Improving the Understanding of Emissions

Transcription

1 Improving the Understanding of Emissions Gregory Frost NOAA/Earth System Research Laboratory University of Colorado/CIRES Boulder, Colorado Co- Chair, Global Emissions IniCACve

2 Outline Mo6va6on for understanding emissions Challenges with current emissions knowledge Global Emissions Ini6A6ve (GEIA) Top- down emissions approaches & case studies Summary and future direc6ons Acknowledgements Thanks to Claire Granier, PauleKe Middleton, Leonor Tarrasón, Jean- François Lamarque, Steven Smith, Terry Kea6ng, David Fahey, Megan Melamed, David Parrish, Owen Cooper, Jennifer Logan, David Stevenson, Paul Young, Cathy Liousse, Qiang Zhang, Jeff Peischl, Si- Wan Kim, Jerome Brioude, Ilana Pollack, Carsten Warneke, Gabrielle Pétron, Anna Karion, and many other colleagues who carried out the research and contributed to this presenta6on.

3 Mo?va?ons for Understanding Emissions Ac6ons and decisions about the atmosphere focus on emissions. Figure: A.R. Ravishankara Figure courtesy of A.R. Ravishankara Accurate emissions informa6on is needed for many purposes. QuanCfy and predict Understand changes Make choices Evaluate micgacon Demonstrate compliance This is the Century of Accountability. David Fahey Societal development and scien6fic innova6on result in new challenges in emissions understanding. Dynamic economies Changing demographics Evolving land use Emerging energy sources New measurements BeRer process descripcons Improved models Stakeholders and decision- makers have common requirements for emissions informa6on, but challenges with emissions informa6on persist. Transparency Consistency Accuracy Timeliness Uncertainty Complexity Development Analysis CommunicaCon G. J. Frost et al., Atmos. Environ., 2012 & 2013

4 Many Needs for Emissions Informa?on! Emissions informa?on addresses mul?ple mandates & serves many uses! Scien?fic research one of many consumers of emissions informa?on Research Forecas6ng & analysis Air quality Long- range transport Climate change Economics Emissions trading Control implementa6on Regula?on Atmospheric modeling Human exposure Permi]ng & compliance Standards akainment Public repor6ng Diplomacy Pollu6on conven6ons Data sharing Mul6na6onal agreements Assessments

5 Total mass of compound X emiked Sum up all sources S BoKom- Up Inventory Methods E X = Σ S [EF X,S " A S " (1 CE X,S )] Emissions factor = mass of compound X emiked by source S per unit ac6vity Ac?vity of source S, e.g., amount of fuel burned Effec?veness of control measures for compound X at source S Calculated for Specific region Specific 6me Also need Spa6al alloca6on Temporal varia6on Specia6on Example: On- road motor vehicles Vehicle fleet Emissions source Road type Fuel type Fuel economy Distance driven Control technology Vehicle condicon Vehicle load

6 Inventories are necessary, Connect disciplines High granularity Comprehensive view Quan6fy changes Key model inputs Predic6on Decision- making but they have many challenges Complexity Insufficient data Long, costly development cycle Diverse data providers Proprietary data Inconsistencies Uncertain6es Analysis and evalua6on Transparency Access Communica6on Educa6on

7 Challenge: Explaining Observed Composi?on Do observed changes in atmospheric composi6on result from emissions changes? Zugspitze, Jungfraujoch, Sonnblick Logan et al. (2012) Parrish et al. (2012) Cooper et al. (2012) Western US Eastern US

8 Challenge: Modeling Composi?on & Climate Models are not able to simulate observed composi6on trends and distribu6ons Emissions represent significant por6on of uncertainty in modeled composi6on and climate forcing Troposphere ozone column difference Normalized surface ozone trend Young et al. (2013) 3076 D. S. Stevenson et al.: Atmospheric C Ozone radia?ve forcing ACCMIP 8- model mean RCP8.5 T C a c Parrish et al., in review O 3 RF / mwm Stevenson et al. (2013) RCP4.5 RCP RCP Year Fig. 5. Evolution of tropospheric ozone RF (mw m 2 ),

9 Global Emissions Ini?A?ve hkp:// GEIA Mission GEIA is a global community ini6a6ve that builds bridges between environmental science and policy, by bringing together people, data, and tools to create and communicate the highest quality informa6on about emissions to stakeholders and decision- makers.

10 GEIA Vision By 2020, GEIA will be a key forum for emissions knowledge that serves stakeholders and decision- makers in a rapidly evolving global society. PromoCng broad and consistent access to emissions informacon Emissions & Ancillary Data Data Sharing Access New Emissions Challenges Informa6on about Emissions Process Understanding GEIA Network & Web Portal Science - Policy Links Analysis Projects & Collabora6ons Capacity Building Outreach Community Building the sciencfic basis for emissions data by enhancing analysis of emissions processes Strengthening the community of emissions stakeholder groups hkp://

11 GEIA Leadership Team Co- Chairs: Gregory Frost, Leonor Tarrasón Database Manager: Claire Granier Network Manager: PauleKe Middleton Interna?onal Scien?fic Connec?ons GEIA Community GEIA Scien?fic Steering CommiKee Gregory Frost Leonor Tarrasón Alexander Baklanov Beatriz Cardenas Hugo Denier van der Gon Claire Granier Alex Guenther Greet Janssens- Maenhout Johannes Kaiser Terry Kea6ng GEIA Network Zbigniew Klimont Jean- François Lamarque Catherine Liousse PauleKe Middleton Toshimasa Ohara Mar6n Schultz Ute Skiba John van Aardenne Yuxuan Wang Na6ons with GEIA member(s) SSC member(s) 1500 contacts worldwide hkp://

12 GEIA History Guiding programs Formed in 1990 under IGBP/IGAC Connec6ons developed with other IGBP ac6vi6es (ileaps, AIMES) Original goal Develop one best inventory for anthropogenic & biogenic sources: GEIA inventory Evolving goals Enhance access to available emissions data Standardize formats and documenta6on Facilitate analyses of emissions data Build emissions community Chairs T. Graedel: G. Marland: J. Olivier & D. Cunnold: A. Guenther & C. Granier: G. Frost & L. Tarrasón: present hkp://

13 New vision: Frost et al. (2013) New web site: hkp:// Improved data access/visualiza6on plaxorm Emissions data for research & assessment ac6vi6es Sessions at conferences (AGU, etc) China Emissions Working Group Interdisciplinary Biomass Burning Ini6a6ve VOC Specia6on Working Group Some Recent GEIA Ac?vi?es 2014 GEIA Conference in Boulder Community historical global emissions effort Emissions & Ancillary Data Data Sharing Access New Emissions Challenges Informa6on about Emissions Process Understanding GEIA Network & Web Portal Science - Policy Links Analysis Projects & Collabora6ons Capacity Building Outreach Community

14 ECCAD = Emissions of atmospheric Compounds & Compila?on of Ancillary Data hkp://pole- ether.fr/eccad GEIA s emissions database and visualizacon/analysis plaborm Global Inventories Regional Inventories Ancillary Datasets

15 Examples of ECCAD tools hkp://pole- ether.fr/eccad Visualiza6on of emissions maps Temporal varia6on of na6onal emissions Total emiked for different regions Ancillary data Currently under development: maps of comparison calculacons, scarer plots Limita?ons of ECCAD- 1: resolu6on, download system, data selec6on

16 ECCAD- 2 Pla]orm Under Development hkp://eccad2.sedoo.fr/interface/ Thanks to US EPA! HTAPv total NOx emissions HTAPv total NOx emissions Any lat/lon resolu6on Country- level data (summer 2014) Adapted to interoperability Detailed metadata, documenta6on Regrid to any lat/lon grid HTAPv2 currently available; other datasets to be added soon

17 China Emissions Working Group East Asian Emissions Assessment

18 16 th GEIA Conference Bridging Emissions Science and Policy June 2014 Na=onal Center for Atmospheric Research Boulder, Colorado, USA Program, registra?on, etc. available at Conference Objec?ve Explore role of emissions as crucial link between scien6fic innova6on and societal development Intended Audience Emissions informa6on developers and users Research, regulatory, policy, and assessment communi6es Boulder FlaCrons Conference LocaCon: NCAR Center Green

19 Community Historical Global Emissions ACCMIP inventory development China anthropogenic CO emissions Lamarque et al. (2010) Granier et al. (2011) Update of Granier et al. including recent inventories (in preparacon) CO$Total$global$emissions$(Tg$CO/yr)$ 850$ 800$ 750$ 700$ 650$ 600$ 550$ 500$ 450$ MACCity$ 2010 global anthropogenic Total$ CO emissions RCP8.5$ RCP6$ RCP4.5$ RCP2.6$ EDGAR5HTAP2$ PEGASOS_PBL$ PEGASOS_MFR$ ECLIPSE_CLE$ New community effort underway: See Smith presenta?on next!

20 Top- Down Emissions Evalua?ons Atmospheric observa6ons measure abundance of cons6tuent and quan6fy spa6al and temporal variability Models translate between atmospheric abundance and emission flux Quan6fy: Interannual trends Day- of- week variability Sector par66oning Total emissions Compare to bokom- up inventories Uncertain6es usually quan6fiable

21 Examples of Top- Down Emissions Evalua?ons Pollutants relevant to air quality & climate NOx, SO 2, CO, VOCs, CO 2, CH 4 Mul6ple species # source fingerprint Examine US emissions sectors: Power plants Urban areas/motor vehicles Oil/natural gas produc6on & distribu6on Examples from NOAA/CU research

22 Power Plant Emissions Trends - Aircrad Sampling Aircrad plume sampling Aircra} sampling quan6fies atmospheric NO x declines downwind of power plants Confirma6on of in- stack monitoring (CEMS) Aircrad data before & ader NOx controls Mon6cello power plant (TX), 9/16/06 Parish PP CorrelaCon plot slope fit Peischl et al. (2010) CEMS - aircrad comparison

23 Power Plant Emissions Trends Satellites SCIAMACHY tropospheric NO 2 ver=cal columns, summer 2004 mean Satellite column NO 2 retrievals map point and urban sources Satellite NO 2 column trends show impacts of NO x controls on US power plants Confirma6on of in- stack monitoring (CEMS) Kim et al. (2006) Ohio River Valley: Satellite Ohio River Valley: Inventory Northeast US: Satellite Northeast US: Inventory

24 Urban Interannual Emissions Trends South Coast Air Basin (Los Angeles) Pollack et al. (2013) Warneke et al. (2012) LAX Cal Tech Ontario 2005 Surface, airborne, & satellite observa6ons show consistency in interannual trends! Ambient NOx & VOCs decreasing for 50 yrs! Demonstrates declining motor vehicle emissions LAX Cal Tech Kim et al., in prep Ontario 2010 OMI NO2 Columns, May- Sept NO 2 ver6cal column density, molec. cm - 2

25 Urban Day- of- Week Emissions Varia?ons Weekend Weekday Surface, airborne, & satellite observa6ons show consistency in weekend effect:! Lower ambient NOx on weekends! Atmospheric changes result from lower weekend NOx emissions! Inverse modeling demonstrates which inventories capture weekend effect CalNex 2010 South Coast Air Basin BoKom- up & Posterior NOx Flux, kg/s Pollack et al. (2012) Brioude et al. (2013)

26 Tg CH 4 /yr Oil and Natural Gas Produc?on Emissions EPA GHG Inventories for NG Produc?on, Reported 2σ error: 20-30% US GHG emission inventories for natural gas produc6on revised frequently Inventories underes6mate methane leakage from natural gas produc6on Downwind Aircrad mass balance Wind emissions Wind mixing height (PBL) Upwind Hydrocarbon leak rates inferred from observa6ons in oil & gas produc6on basins 2008 Denver- Julesburg Basin, CO Pétron et al. (2012) 2012 Denver- Julesburg Basin, CO Pétron et al., in review 2012 Uintah Basin, UT Karion et al. (2013)

27 Urban CH 4 Emissions Mul?variate source appor?onment CalNex 2010 Los Angeles Basin Measured CH 4 /CO + inventory CO # Total E(CH 4 ) in LA Basin Mass balance of E(CH 4 ) # Validate landfill, dairy inventories Alkane ra6os # Par66on source contribu6ons $ Resolve top- down/bokom- up CH 4 discrepancy in LA Basin $ Raw gas leaks significant CH 4 sources (12-17%) Peischl et al. (2013)

28 Summary High quality emissions informa6on is cri6cal to understand the atmosphere and make good decisions about how to manage it. BoKom- up inventories are integral to these efforts, but there are challenges associated with these complex datasets. GEIA is helping a broad community of scien6sts, regulators, and policymakers to work together at improving and communica6ng emissions informa6on. Atmospheric observa6ons and modeling provide objec6ve approaches for improving emissions understanding. Top- down methods have been successful at quan6fying emissions across regions, between sectors, and over 6me.

29 Some Future Direc?ons Long- term trends Fine temporal scales Spa6al alloca6on Specia6on Inverse approaches Satellite data Energy produc6on Biogenic emissions Wildfires, trash burning Historic inventory system Regional working groups

30 References Electronic copies of the following are available upon request Brioude, J., et al., 2011: J. Geophys. Res., 116, D20305 Brioude, J., et al., 2012: J. Geophys. Res., 117, D05312 Brioude, J., et al., 2013: Atmos. Chem. Phys., 13, Cooper, O. R., et al., 2012: J. Geophys. Res., 117, D22307 Frost, G. J., et al., 2012: Atmos. Environ., 51, Frost, G. J., et al., 2013: Atmos. Environ., 81, Granier, C., et al., 2011: ClimaCc Change, 109, Karion, A., et al., 2013: Geophys. Res. LeR., 40, Kim, S.- W., et al., 2006: Geophys. Res. LeR., 33, L22812 Kim, S.- W., et al., 2011: Atmos. Chem. Phys., 11, Lamarque, J.- F., et al., 2010: Atmos. Chem. Phys., 10, Logan, J., et al., 2012: J. Geophys. Res., 117, D09301 Parrish, D. D., et al., 2012: Atmos. Chem. Phys., 12, Peischl, J., et al., 2010: J. Geophys. Res., 115, D16303 Peischl, J., et al., 2013: J. Geophys. Res., 118, Pétron, G., et al., J. Geophys. Res., 117, D04304 Pollack, I., et al., 2012: J. Geophys. Res., 117, D00V05 Pollack, I., et al., 2013: J. Geophys. Res., 118, Stevenson, D. S., et al., 2013: Atmos. Chem. Phys., 13, Warneke, C., et al., 2012: J. Geophys. Res., 117, D00V17 Young, P. J., et al., 2013: Atmos. Chem. Phys., 13,

31 Separa?ng Mixed Source Sectors Houston and Dallas, TexAQS 2006 Aircrad vs. Model NO 2 Kim et al. (2011) NOx avg flux (kg/s/m^2 *10-9 ) Inverse vs. Inventory E(NOx) Brioude et al. (2011) EPA NEI 3DVAR 4DVAR Houston Urban area Ship channel Aircra} measurements enable spa6al separa6on of sources! Evaluate sectoral par66oning! Observa6ons & models consistent Houston, 9/26/06 Inverse vs Inventory E(CO 2 ) Use rela6onships between tracers in inversion! Es6mate fossil fuel CO 2 emissions Brioude et al. (2012)