The document summarizes a study conducted at the University of California, Irvine to safely reduce energy usage in laboratory building exhaust systems through techniques like increased stack heights, variable speed fans, and lowered minimum exhaust flow rates. Wind tunnel testing of exhaust stack designs showed energy savings could be achieved without compromising safety. Retrofitting three campus buildings with these methods resulted in estimated annual energy savings of $61,000 or more and payback periods of 1.6 to 5.3 years.
To Measure Not Model: Case Study -- Purdue University Center for High Perform...AEI / Affiliated Engineers
AEI / Affiliated Engineers, Inc. presents the Purdue University Center for High Performance Design at the Ray W. Herrick Labs, a 68,000 square foot research building focused on systems and environments that improve building performance. Laboratories and research areas include:
• The Perception-Based Engineering Laboratory enables cross-disciplinary research that measures human behavior against an array of stimuli such as lighting, acoustic environment, air quality, temperature, humidity, airflow, and vibration.
• The Electro-Mechanical Vibrations Area allows for both large-scale testing (e.g., aerospace components) and fine-scale testing (e.g., microprocessor scale) with exceptional isolation of vibration and sound.
• Geoexchange research includes ground/earth analysis and simulation.
• Thermal sciences research includes the development of new HVAC technologies, including the use of psychrometric chambers, indoor air quality chambers, wind tunnels, solar thermal arrays, benchtop experiments, and simulated environmental testing.
• The unique Living Laboratory office wing serves as both working office space and as a test site for building systems and concepts.
• The Powertrain/Engine Test Cell Wing is dedicated to testing alternative fuels and emissions to advance engine fuel economy, horsepower, and torque.
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 An evaluation of what is being proposed in the draft guidance related to background concentrations and an alternative approach to determine background concentrations for dispersion modeling evaluations is presented.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.
To Measure Not Model: Case Study -- Purdue University Center for High Perform...AEI / Affiliated Engineers
AEI / Affiliated Engineers, Inc. presents the Purdue University Center for High Performance Design at the Ray W. Herrick Labs, a 68,000 square foot research building focused on systems and environments that improve building performance. Laboratories and research areas include:
• The Perception-Based Engineering Laboratory enables cross-disciplinary research that measures human behavior against an array of stimuli such as lighting, acoustic environment, air quality, temperature, humidity, airflow, and vibration.
• The Electro-Mechanical Vibrations Area allows for both large-scale testing (e.g., aerospace components) and fine-scale testing (e.g., microprocessor scale) with exceptional isolation of vibration and sound.
• Geoexchange research includes ground/earth analysis and simulation.
• Thermal sciences research includes the development of new HVAC technologies, including the use of psychrometric chambers, indoor air quality chambers, wind tunnels, solar thermal arrays, benchtop experiments, and simulated environmental testing.
• The unique Living Laboratory office wing serves as both working office space and as a test site for building systems and concepts.
• The Powertrain/Engine Test Cell Wing is dedicated to testing alternative fuels and emissions to advance engine fuel economy, horsepower, and torque.
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.
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.
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.
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.
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.
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.
NOVEL DATA ANALYSIS TECHNIQUE USED TO EVALUATE NOX AND CO2 CONTINUOUS EMISSIO...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.
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.
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.
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.
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.
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
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.
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.
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.
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.
EFFECTS OF MET DATA PROCESSING IN AERMOD CONCENTRATIONSSergio A. Guerra
The current study evaluates the effect that different parameters used to process meteorological data have on AERMOD concentrations. Specifically, this study evaluates the effect from the use of AERMET processed with; 1-minute wind data collected by the Automated Surface Observing System (ASOS) and pre-processed using AERMINUTE, refined National Climatic Data Center (NCDC) station location and anemometer height, surface moisture, and urban/rural options. In this evaluation, one year of meteorological data was processed with nine different sets of input parameters and then used in AERMOD to run a short, medium and tall stack scenario for 1-hour, 24-hour and annual averaging periods. Downwash and terrain effects were not considered in this study. The results indicate that the three stack scenarios are sensitive to the location used for the meteorological station. Anemometer height changes had a small effect on concentrations for all scenarios except for the tall stack scenario which produced a modest increase in concentrations for the annual averaging period. Surface moisture was not found to have a strong effect on the scenarios evaluated. The use of AERMINUTE data resulted in significantly higher concentrations for the 1-hour (85%), 24-hour (81%), and annual (88%) averaging periods. The ice free group station option in AERMINUTE was also evaluated. When using AERMINUTE without specifying that the station is part of the ice free wind group stations, the concentrations obtained for tall stack scenario were lower for the 1-hour (64%), 24-hour (68%), and annual (78%) averaging periods. Finally, when it comes to the urban/rural evaluation, the greatest effect is observed in the medium stack scenario where concentrations double for the 1-hour scenario when using the rural option. However, in the tall stack scenario, significantly lower concentrations were obtained by using the urban parameter for the three averaging periods evaluated.
Presented at the 10th Conference of Air Quality Modeling
EPA‐Research Triangle Park, NC Campus on March 15, 2012; at the AWMA UMS Dispersion Modeling Workshop on May 15, 2012 and at the Annual AWMA Conference on June 20, 2012.
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.
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.
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.
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.
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.
NOVEL DATA ANALYSIS TECHNIQUE USED TO EVALUATE NOX AND CO2 CONTINUOUS EMISSIO...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.
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.
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.
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.
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.
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
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.
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.
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.
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.
EFFECTS OF MET DATA PROCESSING IN AERMOD CONCENTRATIONSSergio A. Guerra
The current study evaluates the effect that different parameters used to process meteorological data have on AERMOD concentrations. Specifically, this study evaluates the effect from the use of AERMET processed with; 1-minute wind data collected by the Automated Surface Observing System (ASOS) and pre-processed using AERMINUTE, refined National Climatic Data Center (NCDC) station location and anemometer height, surface moisture, and urban/rural options. In this evaluation, one year of meteorological data was processed with nine different sets of input parameters and then used in AERMOD to run a short, medium and tall stack scenario for 1-hour, 24-hour and annual averaging periods. Downwash and terrain effects were not considered in this study. The results indicate that the three stack scenarios are sensitive to the location used for the meteorological station. Anemometer height changes had a small effect on concentrations for all scenarios except for the tall stack scenario which produced a modest increase in concentrations for the annual averaging period. Surface moisture was not found to have a strong effect on the scenarios evaluated. The use of AERMINUTE data resulted in significantly higher concentrations for the 1-hour (85%), 24-hour (81%), and annual (88%) averaging periods. The ice free group station option in AERMINUTE was also evaluated. When using AERMINUTE without specifying that the station is part of the ice free wind group stations, the concentrations obtained for tall stack scenario were lower for the 1-hour (64%), 24-hour (68%), and annual (78%) averaging periods. Finally, when it comes to the urban/rural evaluation, the greatest effect is observed in the medium stack scenario where concentrations double for the 1-hour scenario when using the rural option. However, in the tall stack scenario, significantly lower concentrations were obtained by using the urban parameter for the three averaging periods evaluated.
Presented at the 10th Conference of Air Quality Modeling
EPA‐Research Triangle Park, NC Campus on March 15, 2012; at the AWMA UMS Dispersion Modeling Workshop on May 15, 2012 and at the Annual AWMA Conference on June 20, 2012.
Energy, Environment, Experiential LearningCybera Inc.
John Greggs
University of Calgary
Presented at the Cybera/CANARIE National Summit 2009, as part of the session "Green IT: Does it Work?" In this session, leaders from academia, industry and government debated the value proposition of green IT and its potential to contribute to research, business and policy objectives.
You will hear about an LLNL developed high-efficiency filter made from ceramic materials in a metal housing. The filters are scalable and can be engineered for myriad commercial applications.
Exhaust Stack Discharge Velocity Reduction Study for Labs21 2009
1. Safely Achievable Reductions in Exhaust Fan Energy in Laboratory Buildings Chet Wisner, President, Ambient Air Technologies Jay Hayashi, P2S Engineering Marc Gomez, Director, UCI EH&S Fred Bockmiller, Principal Engineer, UCI Facilities Chris Abbamonto, Energy Manager, UCI Facilities
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3. Campus Energy $avings Challenge Recipe for Success Safety Management Visionary & Supportive Upper Management Engineers Facility Managers Patience Team Synergy Supportive Users / Researchers
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5. Can We Build “Smart Labs” that Greatly Reduce Energy Use?
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7. Smart Laboratory Concept Balancing Laboratory Safety and Climate Safety Create lab buildings that out perform ASHRAE 90.1 / CA Title 24 by 40-50%. Combine energy initiatives such as centralized demand controlled ventilation (CDCV), low flow (high performance) fume hoods, reduced building exhaust stack airspeeds, and use of energy-efficient lighting. Building Exhaust System Labs w/CDCV real time lab air monitoring 4 ach occupied 2 ach unoccupied Energy efficient lighting Labs with low flow fume hoods (as appropriate )
8. Centralized Demand Controlled Ventilation (CDCV) Utilizing real time lab air monitoring, reduce air changes in labs from approximately 6 ACH to 4 ACH while the lab is occupied and 2 ACH when lab is unoccupied.
9. Low Flow (High Performance) Fume Hoods Utilize fume hoods that are designed to operate safely at lower face velocities, i.e., 70 FPM rather than 100 FPM. Exhaust plenum Deeper work surface Unique airfoil design Advanced baffle design
10. Laboratory Lighting Controls Reduce Power Density by 50% Lab Area LPD from 1.1 to 0.55 Lab Prep LPD from 0.9 to 0.36 Prep Room LPD from 2.0 to 1.0 Corridor LPD from 0.6 to 0.3 - Daylight sensors for fixtures near windows - Occupancy sensing by lab bay
11. Lab Building Exhaust Fan Energy Reduction Building Exhaust System Slightly higher stacks Variable speed fans (wind responsive if necessary) Air handler with fresh air intake
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13. Can We Reduce Lab Building Exhaust Discharge Rates & Achieve Real Energy Savings Without Compromising Safety? This Initiative
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15. Lab Exhaust Diagram Animated Wind Exhaust Fan Bypass Damper Plenum Fume Hood Supply Fan Duct Balcony Re-Entrainment of Contaminated Air
30. Typical Timeline of Exit Velocity Requirements Typical Design 1% Design Required by Dispersion Required by High Air Change Rate Required by Low Air Change Rate
MG D EH&S UCI Thanks for letting us share our…
UC Irvine is a growing…
We are constantly challenging ourselves to save energy. Our recipe for taking on these ambitious projects is to have a multi-disciplinary team of professionals focused on a common goal.
This is our agenda for today. Lets take a few minutes to overview our Smart Lab concept
So,
The great news is that energy efficient labs are evolving in the right direction.
Our goal at UC Irvine is to outperform ASHRAE 90.1 or CA Title 24 by 40 to 50%. We have a poster session on our Smart Lab concept and hope you have stopped by or stop by today so we can brainstorm together on this concept.
We are attempting to do this utilizing CDCV with real time lab air monitoring…
We think low flow fume hoods are also a part of the solution
We are reducing our lab lighting power density by 50%
Which brings us to this study…
We want to take a few minutes to share our Smart Lab concept
Wendell This study asks the question… The overarching principal in this study is to maintain a safe environment for occupants of the laboratory building, for occupants of neighboring buildings, roof workers and others in the nearby campus environment. Safety is the primary purpose of a laboratory exhaust system. And that purpose must not be compromised by actions taken to improve energy efficiency. With that said, our goal is to find the sweet spot where we balance safety and energy savings
Wendell The reason we performed this study is we thought…
Wendell Discuss components of system… Note the plumes and effects on dispersion of short/tall stacks and low/high exit velocities. So, we would likely select a taller stack for energy reduction which allows us to reduce the fan speed and exit velocity.
We want to take a few minutes to share our Smart Lab concept
Selection process considered a large array of building characteristics… Exhaust stack parameters including stack height, exit velocity, flow per stack, and momentum flux Additional considerations included… Whether the building utilized a variable air volume or constant air volume HVAC design Whether the laboratory design was supported by wind tunnel testing of exhaust dispersion
Taken together, these three laboratory buildings provide a representative group, allowing reasonable extrapolation of the results that is reported here to other laboratory buildings on the campus, other UC campuses and potentially other California campuses.
These three buildings were selected based on the following criteria: Representative Campus Environments Locations of the selected buildings are representative of two different types of surrounding campus environments, mature region which includes numerous laboratory buildings and significant topographic relief, and a newer region of campus which does not have buildings on one side and contains relatively flat terrain. Representative Exhaust Stack Parameters The exhaust stack parameters of the selected buildings are representative of the general lab building population Significant Lab Activity Each selected building houses a significant level of laboratory activity. Induced-Air Fans I nduced-air lab fans is a type of fan that has been used in a number of recent laboratory exhaust system renovations on the UCI campus and is a popular design option for labs on other campuses as well. Curved Metal Roofs is an important design feature repeated with variations on other laboratory buildings on the UCI campus. Manifolded Exhaust Another design feature that is repeated on the UCI campus. With this configuration it also provides enhanced in-stack dilution of hazardous releases and provides enhanced momentum flux to support larger plume rise and better atmospheric dispersion of the exhaust plumes. Modern Design Approach All three buildings are representative of modern design approaches.
Chet starts here.
Chet or Jay Show the plumes and effects on dispersion of short/tall stacks and low/high exit velocities. So, we would likely select a taller stack for energy reduction which allows us to reduce the fan speed and exit velocity.
Whenever we reduce the exit velocities, we lose some safety margin. This can be offset in some cases through other measures such as raising stack heights, clustering stacks, etc., however, the tendency overall is to remove some of the safety margin. As a result, we must Be more comprehensive in the wind tunnel testing – including such things as taking care to ensure enough receptors are installed on roofs. Perform field commissioning of the exhaust plume dispersion of the renovated system. This provides an overall test of the safety and energy efficiency of the system. Educate the lab users in proper use of fume hoods and other exposure control devices which are used in the labs. Particularly, they should know how much dilution they can count on from the lab hazardous exhaust system and how to relate that to the activities they are performing in fume hoods.
Wind tunnel testing is based on fluid dynamic similarity modeling—like wind tunnel tests of aircraft wings. Once the test is properly set up, we can measure in the wind tunnel almost anything related to wind and multiply it by the appropriate scale factor to determine the full-scale real-world value. The dilution of exhaust plumes is one of the wind-related parameters which can be well modeled in the wind tunnel. The wind tunnel is the only means available today to accurately model wind flow and related parameters around buildings. If you are considering using alternative methods such as desktop calculations or Computational Fluid Dynamics for this purpose, please talk to me off-line. I can provide references to articles in the technical literature which clearly describe the shortcomings of non-wind-tunnel approaches. The first step in setting up a wind tunnel test is to build an accurate scale model of the building under study and the buildings, terrain and trees around it. You need to extend the model out about ¼ mile in all directions to take account of the effects of upwind buildings, etc on the wind and turbulence at the building under study. Here we see the model used in this study for the Biological Sciences 3 and Natural Sciences 1 lab buildings. They are the blue buildings in the center. The model is at a scale of 1:200 and includes terrain and trees as well as buildings for ¼ mile radius. The accuracy of the model is directly related to the accuracy of the results. So it is important to put sufficient effort into recreating a model which accurately represents the existing buildings as well as those which are expected to be built within the next few years. The model is mounted on a turntable will is rotated by the wind tunnel operator to model different wind directions. In this photo, you are looking upwind and can see the wood blocks which are used to create the proper profile of wind speed and turbulence in the air approaching the test model—more about that a little later.
Brass tubes are installed in the model to represent the exhaust stacks. The flow through these stacks must be properly scaled to produce accurate dispersion results.
Tubes are installed in the model to take air samples at locations where the concentration of the exhaust plume might be important. The jargon term for these points is “receptors.” The locations are indicated by the numbered arrows. Note that some of the receptors use blue plastic fixtures which are designed to take their sample at a height of about 5 feet full scale. This is representative of the breathing zone for the average person.
The air approaching the model must reproduce the vertical profile of wind speed and turbulence found in the real atmosphere. These profiles are the result of the eddies caused at the ground by obstacles to the flow—buildings, trees, vehicles, etc. We simulate these in the wind tunnel using an array of blocks on the floor of the wind tunnel upwind of the model. This part of the wind tunnel is called the approach section and must be long enough to allow an equilibrium profile (boundary layer) to be established in the flow before it reaches the test model. Longer approach sections allow more well-developed profiles. The diagram shows the AAT wind tunnel layout with 120 feet of approach section upwind of the test section. Here is a picture of the AAT wind tunnel showing the approach and test sections. The vertical profiles of wind speed and turbulence are measured to ensure they reasonably match those in the real atmosphere—as shown in these graphs.
The data for each receptor/stack combination was taken for each wind direction of consequence for all wind speeds. These were plotted as shown in the graph. The blue line is for a 7.2-foot stack and the magenta line is for a 12.2-foot stack. Note 1) the taller stack produces smaller concentrations and 2) the maximum concentration occurs at the “critical wind speed.” Below this speed the plume rises higher leading to lower concentrations. Above this speed, the dilution cause by mixing with the greater amount of air passing by the stack reduces the concentrations. Both of these effects are present for all wind speeds. There effects add to produce the resulting curve. In a typical design project, the wind tunnel is used to find the maximum concentration up to the critical wind speed or the 1-% wind speed, which ever is higher. The 1-% wind speed is the 99 th -percentile speed at the site. We took the more complete set of data for this project to facilitate evaluation of design alternatives.
The first step (which has some major ramifications later on) is to establish the “design criteria.” This specifies the minimum acceptable dilution for the exhaust plumes. It is most convenient to specify this in terms of “normalized concentration” because the normalized concentration does not change if the exhaust flow from the stack changes. The normalized concentration is simply the concentration of the pollutant at a receptor (µg m -3 ) divided by the emission rate of the pollutant from the exhaust stack (g s -1 ). This is solely a function of the plume dispersion. The ASHRAE recommendation for the design criteria for lab exhaust is 400 (µg m -3 )/ (g s -1 ). It generally provides a good starting point when little is known about the future activity in the lab—the most common situation. ANSI Z9.5 provides an alternative recommendation of 750 (µg m -3 )/ (g s -1 ). This is based on the idea that the lab exhaust system should ensure at least as much protection as is afforded a lab worker using a fume hood. We prefer the more conservative ASHRAE standard partly since it seems inappropriate to expose the general population, who may not have made a career decision to work in a lab, to the same level of pollution as a lab worker who supposedly knows and has some control over the risks. The recommended standards should serve only as a starting point. As more is known about the activities (existing and future) in a lab, more appropriate design criteria can be developed. A few consultants provide the service of evaluating the lab activities to develop an appropriate exhaust dispersion design criteria. Tom Smith at Exposure Control Technologies provided that service for this study. ECT can also provide consulting to lower the energy use inside the lab while maintaining or improving the safety of workers.
We want to take a few minutes to share our Smart Lab concept
Most of the time, the exhaust fans are running much faster (higher exit velocity) than is actually required. Here is a reasonably typical hour-by-hour look at the flow (CFM) required to meet plume dispersion requirements for a lab exhaust (Required by Dispersion). The hour-by-hour variation is due to variations in the wind speed and direction at the building. The spike at 1600 hours (4 pm) could be the result of a cold front passing over the building and producing high winds for a short time. (Required by High Air Change Rate) This curve shows the exhaust flow required to support a high air change rate in the imaginary building. You can see that at times the flow required to maintain the air change rate determines the required stack flow—other times the plume dispersion requirements dominate. (Required by Low Air Change Rate) This curve demonstrates the potential effect of lowering the air change rate in the building. The relative magnitude of these three curves can, of course, vary dramatically from building to building, but this chart serves well for demonstration. (1% Design) The blue line shows the continuous air flow that would be specified if the 1% wind speed was accurately accounted for and happened to occur on the day we’ve plotted. More commonly, the design (Typical Design) incorporates additional conservatism as represented by the orange curve. The static system designs (constant exit velocities) discussed here are best represented by the blue line—the 1% design. Using dynamic control systems to adjust the exit velocities in response to the wind speed and direction, the flow required can be reduced to the highest of the three lines at the bottom of the chart—the highest of the red, black or gray lines.
NOTE – General Laboratory Savings are limited by the minimum exhaust flow required to obtain acceptable plume dispersion. Reducing the minimum air exhaust rate below 6 ACH will not affect these results. However, reducing the minimum air change rate will result in a smaller quantity of air serviced by the supply fans. NOTE – BSL 3 Lab Savings are limited by the minimum exhaust flow required to obtain acceptable plume dispersion. Reducing the minimum air exhaust rate below 6 ACH will not affect these results. However, reducing the minimum air change rate will result in a smaller quantity of air that needs to be conditioned for use in the building. The resulting savings in energy require to condition that air could be substantial.
In order to ensure the safety of persons on the Natural Sciences 2 rooftop terrace and those on the Natural Sciences 1 roof and also save energy and on-going utility costs. NOTE: savings are limited by the minimum exhaust flow required to obtain acceptable plume dispersion. Reducing the minimum air exhaust rate below 6 ACH will not affect these results. However, reducing the minimum air change rate will result in a smaller quantity of air serviced by the AHU supply fans.
We want to take a few minutes to share our Smart Lab concept
As was discussed earlier on in the presentation: Establish design criteria/performance guidelines for the design and use of laboratory exhaust systems Wind tunnel screening study to prioritize the other existing laboratory buildings that can benefit from this type of study New and renovated designs should be audited to ensure consistency with wind tunnel results Field commissioning studies should be performed on new and renovated exhaust systems Wind tunnel firms need to install a sufficient number of receptors on the roofs of test models to ensure detecting maximum concentrations and should submit model construction drawings.
Jay-
The goal of our smart labs project is to find the sweet spot where we maximize energy savings without compromising safety. At this point all turn it over to Chris Abbamanto.
Based on the evaluation of the existing exhaust system, identify reasonable alternative renovation strategies. These will be approaches which can reduce the exit velocities of the exhaust while maintaining safe plume dispersion. Variable frequency drives provide an efficient means to reduce the flow through fan with large energy penalties. Stack extensions are a common way to improve plume dispersion. In this photo, a set of lab exhaust stacks was originally design too short (the white part of the stacks). In response to recurring odor problems, the stack height was increased (the black portion of the stacks), plume dispersion was improved, and the odor problem was resolved. Extensive manifolding and clustering are also demonstrated by this set of exhaust stacks. (Use cursor to point out manifolding). You can see at least two exhaust streams manifolded into this stack. And the close grouping of stacks (clustering) allows their plumes to merge in the air above the exit plane. There are some additional requirements for clustering to be effective which I’ll be happy to discuss with anyone interested off line. With either clustering or manifolding, we end up with larger plumes which are more diluted and rise to greater heights above the roof. When two or more fans service the same plenum, a relatively simple action which can save fan energy is to redefine which fans come on at what speeds to exhaust the plume(s) to the atmosphere. For example, if only one fan of a pair is running (a typical N+1 redundancy), splitting the flow between the two fans/stacks would reduce the exit velocity by a factor of 2. Since the energy required to move the air is proportional to the cube of the speed, this can theoretically reduce the fan energy by a factor of 2 cubed—or eight. Before implementing such an approach, it is necessary to review the fan efficiency curves and perform wind tunnel testing to ensure that plume dispersion at the lower exit velocity continues to provide acceptable plume dispersion. Installation of VFD controllers can solve the common issue of inefficient operation of the fans as speeds are reduced. After the alternative renovation designs have been identified, wind tunnel testing is conducted to determine whether acceptable plume dispersion is achieved. Wind tunnel testing can be used to determine minimum acceptable design parameter to ensure safety. For example, how low can the exit velocity be and still provide safe plume dispersion?
Based on the evaluation of the existing exhaust system, identify reasonable alternative renovation strategies. These will be approaches which can reduce the exit velocities of the exhaust while maintaining safe plume dispersion. Variable frequency drives provide an efficient means to reduce the flow through fan with large energy penalties. Stack extensions are a common way to improve plume dispersion. In this photo, a set of lab exhaust stacks was originally design too short (the white part of the stacks). In response to recurring odor problems, the stack height was increased (the black portion of the stacks), plume dispersion was improved, and the odor problem was resolved. Extensive manifolding and clustering are also demonstrated by this set of exhaust stacks. (Use cursor to point out manifolding). You can see at least two exhaust streams manifolded into this stack. And the close grouping of stacks (clustering) allows their plumes to merge in the air above the exit plane. There are some additional requirements for clustering to be effective which I’ll be happy to discuss with anyone interested off line. With either clustering or manifolding, we end up with larger plumes which are more diluted and rise to greater heights above the roof. When two or more fans service the same plenum, a relatively simple action which can save fan energy is to redefine which fans come on at what speeds to exhaust the plume(s) to the atmosphere. For example, if only one fan of a pair is running (a typical N+1 redundancy), splitting the flow between the two fans/stacks would reduce the exit velocity by a factor of 2. Since the energy required to move the air is proportional to the cube of the speed, this can theoretically reduce the fan energy by a factor of 2 cubed—or eight. Before implementing such an approach, it is necessary to review the fan efficiency curves and perform wind tunnel testing to ensure that plume dispersion at the lower exit velocity continues to provide acceptable plume dispersion. Installation of VFD controllers can solve the common issue of inefficient operation of the fans as speeds are reduced. After the alternative renovation designs have been identified, wind tunnel testing is conducted to determine whether acceptable plume dispersion is achieved. Wind tunnel testing can be used to determine minimum acceptable design parameter to ensure safety. For example, how low can the exit velocity be and still provide safe plume dispersion?
After the chosen exhaust system renovation is installed, a commissioning test of the entire system including plume dispersion should be performed to ensure that the design criteria is achieved—and safe exposure levels are obtained. The commissioning test involves releasing tracer gas through the actual exhaust stack and measuring the resulting concentrations at key receptor locations downwind. This 1) provides an overall check of the entire exhaust system include dispersion and 2) ensure a margin of safety is actually achieved.
How would you approach a comprehensive program to obtain these energy saving for all off the lab buildings on your campus?
Since the purpose of this study is to provide results generally representative of laboratory buildings on the UCI campus – and potentially representative of those on other UC campuses – three buildings were selected after careful consideration of a list of nine laboratory buildings on the UCI campus. The nine buildings considered for inclusion in this study were: Biological Sciences Nat Sci 1 Nat Sci 2 Croul Hall Hewitt Hall Sprague Hall Cal-IT2 Engineering Lab Facility Engineering Gateway
First establish a campus-wide guideline for how design criteria are to be specified for the lab buildings. This is fundamental to a successful effort. You also need to specify which areas are subject to the design criteria and which are not—roofs? Mechanical rooms? Jay- It would also be useful to have a campus-wide guideline regarding the required air change rate in lab buildings to facilitate calculation of exhaust air flow rate.
To make the best use of progressively scarcer resources it is useful to conduct a campus-wide screen study to identify the “low-hanging fruit”—lab buildings for which small up-front investments can produce large energy and cost savings. The screening study consists of an abbreviated wind tunnel study and a preliminary mechanical review of hazardous exhaust systems. The wind tunnel study would primarily use qualitative test (smoke visualization) to identify the predominate flow and dispersion features, including a limited number of quantitative measurements (tracer gas studies) to verify the magnitude of suspected issues. Preliminary estimates should be made of the required up-front investment and cost/energy savings.
Based on the results of the screening study, prioritize the buildings for renovation design and implementation. Perform the design effort as previously discussed. Be sure to include field commissioning of the exhaust plume dispersion to ensure that everything has been implemented according to the design and that safety and energy savings will be achieved.
Wind tunnel testing of exhaust dispersion is done in two primary modes. The first is smoke visualization as shown in this video clip. This allows us to see the plume and gives us a good idea of the flow phenomena controlling where the plume goes and how fast it is being diluted. This is very useful in understanding what is happening and devising alternative exhaust design approaches. The second mode of testing is the use of a precision tracer gas and analysis of its concentration in air samples at receptors to quantitatively specify the exhaust plume dilution. This is the fundamental set of measurements which tell us whether the maximum concentrations at receptors will exceed those allowed by health or odor standards.