Air Sensors Data Interpretation and Application

Transcription

1 Air Sensors Data Interpretation and Application Mecklenburg County Air Quality Forum November 17, 2016 Kristen Benedict Office of Air Quality Planning & Standards U.S Environmental Protection Agency 1

2 Proliferation of Air Sensors 2

3 Emerging Technology Characteristics Emerging air monitoring systems (informal classification) Group 1: Regulatory or regulatoryequivalent air monitoring stations Cost: 100Ks (in thousands), Data existing reliability = A+ emerging Group 2: Smaller-footprint monitoring systems for community screening and research studies Cost: 1-10Ks, Data reliability = B+ (target) Group 3: Very small, very low cost systems enabling dense sensor networks, citizen science Cost: 0.1-1Ks, Data reliability =? (slide courtesy of Gayle Hagler)

4 Emerging Technology Characteristics Current Technology Expensive Often snapshot Big footprint with dedicated power source May require expertise to use Often delays for lab analysis Established QA protocols Collected by gov, industry, researchers Data stored and explained on gov websites New Technology Low cost Often continuous Small footprint or mobile, battery or solar power Perhaps easy-to-use Real-time w/o lab analysis QA protocol gaps Collected by communities and individuals Data shared and accessed on non-gov sites U.S. Environmental Protection Agency 4

5 Data Application - Example Pre- Construction PSD Permit Permitting agency may require postconstruction monitoring Role for Sensors? Monitor for one year CAA Section 165(c)(2) Existing source expansion option for monitoring* *Use sensors in design phase to inform placement of regulatory monitor 5

6 Data Application 1 Tier Application Area Pollutants I II III Education and Information Hotspot Identification and Characterization Supplemental Monitoring Precision & Bias Error 2 Data Completeness 2 All <50% 50% All <30% 75% Criteria pollutants, Air Toxics (incl. VOCs) <20% 80% IV Personal Exposure All <30% 80% V Regulatory Monitoring O 3 CO, SO 2 NO 2 PM 2.5, PM 10 <7% <10% <15% <10% 75% 1. These are guidelines only (Tier I- Tier IV), and are likely to evolve over time as technology continues to develop and the state of the science continues to advance. The amount of data needed for any air quality purpose is highly specific to that purpose and could range from minutes to even years of data measurements. 2. Precision, bias, and data completeness requirements in part were taken from Appendix D of the EPA Quality Assurance Handbook for Air Pollution Measurement Systems Volume II (May 2013 edition). Refer to 40 CFR Parts 50, 53, 58, and the QA Handbook Volume II for all activities/criteria required for monitoring network data. 6

7 PM 2.5 Sensor Field Study - Overview 7 Main Objective: Examine the use of low-cost particulate matter (PM) sensors for answering questions about Tribal air quality Monitoring is being conducted in two phases: Phase 1:: Collocation of the sensors with existing PM 2.5 Federal Reference Method (FRM) monitor Phase 2: Monitoring near a local source to examine impacts on local air quality and nearby PM concentration gradients

8 Phase 2: Near-Source Monitoring 8 Collected data near a 1940 s boiler/kiln on June 13-17, 2016 MicroPEM and both AirBeams (AirBeam A is working under more moderate, summertime conditions) Performed meteorological forecasts 1-day ahead to determine which site to monitor at each day given forecasted prevailing winds Set up a small meteorological tripod to monitor wind speed and direction Performed mobile monitoring with one AirBeam to examine spatial gradients near the source

9 Mobile Monitoring Preliminary Results 9

10 Sensors Moving Forward E-Enterprise Advanced Monitoring Scoping Team (EEAMT) Recommendations E-Enterprise Leadership endorsed five recommendations in April 2016 All five teams moved into the implementation phase in summer 2016 Members: States (organized by ECOS), OAR, ORD, OECA, OW, OEI, and EPA Regions Recommendations: #1: Feasibility study for a voluntary 3 rd party certification program #2: Technology screening and support network #3: Interpretation of data from advanced monitoring approaches #4: Data standards & data quality tiers #5: Lean technology evaluation parameters 10

11 Sensors Moving Forward Sensor technology has great potential to empower people to understand local air quality but communicating real-time data is complicated Health studies do not support linking short term (e.g. 1-minute O 3 or PM 2.5 ) exposures to adverse health effects Many developers are incorrectly using whatever information is available currently, e.g., AQI 11

12 Sensor Scale Pilot Project On May 6 th, 2016 EPA launched a new sensor scale EPA developed the scale to help the public understand 1- minute data from Village Green stations EPA is working to finalize messaging for O 3 and PM 2.5 and plans to develop messaging for additional pollutants Pilot appears on existing Village Green data webpage A fact sheet, FAQs, and other information available on the Air Sensors Toolbox 12

13 EPA s Smart City Air Challenge A challenge that encourages communities to deploy hundreds ( ) of air quality sensors and make the data open EPA will award prizes of up to $40,000 to two communities based on their strategies, including their plans to share data management methods so others can benefit The prizes are intended to be seed money - partnerships are essential Challenge closed October 28 th, 2016 EPA is reviewing submittals 13

14 Discussion 14

15 Discussion Questions Where do you see sensors being of most use? What questions have you fielded or expect to field concerning air sensors? Has anyone approached you about using air sensors for what purpose? What questions/comments/concerns do you have for EPA? 15