Greenhouse Gas Inventory and Electric Demand Predictions Mike Aucott, Ph.D. NJDEP Office of Science New Jersey Clean Air Council 2009 Annual Public Hearing Trenton, NJ April 1, 2009

GHG Emissions Estimates Developed by NJDEP based primarily on energy use data from USDOE/EIA NJDEP and EPA data also used Methods continue to be refined New NJ-specific data will become available soon and will improve the process

GHG Energy to Greenhouse Gas Conversions, NJ, 2004; based on carbon content of fuel, GWP of other gases, portion of emissions emitted in NJ, and other factors

GHG Emissions Predictions Developed with linear projections of trends from 1990 through 2004 Major uncertainties exist

2005 and 2006 Estimates Now Available Reflect minor modifications of methods for some sectors Are preliminary Show large reduction from 2005 to 2006; this is true at the national level as well

Estimated NJ GHG Emissions; Preliminary

Why the reduction from 2005 to 2006? May reflect some progress in energy efficiency and development of renewable sources, but Weather fluctuation is likely the major factor

Estimated NJ GHG Emissions; Preliminary

What about the future? Prediction is difficult Nevertheless, we must try to predict and plan NJ Energy Master Plan presents predictions for electric use

from Energy Master Plan (EMP):

Predicted BAU growth in electric use (from EMP) Overall, growth of 1.38% per year between 2007 & 2020 This rate leads to 97,800 GWh use in 2020 In peak demand, growth of 1.75% per year between 2007 and 2020

EMP identifies 4 big challenges: Growth in supply of electricity has not kept pace with growth in demand Price of energy has increased substantially recently, and has become more volatile Without action, contribution to global warming and other pollution will continue State has much less authority over supply and price than previously

EMP identifies 5 major actions to meet these challenges: Maximize energy conservation and energy efficiency Reduce peak electricity demand Strive to exceed current RPS and meet 30% of demand with renewables by 2020 Develop a 21 st century infrastructure Invest in innovative clean energy technologies and businesses

If successful, these actions will lead to major reductions in demand and increases in supply of clean and renewable electric power But, “Prediction is very difficult, especially if it's about the future.” Niels Bohr And, major systems have not been behaving in a linear manner recently

And we have a long way to go in GHG emissions reduction to meet the 2050 goal

Challenges ahead suggest it is important to: Take long-term view Expect variations from predictions Strive for broad-based, multi-faceted approach to meeting energy needs and cutting GHG emissions Maximize resiliency, redundancy, flexibility