Feasibility Study for Multi-Family Housing

Energy Benchmarking and Disclosure Program

Richmond Region Energy Alliance

Virginia Commonwealth University, Douglas L. Wilder School of Government

and Public Affairs Masters of Urban and Regional Planning

Anna Lauher Carson Lucarelli Jonathan Howard

Table of Contents

Section 1. The purpose of the feasibility study Pgs. 3-5

Section 2. Description of the energy benchmarking and disclosure alternative Pgs. 5-6

Section 3. Description of the energy assessment alternative Pg. 6

Section 4. Contents of studyPgs. 7-19

--4.1 Case studies --4.2 Literature review --4.3 Analysis of potential energy and GHG savings --4.4 Interview results --4.5 Recommendations

Appendix A. Research Methodology and Findings Pgs. 19-28

1

Project Abstract

Feasibility Study for Richmond Multi-Family Housing Energy Benchmarking and

Disclosure Program

The purpose of this study is to explore the feasibility of a hypothetical energy

performance benchmarking and disclosure program in Richmond. Energy benchmarking and

disclosure programs require large building owners to maintain public records of their buildings'

energy needs. By identifying the costs associated with heating, cooling and electricity, these

programs give apartment building owners the information needed to make smart decisions on

how to retrofit their properties to reduce their energy consumption.  Providing energy bill

information to renters also allows them to make informed property decisions, which in turn may

provide incentives for building owners to invest in energy efficiency upgrades that would reduce

their tenants' energy bills.

The methodology for this project includes case study analysis, interviews with

multifamily unit property owners and analysis of secondary data from the US Census and the

City of Richmond tax assessment records. Preliminary results suggest that a voluntary energy

benchmarking and disclosure program for multi-family housing is more favorable than a

mandatory program.  Given Richmond’s sizable multi-family housing stock, such a bill could

potentially have lasting impacts on community-wide energy consumption and GHG emissions.

2

City of Richmond Feasibility Study of Energy Benchmarking and Disclosure Program for

Multi-Family Housing

Section 1 - The purpose of the feasibility study

The Richmond Region Energy Alliance (RREA) and VCU Urban and Regional Planning

graduate students have created a feasibility study for a potential energy benchmarking and

disclosure program for multi-family housing units in Richmond. Under this program, apartment

building owners would either volunteer or be required to maintain records of energy

consumption within their units and make that information available to potential renters.

The purpose of this study is to assess the feasibility of an energy bill transparency

program targeted for low to moderate-income renters in Richmond. We are assessing two

approaches other cities have used to help provide energy bill information to renters so they can

make informed decisions on what apartment to rent and produce potential solutions to the “split

incentive” problem that traditionally limits energy efficiency programs. The two approaches are

the Benchmarking and Disclosure Ordinance and whether a building Energy Assessment.

A benchmarking and disclosure ordinance would require building owners to record their

properties’ energy use over a specified time frame and disclose the recorded energy use

information to potential tenants. A program such as this not only informs the tenants of potential

energy costs associated with a unit, it creates a spirit of friendly completion for energy efficiency

among property owners. The second approach to energy bill transparency, a building Energy

Assessment would require all multi-family rental properties have periodic building energy

assessments. The assessment would calculate the average monthly energy bill for a unit within

that building which would be shared with prospective tenants.

It is the goal of the group to identify whether or not a benchmarking and disclosure

program to provide potential tenant’s energy cost information to incorporate into rental housing

decisions, which in turn would incentivize rental property owners to invest in energy efficiency

upgrades for their rental properties. The cities that have implemented energy benchmarking and

disclosure programs have faced significant setbacks in progress due to public opposition and

legal stalling tactics. For a city like Richmond, understanding the challenges and hurdles of other

cities will be useful in identifying how to eventually pitch the idea to the lawmakers and the

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public here in the capital. Following the analysis of other cities, the plan will present potential

energy savings programs followed by policy recommendations for the City of Richmond.

The objectives of an energy benchmarking and disclosure program under an energy

benchmarking and disclosure program, apartment building owners would volunteer (or be

required) to maintain records of energy consumption within their units and make that

information available to potential renters. Create a spirit of competition among property owners

for energy efficiency upgrades and improvements. The program would decrease energy use in

Richmond City and increase energy improvement in rental units help to lower renter’s energy

costs.

The goal of this research is to identify whether energy bill transparency actually

influences renter’s decisions and the environmental impacts of energy retrofits to existing

multifamily housing units. Three cities case studies were selected, Washington D.C., Austin,

Texas and New York City, to identify the best practices and strategies of their benchmarking and

disclosure programs. Using GIS software and data from the Richmond Regional Energy Alliance

and the 2010 US Census ArcGIS maps were generated to spatially analyze the various multi-

family housing densities across the city. Bar and pie charts are also being utilized to display the

proportions of Multi-family properties and dwelling units and types, year built, building use

types (commercial, dwelling, other), and the ratio of Low Income Housing Tax Credit (LIHTC)

properties to total Multi-housing Family. Interviews were conducted over the telephone and

analyzed in terms of consistency and/or disparities.

Through initial research, it has become evident that many regions have faced significant

setbacks in progress due to public opposition and legal stalling tactics. Since Richmond does not

require rental property owners to benchmark energy usage, understanding the challenges and

hurdles of other cities will be useful in identifying how to pitch an energy benchmarking and

disclosure program to Richmond property owners. Following the literature analysis, the plan will

conclude with calculating potential energy use and greenhouse gas (GHG) emissions reductions

from energy efficiency retrofits to multi-family residential buildings in Richmond and policy

recommendations for the City of Richmond. It is of great importance to take note and apply the

best practices, challenges and obstacles faced by the cities reviewed in the case studies to

circumstances here in Richmond.

4

Building energy performance in the residential and commercial sectors has traditionally

been ignored which has created a building performance information gap. The lack of available

information on building energy performance restricts the ability of the owner, manager and

consumer to accurately quantify and compare building energy efficiency values thus limiting the

market drive to make building efficiency investments.

With energy prices and building operating costs climbing, the demand for sustainable

options increases. It is imperative to develop and implement a program that assesses or

benchmarks and discloses building energy performance. Such a program will require property

owners invest in building energy efficiency improvements that will lower a building's

environmental impact, improve the property owners bottom line as well as stimulating friendly

building efficiency competition among peers. Two such programs are Energy Benchmarking and

Disclosure and the Energy Assessment alternative.

-http://www.buildingrating.org/content/benchmarking-understanding-building-performance

Section 2 - Description of the energy benchmarking and disclosure alternative

A building energy benchmarking and disclosure program is a process that involves

gathering a buildings energy consumption data, measuring and rating it’s consumption by

comparing it to a standard benchmark. The resulting report determines the buildings energy

efficiency rating based on the set benchmark standard. In order to understand how each building

is currently performing relative to other building with similar operating characteristics, it is

imperative to establish a building energy use benchmark first. This process requires a sample of

property owners and managers to collect their building’s energy use data, then that data is used

to calculate the energy consumed per square foot, also known as energy use intensity (EUI).  The

EUI is used to establish the benchmark baseline.  In the case of Benchmarking would utilize a

web-based program like Energy Star Portfolio Manager for building data entry, management and

analysis. Energy Star calculates building energy consumption and assigns the building an energy

efficiency score.

Users input basic building information, such as square footage, number of occupants, as

well as 12 months of total energy data. This information is analyzed based on weather conditions

and compared to buildings with similar operating characteristics from the CBECS database. The

5

program calculates a rating of 1 to 100 based on the building source EUI;. This score represents

the buildings performance comparable to other buildings.

For example, a score of 67 means the building is performing better than 67% of all

similar buildings nationwide. A rating of 50 is average, while 75 earns the building an Energy

Star certification label for that year. This system compares all buildings on one scale and allows

for tracking throughout the lifetime of the facility.

http://www.buildingrating.org/content/benchmarking-understanding-building-performance

Section 3 - Description of the energy assessment alternative

Energy assessment and disclosure “refers to the practice of evaluating the relative energy

efficiency of a home or building and making this information known to consumers. The building

energy assessment calculates the average monthly energy bill for the building, home or a unit

within a building. The mechanism aims to raise consumer awareness about energy performance

and encourage building energy improvements through greater market transparency.”[1]

Rating structural energy consumptions patterns and energy efficiency is a complex

processes that involves the physical building energy efficiency assessment which produces a

score that is used to calculate consumption patterned based on local climate and occupancy.

There are multiple ways to assess building energy efficiency.  An asset rating projects energy

efficiency of a building and requires an energy use simulation based on architectural and

building system characteristics.  A second ratings method, operational rating determines relative

energy efficiency by comparing real utility data of building energy consumption to energy use of

similar buildings.

http://www.buildingrating.org/content/rating-disclosure

6

Section 4.1 – Case Studies

Washington D.C.

In 2008, under the recommendation of the director of District Department of the

Environment (DDOE), D.C. Council passed the Clean and Affordable Energy Act (CEAE)[2],

which among other things required building owners to disclose their annual energy usage to the

marketplace using Energy Star Portfolio Manager Software starting Spring 2013. Information on

each building is kept as public record and includes all commercial and multifamily units with

floor space greater than 100,000 Sq. Ft. Starting in April of 2014; the minimum requirement will

drop down to 50,000 Sq. Ft. The purpose of the bill is to not only identifying buildings that are

using more energy than necessary, but also to establish measurable goals for energy use

reduction. The bill is also beneficial for prospective tenants wishing to understand more about

the energy demands of the apartment they are interested in. Buildings that do not comply are

fined $100/day for late data.

In efforts to further reduce the energy needs of federal government buildings, the act also

requires that all government buildings with square footage of 10,000 or greater to benchmark

their energy and water usage. In a recent article out of the National Journal, Senator Al Franken

defends such bills by adding "The federal government is the nation's largest consumer of energy.

Taxpayers are paying for all of that energy. We owe it to them to make sure our buildings save

as much energy as possible."[3] From the same article, D.C. Department of the Environment,

Marshall Duer-Balkind adds that these measures help target buildings in need of “work”.

As an incentive to building owners, the District of Columbia Sustainable Energy Utility

(DCSEU) has constructed an elaborate “Business Energy Rebate” program[4]; which offers

rebates on projects that involve “facility improvements result[ing] in a permanent reduction in

kWh and/or natural gas (McF) energy usage.” The Department of the Environment has also

established online databases guiding individuals of large building subject to this law which

property owns can access to determine exactly what information they need to report.

There are many opponents to the bills, and some reports even indicate that these

benchmarking tactics not only stigmatize building owners, but also promise no guarantee of

actual savings[5]. While its still too early to determine whether or not such policies influence

renter decisions, there are localities in the United States where such programs are paying off. Out

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on the west coast however Seattle[6] is reporting a high rate of compliance with their program; it is

noteworthy to mention that Seattle disclosed records to tenants, financial institutions and buyers.

DC has experienced a high success rate too, and the EPA for the compliance and contributions

towards energy reduction has awarded several buildings[7]. The policy has also been successful in

identifying the districts “worst offenders” and has shed light on how the Government is also a

huge consumer of energy as well as being helpful in creating a new market of jobs for planners.

New York City

New York City has not only envisioned a healthier future by reducing carbon emissions,

but they also see it as a wise investment because “buildings account for a staggering 80% of the

city’s carbon emissions and $15 billion in energy costs.”[8] Since 2007, New York City has taken

positive strides towards addressing Mayor’s Bloomberg’s PlaNYC vision statement in order “to

prepare the city for one million more residents, strengthen our economy, combat climate change,

and enhance the quality of life for all New Yorkers.”[9] The City has published numerous updates

to existing legislation and progress reports to ensure proper implementation of PlaNYC.

The major hurdle in 2011 was to overcome the “split incentive problem.” This was

solved by a work group of private interests appointed by the Mayor’s office to change the energy

cost relationship between owner and tenant by agreeing, “to share costs of capital

improvements.” The solution proposed was the “Energy-Aligned Lease” that includes a 20%

performance buffer that protects tenants and owners from potential loss due to under-performing

energy retrofits.[10] The lease language is simple and can be standardized to fit a wide array of

existing leasing and commercial contracts.

The concept is further explained in a 2011 press release from the Mayor’s office:

“The lease counts savings over the length of a projected payback period, instead of the useful life

of the improvements, shortening the amount of time it takes for the owner to recoup the money

from savings, thus making it more likely the owner and tenant will make capital

improvements.”[11] Therefore, the lease incentivizes the owner and tenant by realizing potential

energy cost savings and protecting them from potential cost-benefit loss simultaneously.

With the split incentive problem solved, the city can focus on further expanding annual

benchmarking and disclosure compliance in New York City Local Law 84. Passed in August

2012, law 84 requires “all City-owned buildings larger than 10,000 square feet … and private

8

buildings larger than 50,000 square feet, or lots with groups of buildings that are collectively

larger than 100,000 square feet” to annually benchmark and disclose reports online at

www.nyc.gov/ll84data.[12] The buildings are typically rated according to Energy Star Scores, but

other energy parameter data is available online as well. In 2011, the average median score of

energy star scores of buildings in NYC was 64 whereas a score of 75 or above qualifies them for

Energy Star certification from the EPA.

Austin, Texas

In 2007, Austin Mayor, Will Wynn released an updated Climate Protection Plan that

identified building energy efficiency a top priority.  Austin buildings used 70% of the city’s

energy use.  Promoting energy conservation and efficiency was the Climate Protection Plan’s top

priority.  In 2011 the city of Austin Texas expanded the Climate Protection plan to include an

energy conservation audit and disclosure (ECAD) ordinance, as means to achieve 700 MW in

savings through energy efficiency and conservation by 2020.  Eligible sectors for the ECAD

ordinance included commercial and multi-family properties.[1]

The ECAD Ordinance requires multi-family properties with five or more units and that

receives electricity from Austin Energy Utility to conduct an energy audit if the multifamily

property is at least ten years old and there after every subsequent ten years.  Owners of the multi-

family facilities must publicly post the energy audit and provide the energy audit to prospective

tenants.[2]

A multi-family property is exempt from an energy audit if the property is less than 10

years old by June 1, 2011, the owner has completed comprehensive duct remediation work or the

owner has replaced air conditioning equipment for all units through the Austin Energy rebate

offering within 10 years.

Energy use is calculated based on the fuel type, either all electric or gas and electric and

the energy code, no national code – prior to 1985, model energy code – 1985 – 2001 and

international energy conservation code 2002 to present.[3]  Multi-family properties are considered

high-energy use is they use more than 150% of the average energy of other multi-family

properties in the Austin Energy service area.  The ECAD requires high-energy use multi-family

properties to reduce energy use by 20%.  To offset the cost of energy saving improvements the

city of Austin Energy provides incentives for high energy-use properties.[4]

9

The city of Austin connected with Austin Energy Utility, the community owned electric

company to provide the residence of Austin energy strategies and cost saving programs to reduce

and conserve the use of energy throughout the city.  While Austin Energy Utility strives to

improve its carbon footprint by increasing its energy supply from renewable resources to 35%, it

also offers rebate programs both for residential and commercial customers to help pay for

efficiency improvements.  The benchmarking program and standards used for the multi-family

property audit are based on the ECAD ordinance and non-compliance is a class C misdemeanor.[5]

Owner’s benefit from the cost saving benefits of improvements made to multi-family

properties.  Costs saving benefits include lower operating costs, decreased turnover rates,

increased occupancy rates, increases in the market values of their communities and rebates up to

$200,000.00.  Multi-family residents see benefits that range from utility savings from 10%-40%,

improved air quality and a higher level of comfort.[6] The ECAD ordinance was smoothly initiated

and implemented has lowered Austin, TX energy consumption and energy costs to multi-family

renters.  Such an ordinance provides benefits to the community as a whole.

[1] http://www.iscvt.org/resources/documents/austin_energy_disclosure.pdf

[2] ORDINANCE NO. 20110421-002 http://www.austinenergy.com/about%20us/environmental%20initiatives/

ordinance/ordinance.pdf[3] Energy Conservation Audit and Disclosure (ECAD) Ordinance for Multifamily Properties

http://www.austinenergy.com/about%20us/environmental%20initiatives/ordinance/multifamily.htm[4] Case Study: Austin, Texas Using Energy Information Disclosure to Promote Retrofitting

http://www.iscvt.org/resources/documents/austin_energy_disclosure.pdf[5] Energy Conservation Audit and Disclosure (ECAD) Ordinance for Multifamily Properties

http://www.austinenergy.com/about%20us/environmental%20initiatives/ordinance/multifamily.htm[6]Power Saver™ Program Multifamily Rebates

http://www.austinenergy.com/energy%20efficiency/programs/rebates/commercial/Multi-Family

%20Properties/index.htm

10

Austin Energy Multi-Family Disclosure Report (2 pages)

11

h

ttp://www.austinenergy.com/About%20Us/Environmental%20Initiatives/ordinance/

ecadRules.pdf

12

Case Studies Summary Table:

Program Element Austin New York Washington, DC

Year initiated: 2011 2012 2008

Sponsor: City Council of the City

of Austin, TX

PlanNYC-Office of the Mayor of New York

City

District Department of the

Environment (DDOE)

Stated goals: June 1, 2012: Buildings

75,000 SF and greater

June 1, 2013: Buildings

30,000 SF to 69,999 SF

June 1, 2014: Buildings

10,000 SF to 29,000 SF

Reduce greenhouse gas emissions by more

than 30%. Build 1 million new dwelling units.

Clean and Smart Water initiative.

Achieve

75 points on the EPA

national energy

performance scale

Requirements: Audits every 10 years Benchmarking

NYC Energy Conservation Code

Energy Audits & Retro-commissioning

Lighting Upgrades & Sub-metering

Outreach & Training

Annual benchmarking

Eligible sectors: Commercial and multi-

family

Municipal, multi-family and commercial Municipal, commercial

and multi-family

Exceptions: Buildings less than 10

years old or retrofitted

within last 10 years

Privately-owned properties with indiv.

buildings less than 50,000 sq. ft. With multiple

buildings (ex. hospital) less than 100,000 sq. ft.

Privately-owned

properties

Utility

participation:

Austin Electric

Benchmarking or

audit software:

Energy Star Portfolio

Manager

Energy Star Portfolio Manager Energy Star Portfolio

Manager

Cost to building

owners:

$200.00 - $300.00 N/A Free

Disclosure

requirement:

Results displayed publicly

on site

Results are published on a publicly available

online database

Results are published on a

publicly available online

database

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Section 4.2 - Literature review

Benchmarking is a tool that has widespread benefits and is aimed towards energy bill

transparency. Research on cities that partake in this approach revealed several commonalities.

Primarily, that the implementation must remain rigid, with a new benchmark standard every year

(or as to be determined) and penalties for those who do not comply. This not only increases the

atmosphere for competition but also narrows the gap between those measured, and those who are

not. Second, that there needs to be consumer education, which not only streamlines the process,

but keeps building owners up to date on how to effectively benchmark their data.

Many programs are still in their developing stages, and as a result, information on how

these bills influence renter decisions is scarce. Research and interviews revealed that skepticism

among the public is present, but in low doses. The trend however, seems to be that energy bill

transparency has a stronger influence on building owners to retrofit, vice tenants. Renters

instead, are more likely to perform small-scale retrofits such as compact fluorescents (CFL’s)

and turning back the thermostat. The policy creates a competitive atmosphere, that forces

building owners to become more energy efficient, or risk being underutilized due to exorbitant

energy costs.

It can be said then, that this policy approach is in fact a viable measure for curbing GHG

emissions and reducing building energy demand (Santamouris). One could even argue that the

up tick in rooftop greening, a widely accepted tactic for reducing building energy demands, has

surged in recent years thanks to benchmarking and disclosure policies; over 5,500,000 added

acres between 2011 and 2012, an increase from the previous year by 24% (www.greenroofs.org).

The practice of greening rooftops has been shown to not only mitigate the urban heat island

effect, but also reduce cooling energy demand (Santamouris).

The case studies have demonstrated that in order for these policies to be effective, there

needs to be a streamlined process, coupled with incentives, that helps pave the way for change.

These policies must also be strictly enforced, and evaluated on an annual basis for efficacy. Most

importantly, they must be offered in tandem with incentives; on the state, local and federal

government level. These incentives can come from TIF (tax increment financing), carbon/fossil

fuels tax, or in some cases, municipal bonds. At any rate, the community should participate to

identifying which measure works best.

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Section 4.3 - Analysis of potential energy and GHG savings

The methodology for calculating per unit energy consumption and GHG emissions is

adapted from Pitt (2012) and is explained in detail in Appendix A.  About three quarters of

Richmond’s housing stock was built before 1940, which is problematic because they are also the

most inefficient due to the relatively higher per unit energy consumption shown in figure A-1 in

Appendix A. Figure A-1 also shows that 1941-1980 buildings are only slightly more efficient

than Pre-1940 buildings. As to be expected, the 1981 and newer multi-family housing stock are

the most efficient due to a number of factors like: type of building materials, building codes, and

age itself.

Multi-family housing retrofits have the potential to be an important component of

comprehensive sustainability or climate action plans. Depending on the extent of market

penetration, retrofits to multi-family housing in the City of Richmond can reduce energy

consumption by over 12% and GHG emissions by almost 10%. It is instructive to look at the

adoption scenarios in Figure A-4 to determine savings.  In the 10% adoption scenario, savings

would be relatively minimal. For Pre-1980 buildings, about 31 billion BTU would be saved

annually. These savings represent only 1.3% of multifamily energy consumption. According to

most recent census, Richmond multi-family housing is comprised of nearly 70% Gas and 30%

Electric as main heating source. Greenhouse Gas coefficients for Natural Gas and Electricity

were used to convert from energy use (million Btu) to GHG emissions (Metric Tonnes of CO2

equivalent)

In the 10% scenario, GHG emissions would be reduced by 2,557 MT CO2-e, or 1%. If

half of all multifamily units were retrofit (50% scenario), the region would achieve energy

consumption savings of 155 billion Btu (6.4%), and GHG emission reductions of 12,785 MT

CO2-e (5.3%). While the total savings seem minimal, the energy savings would be equivalent to

installing 8,258 homes in Richmond with a 4 KW solar PV system. A more detailed analysis of

energy consumption and GHG emissions of Richmond’s multi-family housing stock is explained

in Appendix A. Age of buildings continues to be Richmond’s biggest roadblocks because older

buildings are generally more expensive to retrofit. However, this paper proposes some strategies

in the recommendation section that will help circumvent this problem.

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Section 4.4 - Interview Results

Another important element of the methodology was a series of interviews with multi-

family property owners in and around the Richmond Metropolitan. These interviews, like the

case studies and literature reviews, revealed striking similarities. Namely, that property

managers/owners in Richmond are not receptive to a compulsory benchmarking disclosure

program.

The interviews provided this study with important information on the attitudes of

prominent property owners/managers in the metropolitan. The business owners indicated that a

compulsory program, as seen in Washington D.C. and New York City, was perceived as invasive

and redolent of stricter government oversight.

The interviews were useful because the vast majority of respondents were in favor of a

voluntary program and even hinted that more efficient buildings could be rented for higher rates.

Many property owners were in the process of taking steps to retrofit buildings to make them

more energy efficient and since all were individually metered, this would give, in theory, owners

a greater incentive to comply, given the reductions that could result from retrofits.

Most notable of the interviews was the in-depth response from Miller & Associates

properties that consist of mostly middle-income workforce housing. Tenants must make $25k

annual income to sign a lease. This is significant, because the responses show that middle and

higher income tenants are uninterested in their energy bill. Mr. Miller claims that only 20% of

his tenants even inquire about energy usage and costs. Miller & Associates strongly advocate the

use of energy upgrades as a marketing technique. The marketing of green energy bonuses may

create a false sense of accomplishment among tenants rendering them disinterested in energy

consumption and costs.

Mr. Miller, a private sector advocate that prefers no government intervention, but he does

support tax credits and other incentives for energy upgrades. Mr. Miller believes that the passage

of energy benchmarking and disclosure ordinances would be counter-productive in Richmond

because tenants are not concerned with energy bill transparency. In addition, Mr. Miller believes

that the bureaucracy that would enforce the ordinances would cost more to the taxpayer than

potential energy cost savings.

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One of Richmond’s most difficult challenges towards reducing energy consumption and

lowering GHG emissions is the age of the multi-family buildings. Older buildings are generally

more expensive to retrofit, but as one of the property owners (Mr. Miller) we interviewed uses a

combined strategy of: 1) using historic tax credits to renovate old and historically significant

buildings into multi-family residential, mixed-use or office space and 2) using the historic value

and aesthetics as a marketing tool, which has so far been hugely successful for Miller and

Associates and others in the industry

Section 4.5 – Recommendations

In order for Richmond, Virginia to achieve greater reduction of energy costs for multi-

family rental properties, lower green house gas emissions, raise consumer awareness about

multi-family rental property energy use and multi-family rental property energy efficiency

improvements it is recommended a voluntary energy benchmarking and disclosure program be

adopted. Initially the voluntary benchmarking and disclosure program will target multi-family

buildings built prior to 1980 with electricity as the primarily energy source. Based on the GHG

emissions calculations, electric sourced multi-family rental properties build prior to 1980 are the

least efficient as they rely on coal generated electricity and coal powered energy plants are

extremely inefficient.

Reducing energy waste of multi-family rental properties will in turn reduce GHG

emissions, as the properties will require less electricity. A properties energy use will either be

rated through Energy Star Portfolio Manager or directly through RREA. The building will be

publicly labeled with its energy efficiency score, thus creating friendly energy efficiency

competition among multi-family property owners while building energy efficiency awareness of

consumers. It is still to be determined if tax credits, grant or rebates will be available to finance

or assist in covering upfront program costs.

Richmond’s voluntary energy benchmarking and disclosure program will utilize the free

web-based Energy Star Portfolio Manager, a data management and analysis program. Energy

Star Portfolio Manager is an international energy efficiency standard that originated in the

United States of America. Users enter basic building information and past energy use data into

Energy Star and the program will a rate the properties based on a comparison to similar

properties and local weather conditions.

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Energy Star will calculate and assign the buildings Energy Use Intensity (EUI) rating 1-

100. An EUI rating is a properties energy use performance comparable to other similar U.S.

buildings. An EUI of 67 means the building is performing better than 67% of all similar

buildings nationwide. An EUI rating of 50 is average, while an EUI rating 75 or higher earns the

Energy Star certification label for that year. Energy Star Portfolio Manager allows a buildings

energy performance be tracked throughout the lifetime of the facility.

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Appendix A. Quantitative Methodology and FindingsA.1. Methodology: Study Area

The Census-defined Richmond MSA includes 20 jurisdictions and is geographically

expansive. Instead of using MSA boundaries, the study area was limited to the independent

Richmond City boundary.

A.2 Methodology: Spatial Analysis of Richmond Multifamily Housing

Housing data supplied by RREA was used to identify certain study characteristics, such

as unit size, location and age of buildings to allow us to map Richmond’s multi-family housing.

Figure A-1shows the distribution of multifamily housing by age, which indicates that about 92%

of all buildings were built in 1980 or before. The next step was to organize the data in a way that

it could be represented on a map. The data needed to be merged with City of Richmond GIS

Data in order to assign the geocode attributes. However, there were some conflicts when merging

the two databases and duplicate addresses needed to be removed from the dataset. Due to the

limitations of scope of the study

and the conflicts between the

RREA and Richmond GIS

databases, the spatial location

of each dot on the maps do not

100% accurately represent each

address point, yet they do

accurately represent the spatial

distribution of multifamily

housing building locations by

unit size and age.

19

Maps A-1 and A-2: Distribution of Housing Stock by Unit Count

20

Maps A-3 and A-4: Distribution of Housing Stock by Age

21

A.3. Methodology: Multifamily Housing Energy Consumption

The methodology for determining baseline multifamily housing average annual energy

consumption was adapted from Pitt (2012).1 Data was gathered from the U.S. Energy

Information Administration’s (EIA) 2009 Residential Energy Consumption Survey (RECS). The

2009 RECS collected data from 12,083 households using a sample designed to represent 113.6

million U.S. households.2 This study utilized the end-use energy consumption data from Public

Use microdata File 11, which divides the energy consumption from each household in the survey

into the categories of space heating, cooling, water heating, refrigerators, and other appliances /

lighting. The data also provides the average annual heating-degree days (HDD) and cooling

degree days (CDD) associated with each response’s specific location. Each RECS response in

the micro-data includes a “sample weight” value that identifies the number of similar units (same

region, age, size, etc.) that it represents among the greater population of U.S. households. This

microdata includes 669 responses from the Census-defined South Atlantic region (includes VA),

of which 149 represent multi-family housing units. These responses were isolated and then

sorted by their building size categories: units in buildings with 2-4 units and those in buildings

with five or more units.

The analysis of energy consumption from those multi-family units in the South Atlantic

region focused on the following energy end-use categories: space heating, cooling, and water

heating. These are the end uses most affected by common energy efficiency retrofit measures.3

The end-use energy consumption from each of the 149 isolated RECS responses was multiplied

by their respective sample weight values, thus yielding total energy consumption in each end use

for all similar housing units in the U.S. These totals were added together and then divided by the

total of their sample weights, generating an estimate of the average annual energy consumption

by end use for each multifamily housing type. Further calculations from the micro-data generated

the average space heating energy consumption by heating degree-day (HDD), and average

cooling energy consumption by cooling degree-day (CDD).

1 Pitt, D., 2012. Evaluating the greenhouse gas reduction benefits of compact housing development. Journal of environmental planning and management.2The U.S. Energy Information Administration (EIA), “About the RECS”. http://www.eia.gov/consumption/residential/about.cfm.3 Measures implemented by RREA and identified in the study “Recognizing the Benefits of Energy Efficiency in

Multifamily Underwriting.”

22

The next critical step was to multiply this energy consumption per HDD/CDD from the

South Atlantic region times the average annual HDD4 and CDD5 values from the Richmond area,

thus generating estimated annual energy consumption per end use for each type of multi-family

unit. This procedure using the HDD and CDD values allows the resulting estimated annual

energy consumption per housing unit type to more accurately reflect conditions in the Richmond

area rather than the broader South Atlantic region, most of which lies south of Richmond and

thus has lower heating demand and higher cooling demand. Using this procedure we estimate

that the average annual energy consumption for space heating, cooling, water heating,

refrigerators, and other appliances / lighting for multi-family units in the Richmond region is

51.66 million Btu (MBtu) per year

for units in buildings with 2-4 units

and 43.17 million Btu (MBtu) per

year for units in buildings with five

or more units, as shown in the first

column of Figure A-2. Units were

also broken down into building age

groups to better illustrate the

distribution of energy consumption.

According to data supplied

by RREA, there are 48,830 multifamily units with the Richmond City limits. Of these, 8,581 are

in buildings with 2-4 units and 40,223 are in buildings with 5+ units. Multiplying the average

annual energy consumption per unit type times the number of those units in the region results in

an estimated total space energy consumption of 2.43 trillion Btu for the region. As shown in

Figure A-3 identifies the types of units built in each era and the majority (80%) of energy is

consumed by 1940 buildings and older.

A.4. Methodology: Multifamily Housing GHG Emissions from Energy Consumption

4 National Oceanic and Atmospheric Administration, 2008. Normal monthly heating degree days (base 65). National Climate Data Center. http://www.ncdc.noaa.gov/oa/climate/online/ccd/nrmhdd.html

5 National Oceanic and Atmospheric Administration, 2008. Normal monthly cooling degree days (base 65). National Climate Data Center. http://www.ncdc.noaa.gov/oa/climate/online/ccd/nrmcdd.html

23

The next step in the analysis was to derive GHG emission estimates from end use energy

consumption estimates. Again, methodology for this aspect of the analysis was developed from

the work of Pitt (2012).6 First was to determine the type and distribution of energy used in the

region’s multifamily housing for each end use. For cooling, this is straight forward, as all air

conditioners are powered by electricity. For space heating and water heating, assumptions must

be made from broader regional data. Again, data from ACS 2010 5-years estimates were used.

ACS file DP04 (available for each jurisdiction) contains information regarding home heating fuel

for occupied housing units. Unfortunately, the Census Bureau does not cross tabulate heating

fuel data by housing type. Therefore, heating fuel distribution across all housing types must be

applied to multifamily housing. It was found that the large majority of housing units (over 77%)

used either electricity (31%) or natural gas (69%) for heat. As fuel usage in the remaining ~23%

of homes was distributed over six

additional fuel types, this analysis

distributes their share proportionally

between the more commonly used

heating fuels. As a result, it was

estimated that 31% of multifamily

housing units in the City of

Richmond use electricity as a

heating fuel and 70% use natural

gas. These same percentages were

assumed for water heating.

Next, carbon coefficients for each fuel type were determined. The EIA provides

emissions factors by fuel type.7 On average, combustion of natural gas emits .053 metric tons

(MT) of CO2 per MBtu of energy generated. Determining a carbon coefficient for electricity is

more complicated, as emissions from electricity generation varies significantly by region.

According to the Environmental Protection Agency (EPA),8 electric power generation in the

6 Pitt, D., 2012.7 US Department of Energy, 2012. Voluntary reporting of greenhouse gasses program: fuel emission coefficients.

Energy Information Administration. http://www.eia.gov/oiaf/1605/coefficients.html#tbl18 US Environmental Protection Agency , 2012. eGRID2012 version 1.0 year 2009 GHG annual output emission

rates. http://www.epa.gov/cleanenergy/energy-resources/egrid/index.html

24

SERC Virginia/Carolina region, which encompasses South Carolina, North Carolina, and non-

Appalachian Virginia, emits 1,041.73lb of carbon dioxide equivalent (CO2-e) per MWh of

electricity generated. This converts to a carbon coefficient of 0.138 MT CO2-e/MBtu. In order to

estimate regional GHG emissions, energy consumption totals for each end use were multiplied

by the appropriate carbon coefficient. For example, regional energy consumption for cooling was

multiplied by .138 to determine how many metric tons of C02-e are emitted by air conditioning

use in multifamily housing units. Finally, emissions estimates were totaled across end uses.

In the City of Richmond, 248,576 MT CO2-e are

emitted each year from energy used in multi-family

housing. As might be inferred from the regional energy

use estimates in Figure A-3, the majority of GHG

emissions result from buildings made in 1940 and

before. However, there is not a directly proportional

relationship between energy use and emissions. Because

electric heat relies entirely on energy from a relatively

“dirtier” source than natural gas, the proportion of total

GHG emissions is slightly higher for electric heated

units than the proportion of energy consumption (30%

electric, 70% gas) as shown in Figure A-4.

It is particularly instructive to look at GHG emissions by building size and age. Units in

buildings with electric heat emit about two metric tons more CO2 equivalent per year than

respective averages of natural gas buildings. Also, units in buildings with 2-4 units emit almost 1

MT of GHG more than units in buildings with 5+ units. The starkest contrast is in emissions

from units heated with natural gas and those heated with electricity in 2-4 units, Pre-1940

buildings at a difference of nearly 3 MT of CO2 equivalent per year. These numbers are shown in

25

Table A-1.

Table A-1: Per-Unit GHG Emissions (in Metric Tons) by Building Size and Age

Annual Per-Unit Baseline

GHGs- Gas

Unit Size All Units Avg. 1800s - 1940 1941 - 1980 1981 - present

2-4 Unit 4.7 5.12 4.72 4.5

5+ Unit 3.84 4.32 3.94 3.68

Annual Per-Unit Baseline

GHGs-Electric

Unit Size All Units Avg. 1800s - 1940 1941 - 1980 1981 - present

2-4 Unit 7.13 8.07 7.37 6.4

5+ Unit 5.96 6.92 6.26 5.53

A.4. Methodology: Energy Consumption and GHG Emission Savings from Retrofits

Energy savings estimates were made by determining the amount of energy that could be

saved, in percentage terms, from a multi-family energy efficiency retrofit, and applying those

savings to the per-unit energy consumption figures estimated above. As described in Section 5.3,

we assumed retrofit savings for 20% of heating, 15% for cooling and 20% for water heating, but

only for units built 1980 and before. Pre-1980 buildings were selected because of the disparities

in energy use, meaning that retrofits applied to post-1980 buildings would not be as beneficial.

Also as indicated in Section 5.3, about 85% of Richmond multi-family housing stock is

comprised of pre-1980 buildings. The retrofit savings figures were derived from a 2012 study by

the Deutsche Bank Americas Foundation (DBAS) and Living Cities (LC) on multi-family

retrofits in New York City.9 For air conditioning we used a study by CNT Energy and the

American Council for an Energy Efficient Economy (ACEEE),10 which found average electricity

savings of 15.79%.

We then estimated total energy consumption savings across these end uses based on three

scenarios for the adoption of multi-family energy-efficiency retrofits for all pre-1980 buildings in

9 Deutsche Bank Americas Foundation and Living Cities, 2012. 10 CNTenergy and American Council for an Energy-Efficient Economy, 2012. Emerging as partners in energy

efficiency: multifamily housing and utilities. http://www.cnt.org/repository/CNT_EngagingUtilities_012512.pdf

26

the region: 10% adoption (4,170 units); 30% adoption (12,510 units); and 50% adoption (20,850

units). For each scenario, post-retrofit regional energy consumption for each building unit type

and age category was calculated. These post-retrofit figures were then subtracted from baseline

energy consumption levels as outlined in Table A-1. Finally, GHG emission reduction scenarios

were calculated in the same manner. Post-retrofit emissions totals were subtracted from the

baseline levels. While it would seem, for example, that a 10% reduction in energy consumption

would result in a 10% reduction in GHG emission, this is not the case. This is because electricity

generation emission rates used to develop a carbon footprint or emission inventory correspond to

a region’s overall generation portfolio. However, non-baseload emission rates should be used to

estimate GHG emissions reductions from reductions in electricity use.11 Hypothetical reductions

in electricity use would come from non-baseload power generation facilities, which have higher

GHG emission rates. Earlier, a carbon coefficient of 0.138 MT CO2-e/MBtu was used for general

electricity generation (baseload and non-baseload). Non-baseload power generated in the SERC

Virginia/Carolina region has a higher carbon coefficient of 0.224 MT CO2-e/MBtu. This higher

coefficient results in GHG emission percent savings that are not directly proportional to percent

reduction in energy consumption. For example, in Richmond, 7.25 MBtu of electricity

generation would result in 1 MT of GHG emissions. However, reducing non-baseload generation

by 7.25 MBtu would result in a 1.62 MT reduction of GHG emissions.

A.5. Findings: Energy Use and GHG Emissions Savings

Multi-family housing retrofits have the potential to be an important component of

comprehensive sustainability or climate action plans. Depending on the extent of market

penetration, retrofits to multi-family housing in the City of Richmond can reduce energy

consumption by over 12% and GHG emissions by almost 10%. It is instructive to look at the

adoption scenarios to determine savings. In the 10% adoption scenario, savings would be

relatively minimal. For Pre-1980 buildings, about 31 billion BTU would be saved annually.

These savings represent only 1.3% of multifamily energy consumption. Also in the 10%

scenario, GHG emissions would be reduced by 2,557 MT CO2-e, or 1%. If half of all multifamily

units were retrofit (50% scenario), the region would achieve energy consumption savings of 155

billion Btu (6.4%), and GHG emission reductions of 12,785 MT CO2-e (5.3%). While the

11 US Environmental Protection Agency, 2012.

27

savings seem minimal, the energy savings would be equivalent to installing 8,258 homes in

Richmond with a 4 KW solar PV system. Energy consumption reductions and GHG emission

savings for the all adoption scenarios are shown in Figures A-5 below.

28

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