High resolution fossil\industrial CO 2 : Historical Context Kevin Gurney Purdue University Department of Earth and Atmospheric Science Purdue Climate Change Research Center A52B: Frost & Petron presiding ……..In place of talk by Blasing and colleagues

Posters and talks 9 excellent posters yesterday (A41C-0042 to 0049) 6 talks this morning  Global  Regional: Asia, Europe  Urban: Salt Lake  Methodological: Radon/ 14 C, air quality, energy sales/consumption This session and the work in recent years heralds a renewed interest in the topic and a broadening of motivations and methods

History: evolution of estimates Motivation:  Explain observed CO 2 rise  Support climate change projections Work in the 1980s:  Keeling: (1978)  Rotty: global national inventory  Marland:  Global 0-D UN production for years  UN 5 º x 5 º for average year

Evolution of estimates continued 5º x 5º with population  and industrial concentration Marland and Rotty, 1984 using consumption

Adding more space & time Rotty: seasonal global and regional (captured ~87% of globe) Found ptp of 24% of the annual mean. Andres et al., 1996: moved to 1 º x 1 º with decadel res time series EDGAR in the late 1990s - more sectoral/fuel detail

Other disciplines Atm chemistry campaigns: Trace-P  Modeling efforts  NOx, CO, VOCs IPCC: integrated assessment - combining socioeconomics and energy systems analysis (we’ll come back to this)

We thought we were done! By the 00’s, the carbon cycle community considered the fossil CO 2 problem “solved” at least to the extent that was needed. Focus on “missing sink”, terrestrial net uptake

What have we been using? 1 degree resolution Sales, consumption at national level with pop for proxy spatial

Why is this no longer adequate? 1.Inversion moving to smaller scales driven, in part, by planned satellite CO 2 measurements (OCO) 2.There is likely bias lurking (pop not best proxy) California electricity Interstates Diurnal, seasonal cycles 3.“local” climate policy has emerged in many places: significant need for spatiotemporal information 4.inadequate for dynamic, process understanding 1. Inversions moving to smaller scales driven, in part, by planned satellite CO 2 measurements (OCO) NACP Science Implementation Strategy (Denning, editor), 2005 Fossil emissions are the dominant net source of CO 2 in North America…. State- or county-level inventories of fossil fuel emissions must be downscaled using emission models driven by statistics of power and industrial plant usage, locations, pop , weather, vehicular traffic, and other data….. The goal is to provide daily or subdiurnal gridded emissions estimates commensurate with the <10 km flux analyses

Why is this no longer adequate? 1.Inversions moving to smaller scales driven, in part, by planned satellite CO 2 measurements (OCO) 2.There is likely bias lurking (pop not best proxy) California electricity Interstates Diurnal, seasonal cycles 3.“local” climate policy has emerged in many places: significant need for spatiotemporal information 4.inadequate for dynamic, process understanding 2. There is likely bias lurking (pop not best proxy) California electricity Interstates Diurnal, seasonal cycles

Why is this no longer adequate? 1.Inversion moving to smaller scales driven, in part, by planned satellite CO 2 measurements (OCO) 2.There is likely bias lurking (pop not best proxy) California electricity Interstates Diurnal, seasonal cycles 3.“local” climate policy has emerged in many places: significant need for spatiotemporal information 4.inadequate for dynamic, process understanding 3. “local” climate policy has emerged in many places: significant need for spatiotemporal information

New approaches? Our Options: Downscale further? Better proxies? Scale with other pollutants? Energy modeling? what sources burn when, where and why????? trains, planes & automobiles Powerplants, factories Home heat, gas stations

The latest wave There is now a growing community of researchers tackling various aspects of high resolution CO 2 emissions Petron, Frost and colleagues: CEM and mobile emissions Gurney, Fischer and colleagues: 10s km and hourly Andres, Gregg: state level and monthly Hirsch: 14 C/Radon Pataki: urban Blasing, Broniak & Marland: state level/monthly Ackerman & Sundquist: point comparisons

1 st HRFF meeting Meeting at Purdue: Spring ‘07  Prioritize  Strategize  Plan proposals, collaborative work  This work can contribute to more than C science

Hestia Build a global high resolution fossil/industrial CO 2 model-data fusion system that is fully process-driven: Google Earth Emissions

Thank you