National Energy Statistics...$0.00 $0.10 $0.20 $0.30 $0.40 $0.50 $0.60 $0.70 $0.80 $0.90 $1.00 0 100...

National Energy Statistics:Opportunities and Challenges for

Food-Energy-Water (FEW) Data Integration

Eric Masanet, Ph.D.

Associate Professor

McCormick School of Engineering and Applied Science

Director, Energy and Resource Systems Analysis Laboratory (ERSAL)

Guest Faculty Researcher, Argonne National Laboratory

[email protected]

http://ersal.mccormick.northwestern.edu/

mailto:[email protected]

http://ersal.mccormick.northwestern.edu/

Agricultural inputs (fertilizers,

etc.)

Farm

operationsFreight Processing

Preparation

(cooking,

refrigeration)

Waste

managementFreight

Stages of the food life cycle:

Typical representation in national energy statistics

Data

resolution

Sector

Subsector/

mode/end use

Product

= most often = less often = rarely

Source: IEA World Energy Balances, http://www.iea.org/

http://www.iea.org/

At what level of data resolution does FEW decision science often

require?

Example of ERSAL California cap and trade modeling of the

tomato processing industry

Methods/opportunities for bridging the gap

National

energy

data

FEWS

decision

models

• Surveys

• Engineering models

• Case studies

• Statistical analysis

• Dataset integration

Source: IEA World Energy Balances, http://www.iea.org/

Some strengths:

• Availability (annual)

• Consistency (int’l standards)

• Reliability (verified)

• Fuel resolution

• Useful for macro-calibration

• Broad energy trends

Some weaknesses:

• Lack of industry resolution:

• Subsectors

• End uses/modes/products

• Non-specified

• Lack of interdependencies

• Lack of spatial resolution

http://www.iea.org/

IEA Energy Efficiency Indicators:

Tracking Sectoral Energy Progress

United States

IEA Energy Efficiency Indicators:

Tracking Sectoral Energy-Related CO2 Progress

U.S. Manufacturing Energy Consumption Survey (MECS) end use and subsector data resolution

Evolution of MECS Food Industry Data Resolution

311 Food

3112 Grain and Oilseed Milling

311221 Wet Corn Milling

31131 Sugar Manufacturing

3114Fruit and Vegetable Preserving and Specialty Food

3115 Dairy Product

3116 Animal Slaughtering and Processing

312 Beverage and Tobacco Products

3121 Beverages

3122 Tobacco

2014311 Food




3114

Fruit and Vegetable Preserving and Specialty

Foods

3115 Dairy Products



3121 Beverages

3122 Tobacco

2006

311 Food




3114 Fruit and Vegetable Preserving and Specialty Food

3115 Dairy Product



3121 Beverages

3122 Tobacco

2010

311 Food


31131 Sugar

311421 Fruit and Vegetable Canning


3121 Beverages

3122 Tobacco

2002

311 Food



1998

20 Food and Kindred Products

2011 Meat Packing Plants

2033 Canned Fruits and Vegetables

2037 Frozen Fruits and Vegetables


2051

Bread, Cake, and Related

Products

2061 Cane Sugar, Except Refining

2062 Cane Sugar Refining

2063 Beet Sugar

2075 Soybean Oil Mills

2082 Malt Beverages

21 Tobacco Products

1994

U.S. Manufacturing Energy Consumption Survey (MECS) end use and subsector data resolution

Some strengths:

• End use resolution

• Large sample set

• Useful for macro-calibration

• Broad energy trends

• Many ancillary data:

• Adoption of efficient

technologies

• Floor area

• Economic indicators

Some weaknesses:

• Fewer data at regional level

• Quadrennial

• Lack of interdependencies

• Lack of subsector resolution

2007 U.S. IO Total

Requirements

Matrix (389)

IO Analysis

Output

(purchase) from

IO sector i ($)

Input required from

IO sector 1 ($)

Input required from

IO sector n ($)

…

Environmental Coefficients

for Supply Chain Sector n

Electricity (kWh/$)

Natural gas (Th/$)

Coal (Btu/$)

CH4 (g/$)

…

and so on

X

Fuel Use and Emissions for Supply Chain Sector n

Electricity (kWh) Natural Gas (Th) Coal (Btu) And so on …

=

Producing Sector

Supply Chain Sectors

Black = Input-output model Purple = US national energy statistics

$0.00

$0.10

$0.20

$0.30

$0.40

$0.50

$0.60

$0.70

$0.80

$0.90

$1.00

0 100 200 300 400 500 600 700 800

Co

st o

f C

on

serv

ed

En

erg

y (

2004 $

/Th

-saved

)

Cumulative Savings (MTh)

Industrial Natural Gas Maximum Achievable Potential -California Cumulative through 2012 (MTh)

Friedmann, R., F. Coito, E. Worrell, L. Price, E. Masanet, and M. Rufo (2005). “California Industrial Energy Efficiency Potential.” Proceedings

of the 2005 ACEEE Summer Study on Energy Efficiency in Industry, West Point, New York, ACEEE.

Maintain

boilers

Steam system

controls

Process heater

upgrade

Eff

icie

ncy m

ea

su

re in

ve

stm

en

t co

st

= discrete efficiency technology/practice

Techno-Economic Potentials Analysis

Industrial Natural Gas Efficiency Example

2007 U.S. IO Total

Requirements

Matrix (389)

IO Analysis

Output

(purchase) from

IO sector i ($)

Input required from

IO sector 1 ($)

Input required from

IO sector n ($)

…

Environmental Coefficients

for Supply Chain Sector n

Electricity (kWh/$)

Natural gas (Th/$)

Coal (Btu/$)

CH4 (g/$)

…

and so on

X

Fuel Use and Emissions for Supply Chain Sector n

Electricity (kWh) Natural Gas (Th) Coal (Btu) And so on …

=

Fuel End Use Breakdown

Lighting (kWh) HVAC (kWh) Pumping systems (kWh) Compressed air (KWh) And so on …

Energy-efficient measure 1 Energy-efficient measure n…

Fuel use and

emissions

reduction potentials

Producing Sector

Supply Chain Sectors

Black = Input-output model Green = Techno-economic potentials modelsPurple = US national energy statistics

Results for the California Wine Sector

Source:

Masanet, E., Matthews, H.S., Carlson, D., and A. Horvath (2012). Retail Climate Change

Mitigation: Life-Cycle Emission and Energy Efficiency Labels and Standards. California

Air Resources Board, Sacramento, California.

0 20 40 60 80 100 120

Wholesale trade

Coal mining

Petroleum refineries

Fertilizer Manufacturing

Oil and gas extraction

Iron and steel mills

Truck transportation

Glass container manufacturing

Fruit farming

Wineries

GHG Emissions (g CO2e/$)

Electricity

Process CO2

CH4

N2O

HFC/PFCs

Coal

Natural Gas

Petroleum

Biomass/Waste

Top 10 contributing sectors to the GHG emissions footprint of product manufacture (MJ/$)

0 5000 10000 15000 20000 25000 30000

CH4 reduce methane leaks

Petroleum process heating

Coal Steam Systems

Reduce PFC use

Electric HVAC

Electric refrigeration

Coal Process Heating

CH4 methane capture

Natural gas HVAC

Electric lighting

Petroleum engines

Electric motors

N2O soil nutrient management

Natural gas process heat

Natural gas steam

GHG emission reduction potential (Mg CO2e/yr)

Va

lue

ch

ain

eff

icie

ncy

/ab

ate

me

nt

op

po

rtu

nit

y

Top 15 estimated supply chain efficiency and

GHG mitigation reductions by improvement

opportunity and emissions source

Characterizing Multiple Benefits of Industrial Energy Efficiency Investments:

Water Use ReductionsSteam systems are the largest onsite

consumer of fuel

Estimating Process Water Use via National Energy Statistics

Process Technology Model (Boiler Fuel Input) Nature of Annual Steam System Water Use by Sector

Equivalent to the daily residential water use of Los Angeles!

Walker, M.E., Lv, Z., and E. Masanet (2013). “Industrial Steam Systems and the Energy-Water

Nexus.” Environmental Science & Technology. 47 (22), pp 13060–13067.

Masanet, E., and M.E. Walker (2013). "Energy-Water Efficiency and U.S. Industrial

Steam." AIChE Journal. Volume 59, Number 7, pages 2268-2274. Cover article

U.S. DOE Audits: Untapped Water Savings

Improving Industrial Sector Energy Modeling via Data Mining/Matching

Data Mining/Matching Scope

• Total of 6,928 facilities are included

Additional data sources for mining/matching:

• EPA MACT boiler/process heater registry

• Regional air permit applications

• Plant registries (product data)

• ERSAL process model library

MECS/GHGRP Data Hierarchy

Data Mining/Matching Suggests Different Energy Patternsand Government Data Improvement Opportunities!

311 MECS: 64% of energy use for steam systems

311 matched: 87% of energy use for steam systems

THANK YOU!

National Energy Statistics...$0.00 $0.10 $0.20 $0.30 $0.40 $0.50 $0.60 $0.70 $0.80 $0.90 $1.00 0 100...

Documents

Transcript of National Energy Statistics...$0.00 $0.10 $0.20 $0.30 $0.40 $0.50 $0.60 $0.70 $0.80 $0.90 $1.00 0 100...