Quality Assurance Project Plan. Project

Transcription

1 Quality Assurance Project Plan Project Analysis of Global Models as a Source of Regional Background Ozone in Texas Chris Emery ENVIRON International Corporation Meiyun Lin Princeton University Summary of Project QAPP Category Number: III Type of Project: Research or Development (Modeling) QAPP Requirements: This QAPP includes descriptions of the project and objectives; organization and responsibilities; scientific approach; air quality modeling procedures; quality metrics; data analysis, interpretation, and management; reporting; and references. QA Requirements: Audits of Data Quality: Cat III = 10% Required Report of QA Findings: In final report Revision #: 2

2 DISTRIBUTION LIST Elena McDonald-Buller, Project Manager, Texas Air Quality Research Program Cyril Durrenberger, Quality Assurance Project Plan Officer, Texas Air Quality Research Program Jim Smith, Project Liaison, Texas Commission on Environmental Quality Chris Owen, Quality Assurance Project Plan Officer, Texas Commission on Environmental Quality Maria Stanzione, Program Manager, Texas Air Quality Research Program 2

3

4 1. PROJECT DESCRIPTION AND OBJECTIVES 1.1 Problem Statement The production, transport, and fate of tropospheric ozone are highly dynamic processes with contributions from a multitude of anthropogenic and natural sources spanning spatial scales from local to global. The US Environmental Protection Agency (EPA) requires the use of regional photochemical models to demonstrate that local emission control plans will achieve the federal standard for ground-level ozone. As the ozone standard is lowered, sources contributing to uncontrollable background ozone become more significant and must be more accurately accounted. In response, regulatory modeling applications have employed continuously larger domains to explicitly include sources over broader portions of the continent. Regional models now include worldwide contributions by deriving boundary conditions from global models. As global models continue to emerge and improve, their contributions to background ozone as represented in regional models need to be evaluated. The Texas Commission on Environmental Quality (TCEQ) uses the Comprehensive Air quality Model with extensions (CAMx) for research and regulatory photochemical modeling. Two popular global models have been routinely coupled to CAMx: the Goddard Earth Observing System - Chemistry model (GEOS-Chem), developed and distributed by Harvard University, and the Model for OZone and Related chemical Tracers (MOZART), developed and distributed by the National Center for Atmospheric Research (NCAR). A newer global model called AM3, which is the atmospheric component of the CM3 global coupled atmosphere-oceans-land-sea ice model, is developed by Princeton University and the National Oceanic and Atmospheric Administration s Geophysical Fluid Dynamics Laboratory (GFDL). 1.2 Project Objectives The objective of this project is to develop boundary condition inputs for CAMx utilizing output from all three global models (GEOS-Chem, MOZART, and AM3) and to analyze the sensitivity of simulated ozone to regional boundary conditions. We will develop quantitative comparisons of these global models with respect to their ability to provide accurate and reasonable boundary conditions for regional downscaling, particularly as it applies to regulatory ozone modeling. 4

5 2. ORGANIZATION AND RESPONSIBILITIES 2.1 Personnel and Responsibilities This project is a collaborative effort between ENVIRON International Corporation (ENVIRON) and Dr. Meiyun Lin of Princeton University. Mr. Christopher Emery, senior manager at ENVIRON, is the Principal Investigator with overall responsibility for the research and associated quality assurance. The project will be overseen by the Texas Air Quality Research Program (AQRP) Project Manager Dr. Elena McDonald-Buller and TCEQ Project Liaison Dr. Jim Smith. Project participants and their responsibilities are provided in Table 1 below. Table 1. Project participants and their affiliations and key responsibilities. Participant (Organization) Key Responsibilities Mr. Christopher Emery (ENVIRON) Principal Investigator with overall responsibility for the air quality modeling studies, including quality assurance and quality control activities, and reporting. Dr. Greg Yarwood (ENVIRON) Principal at ENVIRON, who will provide technical input on chemical mapping and model performance techniques. Mr. Ed Tai (ENVIRON) Mr. Jeremiah Johnson (ENVIRON) Dr. Meiyun Lin (Princeton) Senior Associate at ENVIRON who will lead AM3-CAMx interface development, CAMx modeling, global and CAMx model performance evaluation. Senior Associate at ENVIRON who will provide general technical assistance and graphics development. Research Associate who will lead AM3 modeling and assist in AM3-CAMx interface development. 2.2 Schedule The schedule for specific tasks is listed in Table 2. Table 2. Schedule of project activities. ID Task 1/13 2/13 3/13 4/13 5/13 6/13 7/13 8/13 1 Global Model Evaluation X X X 2 Global-Regional Coupling and MPE X X X 3 Reporting X X X X 5

6 3. SCIENTIFIC APPROACH 3.1 Evaluation of Global Modeling Products Over North America The standard versions of MOZART and GOES-Chem both employ 2-3 degree latitude/longitude global resolution ( km). MOZART-4 uses 28 layers to resolve the troposphere and the lower stratosphere (~40 km) while GOES-Chem uses 47 layers up to 80 km. ENVIRON runs GEOS-Chem to generate global fields at 3-hourly intervals for use in developing CAMx boundary conditions for continental-scale applications. MOZART 6-hourly model output fields are available from NCAR spanning 2003 through mid MOZART output has been routinely used to generate CAMx boundary conditions for several projects in Texas. Princeton/GFDL has run AM3 for the years with ~200 km resolution and 48 layers up to 86 km. However, only daily-averaged fields of a few key long-lived species (e.g., ozone, peroxyacetyl nitrate [PAN], carbon monoxide (CO), particulate matter [PM], etc.) have been archived at GFDL. Concentration fields of ozone and other species generated by GEOS-Chem, MOZART-4, and AM3 will be inter-compared for the period spanning April-October 2008, which is the period we will model with CAMx (described below). ENVIRON will run GEOS-Chem for 2008; ENVIRON already possess MOZART data for Princeton will run AM3 for 2008 on its native ~200 km global grid system to develop 6-hourly three-dimensional output fields containing speciated nitrogen oxides (NOx and NOy), volatile organic compounds (VOC), CO, and ozone concentrations. Princeton will post-processes raw output fields from the native grid system to a standard latitude/longitude grid similar to that of GEOS-Chem and MOZART, and provide to ENVIRON for analysis. Surface ozone predictions will be analyzed against available rural surface measurements from the EPA Clean Air Status and Trends Network (CASTNET; javaweb/index.html). The surface evaluation will focus on Texas, the Gulf of Mexico and the southeastern US, where all three global models tend to over predict surface ozone. Differences in performance will be tabulated on a monthly basis. Additionally, we will graphically compare global model predictions of ozone aloft over the US against ozonesonde measurement data. Routine ozonesonde measurements are available about every 6th day at several sites across the US, including Trinidad Head, California; Boulder, Colorado; and Huntsville, Alabama (ftp://ftp.cmdl.noaa.gov/ozwv/ozone/). Additionally, there were approximately 45 ozonesonde launches in Houston during 2008 as part of the Tropospheric Ozone Pollution Project (TOPP; #2008). First, individual observed ozone profiles will be translated to the model vertical grid. Then season-mean observed and simulated ozone profiles will be plotted for each ozonesonde site, along with error bars at each vertical grid level representing the seasonal standard deviation among the individual profiles. 3.2 Global-Regional Model Coupling and Performance Comparison CAMx will be run using the boundary conditions generated from each of the three global models, from which output model predictions of surface ozone will be compared. We will employ an April-October 2008 CAMx dataset developed by Alpine Geophysics for the Eight Hour Coalition (a cooperative of Houston petrochemical and refining companies). This dataset includes both ozone and PM precursor emissions, has a large 12 km grid (Figure 1), and uses emissions data from both the TCEQ and EPA (Table 3). Emissions are chemically speciated for the Carbon Bond 2005 (CB05) chemical mechanism but can be used with the newer Carbon Bond version 6 (CB6) mechanism due to backwards compatibility. Biogenic 6

7 emissions are available from both MEGAN and GloBEIS and a selection can be made based on model performance or other considerations. The 36 and 12 km grids will be run in 2-way interactive nested mode; the 4-km grid shown in Figure 1 will not be used. Boundary conditions will be developed for the 36 km CONUS grid shown in Figure 1 using the output from GEOS-Chem and AM3 (MOZART boundary conditions for this grid and modeling period have already been developed by ENVIRON for other projects). With assistance from Princeton University, ENVIRON will develop a new interface tool to translate AM3 output to the boundary condition inputs required by CAMx. Special consideration will be given to the chemical mapping of AM3 NOx, NOy, and VOC species to the CB6 photochemical mechanism employed in CAMx. Table 3. Model configuration and default input data for the 2008 CAMx model. Model Component Description Modeling Period April 1 - October 18, 2008 Modeling Domain 36/12/4 km Vertical Structure 30 Vertical Layers Meteorological Model WRF Chemical Mechanism CB05 Boundary Conditions MOZART4 Deposition Zhang Emissions Biogenics MEGAN or GloBEIS On Road Mobile MOVES Off Road Mobile EPA NEI Shipping EPA NEI Area Source EPA NEI Point Source TCEQ Wildfire BlueSky/EPA SMARTFIRE 2 Figure 1. CAMx modeling grids: Outer 36 km grid, 12 km nest (red), 4 km nest (green). 7

8 Although this project will not address particulate matter, the AM3-CAMx interface will be developed for PM as well. We will evaluate resulting ozone patterns on both modeling grids, graphically intercompare results, and statistically gauge performance differences against rural hourly surface CASTNET ozone measurements throughout the south-central, southeastern, and southwestern US, with special emphasis on Texas. Statistics will include standard fractional bias and error as recommended in EPA modeling guidance for ozone. Evaluation against urban-oriented Air Quality System (AQS) sites will not be performed as the analysis will focus on background ozone levels as introduced to CAMx via boundary conditions. Performance at urban monitors will be dominated by simulated local emissions, which decay background ozone and thus obscure differences among the three global model contributions. Additionally, CAMx results will be compared to available Houston ozonesonde data throughout 2008 to evaluate ozone differences above the Houston urban boundary layer arising from the use of the three sets of boundary conditions. Graphics similar to the global model inter-comparisons will be developed. Results from all of these analyses will lead to a recommendation on which global model(s) appear to be most appropriate for Texas-specific application. 8

9 4. QUALITY METRICS The U.S. Environmental Protection Agency (EPA) has not specified specific data quality requirements for this work, nor is it expected that the EPA will evaluate this specific application. All modeling platforms to be employed in this project have undergone significant levels of development and evaluation. Summaries of each model are provided at their respective web pages, while a multitude of model descriptions and application results are published in peerreviewed journal articles, for example: CAMx ( ENVIRON, 2012; Emery et al., 2012) GEOS-Chem ( Zhang et al., 2011) MOZART ( Emmons et al., 2010) AM3 ( Donner et al., 2011) Data to be accessed and/or developed for this study are of three types: (1) Global model output datasets for the year 2008 from GEOS-Chem, MOZART-4, and AM3. These include all photochemically-relevant chemical species, including primary nitrogen oxides (NOx = NO+NO 2 ) and NOx oxidation products (NOy), VOC, CO, and ozone. Three-dimensional gridded fields are required on output latitude/longitude grids every 3 to 6 hours (depending on the model). (2) Model input data for the CAMx model for the year Alpine Geophysics 2008 CONUS database will be used (as described in detail in Section 3). (3) Surface-based hourly rural ozone measurement data from the EPA Clean Air Status and Trends Network (CASTNET; and routine aloft ozonesonde data across the US for the year 2008 (ftp://ftp.cmdl.noaa.gov/ozwv/ozone/). ENVIRON will run GEOS-Chem for 2008; we already possess MOZART data for Princeton will run AM3 for 2008 on its native ~200 km grid system to develop 6-hourly threedimensional output fields containing speciated NOx, NOy, VOC, CO, and ozone concentrations. All runs will be assessed for reasonableness using graphical software. ENVIRON will obtain the 2008 CAMx modeling database from Alpine Geophysics and run the episode as transferred to ensure replication of the results of Alpine using visualization and analytical software. A primary goal will be to check for spurious features or localized anomalies potentially caused by transmittal errors associated with the model input data and/or model configurations or by differences associated with the computing platform. ENVIRON will work with Alpine Geophysics (independently) to resolve discrepancies should they arise. Ozone measurement data will focus on rural sites from the CASTNET system, and less frequent aloft ozone profiles from routine ozonesondes launched usually once per week at several locations across the US. Such data will allow for assessment of modeled (both global and CAMx) background ozone levels that are not directly or heavily influenced by urban emissions. The instruments deployed for the CASTNET system and the ozonesonde program have undergone rigorous internal testing to determine their accuracy, time response, precision and potential artifacts. All of these characteristics have been reported in the peer reviewed literature for these instruments. Validiation and quality assurance steps are independently conducted by the respective reporting institutions to flag missing or suspect data due to a variety of causes. Only final quality-assured un-flagged data will be employed in the comparisons to modeling data. This work will result in the generation of new AM3-CAMx boundary condition interface. Boundary conditions developed from AM3 will be processed in a format suitable for input to 9

10 CAMx. Mapping of the magnitude and spatial distribution of ozone and precursor boundary condition estimates will be an important step to assure pre- and post-processing consistency and reasonableness. Discrepancies that warrant further investigation will be identified, and reconciliation approaches will be pursued as appropriate. The team anticipates that maps will be created using PAVE or alternative visualization software such as Surfer or NCAR/NCL, all of which are currently installed on ENVIRON s computer system. 10

11 5. DATA ANALYSIS, INTERPRETATION, AND MANAGEMENT The spatial and temporal performance of the global and regional photochemical models in simulating observed ozone and precursors throughout the 12 km grid for the 2008 historical ozone episode will be evaluated using both graphical and statistical methods that describe the range of predictions among the various model combinations. Graphical methods will include spatial maps and time-series comparing model predictions to observations. Graphics may be developed using a mix of several plotting applications, including GIS, PAVE, Surfer, and NCAR/NCL. Statistical methods will include computation of metrics for bias and error between predictions and observations for ozone and precursors. Standard statistical metrics as described in EPA air quality modeling guidance (EPA, 2007) will be calculated. These include normalized mean and fractional bias (NMB and FB), and normalized mean and fractional absolute error (NME and FE) (Table 4). Statistical calculations will be conducted for both 1 and 8 hour ozone predictions. Use of mean normalized bias (MNB) and error (MNE) is not encouraged due to the propensity for misinterpretation and lack of symmetry around zero (they tend to be skewed by low observed concentrations with the bias skewed towards large positive numbers). Linear regression analysis (e.g., coefficient of determination, r 2 ) will be utilized to examine the model s ability to capture observed variability. A member of the research team who did not conduct the actual fire emissions and air quality model input data processing and model simulations will review at least 10% of the input data and model output for quality assurance purposes. Data generated for this project, including model inputs, final model outputs and various air quality observational data and statistical performance calculations, will be securely archived during the project on portable hard drives and stored for a period of at least three years following the completion of the project. All data obtained for this project will be stored in electronic format. Our teams experience has been that 100+ GB hard drives provide an accessible and portable system for storing data files of the size routinely encountered in the type of modeling activities for this effort. If data are provided on paper, the paper documents will be scanned to electronic PDF files for storage. The University of Texas will receive an electronic copy of all data sets. 11

12 Table 4. Definition of performance metrics. Metric Definition 1 Mean Bias (MB) 1 Mean Error (ME) 1 Mean Normalized Bias (MNB) (-100% to +) Mean Normalized Error (MNE) (0% to +) Normalized Mean Bias (NMB) (-100% to +) Normalized Mean Error (NME) (0% to +) Fractional Bias (FB) (-200% to +200%) Fractional Error (FE) (0% to +200%) Coefficient of Determination (r 2 ) (0 to 1) 1 and are prediction and observation at the i-th site, respectively; and are mean prediction and observation, respectively. 12

13 6. REPORTING A final Technical Work Plan (statement of work, schedule, key personnel, budget and justification) and Quality Assurance Project Plan (this document) will be submitted in January Monthly financial and technical reports will be submitted throughout the duration of the project. The methodologies and results for the global model evaluation, global-regional interface development, and regional air quality data acquisition, processing, modeling, and analyses will be documented in the final project report. A final technical report will be submitted by August 31, 2013, preceded by a draft final report 30 working days earlier. The final report will meet State of Texas Accessibility requirements in 1 TAC 213. Electronic copies of all text, graphic, spreadsheet files and models used in the preparation of any documents related to the project reports, to document results and conclusions (e.g. sampling data, work files, etc.) or developed as work products under this Contract, will be supplied the conclusion of the project. All copies of deliverable documents and other work products will be provided in Microsoft Word and PDF format. During or after completion of the project, the investigators anticipate the preparation of conference presentations and manuscripts for submission to appropriate peer-reviewed journals in the field. Mr. Emery and Dr. Lin will supervise the completion of all reports, presentations, and manuscripts, which will be collaborative efforts between the ENVIRON and Princeton team. 13

14 7. REFERENCES 1) Donner, L.J., and Coauthors, 2011: The Dynamical Core, Physical Parameterizations, and Basic Simulation Characteristics of the Atmospheric Component AM3 of the GFDL Global Coupled Model CM3. J. Climate, 24, doi: JCLI ) Emery, C., and Coauthors, 2012: Regional and global modeling estimates of policy relevant background ozone over the United States. Atmos. Environ., 47, , doi: /j.atmosenv ) Emmons, L.K., and Coauthors, 2010: Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4), Geosci. Model Dev., 3, 43-67, doi: /gmd ) ENVIRON, 2012: User s Guide: Comprehensive Air quality Model with extensions. Prepared by ENVIRON International Corporation, Novato, CA. Available at: 5) EPA, 2007: Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5 and Regional Haze. Prepared by the US Environmental Protection Agency, Research Triangle Park, NC. EPA-454/B April. ( 6) Zhang L., and Coauthors, 2011: Improved estimate of the policy-relevant background ozone in the United States using the GEOS-Chem global model with 1/2 2/3 horizontal resolution over North America. Atmospheric Environment, doi: /j.atmosenv