VACANT LANDI N F I L L D E V E L O P M E N T P O T E N T I A L I N P H I L A D E L P H I A

B R I A N T R A Y L O RCAPSTONE PROJECT

University of PennsylvaniaMaster of Urban Spatial Analytics

Professors John Landis & Amy Hillier

August, 2012

TABLE OF CONTENTS

Executive Summary

Introduction

Urban Vacancy

Market-Driven Approach

Site Selection Model

AVAILABLE LAND

DESIRABLE LAND

PROFITABLE LAND

Composite Suitability Analysis

Results

Conclusions

Appendices & Bibliography

4

6

6

8

9

10

12

14

18

20

23

24

4

Executive Summary

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Vacant land in Philadelphia is one of the most ongoing and unresolved urban issues facing the city. It costs the municipality millions in maintenance costs and uncollected tax revenue, and it represents a loss in billions to private property values in parts of the city already impacted by concentrations of poverty. Several initiatives have been developed to 1)mitigate the impact of vacant land on the city and its residents, 2) prevent more properties from becoming vacant, and 3) stimulate infi ll redevelopment on suitable sites.

This study proposes to add value to all of these efforts by providing a useful and usable analysis based on current data and grounded by market-driven insight. Using the city’s current vacant land data and a layered site suitability analysis, this report will indicate which vacant lots are the best match for future residential development.

By developing a site suitability analysis based on the categories of AVAILABILITY, DESIRABILITY, and PROFITABILITY a robust snapshot of developable land can be created. Within this context, potential investors can be targeted for areas of high probability of development, community groups can be activated to utilize a lot with no chance of future development, and neighborhoods at risk of losing land value can become the focus of municipal programs.

This report summarizes the process and results of a comprehensive analysis of the city’s current vacant lot inventory of over 40,000 parcels. The results are conclusive that relatively few sites would be considered profi table for residential development by market and industry standards; but useful insights can be gleaned from the composite index that results in a rating for vacant sites that closely align with the market-driven factors. The model aims to provide each lot with its own “developability index” that can be compared to others within the neighborhood, or across the city. Individual property owners can begin to realize the potential value of their site, or come to terms with the fact that it is not appropriate for the development he or she was expecting.

The goal of this research was not to locate the next major redevelopment investment for the city of Philadelphia, but rather equip those who are doing community work in the city’s neighborhoods, and the city planners with the knowledge and perspective they need to be the most effective and impactful as possible. As a baseline, the results of this initial index can be compared to future analyses as market conditions change, or as Philadelphia continues to amend its zoning code by planning district.

The model of analysis as market-driven and based in real data serves as a tool, not just to planners, and community leaders, but also to developers who must be accountable to investors before they move forward. The spaces where all of the factors of available, desirable and profi table overlap should be the focus of future redevelopment efforts in Philadelphia

5

Of all the vacant sites analyzed in this report, only 92 resulted in a positive land value per square foot of residential development. These sites were concentrated around the periphery of Center City Philadelphia, extending northeast toward Northern Liberties, and South of Old City. These sites hold the highest potential for future development based on all three criteria of the site suitability analysis.

On the other end of the development spectrum are the vacant lots that are too small, or have too many cost restrictions to be considered profi table for residential development. Although some remain on the fringe, others will never attract private sector funds that must meet a standard return on investment before any redevelopment efforts begin. These areas are concentrated in the neighborhoods of southwest Philadelphia, and Grays Ferry.

6

Introduction

Vacant Land Ownership

Citywide Vacant Land Area is 3x the Area of Center City

77%

14.3%

7% 1.7%

Private

Public

RDA PHDC

The city of Philadelphia has experienced a signifi cant loss in population over the second half of the twentieth century; decreasing from a total of over 2 million residents at its peak in 1950 to only 1.56 million as of the 2010 U.S. Census. This reduction in population has not only presented economic challenges that test the city’s capacity to sustain its’ existing infrastructure with a decreasing tax base, but also environmental effects on Philadelphia’s neighborhoods and a social impact to its’ communities. The loss in population is most noticeable to residents in the form of vacant and abandoned buildings and lots scattered throughout the city, particularly in residential neighborhoods where they pose threats to safety and hold the potential to diminish property values.

Vacant land is distributed throughout Philadelphia, but primarily concentrated in the residential neighborhoods in the north and west of the city. Although the high maintenance costs and lost value of uncollected taxes are shared by the entire city, the local effects of blight on property value and neighborhood perception disproportionately impact these areas. According to the city of Philadelphia’s current property data, there are over 44,000 vacant parcels covering an area of 4,644 acres in the city. This is under utilized land is three times the area of Center City Philadelphia. The Redevelopment Authority of the City of Philadelphia (RDA) reports that vacant land accounts for $3.6 billion in lost household wealth, over $20 million in city maintenance cost each year, and at least $2 million in uncollected property taxes each year.

Urban Vacancy

7

Vacant Land in PhiladelphiaVacant land management has been an ongoing priority of the city of Philadelphia, as well as several local and national agencies that work toward the revitalization of urban areas. Some approaches are focused on creating a more productive landscape than the existing fallow lots; proposing a variety of vegetative and park-type uses as temporary and immediate solutions to a more permanent and eventual infi ll redevelopment. Other proposals have included land banks, and city-sponsored redevelopment efforts. These approaches fail to address an underlying issue regarding vacant land in Philadelphia, particularly relative to ownership.

Over three quarters of the vacant land in Philadelphia is privately owned and subject to the risks associated with a constantly shifting real estate market. Although small scale, grass roots neighborhood efforts may prevent the negative impacts of the blight associated with vacant parcels, a more comprehensive approach to vacant land management and eventual infi ll development must be oriented toward a market-driven audience.

According to a National Vacant Properties Campaign report with recommendations to the city, vacant land in Philadelphia can be regarded as a “reservoir of potential revitalization assets,” provided that a comprehensive systematic approach is undertaken to address the issues of fragmentation and reduce obstacles to private investment.

Source: City of Philadelphia 2012

In some neighborhoods, entire blocks have been abandoned, leaving only vacant lots and deteriorating buildings.

8

Market Driven Approach

A comprehensive and sustainable vacant land strategy must be grounded in the reality of an urban real estate market if it going to move beyond community gardens or using vacant lots for art exhibitions. Although these efforts have their merits, and they are most often the fi rst response to deal with urban vacancy, cities such as Philadelphia with decades of vacancy and a growing vacant land area need to move beyond the site specifi c interventions and move to a more global and market-driven approach.

Every vacant lot within the city presents an opportunity for development, but if there was a potential profi t to be had, chances are a developer would have moved forward on that opportunity. In a market such as Philadelphia, with so many vacant parcels with uncertain development prospects, it is diffi cult for a private investor to justify conducting an independent profi tability analysis any given property without the expectation of recouping that cost. That is where a market-driven approach to conduct a city-wide analysis as the fi rst step that the private sector would take if they were to propose development.

Before any redevelopment effort begins, a series of basic calculations are conducted to determine if a potential profi t is possible (and likely) given a series of estimated costs and expected revenues. Although these calculations are based on many assumptions, the cursory analysis is invaluable to the development process, and immediately sets a line where development is a possibility, or it simply is not. As factors fl uctuate and rates go up and down, the line may change, but the question remains as to where that line occurs.

Where the go or no-go decision is made regarding the potential infi ll of a currently vacant parcel is where this analysis will focus. In order for developers to feel comfortable moving forward with what will be a multiyear (and in many cases multi-million dollar) planning, design and construction effort, there are several factors that must be addressed, but the bottom line is profi tability. In the

Vacant Lots Used for Art: “El Camino” by Cessna Decosimo (Chattanooga, TN)

Community Garden, Philadelphia, PA

9

Site Selection Model

Analysis Proposal:

private sector, where a majority of the vacant lots are held, developers must be accountable to investors in order to move forward with any infi ll redevelopment plans.

Analyzing vacant parcels for development profi tability takes away the fi rst obstacle to redevelopment that potential developers face, and adds value to the city’s existing data. On one side, the results of a citywide profi tability analysis can be used by the private sector in order to narrow their focus on likely successful redevelopment opportunities, but also at the other end where the city and other agencies can focus their efforts because the private sector will have little interest in improvement or investments. The real value of conducting this market-driven analysis at a citywide scale is at the fringe of profi tability, where only a few percentage points mean the difference between a great opportunity being left vacant, and Philadelphia’s next successful redevelopment effort.

Use the city of Philadelphia’s existing parcel data to determine which vacant sites are most likely to be profi table for residential development. The analysis will focus on residential properties to maintain consistent cost and revenue comparisons of multifamily development of rental properties. In an effort to provide realistic and robust results that can actually be used by potential investors, a site suitability analysis approach will be used that take into consideration three main factors; vacant land that is AVAILABLE, DESIRABLE, and PROFITABLE. Although there is no shortage of vacant land in Philadelphia, it can be assumed that many of the lots available for development are not suitable for development; either because of existing regulatory restrictions, environmental limitations or accessibility, in addition to their capacity to yield reasonable profi ts signifi cant enough to offset a substantial investment.

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Accessible to transitClose to parks or open space

In a nice community with good schoolsClose to employment opportunities

Currently vacantResidentially zoned

Large enough to allow residential usesOutside of fl ood hazard areas

Revenue > Costs

10

The city of Philadelphia covers a large land area of about 135 square miles, but a signifi cant portion of that area is reserved for non-residential uses. Industrial and commercial zoned properties account for a large portion of the city’s vacant land area, particularly in South Philadelphia, and areas along the rivers. Residential development is not completely prohibited in all of these areas, but for the purposes of maintaining a conservative profi tability model, this analysis will only look at vacant parcels with existing residential zoning. See the Residential Development Profi tability Model and the Zoning Appendix to see how these properties were eliminated.

Vacant Parcels: 44,016Total Acres: 4,644.51Average Parcel Size: 4,596.39 sf

Available Land: Environmental Preconditions

Nonresidential Zoning

11

Not all of Philadelphia’s currently designated vacant parcels are actually suitable for any proposed development, let alone profi table residential development. The Flood Hazard Zone areas include the city’s waterways, and adjacent areas susceptible to fl ooding. The data for these areas comes from the Flood Insurance Rate Maps (FIRM) maintained by the Federal Emergency Management Administration (FEMA). Residents within the 100 year fl oodplain are required to purchase fl ood insurance. For the purposes of this analysis, the vacant properties within the 100 and 500 year fl oodplains are taken out of the equation.

Flood Hazard Zone Areas Remaining Vacant Parcels:

=Based on the fi rst criteria of available land, the total remaining vacant parcels suitable for further analysis is limited to 7820 parcels, covering an area of 1,248 acres.

12

Philadelphia has a regional public transportation system that extends beyond the central core into surrounding suburban communities and job centers throughout Southeastern Pennsylvania and New Jersey. Access to this system is an asset that residents seek when making decisions about where to live. In an urban environment like Philadelphia, access to transit is one of the most important desirability factors. For this analysis, SEPTA’s high speed stations along the Broad Street and Market Frankford Line are used as centers of a Euclidean Distance that extends to the city limits. Areas closest to the stops rate higher on a scale of 1 to 10.

The park system in Philadelphia is one of the city’s greatest assets. With over 9,000 acres of parks, recreation areas, and open space, Fairmount Park is one of the nations largest urban park systems. However, many parts of the city do not have access to park space, putting them at a disadvantage, and less desirable than other parts of the city. Like distance from transit, the desirability of an area decreases as the Euclidean distance from a park increases. This analysis included a 1 mile limit on the desirability factor for distance from parks, as the value of the space is may not be as directly realized as transit beyond one mile.

A major decision factor for many families choosing where to live is the quality of the schools their children will have access to. Philadelphia’s public education system experiences many of the challenges that face urban school districts including limited funding and retaining quality teachers. The Pennsylvania State Department of Education administers an assessment (the PSSA) to all students to determine if specifi c schools are maintaining an adequate yearly progress (AYP) toward standard levels of profi ciency in reading, math and science. This analysis uses AYP to rate desirability on a scale of 1 to 10 for all schools in the city.

0 5 10MilesDesirable Land: Neighborhood Assets

10 10 10

0 0 0

+ + +

Distance from Transit: Distance from Parks: Elementary School Quality

13

Universities in Philadelphia, and their affi liated hospital systems are the largest employers in the city. Neighborhoods surrounding these institutions are highly desired in the residential market for employees and students, and often maintain a solid mix of amenities to market to potential tenants, including retail, restaurants, and commercial uses. This analysis includes a Euclidean distance spectrum for the highest desirability closest to a university and moving toward 1 for areas farthest away within the city. 38

5

10

0

=

Jobs & Higher Education Composite Desirability Index

Producing a raster-grid for the entire city allows for a gradient of desirability to be measured across these individual factors, each of which is calibrated to the same scale of 1 to 10

Combining all of these factors into a single city-wide grid yields a desirability index between 5 and 38, with no area of the city having all amenities, but also no area lacking all of them.

14

Permitted Development Development Costs

Net Operating Income

Estimating the profi tability of multifamily residential development in a city like Philadelphia is an exercise in speculation. There are countless factors that impact the bottom line of investment, so it is impossible to determine a defi nitive value per square foot. Some of these factors may be partially controllable (design and construction costs) but most are not (vacancy rates and the rental market). It is possible within this context to establish a standard based on a few assumptions, market data and underlying demographic indicators. This proposed model takes each of the vacant parcels that are available for development (zoned residential, large enough, and outside of a fl ood zone) and subjects them to the following residual land valuation. The detailed results of the model are included in the Residual Land Appraisal Appendix

This includes the number of residential units permitted by the zoning code, either regulated by an allowable fl oor-area ratio (FAR), or height limit and lot coverage percentages. This fi gure also accounts for common square footage, and the costs of structured parking in the cases where parking is required.

This fi gure includes an overall price per square foot for construction of $150, and an estimated cost of $22,500 per structured parking space. Included in the development cost model is a soft cost ratio of 35% to account for non-construction related expenses associated with designs, permitting and fees.

The costs to operate and maintain a residential property can range depending on its scale, age and occupancy levels, but the standard assumption for anticipating operating expenses for new construction is 20%. In this analysis the overall net operating income is derived from the gross scheduled rent, based on each parcel’s respective census tract Median Contract Rent, with a 150% multiplier for a new-construction factor. A percentage of the scheduled rent is taken out to account for vacancies, and that number is based on each parcel’s respective census tract Rental Vacancy Rate.

Profi table Land: Value Per Square Foot

15

Capitalization Rate

NET OPERATING INCOME

CAPITALIZATION RATE

ESTIMATED VALUE

TOTAL DEVELOPMENT COST

RESIDUAL LAND VALUE

0 5 10Miles

The capitalization rate is the rate of return on a real estate investment property based on the expected income that the property will generate. This fi gure would be used to estimate the potential return on an investment by dividing the income a property will generate by the total value of that property. In the case of this residual land appraisal model, a market capitalization rate of 7.5 is used based on a 2010 Real Estate Research Corporation estimate of 6.9 for fi rst tier newly constructed properties in prime or good locations in Philadelphia. The national average for apartments was 7.5.

Rental Vacancy Rates:

Median Contract Rent:

Determined by dividing unoccupied and un-rented households by the total of all rental units (unoccupied, occupied, and rented) Data from 2010 ACS 5-Year Estimates.

Low

Low

High

High

Data from 2010 ACS 5-Year Estimates. A citywide mean is used for census tracts with insuffi cient data for rental rates.

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16

Residential Development Residual Land ValueCalculated Land Value

-$181,246,178.00- -$1,426,272.10

-$1,426,272.10 - -$816,581.71

-$816,581.71 - -$630,650.22

-$630,650.22 - -$533,604.52

-$533,604.52 - -$482,524.41

-$482,524.41 - -$439,754.72

-$439,754.72 - -$405,515.99

-$405,515.99 - -$367,831.96

-$367831.96 - -$311692.72

-$311,692.72 - $284,5771.74

Running the residual land appraisal model on the AVAILABLE vacant parcels produced a new data set for the city. These properties have a market-driven property value estimate that can be used to more accurately assess the impact of lost value. Assuming multi-family residential development across all parcels produced a wide range in land values, the majority of which were negative.

Because each property was subject to most of the same constants, (particularly within any given census tract) the calculated land values are not as meaningful as their location within the range. Changinng any one factor may move the profi tability line enough to change entire neighborhood outcomes

17

Land Value/SF

Eastwick

Byberry

Somerton

Roxborough

Bustleton

Richmond

Holmesburg

Wynnefield

West Torresdale

Elmwood

Tioga

Tacony

Olney

Frankford

Pennypack

Mayfair

Overbrook

Logan

Fairhill

Fishtown

Hunting Park

Lawncrest

Chestnut Hill

Pennsport

Rhawnhurst

Oxford Circle

Fox Chase

Girard Estates

Kingsessing

East Falls

Bridesburg

Ogontz

Grays Ferry

Pennypack Park

Juniata Park

Mill Creek

West Mount Airy

Germantown

Cobbs Creek

West Oak Lane

Strawberry Mansion

Allegheny West

East Germantown

Riverfront

East Mount Airy

North Central

HaddingtonKensington

Hartranft

East Oak Lane

Manayunk

Cedarbrook

Fishtown

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Point BreezeSchuylkill

Powelton

Cedar Park

Harrowgate

Brewerytown

South Philadelphia

Concentrations of Likely Residential Development

_-$444.30 - -$285.02

-$285.02 - -$268.84

-$268.84 - -$248.32

-$248.32 - -$231.52

-$231.52 - -$215.90

-$215.90 - -$199.00

-$199.00 - -$174.68

-$174.68 - -$141.45

-$141.45 - -$98.41

-$98.41 - $123.90

A citywide aggregation of the land value/sf shows which neighborhoods have higher concentrations of vacant parcels with estimated positive value. It is clear that neighborhoods in Center City, Northeast Philadelphia and the Chestnut Hill/Roxborough area have the highest valued vacant land in Philadelphia

A more accurate account of the results of the appraisal model is the value of land calculated per square foot for each vacant lot. Although most of the city’s larger parcels were removed from the analysis because of their zoning, or proximity to fl oodplains, there is still signifi cant variety in the scale of these parcels.

The Land Value per Square Foot will be used as the PROFITABLE indicator in the fi nal composite analysis along with the DESIRABLE indicator from the proximity raster analysis. The inset neighborhood map below shows less variety in value than the gross calculated land as a result of aggregating the values into ten quantiles to correspond with the environmental analysis and produce a single summary suitability map.

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Indexed Value/SF Indexed Desirability Factor

10 10

0 0

+

19

Likely Sites for Residential Development

=

The fi nal step in this composite analysis is to overlay the results of the DESIRABILITY analysis with the PROFITABILITY of the residual land value model results to produce a fi nal overall map of likely sites for residential development. In this case, the desirability factor between 1-10 matches the scale of price per square foot indexed between 1-10, but this model can be adjusted to weigh either set of factors more heavily.

Combining these two sets of data holds the potential to produce a variety of numeric outcomes, making it diffi cult to determine which sites may be more profi table, but less desirable or vice versa. In this instance however, only the top quantile of profi table sites were positive, making them easy to isolate. The highest resulting parcel composite index was 20, and the lowest was 3.

In this case, even more than the residual analysis alone, it is more relevant where on the spectrum an particular vacant parcel falls than its individual index value. If the analysis were to be adjusted based on an increase to one of the citywide constant variables such as construction cost or capitalization rate, the line at which these vacant parcels become profi table may move from 20 to 19, or 18. It is highly unlikely however, that based on this method that any of the properties indexed below 10 or 15 would ever come out to be positive, unless they are subject to a signifi cant change in zoning.

20

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As a result of the composite analysis, the highest scores reached a perfect 20, and are clustered around the periphery of Center City Philadelphia. Although this provides little additional insight than what may be considered common sense, it is important to note that expected results indicate the validity of the model.

21

Second Highest Score

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RO

SEW

OO

D

WEBSTER

PENN

SEARS

LEAGUE

HU

TCH

INSO

N

ME

UBE

R

PAR

K

OPA

L21

STAPPLETREE

BOU

VIER

DELA

WAR

E EX

P

PER

CYCAR

LISL

E

FULTON

CAMBRIDGE

THOMPSON

SPRING

MANNING

11TH

OPA

L

TAYL

OR

RANSTEAD

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

The sites that achieved a score of 19 out of possible 20 are still within the realm of potential development, although none of them will have an individual residual value appraisal greater than zero. Only the top quantile of land values per square foot had a positive land value based on the profi tability model, so only the perfect score holds that potential. For these parcels, if a different capitalization rate, or construction rate is used, there is a distinct possibility that the model will yield these sites as profi table in the future. Additionally, with the American Community Survey estimates being updated each year, new rental and vacancy rates could move these vacant parcels from the cusp of profi tability to valuable assets and likely sites for residential development.

22

Lowest Scores

30TH

CECIL

74TH

51ST

ENROSE

61ST

76TH

PASSYUNK

WHEELER

DICKENS

VARE

70TH

WOODLAND

REEDLAND

68TH

24TH

S

26TH

HAZEL

ESSI

NG

TON

63RD

GLENMORE

YOCUM

SHIELDS

MIFFLIN

45TH

55TH

BONAFFON

ISLAN

DAGGETT

THEODOREHO

LSTE

IN

CO

BBS CR

EEK

NO

RWIT

CH

ANGORA

67TH

LINMORE

PH

A D

RIV

EW

AY

47TH

NORFOLK

73RD

58TH

SOUTH

HADFIELD

43RD

KINGSESSIN

G

DIVINITYTHOMAS

CURIE

WA

RFI

ELD

ELLSWOR

SHEA

FF

36T

WILLOWS

GRAYS FERRY

WHITBY

GRAYS

SUFFO

LK

BALTIMORE

WEBSTER

MAIDEN

WARRINGTON

CIVIC CENTER

SA

EAST

WIC

KIBIS

HAMILTON

STAN

LEY

PASCHALL

GAURDIAN

RUBY

Y

CHESTER

BREW

STER

UNIVERSITY

MONTROSE

OSLER

PENTR

IDGE

PEMBERTON

CHRISTIAN

LLOYD

BELM

AR

GUYER

CEMETERY

DOREL

LANIER

CATHARINE

MELVILLE

TRINITY

GIB

SON

MOORE

FARRELL

FINCH

POINT BREEZE

MASSEY

HOLBROOK

OSAGE

WALTON

CONVENTION

BITTERN

GREBE

HOBSON

MARKOE

ALLMAN

ELLIO

TT

GR

OVE

BOTA

NIC

LARK

EGRET

CARROLL

SALFORD

SYLMAR

EN

WAXWING

PELTZ

HOFFMAN

GROVERS

REINHARD

INGRAM

GESNER

YBROOK

GARMAN

MALCOLM

GREYLOCK

MAR

STO

N

LITCHFIELD

HOYT

FLORENCE

BROOMALL

BRANT

FARRAGUT

LONGSPUR

RIDGEWOOD

EAST SERVICE

HAR

MO

NY

FERNWOOD

SHELDRAKE

SANDPIPER

MALLARD

BOREAL

HENSLOW

AIKENS ERNEST

MERGANSER

KINGLE

T

JARDEN

BIALY

PHOEBEBUNTIN

G

MEADOWLARK

RAMBO

BERBR

O

BOBOLINK

BASTIAN

CURLEW

PATT

ON

EDGEWOOD

BAM

BEAUMONT

ITHAN

PASCHALLVODGES

HO

LLYW

OO

D

BELMAR

67TH

YOCUM

BAMBREY

HO

LLY

ITHAN

ALLMAN

69TH

29TH

ALLISON

TRIN

ITY

27TH

BUIST

SIMPSON

GLENMORE

DO

VER

REINHARD

25TH

ALDEN

EARP

DEWEY

62ND

LITCHFIELD

BEAUMONT

NEW

KIR

K

PATT

ON

WILTON

MAY

CEDAR

SAINT BERNARD

28TH

ALLMAN

TANEY

HARL

EY

UPLAND

FELTON

59TH

31ST

NAP

A

34TH

TAN

EY

64TH

65TH

66TH

78TH

REGENT

LARCHWOOD

LINDENWOOD

ETTI

NG

MORRIS

72ND

DO

VER

UPLAND

AVONDALE

MYR

TLEW

OO

D

ALDEN

PAXON

HANSON

CO

RLI

ES

35TH

LTER

MARSTO

N

GROSS

GRAYS

TRINITY

CONESTOGA

EDGEWOOD

71ST

WINDSOR

PASSYUNK

SIMPSON

FELTON

SPRINGFIELD

ROBINSON

YEWDALL

REGENT

CHESTER

BART

RAM

SEARS

ASHLAND

PEACH

LINMORE

FRAZIER

33R

D

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

The sites with the lowest scores represent vacant parcels that are not suited for multifamily residential development. These parcels are concentrated in southwest Philadelphia and the Grays Ferry Neighborhood. In more site specifi c circumstances, many of these parcels would be eliminated from consideration, but they offer important insights regarding the future of sites that will never be profi table for a variety of potential land uses. These should be areas of critical concern to the city and organizations working toward revitalization if there is any expectation that eventual market-driven residential infi ll will reach these sites.

23

ConclusionsFollowing the three tiered approach to conduct a comprehensive analysis of Philadelphia’s vacant lots provides an understandable and usable market-driven index of likely development sites. As may be expected, the most valuable parcels of land with the highest desirability are located adjacent to high quality neighborhoods with stronger residential housing markets. This is a testament to the validity of the valuation model, and also an indicator of the reliability of the model at the lower end of the spectrum. As much can be gleaned from the lowest valued sites as the highest in terms of the city’s priorities and where alternatives to infi ll redevelopment may be explored.

Through this research, it several concepts regarding vacant land and the potential for infi ll redevelopment became clear.

• Zoning Does Matter: Outside of the citywide constant market assumptions and variability of vacancy and rental rates across census tracts, the most signifi cant determinant to the potential profi tability of a site is its zoning regulations. Many residential districts do not require any parking, reducing the construction costs considerably, and taking away valuable land area. This analysis also utilized the city’s newly adopted zoning categories, making the application of standards much simpler than the existing code would have allowed. See the Zoning and Residual Appraisal Appendices for the conversions.

• Construction Costs Matter: Initial analyses used a much higher construction cost rate of over $200 per square foot, resulting in no vacant lots being profi table. Further research indicated that although Philadelphia has higher construction costs than other areas, an accurate fi gure is closer to $150 - $180 per square foot.

• Residential Development is a Major Investment: The estimates produced by the residual land appraisal model represented a substantial level of investment. Collectively, billions would need to be invested in the highest rated parcels alone to produce minimal profi ts. This underscores the value of research being done in the area of vacant land management and urban infi ll development, as well as the need for more temporary solutions that continue to mitigate the impacts of these properties on their neighbors and the city.

• Aggregating Parcels Makes Sense: Due to the minimum size requirements for development in each residential zoning category, several thousand vacant parcels were eliminated from the analysis. It becomes clear why land banking and redevelopment efforts work toward acquiring contiguous land. Although it would be possible to aggregate adjacent parcels in this analysis and run the model considering clusters as one property, that would not produce an accurate index for each parcel independently as was the goal of this process.

24

ZONING APPENDIXPHILADELPHIA’S NEW RESIDENTIAL ZONING CATEGORIES:

RSD, Residential Single-Family Detached DistrictsThe RSD, Residential Single-Family Detached districts are primarily intended to accommodate detached houses on individual lots. It is intended that RSD zoning be applied in areas where the land use pattern is characterized predominately by detached houses on individual lots or where such a land use pattern is desired in the future. The Zoning Code includes three RSD districts that are differentiated primarily on the basis of minimum lot area requirements.

RSA, Residential Single-Family Attached DistrictsThe RSA, Residential Single-Family Attached districts are primarily intended to accommodate attached and semi-detached houses on individual lots, but may be applied in areas characterized by a mix of housing types, including detached houses. The districts are also intended to provide a density transition between RSD districts and RM districts. The Zoning Code includes fi ve RSA districts that are differentiated primarily on the basis of minimum lot area requirements.

RTA, Residential Two-Family Attached DistrictsThe RTA, Residential Two-Family Attached districts are primarily intended to accommodate two-family, semi-detached houses on individual lots, but may be applied in areas with a mix of housing types , including detached and attached houses.

RM, Residential Multi-Family DistrictsThe RM, Residential Multi-Family districts are primarily intended to accommodate moderate- to high-density, multi-unit residential buildings in areas where such development already exists or where it is desired in the future. The Zoning Code includes four RM districts. These districts are differentiated primarily on the basis of allowed minimum lot area per unit and allowed building heights.

RMX, Residential Mixed-Use DistrictsThe RMX, Residential Mixed-Use districts are intended to accommodate residential and mixed- use development. The RMX-1 district is further intended to promote conservation of existing topography, trees, natural waterways, and other natural resources, as well as preservation of historically signifi cant buildings, structures, and property. The RMX-3 district is intended for application primarily in Center City.

25

RESIDENTIAL PARKING REQUIREMENTSMinimum Required Parking Spaces

(spaces per unit/sq. ft. of gross floor area/beds/seats)

RSD-1/2/3

RSA-1/2/3

RTA-1

RMX-1

RSA-4/5

RM-1

RM-2/3/4

RMX-2/3

Residential Use Category (as noted below)

Household Living (as noted below)

Single-Family 1/unit 0 0

Two-Family 1/unit 0 1/2 units

Multi-Family 1/unit 0 3/10 units

Group Living (except as noted below) 1/10 permanent beds 1/10 permanent beds 1/10 permanent beds

Single-Room Residence 1/20 units + 1; min. 2 1/20 units + 1; min. 2 1/20 units + 1; min. 2

DISTRICT R-1 R-1A R-2 R-3 R-4

PERMITTED USES

SINGLE FAMILY Y Y Y Y Y

DUPLEX / TWO FAMILY

MULTI-FAMILY

RESIDENTIAL RELATED USES Y Y

NON-RESIDENTIAL USES Y Y

OTHER PERMITTED USES Y Y Y

PERMITTED BUILDING TYPE

DETACHED Y Y Y Y Y

SEMI-DETACHED Y Y

ATTACHED

MULTIPLE BUILDINGS / LOT

ZONING REQUIREMENTS

MINIMUM LOT WIDTH (FT.) 75 65 50 50 35

MINIMUM LOT AREA (SQ. FT.) 10,000 7,800 5,000 5,000 3,150

MINIMUM OPEN AREA (%) OF LOT 65 65 70 70 60

SET-BACK LINE /FRONT YARD MINIMUM DEPTH (FT.)

35 35 25 25 15

SIDE YARD MINIMUM WIDTH:

Detached single family dwelling (ft.)722 @ 15 2@ 10

2 at 25 total, each

not <10

2 at 25 total, each

not <102 @ 8

Detached single family dwelling – corner lot (ft.)7315 10 7 7 6

Semi-detached single family dwelling (ft.) 25 16

Attached single family dwelling (ft.)

Detached duplex dwelling (ft.)

Detached duplex dwelling – corner lot (ft.)

Semi-detached duplex dwelling (ft.)

Attached duplex dwelling (ft.)

Multiple dwelling (ft.)

Building other than dwellings (ft.) 2 @ 15 2 @ 15 2 @ 10

Building other than dwelling, corner lot (ft.) 15 15 10

REAR YARD MINIMUM DEPTH (FT.) 30 30 25 25 20

REAR YARD MINIMUM AREA (SQ. FT.)

BUILDING HEIGHT LIMIT – DWELLING (FT.) 35 35 35 35 35

BUILDING HEIGHT LIMIT – NON-DWELLING (FT.) 35 35 3535 + add’l

height 1

35 + add’l

height 1

MAXIMUM NO. OF STORIES – DWELLING 3 3 3 3 3

OFF-STREET PARKING See Chapter 14-1400 of this Title.

Residential Unit Count ProcessFor Residential Districts Without FAR 1. Eliminate all lots that do not meet the

minimum lot area requirement.2. Determine the difference between the

open space % required and the total lot size to get the square footage of a residential fl oor plate.

3. Multiply the number of stories allowed by the square footage of the fl oor plate to get the total square footage of the structure permitted.

4. Divide the total square footage by the average 1000 sf unit size to determine the number of units.

26

RESIDUAL LAND APPRAISAL APPENDIX

Residual Land Appraisal Formula: Based on Professor John Landis’

Parcel_ID SHAPE_AREA SHAPE_LEN NAMELSAD10 TotalHousi RenterOccu Unrented_V Rented_Vac TOT_RENT RentalVaca MED_RENT ADJ_RENT CODE New_Code PARKING Stories OpenArea FAR GSF COMMON_SF RES_SF RES_CALC RES_UNITS1 3251.832038 362.208003 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K2*1.5 R10 RM 1 0 3 0.3 3 =(B2 (Q2*B2))*R2 =S2*0.0625 =S2 T2 =U2/1000 6.4020443248122 11277.962488 458.57901 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K3*1.5 R10 RM 1 0 3 0.3 3 =(B3 (Q3*B3))*R3 =S3*0.0625 =S3 T3 =U3/1000 22.203488648253 2376.594543 296.263966 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K4*1.5 R10 RM 1 0 3 0.3 3 =(B4 (Q4*B4))*R4 =S4*0.0625 =S4 T4 =U4/1000 4.6789205065314 1525.122672 201.168736 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K5*1.5 R10A RSA 5 0 3 0.3 3 =(B5 (Q5*B5))*R5 =S5*0.0625 =S5 T5 =U5/1000 3.00258526055 1490.573277 191.517429 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K6*1.5 R10 RM 1 0 3 0.3 3 =(B6 (Q6*B6))*R6 =S6*0.0625 =S6 T6 =U6/1000 2.9345661390936 1796.875205 212.827716 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K7*1.5 R10A RSA 5 0 3 0.3 3 =(B7 (Q7*B7))*R7 =S7*0.0625 =S7 T7 =U7/1000 3.5375980598437 2545.418357 220.053505 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K8*1.5 R10A RSA 5 0 3 0.3 3 =(B8 (Q8*B8))*R8 =S8*0.0625 =S8 T8 =U8/1000 5.0112923903438 2271.994325 217.703805 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K9*1.5 R10A RSA 5 0 3 0.3 3 =(B9 (Q9*B9))*R9 =S9*0.0625 =S9 T9 =U9/1000 4.4729888273439 1759.085528 219.442427 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K10*1.5 R10A RSA 5 0 3 0.3 3 =(B10 (Q10*B10))*R10 =S10*0.0625 =S10 T10 =U10/1000 3.4631996332510 2317.119673 226.418728 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K11*1.5 R10A RSA 5 0 3 0.3 3 =(B11 (Q11*B11))*R11 =S11*0.0625 =S11 T11 =U11/1000 4.56182935621811 1618.832657 196.749538 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K12*1.5 R10A RSA 5 0 3 0.3 3 =(B12 (Q12*B12))*R12 =S12*0.0625 =S12 T12 =U12/1000 3.18707679346812 1466.700923 185.353761 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K13*1.5 R10A RSA 5 0 3 0.3 3 =(B13 (Q13*B13))*R13 =S13*0.0625 =S13 T13 =U13/1000 2.88756744215613 2254.230531 200.790384 Census Tract 366 1350 431 101 3 535 0.188785 1724 =K14*1.5 R10A RSA 5 0 3 0.3 3 =(B14 (Q14*B14))*R14 =S14*0.0625 =S14 T14 =U14/1000 4.43801635790614 3793.627787 310.939148 Census Tract 38 1723 310 21 0 331 0.063444 711 =K15*1.5 R5 RSA 3 =V15 3 0.5 3 =(B15 (Q15*B15))*R15 =S15*0.0625 =S15 T15 =U15/1000 4.42787493263915 2203.960815 262.509154 Census Tract 83.02 2134 766 56 4 826 0.067797 606 =K16*1.5 R9 RM 1 0 3 0.3 3 =(B16 (Q16*B16))*R16 =S16*0.0625 =S16 T16 =U16/1000 4.33904785453117 2013.032382 260.702592 Census Tract 83.02 2134 766 56 4 826 0.067797 606 =K17*1.5 R9 RM 1 0 3 0.3 3 =(B17 (Q17*B17))*R17 =S17*0.0625 =S17 T17 =U17/1000 3.96315750206218 1615.723516 231.422564 Census Tract 83.02 2134 766 56 4 826 0.067797 606 =K18*1.5 R9 RM 1 0 3 0.3 3 =(B18 (Q18*B18))*R18 =S18*0.0625 =S18 T18 =U18/1000 3.18095567212519 1836.894572 257.205468 Census Tract 83.02 2134 766 56 4 826 0.067797 606 =K19*1.5 R9 RM 1 0 3 0.3 3 =(B19 (Q19*B19))*R19 =S19*0.0625 =S19 T19 =U19/1000 3.61638618862520 1796.650534 256.208433 Census Tract 83.02 2134 766 56 4 826 0.067797 606 =K20*1.5 R9 RM 1 0 3 0.3 3 =(B20 (Q20*B20))*R20 =S20*0.0625 =S20 T20 =U20/1000 3.53715573881221 1682.19585 251.918791 Census Tract 83.02 2134 766 56 4 826 0.067797 606 =K21*1.5 R9 RM 1 0 3 0.3 3 =(B21 (Q21*B21))*R21 =S21*0.0625 =S21 T21 =U21/1000 3.31182307968722 1907.113912 269.775356 Census Tract 83.02 2134 766 56 4 826 0.067797 606 =K22*1.5 R9 RM 1 0 3 0.3 3 =(B22 (Q22*B22))*R22 =S22*0.0625 =S22 T22 =U22/1000 3.7546305142523 1650.994507 234.320158 Census Tract 83.02 2134 766 56 4 826 0.067797 606 =K23*1.5 R9 RM 1 0 3 0.3 3 =(B23 (Q23*B23))*R23 =S23*0.0625 =S23 T23 =U23/1000 3.25039543565624 1633.363491 233.74933 Census Tract 83.02 2134 766 56 4 826 0.067797 606 =K24*1.5 R9 RM 1 0 3 0.3 3 =(B24 (Q24*B24))*R24 =S24*0.0625 =S24 T24 =U24/1000 3.21568437290625 5414.331083 360.423074 Census Tract 83.02 2134 766 56 4 826 0.067797 606 =K25*1.5 R9 RM 1 0 3 0.3 3 =(B25 (Q25*B25))*R25 =S25*0.0625 =S25 T25 =U25/1000 10.6594643196526 2191.859501 262.474205 Census Tract 83.02 2134 766 56 4 826 0.067797 606 =K26*1.5 R9 RM 1 0 3 0.3 3 =(B26 (Q26*B26))*R26 =S26*0.0625 =S26 T26 =U26/1000 4.31522339259327 2911.949343 261.393706 Census Tract 176.02 1371 637 91 3 731 0.124487 558 =K27*1.5 R9 RM 1 0 3 0.3 3 =(B27 (Q27*B27))*R27 =S27*0.0625 =S27 T27 =U27/1000 5.73290026903128 7277.35122 348.125019 Census Tract 176.02 1371 637 91 3 731 0.124487 558 =K28*1.5 R5 RSA 3 =V28 3 0.5 3 =(B28 (Q28*B28))*R28 =S28*0.0625 =S28 T28 =U28/1000 8.494033377093

27

SOFT_COST CONST_COST PARKING_COST EXP_RATIO CAP_RATE TOTAL_SF CONST_COST SOFT_COST PARKING_COST DEV_COST GROSS_RENT VACANCIES EXP_EXPENSES NOI EST_VAL RESID_VAL VALUE_SF0.35 150 22500 0.2 0.075 =(W2*1000)+T2 =AC2*Y2 =AD2*X2 =O2*Z2 =AD2+AE2+AF2 =(W2*L2)*12 =((W2*J2)*(K2* 1))*12 =(AH2*AA2)* 1 =AH2+AI2+AJ2 =AK2/AB2 =AL2 AG2 =AM2/B20.35 150 22500 0.2 0.075 =(W3*1000)+T3 =AC3*Y3 =AD3*X3 =O3*Z3 =AD3+AE3+AF3 =(W3*L3)*12 =((W3*J3)*(K3* 1))*12 =(AH3*AA3)* 1 =AH3+AI3+AJ3 =AK3/AB3 =AL3 AG3 =AM3/B30.35 150 22500 0.2 0.075 =(W4*1000)+T4 =AC4*Y4 =AD4*X4 =O4*Z4 =AD4+AE4+AF4 =(W4*L4)*12 =((W4*J4)*(K4* 1))*12 =(AH4*AA4)* 1 =AH4+AI4+AJ4 =AK4/AB4 =AL4 AG4 =AM4/B40.35 150 22500 0.2 0.075 =(W5*1000)+T5 =AC5*Y5 =AD5*X5 =O5*Z5 =AD5+AE5+AF5 =(W5*L5)*12 =((W5*J5)*(K5* 1))*12 =(AH5*AA5)* 1 =AH5+AI5+AJ5 =AK5/AB5 =AL5 AG5 =AM5/B50.35 150 22500 0.2 0.075 =(W6*1000)+T6 =AC6*Y6 =AD6*X6 =O6*Z6 =AD6+AE6+AF6 =(W6*L6)*12 =((W6*J6)*(K6* 1))*12 =(AH6*AA6)* 1 =AH6+AI6+AJ6 =AK6/AB6 =AL6 AG6 =AM6/B60.35 150 22500 0.2 0.075 =(W7*1000)+T7 =AC7*Y7 =AD7*X7 =O7*Z7 =AD7+AE7+AF7 =(W7*L7)*12 =((W7*J7)*(K7* 1))*12 =(AH7*AA7)* 1 =AH7+AI7+AJ7 =AK7/AB7 =AL7 AG7 =AM7/B70.35 150 22500 0.2 0.075 =(W8*1000)+T8 =AC8*Y8 =AD8*X8 =O8*Z8 =AD8+AE8+AF8 =(W8*L8)*12 =((W8*J8)*(K8* 1))*12 =(AH8*AA8)* 1 =AH8+AI8+AJ8 =AK8/AB8 =AL8 AG8 =AM8/B80.35 150 22500 0.2 0.075 =(W9*1000)+T9 =AC9*Y9 =AD9*X9 =O9*Z9 =AD9+AE9+AF9 =(W9*L9)*12 =((W9*J9)*(K9* 1))*12 =(AH9*AA9)* 1 =AH9+AI9+AJ9 =AK9/AB9 =AL9 AG9 =AM9/B90.35 150 22500 0.2 0.075 =(W10*1000)+T10 =AC10*Y10 =AD10*X10 =O10*Z10 =AD10+AE10+AF10 =(W10*L10)*12 =((W10*J10)*(K10* 1))*12 =(AH10*AA10)* 1 =AH10+AI10+AJ10 =AK10/AB10 =AL10 AG10 =AM10/B100.35 150 22500 0.2 0.075 =(W11*1000)+T11 =AC11*Y11 =AD11*X11 =O11*Z11 =AD11+AE11+AF11 =(W11*L11)*12 =((W11*J11)*(K11* 1))*12 =(AH11*AA11)* 1 =AH11+AI11+AJ11 =AK11/AB11 =AL11 AG11 =AM11/B110.35 150 22500 0.2 0.075 =(W12*1000)+T12 =AC12*Y12 =AD12*X12 =O12*Z12 =AD12+AE12+AF12 =(W12*L12)*12 =((W12*J12)*(K12* 1))*12 =(AH12*AA12)* 1 =AH12+AI12+AJ12 =AK12/AB12 =AL12 AG12 =AM12/B120.35 150 22500 0.2 0.075 =(W13*1000)+T13 =AC13*Y13 =AD13*X13 =O13*Z13 =AD13+AE13+AF13 =(W13*L13)*12 =((W13*J13)*(K13* 1))*12 =(AH13*AA13)* 1 =AH13+AI13+AJ13 =AK13/AB13 =AL13 AG13 =AM13/B130.35 150 22500 0.2 0.075 =(W14*1000)+T14 =AC14*Y14 =AD14*X14 =O14*Z14 =AD14+AE14+AF14 =(W14*L14)*12 =((W14*J14)*(K14* 1))*12 =(AH14*AA14)* 1 =AH14+AI14+AJ14 =AK14/AB14 =AL14 AG14 =AM14/B140.35 150 22500 0.2 0.075 =(W15*1000)+T15 =AC15*Y15 =AD15*X15 =O15*Z15 =AD15+AE15+AF15 =(W15*L15)*12 =((W15*J15)*(K15* 1))*12 =(AH15*AA15)* 1 =AH15+AI15+AJ15 =AK15/AB15 =AL15 AG15 =AM15/B150.35 150 22500 0.2 0.075 =(W16*1000)+T16 =AC16*Y16 =AD16*X16 =O16*Z16 =AD16+AE16+AF16 =(W16*L16)*12 =((W16*J16)*(K16* 1))*12 =(AH16*AA16)* 1 =AH16+AI16+AJ16 =AK16/AB16 =AL16 AG16 =AM16/B160.35 150 22500 0.2 0.075 =(W17*1000)+T17 =AC17*Y17 =AD17*X17 =O17*Z17 =AD17+AE17+AF17 =(W17*L17)*12 =((W17*J17)*(K17* 1))*12 =(AH17*AA17)* 1 =AH17+AI17+AJ17 =AK17/AB17 =AL17 AG17 =AM17/B170.35 150 22500 0.2 0.075 =(W18*1000)+T18 =AC18*Y18 =AD18*X18 =O18*Z18 =AD18+AE18+AF18 =(W18*L18)*12 =((W18*J18)*(K18* 1))*12 =(AH18*AA18)* 1 =AH18+AI18+AJ18 =AK18/AB18 =AL18 AG18 =AM18/B180.35 150 22500 0.2 0.075 =(W19*1000)+T19 =AC19*Y19 =AD19*X19 =O19*Z19 =AD19+AE19+AF19 =(W19*L19)*12 =((W19*J19)*(K19* 1))*12 =(AH19*AA19)* 1 =AH19+AI19+AJ19 =AK19/AB19 =AL19 AG19 =AM19/B190.35 150 22500 0.2 0.075 =(W20*1000)+T20 =AC20*Y20 =AD20*X20 =O20*Z20 =AD20+AE20+AF20 =(W20*L20)*12 =((W20*J20)*(K20* 1))*12 =(AH20*AA20)* 1 =AH20+AI20+AJ20 =AK20/AB20 =AL20 AG20 =AM20/B200.35 150 22500 0.2 0.075 =(W21*1000)+T21 =AC21*Y21 =AD21*X21 =O21*Z21 =AD21+AE21+AF21 =(W21*L21)*12 =((W21*J21)*(K21* 1))*12 =(AH21*AA21)* 1 =AH21+AI21+AJ21 =AK21/AB21 =AL21 AG21 =AM21/B210.35 150 22500 0.2 0.075 =(W22*1000)+T22 =AC22*Y22 =AD22*X22 =O22*Z22 =AD22+AE22+AF22 =(W22*L22)*12 =((W22*J22)*(K22* 1))*12 =(AH22*AA22)* 1 =AH22+AI22+AJ22 =AK22/AB22 =AL22 AG22 =AM22/B220.35 150 22500 0.2 0.075 =(W23*1000)+T23 =AC23*Y23 =AD23*X23 =O23*Z23 =AD23+AE23+AF23 =(W23*L23)*12 =((W23*J23)*(K23* 1))*12 =(AH23*AA23)* 1 =AH23+AI23+AJ23 =AK23/AB23 =AL23 AG23 =AM23/B230.35 150 22500 0.2 0.075 =(W24*1000)+T24 =AC24*Y24 =AD24*X24 =O24*Z24 =AD24+AE24+AF24 =(W24*L24)*12 =((W24*J24)*(K24* 1))*12 =(AH24*AA24)* 1 =AH24+AI24+AJ24 =AK24/AB24 =AL24 AG24 =AM24/B240.35 150 22500 0.2 0.075 =(W25*1000)+T25 =AC25*Y25 =AD25*X25 =O25*Z25 =AD25+AE25+AF25 =(W25*L25)*12 =((W25*J25)*(K25* 1))*12 =(AH25*AA25)* 1 =AH25+AI25+AJ25 =AK25/AB25 =AL25 AG25 =AM25/B250.35 150 22500 0.2 0.075 =(W26*1000)+T26 =AC26*Y26 =AD26*X26 =O26*Z26 =AD26+AE26+AF26 =(W26*L26)*12 =((W26*J26)*(K26* 1))*12 =(AH26*AA26)* 1 =AH26+AI26+AJ26 =AK26/AB26 =AL26 AG26 =AM26/B260.35 150 22500 0.2 0.075 =(W27*1000)+T27 =AC27*Y27 =AD27*X27 =O27*Z27 =AD27+AE27+AF27 =(W27*L27)*12 =((W27*J27)*(K27* 1))*12 =(AH27*AA27)* 1 =AH27+AI27+AJ27 =AK27/AB27 =AL27 AG27 =AM27/B270.35 150 22500 0.2 0.075 =(W28*1000)+T28 =AC28*Y28 =AD28*X28 =O28*Z28 =AD28+AE28+AF28 =(W28*L28)*12 =((W28*J28)*(K28* 1))*12 =(AH28*AA28)* 1 =AH28+AI28+AJ28 =AK28/AB28 =AL28 AG28 =AM28/B28

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