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Envisioning a Sustainable Maryland:  Comparing Alternative Development Scenarios Considering Energy Consumption and Water Quality. September 9, 2009. Gerrit-Jan Knaap, Executive Director and Professor National Center for Smart Growth, University of Maryland Glenn Moglen, Professor

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Envisioning a sustainable maryland

Envisioning a Sustainable Maryland: 

Comparing Alternative Development Scenarios Considering Energy Consumption and Water Quality

September 9, 2009

Gerrit-Jan Knaap, Executive Director and Professor

National Center for Smart Growth, University of Maryland

Glenn Moglen, Professor

Civil and Environmental Engineering, Virginia Tech

MatthiasRuth, Director

Center for Integrative Environmental Research, University of Maryland


Presentation outline

Presentation Outline

Project Foundations;

The Maryland Scenario Project;

Model Development;

Nutrient Loading Model;

Residential Energy Model;

Yet to do.


Project foundations

PROJECT FOUNDATIONS


Envisioning a sustainable maryland

Today’s VISION…Tomorrow’s REALITY


Baltimore convention center

Baltimore Convention Center


Compared with buildout and cog forecasts rcp results would have

Compared with Buildout and COG forecasts, RCP results would have..

  • More jobs and housing close to transit;

  • More jobs and housing inside priority funding areas;

  • Less development on green infrastructure; and

  • Less new impervious surfaces;

  • Fewer vehicle miles traveled.


The maryland scenario project

The Maryland Scenario Project


The purpose of the maryland scenario project is

The purpose of the Maryland Scenario Project is….

  • To take an informed and careful look at alternative long-term future scenarios;

  • To conduct a quantitative assessment of each scenario;

  • To identify where and how public policy decisions will increase the likelihood of more desirable scenarios;

  • (To lay the foundation for a state development plan.)


Washington post 7 5 08

Washington Post, 7/5/08


Capital diamond

Capital Diamond


Model development

Model Development


Modeling and analysis infrastructure

Modeling and Analysis Infrastructure

  • Regional econometric model

  • Regional transportation model

  • Regional land use model

  • Nutrient loading model

  • Residential energy consumption model

  • Fiscal impact model

  • Greenhouse gas model


Modeling frameworks

Modeling Frameworks

Nutrient

Loading

Model

Air Quality

Model

Indicators

Econometric

Models

Exogenous

Factors

Land Use

Model

Transportation

Model

Land Use

Policies

Energy

Consumption

Model


Top down bottom up land use models

Top Down / Bottom Up Land Use Models

State

GSP

STEMS model

National

GNP

LIFT model

UMD INFORUM

TOP DOWN

Metro

County

Regional

Hammer

Metro

County

JOBS & HH

(SMZ)

Trends from

BEA & BLS

NCSG

LEAM

Land Uses

30m grid

Land Cover

and

input data

MDP

Growth

Model

MDP

NCSG

Economy

Environment

BOTTOM UP


Envisioning a sustainable maryland

3-Level Transport Model

  • Top Level: National View

  • County/state zones; Interstate road/transit network

  • Economic Forecast model

  • FAF Commodity Flow model

  • Long Distance Person Travel model

  • Middle Level: “Regional” View

  • Sub-county/aggregated MPO zones

  • Arterial network; External Stations

  • Short Distance Person Travel model

    • Trip Generation

    • Trip Distribution

    • Mode Split

    • Assignment

  • Bottom Level: MPO View

  • MPO TAZs; Sub-arterial network

  • No statewide modeling occurs

  • MPO model data aggregation to

  • compare with middle layer Statewide model

BMC

MWCOG


Envisioning a sustainable maryland

Constructing a High Energy Price Growth Scenario


Envisioning a sustainable maryland

Difference in # of jobs in the US

Difference in # of jobs in MD


Envisioning a sustainable maryland

Difference in # of jobs by industry

in the US

Difference in # of jobs

By industry in MD


Envisioning a sustainable maryland

High Energy

In 2040

High Energy


Envisioning a sustainable maryland

High Energy

In 2040

High Energy


Congested links under alternative scenarios

Congested links under alternative scenarios

High Energy Price Business as Usual


Scenario analysis group md leam land use model

SCENARIO ANALYSIS GROUPMD-LEAM - LAND USE MODEL

LEAM LAB, University of Illinois, Urbana-Champaign


Growth 2040

Growth - 2040


Effects of transportation investments on development patterns

Effects of Transportation Investments on Development Patterns


Envisioning a sustainable maryland

Nutrient loading model

Forecast Data (housing, employment)

RESAC Land Cover

Future Land Use

Current Land Use

CBPO in GISHydro

Chesapeake Bay Program Model Loading Coefficients

Current Nutrient Loads (N, P, Sed.)

Future Nutrient Loads (N, P, Sed.)


Envisioning a sustainable maryland

What is Forecast Data?

  • 30 year (?) projections of future housing and employment

  • Four Maryland Regions: Western, Central, Southern, Eastern Shore

  • Modeling done at “block” scale (from 160 to 922 acres)


Envisioning a sustainable maryland

Converting Forecast Data into Future Land Use – Heuristic Rules

  • Rule 1: RC provides estimates of both future housing and employment. All models of future land use are executed twice with each predictor acting alone – the average is simply taken at the end

  • Rule 2:Historical changes in housing and employment from 1990 and 2000 census data are used to provide a background for quantifying magnitude of RC changes.


Envisioning a sustainable maryland

Converting Forecast Data into Future Land Use – Heuristic Rules

  • Rule 3: Increases in housing or employment will lead to decreases in forest cover and/or agricultural land use. (currently assumed in equal proportions)

  • Rule 4: Different urban land uses are added in proportion current urban land use proportions

  • Rule 5: Measures of everything (e.g. census data, current and future land use/land cover)are disjoint at the county level. Each county acts separately.


Envisioning a sustainable maryland

Land Use Distribution in Focus Counties

Allegany

Montgomery

Prince Georges

Caroline


Envisioning a sustainable maryland

Base Case

High Energy Prices

Reality Check

Percent change in nitrogen loading, Prince Georges County, current vs. various scenarios.


Land use and nutrient loading changes in pg

Land Use and Nutrient Loading changes in PG

Case 1

Case 2

Left Figure shows how agricultural land changes within PG County and Right Figure shows corresponding change in nitrogen loading

Darker shade means bigger Ag loss Green = Loading Decrease Red = Loading Increase


Envisioning a sustainable maryland

Base Case

High Energy Prices

Reality Check

Percent change in nitrogen loading, Montgomery County, current vs. various scenarios.


Envisioning a sustainable maryland

Base Case

High Energy Prices

Reality Check

Percent change in nitrogen loading, Allegany County, current vs. various scenarios.


Envisioning a sustainable maryland

Base Case

High Energy Prices

Reality Check

Percent change in nitrogen loading, Caroline County, current vs. various scenarios.


Envisioning a sustainable maryland

County-Wide Aggregate Changes in Nitrogen Loading

All values in tons/year.


Results why future loadings may be more or less than current loadings

Results: Why future loadings may be more (or less) than current loadings:

Loading Rates (lbs/acre-year)

(typical – though they do vary across the Bay watershed)

Agricultural: 14.6

Forest: 1.4

Urban: 8.9

Water: 9.8

Case #1 converts forest into urban land (e.g. Allegany)

Case #2 converts more agricultural land than forest land (e.g. Caroline)

Current

Case #1

Case #2

Future


Envisioning a sustainable maryland

Interpretation and Future Work:

  • Preliminary results show modest NET load changes

  • Preliminary results show moderate GROSS load changes (~20%, locally higher)

    • Aside: BMPs are thought to mitigate loadings by ~10 to 20%

  • Gross Load Changes are shifted in space so different watersheds may be significantly affected.

  • Sign (+/-) of loading change:

    • Agricultural to Urban: loading reduction

    • Forest to Urban: loading increase

    • Urbanization of Agricultural land as a means of load reduction?!


Residential energy model

Residential Energy Model

  • Space conditioning accounts for a significant portion of all end use energy consumed across sectors.

    • 58% of energy consumption in residential households (EIA, 1999)

    • 40% of energy consumption for commercial buildings (EIA, 1995)

    • 6% of energy consumption in industrial facilities (EIA, 2001)

    • Roughly 22% of all end-use energy consumption in the country is used for space conditioning (Amato, 2005)


Methodology

Methodology

Vintage Model

(MDP)

(EIA)


Methodology1

Methodology

Climate

(NCSD)

(UCS)

Average Household Total Energy Consumption

(by County)

Housing Mix

(County Level)

Number of Households

(County Level)


Methodology2

Methodology


Housing characteristics recs

Housing Characteristics (RECS)


Climate degree days

Climate: Degree Days

Figure from Amato et al., 2005


Envisioning a sustainable maryland

Positive relationship between degree-days and household energy consumption.

Single-family detached households consume more energy than all other housing types.

Rural areas consume less energy than other locations, all else equal.

Positive relationship between square footage and total household energy consumption.

Efficiency improvements reduce household energy demand.

Older homes consume more energy than newer homes.


Md climate divisions

MD-Climate Divisions


Md heating degree days by climate division

MD-Heating Degree Days by Climate Division


Md cooling degree days by climate division

MD-Cooling Degree Days by Climate Division


Total energy consumption

Total Energy Consumption

BTU

Base Case

High Energy Prices

Reality Check

Montgomery County, various scenarios.


Envisioning a sustainable maryland

BTU

Base Case

High Energy Prices

Reality Check

Prince Georges County, various scenarios.

Total Energy Consumption


Envisioning a sustainable maryland

BTU

Base Case

High Energy Prices

Reality Check

Allegany County,various scenarios.

Total Energy Consumption


Envisioning a sustainable maryland

BTU

Base Case

High Energy Prices

Reality Check

Caroline County, various scenarios.


Per capita energy consumption

Per Capita Energy Consumption

BTU

Base Case

High Energy Prices

Reality Check

Montgomery County, Per Capita, various scenarios.


Envisioning a sustainable maryland

BTU

Base Case

High Energy Prices

Reality Check

Allegany County, Per Capita, various scenarios.

Per capita Energy Consumption


Notes

Notes

The results are preliminary

Energy consumption are different in various scenarios because –

The number of households are different

The spatial arrangement of households are different

The climate zones they are in are different

The densities they cluster around are different (i.e. Urban vs. Rural.)

The mix of housing types (single family vs. Multifamily etc.) are different


Where do we go from here

Where do we go from here?

  • Refine both bottom up and top down land use models;

  • Integrate land use and transportation models;

  • Link land use/transportation models with Bay model;

  • Develop “what would it take” scenario;

  • Engage public in scenario evaluation;


Scenario testing

Scenario Testing

  • Business as usual

  • High Energy Price (Concentrated Growth)

  • Resource land protection

  • Transit Oriented Development

  • What would it take

  • Build Out


Thanks to our sponsors

Thanks to our sponsors

  • US EPA

  • Maryland State Highway Administration

  • Maryland Department of Transportation

  • Maryland Department of Planning

  • University of Maryland Transportation Center

  • Cafritz Foundation

  • Maryland Sea Grant Program

  • Chesapeake Bay Trust

  • Lincoln Institute of Land Policy


Envisioning a sustainable maryland

The National Center for Smart Growth

Research and Education

Suite 1112, Preinkert Field House

College Park, Maryland 20742

301.405.6788

www.smartgrowth.umd.edu

Dr. Glenn E. Moglen

Dept.of Civil and Environmental Engineering, Virginia Tech 7054 Haycock Road Falls Church, VA 22043

703.538.3786

[email protected]

Center for

Integrative Environmental Research 2101 Van Munching Hall College Park, Maryland 20742 301.405.3988 www.cier.umd.edu


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