NACAA MSC, North Carolina

Slides:

Advertisements

Similar presentations

Gas Detection Strategies Overview of Selection Criteria for Gas Detection Systems.

Advertisements

1 History of the Development and Deployment of a Real Time Multi- Metals CEMS and Fence Line Monitor Dan Bivins Measurement Technology Group U. S. EPA.

Although this monitor is owned and operated by the State of Missouri, significant research was conducted with this technology for fence-line monitoring.

Comparing Methods for the Real- Time Measurement of Secondhand Tobacco Smoke Particles Neil E. Klepeis Visiting Scholar, Stanford University, Department.

A Study of Temporal Variability of Atmospheric Total Gaseous Mercury Concentrations in Windsor, Ontario, Canada Xiaohong (Iris) Xu, Umme Akhtar, Kyle Clark,

Halûk Özkaynak US EPA, Office of Research and Development National Exposure Research Laboratory, RTP, NC Presented at the CMAS Special Symposium on Air.

Distribution of NO 2 concentrations over shooting (400 µg/m 3 per 1 hour) calculated with POLAIR dispersion model using (2004) NO 2 concentrations from.

AOSC 634 Air Sampling and Analysis Lecture 1 Measurement Theory Performance Characteristics of instruments Nomenclature and static response Copyright Brock.

Three-State Air Quality Study (3SAQS) Three-State Data Warehouse (3SDW) 2008 CAMx Modeling Model Performance Evaluation Summary University of North Carolina.

Integrating satellite observations for assessing air quality over North America with GEOS-Chem Mark Parrington, Dylan Jones University of Toronto

EPA Precursor Gas Training Workshop Kevin A Cavender EPA-Office of Air Quality, Planning and Standards Precursor Gas Monitoring NO y Monitoring Training.

Dr. Sarawut NINSAWAT GEO Grid Research Group/ITRI/AIST GEO Grid Research Group/ITRI/AIST Development of OGC Framework for Estimating Near Real-time Air.

Revisions To Heavy Duty Validation Report General Numerous clarifications to text as requested at December meeting Partial flow systems referred to consistently.

What to compare against the validation templates (see templates in course webpage: Resources/Validation%20Templates%20from%20Red.

OTAG Air Quality Analysis Workgroup Volume I: EXECUTIVE SUMMARY Dave Guinnup and Bob Collom, Workgroup co-chair “Telling the ozone story with data”

South Coast AQMP/SIP Ozone & PM2.5 Control Strategy Laki Tisopulos, Ph.D., P.E. Assistant Deputy Executive Officer South Coast Air Quality Management.

European Metrology Research Program (EMRP) MeteoMet Project (October 2011) WP3. Traceable measurements methods and protocols for ground based meteorological.

CMAS Conference, October 16 – 18, 2006 The work presented here was performed by the New York State Department of Environmental Conservation with partial.

Continuous Particulate Training Workshop

Alternative Approaches for PM2.5 Mapping: Visibility as a Surrogate Stefan Falke AAAS Science and Engineering Fellow U.S. EPA - Office of Environmental.

Earth System Sciences, LLC Suggested Analyses of WRAP Drilling Rig Databases Doug Blewitt, CCM 1.

June 12 &13, 2007 Mickey Leland National Urban Air Toxics Workshop II – Houston, Texas 1 Albuquerque, New Mexico Community Scale Ambient Air Monitoring.

Lidar Working Group on Space-Based Winds, Snowmass, Colorado, July 17-21, 2007 A study of range resolution effects on accuracy and precision of velocity.

Drivers of multidecadal variability in JJA ozone concentrations in the eastern United States Lu Shen, Loretta J. Mickley School of Engineering and Applied.

PM2.5 Model Performance Evaluation- Purpose and Goals PM Model Evaluation Workshop February 10, 2004 Chapel Hill, NC Brian Timin EPA/OAQPS.

Importance of Lightning NO for Regional Air Quality Modeling Thomas E. Pierce/NOAA Atmospheric Modeling Division National Exposure Research Laboratory.

Modeling Overview For Barrio Logan Community Health Neighborhood Assessment Program Andrew Ranzieri Vlad Isakov Tony Servin Shuming Du October 10, 2001.

Ammonia Measurement Techniques Ji-Qin (Jee-Chin) Ni, Ph.D. Dept. of Agricultural and Biological Engineering Purdue University October 21, 2008 Albuquerque,

WESTAR Council – Continuous PM 2.5 Monitoring Workshop Portland, Oregon April 13-14, 2005 Real-Time Smoke Monitoring.

Climate, Air Quality and Noise Graham Latonas Gartner Lee Limited RWDI Air Inc.

CARB Continuous PM 2.5 Monitoring Activity (BAM’s) Reggie Smith California Air Resources Board.

Next Generation Air Monitoring: An Overview of US EPA Activities National Air Quality Conference RTP, NC February 12, 2014 Tim Watkins US EPA/Office of.

Latvian Environmental, Geology and Meteorology agency Future development scenarios for traffic system and air pollution in Riga city Iveta Steinberga La.

PM Model Performance in Southern California Using UAMAERO-LT Joseph Cassmassi Senior Meteorologist SCAQMD February 11, 2004.

Ozone Update Ben Wells U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Air Quality Analysis Group February 11, 2014.

Transboundary Air Pollution Plan of Islamic Republic of Iran

OAR Perspective on Air Sensors Kristen Benedict National Tribal Forum on Air Quality 5/13/14.

OTAG Air Quality Analysis Workgroup Volume I: EXECUTIVE SUMMARY Dave Guinnup and Bob Collom, Workgroup co-chair Telling the OTAG Ozone Story with Data.

Regional Modeling Joseph Cassmassi South Coast Air Quality Management District USA.

Office of Research and Development National Exposure Research Laboratory, Atmospheric Modeling and Analysis Division Office of Research and Development.

Meteorological Observatory Lindenberg Results of the Measurement Strategy of the GCOS Reference Upper Air Network (GRUAN) Holger Vömel, GRUAN.

1 Overview Community Health Modeling Working Group Meeting Tony Servin, P.E. Modeling Support Section Planning and Technical Support Division May 6, 2003.

Janice Lam Snyder, SMAQMD December 11, 2015

1 Greenhouse Gas Monitoring Network Update Pat Vaca, Air Pollution Specialist

Low-cost Sensor Packages for Roadside Emissions Factor Estimation CMAS – 10/7/2015 KAROLINE K. JOHNSON, MICHAEL H. BERGIN, DUKE UNIVERSITY ARMISTEAD G.

Uncertainties in Wildfire Emission Estimates Workshop on Regional Emissions & Air Quality Modeling July 30, 2008 Shawn Urbanski, Wei Min Hao, Bryce Nordgren.

Alternative Approaches for PM2.5 Mapping: Visibility as a Surrogate Stefan Falke AAAS Science and Engineering Fellow U.S. EPA - Office of Environmental.

PM Methods Update and Network Design Presentation for WESTAR San Diego, CA September 2005 Peter Tsirigotis Director Emissions, Monitoring, and Analysis.

Breakout Session 1 Air Quality Jack Fishman, Randy Kawa August 18.

Emission reductions needed to meet proposed ozone standard and their effect on particulate matter Daniel Cohan and Beata Czader Department of Civil and.

Evaluating the Use of Many Low-Cost Sensors for Monitoring NO 2 Gradients Presented by Timothy S. Dye, David L. Vaughn, Alison E. Ray, and Paul T. Roberts.

New technologies and architectures for sensing gases and particles in air are emerging for criteria pollutants, air toxics, and greenhouse gases. These.

Continuous Particulate Matter (PM 2.5 ) Monitoring Tom Dann Luc White, Alain Biron Luc White, Alain Biron Environment Canada, Ottawa Tom Dann Luc White,

Preliminary Analysis by: Fawn Hornsby 1, Charles Rogers 2, & Sarah Thornton 3 1,3 North Carolina State University 2 University of Texas at El Paso Client:

Applying Sensor Networks to Evaluate Air Pollutant Emissions from Fugitive and Area Sources Office of Research and Development National Risk Management.

Environment Canada, ETC, Ottawa

Implementation of Exceptional and Natural Events Policies and Rules in Arizona Ira Domsky, Deputy Director February 25, 2009.

AIR CLIMATE & ENERGY RESEARCH PROGRAM B U I L D I N G A S C I E N T I F I C F O U N D A T I O N F O R S O U N D E N V I R O N M.

1 National Monitoring Committee Report Bruce Louks WESTAR Fall Meeting Portland, OR September 28, 2010.

7. Air Quality Modeling Laboratory: individual processes Field: system observations Numerical Models: Enable description of complex, interacting, often.

Introduction to Aeroqual

Modeling & Monitoring Update

Presented by Harry C. Elinsky, Jr. Filtech, Inc.

Region 4 Air Sensor Projects

National Monitoring Steering Committee Report

Proposed Ozone Monitoring Revisions Ozone Season and Methods

PMcoarse , Monitoring Budgets, and AQI

J. Burke1, K. Wesson2, W. Appel1, A. Vette1, R. Williams1

Summary: TFMM trends analysis

Measurement Needs for AQ Models

Presentation transcript:

NACAA MSC, North Carolina Update NACAA MSC, North Carolina October 29, 2015 Laki Tisopulos, Ph.D., P.E. Assistant Deputy Executive Officer South Coast Air Quality Management District

AQ-SPEC - Background Governing Board direction to establish center - July 2014 Over $600,000 investment Main Goals & Objectives Evaluate sensor performance Provide guidance & clarity for ever-evolving sensor technology & data interpretation Catalyze successful evolution and use of sensor technology Minimize confusion AQMesh CairClip Shinyei Dylos (prototype) DC1100 Pro SmartCitizens

AQ-SPEC - Overview FIELD TESTING LAB TESTING RESULTS vs (Side-by-side comparison w/ FRMs) LAB TESTING (Controlled conditions) RH = 30% T = 25C Conc = 10 ppb vs RESULTS (Categorize sensors based on performance)

Website / Clearinghouse AQ-SPEC – Overview (continued) SCAQMD Website / Clearinghouse AQ Officials Community Vendors RESULTS

AQ-SPEC Field Testing Started on 09/12/2014 Locations: Sensor tested in triplicates Two month deployment Locations: Rubidoux station Inland site Fully instrumented I-710 station Near-roadway site

AQ-SPEC Field Testing (continued)

T and RH controlled: T (0-50 0C); RH (5-95%) AQ-SPEC Lab Testing Particle testing Particle generation system Particle monitors: mass concentration and size distribution Gas testing Gas generation / dilution system Gas monitors: CO, NOX, O3, SO2, H2S, CH4/NMHC T and RH controlled: T (0-50 0C); RH (5-95%)

AQ-SPEC Lab Testing (continued) Test for: Linearity of response (range) Accuracy & precision Lower detectable limit Concentration resolution Response time Interference equivalents RH and T influences Other T and RH controlled: T (0-50 0C); RH (5-95%)

www.aqmd.gov/aq-spec

www.aqmd.gov/aq-spec

www.aqmd.gov/aq-spec

Sensor vs FEM/FRM Method* Field Testing - Summary Manufacturer (Model) Type Pollutant(s) Cost Time Resolution Sensor vs FEM/FRM Method* HabitatMap (AirBeam) Optical PM2.5 ~$200 1 min R2~0.70 Dylos (DC1100) PM(0.5-2.5) ~$300 R2~0.85 Alphasense (OPC-N2) PM1 PM10 ~$400 15 sec R2~0.90 R2~0.80 Shinyei (PM Evaluation Kit) ~$1,000 MetOne (Neighborhood Sensor) ~$1,900 RTI (MicroPEM) ~$2,000 10 sec *Comparisons refer to 1-hr average data; results are still preliminary; laboratory evaluations needed to confirm field results

Sensor vs FEM/FRM Method* Field Testing – Summary (continued) Manufacturer (Model) Type Pollutant(s) Cost Time Resolution Sensor vs FEM/FRM Method* Smart Citizen Kit Metal oxide CO, NO2 ~$200 1 min R2(CO)~0.85 R2(NO2): unreliable Aeroqual (S-500) O3 ~$500 R2~0.85 Landtec (AQMesh AQM-5) Electrochem. CO, NO, NO2, SO2, and O3 ~$10,000 1-15 min R2(NO)~0.85 R2(NO2)<0.50 R2(O3)<0.50 R2(SO2): unreliable *Comparisons refer to 1-hr average data; results are still preliminary; laboratory evaluations needed to confirm field results

AirBeam PM Sensor AirBeam Sensor (3 units tested): Optical particle counter (non-FEM) PM2.5 count (hundred particles/ft3) and PM2.5 mass (ug/m3) Time resolution: 1-min Unit cost: ~$200 MetOne BAM (reference method): Beta-attenuation monitor (FEM) Measures PM2.5 Cost: ~$20,000 Time resolution: 1-hr GRIMM (reference method): Optical particle counter (FEM) Uses proprietary algorithms to calculate total PM, PM2.5, and PM1 from particle number measurements Cost: ~$25,000 and up Time resolution: 1-min

AirBeam PM Sensor (continued) Preliminary results: High intra-model variability Particle count conc. Good correlation with FEM Particle mass conc. Calibration issues AirBeam v2 recalibrated using field testing data 1-hr ave. R2~0.70

Dylos DC1100/DC1700 Dylos (3 units tested): Optical particle counter (non-FEM) Three different size fractions including PM(0.5-2.5) (used as an estimate of PM2.5) Time resolution: 1-min Cost: ~$300 MetOne BAM (reference method): Beta-attenuation monitor (FEM) Measures PM2.5 Cost: ~$20,000 Time resolution: 1-hr GRIMM (reference method): Optical particle counter (FEM) Uses proprietary algorithms to calculate total PM, PM2.5, and PM1 from particle number measurements Cost: ~$25,000 and up Time resolution: 1-min

Dylos DC1100/DC1700 (continued) Preliminary results: Modest intra-model variability Particle count conc. Good correlation with FEM Particle mass conc. Can be derived via FEM calibration 5-min ave. 5-min ave. 5-min ave. R2~0.80

SmartCitizen Kit Smart Citizen Kit (3 units tested): Metal-oxide sensor (non-FEM) CO (kOhm), NO2 (kOhm), Temperature (C) and Relative Humidity (%) Time resolution: 1-min Unit cost: ~$200 SCAQMD FRM instruments: CO instrument; cost: ~$10,000 Time resolution: 1-min NOx instrument; cost: ~$11,000 Meteorological station (wind speed, wind direction temperature, relative humidity, and pressure); cost: ~$5,000 http://www.smartcitizen.me/

SmartCitizen Kit (continued) 5-min ave. R2<0.80 1-hr ave. R2>0.95 1-hr ave. R2>0.95 Preliminary results: Low intra-model variability CO: good correlation with FRM NO2: no correlation with FRM Reliable T and RH data

AeroQUAL S-500 aeroQUAL S-500 (3 units tested): Metal-oxide sensor (non-FRM) Ozone (pphm) Temperature (C) and Relative Humidity (%) Time resolution: 1-min Unit cost: ~$500 SCAQMD FRM instruments: Ozone instrument; cost: ~$7,000 Time resolution: 1-min Meteorological station (wind speed, wind direction temperature, relative humidity, and pressure); cost: ~$5,000

AeroQUAL S-500 (continued) Preliminary results: Low intra-model variability Ozone conc. Good correlation with FEM Slight signal degradation over time (sensor replacement available) 1-hr ave. R2~0.85

Field Testing - Discussion PM (optical) sensors: Minimal down time Low intra-model variability Strong correlation (R2) with two different FEM instruments Sensor “calibration” may be needed Potential sources of error: Sensors cannot detect very small particles (e.g. <0.5 μm for Dylos) Bias in algorithms used to convert particle counts to particle mass Gaseous sensors: CO; NO; O3 (when measured alone): good correlation with FRMs O3 and/or NO2: low correlation with FRM (potential O3 NO2 interference) SO2: difficult to measure with current electrochemical sensors Chamber testing is necessary to fully evaluate the performance of these sensors All results are still preliminary

Upcoming SCAQMD Activities Low-Cost Sensors Continue w/ testing Identify good performing sensors Pilot sensor network deployment options Geographic/Area wide network applications Fence-line applications Characterization of industrial emissions and their impact on nearby communities US EPA Community Scale Air Toxics Grant Monitor HAP emissions from refineries / other industrial sources (e.g. port) Use ORS techniques (e.g. SOF, max-DOAS, other) and “low-cost” sensors to assess spatial / temporal dispersion of emissions on surrounding communities 3 year study in the Carson-Wilmington area EJ communities participation

Thank you!