The New Era of National Ambient Air Quality Standards

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Presentation delivered at the Annual Air and Waste Management Association conference in Long beach, California on June 26, 2014. Innovative dispersion modeling techniques are presented including ARM2, EMVAP and the 50th percentile background concentration. Case study involves peaking engines that are used 250 hour per year. These intermittent sources are required to undergo a modeling evaluation in many states. Current modeling techniques grossly overestimate the emissions from these sporadic sources.

INNOVATIVE DISPERSION MODELING PRACTICES TO ACHIEVE A REASONABLE LEVEL OF CON...

Sergio A. Guerra

The advent of the short term National Ambient Air Quality Standards (NAAQS) prompted modelers to reassess the common practices in dispersion modeling analyses. The probabilistic nature of the new short term standards also opens the door to alternative modeling techniques that are based on probability. One of these is the Monte Carlo technique that can be used to account for emission variability in permit modeling. Currently, it is assumed that a given emission unit is in operation at its maximum capacity every hour of the year. This assumption may be appropriate for facilities that operate at full capacity most of the time. However, in most cases, emission units operate at variable loads that produce variable emissions. Thus, assuming constant maximum emissions is overly conservative for facilities such as power plants that are not in operation all the time and which exhibit high concentrations during very short periods of time. Another element of conservatism in NAAQS demonstrations relates to combining predicted concentrations from the AMS/EPA Regulatory Model (AERMOD) with observed (monitored) background concentrations. Normally, some of the highest monitored observations are added to the AERMOD results yielding a very conservative combined concentration. A case study is presented to evaluate the use of alternative probabilistic methods to complement the shortcomings of current dispersion modeling practices. This case study includes the use of the Monte Carlo technique and the use of a reasonable background concentration to combine with the AERMOD predicted concentrations. The use of these methods is in harmony with the probabilistic nature of the NAAQS and can help demonstrate compliance through dispersion modeling analyses, while still being protective of the NAAQS.

Use of Probabilistic Statistical Techniques in AERMOD Modeling Evaluations

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1-Hour NO2 NAAQS Air Quality Modeling

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Advance modeling techniques can be used in AERMOD to refine the inputs that are entered in the model to get more accurate results. This presentation covers: -AERMOD’s Temporal Mismatch Limitation -Building Downwash Limitations in BPIP/PRIME -Advanced Modeling Techniques to Overcome these Limitations Solutions include: Equivalent Building Dimensions (EBD) Emission Variability Processor (EMVAP) Updated ambient ratio method (ARM2) Pairing AERMOD values with the 50th % background concentrations in cumulative analyses.

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Presentation delivered at the EPA 11th Conference on Air Quality Modeling at RTP, NC. Topics covered include background concentrations and the need for a new system to update AERMOD. An evaluation of what is being proposed in the draft guidance related to background concentrations and an alternative approach to determine background concentrations for dispersion modeling evaluations is presented. A review of the lessons learned from Appendix W and a proposed new method to incorporate science into the model.

Background Concentrations and the Need for a New System to Update AERMOD

Sergio A. Guerra

The current study presents a new data analysis technique developed while evaluating continuous emission data collected from a trash compactor. The evaluation involved tailpipe sampling with a portable emission monitoring system (PEMS) from a diesel fueled 525-horsepower trash compactor. The sampling campaign took place by running the compactor with regular no. 2 diesel, B20 and ULSD fuels. The purpose was to determine the possible emission reductions in nitrous oxides (NOx) and carbon dioxide (CO2) from the use of B20 and ULSD in an off-road vehicle. The results from the NOx analysis are discussed. The initial data analysis identified two important issues. The first concern related to a bias in the calculated F values due to the very large number of samples (N). The large N influenced the probability values and indicated a false statistical significance for all factors tested. Additionally, the data observations were found to be highly autocorrelated. Thus, a time interval data reduction technique was used to address these two statistical limitations to the robustness of the statistical analyses. The result in each case was a subset of quasi-independent observations sampled at an interval of 800 seconds. The autocorrelation and false statistical significance issues were promptly resolved by using this technique. Since the issues of false statistical significance and autocorrelation are inherent in continuous data, the positive results obtained from the use of this technique can be far-reaching. This technique allowed for a valid use of the general linear model (GLM) with engine speed as the covariate factor to test day, fuel type and compactor factors. This technique is most relevant given the advancements in data collection capabilities that require data handling techniques to satisfy the statistical assumptions necessary for valid analyses to ensue.

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Pairing aermod concentrations with the 50th percentile monitored value

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The Plume Rise Model Enhancements (PRIME) building downwash algorithms1 (Schulman et al. 2000) in AERMOD2 are being updated to address some of the most critical limitations in the current theory. These enhancements will incorporate the latest advancements related to building downwash effects. The technical aspects of these enhancements are discussed in more detail in a companion paper titled “PRIME2: Development and Evaluation of Improved Building Downwash Algorithms for Solid and Streamlined Structures (MO13)”. The updates to the PRIME code include new equations to account for building wake effects that decay rapidly back to ambient levels above the top of the building; reduced wake effects for streamlined structures; and reduced wake effects for high approach roughness. A consequence analysis comparing the current AERMOD/PRIME model versus the new AERMOD/PRIME2 model was performed. Additionally, a field data evaluation was conducted with the Bowline Point database. The results from these analyses are discussed below.

PRIME2_consequence_analysis_and _model_evaluation

Sergio A. Guerra

The revision of the Guideline on AQ Models (Appendix W) will prompt many changes in the way dispersion modeling is conducted for regulatory purposes. Some of the changes to the Guideline include enhancements and bug fixes to the AERMOD modeling system, new screening techniques to address ozone and secondary PM2.5, delisting CALPUFF as the preferred long-range transport model, and updates on the use of meteorological input data. These changes will have a significant impact on the regulated community. In anticipation of these updates, the Air & Waste Management Association will hold its 6th Specialty Conference: “Guideline on Air Quality Models: The New Path” to provide a technical forum to discuss the Guideline. This talk covered the main highlights from this conference including the presentations from EPA on the status and future direction of the Guideline. Learn how these changes may impact dispersion modeling evaluations for short and long range transport.

Highlights from the 2016 Guideline on Air Quality Models Conference

Sergio A. Guerra

The proposed Alaska LNG GTP project includes the construction of a natural gas treatment plant on the Alaska North Slope. The Gas Treatment Plant (GTP) is proposed to be located on the west coast of Prudhoe Bay and would treat natural gas produced on the North Slope. Initial dispersion modeling of the Alaska LNG Gas Treatment Plant (GTP) found results inconsistent with local and regional measurements when evaluating compliance with the 1-hour NO2 National Ambient Air Quality Standard (NAAQS) due in part to two adjacent nearby sources. These existing sources include the Central Gas Facility (CGF) and Central Compression Plant (CCP) located immediately east of the GTP. The prevailing winds at the site are east-northeast and west-southwest which align with the arrangement of the facilities. The building downwash inputs generated by the Building Profile Input Program for PRIME (BPIPPRM) were evaluated for the CGF and CCP facilities. This analysis confirmed that the building dimension inputs for numerous wind directions were outside of the tested theory used to develop the building downwash algorithms in AERMOD. Previous studies2,8,11,12,13 suggest that AERMOD predictions are biased to overstate downwash effects for certain building input ratios. Wind tunnel determined equivalent building dimensions (EBD) were conducted for the most critical stacks and wind directions to refine AERMOD-derived predicted concentrations. The current paper covers the EBD method used to refine the building inputs for the CGF and CCP facilities. The regulatory process and benefits from this physical modeling method is also discussed.

Use of Wind Tunnel Refinements in the Dispersion Modeling Analysis of the Ala...

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dispersion modeling requirements are more common in air permitting projects and in many cases become the bottleneck in permitting. Unlike any other consulting firm, CPP promotes cutting edge techniques which can alleviate excessive conservatism in permit modeling to a reasonable level that still protects public health. At CPP we start with the standard modeling techniques and apply the following advanced analysis tools, as needed, to optimize your permitting strategy: • Analysis of BPIP output to verify if AERMOD is overpredicting, • Screening tool to assess the benefit of refining the BPIP building dimensions inputs, • Use of Equivalent Building Dimension (EBD) studies to correct building wake effects in AERMOD, • Evaluation of background concentrations to determine a reasonable value to combine with predicted concentrations, • Use of the Monte Carlo approach (i.e., EMVAP) to address sources with variable emissions, • Use of the adjusted friction velocity (u-star) option in AERMET to address AERMOD’s overestimation during low wind stable hours, • Site analysis to determine whether stacks taller than formula GEP stack heights are justified, • Site specific wind tunnel modeling to determine GEP stack heights and Equivalent Building Dimensions, • Site-specific wind erosion inputs, and • Area and volume source enhancements.

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On January 4, 2012, the EPA committed to engage in rulemaking to evaluate updates to the Guideline on Air Quality Models (AppendixWof 40 CFR 51) and, as appropriate, incorporate new analytical techniques or models for secondary PM2.5. As a result, the National Association of Clean Air Agencies (NACAA) developed a screening method involving offset ratios to account for secondary PM2.5 formation. This method can be used to evaluate total (direct and indirect) PM2.5 impacts for permitting purposes. Therefore, the evaluation of this method is important to determine its viability for widespread use.

EVALUATION OF SO2 AND NOX OFFSET RATIOS TO ACCOUNT FOR SECONDARY PM2.5 FORMATION

Sergio A. Guerra

Important theoretical issues that significantly affect the accuracy of predicted concentrations subject to downwash effects have been identified in AERMOD/PRIME. These issues have prompted a number of industry groups to fund new research aiming at overcoming these shortcomings. The Plume Rise Model Enhancements (PRIME) building downwash algorithms1 (Schulman et al. 2000) in AERMOD2 are being updated to address some of the most critical limitations in the current theory. These enhancements will incorporate the latest advancements related to building downwash effects. The technical aspects of these enhancements are discussed in more detail in a recent publication "PRIME2: Development and Evaluation of Improved Building Downwash Algorithms for Solid and Streamlined Structures". The updates to the PRIME code include new equations to account for building wake effects that decay rapidly back to ambient levels above the top of the building; reduced wake effects for streamlined structures; and reduced wake effects for high approach roughness. A comparison with field data was conducted with the Bowline Point, Alaska North Slope, Millstone Nuclear Power Station, and the Duane Arnold Energy Center databases. A new experimental BPIP-PRM version is also discussed.

PRIME2 Model Evaluation

Sergio A. Guerra

The Plume Rise Model Enhancements (PRIME) formulation in AERMOD has been updated based new equations developed from wind tunnel measurements taken downwind of various solid and streamlined structures. These new equations, along with other building downwash improvements have been included as alpha options in the upcoming new version of AERMOD. The PRIME2 options include: • PRIME2UTurb which enables enhanced calculations of turbulence and wind speed • PRIME2Ueff which defines the height used to compute effective parameters Ueff, Sweff, Sveff and Tgeff at plume height and at 30 m • Streamline defines the set of constants for modeling all structures as streamlined. If omitted, rectangular building constants are used. The ORD Options include: • PRIMEUeff which controls the heights for which the wind speed is calculated for the main plume concentrations. • Average between plume height and receptor height recommended in ORD version • Default is current method in AERMOD, stack height wind speed. • PRIMETurb which adjusts the vertical turbulence intensity, wiz0 from 0.6 to 0.7. • PRIMECav modifies the cavity calculations These improvements aim to address important theoretical issues that significantly affect the accuracy of predicted concentrations subject to downwash effects. This research effort was funded in part by the American Petroleum Institute, the Electric Power Research Institute, the Corn Refiners Association and the American Forest & Paper Association. As part of it, the PRIME2 subcommittee under the A&WMA APM committee was formed to: (1) establish a mechanism to review, approve and implement new science into the model for this and future improvements; and (2) provide a technical review forum to improve the PRIME building downwash algorithms. Collaboration and cooperation from the EPA Office of Research and Development (ORD) has been on-going during the research project resulting in new alpha options aimed at solving known issues with the treatment of building downwash effects in AERMOD. The intent is that these experimental options will be tested by the user community to create enough justification to make these beta (approved on a case-by-case basis) and eventually default options in AERMOD. A preliminary evaluation for the following four cases will be presented: • Arconic- Davenport, IA (formerly Alcoa) • Mirant Potomac River Generating Station- Alexandria, VA • Basic American Foods- Blackfoot, ID • Oakley Generating Station- Oakley, CA The evaluation includes comparing 1-hr, 24-hr and annual averages along with Q-Q plots and isopleths. A discussion related to the results obtained will also be presented.

PRIME2 Model Evaluation

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While the current EBD method is the best available option to determine correct building dimensions in the model, a different method was suggested by EPA in the 2011 Memo: Model Clearinghouse Review of EBD for AERMOD.9 Attachment B to the 2011 Memo includes an assessment of the Alcoa Davenport Works EBD Study. In this evaluation EPA compared wind tunnel observations with AERMOD derived concentrations. However, this evaluation has important shortcomings. First, to carry out this comparison between wind tunnel and AERMOD concentrations, it is necessary to collect velocity profiles that include longitudinal and vertical turbulent intensity measurements upwind of the stack. These data were not available for the EPA evaluation of the Alcoa Davenport Works EBD Study. Second, the wind tunnel model operating conditions were converted to full scale conditions by using exact similarity. However, exact similarity is not used to specify model operating conditions since only momentum ratios are matched but not buoyancy ones. Whereas EPA did not provide important details on how this study was performed, this paper outlines how to properly carry out this new method where AERMOD is used to determine equivalent building dimensions. The viability of this new method was also evaluated and discussed.

Evaluating AERMOD and Wind Tunnel Derived Equivalent Building Dimensions

Sergio A. Guerra

Achieving compliance in dispersion modeling can be quite challenging because of the tight National Ambient Air Quality Standards (NAAQS). In addition, AERMOD’s limitations can, in many cases, produce higher than normal concentrations due to the inherent assumptions and simplifications in its formulation. In the case of downwash, the theory used to estimate these effects was developed for a limited set of building types. However, these formulations are commonly used indiscriminately for all types of buildings. This presentation will cover how the basics of wind tunnel modeling can overcome some of these limitations and be used to mitigate downwash induced overpredictions to achieve compliance.

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