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Quantifying air pollution removal by green roofs in Chicago


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The level of air pollution removal by green roofs in Chicago was quantified using a dry deposition model. The result showed that a total of 1675 kg of air pollutants was removed by 19.8 ha of green roofs in one year with O3 accounting for 52% of the total, NO2 (27%), PM10 (14%), and SO2 (7%). The highest level of air pollution removal occurred in May and the lowest in February. The annual removal per hectare of green roof was 85 kg ha−1 yr−1. The amount of pollutants removed would increase to 2046.89 metric tons if all rooftops in Chicago were covered with intensive green roofs. Although costly, the installation of green roofs could be justified in the long run if the environmental benefits were considered. The green roof can be used to supplement the use of urban trees in air pollution control, especially in situations where land and public funds are not readily available.
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Quantifying air pollution removal by green roofs in Chicago
Jun Yang
, Qian Yu
, Peng Gong
Department of Landscape Architecture and Horticulture, Temple University, 580 Meetinghouse Road, Ambler, PA 19002, USA
Department of Geosciences, University of Massachusetts, 611 N Pleasant Street, Amherst, MA 01003, USA
State Key Lab of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Science and Beijing Normal
University, Beijing 100101, China
article info
Article history:
Received 17 March 2008
Received in revised form 30 June 2008
Accepted 2 July 2008
Extensive green roofs
Intensive green roofs
Dry deposition
The level of air pollution removal by green roofs in Chicago was quantified using a dry
deposition model. The result showed that a total of 1675 kg of air pollutants was removed
by 19.8 ha of green roofs in one year with O
accounting for 52% of the total, NO
(14%), and SO
(7%). The highest level of air pollution removal occurred in May and
the lowest in February. The annual removal per hectare of green roof was 85 kg ha
The amount of pollutants removed would increase to 2046.89 metric tons if all rooftops in
Chicago were covered with intensive green roofs. Although costly, the installation of green
roofs could be justified in the long run if the environmental benefits were considered. The
green roof can be used to supplement the use of urban trees in air pollution control,
especially in situations where land and public funds are not readily available.
Ó2008 Elsevier Ltd. All rights reserved.
1. Introduction
City air often contains high levels of pollutants that are
harmful to human health (Mayer, 1999). The American
Lung Association (ALA, 2007) reported that over 3700
premature deaths annually in the United States could be
attributed to a 10-ppb increase in O
levels. Worldwide, the
World Health Organization (WHO, 2002) estimated that
more than 1 million premature deaths annually could be
attributed to urban air pollution in developing countries.
The United Nations Population Fund (UNFPA, 2007)pre-
dicted that the urban population worldwide would
increase from 3.3 billion in 2008 to 5 billion by 2030,
meaning that there will be an increase in sensitive pop-
ulation groups such as children and the elderly. Therefore,
cities with serious air pollution problems need to come up
with ways to control the problem and reduce the damages.
Conventional air pollution management programs focus
on controlling the source of air pollutants (Schnelle and
Brown, 2002). This strategy effectively reduces the emis-
sion of new air pollutants but does not address the
pollutants already in the air. Innovative approaches can be
adopted to remove existing air pollutants thereby reducing
air pollution concentrations to an acceptable level. One way
to reach that goal is the use of urban vegetation which can
reduce air pollutants through a dry deposition process and
microclimate effects. The high surface area and roughness
provided by the branches, twigs, and foliage make vege-
tation an effective sink for air pollutants (Beckett et al.,
1998; Hill, 1971). Vegetation also has an indirect effect on
pollution reduction by modifying microclimates. Plants
lower the indoor air temperature through shading, thus
reducing the use of electricity for air conditioning (Heisler,
1986). The final result is that the emission of pollutants
from power plants decreases due to reduced energy use.
Vegetation also lowers the ambient air temperature by
changing the albedos of urban surfaces and evapotranspi-
ration cooling. The lowered ambient temperature then
slows down photochemical reactions and leads to less
secondary air pollutants, such as ozone (Akbari, 2002;
*Corresponding author. Department of Landscape Architecture and
Horticulture, Temple University, 580 Meetinghouse Road, Ambler, PA
19002, USA. Tel.: þ1 267 468 8186; fax: þ1 267 468 8188.
E-mail addresses: (J. Yang),
(Q. Yu), (P. Gong).
Contents lists available at ScienceDirect
Atmospheric Environment
journal homepage:
1352-2310/$ – see front matter Ó2008 Elsevier Ltd. All rights reserved.
Atmospheric Environment 42 (2008) 7266–7273
Rosenfeld et al., 1998). Studies show that trees could
contribute significantly to air pollution reduction in cities
(Nowak, 1994; Nowak et al., 2006; Rosenfeld et al., 1998;
Scott et al., 1998). Nowak et al. (2006) estimated that urban
trees remove a total of 711000 metric tons annually in the
U.S. These findings led to the inclusion of tree planting as
a state implementation strategy for improving air quality
by the United States Environmental Protection Agency
(EPA) in 2004 (US EPA, 2004).
While it is desirable to use trees for controlling air
pollution, it is not always easy to plant trees in a densely
populated city. For example, the percentage of impervious
area in New York City is 64%; it can reach as high as 94% in
districts like Mid-Manhattan west (Rosenzweig et al., 2006 ).
The green roof can be a solution to this dilemma since it
makes use of rooftops, usually 40–50% of the impermeable
area in a city (Dunnett and Kingsbury, 2004). Nevertheless,
the limited number of studies on the air pollutant removal
capacity of green roofs does not provide enough informa-
tion for people to judge their effectiveness in air pollution
control. The methods and main findings of the few reported
studies are summarized in the following section.
Currie and Bass (2005) estimated that 109 ha of green
roofs in Toronto could remove a total of 7.87 metric tons of
air pollutants annually. They pointed out in their paper that
the urban forest effects (UFORE) model they used was
developed specifically for trees and shrubs. The majority of
plants used on green roofs are herbaceous plants which
would have an impact on estimates when using this model.
Deutsch et al. (2005) conducted a simulation of different
planting scenarios of green roofs in Washington, DC, using
the UFORE model. They showed that 58 metric tons of air
pollutants could be removed if all the roofs in the city were
converted to green roofs. Corrie et al. (2005) estimated the
annual reduction of NO
by green roofs in Chicago and
Detroit. Their study showed by covering 20% of the roof
surface in Chicago the reduction of NO
was between 806.48
and 2769.89 metric tons depending on the type of plants
used. These estimates were reached by assuming the NO
uptake rates by green roof plants were constant. This could
be problematic because NO
uptake is influenced by many
factors (e.g., meteorological conditions, concentration of
, plant physiology). In one field study, Tan and Sia (2005)
measured the concentrations of acidic gaseous pollutants
and particulate matters on a 4000 m
roof in Singapore
before and after the installation of a green roof. They found
that the levels of particles and SO
in air above the roof were
reduced by 6% and 37%, respectively, after installation of the
green roof. This field measurement proved that green roofs
can reduce certain air pollutants but it is difficult to
extrapolate their results to other places or to a larger scale.
The measurement was site specific and the volume of air
that was influenced by the green roof was not given.
The cases discussed above have shown the potential
benefit of using green roofs in air pollution control.
However, there are many aspects of this mitigation
measure that remain unclear. More studies are needed to
help cities decide whether the green roof can be an effec-
tive way to improve air quality. We believe the following
questions need to be answered: How can we quantify the
level of air pollutant removal after installing green roofs in
one city? Is there a difference between different types of
green roofs in the level of air pollutant removal? How does
the green roof compare to other mitigation measures such
as planting trees? In this paper, we will address those
questions with a case study in Chicago, Illinois.
2. Study site and methods
2.1. Study site
This study took place in Chicago, Illinois, which is
located along the southwest shore of Lake Michigan with
a center coordinate of 41
N and 87
W. The total area
of the city is 588.3 km
. Chicago is the third most populous
city in the U.S with a population of 2.9 million in 2000.
According to ALA (2007), over 2 million people in Chicago
were at heightened risk for health problems resulting from
acute exposure to O
and particulate matters.
Chicago is ranked number one in terms of total area of
installed green roofs among North American cities.
According to Taylor (2007), green roofs were installed on
300 buildings resulting in a total area of 27.87 ha by June
2007. There are three types of green roofs in Chicago:
extensive green roofs, intensive green roofs, and semi-
intensive green roofs. Extensive green roofs are planted
with low height and slow growing plants. The depth of the
growth media is less than 15 cm. Intensive green roofs
consist of large perennial herbaceous plants and, occa-
sionally, shrubs and small trees. The depth of growth media
on an intensive green roof usually varies between 20 cm
and 1.2 m. The semi-intensive green roof is a mixture of
extensive and intensive green roof with 25% or less of the
area as extensive green roof.
2.2. Survey of green roofs in Chicago
A request for information was submitted to Chicago’s
Department of Environment for a list of green roofs
resulting in a list of 170 green roofs. Two steps were taken
to verify the list. First, information including the address of
the green roof, type of the green roof, size, and the date it
was completed was gathered from various sources. We
then searched the address of each green roof through an
image database hosted by Pictometry International Crop.
Digital aerial photographs covering Chicago were taken by
Pictometry International Corp in July 2006. Because the
photographs have a ground resolution of 16 cm and were
taken from multiple angles, the location, size, type of the
green roof, and the type of building could be clearly inter-
preted. For each green roof, the area of grass, trees, and
other surfaces was measured and the percentage to the
total area was calculated. Pictometry software allows users
to directly measure distances and areas on those geore-
ferenced images. The error margin of the measurement was
estimated to be 1% or smaller (Federal Emergency
Management Agency, 2005).
2.3. Removal of air pollutants by green roofs
In this study, a big-leaf resistance model was used to
quantify the dry deposition of air pollutants. The structure
J. Yang et al. / Atmospheric Environment 42 (2008) 7266–7273 7267
of the model and how the input parameters were fitted are
explained below.
The removal of a particular air pollutant at a given place
over a certain time period was calculated as (Nowak, 1994):
where Qis the amount of a particular air pollutant removed
by certain area of green roofs in a certain time period (g), F
is the pollutant flux (g m
), Lis the total area of green
roof (m
), and Tis the time period (s). The pollutant flux Fis
calculated as in Eq. (2):
where V
¼dry deposition velocity of a particular air
pollutant (cm s
), and C¼concentration of that pollutant
in the air (
). The dry deposition process can be
described as the inverse of total resistance (Baldocchi et al.,
where R
¼aerodynamic resistance, R
boundary layer, and R
¼canopy resistance. The algorithms
for calculating R
and R
were reported in Yang et al. (2005).
In this study, the roughness length z
and displacement
length dfor short grasses were used to represent extensive
green roofs. The intensive green roofs were treated as
mixtures of short grass, tall herbaceous plants, and small
deciduous tree. The z
and dvalues used in the model are
listed in Table 1.
The hourly canopy resistances R
for O
, and NO
are calculated as (Walmsley and Wesely, 1996).
Rc¼hðRsx þRmxÞ1þR1
þðRdc þRclxÞ1þRac þRgsx 1i1(4)
In Eq. (4),R
is leaf stomata resistance, R
is leaf meso-
phyll resistance, R
is leaf cuticles resistance, R
is the
resistance for gas-phase transfer by buoyant convection in
canopies, R
is resistance by leaves, twigs, bark or other
exposed surfaces in the lower canopy, R
is transfer resis-
tance which depends only on canopy height and density,
and R
is ground surface resistance. Resistance compo-
nents can vary with solar intensity, seasons, and vegetation
types. Algorithms are available for calculating resistance
components for grass and deciduous trees. The tall herba-
ceous plants were modeled as crops in this study. Details of
the algorithms were described in Wesely (1989);Walmsley
and Wesely (1996);Zhang et al. (2002).
The deposition velocity of PM over green roofs was
calculated as (Zhang et al., 2001).
Where V
is the gravitational settling velocity, R
is the
aerodynamic resistance above the canopy, R
is the surface
The gravitational settling is calculated as.
is the density of the particle, in this study, a value
of 1800 kg m
was used as suggested by Lim et al. (2006),
is the particle diameter, gis the acceleration of gravity, C
is the correction factor for small particles and is calculated
as (Zhang et al., 2001),
is the viscosity coefficient of air.
The aerodynamic resistance R
is calculated as before.
The surface resistance R
is based on the size of deposition
particles, atmospheric conditions, and surface properties. It
was calculated as (Zhang et al., 2001).
is an empirical constant and taken as 3 here,
the friction velocity. E
, and E
are collection efficiency
from Brownian diffusion, impaction and interception,
respectively. The re-suspension of particles after hitting
a surface was modeled by modifying the total collection
efficiency by the factor of R
, which represents the fraction
of particles sticking to the surfaces. The extensive green
roofs and intensive green roofs were modeled in the same
manner as in calculating R
. Details on how those param-
eters were fitted can be found in Zhang et al. (2001).
The final deposition velocity for PM
was the weight-
averaged V
for all particles with a size less than 10
Information on size classes and mass concentration of
particles in Chicago were obtained from Offenberg and
Baker (2000).
Hourly air pollution data including NO
, and
concentration from an air pollution monitoring
station in central Chicago between 8/1/2006 and 7/31/2007
were obtained from the U.S. EPA. Hourly surface meteo-
rology data including sky condition, air temperature, rela-
tive humidity, atmospheric pressure, wind speed,
precipitation, and snow cover measured by a station located
at O’Hara International Airport for the same time period
was obtained from the National Climatic Data Center. The
hourly solar radiation intensity was simulated by using the
meteorological/statistical solar radiation model (METSTAT,
Maxwell et al., 1995). During precipitation and when the
ground was covered by snow, the value of V
was set as zero
because the dry deposition process could not occur. Hourly
fluxes of NO
, and PM
to green roofs in Chicago
were calculated by using weather data, concentration of
pollutants, and the modeled deposition velocities.
2.4. Additional removal with different planting
scenarios and costs
Three future planting scenarios were assumed and the
amount of air pollutionremoval for each scenario calculated.
Table 1
Value of roughness lengths and displacement heights used in the model
height h
(m) d¼0.7h
Short grass 0.15 0.015 0.105
Tall herbaceous plants 1.0 0.1 0.7
Deciduous trees 5.0 0.5 3.5
J. Yang et al. / Atmospheric Environment 42 (2008) 7266–72737268
The first scenario assumed planting all roofs in Chicago with
the same ratio of extensive vs. intensive green roofs used
currently. The second scenario assumed the remaining roofs
would only be planted with extensive roofs. The third
scenario assumed only intensive roofs would be used in
future projects. In all these scenarios, the intensive roof was
treated as a mixture of tall herbaceous plants and small
deciduous trees and shrubs at a ratio of 50:50. The total area
of roofs in Chicago was obtained from Gray and Finster
(2000) study, which showed that Chicago’s roof surface was
27.86% of the urban area. According to information gathered
from the green roof companies and the literature, the
average installation cost for green roofs are as follows:
extensive green roofs between $107.64 and $161.46 per m
($10–$15 per ft
); intensive green roofs between $161.46
and $269.1 per m
($10––$25 per ft
). The medians of those
ranges were used in the calculation. The maintenancecost of
green roofs was not included in this calculation.
3. Results
Among the 170 green roofs included in the list, detailed
information for 71 green roofs was obtained and verified
through aerial photographs. The total area of those 71
green roofs is 19.8 ha, 71% of the total area of green roofs in
Chicago reported by Taylor (2007).
The information about those green roofs is shown in
Table 2.
The green roofs surveyed were located mainly on
commercial building and the size of each individual roof
was relatively large. Among the 71 green roofs, half had an
area larger than 500 m
and 23 green roofs were larger than
1000 m
. The green roof in the Soldier Field was 22 445 m
while the one in Millennium Park was 99 983 m
Based on the analysis of aerial photographs, the 19.8 ha
of green roof consisted of 63% short grass and other low
growing plants, 14% large herbaceous plants, 11% trees and
shrubs, and about 12% various structures and hard surfaces.
The monthly air quality between August 2006 and July
2007 in Chicago is shown below (Fig. 1).
It can be seen from Fig. 1 that O
was the main air
pollutant in Chicago. PM
ranked second while the SO
pollution was low. PM
and O
pollution peaked in
summer while SO
and NO
peaked in winter.
The monthly mean deposition velocities for air pollut-
ants calculated for different vegetation types showed
a seasonal trend (Table 3). The deposition velocities for all
air pollutants were highest in May and lowest in February.
The modeled monthly uptake of air pollutants by green
roofs is shown in Fig. 2.
The total air pollution removal by 19.8 ha of green roofs
was 1675 kg between August 2006 and July 2007. If the
reported 27.87 ha of green roofs were all completed and
had the same ratio of extensive vs. intensive green roofs,
the air pollutants removed could reach 2388 kg.
Among the four air pollutants, the uptake of O
was the
largest, 52% of the total uptake followed by NO
(27%), PM
(14%), and SO
(7%). Seasonally, the highest uptake
occurred in May and the lowest in February. The annual
removal rate among different vegetation types is compared
in Table 4.
If all remaining roofs in Chicago were planted with
intensive green roofs, the direct removal of air pollutants
could reach as high as 2046.89 metric tons, assuming the
same level of air pollution as 2006–2007. However, the
installation cost would be $35.2 billion.
4. Discussion
4.1. Evaluation of results
The results showed that air pollutant removal by green
roofs in Chicago was affected by air pollutant concentra-
tions, weather conditions, and the growth of plants. The
highest air pollutant removal occurred in May when leaves
of plants were fully expanded and the concentration of
pollutants was high. The lowest removal was in February
when the vegetation was covered in snow. The reliability of
the estimate was evaluated by comparing it to values
reported in other studies.
The dry deposition velocities of air pollutants influence
the magnitude of air pollutant removal most. We found
that the modeled deposition velocities were within
a reasonable range compared to the measured values
reported in the literature (Tables 4 and 6). It should be
noted that the size of PM has a strong influence on the
deposition velocity. In Chicago, Offenberg and Baker (2000)
found that the bulk mass of PM was at particles with a d
less than 2
m. The modeled V
values for PM
in this
Table 2
Percentages of different type of green roofs in Chicago
Type of green roof On residential
buildings (%)
On commercial
buildings (%)
On office
buildings (%)
Total (%)
Extensive 4.05 20.55 7.98 32.58
0.10 61.42 5.90 67.42
Sub total (%) 4.15 81.97 13.88 100.00
Concentration (ug/m3)
NO2 by Month
Fig. 1. Concentrations of criteria air pollutants in Chicago between August
2006 and July 2007. The monthly mean values were shown in the figure.
J. Yang et al. / Atmospheric Environment 42 (2008) 7266–7273 7269
study were comparable to the values for fine particles
reported in the literature.
The removal rate was compared to the removal rate of
air pollutants, including SO
, and O
, extracted
from similar studies. The results showed that the annual
removal per hectare of green roof was 85 kg ha
the annual removal per hectare of canopy cover was
97 kg ha
. The annual removal per hectare of canopy
cover reported in this study was higher than the removal
rate of 69 kg ha
estimated for green roofs in Toronto
by Currie and Bass (2005).Deutsch et al. (2005) reported
a removal rate of 77 kg ha
for Washington, DC. As
suggested by Nowak et al. (2006), the different pollution
removal rates among cities can be caused by factors such as
the amount of vegetation cover, pollution concentration,
length of growing season, and meteorological conditions.
Furthermore, the different methods used in modeling the
air pollution removal by grass and large herbaceous plants
in those studies also contributed to difference in results.
Currie and Bass (2005) did not model grass and large
herbaceous plants separately. Instead, they adjusted the
estimated V
value of air pollutants from trees to grasses by
using the ratio of leaf area index (LAI) of grasses to trees
(3:6). The ratio of 1:2 was supported by Shreffler (1978)
study on modeled deposition velocity for SO
over grass-
lands vs. forests. However, based on the V
values modeled
in this study, and also from the observed values reported in
the literature (Table 6), we found that the V
values of air
pollutants for trees may not always be two times those of
grass and large herbaceous plants. Finally, the UFORE
model tends to give conservative estimation of PM
removal because it assumes a fixed deposition velocity of
0.064 m s
and a 50% re-suspension rate for PM
et al., 2006). As pointed out by Ould-Dada and Baghini
(2001), the 50% re-suspension was much larger than the re-
suspension rate they measured for fine particles. All those
differences can lead to the relatively high removal rates
reported in this study.
4.2. Uncertainties of the approach
The estimated air pollutant removal for green roofs in
Chicago should be treated as an approximation rather than
an accurate estimation of actual air pollution removal.
Several uncertainties should be noted. The green roofs in
Chicago were generalized as continuous surfaces of short
grass, tall herbaceous plants, and deciduous trees with
uniform heights. This generalization was necessary for
running a big-leaf model at a city scale. Nevertheless,
small-scale effects such as the differing heights of green
roofs, arrangement of vegetation, and relation to the
geometry of street canyons could influence turbulence and
Uptake by green roofs (kg)
NO2 by Month SO2
O3 PM10
Fig. 2. Monthly uptake of air pollutants by green roofs in Chicago between August 2006 and July 20 07.
Table 3
Annual removal rate of air pollutants per canopy cover by different vegetation types in Chicago between August 2006 and July 2007
Type of vegetation SO
(g m
(g m
(g m
(g m
) Total (g m
Short grass 0.65 2.33 1.12 4.49 8.59
Tall herbaceous plants 0.83 2.94 1.52 5.81 11.10
Deciduous trees 1.01 3.57 2.16 7.17 13.91
The non-vegetated surfaces were excluded from the calculation.
J. Yang et al. / Atmospheric Environment 42 (2008) 7266–72737270
transport in wind canopies (McDonald et al., 2007). The
concentrations of air pollutants were considered uniform
for the entire study area. This assumption works for situa-
tions where a well-mixed boundary layer exists in daytime
under unstable conditions (Colbeck and Harrison, 1985).
Nevertheless, the influence of buildings and the distances
to sources of emission could cause the concentrations of air
pollutants to vary spatially. Green roofs close to highly
polluted streets could have higher uptake of air pollutants
than those located in relatively clean areas.
Another source of uncertainty is the way the V
modeled. The resistance components were modeled by
simplifying all plants into three prototypes: grass, crops,
and deciduous trees. Values adopted from existing litera-
tures were used to represent the vegetation characteristics.
However, the differences among plant species (e.g.,
photosynthetic pathways, stomatal densities, LAI, growth
speed) can introduce uncertainties into the estimate of V
In the future, more field measurements on the dry depo-
sition velocities of pollutants on urban grass should be
conducted to calibrate the dry deposition model and verify
the modeling results.
Finally, green roofs can also become a source of pollut-
ants. Pollens produced by plants and erosion of growth
media under a strong wind can increase particle pollution
(Tan and Sia, 2005). Plants can also emit volatile organic
compounds (VOC) that can result in O
(Benjamin and Winer, 1998). Those factors were not
considered in this study but they can potentially lower the
estimate of air pollutant removal by green roofs.
4.3. Practical considerations
It can be seen from Table 5 that a large amount of air
pollutants can be removed if all roofs in Chicago were
converted to green roofs. However, it was also obvious that
the cost of constructing the specified area of green roofs
would be prohibitively high. Compared to the cost of
traditional air pollution controls, between $935 per metric
ton for CO and $4482 per metric ton for NO
1994), the green roof is not an economically viable measure
in air pollution control.
Although the removal rate of 97 kg ha
comparable to the removal rates for urban forests reported
by Nowak et al. (2006) in 55 cities, which range between
59 kg ha
and 168 kg ha
, green roofs cost more
than planting trees. Based on the results of Nowak (1994),
a medium size tree can remove the same amount of air
pollutants as a 19 m
extensive green roof in one year but
the planting costs for them are around $400 and $3059,
Even with their high cost, there are several reasons why
the green roof is a viable alternative to trees in air pollution
control. The high initial installation cost of a green roof can
be justified by its long-term benefits. Benefits contributed
by green roofs include reduction of storm water runoff,
saving energy, reducing urban heat islands, and extending
the life span of roofs (Carter and Keeler, 2007; Wong et al.,
2003). Acks (2005) did a cost-benefit analysis of several
planting scenarios of green roofs in New York City and
found the medium benefit/cost ratio was 1.02 over a period
of 55 years. The cost-benefit ratio of building green roofs
can be further improved by increasing the efficiency of air
pollutant removal and simultaneously lowering the
construction cost. Plant species used in green roofs can be
selected to increase the amount of air pollutants removed
and reduce the emission of VOC (Benjamin et al., 1996). The
construction and maintenance costs of a green roof can be
reduced if the industry is standardized and a complete
system for green roof production, delivery, and installation
is formed. Currently, as estimated by Philippi (2006), the
unit installation cost of the extensive green roof in the U.S.
was ten times that in Germany. Furthermore, unlike tree
planting programs where land has to be set aside for the
plantings, green roofs do not occupy land; they are built on
rooftops. This is an important factor for high-density urban
5. Conclusion
Air pollution in the urban environment is a major
threat to human health. As the global population is
becoming more concentrated in urbanized areas, new
ideas and approaches are needed to help maintain clean
air that is safe for everyone to breathe. This study eval-
uated one such innovative approach: using green roofs for
air pollution control. By using a big-leaf dry deposition
model, the air pollutants removed by green roofs in Chi-
cago were quantified. The result showed that the green
roofs in Chicago can remove a large amount of pollutants
from air. Currently, the green roof cannot be used as
a stand-alone measure in air pollution controls because of
its high cost. However, a comprehensive look at its envi-
ronmental benefits shows that it can be an effective
option to mitigate air pollution as well as other environ-
mental problems.
Table 5
Additional air pollution removal from planting more green roofs and the
estimated installation cost
Scenarios Total air
(metric tons)
Total installation
cost ($ million)
Cost of removal
($ million/
metric ton)
Current ratio 1835.23 3086.52 1.68
Extensive only 1405.50 2201.51 1.57
Intensive only 2046.89 3522.42 1.72
Table 4
Modeled deposition velocities of pollutants over different vegetation
Type of vegetation SO
(cm s
(cm s
(cm s
(cm s
Short grass 0.04 (0.005) 0.01 (0.001) 0.10 (0.005) 0.01 (0.001)
0.39 (0.006) 0.39 (0.006) 0.19 (0.003) 0.42 (0.007)
Tall herbaceous
0.04 (0.006) 0.01 (0.001) 0.10 (0.006) 0.01 (0.001)
0.48 (0.007) 0.49 (0.007) 0.25 (0.004) 0.54 (0.008)
Deciduous trees 0.05 (0.006) 0.01 (0.001) 0.13 (0.008) 0.01 (0.001)
0.57 (0.007) 0.58 (0.008) 0.36 (0.006) 0.65 (0.008)
The minimum and maximum monthly average deposition velocities were
shown here. The numbers inside the parenthesis were standard errors.
J. Yang et al. / Atmospheric Environment 42 (2008) 7266–7273 7271
We thank two anonymous reviewers for their helpful
suggestions on the manuscript. Also, we express our
appreciation to Department of Environment, Chicago
City for directing us to information on green roofs in
Chicago. Finally, we thank Pictometry International Corp
for providing us the free trial of the image database.
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Table 6
Observed deposition velocities of SO
, and O
over different vegetation types reported in the literature
Pollutants Vegetation
in m)
(cm s
Short grass (0.1) 0.2 0.1–0.4 0.2 Sorimachi et al. (2003)
Grass (0.3) 0.6–0.8 Feliciano et al. (2001)
Heathland 0.8 0.4 Erisman et al. (1993)
Grassland 1.20.3 Erisman et al. (1993)
Grassland (0.1–0.8) 0.4–0.7 Pio and Feliciano (1996)
Deciduous forest 0.480.45 Zhang et al. (2002)
Deciduous forest (22) 0.30–1.04 Finkelstein (2001)
Heathland 0.10–0.35 Coe and Gallagher (1992)
Grass (0.15) 0.27 0.017 Watt et al. (2004)
Wheat 0–0.35 Pilegaard et al. (1998)
Grassland 0.11–0.24 Hesterberg et al. (1996)
Orchard (2.1) 0.2–0.6 Walton et al. (1997)
Coniferous forest 0.4 Rondo
´n et al. (1993)
Short grass (0.1) 0.2 0.2–0.4 0.3 Sorimachi et al. (2003)
Grassland (0.22) 0.22–0.36 Stocker et al. (1993)
Grass (0.1–0.8) 0.1–0.5 Pio et al. (2000)
Mooreland 0.2–0.7 Fowler et al. (2001)
Deciduous trees (33) 0.2–1.0 Padro (1996)
Deciduous forest (22) 0.10–0.75 Finkelstein (2001)
Grass (0.06) 0.16–0.12 (d
¼5) Chamberlain (1967)
Nature grass (0.3–0.5) 0.22 0.06 Wesely et al. (1985)
Rye grass (0.75–1) 0.16 0.072 (NGMD ¼0.52) Vong et al. (2004)
Urban grass (0.1–0.25) 0.33–0.38 (d
¼0.6–0.8) Fowler et al. (2004)
Urban woods (25) 0.7–1.07 (d
Deciduous trees (22) 0.1 (d
<2) Hicks et al. (1989)
Beach (24–25) 0.45 (NGMD
¼0.02–0.03) Pryor (2006)
0.15 (NGMD
NGMD is the number geometrical mean diameter (
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... These areas, including the city centre and main routes to the centre, are characterised by city canyons and high vehicle traffic, with a high proportion of bus shelters. Pollution management programmes, including Cleaner Air for Scotland-The Road to a Healthier Future [52], only focus on the source of pollution instead of addressing already produced air pollution as well [56]. While many cities have mandated the incorporation of green infrastructure on all new buildings, Edinburgh has not yet introduced such a mandate. ...
... Removal levels of SO 2 , NO 2 , PM 10 , and O 3 were calculated for an area of EGRs. B£ST's default values of removal levels based on the studies by Yang et al. [56] and Currie and Bass [33] were used ( Table 2). The pollutant removal monetary value was not available for O 3 and, therefore, was excluded from the benefit value estimation. ...
... However, the O 3 sequestration value was not included due to the lack of data in the B£ST analysis. In previous studies, a green roof with short grass sequestered 4.3 g/m 2 of O 3 , which constituted the highest portion (52%) of all sequestered pollutants (O 3 , NO 2 , PM 10 , SO 2 ) [56]. In Toronto, O 3 sequestration posed 41.7% of the total pollutant sequestration [33]. ...
Full-text available
The presence of green roofs in urban areas provides various ecosystem services that help mitigate climate change. They play an essential role in sustainable drainage systems, contribute to air quality and carbon sequestration, mitigate urban heat island, support biodiversity, and create green spaces supporting public well-being. Bus stops provide good opportunities for installing green roofs. Various cities worldwide have started installing green roofs on bus shelters, but often without thoroughly comparing expenses and the resulting benefits. This study quantifies the social and environmental benefits of installing green roofs on bus shelters in the City of Edinburgh. An assessment of the benefits and their monetary values was conducted using the B£ST analysis tool combined with manual calculations, which is easily transferable to other cities worldwide. It was compared to the current situation with no green roofs installed at bus stops. Installation of green roofs on all bus shelters in the City of Edinburgh may result in £12.9 million–£87.2 million in total benefit present value. The total cost was projected to be £15,994,000. By green roof installation, the City of Edinburgh can be closer to being carbon-neutral by 2030, a sustainable city as part of the City Plan 2030 and City Vision 2050.
... Applications of green infrastructure, such as green roofs and walls, have demonstrated an improvement in air quality and regulation of temperature, in addition to improving human health outcomes associated with air pollution and extreme heat [35,[38][39][40][41][54][55][56][57][58][59][60][61][62][63][64]. Deposition and immobilization of localized air pollutants such as ozone, nitrogen dioxide, and particulate ma er occurs through the application of green roofs, green walls, and urban vegetation and forestry, which can ameliorate local air quality [32,33,[35][36][37]44,54,60,[63][64][65][66][67]. ...
... Green infrastructure research to date has primarily focused on specific applications and discrete benefits [32][33][34][35][36][37]42,43,45,46,53,54,57,60,62,63,67,[73][74][75][76][77][78][79][80][81]. Studies of the air quality benefits of green infrastructure have examined individual applications of green infrastructure [35][36][37]54,66,67]. ...
... Analyses of the data collected to measure the potential of green infrastructure to reduce nitrogen dioxide concentrations is consistent with the hypothesis that green infrastructure can remediate air pollution in Southern Ontario, Canada, regardless of location, geography, or land-use type. The potential of green infrastructure to remediate air pollution is well-established in the literature [30][31][32][33][35][36][37][38]40,51,63,66,[77][78][79][80]. In this work, we used these microscale results to provide both a source and sink lens rather than just a source lens to interpret the atmospheric distribution of nitrogen dioxide. ...
Full-text available
Green infrastructure is a nature-based solution that supports sustainable development and restores urban, suburban, and peri-urban environments. Using a multi-scale evaluation, this study explores the impact of the application of green infrastructure, as a form of atmospheric cleansing, on tropospheric nitrogen dioxide. The impacts are not limited to specific green infrastructure treatments nor geographic location and land use type. Using both site-specific stationary air monitoring and coarser resolution satellite derived remote sensing, this study demonstrates the nature-based remediation effect of green infrastructure on nitrogen dioxide concentrations in Southern Ontario, Canada. At these scales, remote sensing and stationary air monitoring observations support the hypothesis that green infrastructure can cleanse the atmosphere by reducing nitrogen dioxide through scavenging by trees and dense vegetation at the neighbourhood level, consistent with the findings from microscale field campaigns. The study showed a clear link between compact, built-up, industrialized areas and higher nitrogen dioxide levels at the mesoscale, particularly notable to the west of the city of Toronto. Nature-based solutions provide an opportunity to address the impacts of urbanization, increase climate resilience, and support healthy urban environments.
... In Singapore, emissions of sulphur dioxide and nitrite directly acting on green roofs were reduced by 37% and 21% (Tan and Sia, 2005). According to Yang et al. (2008) research, if all of Chicago's roofs were designed to be intensive, 2,046.89 metric tonnes of pollutants could be removed, and the installation cost to complete the work was estimated at USD 35.2 billion. ...
... Several additional benefits are associated with the utilization of green roofs that, while not explicitly addressed in the bibliometric review conducted in this study, are extensively examined and deliberated upon within the scientific literature. These include but are not limited to the mitigation of air pollution, as explored by (Yang 2008;Speak et al. 2012;Shafique et al. 2020). Furthermore, green roofs contribute to ameliorating urban heat islands (Klein and Coffman 2015;Mutani and Todeschi 2020). ...
This study brings a systematic review that evaluated 43 articles on Nature-Based Solutions (NBS) applied to stormwater management in urban areas. This review aims to establish a reference on NBS effectively applied and whose environmental, social, and economic benefits have been duly discussed. The results address 13 NBS techniques/methodologies implemented and their ecosystem benefits. Our findings suggest that the multifunctional nature of NBS makes it challenging to categorize environmental services and social benefits since there are multiple interactions and scales among the various benefits of NBS. Most studies have made greater efforts in approaches that use modeling, test benches, and/or laboratory facilities. However, although they work well for their purposes, there is no guarantee that the benefits will be maintained when applied on a full scale. We concluded that only a few studies scientifically evaluated the performance of installed NBS infrastructures, almost all in developed countries.
... Calculating the ESs and ecosystem disservices (EDs) of constructed wetlands in urban areas is a complex task, and previous researchers have explored different methods, including economic or monetary approaches. For instance, Yang et al. (2008) assessed the economic values of a constructed wetland system's ES through the contingent valuation method in Hangzhou, China. The contingent valuation method measured the total economic value of the constructed wetland at 800000 yuan over a 20-year period. ...
Climate change and rapid urbanization are pressing environmental and social concerns, with approximately 56% of the global population living in urban areas. This number is expected to rise to 68% by 2050, leading to the expansion of cities and encroachment upon natural areas, including wetlands, causing their degradation and fragmentation. To mitigate these challenges, green and blue infrastructures (GBIs), such as constructed wetlands, have been proposed to emulate and replace the functions of natural wetlands. This study evaluates the potential of eight constructed wetlands near Beijing, China, focusing on their ecosystem services (ESs), cost savings related to human health, growing/maintenance expenses, and disservices using an emergy-based assessment procedure. The results indicate that all constructed wetlands effectively purify wastewater, reducing nutrient concentrations (e.g., total nitrogen, total phosphorus, and total suspended solids). Among the studied wetlands, the integrated vertical subsurface flow constructed wetland (CW-4) demonstrates the highest wastewater purification capability (1.63E+14 sej/m2/yr) compared to other types (6.78E+13 and 2.08E+13 sej/m2/yr). Additionally, constructed wetlands contribute to flood mitigation, groundwater recharge, wildlife habitat protection, and carbon sequestration, resembling the functions of natural wetlands. However, the implementation of constructed wetlands in cities is not without challenges, including greenhouse gas emissions, green waste management, mosquito issues, and disturbances in the surrounding urban areas, negatively impacting residents. The ternary phase diagram reveals that all constructed wetlands provide more benefits than costs and impacts. CW-4 shows the highest benefit-cost ratio, reaching 50%, while free water surface constructed wetland (CW-3) exhibits the lowest benefits (approximately 38%), higher impacts (approximately 25%), and lower costs (approximately 37%) compared to other wetlands. The study advocates the use of an emergy approach as a reliable method to assess the quality of constructed wetlands, providing valuable insights for policymakers in selecting suitable constructed wetlands for effective urban ecological management.
... The sequestration capacity values differ based on the category of green area. For deciduous trees, the sequestration capacity is 0.11 µg⋅m − 2 ⋅s − 1 , for tall herbaceous plants it is 0.09 µg⋅m − 2 ⋅s − 1 , and for short grass it is 0.07 µg⋅m − 2 ⋅s − 1 (Yang et al., 2008). All green areas in the city are classified according to these values. ...
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In the first decades of the 21st century, urban agriculture has gained attention for its role in enhancing food security, particularly in developing nations. Additionally, it is commonly assumed that urban agriculture also has positive implications for other aspects of urban sustainability, such as mitigating runoff and creating job opportunities. However, the extent of these contributions has not been extensively quantified. This study aims to address this gap by presenting a stochastic model that quantifies the contributions of urban agriculture to urban sustainability, using Sant Feliu de Llobregat, a Mediterranean city, as a case study. We assessed eight indicators, including accessibility to green areas, food self-reliance, green surface area per capita, job creation, NO 2 sequestration, runoff mitigation, urban heat island effect, and volunteer participation. These indicators were estimated across twelve different simulated scenarios using 1000 Monte Carlo simulations for each scenario, to account for uncertainties. The findings revealed that the contributions of urban agriculture are not straightforward , as they are influenced by factors such as garden typology and location. Although urban agriculture typically originates as a grassroots movement, it often receives administrative support. Therefore, strategic planning can be employed to maximize the contributions of urban agriculture to urban sustainability and minimize trade-offs between social and environmental benefits.
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A dry deposition model was employed to estimate air pollutant uptake by Sacramento's urban forest. Assuming 1990 air pollutant concentrations, model simulations estimated that approximately 1,457 metric tons of air pollutant are absorbed annually, at an implied value of US$28.7 million. The growing season daily uptake for ozone was approximately 2.4 metric tons per day, while particulate matter (< 10 μ diameter, PM10) uptake was slightly greater, at 2.7 metric tons per day. Daily uptake of NO2 and particulate matter represented 1% to 2% of anthropogenic emissions for the county. Estimated growing-season annual air pollutant uptake rates averaged 10.9 kg/(ha land area per yr) for the entire study area, 13.9 kg/(ha land area per yr) for urban areas and 4.2 kg/(ha land area per yr) for rural areas. Pollutant uptake rates decreased with decreasing tree canopy cover, along an urban-to-rural gradient.
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Ozone deposition to vegetation represents the major sink for boundary layer ozone and yet the underlying mechanism of reaction and uptake at the surface is poorly understood. While overall rates of O3 deposition are known, the fractions of the flux absorbed by stomata and deposited to non-stomatal surfaces in the field have been poorly quantified. This paper reports 4 years of continuous fluxes by micrometeorological methods to moorland vegetation in southern Scotland. The flux has been partitioned between stomatal and non-stomatal fluxes and shows over a seasonal scale that the non-stomatal deposition (50 kg O3 ha− y−1) dominates the overall flux (77 kg O3 ha−1 y−1) and represents 70% of the total deposition. The surface resistance for non-stomatal O3 deposition (rns) decreases with temperature from 400 s m−1 at 0°C to 200 s m−1 at 15°C in dry conditions and is consistent with thermal decomposition of ozone at the surface with an apparent activation energy of about 36 kJ mole−1. The 4 years of continuous flux measurements show that stomatal conductance, when O3 concentrations are 80 µg m−3, is substantially smaller than for smaller O3 concentrations, although whether this is a response to VPD or O3 remains unclear.
An experiment was conducted to measure aerosol turbulent fluxes to a grass field. A new high-flow-rate aerosol sensor was deployed from a tower to make eddy correlation (EC) measurements of aerosol turbulent flux and deposition velocity. The EC data were screened and analysed for uncertainties associated with advection, boundary layer growth, instrument separation and counting particles. An apparent bias in the aerosol flux due to particle hygroscopic growth was evaluated from chemical and microphysical measurements and removed from the results based on derived corrections. The resulting aerosol deposition velocity for 0.52 μm diameter particles depended on atmospheric stability with values of 0.3 cm s −1 during near-neutral stability, 0.44 cm s −1 during unstable periods and 0.16 cm s −1 during stable periods with an estimated uncertainty of ±0.07 cm s −1 due to chemical composition and particle counting. DOI: 10.1111/j.1600-0889.2004.00098.x
Measurements have been made in the field and in a wind tunnel of the transport of Lycopodium spores to grass and other surfaces, and wind tunnel experiments also have been done with aerosols of various smaller particle sizes. The spores and other particles were made radioactive to enable the deposition of small numbers on rough surfaces to be detected. In principle the experiments in the wind tunnel were similar to those previously done with gases (Chamberlam 1966), but the mechanisms by which particles and gases are transported across the boundary layer are different. The velocity of deposition v_g of the particle to the surface is equal to the terminal velocity v_s if the wind speed is very small, but at higher speeds deposition by impaction on roughness elements becomes progressively more important. If the roughness elements are of a form which gives good impaction efficiency, and have a sticky surface, v_g is determined by the rate of eddy diffusion in the turbulent boundary layer above the surface, and may equal or even exceed the analogous velocity of deposition of momentum. The effect of surface texture and stickiness was investigated by comparing the catch of particles on segments of real leaves with the catch on similarity shaped segments of PVC treated with adhesive. Stickiness is important in determining v_g for particles of about 10 mum diameter upwards, but not for smaller particles. In the field experiments, the use of radioactive tagging enabled the presence of a few Lycopodium spores in several grams of grass or soil to be detected, and the deposition could be measured at ranges up to 100 m from the source. At low wind speeds, v_g was only a little greater than v_s but at higher speeds the contribution of impaction became evident. A particularly high value was obtained when the grass was wet after recent rain. The field results with Lycopodium give a ratio of velocity of deposition to wind speed of 0\cdot01, and this value is used to calculate the percentage of large spores or pollen grains which will travel various distances in normal meteorological conditions. It is found that the median range is about 1 km if the particles are liberated at a height of 50 cm, but 10 km if the height is 10 m. The relative importance of direct deposition to the ground and washout by ram of the air spora is considered, and is shown to depend on the effective height of the cloud of particles. For an effective height of 500 m, derived from vertical profiles of concentration observed from aircraft, it is calculated that about 25% of the total deposition of pollen grains may be in rain.