Assessing Ambient Levels and Personal Exposures in Baltimore: The SEARCH Project

Transcription

1 Assessing Ambient Levels and Personal Exposures in Baltimore: The SEARCH Project Misti Levy Zamora Benjamin F. Hobbs Dept. Environmental Health & Engineering Johns Hopkins University MARAMA MONITORING COMMITTEE TRAINING WORKSHOP Wayne, PA Nov. 1-3, 2017 Thanks to Kirsten Koehler, Howard Katz, & Ben Zaitchik for their contributions Air Climate & Energy (ACE) Center Grant funded by US Environmental 1 Protection Agency Assistance Agreement No. RD

2 Introduction to SEARCH Center Michelle Bell, Yale U, Director Benjamin Hobbs, JHU, Co-Director 2

3 1999 History of EPA Air Research Centers Particulate Matter Harvard USC+ Univ. of Rochester NYU Univ. of Washington 2005 Particulate Matter Harvard USC+ Univ. of Rochester Johns Hopkins San Joaquin 2011 Clean Air 2015/16 Harvard Emory/Georgia Tech Univ. of Washington Univ. of Michigan Air, Climate, & Energy Yale/Johns Hopkins Harvard/MIT CMU 3

4 SEARCH Objectives 1. To investigate energy-related transitions 2. To characterize how transitions contribute to emissions, air quality and health Combining state-of-art modeling of energy systems, air quality, climate, & health Focus: Their effect on regional & local differences in air pollution and public health effects under today s and tomorrow s climate 3. To identify key modifiable factors (e.g., transportation, landuse, power generation) And how their air quality impacts are likely to change over time 4

5 SEARCH Conceptual Model 5

6 Project 2 Study Area In the I-95 corridor Moderate Ozone Non-Attainment Area Upcoming Energy Transitions in Baltimore Retirement of 2 coal-fired power plants (2018) New natural gas-fired plants Evolving motor vehicle fleet Major port expansion New light-rail line Baltimore, MD Opportunity to assess how real-world changes impact air quality 6

7 Kirsten Koehler JHU Drew Gentner Yale Project 2: Assess air impacts of energy-related sources & transitions using novel high-resolution ambient monitoring networks & personal monitors Principal Hypothesis: Energy-related factors account for a significant fraction of observed heterogeneity in regional air quality & personal exposure Key elements: Novel portable & stationary multi-pollutant monitors High spatiotemporal monitoring with stationary & personal networks Policy-relevant evaluation of how individual & regional energy/sustainabilityrelated choice impact personal exposure and ambient pollution 7

8 Develop novel online sensors for oxidizing air pollutants (Howard Katz Lab, JHU) Produce large quantities of inexpensive, widely deployable sensors for oxidizing air pollutants (e.g., NO 2 ) Synthesize printable responsive materials, such as conducting polymers, with response patterns characteristic of the pollutant of interest Produce prototype sensor devices and characterize: physical properties responses to pollutants and interferents Seek commercialization 8

9 Monitor Development Accomplishments NO 2 -responsive polymer-based organic field-effect transistors (OFETs) with 1 ppm detection made: Two thiophene polymers, poly(bisdodecylquaterthiophene) and poly(bisdodecylthioquaterthiophene) (PQT12 and PQTS12, respectively), were active layers The proportional on-current change of OFETs using these polymers reached over 400% for PQTS12 -- among the highest sensitivities reported for NO 2 -responsive devices based on organic semiconducting films The ratio of responses of PQTS12 and PQT12 is higher for exposures to lower concentrations, making this parameter a means of distinguishing responses to low concentrations for extended times from exposures to high concentrations from shorter times Schematic of device structure Structures of polymer semiconductors 9

10 Baltimore Urban Heat Island monitoring network (Ben Zaitchik Lab, JHU) Objective: Temperature and humidity sensors deployed in East Baltimore Quantify & explain neighborhoodscale variability in Baltimore s urban heat island Activity: > 100 low cost temp/humidity sensors deployed in Findings to date: Green spaces systematically cooler, day and night No air temperature impact detected for street trees alone Urban heat island shrinks on hottest days Ben Zaitchik & Anna Scott, JHU 10

11 SEARCH Project 2: Assessment of energy-related sources, factors, and transitions using novel high-resolution ambient air monitoring networks and personal monitors Presenter: Misti Levy Zamora, Johns Hopkins University 11

12 Project Team Members Co-PIs: Kirsten Koehler (JHU) & Drew Gentner (Yale) Monitor development: Lizi Xiong (Yale), Branko Kerkez (U. Mich.), Jordan Peccia (Yale) Sensor development: Howard Katz (JHU) Monitor siting: Jesse Berman (now at University of MN) and Ben Zaitchik (JHU) 12

13 Project Objectives Objective 1: Develop novel online multi-pollutant monitors (stationary and portable models) to measure air pollutants and greenhouse gases. Objective 2: Measure pollutants with high spatiotemporal resolution using a multi-pollutant stationary monitoring network. ~50 monitors at ~100 locations over three years Objective 3: Measure temporally resolved personal exposures with detailed time-activity information. 100 participants with personal multi-pollutant monitor + GPS 13

14 Objective 1: Custom Multi-pollutant Monitors Stationary model: Multi-pollutant monitor network Portable model: Wearable multi-pollutant monitors (no backpack!) 14

15 Stationary Custom Multi-pollutant Monitors Measured Air Pollutants Particulate Matter (PM 2.5 ) Ozone (Tropospheric) Nitrogen Dioxide (NO 2 ) Sulfur Dioxide (SO 2 ) (stationary only) Gas PM Carbon Monoxide (CO) Methane (CH 4 ) Carbon Dioxide (CO 2 ) 15

16 Online Monitoring Grafana online Platform Password protected Updates every 5 seconds SD card back up 16

17 Field Calibrations and Evaluation Routine maintenance will be used to assess long-term, field performance of monitors and ensure high quality of the data collected during this field campaign. If zero or span output deviates from baseline by > 15%, monitors will be returned to the laboratory. Sensors will be replaced if they cannot be recalibrated to meet accuracy requirements (±15% 95% of the time). 17

18 Laboratory Monitor Evaluation Each monitor will be calibrated in the lab with our Multi-Gas Calibrator before deployment. The PM monitor has been evaluated in the lab for several scenarios: 6 PM sources High/low Relative Humidity Movement NO 2 Example Calibrations CO 18

19 Monitor Evaluation Cont. We tested the accuracy and precision of the monitors by exposing them to 6 aerosol sources: Incense Oleic Acid NaCl Talcum Powder Ambient Indoor Air Cooking Emissions The measurements were compared with a personal DataRAM pdr- 1200, SMPS, and APS. 19

20 Monitor Evaluation Cont. The instruments exhibited a high degree of precision with Pearson correlation coefficients > Similar degree of accuracy and precision in the high and low moisture environments. A B Movement of the monitor was not found to influence the measuring capabilities of the SEARCH instrument 20

21 Objective 2: Capturing spatiotemporal heterogeneity in Baltimore, MD EPA Stations (hourly-weekly data) Stationary Monitors (time resolution: hourly+) Portable Monitors (time resolution: hourly+) Google Stationary monitors with strategic placement across 100 sites in 3 years. Site locations are shown for example only. High spatial and temporal analyses across multiple platforms are now possible to determine: Pollutant dynamics Exposure Emissions and sources Chemistry Transport 21

22 Objective 3: Personal Exposure Assessment Participants will receive the monitor a GPS unit for 24 hrs. of monitoring Reference monitoring equipment for a subset of ~10% Questionnaire on important sources 2X We will determine the contribution of distinct microenvironments to the individual s cumulative 24- hour exposure. 2X 100 Participants 4 sampling days We will evaluate differences between indoor and outdoor environments using the distributed network and examine changes in personal exposures on high electricity demand days and for seasonal change. 22

23 Personal Monitoring in Texas 23

24 What kind of data will we get? High spatial- and temporal- resolution ambient data 3 years of hourly+ resolution data at 50+ locations Detailed reliability data on low-cost sensor networks High temporal-resolution data on personal exposures for 100 participants. Personal exposures for multiple pollutants at high temporal resolution paired with GPS for microenvironment analyses Impact of energy-related sources to personal exposures (source apportionment with quantitative methods unit) Impact of modifiable factors on personal exposures Exploring regional vs. local sources with meteorological back trajectory modeling and air quality models (with Project 3) Results are directly relevant for public health interventions, personal commute decision-making, and policy-making regarding transportation and community design. 24

25 Thank you for your attention! 25

26 Pollutant Table 1. Sensor Packages Package 1 Package 2 Sensor Stationary Stationary monitors monitors Mobile Personal monitors O 3 MiCS-2614 X X X PM Plantower PMS7003 X X X CO alphasense, CO A4 X X X NO 2 alphasense, NO 2 A4 X X X SO 2 alphasense, SO 2 A4 X X CO 2 alphasense NDIR IRCA1 X X X Volatility resolved VOCs custom w/ alphasense PID AH X Oxidative Potential custom polymer board X CH 4 Temp, RH Figaro TGS SHT25, breakout PCB X X X X X X 26

27 Strategic Monitor Siting Category Transportation Factors (All roads, Major Roads, Bus Routes, Shipping Ports, Airports, Amtrak Lines, Light Rail Lines) Weight 3 Air Pollution 2 Population Density 1 Energy (Petroleum terminals, Power plants coal) Point Sources (e.g., Restaurants) Fixed Sites (e.g., MDE Sites) 3 1 Triangles denote 50 original sample locations; X s denote 10 additional sampling locations 27