A 3-D observational network for determining urban emissions of CO2 and CH4

Transcription

1 A 3-D observational network for determining urban emissions of CO2 and CH4 Jonathan E Franklin1, Taylor S Jones1, Jia Chen2, Harrison Parker3, Jacob Hedelius3, Paul Wennberg3, Manvendra K Dubey4, Ron C Cohen5, Abhinav Guha6, Maryann Sargent1, Kenneth J Davis7, Levi Mielke8, Marc Fischer9, Steven Wofsy1 Harvard University, 2Technical University of Munich, 3California Institute of Technology, 4 Los Alamos National Laboratory, 5University of California Berkeley, 6 Bay Area Air Quality Management District, 7Pennsylvania State University, 8 University of Indianapolis, 9Lawrence Berkeley National Laboratory 1

2 Still have work to do in urban regions!!! Urban regions are responsible for majority of fossil fuel emissions Good targets for mitigation efforts Biogenic sources can not be ignored And many other questions remain Bottom-up emission maps are getting better......but Top-down observations (from ground, tower, or satellite) are still required to validate, constrain, and update emission maps

3 Fixed surface in-situ networks have multiple challenges Sensitive to daily changes in mixing layer height Sensors can be swamped by local emissions M. Sargent

4 Field-deployable ground-based remote sensors Measuring GHGs using solar absorption spectroscopy Provide column-averaged dry-air mole fractions of CO2 and CH4 retrieved using GFIT (TCCON) Less sensitive to changes in mixing layer height O2 CO2 CH4

5 Sensors allow us to quantify total emissions from a region on sunny days by measuring column averaged concentrations both upwind and downwind of a source wind wind Emission ~ Downwind Column Concentration Upwind Column Concentration

6 Side by side calibration measurements at 65m at Harvard University

7 xco2 Precision ~ 0.01% Fairly quick ( ~8 s / scan ) 1σ ~ 0.04 ppm Low-latency ( < 24 hours ) use forecast products However... xch4 Requires sunlight! 1σ ~ 0.2 ppb

8 Differential Column Measurement Across Boston & South Shore 05 March 2017 COLD sunny day with gusty NW winds Upwind sensor placed on Harvard Campus Downwind sensor placed in North Pembroke along the observing track of OCO-2 S NW tro n wi g nd CO2 measured by satellite (OCO-2) (from prior date waiting for 05 March data)

9 Carbon Dioxide ( CO2 ) Strong NW winds aloft carried air from Harvard to Pembroke in ~ 35 minutes Shape of concentration curve is same in both locations Cold day before leaves have come out Difference between the two sensors reveals an enhancement of ~0.5 ppm CO2 consistent throughout most of the day

10 Methane ( CH4 ) Again, shape of concentration curve is same in both locations Difference between the two curves reveals an enhancement of ~3 ppb CH4 consistent throughout most of the day Enhancement caused by emissions between the two locations

11 Indianapolis May 2016 Five EM27/SUN sensors were deployed in Indianapolis for ~2 weeks. Larger measurement region than Boston, but more consistent topography and wind. Five days of field measurements were obtained in addition to side by side calibration days at the start and end. Column measurements were supplemented with ground, tower, and aircraft in-situ measurements. Harvard University, Environmental Defense Fund, Los Alamos National Laboratories, Technical University of Munich, Karlsruhe Institute of Technology, Purdue University, Pennsylvania State University, University of Indianapolis, Ivy Tech Community College, NOAA

12

13

14

15 Indianapolis May 2016 PM AM XCH4 20 km 13 May of 5 days of column measurements CH4 measurements reveal presence of strong local source but also a smooth enhancement throughout the city. Almost no enhancement in CO2 during campaign significant spring uptake?

16 Atmospheric transport modeled using HYSPLIT-STILT With NAM 12 km resolution meteorology

17 Inventory from Lamb et al Preliminary results!!! (T. Jones poster) Inventory from Lamb et al (2016) & slant column footprints from HYSPLITSTILT w/ NAMS 12km Model captures overall shape of concentration curves, but is unable to capture plume of local source Not yet clear how best to characterize background

18 San Francisco Bay Area Oct/Nov week campaign working with the Bay Area Air Quality Management District to investigate CO2 and CH4 emissions from the entire SF Bay Area. Significantly larger region with more varied topography Harvard University, Bay Area Air Quality Management District, Environmental Defense Fund, Technical University of Munich, Karlsruhe Institute of Technology, California Institute of Technology, University California Berkeley, San Jose State Univerisity, Sandia National Laboratories, Lawrence Berkeley National Laboratory, NASA AJAX, GOSAT J. E. Franklin

19

20

21

22

23

24 XCO2 50 km XCH4 20 October 2016 Monitoring larger regions with significant terrain variability requires using more sensors. NW wind crossed entire SF Bay Area and drove enhancements of ~25 ppb CH4 and 3 ppm CO2

25

26 xco2

27 xch4

28 Summary Column sensors can be a powerful tool in determining urban and regional scale emissions of GHGs. We can achieve a high degree of confidence using a framework combining: A surface measurement network A set of carefully spaced column sensors A high resolution analysis framework including transport and independently determined spatial distribution of emissions Thank you! Jonathan Franklin j.franklin@g.harvard.edu