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.
INNOVATIVE DISPERSION MODELING PRACTICES TO ACHIEVE A REASONABLE LEVEL OF CON...Sergio A. Guerra
Presentation delivered at the Board meeting for the Upper Midwest section of the Air and Waste Management Association meeting on September 16, 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
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.
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.
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.
PRIME2_consequence_analysis_and _model_evaluationSergio A. Guerra
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.
Pairing aermod concentrations with the 50th percentile monitored valueSergio A. Guerra
Presentation delivered to the Background Concentrations Workgroup for Air Dispersion Modeling organized by the Minnesota Pollution Control Agency. delivered on May 29, 2014. Three topics covered include 1) Screening monitoring data, 2) AERMOD’s time-space mismatch, and
3) Proposed 50th % Bkg Method
AIR DISPERSION MODELING HIGHLIGHTS FROM 2012 ACESergio A. Guerra
Presentation includes some highlights from the dispersion modeling papers presented at the Annual AWMA conference in San Antonio, TX. Topics covered include: EMVAP, distance limitations of AERMOD, and two case studies comparing predicted and monitoring data,
Presented at the A&WMA UMS Board Meeting on August 21, 2012.
Background Concentrations and the Need for a New System to Update AERMODSergio A. Guerra
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.
INNOVATIVE DISPERSION MODELING PRACTICES TO ACHIEVE A REASONABLE LEVEL OF CON...Sergio A. Guerra
Presentation delivered at the Board meeting for the Upper Midwest section of the Air and Waste Management Association meeting on September 16, 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
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.
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.
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.
PRIME2_consequence_analysis_and _model_evaluationSergio A. Guerra
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.
Pairing aermod concentrations with the 50th percentile monitored valueSergio A. Guerra
Presentation delivered to the Background Concentrations Workgroup for Air Dispersion Modeling organized by the Minnesota Pollution Control Agency. delivered on May 29, 2014. Three topics covered include 1) Screening monitoring data, 2) AERMOD’s time-space mismatch, and
3) Proposed 50th % Bkg Method
AIR DISPERSION MODELING HIGHLIGHTS FROM 2012 ACESergio A. Guerra
Presentation includes some highlights from the dispersion modeling papers presented at the Annual AWMA conference in San Antonio, TX. Topics covered include: EMVAP, distance limitations of AERMOD, and two case studies comparing predicted and monitoring data,
Presented at the A&WMA UMS Board Meeting on August 21, 2012.
Background Concentrations and the Need for a New System to Update AERMODSergio A. Guerra
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.
Evaluation of the Theoretical Problems with Building Downwash Using A New Met...Sergio A. Guerra
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. 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.
Using Physical Modeling to Refine Downwash Inputs to AERMODSergio 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.
Highlights from the 2016 Guideline on Air Quality Models ConferenceSergio 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.
Using Physical Modeling to Evaluate Re-entrainment of Stack EmissionsSergio A. Guerra
Fume re-entry is an important concern for many types of facilities such as hospitals and laboratories that emit pathogens and toxic chemicals that may impact public health by being re-entrained into the building though nearby air intakes. Numerical methods can be used to evaluate dispersion of pollutants from stacks at sensitive receptors. However, numerical methods have limitations and simplifications that can significantly affect its predictions. An alternate way of analyzing stack re-entrainment is with physical modeling in a wind tunnel. In such a study, a scale model that accounts for buildings, topography, and vegetation is used with planned and alternate stack designs to determine the toxic emission impacts on air intakes and other sensitive locations. In a wind tunnel study different stack designs and possible mitigation options can be evaluated. This method is superior to numerical methods (e.g., dispersion models) because it accounts for the immediate structures, topography, and vegetation that is often ignored or oversimplified in numerical methods.
This presentation will show a hypothetical case study evaluating a site with toxic air emissions using AERMOD and physical modeling.
Presentation includes information related to gently sloping terrain, AERMINUTE, and EPA formula height.
Presented at the 27th Annual Conference on the Environment on November 13, 2012.
Advanced Modeling Techniques for Permit Modeling - Turning challenges into o...Sergio A. Guerra
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.
Use of Probabilistic Statistical Techniques in AERMOD Modeling EvaluationsSergio 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.
EVALUATION OF SO2 AND NOX OFFSET RATIOS TO ACCOUNT FOR SECONDARY PM2.5 FORMATIONSergio A. Guerra
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.
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.
Complying with EPA's Guidance for SO2 DesignationsSergio A. Guerra
EPA is under a Court order to complete the remaining SO2 designations for the rest of the country in three additional rounds. On March 20, 2015 the EPA released an updated guidance for 1-hr SO2 area designations. The two options included are compliance through dispersion modeling or ambient monitoring. Of these two options, dispersion modeling is the fastest and most cost effective one to characterize SO2 air quality. However, this compliance demonstration can be challenging given that AERMOD tends to produce overly conservative concentration estimates. Source characterization techniques and probabilistic techniques may be used to achieve compliance with the 1-hour NAAQS. Three advanced methods discussed: 1) Equivalent Building Dimensions (EBD); 2) Emission Variability Processor (EMVAP); 3) 50th Percentile Background Concentrations.
Using Physical Modeling to Refine Downwash Inputs to AERMOD at a Food Process...Sergio A. Guerra
Demonstrating compliance with air quality standards using dispersion modeling is increasingly difficulty because of significant tightening National Ambient Air Quality Standards (NAAQS) that has occurred in the last decade. Compliance with these standards is usually demonstrated using AERMOD, EPA’s standard model for assessing air quality impacts from industrial sources. However, AERMOD often produces higher predictions of air quality impacts due to the inherent conservative (high) assumptions and simplifications in its formulation. A specific situation involves the calculations used to assess the impacts of air flow downwash around buildings. Although the theory used to estimate these effects was developed for a limited set of building types, these formulae are applied indiscriminately to all types of buildings in a conservative fashion, often leading to significant overpredictions of downwash effects.
This presentation covers the basics of wind tunnel modeling and how it can be used to correct downwash induced overpredictions to achieve compliance. The presentation will also describe the setup and execution of wind tunnel modeling at a food processing facility to develop improved downwash parameters and increase the accuracy of dispersion modeling results.
New Guideline on Air Quality Models and the Electric Utility IndustrySergio 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. This presentation will cover the main highlights from this guidance and how the electric utility industry will be impacted. In addition, the latest information provided by EPA during the 2016 Regional, State, and Local Modelers' Workshop will also be presented.
Evaluating AERMOD and Wind Tunnel Derived Equivalent Building DimensionsSergio A. Guerra
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.
Use of Wind Tunnel Refinements in the Dispersion Modeling Analysis of the Ala...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.
Probabilistic & Source Characterization Techniques in AERMOD ComplianceSergio A. Guerra
The short term NAAQS are more stringent and traditional techniques are not suitable anymore. The probabilistic nature of these standards also opens the door to modeling techniques based on probability. Source characterization studies can also be used to refine AERMOD’s inputs to be more accurate and achieve reductions of more than half. This presentation will cover these compliance methods.
Currently, it is assumed that a given emission unit is in operation at its maximum capacity every hour of the year. However, assuming constant maximum emissions is overly conservative for facilities such as power plants that are not in operation all the time at full load. A better approach is the use of the Monte Carlo technique to account for emission variability. Another conservative assumption in NAAQS modeling relates to combining predicted concentrations from AERMOD with maximum or design concentrations from the monitor. A more reasonable approach is to combine the 50th percentile background concentration with AERMOD values.
The inputs to AERMOD can be obtained by more accurate source characterization studies. Such is the case of building dimensions commonly calculated with BPIP. These dimensions tend to overstate the wake effects and produce significantly higher concentrations especially for lattice structures, elongated buildings, and streamlined structures. An Equivalent Building Dimensions (EBD) study can be used to inform AERMOD with more accurate downwash characteristics.
Pairing aermod concentrations with the 50th percentile monitored valueSergio A. Guerra
Presentation delivered to the Background Concentrations Workgroup for Air Dispersion Modeling organized by the Minnesota Pollution Control Agency. delivered on March 25, 2014. Three topics covered include 1) Screening monitoring data, 2) AERMOD’s time-space mismatch, and
3) Proposed 50th % Bkg Method
Evaluation of the Theoretical Problems with Building Downwash Using A New Met...Sergio A. Guerra
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. 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.
Using Physical Modeling to Refine Downwash Inputs to AERMODSergio 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.
Highlights from the 2016 Guideline on Air Quality Models ConferenceSergio 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.
Using Physical Modeling to Evaluate Re-entrainment of Stack EmissionsSergio A. Guerra
Fume re-entry is an important concern for many types of facilities such as hospitals and laboratories that emit pathogens and toxic chemicals that may impact public health by being re-entrained into the building though nearby air intakes. Numerical methods can be used to evaluate dispersion of pollutants from stacks at sensitive receptors. However, numerical methods have limitations and simplifications that can significantly affect its predictions. An alternate way of analyzing stack re-entrainment is with physical modeling in a wind tunnel. In such a study, a scale model that accounts for buildings, topography, and vegetation is used with planned and alternate stack designs to determine the toxic emission impacts on air intakes and other sensitive locations. In a wind tunnel study different stack designs and possible mitigation options can be evaluated. This method is superior to numerical methods (e.g., dispersion models) because it accounts for the immediate structures, topography, and vegetation that is often ignored or oversimplified in numerical methods.
This presentation will show a hypothetical case study evaluating a site with toxic air emissions using AERMOD and physical modeling.
Presentation includes information related to gently sloping terrain, AERMINUTE, and EPA formula height.
Presented at the 27th Annual Conference on the Environment on November 13, 2012.
Advanced Modeling Techniques for Permit Modeling - Turning challenges into o...Sergio A. Guerra
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.
Use of Probabilistic Statistical Techniques in AERMOD Modeling EvaluationsSergio 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.
EVALUATION OF SO2 AND NOX OFFSET RATIOS TO ACCOUNT FOR SECONDARY PM2.5 FORMATIONSergio A. Guerra
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.
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.
Complying with EPA's Guidance for SO2 DesignationsSergio A. Guerra
EPA is under a Court order to complete the remaining SO2 designations for the rest of the country in three additional rounds. On March 20, 2015 the EPA released an updated guidance for 1-hr SO2 area designations. The two options included are compliance through dispersion modeling or ambient monitoring. Of these two options, dispersion modeling is the fastest and most cost effective one to characterize SO2 air quality. However, this compliance demonstration can be challenging given that AERMOD tends to produce overly conservative concentration estimates. Source characterization techniques and probabilistic techniques may be used to achieve compliance with the 1-hour NAAQS. Three advanced methods discussed: 1) Equivalent Building Dimensions (EBD); 2) Emission Variability Processor (EMVAP); 3) 50th Percentile Background Concentrations.
Using Physical Modeling to Refine Downwash Inputs to AERMOD at a Food Process...Sergio A. Guerra
Demonstrating compliance with air quality standards using dispersion modeling is increasingly difficulty because of significant tightening National Ambient Air Quality Standards (NAAQS) that has occurred in the last decade. Compliance with these standards is usually demonstrated using AERMOD, EPA’s standard model for assessing air quality impacts from industrial sources. However, AERMOD often produces higher predictions of air quality impacts due to the inherent conservative (high) assumptions and simplifications in its formulation. A specific situation involves the calculations used to assess the impacts of air flow downwash around buildings. Although the theory used to estimate these effects was developed for a limited set of building types, these formulae are applied indiscriminately to all types of buildings in a conservative fashion, often leading to significant overpredictions of downwash effects.
This presentation covers the basics of wind tunnel modeling and how it can be used to correct downwash induced overpredictions to achieve compliance. The presentation will also describe the setup and execution of wind tunnel modeling at a food processing facility to develop improved downwash parameters and increase the accuracy of dispersion modeling results.
New Guideline on Air Quality Models and the Electric Utility IndustrySergio 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. This presentation will cover the main highlights from this guidance and how the electric utility industry will be impacted. In addition, the latest information provided by EPA during the 2016 Regional, State, and Local Modelers' Workshop will also be presented.
Evaluating AERMOD and Wind Tunnel Derived Equivalent Building DimensionsSergio A. Guerra
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.
Use of Wind Tunnel Refinements in the Dispersion Modeling Analysis of the Ala...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.
Probabilistic & Source Characterization Techniques in AERMOD ComplianceSergio A. Guerra
The short term NAAQS are more stringent and traditional techniques are not suitable anymore. The probabilistic nature of these standards also opens the door to modeling techniques based on probability. Source characterization studies can also be used to refine AERMOD’s inputs to be more accurate and achieve reductions of more than half. This presentation will cover these compliance methods.
Currently, it is assumed that a given emission unit is in operation at its maximum capacity every hour of the year. However, assuming constant maximum emissions is overly conservative for facilities such as power plants that are not in operation all the time at full load. A better approach is the use of the Monte Carlo technique to account for emission variability. Another conservative assumption in NAAQS modeling relates to combining predicted concentrations from AERMOD with maximum or design concentrations from the monitor. A more reasonable approach is to combine the 50th percentile background concentration with AERMOD values.
The inputs to AERMOD can be obtained by more accurate source characterization studies. Such is the case of building dimensions commonly calculated with BPIP. These dimensions tend to overstate the wake effects and produce significantly higher concentrations especially for lattice structures, elongated buildings, and streamlined structures. An Equivalent Building Dimensions (EBD) study can be used to inform AERMOD with more accurate downwash characteristics.
Pairing aermod concentrations with the 50th percentile monitored valueSergio A. Guerra
Presentation delivered to the Background Concentrations Workgroup for Air Dispersion Modeling organized by the Minnesota Pollution Control Agency. delivered on March 25, 2014. Three topics covered include 1) Screening monitoring data, 2) AERMOD’s time-space mismatch, and
3) Proposed 50th % Bkg Method
Marc stettler modelling of instantaneous vehicle emissions - dmug17IES / IAQM
DMUG remains the key annual event for experts in this field. Unmissable speakers will be examining topical issues in emissions, exposure and dispersion modelling.
Case Study: Data Analytics and PEMS Testing for a Final Tier 4 ExcavatorSGS
The US NTE method and EU WBW approaches both experience obstacles when it comes to calculating final emission rates for NRMM using Portable Emission Measurement System (PEMS).
SGS presented results of an experiment conducted in Michigan, USA. To better understand and characterize the emission rates during individual modes of operation, SGS performed an in-field experiment to measure the emission rates of a Final Tier 4 Excavator.
The following modes of operation were measured and compared: cold start, auto-warm up, idle, crawl, trenching, and excavation. CO, CO2, NO, NO2, THC and PM were collected and analyzed for each operational mode.
Emissions Inventory for the Arctic Air Quality Modeling StudyJennifer Sharp
Eastern Research Group's Paula Fields Simms recently presented on this study at EPA's 2015 Emission Inventory Conference. The study, which was sponsored by the Bureau of Ocean Energy Management, resulted in a comprehensive inventory of sources of criteria and hazardous air pollutants, greenhouse gases, hydrogen sulfide, and ammonia. The ERG team will use Paula's study to model on-shore air quality impacts.
JPRO Professional Heavy Duty Truck Diagnostic Toolbox User ManualTim Miller
This is the user manual of JPRO Professional Heavy Duty Truck Diagnostic Toolbox.
>> READ MORE: https://www.obdadvisor.com/autel-scanners/
Here is a detailed review of the toolbox based on my own experience, including:
- Compatibility
- Display
- Software
- Features and Functions
- Pros and Cons
Check it out to get the REVIEW and some NOTES about using this tool.
Operation of Internal Combustion Engines on Digas for Electricity ProductionLPE Learning Center
Proceedings available at: http://www.extension.org/67668
The purpose of this research is to review engine performance and technology issues relating to generating electricity from digester gas in reciprocating internal combustion engines. Research performed at the Colorado State University (CSU) Engines & Energy Conversion Laboratory (EECL) and published material from other organizations is utilized.
Digester gas (digas) can be used effectively in internal combustion engines for electricity production to offset operating costs and/or sell to the electric utility. Stationary industrial engines are generally employed for this purpose. Four application areas where systems have been successfully demonstrated are sewage processing plants, animal waste facilities, landfills, and agricultural waste processing systems. Digas is generated through anaerobic digestion, or biomethanization, for all these cases. There are many common engine technical issues within these areas, although the digas generation systems employed in each case are different. In this presentation issues pertinent to running engines on digas are explored. The focus is on animal waste facilities, but the presentation draws upon the other application areas for technical insight related to engine technology. Specific stationary engine types are discussed. High engine efficiency and power density are important to the economic viability of anaerobic digestion systems. Engine operational and design changes to maintain high efficiency and power density for digas fueling are analyzed. Management of engine maintenance problems is also key to economic viability. Corrosive gases contained in digas, such as hydrogen sulfide (H2S), are evaluated.
Routes to Clean Air 2016 - Jane Thomas, Emissions AnalyticsIES / IAQM
Talk title: Measuring and monitoring emissions of nitrogen oxides from passenger cars. a 1200 vehicle case study
Routes to Clean Air is a two-day conference from the IAQM where academics, professionals and policy makers share their experiences of improving traffic emissions.
This event highlights the importance of public communication and behavioural change surrounding road transport and air quality issues.
PEMS is a powerful emissions measurement tool that can be used for certification tests and development research. SGS presented three case studies using PEMS to: 1) Benchmark a Final Tier 4 Excavator by classifying modal emissions, 2) Develop in-use routes to compare route selection and altitude effects on light-duty vehicles, and 3) Validate a predictive analytics platform for on-road fuel consumption and emissions.
A renewed interest and scrutiny of downwash shortcomings has fueled a parallel, yet complementary effort, led by industry and EPA. Industrial groups funded the update to the Plume Rise Model Enhancements (PRIME) formulation in AERMOD based on new equations derived from wind tunnel measurements. Concurrently, EPA’s Office of Research and Development (ORD) conducted research that led to new enhancements to the downwash formulation.2 The new PRIME equations (PRIME2), along with EPA-ORD’s building downwash improvements, have been included as alpha options in an upcoming new EPA version of AERMOD.
As part of the renewed interest in building downwash, 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 EPA’s ORD and OAQPS have been on-going during this research project. These efforts included a downwash summit at EPA’s RTP facilities on February 16, 2018 where representatives of the PRIME2 committee and research funders met with EPA’s ORD and OAQPS staff to discuss the newly developed building downwash improvements. During that meeting it was decided that these enhancements would be included as new alpha options in AERMOD. The intent is that these experimental options will be tested by the user community to create enough justification to transition them to a beta status (approved on a case-by-case basis) and eventually to default options in AERMOD. An evaluation of some of these new downwash options is presented.
Solution to AERMOD/PRIME PM10 Overpredictions for Extremely Short, Long and W...Sergio A. Guerra
The current formulation in AERMOD/PRIME is prone to downwash overestimations as documented by Petersen et al. Some of these overpredictions can be minimized by conducting a wind tunnel study to refine the building inputs used in AERMOD/PRIME for critical stacks and wind directions. Most of the wind tunnel studies conducted to date involve taller building structures of at least 20 meters in height. However, a recent wind tunnel study was conducted for the Basic American Foods, Blackfoot, Idaho facility, which has extremely short buildings (7 to 12 meters in height) with very long and wide footprints and many exhaust stacks which are less than 25 meters above ground
The wind tunnel study confirmed that AERMOD was vastly overstating downwash effects for certain critical wind directions. In some cases, AERMOD-predicted concentrations were almost four times higher without the wind tunnel refinements. This study indicates that the previously identified tendency of AERMOD to overpredict downwash using the traditional BPIP-derived building inputs also applies to sites with shorter buildings. Because shorter buildings with shorter stacks are common in many sources subject to the minor New Source Review program (such as most food and beverage and manufacturing facilities), AERMOD’s overpredictions may be causing significantly higher predicted concentrations for many industrial sources.
This paper describes the wind tunnel study performed for this site, presents the benefits obtained from these building input refinements, and reviews comments received on the project from regulatory agencies.
PRIME2: Consequence Analysis and Model EvaluationSergio A. Guerra
This presentation will cover a preliminary consequence analysis and field evaluation related to the updates to the Plume Rise Model Enhancements updates (PRIME2). Additional research needs uncovered through this research project will also be discussed.
Evaluation of AERMOD and Wind Tunnel Derived Equivalent Building DimensionsSergio A. Guerra
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. 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.
Overview and update of the PRIME2 Advisory Committee from the Atmospheric Modeling and Meteorology (APM) Technical Committee of the Air and Waste Management Association (A&WMA). Presentation delivered at the 2016 EPA RSL Modelers’ Workshop in New Orleans, LA. Update relates to downwash improvements being done to the current Plume Rise Enhancements Model (PRIME) in AERMOD.
Diesel backup generators are commonly installed in hospitals, data centers, universities, hotels, and other businesses for use in the event of power disruptions. These engines have quick response times that provide an unmatched reliable source of emergency backup power. Facilities that have these backup engines can also benefit from enrolling in demand response (DR) programs that offer economic incentives to participants who volunteer the use of their backup generators to supply electricity to the grid during certain periods of high electricity demand. In recent years, there has been an increase in the number of backup engines that have enrolled in DR programs in exchange for economic incentives. DR programs provide grid reliability, especially during periods of high electricity demand. Therefore, this is a win-win situation for backup engine owners and power utility companies offering these incentives. Generally, a backup generator with a capacity of 500 kilowatt (kW) or more is necessary to participate in DR programs. Participants in these DR programs agree with the local power company to use their backup engines when directed; usually during periods of peak electricity demand or power disruption. However, recent air quality regulations that apply to backup generators can be challenging to meet when participating in a DR program. That is the case because the applicable requirements for backup engine depend on whether the use is strictly for emergency purposes or for DR (considered non-emergency). Purely emergency use engines are subject to work practice standards while non-emergency engines are subject to emission limits that may require emission controls. Additionally, non-emergency engines may be subject to dispersion modeling requirements to show compliance with the national ambient air quality standards (NAAQS). At the moment the dispersion model used in permitting evaluations is extremely conservative and can show compliance issues. In conclusion, DR programs can be a profitable way to get additional cash for owners and operators of backup engines. However, the permitting implications should be considered thoroughly before enrolling in such a program to avoid any unintended adverse consequences.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
NOVEL DATA ANALYSIS TECHNIQUE USED TO EVALUATE NOX AND CO2 CONTINUOUS EMISSIONS DATA
1. NOVEL DATA ANALYSIS TECHNIQUE
USED TO EVALUATE NOX AND
CO2 CONTINUOUS EMISSIONS DATA
AWMA 106th Annual Conference, June 27, 2013
Sergio A. Guerra - Wenck Associates, Inc.
Dennis D. Lane, Norman A. Slade, Ray E. Carter, Edward Peltier, Glen Marotz University of Kansas
2. BACKGROUND
• Society depends heavily on diesel engines
• Diesel engines are more durable and fuel efficient than
gasoline ones
• At full load diesel engine use ~70% of the fuel a
comparable gasoline engine consumes (Lloyd et al., 2001)
• Off-road diesel vehicles not well studied
4. OBJECTIVES
1.Collect real-world NOx and CO2 emission profiles from an
off-road diesel vehicle
2.Evaluate NOx and CO2 emission profiles for a diesel offroad vehicle running on diesel, B20 and ULSD fuels to
determine potential emission reductions
3.Evaluate the effect that temporal factors exert on NOx and
CO2 emission profiles
5. Methodology - Test Vehicle
• 2002 Terex CMI Trashmaster 3-90E.
• Cummins Model QSK-19, 525-hp diesel engine.
• Operated from ~ 7 AM to 5:30 PM M-F
• Average fuel use of over 200 gallons per day.
6. PEMS
Portable Emission Monitoring Systems
1.Increasingly more common
2.Affordable
3.Small size and ease of installation
4.Increasingly more accurate
7. Sampling System
• Simple, Portable, On-vehicle,
Testing (SPOT) system.
• Capable of measuring at 1Hz:
• NOx and O2 emissions
• Exhaust mass flow
• Relative humidity
• Ambient temperature
• Engine speed
• Calculated CO2
• Composed of:
• main console
• alternator sensor
• battery connections
• exhaust probe
9. Analysis of PEMS Data
•Autocorrelation
• Frequent successive observations tend to be positively
correlated
• Issue in PEMS generated data
•Binning Approach Frey et al. (2002) and EPA (2002 C,D)
• Driving modes are defined to segregate data
• Produces discontinuous time series to reduce
autocorrelation
• Each “bin” is analyzed separately
10. Analysis of PEMS Data
•Averaging Approach EPA 2002D, Rubino et al. (2007), Weiss
et al. (2011 AB),
• Can be used to “smooth” data
• It will miss peaks and valleys that may be driving emissions
• Good way to compare test cycles to field observations
17. Statistical Analysis
•General Linear Model (GLM) with Engine Speed as a covariate
term. Evaluated the following questions:
1.Are there statistically significant differences in NOx and CO2
concentrations from a diesel compactor running on no. 2 diesel,
ULSD and B20 fuel types?
2.Are there statistically significant differences in NOx and CO2
concentrations due to temporal factors?
18. RESULTS- Tested Fuel Type factor on NOx Concentrations
Factor
DF
F
P-value
Engine
Speed
1
655115.01
0.000
Fuel Type
2
610.58
0.000
2
781.41
0.000
Fuel type*
Engine
Speed
N
276485
20. RESULTS- Time to Independence Method
•Swihart, R. K., and N. A. Slade. (1985). “Testing for independence of
observations in animal movements.” Ecology 66: 1176-1184.
• Developed a procedure for determining the time interval at which
autocorrelation becomes negligible by using location data of a radiotagged adult female cotton rat
• Study showed that if a fixed interval separates successive observations
in an autocorrelated data set, the dependency can be removed by
using observations separated by several intervals
•Method was adapted to emission data and different intervals were
evaluated
•Interval of 800 seconds per observation was selected to produce quasiindependent observations
21. RESULTS- GLM for Reduced Data Set
Factor
N
Fuel Type
Fuel type * Engine
Speed
346
F
P-value
1
Engine Speed
DF
824.72
0.000
2
0.52
0.595
2
0.44
0.645
23. RESULTS- Fuel Analysis
Pollutant
NOx
CO2
Factor
N
Engine Speed
Fuel Type
346
Fuel Type* Engine Speed
Engine Speed
Fuel Type
346
Fuel Type* Engine Speed
DF
1
2
2
1
2
2
PDifference
value Significant?
824.72 0.000
YES
0.52 0.595
NO
0.44 0.645
NO
1454.71 0.000
YES
0.95 0.389
NO
0.34 0.714
NO
F
24. RESULTS- Temporal Analysis
Pollutant
NOx
CO2
Factor
Engine Speed
Day
Day* Engine Speed
Engine Speed
Day
Day* Engine Speed
N
346
346
DF
1
7
7
1
2
2
PDifference
value Significant?
921.77 0.000
YES
0.28 0.960
NO
0.51 0.823
NO
1555.83 0.000
YES
0.38 0.914
NO
0.25 0.972
NO
F
25. CONCLUSIONS
1.Raise awareness about autocorrelation and spurious
statistical significance in continuous emission data
2.Development of a data handling technique to deal with
autocorrelation in continuous data
3.Finding that NOx and CO2 emissions are unaffected from
the use of ULSD and B20 fuel