, Katherine

2016-09-01

One of the potential environmental issues associated with oil sands development is increased ozone formation resulting from NOX and volatile organic compound emissions from bitumen extraction, processing and upgrading. To manage this issue in the Athabasca Oil Sands Region (AOSR) in northeast Alberta, a regional multi-stakeholder group, the Cumulative Environmental Management Association (CEMA), developed an Ozone Management Framework that includes a modelling based assessment component. In this paper, we describe how the Community Multi-scale Air Quality (CMAQ) model was applied to assess potential ground-level ozone formation and impacts on ambient air quality and vegetation health for three different ozone precursor cases in the AOSR. Statistical analysis methods were applied, and the CMAQ performance results met the U.S. EPA model performance goal at all sites. The modelled 4th highest daily maximum 8-h average ozone concentrations in the base and two future year scenarios did not exceed the Canada-wide standard of 65 ppb or the newer Canadian Ambient Air Quality Standards of 63 ppb in 2015 and 62 ppb in 2020. Modelled maximum 1-h ozone concentrations in the study were well below the Alberta Ambient Air Quality Objective of 82 ppb in all three cases. Several ozone vegetation exposure metrics were also evaluated to investigate the potential impact of ground-level ozone on vegetation. The chronic 3-months SUM60 exposure metric is within the CEMA baseline range (0-2000 ppb-hr) everywhere in the AOSR. The AOT40 ozone exposure metric predicted by CMAQ did not exceed the United Nations Economic Commission for Europe (UN/ECE) threshold of concern of 3000 ppb-hr in any of the cases but is just below the threshold in high-end future emissions scenario. In all three emission scenarios, the CMAQ predicted W126 ozone exposure metric is within the CEMA baseline threshold of 4000 ppb-hr. This study outlines the use of photochemical modelling of the impact of an industry (oil sands) on ground-level ozone levels as an air quality management tool in the AOSR. It allows an evaluation of the relationships between the pollutants emitted to the atmosphere and potential ground level ozone concentrations throughout the AOSR thereby extending the spatial coverage of the results beyond the monitoring network and also allowing an assessment of the potential impacts of possible future emission cases.

A numerical study of tropospheric ozone in the springtime in East Asia

NASA Astrophysics Data System (ADS)

Zhang, Meigen; Xu, Yongfu; Itsushi, Uno; Hajime, Akimoto

2004-04-01

The Models-3 Community Multi-scale Air Quality modeling system (CMAQ) coupled with the Regional Atmospheric Modeling System (RAMS) is applied to East Asia to study the transport and photochemical transformation of tropospheric ozone in March 1998. The calculated mixing ratios of ozone and carbon monoxide are compared with ground level observations at three remote sites in Japan and it is found that the model reproduces the observed features very well. Examination of several high episodes of ozone and carbon monoxide indicates that these elevated levels are found in association with continental outflow, demonstrating the critical role of the rapid transport of carbon monoxide and other ozone precursors from the continental boundary layer. In comparison with available ozonesonde data, it is found that the model-calculated ozone concentrations are generally in good agreement with the measurements, and the stratospheric contribution to surface ozone mixing ratios is quite limited.

Data for Figures and Tables in Journal Article Assessment of the Effects of Horizontal Grid Resolution on Long-Term Air Quality Trends using Coupled WRF-CMAQ Simulations, doi:10.1016/j.atmosenv.2016.02.036

EPA Pesticide Factsheets

The dataset represents the data depicted in the Figures and Tables of a Journal Manuscript with the following abstract: The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental United State are performed over the 2001 to 2010 time period at two different horizontal resolutions of 12 and 36 km. Both simulations used the same emission inventory and model configurations. Model results are compared both in space and time to assess the potential weaknesses and strengths of using coarse resolution in long-term air quality applications. The results show that the 36 km and 12 km simulations are comparable in terms of trends analysis for both pollutant concentrations and radiation variables. The advantage of using the coarser 36 km resolution is a significant reduction of computational cost, time and storage requirement which are key considerations when performing multiple years of simulations for trend analysis. However, if such simulations are to be used for local air quality analysis, finer horizontal resolution may be beneficial since it can provide information on local gradients. In particular, divergences between the two simulations are noticeable in urban, complex terrain and coastal regions.This dataset is associated with the following publication

Using optimal interpolation to assimilate surface measurements and satellite AOD for ozone and PM2.5: A case study for July 2011.

PubMed

Tang, Youhua; Chai, Tianfeng; Pan, Li; Lee, Pius; Tong, Daniel; Kim, Hyun-Cheol; Chen, Weiwei

2015-10-01

We employed an optimal interpolation (OI) method to assimilate AIRNow ozone/PM2.5 and MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth (AOD) data into the Community Multi-scale Air Quality (CMAQ) model to improve the ozone and total aerosol concentration for the CMAQ simulation over the contiguous United States (CONUS). AIRNow data assimilation was applied to the boundary layer, and MODIS AOD data were used to adjust total column aerosol. Four OI cases were designed to examine the effects of uncertainty setting and assimilation time; two of these cases used uncertainties that varied in time and location, or "dynamic uncertainties." More frequent assimilation and higher model uncertainties pushed the modeled results closer to the observation. Our comparison over a 24-hr period showed that ozone and PM2.5 mean biases could be reduced from 2.54 ppbV to 1.06 ppbV and from -7.14 µg/m³ to -0.11 µg/m³, respectively, over CONUS, while their correlations were also improved. Comparison to DISCOVER-AQ 2011 aircraft measurement showed that surface ozone assimilation applied to the CMAQ simulation improves regional low-altitude (below 2 km) ozone simulation. This paper described an application of using optimal interpolation method to improve the model's ozone and PM2.5 estimation using surface measurement and satellite AOD. It highlights the usage of the operational AIRNow data set, which is available in near real time, and the MODIS AOD. With a similar method, we can also use other satellite products, such as the latest VIIRS products, to improve PM2.5 prediction.

MODELING ASSESSMENT OF THE IMPACT OF NITROGEN OXIDES EMISSION REDUCTIONS ON OZONE AIR QUALITY IN THE EASTERN UNITED STATES: OFFSETTING INCREASES IN ENERGY USE

EPA Science Inventory

The objective of this study is to examine changes in ambient ozone concentrations estimated by a photochemical air quality model in response to the NOx emission reductions imposed on the utility sector. To accomplish this task, CMAQ air quality model simulations were performe...

Assessment of the Aerosol Optics Component of the Coupled WRF-CMAQ Model usingCARES Field Campaign data and a Single Column Model

EPA Science Inventory

The Carbonaceous Aerosols and Radiative Effects Study (CARES), a field campaign held in central California in June 2010, provides a unique opportunity to assess the aerosol optics modeling component of the two-way coupled Weather Research and Forecasting (WRF) – Community Multisc...

Ozone distributions over southern Lake Michigan: comparisons between ferry-based observations, shoreline-based DOAS observations and model forecasts

NASA Astrophysics Data System (ADS)

Cleary, P. A.; Fuhrman, N.; Schulz, L.; Schafer, J.; Fillingham, J.; Bootsma, H.; McQueen, J.; Tang, Y.; Langel, T.; McKeen, S.; Williams, E. J.; Brown, S. S.

2015-05-01

Air quality forecast models typically predict large summertime ozone abundances over water relative to land in the Great Lakes region. While each state bordering Lake Michigan has dedicated monitoring systems, offshore measurements have been sparse, mainly executed through specific short-term campaigns. This study examines ozone abundances over Lake Michigan as measured on the Lake Express ferry, by shoreline differential optical absorption spectroscopy (DOAS) observations in southeastern Wisconsin and as predicted by the Community Multiscale Air Quality (CMAQ) model. From 2008 to 2009 measurements of O3, SO2, NO2 and formaldehyde were made in the summertime by DOAS at a shoreline site in Kenosha, WI. From 2008 to 2010 measurements of ambient ozone were conducted on the Lake Express, a high-speed ferry that travels between Milwaukee, WI, and Muskegon, MI, up to six times daily from spring to fall. Ferry ozone observations over Lake Michigan were an average of 3.8 ppb higher than those measured at shoreline in Kenosha, with little dependence on position of the ferry or temperature and with greatest differences during evening and night. Concurrent 1-48 h forecasts from the CMAQ model in the upper Midwestern region surrounding Lake Michigan were compared to ferry ozone measurements, shoreline DOAS measurements and Environmental Protection Agency (EPA) station measurements. The bias of the model O3 forecast was computed and evaluated with respect to ferry-based measurements. Trends in the bias with respect to location and time of day were explored showing non-uniformity in model bias over the lake. Model ozone bias was consistently high over the lake in comparison to land-based measurements, with highest biases for 25-48 h after initialization.

Watershed Deposition Tool for air quality impacts

EPA Pesticide Factsheets

The WDT is a software tool for mapping deposition estimates from the CMAQ model to watersheds. It provides users with the linkage of air and water needed for the total maximum daily load (TMDL) and related nonpoint-source watershed analyses.

RAGG - R EPISODIC AGGREGATION PACKAGE

EPA Science Inventory

The RAGG package is an R implementation of the CMAQ episodic model aggregation method developed by Constella Group and the Environmental Protection Agency. RAGG is a tool to provide climatological seasonal and annual deposition of sulphur and nitrogen for multimedia management. ...

77 FR 19098 - Approval and Promulgation of Implementation Plans; Commonwealth of Kentucky; Regional Haze State...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-30

... located across a broad geographic area and emit fine particles (e.g., sulfates, nitrates, organic carbon...-3/Community Multiscale Air Quality (CMAQ) model used by the Commonwealth has not been established to...

NUMERICAL NOISE PM SIMULATION IN CMAQ

EPA Science Inventory

We have found that numerical noise in the latest release of CMAQ using the yamo advection scheme when compiled on Linux cluster with pgf90 (5.0 or 6.0). We recommend to use -C option to eliminate the numerical noise.

NCEP Air Quality Forecast(AQF) Graphics

Science.gov Websites

NAM-CMAQ Experimental Run predictions 00 03 06 09 12 15 18 21 24 27 30 33 36 39 42 45 48 Select experimental bias correction predictions NAM vs Nest forecasts Change Variable Type: Hourly CMAQ Forecasts

Using NASA Satellite Aerosol Optical Depth to Enhance PM2.5 Concentration Datasets for Use in Human Health and Epidemiology Studies

NASA Astrophysics Data System (ADS)

Huff, A. K.; Weber, S.; Braggio, J.; Talbot, T.; Hall, E.

2012-12-01

Fine particulate matter (PM2.5) is a criterion air pollutant, and its adverse impacts on human health are well established. Traditionally, studies that analyze the health effects of human exposure to PM2.5 use concentration measurements from ground-based monitors and predicted PM2.5 concentrations from air quality models, such as the U.S. EPA's Community Multi-scale Air Quality (CMAQ) model. There are shortcomings associated with these datasets, however. Monitors are not distributed uniformly across the U.S., which causes spatially inhomogeneous measurements of pollutant concentrations. There are often temporal variations as well, since not all monitors make daily measurements. Air quality model output, while spatially and temporally uniform, represents predictions of PM2.5 concentrations, not actual measurements. This study is exploring the potential of combining Aerosol Optical Depth (AOD) data from the MODIS instrument on NASA's Terra and Aqua satellites with PM2.5 monitor data and CMAQ predictions to create PM2.5 datasets that more accurately reflect the spatial and temporal variations in ambient PM2.5 concentrations on the metropolitan scale, with the overall goal of enhancing capabilities for environmental public health decision-making. AOD data provide regional information about particulate concentrations that can fill in the spatial and temporal gaps in the national PM2.5 monitor network. Furthermore, AOD is a measurement, so it reflects actual concentrations of particulates in the atmosphere, in contrast to PM2.5 predictions from air quality models. Results will be presented from the Battelle/U.S. EPA statistical Hierarchical Bayesian Model (HBM), which was used to combine three PM2.5 concentration datasets: monitor measurements, AOD data, and CMAQ model predictions. The study is focusing on the Baltimore, MD and New York City, NY metropolitan regions for the period 2004-2006. For each region, combined monitor/AOD/CMAQ PM2.5 datasets generated by the HBM are being correlated with data on inpatient hospitalizations and emergency room visits for seven respiratory and cardiovascular diseases using statistical case-crossover analyses. Preliminary results will be discussed regarding the potential for the addition of AOD data to increase the correlation between PM2.5 concentrations and health outcomes. Environmental public health tracking programs associated with the Maryland Department of Health and Mental Hygiene, the New York State Department of Health, the CDC, and the U.S. EPA have expressed interest in using the results of this study to enhance their existing environmental health surveillance activities.

Updating CMAQ secondary organic aerosol properties relevant for aerosol water interactions

EPA Science Inventory

Properties of secondary organic aerosol (SOA) compounds in CMAQ are updated with state-of-the-science estimates from structure activity relationships to provide consistency among volatility, molecular weight, degree of oxygenation, and solubility/hygroscopicity. These updated pro...

Emission Reduction Potential of the Congestion Mitigation and Air Quality Program

DOT National Transportation Integrated Search

1997-05-19

The Congestion Mitigation and Air Quality Improvement Program (CMAQ) provides : funds to states for projects designed to help attain and maintain the national : ambient air quality standards (NAAQS) set under the Clean Air Act (CAA). CMAQ : was creat...

CMAQ AEROSOL MODULE DEVELOPMENT RECENT ENHANCEMENTS & FUTURE PLANS

EPA Science Inventory

Recent enhancements to the CMAQ aerosol module will be reviewed briefly. These include revision of the secondary organic aerosol subroutine to improve numerical efficiency and control the growth of the accumulation mode standard deviation, revision of the nucleation subroutine t...

Comparison of human exposure model estimates of PM2.5 exposure variability using fine-scale CMAQ simulations from the Baltimore DISCOVER-AQ evaluation

EPA Science Inventory

Human exposure models estimate population distributions of exposure to air pollutants by combining ambient (outdoor) concentration data with human activity patterns to account for the time people spend in different locations (e.g., outdoors, indoors, in vehicles) and the various ...

THE FATE AND TRANSPORT OF AMMONIA AT THE LOCAL TO REGIONAL LEVEL

EPA Science Inventory

Air quality model results are developed and presented as to where ammonia goes once it is emitted. The ammonia budget is dissected in terms of dry and wet deposition and turbulent and wind transport. The domain of analysis is the eastern U.S. The CMAQ model is used with process ...

Investigation of Effects of Varying Model Inputs on Mercury Deposition Estimates in the Southwest US

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model version 4.7.1 was used to simulate mercury wet and dry deposition for a domain covering the continental United States (US). The simulations used MM5-derived meteorological input fields and the US Environmental Protection Agency (E...

Observations and modeling of air quality trends over 1990-2010 across the northern hemisphere: China, the United States and Europe

EPA Science Inventory

Trends in air quality across the Northern Hemisphere over a 21-year period (1990–2010) were simulated using the Community Multiscale Air Quality (CMAQ) multiscale chemical transport model driven by meteorology from Weather Research and Forecasting WRF) simulations and internally ...

MODELING THE ATMOSPHERE FORMATION OF REACTIVE MERCURY IN FLORIDA AND THE GREAT LAKES

EPA Science Inventory

Reactive mercury in the troposphere is affected by a complex mix of local emissions, global-scale transport, and gas and aqueous-phase chemistry. Here, we describe a modified version of the EPA model for urban/regional air quality (CMAQ) to include the chemistry of mercury, and m...

EFFECTS OF USING THE CB05 VS SAPRC 99 VS CB4 CHEMICAL MECHANISMS ON MODEL PREDICTIONS

EPA Science Inventory

In this study, we examine differences in predictions of ozone, other oxidants, and ozone precursors for 3 chemical mechanisms: the CB4, CB05 and SAPRC99 mechanism (CMAQ/Models3 version). We present results for current conditions and differences among the mechanisms with emission...

COMPARISON OF CMAQ DERIVED CARBON MONOXIDE COLUMNS WITH MOPITT CARBON MONOXIDE DATA, SENSITIVITY TO WILDFIRE EMISSIONS

EPA Science Inventory

All model results need to be evaluated against observed data, no matter what the model

scale. Traditionally for air quality applications, the observed data have been limited to

concentrations measured by networks of ground stations. These are located mostly in

PHOTOCHEMICAL SIMULATIONS OF POINT SOURCE EMISSIONS WITH THE MODELS-3 CMAQ PLUME-IN-GRID APPROACH

EPA Science Inventory

A plume-in-grid (PinG) approach has been designed to provide a realistic treatment for the simulation the dynamic and chemical processes impacting pollutant species in major point source plumes during a subgrid scale phase within an Eulerian grid modeling framework. The PinG sci...

Can a coupled meteorology–chemistry model reproduce the historical trend in aerosol direct radiative effects over the Northern Hemisphere?

EPA Science Inventory

The ability of a coupled meteorology–chemistry model, i.e., Weather Research and Forecast and Community Multiscale Air Quality (WRF-CMAQ), to reproduce the historical trend in aerosol optical depth (AOD) and clear-sky shortwave radiation (SWR) over the Northern Hemisphere h...

Modeling the impacts of green infrastructure land use changes on air quality and meteorology case study and sensitivity analysis in Kansas City

EPA Science Inventory

Changes in vegetation cover associated with urban planning efforts may affect regional meteorology and air quality. Here we use a comprehensive coupled meteorology-air quality model (WRF-CMAQ) to simulate the influence of planned land use changes from green infrastructure impleme...

CMAQ predictions of tropospheric ozone in the U.S. southwest: influence of lateral boundary and synoptic conditions.

PubMed

Shi, Chune; Fernando, H J S; Hyde, Peter

2012-02-01

Phoenix, Arizona, has been an ozone nonattainment area for the past several years and it remains so. Mitigation strategies call for improved modeling methodologies as well as understanding of ozone formation and destruction mechanisms during seasons of high ozone events. To this end, the efficacy of lateral boundary conditions (LBCs) based on satellite measurements (adjusted-LBCs) was investigated, vis-à-vis the default-LBCs, for improving the predictions of Models-3/CMAQ photochemical air quality modeling system. The model evaluations were conducted using hourly ground-level ozone and NO(2) concentrations as well as tropospheric NO(2) columns and ozone concentrations in the middle to upper troposphere, with the 'design' periods being June and July of 2006. Both included high ozone episodes, but the June (pre-monsoon) period was characterized by local thermal circulation whereas the July (monsoon) period by synoptic influence. Overall, improved simulations were noted for adjusted-LBC runs for ozone concentrations both at the ground-level and in the middle to upper troposphere, based on EPA-recommended model performance metrics. The probability of detection (POD) of ozone exceedances (>75ppb, 8-h averages) for the entire domain increased from 20.8% for the default-LBC run to 33.7% for the adjusted-LBC run. A process analysis of modeling results revealed that ozone within PBL during bulk of the pre-monsoon season is contributed by local photochemistry and vertical advection, while the contributions of horizontal and vertical advections are comparable in the monsoon season. The process analysis with adjusted-LBC runs confirms the contributions of vertical advection to episodic high ozone days, and hence elucidates the importance of improving predictability of upper levels with improved LBCs. Copyright © 2011 Elsevier B.V. All rights reserved.

Impacts of WRF lightning assimilation on offline CMAQ simulations

EPA Science Inventory

Deep convective clouds vertically redistribute trace gases and aerosols and also provide a source for scavenging, aqueous phase chemistry, and wet deposition, making them important to air quality.? Regional air quality simulations are typically driven by meteorological models tha...

User's Manual for Downscaler Fusion Software

EPA Science Inventory

Recently, a series of 3 papers has been published in the statistical literature that details the use of downscaling to obtain more accurate and precise predictions of air pollution across the conterminous U.S. This downscaling approach combines CMAQ gridded numerical model output...

"Total Deposition (TDEP) Maps"

EPA Science Inventory

The presentation provides an update on the use of a hybrid methodology that relies on measured values from national monitoring networks and modeled values from CMAQ to produce of maps of total deposition for use in critical loads and other ecological assessments. Additionally, c...

Tracking Continental Scale Background Ozone with CMAQ

EPA Science Inventory

As the National Ambient Air Quality Standards (NAAQS) for ozone become more stringent, there has been growing attention on characterizing the contributions and the uncertainties in ozone from outside the US to the ozone concentrations within the US. Modeling techniques readily av...

SAFETEA-LU 1808 : CMAQ, evaluation and assessment, phase I, final report.

DOT National Transportation Integrated Search

2008-10-01

In SAFETEA-LU Section 1808, Congress required the U.S. Department of Transportation, in consultation with the Environmental Protection Agency (EPA), to evaluate and assess the direct and indirect impacts of CMAQ-funded projects on air quality and con...

Air quality analysis of MDT transportation improvements, cost-effectiveness analysis of the MACI Program.

DOT National Transportation Integrated Search

2004-03-01

"Under TEA-21, part of Montana's CMAQ apportionment is dedicated to Missoula and at the direction of the : Montana Transportation Commission, the Montana Department of Transportation (MDT) directs the remainder of : the CMAQ apportionment to areas in...

Air quality analysis of MDT transportation improvements : cost-effectiveness analysis of the MACI program.

DOT National Transportation Integrated Search

2004-03-01

Under TEA-21, part of Montana's CMAQ apportionment is dedicated to Missoula and at the direction of the : Montana Transportation Commission, the Montana Department of Transportation (MDT) directs the remainder of : the CMAQ apportionment to areas in ...

SAFETEA-LU 1808 : CMAQ, evaluation and assessment, phase II, final report.

DOT National Transportation Integrated Search

2009-07-01

In SAFETEA-LU Section 1808, Congress required the U.S. Department of Transportation, in consultation with the Environmental Protection Agency (EPA), to evaluate and assess the direct and indirect impacts of CMAQ-funded projects on air quality and con...

A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods

NASA Astrophysics Data System (ADS)

Tang, Youhua; Pagowski, Mariusz; Chai, Tianfeng; Pan, Li; Lee, Pius; Baker, Barry; Kumar, Rajesh; Delle Monache, Luca; Tong, Daniel; Kim, Hyun-Cheol

2017-12-01

This study applies the Gridpoint Statistical Interpolation (GSI) 3D-Var assimilation tool originally developed by the National Centers for Environmental Prediction (NCEP), to improve surface PM2.5 predictions over the contiguous United States (CONUS) by assimilating aerosol optical depth (AOD) and surface PM2.5 in version 5.1 of the Community Multi-scale Air Quality (CMAQ) modeling system. An optimal interpolation (OI) method implemented earlier (Tang et al., 2015) for the CMAQ modeling system is also tested for the same period (July 2011) over the same CONUS. Both GSI and OI methods assimilate surface PM2.5 observations at 00:00, 06:00, 12:00 and 18:00 UTC, and MODIS AOD at 18:00 UTC. The assimilations of observations using both GSI and OI generally help reduce the prediction biases and improve correlation between model predictions and observations. In the GSI experiments, assimilation of surface PM2.5 (particle matter with diameter < 2.5 µm) leads to stronger increments in surface PM2.5 compared to its MODIS AOD assimilation at the 550 nm wavelength. In contrast, we find a stronger OI impact of the MODIS AOD on surface aerosols at 18:00 UTC compared to the surface PM2.5 OI method. GSI produces smoother result and yields overall better correlation coefficient and root mean squared error (RMSE). It should be noted that the 3D-Var and OI methods used here have several big differences besides the data assimilation schemes. For instance, the OI uses relatively big model uncertainties, which helps yield smaller mean biases, but sometimes causes the RMSE to increase. We also examine and discuss the sensitivity of the assimilation experiments' results to the AOD forward operators.

NEIGHBORHOOD SCALE AIR QUALITY MODELING IN HOUSTON USING URBAN CANOPY PARAMETERS IN MM5 AND CMAQ WITH IMPROVED CHARACTERIZATION OF MESOSCALE LAKE-LAND BREEZE CIRCULATION

EPA Science Inventory

Advanced capability of air quality simulation models towards accurate performance at finer scales will be needed for such models to serve as tools for performing exposure and risk assessments in urban areas. It is recognized that the impact of urban features such as street and t...

New particle formation and growth in CMAQ via application of comprehensive modal methods

EPA Science Inventory

The formation and growth of new atmospheric ultrafine particles are exceedingly complex processes and recent scientific efforts have grown our understanding of them tremendously. This presentation describes the effort to apply this new knowledge to the CMAQ chemical transport mod...

Congestion Mitigation and Air Quality (CMAQ) Improvement Program: Cost-Effectiveness Tables Development and Methodology

DOT National Transportation Integrated Search

2015-05-01

This document presents summary and detailed findings from a research effort to develop estimates of the cost-effectiveness of a range of project types funded under the Congestion Mitigation and Air Quality (CMAQ) Improvement Program. In this study, c...

Persistence of initial conditions in continental scale air quality simulations

EPA Science Inventory

This study investigates the effect of initial conditions (IC) for pollutant concentrations in the atmosphere and soil on simulated air quality for two continental-scale Community Multiscale Air Quality (CMAQ) model applications. One of these applications was performed for springt...

Understanding the impact of recent advances in isoprene photooxidation on simulations of regional air quality

EPA Science Inventory

The CMAQ (Community Multiscale Air Quality) us model in combination with observations for INTEX-NA/ICARTT (Intercontinental Chemical Transport Experiment–North America/International Consortium for Atmospheric Research on Transport and Transformation) 2004 are used to evalua...

Understanding pathways to organic aerosol: How the sweat and communications of plants influence our air quality

EPA Science Inventory

Isoprene and monoterpenes are major contributors to organic aerosol in in the southeastern U.S. This work presents results from 4 years of work improving the CMAQ model representation of aerosol from these precursors.

DIAGNOSTIC EVALUATION OF CMAQ RESPONSE OF INORGANIC FINE PARTICULATE SPECIES OF EMISSIONS CHANGES

EPA Science Inventory

The Gas Ratio proposed by Spyros Pandis, which identifies whether the system is nitric acid or ammonia limited, is an indicator of the sensitivity of the inorganic system to changes in conditions. This indicator is investigated in this work to find out how well it can diagnose se...

Particulate Matter Pollution and its Regional Transport in the Mid-Atlantic States

NASA Astrophysics Data System (ADS)

He, H.; Goldberg, D. L.; Hembeck, L.; Canty, T. P.; Vinciguerra, T.; Ring, A.; Salawitch, R. J.; Dickerson, R. R.

2015-12-01

Particulate matter (PM) causes negative effects on human health, impair visibility in scenic areas, and affect regional/global climate. PM can be formed through chemical changes of precursors, including biogenic VOCs and anthropogenic SO2 and NOx often from fossil fuel combustion. In the past decades, PM pollution in the US has improved substantially. However, some areas in the Mid-Atlantic States are still designated as 'moderate' nonattainment by EPA. We utilize datasets obtained during the NASA 2011 DISCOVER-AQ campaign to characterize the composition and distribution of summertime PM pollution in the Mid-Atlantic States. Aircraft measurements and OMI satellite retrieval of major anthropogenic precursors (NO2 and SO2) are analyzed to investigate the regional transport of PM precursors from upwind sources. We compare PM concentration and chemical composition observed during the field campaign to CMAQ simulations with the latest EPA emission inventory. Specifically, we focus on the secondary organic aerosol (SOA) chemistry in CMAQ simulations using various biogenic VOCs estimates from the MEGAN and BEIS models. Airborne PM observations including PILS measurements from DISCOVER-AQ campaign and OMI retrievals of HCHO are also used to validate and improve the representation of SOA chemistry and PM pollution within CMAQ. The comparison reveals the source and evolution of PM pollution in the Mid-Atlantic States.

O3 Source Contribution During a Heavy O3 Pollution Episode in Shanghai China

EPA Science Inventory

Source culpability assessments are useful for developing effective emission control strategies. The Integrated Source Apportionment Method (ISAM) has been implemented in CMAQ to track contributions from source groups and regions to ambient levels and deposited amounts of O3. CMAQ...

Differences Between Magnitudes and Health Impacts of BC Emissions Across the United States Using 12 km Scale Seasonal Source Apportionment

EPA Science Inventory

Recent assessments have analyzed the health impacts of PM2.5 from emissions from different locations and sectors using simplified or reduced-form air quality models. Here we present an alternative approach using the adjoint of the Community Multiscale Air Quality (CMAQ) model, wh...

Development of the High-Order Decoupled Direct Method in Three Dimensions for Particulate Matter: Enabling Advanced Sensitivity Analysis in Air Quality Models

EPA Science Inventory

The high-order decoupled direct method in three dimensions for particular matter (HDDM-3D/PM) has been implemented in the Community Multiscale Air Quality (CMAQ) model to enable advanced sensitivity analysis. The major effort of this work is to develop high-order DDM sensitivity...

On the Relationship between Observed NLDN Lightning Strikes and Modeled Convective Precipitation Rates Parameterization of Lightning NOx Production in CMAQ

EPA Science Inventory

Lightning-produced nitrogen oxides (NOX=NO+NO2) in the middle and upper troposphere play an essential role in the production of ozone (O3) and influence the oxidizing capacity of the troposphere. Despite much effort in both observing and modeling lightning NOX during the past dec...

“FEST-C 1.0 for CMAQ Bi-directional NH3 Modeling and Apatial Allocator 4.1”

EPA Science Inventory

Accurate estimation of ammonia emissions in space and time has been a challenge in meso-scale air quality modeling. For instance, fertilizer applications vary in the date of application and amount by crop types and geographical area. With the support of the U.S EPA, we have devel...

Two Decades of WRF/CMAQ simulations over the continental ...

EPA Pesticide Factsheets

Confidence in the application of models for forecasting and regulatory assessments is furthered by conducting four types of model evaluation: operational, dynamic, diagnostic, and probabilistic. Operational model evaluation alone does not reveal the confidence limits that can be associated with modeled air quality concentrations. This paper presents novel approaches for performing dynamic model evaluation and for evaluating the confidence limits of ozone exceedances using the WRF/CMAQ model simulations over the continental United States for the period from 1990 to 2010. The methodology presented here entails spectral decomposition of ozone time series using the KZ filter to assess the variations in the strengths of the synoptic (i.e., weather-induced variation) and baseline (i.e., long-term variation attributable to emissions, policy, and trends) forcings embedded in the modeled and observed concentrations. A method is presented where the future year observations are estimated based on the changes in the concentrations predicted by the model applied to the current year observations. The proposed method can provide confidence limits for ozone exceedances for a given emission reduction scenario. We present and discuss these new approaches to identify the strengths of the model in representing the changes in simulated O3 air quality over the 21-year period. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates

Evaluation of model-predicted hazardous air pollutants (HAPs) near a mid-sized U.S. airport

NASA Astrophysics Data System (ADS)

Vennam, Lakshmi Pradeepa; Vizuete, William; Arunachalam, Saravanan

2015-10-01

Accurate modeling of aircraft-emitted pollutants in the vicinity of airports is essential to study the impact on local air quality and to answer policy and health-impact related issues. To quantify air quality impacts of airport-related hazardous air pollutants (HAPs), we carried out a fine-scale (4 × 4 km horizontal resolution) Community Multiscale Air Quality model (CMAQ) model simulation at the T.F. Green airport in Providence (PVD), Rhode Island. We considered temporally and spatially resolved aircraft emissions from the new Aviation Environmental Design Tool (AEDT). These model predictions were then evaluated with observations from a field campaign focused on assessing HAPs near the PVD airport. The annual normalized mean error (NME) was in the range of 36-70% normalized mean error for all HAPs except for acrolein (>70%). The addition of highly resolved aircraft emissions showed only marginally incremental improvements in performance (1-2% decrease in NME) of some HAPs (formaldehyde, xylene). When compared to a coarser 36 × 36 km grid resolution, the 4 × 4 km grid resolution did improve performance by up to 5-20% NME for formaldehyde and acetaldehyde. The change in power setting (from traditional International Civil Aviation Organization (ICAO) 7% to observation studies based 4%) doubled the aircraft idling emissions of HAPs, but led to only a 2% decrease in NME. Overall modeled aircraft-attributable contributions are in the range of 0.5-28% near a mid-sized airport grid-cell with maximum impacts seen only within 4-16 km from the airport grid-cell. Comparison of CMAQ predictions with HAP estimates from EPA's National Air Toxics Assessment (NATA) did show similar annual mean concentrations and equally poor performance. Current estimates of HAPs for PVD are a challenge for modeling systems and refinements in our ability to simulate aircraft emissions have made only incremental improvements. Even with unrealistic increases in HAPs aviation emissions the model could not match observed concentrations near the runway airport site. Our results suggest other uncertainties in the modeling system such as meteorology, HAPs chemistry, or other emission sources require increased scrutiny.

A Performance Evaluation of Lightning-NO Algorithms in CMAQ

EPA Science Inventory

In the Community Multiscale Air Quality (CMAQv5.2) model, we have implemented two algorithms for lightning NO production; one algorithm is based on the hourly observed cloud-to-ground lightning strike data from National Lightning Detection Network (NLDN) to replace the previous m...

A PRELIMINARY EVALUATION OF MODELS-3 CMAQ USING VISIBILITY PARAMETERS

EPA Science Inventory

Ambient air concentrations of fine particulate matter (PM 2.5) continue to be a major concern for the U.S. Environmental Protection Agency. High concentrations of fine particles have been linked to detrimental health effects (including an increase in mortality) and visibility ...

A COMPARISON OF AEROSOL OPTICAL DEPTH SIMULATED USING CMAQ WITH SATELLITE ESTIMATES

EPA Science Inventory

Satellite data provide new opportunities to study the regional distribution of particulate matter. The aerosol optical depth (AOD) - a derived estimate from the satellite measured irradiance, can be compared against model derived estimate to provide an evaluation of the columnar ...

A DYNAMIC SIMULATOR OF ENVIRONMENTAL CHEMICAL PARTITIONING

EPA Science Inventory

A version of the Community Multiscale Air Quality (CMAQ) model has been developed by the U.S. EPA that is capable of addressing the atmospheric fate, transport and deposition of some common trace toxics. An initial, 36-km rectangular grid-cell application for atrazine has been...

THE VALUE OF NUDGING IN THE METEOROLOGY MODEL FOR RETROSPECTIVE CMAQ SIMULATIONS

EPA Science Inventory

Using a nudging-based data assimilation approach throughout a meteorology simulation (i.e., as a "dynamic analysis") is considered valuable because it can provide a better overall representation of the meteorology than a pure forecast. Dynamic analysis is often used in...

Green Infrastructure in Kansas City

EPA Science Inventory

We use the state-of-the-art WRF-CMAQ coupled model to simulate the likely effects of a GI implementation strategy in Kansas City, MO/KS on regional meteorology and air quality changes. Two different land surface schemes (Pleim-Xiu and Noah) were implemented to characterize the di...

Predicting SOA from organic nitrates in the southeastern United States

EPA Science Inventory

Organic nitrates have been identified as an important component of ambient aerosol in the Southeast United States. In this work, we use the Community Multiscale Air Quality (CMAQ) model to explore the relationship between gas-phase production of organic nitrates and their subsequ...

A Five- Year CMAQ Model Performance for Wildfires and Prescribed Fires

EPA Science Inventory

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. Two components of the biomass burning inventory, wildfires and prescribed fires are routinely estimated in the national emissio...

PHOTOCHEMICAL AND AEROSOL MODELING WITH THE CMAQ PLUME-IN-GRID APPROACH

EPA Science Inventory

Emissions of nitrogen oxides (NO) and/or sulfur oxides (SO) from individual point sources, such as coal-fired power plants, with tall stacks contribute to reduced air quality. These primary species are important precursors of various oxidant species and secondary fine particul...

The congestion mitigation and air quality improvement (CMAQ) program : a summary of fifth year activities (FY 1996 : October 1995-September 1996)

DOT National Transportation Integrated Search

1998-02-01

This report is the fifth annual national review of activities funded under the : Congestion Mitigation and Air Quality Improvement (CMAQ) Program, covering : fiscal year (FY) 1996. It covers the distribution of funding among project : categories, an ...

New particle formation and growth in CMAQ: Application of comprehensive modal methods to observations during CalNex and CARES

EPA Science Inventory

The formation and growth of new atmospheric ultrafine particles are exceedingly complex processes and recent scientific efforts have grown our understanding of them tremendously. This presentation describes the effort to apply this new knowledge to the CMAQ chemical transport mod...

Public health impacts of secondary particulate formation from aromatic hydrocarbons in gasoline

PubMed Central

2013-01-01

Background Aromatic hydrocarbons emitted from gasoline-powered vehicles contribute to the formation of secondary organic aerosol (SOA), which increases the atmospheric mass concentration of fine particles (PM2.5). Here we estimate the public health burden associated with exposures to the subset of PM2.5 that originates from vehicle emissions of aromatics under business as usual conditions. Methods The PM2.5 contribution from gasoline aromatics is estimated using the Community Multiscale Air Quality (CMAQ) modeling system and the results are compared to ambient measurements from the literature. Marginal PM2.5 annualized concentration changes are used to calculate premature mortalities using concentration-response functions, with a value of mortality reduction approach used to monetize the social cost of mortality impacts. Morbidity impacts are qualitatively discussed. Results Modeled aromatic SOA concentrations from CMAQ fall short of ambient measurements by approximately a factor of two nationwide, with strong regional differences. After accounting for this model bias, the estimated public health impacts from exposure to PM2.5 originating from aromatic hydrocarbons in gasoline lead to a central estimate of approximately 3800 predicted premature mortalities nationwide, with estimates ranging from 1800 to over 4700 depending on the specific concentration-response function used. These impacts are associated with total social costs of $28.2B, and range from $13.6B to $34.9B in 2006$. Conclusions These preliminary quantitative estimates indicate particulates from vehicular emissions of aromatic hydrocarbons demonstrate a nontrivial public health burden. The results provide a baseline from which to evaluate potential public health impacts of changes in gasoline composition. PMID:23425393

Modeling the diurnal variability of agricultural ammonia in Bakersfield, California, during the CalNex campaign

NASA Astrophysics Data System (ADS)

Lonsdale, Chantelle R.; Hegarty, Jennifer D.; Cady-Pereira, Karen E.; Alvarado, Matthew J.; Henze, Daven K.; Turner, Matthew D.; Capps, Shannon L.; Nowak, John B.; Neuman, J. Andy; Middlebrook, Ann M.; Bahreini, Roya; Murphy, Jennifer G.; Markovic, Milos Z.; VandenBoer, Trevor C.; Russell, Lynn M.; Scarino, Amy Jo

2017-02-01

NH3 retrievals from the NASA Tropospheric Emission Spectrometer (TES), as well as surface and aircraft observations of NH3(g) and submicron NH4(p), are used to evaluate modeled concentrations of NH3(g) and NH4(p) from the Community Multiscale Air Quality (CMAQ) model in the San Joaquin Valley (SJV) during the California Research at the Nexus of Air Quality and Climate Change (CalNex) campaign. We find that simulations of NH3 driven with the California Air Resources Board (CARB) emission inventory are qualitatively and spatially consistent with TES satellite observations, with a correlation coefficient (r2) of 0.64. However, the surface observations at Bakersfield indicate a diurnal cycle in the model bias, with CMAQ overestimating surface NH3 at night and underestimating it during the day. The surface, satellite, and aircraft observations all suggest that daytime NH3 emissions in the CARB inventory are underestimated by at least a factor of 2, while the nighttime overestimate of NH3(g) is likely due to a combination of overestimated NH3 emissions and underestimated deposition.Running CMAQ v5.0.2 with the bi-directional NH3 scheme reduces NH3 concentrations at night and increases them during the day. This reduces the model bias when compared to the surface and satellite observations, but the increased concentrations aloft significantly increase the bias relative to the aircraft observations. We attempt to further reduce model bias by using the surface observations at Bakersfield to derive an empirical diurnal cycle of NH3 emissions in the SJV, in which nighttime and midday emissions differ by about a factor of 4.5. Running CMAQv5.0.2 with a bi-directional NH3 scheme together with this emissions diurnal profile further reduces model bias relative to the surface observations. Comparison of these simulations with the vertical profile retrieved by TES shows little bias except for the lowest retrieved level, but the model bias relative to flight data aloft increases slightly. Our results indicate that both diurnally varying emissions and a bi-directional NH3 scheme should be applied when modeling NH3(g) and NH4(p) in this region. The remaining model errors suggest that the bi-directional NH3 scheme in CMAQ v5.0.2 needs further improvements to shift the peak NH3 land-atmosphere flux to earlier in the day. We recommend that future work include updates to the current CARB NH3 inventory to account for NH3 from fertilizer application, livestock, and other farming practices separately; adding revised information on crop management practices specific to the SJV region to the bi-directional NH3 scheme; and top-down studies focused on determining the diurnally varying biases in the canopy compensation point that determines the net land-atmosphere NH3 fluxes.

A Novel Method to Estimate Surface NO_{2} Concentrations from the Space-borne Ozone Monitoring Instrument

NASA Astrophysics Data System (ADS)

Li, Yanshun; Zhang, Qiang; Geng, Guannan; Zheng, Yixuan; Guo, Jianping

2017-04-01

Atmospheric NO2near the surface has notable health effects and is precursor of tropospheric ozone. In this work, we propose a novel method to estimate daily surface NO2 concentrations from the Ozone Monitoring Instrument (OMI) with improved accuracy. Two chemical transport models GEOS-Chem and WRF/CMAQ are used to simulate converting factors between OMI column densities and surface concentrations. GEOS-Chem is found to better capture the distribution of converting factors, while CMAQ has advantage in simulating the magnitude. We combine the two models to calculate optimal values of converting factors and further constrain them by using colocated boundary layer heights (BLH) derived from fine-resolution sounding observations made at OMI overpass time. Calculated converting factors over Chinese Mainland vary by more than three orders of magnitude (10-18 ˜10-15 μgṡcm-1ṡmolecule-1), indicating complexity of NO2 vertical structure over large spatial extent. We generate a map of surface NO2 mass concentrations during June 2013 from OMI retrievals at 0.1˚ ×0.1˚ grids. Estimated concentrations from our novel method show reasonable spatial agreement with in situ chemiluminescent measurements (R = 0.70, Slope = 0.58, N = 353), which significantly outperform estimations using only GEOS-Chem (R = 0.60, Slope = 0.20, N = 353) or WRF/CMAQ (R = 0.19, Slope = 0.52, N = 353) to simulate the converting factor. Preliminary results show that the novel method developed in this study could improve capability of satellite sensors to quantify surface NO2 pollution.

Enhanced representation of soil NO emissions in the ...

EPA Pesticide Factsheets

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12 km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and

Diagnostic Air Quality Model Evaluation of Source-Specific ...

EPA Pesticide Factsheets

Ambient measurements of 78 source-specific tracers of primary and secondary carbonaceous fine particulate matter collected at four midwestern United States locations over a full year (March 2004–February 2005) provided an unprecedented opportunity to diagnostically evaluate the results of a numerical air quality model. Previous analyses of these measurements demonstrated excellent mass closure for the variety of contributing sources. In this study, a carbon-apportionment version of the Community Multiscale Air Quality (CMAQ) model was used to track primary organic and elemental carbon emissions from 15 independent sources such as mobile sources and biomass burning in addition to four precursor-specific classes of secondary organic aerosol (SOA) originating from isoprene, terpenes, aromatics, and sesquiterpenes. Conversion of the source-resolved model output into organic tracer concentrations yielded a total of 2416 data pairs for comparison with observations. While emission source contributions to the total model bias varied by season and measurement location, the largest absolute bias of −0.55 μgC/m3 was attributed to insufficient isoprene SOA in the summertime CMAQ simulation. Biomass combustion was responsible for the second largest summertime model bias (−0.46 μgC/m3 on average). Several instances of compensating errors were also evident; model underpredictions in some sectors were masked by overpredictions in others. The National Exposure Research L

Diagnostic air quality model evaluation of source-specific primary and secondary fine particulate carbon.

PubMed

Napelenok, Sergey L; Simon, Heather; Bhave, Prakash V; Pye, Havala O T; Pouliot, George A; Sheesley, Rebecca J; Schauer, James J

2014-01-01

Ambient measurements of 78 source-specific tracers of primary and secondary carbonaceous fine particulate matter collected at four midwestern United States locations over a full year (March 2004-February 2005) provided an unprecedented opportunity to diagnostically evaluate the results of a numerical air quality model. Previous analyses of these measurements demonstrated excellent mass closure for the variety of contributing sources. In this study, a carbon-apportionment version of the Community Multiscale Air Quality (CMAQ) model was used to track primary organic and elemental carbon emissions from 15 independent sources such as mobile sources and biomass burning in addition to four precursor-specific classes of secondary organic aerosol (SOA) originating from isoprene, terpenes, aromatics, and sesquiterpenes. Conversion of the source-resolved model output into organic tracer concentrations yielded a total of 2416 data pairs for comparison with observations. While emission source contributions to the total model bias varied by season and measurement location, the largest absolute bias of -0.55 μgC/m(3) was attributed to insufficient isoprene SOA in the summertime CMAQ simulation. Biomass combustion was responsible for the second largest summertime model bias (-0.46 μgC/m(3) on average). Several instances of compensating errors were also evident; model underpredictions in some sectors were masked by overpredictions in others.

On the Relationship between Observed NLDN Lightning ...

EPA Pesticide Factsheets

Lightning-produced nitrogen oxides (NOX=NO+NO2) in the middle and upper troposphere play an essential role in the production of ozone (O3) and influence the oxidizing capacity of the troposphere. Despite much effort in both observing and modeling lightning NOX during the past decade, considerable uncertainties still exist with the quantification of lightning NOX production and distribution in the troposphere. It is even more challenging for regional chemistry and transport models to accurately parameterize lightning NOX production and distribution in time and space. The Community Multiscale Air Quality Model (CMAQ) parameterizes the lightning NO emissions using local scaling factors adjusted by the convective precipitation rate that is predicted by the upstream meteorological model; the adjustment is based on the observed lightning strikes from the National Lightning Detection Network (NLDN). For this parameterization to be valid, the existence of an a priori reasonable relationship between the observed lightning strikes and the modeled convective precipitation rates is needed. In this study, we will present an analysis leveraged on the observed NLDN lightning strikes and CMAQ model simulations over the continental United States for a time period spanning over a decade. Based on the analysis, new parameterization scheme for lightning NOX will be proposed and the results will be evaluated. The proposed scheme will be beneficial to modeling exercises where the obs

Cross-cultural attitudes of flight crew regarding CRM

NASA Technical Reports Server (NTRS)

Merritt, Ashleigh

1993-01-01

This study asks if the Cockpit Management Attitude Questionnaire (CMAQ) can detect differences across countries, and/or across occupations. And if so, can those differences be interpreted? Research has shown that the CMAQ is sensitive to attitude differences between and within organizations, thereby demonstrating its effectiveness with American populations. But the CMAQ was originally designed by American researchers and psychometrically refined for American pilots. The items in the questionnaire, though general in nature, still reflect the ubiquitous Western bias, because the items were written by researchers from and for the one culture. Recognizing this constraint, this study is nonetheless interested in attitudes toward crew behavior, and how those attitudes may vary across country and occupation.

EnviroAtlas - Atmospheric Nitrogen Deposition by 12-digit HUC for the Conterminous United States (2002)

EPA Pesticide Factsheets

This EnviroAtlas dataset includes annual nitrogen and sulfur deposition within each 12-digit HUC subwatershed for the year 2002. Values are provided for total oxidized nitrogen (HNO3, NO, NO2, N2O5, NH3, HONO, PAN, organic nitrogen, and particulate NO3), oxidized nitrogen wet deposition, oxidized nitrogen dry deposition, total reduced nitrogen (NH3 and particulate NH4), reduced nitrogen dry deposition, reduced nitrogen wet deposition, total dry nitrogen deposition, total wet nitrogen deposition, total nitrogen deposition (wet+dry), total sulfur (SO2 + particulate SO4) dry deposition, total sulfur wet deposition, and total sulfur deposition. The dataset is based on output from the Community Multiscale Air Quality modeling system (CMAQ) v5.0.2 run using the bidirectional flux option for the 12-km grid size for the US, Canada, and Mexico. The CMAQ output has been post-processed to adjust the wet deposition for errors in the location and amount of precipitation and for regional biases in the TNO3 (HNO3 + NO3), NHx (NH4 + NH3), and sulfate wet deposition. Model predicted values of dry deposition were not adjusted. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadab

EnviroAtlas - Atmospheric Nitrogen and Sulfur Deposition by 12-digit HUC for the Conterminous United States (2011)

EPA Pesticide Factsheets

This EnviroAtlas dataset includes annual nitrogen and sulfur deposition within each 12-digit HUC subwatershed for the year 2011. Values are provided for total oxidized nitrogen (HNO3, NO, NO2, N2O5, NH3, HONO, PAN, organic nitrogen, and particulate NO3), oxidized nitrogen wet deposition, oxidized nitrogen dry deposition, total reduced nitrogen (NH3 and particulate NH4), reduced nitrogen dry deposition, reduced nitrogen wet deposition, total dry nitrogen deposition, total wet nitrogen deposition, total nitrogen deposition (wet+dry), total sulfur (SO2 + particulate SO4) dry deposition, total sulfur wet deposition, and total sulfur deposition. The dataset is based on output from the Community Multiscale Air Quality modeling system (CMAQ) run using the bidirectional flux option for the 12-km grid size for the US, Canada, and Mexico. The CMAQ output has been post-processed to adjust the wet deposition for errors in the location and amount of precipitation and for regional biases in the TNO3 (HNO3 + NO3), NHx (NH4 + NH3), and sulfate wet deposition. Model predicted values of dry deposition were not adjusted. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data

EnviroAtlas - Atmospheric Nitrogen Deposition by 12-digit HUC for the Conterminous United States (2006)

EPA Pesticide Factsheets

This EnviroAtlas dataset includes annual nitrogen and sulfur deposition within each 12-digit HUC subwatershed for the year 2006. Values are provided for total oxidized nitrogen (HNO3, NO, NO2, N2O5, NH3, HONO, PAN, organic nitrogen, and particulate NO3), oxidized nitrogen wet deposition, oxidized nitrogen dry deposition, total reduced nitrogen (NH3 and particulate NH4), reduced nitrogen dry deposition, reduced nitrogen wet deposition, total dry nitrogen deposition, total wet nitrogen deposition, total nitrogen deposition (wet+dry), total sulfur (SO2 + particulate SO4) dry deposition, total sulfur wet deposition, and total sulfur deposition. The dataset is based on output from the Community Multiscale Air Quality modeling system (CMAQ) run using the bidirectional flux option for the 12-km grid size for the US, Canada, and Mexico. The CMAQ output has been post-processed to adjust the wet deposition for errors in the location and amount of precipitation and for regional biases in the TNO3 (HNO3 + NO3), NHx (NH4 + NH3), and sulfate wet deposition. Model predicted values of dry deposition were not adjusted. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable dat

A new physically-based windblown dust emission parametrization in CMAQ

EPA Science Inventory

Dust has significant impacts on weather and climate, air quality and visibility, and human health; therefore, it is important to include a windblown dust emission module in atmospheric and air quality models. In this presentation, we summarize our efforts in development of a phys...

ADVANCED URBANIZED METEOROLOGICAL MODELING AND AIR QUALITY SIMULATIONS WITH CMAQ AT NEIGHBORHOOD SCALES

EPA Science Inventory

We present results from a study testing the new boundary layer parameterization method, the canopy drag approach (DA) which is designed to explicitly simulate the effects of buildings, street and tree canopies on the dynamic, thermodynamic structure and dispersion fields in urban...

CMAQ modeling in the nitrogen inventory study in the Nooksack-Abbotsford-Sumas Transboundary Region

EPA Science Inventory

Optimizing nitrogen (N) use for food production while minimizing the release of N and co-pollutants to the environment is an important challenge. The Nooksack-Abbotsford-Sumas Transboundary (NAS) Region, spanning a portion of the western interface of British Columbia, Washington...

A COMPARISON OF AEROSOL OPTICAL DEPTH SIMULATED USING CMAQ WITH SATELLITE ESTIMATES

EPA Science Inventory

Satellite data provide new opportunities to study the regional distribution of particulate matter.

The aerosol optical depth (AOD) - a derived estimate from the satellite-measured radiance, can be compared against model estimates to provide an evaluation of the columnar ae...

Estimation of NH3 Bi-Directional Flux from Managed Agricultural Soils

EPA Science Inventory

The Community Multi-Scale Air Quality model (CMAQ v4.7) contains a bi-directional ammonia (NH₃) flux option that computes emission and deposition of ammonia derived from commercial fertilizer via a temperature dependent parameterization of canopy and soil compensation ...

Improved MEGAN predictions of biogenic isoprene in the contiguous United States

NASA Astrophysics Data System (ADS)

Wang, Peng; Schade, Gunnar; Estes, Mark; Ying, Qi

2017-01-01

Isoprene emitted from biogenic sources significantly contributes to ozone and secondary organic aerosol formation in the troposphere. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) has been widely used to estimate isoprene emissions from local to global scales. However, previous studies have shown that MEGAN significantly over-predicts isoprene emissions in the contiguous United States (US). In this study, ambient isoprene concentrations in the US were simulated by the Community Multiscale Air Quality (CMAQ) model (v5.0.1) using biogenic emissions estimated by MEGAN v2.10 with several different gridded isoprene emission factor (EF) fields. Best isoprene predictions were obtained with the EF field based on the Biogenic Emissions Landcover Database v4 (BELD4) from US EPA for its Biogenic Emission Inventory System (BEIS) model v3.61 (MEGAN-BEIS361). A seven-month simulation (April to October 2011) of isoprene emissions with MEGAN-BEIS361 and ambient concentrations using CMAQ shows that observed spatial and temporal variations (both diurnal and seasonal) of isoprene concentrations can be well predicted at most non-urban monitors using isoprene emission estimation from the MEGAN-BEIS361 without significant biases. The predicted monthly average vertical column density of formaldehyde (HCHO), a reactive volatile organic compound with significant contributions from isoprene oxidation, generally agree with the spatial distribution of HCHO column density derived using satellite data collected by the Ozone Monitoring Instrument (OMI), although summer month vertical column densities in the southeast US were overestimated, which suggests that isoprene emission might still be overestimated in that region. The agreement between observation and prediction may be further improved if more accurate PAR values, such as those derived from satellite-based observations, were used in modeling the biogenic emissions.

Application of Satellite and Ozonesonde Data to the Study of Nighttime Tropospheric Ozone Impacts and Relationship to Air Quality

NASA Astrophysics Data System (ADS)

Osterman, G. B.; Eldering, A.; Neu, J. L.; Tang, Y.; McQueen, J.; Pinder, R. W.

2011-12-01

To help protect human health and ecosystems, regional-scale atmospheric chemistry models are used to forecast high ozone events and to design emission control strategies to decrease the frequency and severity of ozone events. Despite the impact that nighttime aloft ozone can have on surface ozone, regional-scale atmospheric chemistry models often do not simulate the nighttime ozone concentrations well and nor do they sufficiently capture the ozone transport patterns. Fully characterizing the importance of the nighttime ozone has been hampered by limited measurements of the vertical distribution of ozone and ozone-precursors. The main focus of this work is to begin to utilize remote sensing data sets to characterize the impact of nighttime aloft ozone to air quality events. We will describe our plans to use NASA satellite data sets, transport models and air quality models to study ozone transport, focusing primarily on nighttime ozone and provide initial results. We will use satellite and ozonesonde data to help understand how well the air quality models are simulating ozone in the lower free troposphere and attempt to characterize the impact of nighttime ozone to air quality events. Our specific objectives are: 1) Characterize nighttime aloft ozone using remote sensing data and sondes. 2) Evaluate the ability of the Community Multi-scale Air Quality (CMAQ) model and the National Air Quality Forecast Capability (NAQFC) model to capture the nighttime aloft ozone and its relationship to air quality events. 3) Analyze a set of air quality events and determine the relationship of air quality events to the nighttime aloft ozone. We will achieve our objectives by utilizing the ozone profile data from the NASA Earth Observing System (EOS) Tropospheric Emission Spectrometer (TES) and other sensors, ozonesonde data collected during the Aura mission (IONS), EPA AirNow ground station ozone data, the CMAQ continental-scale air quality model, and the National Air Quality Forecast model.

EVALUATING TEMPORAL AND SPATIAL O3 AND PM2.5 PATTERNS SIMULATED DURING AN ANNUAL CMAS APPLICATION OVER THE CONTINENTAL U.S.

EPA Science Inventory

Over the next several years, grid-based photochemical models such as the Community Multiscale Air Quality (CMAQ) model and REMSAD will be used by regulatory agencies to design emission control strategies aimed at meeting and maintaining the NAAQS for O3 and PM2.5. The evaluation ...

Lightning NOx Production in CMAQ: Part II - Parameterization Based on Relationship between Observed NLDN Lightning Strikes and Modeled Convective Precipitation Rates

EPA Science Inventory

Lightning-produced nitrogen oxides (NOX=NO+NO2) in the middle and upper troposphere play an essential role in the production of ozone (O3) and influence the oxidizing capacity of the troposphere. Despite much effort in both observing and modeling lightning NOX during the past dec...

NAQFC Reports

Science.gov Websites

Forecasts Recent NCEP NAM-CMAQ AQF Reports EPA CMAQ Bibliography 2016-2017 Huang, J., et al., 2017: Wea Stajner, I., et al., 2016: EGU: NAQFC Overview Huang, J., et al. 2016: AMS: Bias Correction Stajner, I, et . Huang, J., et al.,(2015): CMAS, Testing of two bias correction approaches for reducing biases of

Improving Air Quality Forecasts with AURA Observations

NASA Technical Reports Server (NTRS)

Newchurch, M. J.; Biazer, A.; Khan, M.; Koshak, W. J.; Nair, U.; Fuller, K.; Wang, L.; Parker, Y.; Williams, R.; Liu, X.

2008-01-01

Past studies have identified model initial and boundary conditions as sources of reducible errors in air-quality simulations. In particular, improving the initial condition improves the accuracy of short-term forecasts as it allows for the impact of local emissions to be realized by the model and improving boundary conditions improves long range transport through the model domain, especially in recirculating anticyclones. During the August 2006 period, we use AURA/OMI ozone measurements along with MODIS and CALIPSO aerosol observations to improve the initial and boundary conditions of ozone and Particulate Matter. Assessment of the model by comparison of the control run and satellite assimilation run to the IONS06 network of ozonesonde observations, which comprise the densest ozone sounding campaign ever conducted in North America, to AURA/TES ozone profile measurements, and to the EPA ground network of ozone and PM measurements will show significant improvement in the CMAQ calculations that use AURA initial and boundary conditions. Further analyses of lightning occurrences from ground and satellite observations and AURA/OMI NO2 column abundances will identify the lightning NOx signal evident in OMI measurements and suggest pathways for incorporating the lightning and NO2 data into the CMAQ simulations.

Development and analysis of air quality modeling simulations for hazardous air pollutants

NASA Astrophysics Data System (ADS)

Luecken, D. J.; Hutzell, W. T.; Gipson, G. L.

The concentrations of five hazardous air pollutants were simulated using the community multi-scale air quality (CMAQ) modeling system. Annual simulations were performed over the continental United States for the entire year of 2001 to support human exposure estimates. Results are shown for formaldehyde, acetaldehyde, benzene, 1,3-butadiene and acrolein. Photochemical production in the atmosphere is predicted to dominate ambient formaldehyde and acetaldehyde concentrations, and to account for a significant fraction of ambient acrolein concentrations. Spatial and temporal variations are large throughout the domain over the year. Predicted concentrations are compared with observations for formaldehyde, acetaldehyde, benzene and 1,3-butadiene. Although the modeling results indicate an overall slight tendency towards underprediction, they reproduce episodic and seasonal behavior of pollutant concentrations at many monitors with good skill.

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Johnson, Hoyt; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Remote Sensing and Spatial Growth Modeling Coupled With Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Estes, M. G.; Crosson, W. L.; Johnson, H.; Khan, M.

2006-05-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world's population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta's growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Modeling biogenic secondary organic aerosol (BSOA) formation from monoterpene reactions with NO3: A case study of the SOAS campaign using CMAQ

NASA Astrophysics Data System (ADS)

Qin, Momei; Hu, Yongtao; Wang, Xuesong; Vasilakos, Petros; Boyd, Christopher M.; Xu, Lu; Song, Yu; Ng, Nga Lee; Nenes, Athanasios; Russell, Armistead G.

2018-07-01

Monoterpenes react with nitrate radicals (NO3), contributing substantially to nighttime organic aerosol (OA) production. In this study, the role of reactions of monoterpenes + NO3 in forming biogenic secondary organic aerosol (BSOA) was examined using the Community Multiscale Air Quality (CMAQ) model, with extended emission profiles of biogenic volatile organic compounds (BVOCs), species-specific representations of BSOA production from individual monoterpenes and updated aerosol yields for monoterpene + NO3. The model results were compared to detailed measurements from the Southern Oxidants and Aerosol Study (SOAS) at Centreville, Alabama. With the more detailed model, monoterpene-derived BSOA increased by ∼1 μg m-3 at night, accounting for one-third of observed less-oxidized oxygenated OA (LO-OOA), more closely agreeing with observations (lower error, stronger correlation). Implementation of a multigenerational oxidation approach resulted in the model capturing elevated OA episodes. With the aging model, aged semi-volatile organic compounds (ASVOCs) contributed over 60% of the monoterpene-derived BSOA, followed by SOA formation via nitrate radical chemistry, making up to 34% of that formed at night. Among individual monoterpenes, β-pinene and limonene contributed most to the monoterpene-derived BSOA from nighttime reactions.

Simulating Emission and Chemical Evolution of Coarse Sea-Salt Particles in the Community Multiscale Air Quality (CMAQ) Model

EPA Science Inventory

Chemical processing of sea-salt particles in coastal environments significantly impacts concentrations of particle components and gas-phase species and has implications for human exposure to particulate matter and nitrogen deposition to sensitive ecosystems. Emission of sea-sal...

A PRELIMINARY EVALUATION OF MODELS-3 CMAQ USING PARTICULATE MATTER DATA FROM THE IMPROVE NETWORK

EPA Science Inventory

The Clean Air Act and its Amendments require the United States Environmental Protection Agency (EPA) to establish National Ambient Air Quality Standards for Particulate Matter (PM) and to assess current and future air quality regulations designed to protect human health and wel...

Application of Lidar Data to the Performance Evaluations of CMAQ Model

EPA Science Inventory

The Tropospheric Ozone (O3) Lidar Network (TOLNet) provides time/height O3 measurements from near the surface to the top of the troposphere to describe in high-fidelity spatial-temporal distributions, which is uniquely useful to evaluate the temporal evolution of O3 profiles in a...

New framework for extending cloud chemistry in the Community Multiscale Air Quality (CMAQ) modeling

EPA Science Inventory

Clouds and fogs significantly impact the amount, composition, and spatial distribution of gas and particulate atmospheric species, not least of which through the chemistry that occurs in cloud droplets. Atmospheric sulfate is an important component of fine aerosol mass and in an...