Assessing Urban Forest 

Eff ects and Values

Northern 

Research Station

Resource Bulletin NRS-7

United States

Department of 

Agriculture

Forest Service

Philadelphia’s Urban Forest
Published by: For additional copies:

USDA FOREST SERVICE USDA Forest Service 

11 CAMPUS BLVD SUITE 200 Publications Distribution

NEWTOWN SQUARE PA 19073-3294 359 Main Road

 Delaware, OH 43015-8640

February 2007 Fax: (740)368-0152

Visit our homepage at: http://www.nrs.fs.fed.us

Abstract

An analysis of trees in Philadelphia reveals that this city has about 2.1 million trees with 

canopies that cover 15.7 percent of the area. The most common tree species are black 

cherry, crabapple, and tree of heaven. The urban forest currently stores about 530,000 tons 

of carbon valued at $9.8 million. In addition, these trees remove about 16,100 tons of carbon 

per year ($297,000 per year) and about 802 tons of air pollution per year ($3.9 million per 

year). The structural, or compensatory, value is estimated at $1.8 billion. Information on the 

structure and functions of the urban forest can be used to improve and augment support for 

urban forest management programs and to integrate urban forests within plans to improve 

environmental quality in the Philadelphia area.

The Authors

DAVID J. NOWAK is a research forester and project leader, ROBERT E. HOEHN III, is a 

biological sciences technician, DANIEL E. CRANE is an information technology specialist, 

JACK C. STEVENS is a forester, and JEFFREY T. WALTON is a research forester with the 

Forest Service’s Northern Research Station at Syracuse, NY.

Photographs

Cover photo by Phillip Rodbell; pages 1, 3 (lower right), 5, 6, 7, 8, 9, 10, and 13 courtesy of 

the Pennsylvania Horticultural Society.

Acknowledgments

This study was funded in part by the National Urban and Community Forestry Advisory 

Council (NUCFAC).
1

Executive Summary

Trees in cities can contribute signifi cantly to human health and environmental quality. 

Unfortunately, little is known about the urban forest resource and what it contributes 

to the local and regional society and economy. To better understand the urban forest 

resource and its numerous values, the USDA Forest Service, Northern Research 

Station, developed the Urban Forest Effects (UFORE) model. Results from this model 

are used to advance the understanding of the urban forest resource, improve urban 

forest policies, planning and management, provide data for potential inclusion of trees 

within environmental regulations, and determine how trees affect the environment and 

consequently enhance human health and environmental quality in urban areas.

Forest structure is a measure of various physical attributes of the vegetation, such as 

tree species composition, number of trees, tree density, tree health, leaf area, biomass, 

and species diversity. Forest functions, which are determined by forest structure, 

include a wide range of environmental and ecosystem services such as air pollution 

removal and cooler air temperatures. Forest values are an estimate of the economic 

worth of the various forest functions.

To help determine the vegetation structure, functions, and values of the urban forest 

in Philadelphia, a vegetation assessment was conducted during the summer of 1996. 

For this assessment, one-tenth acre fi eld plots were sampled and analyzed using the 

UFORE model. This report summarizes results and values of:

• Forest structure

• Potential risk to forest from insects or diseases

• Air pollution removal

• Carbon storage

• Annual carbon removal (sequestration)

• Changes in building energy use

Urban forests 

provide numerous 

benefi ts to society, 

yet relatively little 

is known about this 

important resource.

In 1996, the UFORE 

model was used to 

survey and analyze 

Philadelphia’s 

urban forest.

The calculated 

environmental 

benefi ts of the 

urban forest 

are signifi cant, 

yet many 

environmental and 

social benefi ts 

still remain to be 

quantifi ed.

Philadephia Urban Forest Summary 

Feature Measure

Number of trees 2.1 million

Tree cover 15.7%

Most common species black cherry, crabapple, tree of heaven

Percentage of trees < 6-inches diameter 57.5%

Pollution removal 802 tons/year ($3.9 million/year)

Carbon storage 530,000 tons ($9.8 million)

Carbon sequestration 16,100 tons/year ($297,000/year)

Building energy reduction $1,178,000/year

Avoided carbon emissions $14,400/year

Structural value $1.8 billion

Ton – short ton (U.S.) (2,000 lbs)
2

Urban Forest Effects Model 

and Field Measurements

Though urban forests have many functions and values, currently only a few of these 

attributes can be assessed. To help assess the city’s urban forest, data from 210 fi eld 

plots located throughout the city were analyzed using the Forest Service’s Urban Forest 

Effects (UFORE) model.1

UFORE is designed to use standardized fi eld data from randomly located plots and 

local hourly air pollution and meteorological data to quantify urban forest structure 

and its numerous effects, including:

• Urban forest structure (e.g., species composition, tree density, tree health, leaf 

area, leaf and tree biomass, species diversity, etc.).

• Amount of pollution removed hourly by the urban forest, and its associated 

percent air quality improvement throughout a year. Pollution removal is 

calculated for ozone, sulfur dioxide, nitrogen dioxide, carbon monoxide and 

particulate matter (<10 microns).

• Total carbon stored and net carbon annually sequestered by the urban forest.

• Effects of trees on building energy use and consequent effects on carbon 

dioxide emissions from power plants.

• Compensatory value of the forest, as well as the value of air pollution removal 

and carbon storage and sequestration.

• Potential impact of infestations by Asian longhorned beetles, emerald ash 

borers, gypsy moth, and Dutch elm disease.

For more information go to http://www.ufore.org

In the fi eld, one-tenth acre plots were randomly located in the different land use strata 

of Philadelphia. These land uses were used to divide the analysis into smaller zones. 

The plots were divided among the following land uses: Commercial/Industrial (10 

plots), Institutional (11 plots), Multi-Family Residential (35 plots), Park (19 plots), 

Single Family Residental (30 plots), Transportation (10 plots), Vacant (15 plots), and 

Wooded (80 plots). This distribution 

allows for comparison among land uses.

Field data were collected for the 

Forest Service by ACRT Inc. 

(Appraisal, Consulting, Research, 

and Training, Akron, OH); data 

collection took place during the 

leaf-on season to properly assess 

Benefi ts ascribed to 

urban trees include:

• Air pollution 

removal

• Air temperature 

reduction

• Reduced building 

energy use

• Absorption 

of ultraviolet 

radiation

• Improved water 

quality

• Reduced noise

• Improved human 

comfort

• Increased 

property value

• Improved 

physiological & 

psychological 

well-being

• Aesthetics

• Community 

cohesion
3

tree canopies. Within each plot, data included land-use, ground and tree cover, shrub 

characteristics, and individual tree attributes of species, stem-diameter at breast 

height (d.b.h.; measured at 4.5 ft.), tree height, height to base of live crown, crown 

width, percentage crown canopy missing and dieback, and distance and direction to 

residential buildings.2

To calculate current carbon storage, biomass for each tree was calculated using 

equations from the literature and measured tree data. Open-grown, maintained trees 

tend to have less biomass than predicted by forest-derived biomass equations.3

 To 

adjust for this difference, biomass results for open-grown urban trees are multiplied by 

0.8.3

 No adjustment is made for trees found in natural stand conditions. Tree dryweight biomass was converted to stored carbon by multiplying by 0.5.

To estimate the gross amount of carbon sequestered annually, average diameter growth 

from the appropriate genera and diameter class and tree condition was added to the 

existing tree diameter (year x) to estimate tree diameter and carbon storage in year x+1.

Air pollution removal estimates are derived from calculated hourly tree-canopy 

resistances for ozone, and sulfur and nitrogen dioxides based on a hybrid of big-leaf 

and multi-layer canopy deposition models.4, 5 As the removal of carbon monoxide and 

particulate matter by vegetation is not directly related to transpiration, removal rates 

(deposition velocities) for 

these pollutants were based 

on average measured values 

from the literature6, 7 that 

were adjusted depending 

on leaf phenology and leaf 

area. Particulate removal 

incorporated a 50 percent 

resuspension rate of particles 

back to the atmosphere.8

Seasonal effects of trees on 

residential building energy 

use were calculated based 

on procedures described the literature9

 using distance and direction of trees from 

residential structures, tree height and tree condition data.

Compensatory values were based on valuation procedures of the Council of Tree 

and Landscape Appraisers, which uses tree species, diameter, condition and location 

information.10

To learn more about UFORE methods11 visit: 

http://www.nrs.fs.fed.us/UFORE/data/ or www.ufore.org

Field Survey Data

Plot Information

• Land use type

• Percent tree cover

• Percent shrub 

cover

• Percent plantable

• Percent ground 

cover types

• Shrub species/

dimensions

Tree parameters

• Species

• Stem diameter

• Total height

• Height to crown 

base

• Crown width

• Percent foliage 

missing

• Percent dieback

• Crown light 

exposure

• Distance and 

direction to 

buildings from 

trees
4

Tree Characteristics of the Urban Forest

The urban forest of Philadelphia has an estimated 2.1 million trees with a tree cover of 

15.7 percent. Trees that have diameters less than 6 inches account for 57.5 percent of 

the population. The three most common species in the urban forest are black cherry 

(10.2 percent), crabapple (7.5 percent), and tree of heaven (7.1 percent). The 10 

most common species account for 56.5 percent of all trees; their relative abundance is 

illustrated below.

There are an 

estimated 2.1 million 

trees in Philadelphia 

with canopies that 

cover 15.7 percent 

of the city.

The 10 most 

common species 

account for 56.5 

percent of the total 

number of trees.

Tree density is 

highest in the 

Wooded land use, 

and lowest in the 

Institutional land 

use.

crabapple

boxelder

other species 

(including dead)

northern red oak

white mulberry

northern white 

cedar

red maple

tree of heaven

tulip tree

black cherry

other species

The highest density of trees occurs in the Wooded (152.9 trees/acre), followed by the 

Transportation (56.3 trees/acre) and the single Family Residential (44.6 trees/acre). 

The overall tree density in Philadelphia is 25.1 trees/acre, which is comparable to other 

city tree densities (Appendix I), of 14.4 to 119.2 trees/acre.

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

900,000

1,000,000

Wooded

Transportation

1 Family Res.

Commercial/Ind.

Mult. Fam. Res.

Vacant Land

Park

Institutional

Number of Trees

0

20

40

60

80

100

120

140

160

180

Trees per acre

Total Trees

Per acre
5

Urban forests are a mix of native tree species that existed prior to the development 

of the city and exotic species that were introduced by residents or other means. 

Thus, urban forests often have a tree diversity that is higher than surrounding native 

landscapes. An increased tree diversity can minimize the overall impact or destruction 

by a species-specifi c insect or disease, but the increase in the number of exotic plants 

can also pose a risk to native plants if some of the exotic species are invasive plants that 

can potentially out-compete and displace native species. In Philadelphia, about 57 

percent of the trees are from species native to Pennsylvania. Trees with a native origin 

outside of North America are mostly from Asia (18.2 percent of the species).

*North America + refers to tree species that are native to North America and one other continent.

**Americas + refers to tree species that are native to North and South America and one other continent.

0

5

10

15

20

25

30

35

1-34-67-9

10-1213-1516-18

19-2122-2425-2728-30

30+

d.b.h. class (inches)

Percent

Nearly 57 percent 

of the tree species 

in Philadelphia 

are native to 

Pennsylvania.

Urban forests are 

a mix of native 

tree species that 

existed prior to the 

development of 

the city and exotic 

species that were 

introduced by 

residents or other 

means.

0

10

20

30

40

50

60

70

North America

Pennsylvania

Asia

*North America +

Eurasia

Unknown

**Americas +

Percent
6

Urban Forest Cover and Leaf Area

Trees cover about 15.7 percent of Philadelphia; shrubs cover 5.9 percent of the city. 

Dominant ground cover types include impervious surfaces (excluding buildings) (e.g., 

driveways, sidewalks, parking lots) (41.2 percent), herbaceous (e.g., grass, gardens) 

(28.4 percent), and buildings (17.4 percent).

Healthy leaf area 

equates directly 

to tree benefi ts 

provided to the 

community.

Black cherry has the 

greatest importance 

to the Philadelphia 

urban forest based 

on relative leaf 

area and relative 

population.

Many tree benefi ts are linked directly to the amount of healthy leaf surface area of the 

plant. In Philadelphia, trees that dominate in terms of leaf area are tulip tree, London 

planetree, and black cherry.

Tree species with relatively large individuals contributing leaf area to the population 

(species with percent of leaf area much greater than percent of total population) are 

London planetree, American beech, and tulip tree. Smaller trees in the population are 

Austrian pine, crabapple, and boxelder (species with percent of leaf area much less than 

percent of total population). A species must also constitute at least 1 percent of the 

total population to be considered as relatively large or small trees in the population.

The importance values (IV) are calculated using a formula that takes into account 

the relative leaf area and relative abundance. The most important species in the urban 

forest, according to calculated IVs, are black cherry, tulip tree, and red maple.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Commercial/Ind.

Institutional

Mult. Fam. Res.

Park

1 Family Res.

Transportation

Vacant Land

Wooded

Philadelphia

bare soil

duff/mulch cover

herbaceous

water

impervious surfaces (excluding buildings)

buildings

0

2

4

6

8

10

12

tulip tree

London planetree

black cherry

red maple

Norway maple

American beech

northern red oak

white ash

tree of heaven

black walnut

Percent

% of total leaf area

% of all trees

Common

 Name

%

Popa

%

LAb IVc

black 

 cherry

10.2 5.6 15.8

tulip tree 2.8 9.4 12.2

red maple 6.6 5.5 12.1

tree of 

 heaven

7.1 3.4 10.5

crabapple 7.5 2.4 9.9

London 

planetree

1.5 8.4 9.9

white ash 5.1 4.0 9.1

Norway 

 maple

2.6 5.4 8.0

boxelder 5.6 1.8 7.4

northern 

 red oak

2.2 4.5 6.7

a percent of population

b percent of leaf area

c Percent Pop + Percent LA
7

Air Pollution Removal by Urban Trees

Poor air quality is a common problem in many urban areas. It can lead to human 

health problems, damage to landscape materials and ecosystem processes, and reduced 

visibility. The urban forest can help improve air quality by reducing air temperature, 

directly removing pollutants from the air, and reducing energy consumption in 

buildings, which consequently reduce air pollutant emissions from the power plants. 

Trees also emit volatile organic compounds that can contribute to ozone formation. 

However, integrative studies have revealed that an increase in tree cover leads to 

reduced ozone formation.12

Pollution removal by trees and shrubs in Philadelphia was estimated using the UFORE 

model in conjunction with fi eld data and hourly pollution and weather data for the 

year 2000. Pollution removal was greatest for particulate matter less than 10 microns 

(PM10), followed by ozone (O3

), nitrogen dioxide (NO2), sulfur dioxide (SO2), and 

carbon monoxide (CO). It is estimated that trees and shrubs remove 802 tons of air 

pollution (CO, NO2

, O3, PM10, SO2) per year with an associated value of $3.9 million 

(based on estimated national median externality costs associated with pollutants13). 

Trees remove about 2.5 times more air pollution than shrubs in Philadelphia.

The average percentage of air pollution removal during the daytime, in-leaf season was 

estimated to be:

• O3

 0.33% • PM10 0.38%

• SO2

 0.32% • NO2 0.22%

• CO 0.001%

Peak 1-hour air quality improvements during the in-leaf season for heavily-treed areas 

were estimated to be:

• O3

 9.4% • PM10 12.2%

• SO2

 9.6% • NO2 5.3%

• CO 0.05%

The urban forest 

of Philadelphia 

removes 

approximately 802 

tons of pollutants 

each year, with a 

societal value of 

$3.9 million/year.

General urban 

forest management 

recommendations 

to improve air 

quality are given in 

Appendix II.

0

50

100

150

200

250

300

350

CO NO O PM SO

Pollution removed (tons)

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

Value (thousands dollars)

Pollution Removed

Value

2 2 3 10
8

Carbon Storage and Sequestration

Climate change is an issue of global concern. Urban trees can help mitigate climate 

change by sequestering atmospheric carbon (from carbon dioxide) in tissue and by 

reducing energy use in buildings, and consequently reducing carbon dioxide emissions 

from fossil-fuel based power plants.14

Trees reduce the amount of carbon in the atmosphere by sequestering carbon in new 

tissue growth every year. The amount of carbon annually sequestered is increased with 

healthier trees and larger diameter trees. Gross sequestration by trees in Philadelphia 

is about 16,100 tons of carbon per year with an associated value of $297,000. Net 

carbon sequestration in the Philadelphia urban forest is about 11,800 tons.

Carbon storage:

Carbon currently 

held in tree tissue 

(roots, stems, and 

branches).

Carbon 

sequestration:

Estimated amount 

of carbon removed 

annually by 

trees. Net carbon 

sequestration 

can be negative if 

emission of carbon 

from decomposition 

is greater than 

amount sequestered 

by healthy trees.

Carbon storage by trees is another way trees can infl uence global climate change. As 

trees grow, they store more carbon by holding it in their accumulated tissue. As trees 

die and decay, they release much of the stored carbon back to the atmosphere. Thus, 

carbon storage is an indication of the amount of carbon that can be lost if trees are 

allowed to die and decompose. Trees in Philadelphia are estimated to store 530,000 

tons of carbon ($9.8 million). Of all the species sampled, tulip tree stores the most 

carbon (approximately 10.5 percent of the total carbon stored), while black cherry is 

estimated to sequester the most carbon annually (8.0 percent of all sequestered carbon).

0

200

400

600

800

1,000

1,200

1,400

black cherry

London planetree

tree of heaven

tulip tree

crabapple

northern red oak

red maple

Norway maple

white ash

American beech

Sequestration (tons)

0

5,000

10,000

15,000

20,000

25,000

Value (U.S. dollars)

Sequestration

Value

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

0 - 3

3 - 6

6 - 9

9 - 12

12 - 15

15 - 18

18 - 21

21 - 24

24 - 27

27 - 30

30+

d.b.h. class (inches)

Storage (tons)

0

500

1,000

1,500

2,000

2,500

3,000

Sequestration (tons)

Carbon Storage 

Carbon Sequestration
9

Trees Affect Energy Use in Buildings

Trees affect energy consumption by shading buildings, providing evaporative cooling, 

and blocking winter winds. Trees tend to reduce building energy consumption in the 

summer months and can either increase or decrease building energy use in the winter 

months, depending on the location of trees around the building. Estimates of tree 

effects on energy use are based on fi eld measurements of tree distance and direction to 

space-conditioned residential buildings.9

Based on average energy costs in 2002 dollars, trees in Philadelphia are estimated 

to reduce energy costs from residential buildings by $1.18 million annually. Trees 

also provide an additional $14,400 in value per year by reducing the amount of 

carbon released by fossil-fuel based power plants (a reduction of 770 tons of carbon 

emissions).

Trees affect energy 

consumption by 

shading buildings, 

providing 

evaporative cooling, 

and blocking winter 

winds. 

Interactions 

between buildings 

and trees save an 

estimated $1.18 

million in heating 

and cooling costs.

Lower energy use in 

residential buildings 

reduced carbon 

emissions from 

power plants by 770 

tons ($14,400).

Annual energy savings due to trees near residential buildings

Heating Cooling Total

MBTUa -251,300 n/a -251,300

MWHb -3,700 32,300 28,600

Carbon avoided (t) -4,850 5,620 770

a

Million British Thermal Units

b

Megawatt-hour

Annual savingsc (U.S. $) in residential energy expenditures during heating 

and cooling seasons

Heating Cooling Total

MBTUa -1,996,000 n/a -1,996,000

MWHb -414,000 3,588,000 3,174,000

Carbon avoided (t) -90,000 104,300 14,400

a

Million British Thermal Units

b

Megawatt-hour

c

Based on state-wide energy costs
10

Structural and Functional Values

Urban forests have a structural value based on the tree itself (e.g., the cost of having 

to replace the tree with a similar tree). The structural value10 of the urban forest in 

Philadelphia is about $1.8 billion. The structural value of an urban forest tends to 

increase with a rise in the number and size of healthy trees.

Urban forests also have functional values (either positive or negative) based on the 

functions the tree performs. Annual functional values also tend to increase with 

increased number and size of healthy trees, and are usually on the order of several 

million dollars per year. There are many other functional values of the urban forest, 

though they are not quantifi ed here (e.g., reduction in air temperatures and ultraviolet radiation, improvements in water quality). Through proper management, urban 

forest values can be increased. However, the values and benefi ts also can decrease as the 

amount of healthy tree cover declines.

Structural values:

• Structural value: $1.6 billion

• Carbon storage: $9.8 million

Annual functional values:

• Carbon sequestration: $297,000

• Pollution removal: $3.9 million

• Lower energy costs and reduces carbon emissions: $1.19 million

More detailed information on the urban forest in Philadelphia can be found at 

http://www.fs.fed.us/ne/syracuse/Data/data.htm. Additionally, information on other 

urban forest values can be found in Appendix I and information comparing tree 

benefi ts to estimates of average carbon emissions in the city, average automobile 

emissions, and average household emissions can be found in Appendix III.

Urban forests have 

a structural value 

based on the tree 

itself.

Urban forests also 

have functional 

values based on the 

functions the tree 

performs.

Large, healthy, 

long-lived trees 

provide the greatest 

structural and 

functional values.

A map of priority 

planting locations 

for Philadelphia is 

in Appendix IV.

A list of tree 

species found in 

Philadelphia is 

in Appendix V. 0

20

40

60

80

100

120

140

160

180

tulip tree

London planetree

northern red oak

American beech

black cherry

Norway maple

white ash

white mulberry

red maple

crabapple

Structural value (millions of dollars)
11

Potential Insect and Disease Impacts

Various insects and diseases can infest urban forests, potentially killing trees and 

reducing the health, value and sustainability of the urban forest. As various pests have 

differing tree hosts, the potential damage or risk of each pest will differ. Four exotic 

pests were analyzed for their potential impact: Asian longhorned beetle, gypsy moth, 

emerald ash borer, and Dutch elm disease.

The Asian longhorned beetle (ALB)15 is an insect that bores into and kills a wide range 

of hardwood species. ALB represents a potential loss to the Philadelphia urban forest 

of $773 million in structural value (52 percent of the tree population).

Asian longhorned 

beetle

Emerald ash borer

Gypsy moth

Kenneth R. Law 

USDA APHIS PPQ 

(www.invasive.org)

David Cappaert

Michigan State University

(www.invasive.org)

USDA Forest Service Archives 

(www.invasive.org)

Dutch elm disease

The gypsy moth (GM)16 is a defoliator that feeds on many species causing widespread 

defoliation and tree death if outbreak conditions last several years. This pest could 

potentially result in damage to or a loss of $354 million in structural value (13.5 

percent of the population).

Emerald ash borer (EAB)17 has killed thousands of ash trees in Michigan, Ohio, and 

Indiana. EAB has the potential to affect 5.9 percent of the population ($68 million in 

structural value).

American elm, one of the most important street trees in the 20th century, has been 

devastated by the Dutch elm disease (DED). Since fi rst reported in the 1930s, it 

has killed more than 50 percent of the native elm population in the United States.18

Although some elm species have shown varying degrees of resistance, Philadelphia 

possibly could lose 0.9 percent of its trees to this disease ($22 million in structural 

value).

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

ALB GM EAB DED

0

100

200

300

400

500

600

700

800

900

Population at risk

Compensatory Value

Number of trees

Compensatory value ($ millions)
12

Appendix I. Comparison of Urban Forests

A commonly asked question is, “How does this city compare to other cities?” Although comparison among cities 

should be made with caution as there are many attributes of a city that affect urban forest structure and functions, 

summary data are provided from other cities analyzed using the UFORE model.

I. City totals, trees only

City

% Tree 

cover Number of trees

Carbon 

storage (tons)

Carbon 

sequestration 

(tons/yr)

Pollution 

removal 

(tons/yr)

Pollution value 

U.S. $

Calgary, Canadaa 7.2 11,889,000 445,000 21,400 326 1,611,000

Atlanta, GAb 36.7 9,415,000 1,344,000 46,400 1,663 8,321,000

Toronto, Canadac 20.5 7,542,000 992,000 40,300 1,212 6,105,000

New York, NYb 20.9 5,212,000 1,350,000 42,300 1,677 8,071,000

Baltimore, MDd 21.0 2,627,000 597,000 16,200 430 2,129,000

Philadelphia, PAb 15.7 2,113,000 530,000 16,100 576 2,826,000

Washington, DCe 28.6 1,928,000 526,000 16,200 418 1,956,000

Boston, MAb 22.3 1,183,000 319,000 10,500 284 1,426,000

Woodbridge, NJf 29.5 986,000 160,000 5,560 210 1,037,000

Minneapolis, MNg 26.4 979,000 250,000 8,900 306 1,527,000

Syracuse, NYd 23.1 876,000 173,000 5,420 109 568,000

San Francisco, CAa 11.9 668,000 194,000 5,100 141 693,000

Morgantown, WVh 35.5 658,000 93,000 2,890 72 333,000

Moorestown, NJf 28.0 583,000 117,000 3,760 118 576,000

Jersey City, NJf 11.5 136,000 21,000 890 41 196,000

Freehold, NJf 34.4 48,000 20,000 545 22 110,000

II. Per acre values of tree effects

City No. of trees

Carbon Storage 

(tons)

Carbon sequestration 

(tons/yr)

Pollution removal 

(lbs/yr)

Pollution value 

U.S. $

Calgary, Canadaa 66.7 2.5 0.12 3.7 9.0

Atlanta, GAb 111.6 15.9 0.55 39.4 98.6

Toronto, Canadac 48.3 6.4 0.26 15.5 39.1

New York, NYb 26.4 6.8 0.21 17.0 40.9

Baltimore, MDd 50.8 11.6 0.31 16.6 41.2

Philadelphia, PAb 25.1 6.3 0.19 13.6 33.5

Washington, DCe 49.0 13.4 0.41 21.3 49.7

Boston, MAb 33.5 9.1 0.30 16.1 40.4

Woodbridge, NJf 66.5 10.8 0.38 28.4 70.0

Minneapolis, MNg 26.2 6.7 0.24 16.4 40.9

Syracuse, NYd 54.5 10.8 0.34 13.5 35.4

San Francisco, CAa 22.5 6.6 0.17 9.5 23.4

Morgantown, WVh 119.2 16.8 0.52 26.0 60.3

Moorestown, NJf 62.1 12.4 0.40 25.1 61.3

Jersey City, NJf 14.4 2.2 0.09 8.6 20.7

Freehold, NJf 38.3 16.0 0.44 34.9 88.2

Data collection group

a

 City personnel e Casey Trees Endowment Fund b

 ACRT, Inc. f New Jersey Department of Environmental Protection c

 University of Toronto g Davey Resource Group d

 U.S. Forest Service h West Virginia University
13

Appendix II. General Recommendations for Air Quality Improvement

Urban vegetation can directly and indirectly affect local and regional air quality by altering the urban atmospheric 

environment. Four main ways that urban trees affect air quality are:

Temperature reduction and other microclimatic effects

Removal of air pollutants

Emission of volatile organic compounds (VOC) and tree maintenance emissions

Energy conservation in buildings and consequent power plant emissions

The cumulative and interactive effects of trees on climate, pollution removal, and VOC and power plant emissions 

determine the overall impact of trees on air pollution. Cumulative studies involving urban tree impacts on ozone 

have revealed that increased urban canopy cover, particularly with low VOC emitting species, leads to reduced 

ozone concentrations in cities. Local urban forest management decisions also can help improve air quality.

Urban forest management strategies to help improve air quality include:

Strategy Reason

Increase the number of healthy trees Increase pollution removal

Sustain existing tree cover Maintain pollution removal levels

Maximize use of low VOC-emitting trees Reduces ozone and carbon monoxide formation

Sustain large, healthy trees Large trees have greatest per-tree effects

Use long-lived trees Reduce long-term pollutant emissions from planting and removal

Use low maintenance trees Reduce pollutants emissions from maintenance activities

Reduce fossil fuel use in maintaining vegetation Reduce pollutant emissions

Plant trees in energy conserving locations Reduce pollutant emissions from power plants

Plant trees to shade parked cars Reduce vehicular VOC emissions

Supply ample water to vegetation Enhance pollution removal and temperature reduction

Plant trees in polluted or heavily populated areas Maximizes tree air quality benefi ts

Avoid pollutant-sensitive species Improve tree health

Utilize evergreen trees for particulate matter Year-round removal of particles
14

Appendix III. Relative Tree Effects

The urban forest in Philadelphia provides benefi ts that include carbon storage and sequestration, and air pollutant 

removal. To estimate a relative value of these benefi ts, tree benefi ts were compared to estimates of average carbon 

emissions in the city19, average passenger automobile emissions20, and average household emissions.21

General tree information:

Average tree diameter (d.b.h.) = 8.0 in.

Median tree diameter (d.b.h.) = 5.4 in.

Average number of trees per person = 1.4

Number of trees sampled = 1,433

Number of species sampled = 84

Average tree effects by tree diameter:

The Philadelphia urban forest provides:

Carbon storage equivalent to:

Amount of carbon (C) emitted in city in 22 days or

Annual carbon emissions from 318,000 automobiles or 

Annual C emissions from 159,800 single family houses

Carbon monoxide removal equivalent to:

Annual carbon monoxide emissions from 45 automobiles or

Annual carbon monoxide emissions from 200 single family 

houses

Nitrogen dioxide removal equivalent to:

Annual nitrogen dioxide emissions from 6,500 automobiles 

or

Annual nitrogen dioxide emissions from 4,300 single family 

houses

Sulfur dioxide removal equivalent to:

Annual sulfur dioxide emissions from 65,500 automobiles or

Annual sulfur dioxide emissions from 1,100 single family 

houses

Particulate matter less than 10 micron (PM10) removal 

equivalent to:

Annual PM10 emissions from 568,400 automobiles or

Annual PM10 emissions from 54,900 single family houses

Annual C sequestration equivalent to:

Amount of C emitted in city in 0.7 days or

Annual C emissions from 9,700 automobiles or

Annual C emissions from 4,900 single family homes

a

 miles = number of automobile miles driven that produces emissions equivalent to tree effect

Carbon sequestration

Pollution

Carbon storage removal

D.b.h.

Class (inch) (lbs) ($) (miles) a (lbs/yr) ($/yr) (miles)a (lbs) ($)

1-3 8 0.08 30 1.9 0.02 7 0.1 0.18

3-6 57 0.53 210 6.7 0.06 24 0.2 0.45

6-9 172 1.59 630 10.8 0.10 40 0.4 0.98

9-12 342 3.15 1,250 17.1 0.16 63 0.6 1.57

12-15 587 5.40 2,150 21.6 0.20 79 0.8 2.04

15-18 973 8.96 3,560 29.7 0.27 109 1.3 3.24

18-21 1,443 13.29 5,290 37.0 0.34 135 1.8 4.50

21-24 1,930 17.77 7,070 50.3 0.46 184 1.7 4.17

24-27 2,606 24.00 9,540 67.5 0.62 247 2.3 5.58

27-30 3,463 31.90 12,680 82.7 0.76 303 2.8 6.93

30+ 6,152 56.66 22,530 92.0 0.85 337 3.0 7.36
15

Appendix IV. Tree Planting Index Map

To determine the best locations to plant trees, tree canopy and impervious cover maps from National Land 

Cover Data22 were used in conjunction with 2000 U.S. Census data to produce an index of priority planting 

areas. Index values were produced for each census block with the higher the index value, the higher the priority 

of the area for tree planting. This index is a type of “environmental equity” index with areas with higher human 

population density and lower tree cover tending to get the higher index value. The criteria used to make the 

index were:

• Population density: the greater the population density, the greater the priority for tree planting

• Tree stocking levels: the lower the tree stocking level (the percent of available greenspace (tree, grass, and 

soil cover areas) that is occupied by tree canopies), the greater the priority for tree planting

• Tree cover per capita: the lower the amount of tree canopy cover per capita (m2

/capita), the greater the 

priority for tree planting

Each criteria was standardized23 on a scale of 0 to 1 with 1 representing the census block with the highest value 

in relation to priority of tree planting (i.e., the census block with highest population density, lowest stocking 

density or lowest tree cover per capita were standardized to a rating of 1). Individual scores were combined and 

standardized based on the following formula to produce an overall priority index value between 0 and 100:

I = (PD * 40) + (TS * 30) + (TPC * 30)

Where I = index value, PD is standardized population density, TS is standardized tree stocking, and TPC is 

standardized tree cover per capita.
16

Appendix V. List of Species Sampled in Philadelphia

Continued

% % Potential pest b

Genus Species Common Name Population Leaf Area IVa ALB GM EAB DED

Acer negundo boxelder 5.6 1.8 7.4 o

Acer palmatum Japanese maple 0.8 1 1.8 o

Acer platanoides Norway maple 2.6 5.4 8.0 o

Acer rubrum red maple 6.6 5.5 12.1 o

Acer saccharinum silver maple 1.3 1.9 3.2 o

Acer saccharum sugar maple 0.3 0.9 1.2 o

Acer pseudoplatanus sycamore maple 1.1 1 2.1 o

Ailanthus altissima tree of heaven 7.1 3.4 10.5

Alnus species alder 0 0 0.0 o o

Aralia spinosa devils walking stick 0.4 0 0.4

Betula lenta black birch 0.2 0.3 0.5 o

Betula pendula European white birch 0.1 0 0.1 o o

Betula alleghaniensis yellow birch 0.1 0.1 0.2 o

Broussonetia papyrifera paper mulberry 0.2 0.1 0.3

Carpinus caroliniana American hornbeam 0.2 0.1 0.3

Carya cordiformis bitternut hickory 0.3 0.4 0.7

Carya species hickory 0.2 0 0.2

Carya tomentosa mockernut hickory 0.1 0 0.1

Carya glabra pignut hickory 0.3 0.1 0.4

Catalpa speciosa northern catalpa 0.5 0.4 0.9

Catalpa bignonioides southern catalpa 0.1 0 0.1

Cedrus atlantica atlas cedar 0.1 0.1 0.2

Cornus species dogwood 0.2 0.1 0.3

Cornus fl orida fl owering dogwood 1.4 0.9 2.3

Crataegus species hawthorn 0.7 0.6 1.3 o

Euonymus species euonymus 0 0 0.0

Fagus grandifolia American beech 1.4 5.3 6.7

Fraxinus pennsylvanica green ash 0.9 0.6 1.5 o o
17

Appendix V continued.

Continued

Fraxinus americana white ash 5.1 4 9.1 o o

Gleditsia triacanthos honeylocust 0.5 0.6 1.1

Hamamelis virginiana witch hazel 0.2 0.1 0.3

Ilex opaca American holly 0.9 0.6 1.5

Juglans nigra black walnut 1.1 2.9 4.0

Juniperus virginiana eastern red cedar 0.4 1.4 1.8

Lindera benzoin spicebush 0 0 0.0

Liquidambar styracifl ua sweetgum 0.5 0.8 1.3 o

Liriodendron tulipifera tulip tree 2.8 9.4 12.2

Magnolia species magnolia 0 0 0.0

Magnolia x soulangeana saucer magnolia 0.1 0.2 0.3

Magnolia grandifl ora southern magnolia 0.1 0 0.1

Magnolia tripetala umbrella magnolia 0.1 0 0.1

Malus species crabapple 7.5 2.4 9.9 o o

Morus alba white mulberry 3.5 2.6 6.1

Nyssa sylvatica black tupelo 0.6 0.4 1.0

Ostrya virginiana eastern hophornbeam 0.3 0.1 0.4 o

Other species other species 5.2 0.8 6.0

Paulownia tomentosa royal paulownia 1.3 0.5 1.8

Phellodendron amurense amur corktree 2.4 0.8 3.2

Picea mariana black spruce 0.1 0.2 0.3

Picea pungens blue spruce 0.3 0.6 0.9

Picea abies Norway spruce 0.6 0.9 1.5

Pinus nigra Austrian pine 1.1 0.3 1.4

Pinus strobus eastern white pine 1.1 1.8 2.9

Pinus ponderosa ponderosa pine 0.1 0.2 0.3

Platanus occidentalis American sycamore 0.9 2.1 3.0

Platanus acerifolia London planetree 1.5 8.4 9.9

% % Potential pest b

Genus Species Common Name Population Leaf Area IVa ALB GM EAB DED
18

Appendix V continued.

Populus grandidentata bigtooth aspen 0 0 0.0 o o

Populus deltoides eastern cottonwood 1.2 1.5 2.7 o o

Populus heterophylla swamp cottonwood 0.6 1.4 2.0 o o

Populus alba white poplar 0.1 0 0.1 o o

Prunus serotina black cherry 10.2 5.6 15.8 o

Prunus species cherry 1.1 1.2 2.3 o

Prunus cerasifera cherry plum 0.6 0.6 1.2 o

Prunus persica nectarine 0.1 0 0.1 o

Prunus pensylvanica pin cherry 0.2 0.1 0.3 o

Prunus avium sweet cherry 0 0 0.0 o

Pseudotsuga menziesii Douglas fi r 0.1 0.2 0.3

Pyrus calleryana callery pear 0.4 0.5 0.9

Quercus velutina black oak 0.2 0.5 0.7 o

Quercus rubra northern red oak 2.2 4.5 6.7 o

Quercus species oak 0.2 0.6 0.8 o

Quercus palustris pin oak 0.5 0.4 0.9 o

Quercus alba white oak 0.2 0.3 0.5 o

Rhus typhina staghorn sumac 0.1 0 0.1 o

Robinia pseudoacacia black locust 1.5 2 3.5 o

Salix species willow 0.2 0.1 0.3 o o

Sassafras albidum sassafras 1.7 0.7 2.4 o

Sophora japonica Japanese pagoda tree 0.6 0.9 1.5

Taxus species yew 0.2 0 0.2

Thuja occidentalis northern white cedar 2.9 1.8 4.7

Tilia americana American basswood 0.3 0.8 1.1 o

Tsuga canadensis eastern hemlock 1 1 2.0

Ulmus americana American elm 0.9 1.4 2.3 o o

Ulmus pumila Siberian elm 1.3 1.6 2.9 o

Viburnum burkwoodii viburnum 0.2 0.3 0.5

% % Potential pest b

Genus Species Common Name Population Leaf Area IVa ALB GM EAB DED
19

References

1 Nowak, D.J.; Crane, D.E. 2000. The Urban Forest 

Effects (UFORE) Model: quantifying urban 

forest structure and functions. In: Hansen, M.; 

Burk, T., eds. Integrated tools for natural resources 

inventories in the 21st century. Proceedings of 

IUFRO conference. Gen. Tech. Rep. NC-212. St. 

Paul, MN: U.S. Department of Agriculture, Forest 

Service, North Central Research Station: 714-720.

2 Nowak, D.J.; Crane, D.E.; Stevens, J.C.; Hoehn, R.E. 

2005. The urban forest effects (UFORE) model: 

fi eld data collection manual. V1b. [Newtown 

Square, PA]: U.S. Department of Agriculture, 

Forest Service, Northeastern Research Station. 34 p. 

http://www.fs.fed.us/ne/syracuse/Tools/downloads/

UFORE_Manual.pdf

3 Nowak, D.J. 1994. Atmospheric carbon dioxide 

reduction by Chicago’s urban forest. In: 

McPherson, E.G.; Nowak, D.J.; Rowntree, R.A., 

eds. Chicago’s urban forest ecosystem: results of 

the Chicago Urban Forest Climate Project. Gen. 

Tech. Rep. NE-186. Radnor, PA: U.S. Department 

of Agriculture, Forest Service, Northeastern Forest 

Experiment Station: 83-94.

4 Baldocchi, D. 1988. A multi-layer model for 

estimating sulfur dioxide deposition to a 

deciduous oak forest canopy. Atmospheric 

Environment. 22: 869-884.

5 Baldocchi, D.D.; Hicks, B.B.; Camara, P. 1987. A 

canopy stomatal resistance model for gaseous 

deposition to vegetated surfaces. Atmospheric 

Environment. 21: 91-101.

6 Bidwell, R.G.S.; Fraser, D.E. 1972. Carbon 

monoxide uptake and metabolism by leaves.

Canadian Journal of Botany. 50: 1435-1439. 

7 Lovett, G.M. 1994. Atmospheric deposition of 

nutrients and pollutants in North America: an 

ecological perspective. Ecological Applications. 4: 

629-650.

8 Zinke, P.J. 1967. Forest interception studies in the 

United States. In: Sopper, W.E.; Lull, H.W., eds. 

Forest hydrology. Oxford, UK: Pergamon Press: 

137-161.

9 McPherson, E.G.; Simpson, J.R. 1999. Carbon 

dioxide reduction through urban forestry: 

guidelines for professional and volunteer tree 

planters. Gen. Tech. Rep. PSW-171. Albany, CA: 

U.S. Department of Agriculture, Forest Service, 

Pacifi c Southwest Research Station. 237 p. Can 

be accessed through http://www.fs.fed.us/psw/

publications/gtrs.shtml

10 Nowak, D.J.; Crane, D.E.; Dwyer, J.F. 2002. 

Compensatory value of urban trees in the United 

States. Journal of Arboriculture. 28(4): 194-199.

11 Nowak, D.J.; Crane, D.E.; Stevens, J.C.; Ibarra, M. 

2002. Brooklyn’s urban forest. Gen. Tech. Rep. 

NE-290. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northeastern Research 

Station. 107 p.

12 Nowak D.J.; Dwyer, J.F. 2000. Understanding 

the benefi ts and costs of urban forest ecosystems.

In: Kuser, John E., ed. Handbook of urban and 

community forestry in the northeast. New York: 

Kluwer Academics/Plenum: 11-22.

13 Murray, F.J.; Marsh L.; Bradford, P.A. 1994. New 

York state energy plan, vol. II: issue reports.

Albany, NY: New York State Energy Offi ce.

14 Abdollahi, K.K.; Ning, Z.H.; Appeaning, A., eds. 

2000. Global climate change and the urban 

forest. Baton Rouge, LA: GCRCC and Franklin 

Press. 77 p.

15 Northeastern Area State and Private Forestry. 2005. 

Asian Longhorned Beetle. Newtown Square, PA: 
20

U.S. Department of Agriculture, Northeastern Area 

State and Private Forestry. http://www.na.fs.fed.

us/fhp/alb/

16 Northeastern Area State and Private Forestry. 

2005. Gypsy moth digest. Newtown Square, PA: 

U.S. Department of Agriculture, Forest Service, 

Northeastern Area State and Private Forestry. 

http://www.na.fs.fed.us/fhp/gm/

17 Northeastern Area State and Private Forestry. 2005. 

Forest health protection emerald ash borer 

home. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northeastern Area 

State and Private Forestry. http://www.na.fs.fed.

us/fhp/eab

18 Stack, R.W.; McBride, D.K.; Lamey, H.A. 1996. 

Dutch elm disease. PP-324 (revised). Fargo, 

ND: North Dakota State University, Cooperative 

Extension Service. http://www.ext.nodak.edu/

extpubs/plantsci/trees/pp324w.htm
21

Explanation of Calculations of Appendix III and IV

19 Total city carbon emissions were based on 2003 

U.S. per capita carbon emissions, calculated as 

total U.S. carbon emissions (Energy Information 

Administration, 2003, Emissions of Greenhouse 

Gases in the United States 2003. http://www.eia.

doe.gov/oiaf/1605/1605aold.html) divided by 

2003 total U.S. population (www.census.gov). Per 

capita emissions were multiplied by Minneapolis 

population to estimate total city carbon emissions.

20 Average passenger automobile emissions per 

mile were based on dividing total 2002 pollutant 

emissions from light-duty gas vehicles (National 

Emission Trends http://www.epa.gov/ttn/chief/

trends/index.html) by total miles driven in 2002 by 

passenger cars (National Transportation Statistics 

http://www.bts.gov/publications/national_

transportation_statistics/2004/).

Average annual passenger automobile emissions 

per vehicle were based on dividing total 2002 

pollutant emissions from light-duty gas vehicles 

by total number of passenger cars in 2002 

(National Transportation Statistics http://www.

bts.gov/publications/national_transportation_

statistics/2004/).

Carbon dioxide emissions from automobiles 

assumed 6 pounds of carbon per gallon of gasoline 

with energy costs of refi nement and transportation 

included (Graham, R.L.; Wright, L.L.; Turhollow, 

A.F. 1992. The potential for short-rotation woody 

crops to reduce U.S. CO2

 emissions. Climatic 

Change. 22:223-238.)

21 Average household emissions based on average 

electricity kWh usage, natural gas Btu usage, fuel oil 

Btu usage, kerosene Btu usage, LPG Btu usage, and 

wood Btu usage per household from:

Energy Information Administration. Total Energy 

Consumption in U.S. Households by Type of 

Housing Unit, 2001 www.eia.doe.gov/emeu/recs/

recs2001/detailcetbls.html. 

CO2

, SO2, and NOx power plant emission per 

KWh from:

U.S. Environmental Protection Agency. U.S. 

power plant emissions total by year www.epa.gov/

cleanenergy/egrid/samples.htm.

CO emission per kWh assumes one-third of 1 

percent of C emissions is CO based on:

Energy Information Administration. 1994. 

Energy use and carbon emissions: non-OECD 

countries. DOE/EIA-0579(94). Washington, 

DC: Department of Energy, Energy Information 

Administration. http://tonto.eia.doe.gov/bookshelf

PM10 emission per kWh from: 

Layton, M. 2004. 2005 Electricity environmental 

performance report: electricity generation and air 

emissions. Sacramento, CA: California Energy 

Commission. 

http://www.energy.ca.gov/2005_energypolicy/

documents/2004-11-15_workshop/2004-11-15_03-

A_LAYTON.PDF

CO2

, NOx, SO2, PM10, and CO emission per Btu 

for natural gas, propane and butane (average used 

to represent LPG), Fuel #4 and #6 (average used to 

represent fuel oil and kerosene) from:

Abraxas energy consulting. http://www.

abraxasenergy.com/emissions/ 

CO2

 and fi ne particle emissions per Btu of wood 

from:

 Houck, J.E.; Tiegs, P.E.; McCrillis, R.C.; Keithley, 

C.; Crouch, J. 1998. Air emissions from residential 
22

heating: the wood heating option put into 

environmental perspective. In: Proceedings of U.S. 

EPA and Air and Waste Management Association 

conference: living in a global environment, V.1: 

373-384.

CO, NOx and SOx emission per Btu of wood based 

on total emissions from wood burning (tonnes) 

from: 

Residential Wood Burning Emissions in British 

Columbia. 2005. http://www.env.gov.bc.ca/air/

airquality/pdfs/wood_emissions.pdf.

Emissions per dry tonne of wood converted to 

emissions per Btu based on average dry weight per 

cord of wood and average Btu per cord from:

Kuhns, M.; Schmidt, T. 1988. Heating with wood: 

species characteristics and volumes I. NebGuide 

G-88-881-A. Lincoln, NE: University of Nebraska, 

Institute of Agriculture and Natural Resources, 

Cooperative Extension.

22 National Land Cover Data available at: 

www.epa.gov/mrlc/nlcd.html.

23 Standardized value for population density was 

calculated as: 

 PD = (n – m)/r 

 where:

PD is the value (0-1)

n is the value for the census block (population/km2

) 

m is the minimum value for all census blocks, and

r is the range of values among all census blocks 

(maximum value – minimum value).

 Standardized value for tree stocking was calculated as :

 TS = (1 – (T/(T+G)) 

 where: 

TS is the value (0-1) 

T is percent tree cover, and 

G is percent grass cover.

 Standardized value for tree cover per capita was 

calculated as:

 TPC = 1 – [(n – m)/r] 

 where: 

TPC is the value (0-1) 

n is the value for the census block (m2

/capita) 

m is the minimum value for all census blocks, and 

r is the range of values among all census blocks 

(maximum value – minimum value).
Printed on Recycled Paper

Nowak, David J.; Hoehn, Robert E. III, Crane, Daniel E.; Stevens, Jack C.; Walton, 

Jeffrey T. 2007. Assessing urban forest effects and values, Philladelphia’s 

urban forest. Resour. Bull. NRS-7. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northern Research Station. 22 p.

An analysis of trees in Philadelphia reveals that this city has about 2.1 million trees 

with canopies that cover 15.7 percent of the area. The most common tree species 

are black cherry, crabapple, and tree of heaven. The urban forest currently stores 

about 530,000 tons of carbon valued at $9.8 million. In addition, these trees remove 

about 16,100 tons of carbon per year ($297,000 per year) and about 802 tons of 

air pollution per year ($3.9 million per year). The structural, or compensatory, value 

is estimated at $1.8 billion. Information on the structure and functions of the urban 

forest can be used to improve and augment support for urban forest management 

programs and to integrate urban forests within plans to improve environmental 

quality in the Philadelphia area.

KEY WORDS: urban forestry, ecosystem services, air pollution removal, carbon 

sequestration, tree value

Manuscript received for publication 5 December 2006
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Capitalizing on the strengths of existing science 

capacity in the Northeast and Midwest to attain a more 

integrated, cohesive, landscape-scale research program