Progress in estimation of power plant emissions from satellite retrievals

Transcription

1 Progress in estimation of power plant emissions from satellite retrievals Zifeng Lu, David G. Streets Decision and Information Sciences Division, Argonne National Laboratory with Benjamin de Foy Saint Louis University Bryan N. Duncan, Nickolay A. Krotkov, Yasuko Yoshida NASA Goddard Space Flight Center Presented at AQAST 5 Meeting University of Maryland, College Park June 4-6, 013

2 Progress in the past few months The review article was accepted by Atmospheric Environment Emissions estimation from satellite retrievals: A review of current capability David G. Streets, Timothy Canty, Gregory R. Carmichael, Benjamin de Foy, Russell R. Dickerson, Bryan N. Duncan, David P. Edwards, John A. Haynes, Daven K. Henze, Marc R. Houyou, Daniel J. Jacob, Nickolay A. Krotkov, Lok N. Lamsal, Yang Liu, Zifeng Lu, Randall V. Martin, Gabriele G. Pfister, Robert W. Pinder, Ross J. Salawitch, Kevin J. Wecht We applied the knowledge gained from studies in China and India to the U.S. and analyzed the satellite NO retrievals over the U.S. power plants China and India Lu and Streets, 01; Wang et al., 01 Good agreement between NO columns and NO emissions for areas dominated by power plant emissions (i.e., high f power regions) U.S. Identified a number of power plants with NO emissions highly correlated with NO satellite observations Bryan Duncan s net presentation The response of the OMI NO column to NO emission controls on the U.S. power plants: OMI observations of interannual increase in SO emissions from Indian coal-fired power plants during

3 Background India is the nd largest SO emitting country in the world In 010: 8.8 Tg for India (Lu et al., 011) vs. 7.6 Tg for US (USEPA NEI) SO emissions from Indian coal-fired power plants increased dramatically in recent years Electricity generation and fuel consumption have doubled since 1996 No SO emission control in Indian coal-fired power plants The latitude of India is lower than US and China, so India has Small solar zenith angle; low snow cover; and strong radiative flu India is an ideal region for using satellite to observe emissions Very few studies about SO emissions estimation from satellite observations Fioletov et al. (011) first used oversampling technique to successfully quantify the relationship between OMI SO observations and SO emissions from coal-fired power plants in the eastern US 3

4 Unit-based inventory for SO emissions (005-01) Based on previous work for NO emissions from public thermal power plants Additional work Update the activity data to year 01 Modify to estimate SO emissions Include big captive coal-fired power plants Improved Indian coal-fired power plant database Lu and Streets, 01 Data source: Thermal Performance Review (005-01) CEA, Government of India 165 plants, >70 units Plant-wise information is gathered, including geographical location, capacity, boiler type, coal type, coal sulfur content, electricity generation, fuel consumption, and eact time when the unit came into operation and/or retired, etc. Power generation 61% increase during Coal consumption 65% increase during

5 SO emission trend of Indian coal-fired power plants SO emissions 6% increase during Potentially, the dramatic change in SO emissions from these large point sources should be reflected in OMI satellite observations 5

6 Processing Daily OMI SO PBL Level Data Data Source Planetary boundary layer (PBL) SO data in the OMSO Level- products Krotkov et al., 006, 008 Filters Solar zenith angle < 70 degree Radiative cloud fraction < 0. Terrain height < 000 m Cross track positions (1-based) Dynamically filter OMI anomaly piels using RA flag Remove observations higher than 5 DU to eclude cases of transient volcanic SO Additional Pacific correction on a daily basis Lee et al., JGR, 009 Applying monthly local AMF from GEOS-Chem Lee et al., JGR, 009 Local bias correction Fioletov et al., GRL, 011 Oversampling to km km grid Used in Fioletov et al. s study for the US Incorporated in this work for Indian study 6

7 Average OMI SO over India during A number of SO hot spots are observed over India SO hot spots match the locations and the amounts of SO emissions of coal-fired power plants reasonably well 3 power plant regions ~65% of the total emissions 7

8 Seasonality of OMI SO ( average) Due to frequent cloud cover and heavy monsoon rainfall, July to September is the worst period for India to observe SO from space. Similar to NO Lu and Streets, 01 For USA: (Filoetov et al., 011) 4 months 3 years = 1 month data For India: 1 months 1 year = 1 month data It is possible to generate reliable yearly OMI SO maps and monitor the interannual trend of Indian SO emissions 8

9 Increase of OMI SO over India (005 vs. 011) OMI SO 005 OMI SO 011 9

10 Yearly sum of OMI SO for all power plants regions as a function of the distance between the source and the piel center Best fits by 1-D Gaussian function Actual OMI SO measurements are used for the calculation. Error bars are the 95% CIs of the mean The sum of OMI signals over the hotspot were continuously increasing during

11 Fitting hot spots with -D Gaussian function Fioletov et al., GRL, 011 Since, the parameter α represents the total number of SO molecules near the source. i.e., if OMI SO is in molecules/km, and σ and σ y are in km, α is in molecules 11 ), ( y f a OMI SO = + = y y y y y y f σ σ µ µ ρ σ µ σ µ ρ ρ σ πσ ) )( ( ) ( ) ( ) (1 1 ep 1 1 ), ( = 1 ), ( ddy y f

12 Annual SO emissions vs. fitted α All the valid piels within a 60 km radius in a year were used for the -D Gaussian fit. Each point represents the SO emissions for a plant area in a year Power plant regions with annual SO emissions higher than 50 Gg/year produce statistically significant α values Actual OMI SO measurements are used for the fitting. Error bars are the 95% CIs of fitted α. 1

13 Interannual trend of the Σα for all power plants regions Error bars are 95% CIs From 005 to 01: SO emissions from coal-fired power plants 6% increase Total amount of SO observed by the OMI over power plant regions 63% increase 13

14 Summary Using a unit-based methodology, we estimate that the SO emissions from Indian coal-fired power plants increased by 6% during Good agreement between OMI SO observations and SO emissions is found for power plant areas with emissions higher than 50 Gg/year OMI can detect the interannual trend of SO emissions from Indian coal-fired power plants Acknowledgements NASA Air Quality Applied Sciences Team (AQAST) program Contact Thank you for your attention! Questions? Zifeng Lu zlu@anl.gov & David G. Streets dstreets@anl.gov