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Energy Conversion and Management 48 (2007) 1–8

Effect of urban climate on building integratedphotovoltaics performance

Wei Tian, Yiping Wang *, Jianbo Ren, Li Zhu

School of Chemical Engineering and Technology, Basic Experimental Center, No. 92 Weijin Road, Nankai District, Tianjin University,

Tianjin 300072, PR China

Received 4 June 2005; received in revised form 25 November 2005; accepted 30 May 2006Available online 10 July 2006

Abstract

It is generally recognized that BIPV (building integrated photovoltaics) has the potential to become a major source of renewableenergy in the urban environment. The actual output of a PV module in the field is a function of orientation, total irradiance, spectralirradiance, wind speed, air temperature, soiling and various system-related losses. In urban areas, the attenuation of solar radiationdue to air pollution is obvious, and the solar spectral content subsequently changes. The urban air temperature is higher than that inthe surrounding countryside, and the wind speed in urban areas is usually less than that in rural areas. Three different models of PVpower are used to investigate the effect of urban climate on PV performance. The results show that the dimming of solar radiation inthe urban environment is the main reason for the decrease of PV module output using the climatic data of urban and rural sites in MexicoCity for year 2003. The urban PV conversion efficiency is higher than that of the rural PV system because the PV module temperature inthe urban areas is slightly lower than that in the rural areas in the case. The DC power output of PV seems to be underestimated if thespectral response of PV in the urban environment is not taken into account based on the urban hourly meteorological data of Sao Paulofor year 2004.� 2006 Elsevier Ltd. All rights reserved.

Keywords: Urban climate; Building integrated photovoltaics; Global solar radiation; Spectral response

1. Introduction

For the first time, about half of the world’s population isliving in urban areas [1]. The rapid expansion of cities was adirect outcome of the fossil fuel economy that caused cli-mate change, fossil fuel depletion and environmental dam-age. It is generally recognized that PV (photovoltaics) inbuildings has the potential to become a major source ofrenewable energy in the urban environment. The Interna-tional Energy Agency PV Power Systems (PVPS) Task 10,Urban Scale PV Applications, is an international collabora-tive task bringing together architects, builders, financialexperts, utility personnel, municipal planners, the solarindustry and the educational sector to address the eco-

0196-8904/$ - see front matter � 2006 Elsevier Ltd. All rights reserved.

doi:10.1016/j.enconman.2006.05.015

* Corresponding author. Tel./fax: +86 22 27404771.E-mail address: tjtianjin@yahoo.com.cn (Y. Wang).

nomic, institutional, planning and technical issues necessaryto mainstream the use of PV in the urban environment [2].The process of urbanization involves transformation of theradiative, thermal, moisture and aerodynamic characteris-tics and thereby modifies the natural solar and hydrologicbalances [3]. The actual output of a PV system in the fieldis a function of orientation, total irradiance, spectral irradi-ance, wind speed, air temperature, soiling and various sys-tem-related losses [4]. Therefore, it is important tounderstand the effect of the urban climate on the BIPV per-formance to mainstream the use of PV in urban areas.Many researchers have investigated various aspects ofurban PV to develop this new technological application inurban areas [5–8]. However, few studies have been con-ducted on the influence of the urban climate on BIPV.Asl-Soleimani et al. [9] reported that air pollution in Tehrancan reduce the energy output of solar modules by more than

Nomenclature

A PV area (m2)AM air massB0 solar constant (W/m2 �C)Cf tilt correction factor of PV moduleCpv module heat capacity (J/�C)F view factorG solar radiation (W/m2)GH extraterrestrial solar radiation (W/m2)hn natural convection heat transfer coefficient

(W/m2 �C)I intensity coefficient for cell efficiencyIsc short circuit current (A)KT clearness indexNd total number of days per monthP atmospheric pressure (Pa)Pm maximum power output of PV under STC (W)Pmax power at maximum power point (W)P0 average pressure at sea level (Pa)Q monthly average daily electrical output of PV

module (J)q rate of heat exchange (W)Rs series resistance of solar cells (X)Ta ambient air temperature (�C)Tc PV temperature (�C)Tm monthly mean ambient temperature (�C)Tso surface temperature of PV module (�C)UL loss coefficient between cells and ambient

(W/m2 �C)

V wind speed (m/s)Voc open circuit voltage (V)

Greeks

A solar absorptance of PV moduleas incidence angle of solar radiationB temperature coefficient for cell efficiencyC intensity coefficient for cell efficiencyD Stefan–Boltzmann constantE surface emissivityH PV conversion efficiencyH PV tilt anglehM optimum tilt angle for maximum energy collec-

tionhZ zenith solar angleq solar reflectance between array and sun

SubscriptsB beam radiationD diffuse radiationg groundR ground radiationr reference conditionsra radiation heat transferw wind

2 W. Tian et al. / Energy Conversion and Management 48 (2007) 1–8

60%. Wang et al. [10] preliminarily analyzed the interactionbetween the urban microclimate and BIPV.

Several methods have been employed to study the urbanclimate: comparison of urban and rural meteorological sta-tions, analysis of climatic factor time series of stations thathave been included in the urban area due to growth of thecity and the method of transects around the city et al. Inthis study, the first method is used to analyze the impactof urban climate on the PV module performance incomparison with rural PV. The paper firstly introducesthe research progress of the urban climate that is relevantto the PV module performance. To evaluate the PVpower output, three different models were presented. Then,the performance of PV in urban areas was investigatedbased on the meteorological data in Mexico City and SaoPaulo.

2. Urban climate and BIPV performance

Urbanization and industrialization have resulted inmodification of local city climates. These alterations thataffect PV performance are listed in Table 1.

The electrical behavior of PV modules is mainly gov-erned by linear dependence on incident irradiance [4]. Short

wave solar radiation to urban areas is considerably chan-ged in its passage through the polluted atmosphere. Thedecrease of the incoming radiation depends on the natureand amount of pollutants. In a heavy industrial city, solarradiation may be reduced by 10–20% in comparison withits surrounding countryside [3]. Codato et al. [13] and Oli-veira et al. [14] measured the daily and hourly values ofsolar radiation for the cities of Sao Paulo (urban areas)and Botucatu (rural areas) and found that Sao Pauloreceives 16% less global solar radiation in June, 24% lessin July and 4% less in December than Botucatu. Somemore recent investigations have found extremely largeexcess attenuations in cities with significant industrial aer-osol or photochemical smog [15]. Jauregui and Luyando[16] reported that the city receives, on clear days, duringboth the dry and the rainy seasons, 21–22% less globalsolar radiation than the rural surroundings, and the globalradiation attenuation is directly related to air pollutionconcentration and relative humidity.

The efficiency of solar cells varies with cell temperature,light intensity, spectral energy distribution and light inci-dence angle. Performance ratios of systems have beendetermined experimentally in the range 60–85% of thoseat STC (standard test conditions) [17].

Table 1General alterations in climate created by cities

Variable Comparison with rural areas

Oke [11] Landsberg [12]Temperature 1–3 �C warmer per 100 years Annual mean 0.5–3.0 �C higher

1–3 �C annual mean Winter minimum 2.5–4.0 �C higherUp to 12 �C hourly mean Summer maximum 1.0–3.0 �C higher

Solar radiation Global less 1–25% Total, horizontal surface 0–12% lessUV radiation less 25–90% Ultraviolet winter 30% less

Ultraviolet summer 5% lessSunshine duration: 5–15% less

Wind speed Decreased 5–30% (at 10 m in strong flow) Mean 20–30% lowerIncreased in weak flow with heat island Extreme gusts 10–20% lower

Calms 5–20% more

W. Tian et al. / Energy Conversion and Management 48 (2007) 1–8 3

All PV devices are spectrally sensitive, and the solarspectrum on the ground changes with the distance the solarradiation has to travel through the atmosphere. In theurban–rural comparisons, there is general agreement thatthe irradiance from shorter wavelengths is more attenuatedby the urban atmosphere than that from longer wave-lengths [18]. Robaa [19] presents that the urban areareceives less global radiation and UV radiation by 7.0%and 17.8%, respectively, compared to the rural area as anannual average. The difference of the reduction betweenthem is because the radiation loss due to pollutant aerosolsis strongly wavelength dependent. The spectral distributionof direct solar radiation changes significantly over the day,while the spectral content of diffuse radiation remainsnominally the same [20]. Codato et al. [13] and Oliveiraet al. [14] observed that Sao Paulo (urban area) receives33% less direct solar radiation in June, 45% less in Julyand 10% less in December than Botucatu (rural area).The ratio of available to global solar radiation had a sea-sonal variation of 5% for polycrystalline silicon and 14%for amorphous silicon [21]. Hirata et al. [21] found thatthe output of PV modules varies from season to season,and this is directly related to the variation in spectral solarradiation.

As is well known, the power output of a PV moduledecreases with module temperature increase for crystallinesilicon modules. High ambient temperature and low windspeed lead to high module temperature. Urban heat islandrefers to the increase of air temperature in the near surfacelayer of the atmosphere within cities relative to their sur-rounding countryside. Combining the most favorable atmo-spheric and surface conditions, the maximum observed heatisland magnitudes are approximately 12 �C. More typically,heat island intensities are in the range 1–3 �C [22]. Jauregui[23] describes the near surface urban heat island of MexicoCity. The results show that midday heat islands have afrequency of 13% and an intensity of 3–5 �C during thewet season. The lower value of wind speed in the urbanarea may be attributed to the fact that wind speeds are gen-erally lower in built up areas than in their surroundingsresulting from the increase in surface roughness within cities[24].

3. BIPV performance model

In this section, three models of PV modules are describedto understand comprehensively the PV performance:monthly mean daily power generation, Model A; hourlyelectrical output with no solar spectral dependence, ModelB; and hour by hour system output with influence of the solarspectrum considered, Model C, in the urban environment.

3.1. Monthly average electrical output of PV module –

Model A

Evans [25] presents the method for predicting the longterm monthly average electrical output of a photovoltaicarray.

Q ¼ gA

PGi

Nd

ð1Þ

The monthly average array efficiency can be expressedas

g¼ grð1� bðT c � T aÞ � bðT a � T mÞ � bðT m � T rÞ þ clog10IÞð2Þ

A simple and effective correlation between the long termaverage parameters UL(Tc � Ta)/(aq) and the clearnessindexness KT can be written as

ULðT c � T aÞaq

¼ 0:219þ 0:932 KT ð3Þ

Typical meteorological year data for seven sites con-firmed the difference between the average temperature dur-ing solar radiation hours of the day and the mean monthlytemperature as

T a � T m ¼ 3 ð4ÞFor non-optimum tilt, a tilt dependent correction factor,

Cf, is

Cf ¼ 1� 0:17� 10�4ðhM � hÞ ð5ÞThe intensity coefficient for cell efficiency is

log10ðIÞ ¼ 0:64� 0:732KT ð6Þ

4 W. Tian et al. / Energy Conversion and Management 48 (2007) 1–8

3.2. Hourly electrical output of PV with no spectral

response – Model B

As is well known, crystalline silicon solar cells remainthe mainstream for PV power generation despite significantadvances in other PV devices [4]. Luque and Hggedus [4]present a simple methodology that allows estimation ofthe I–V curve of c-Si PV modules operating in any prevail-ing environmental condition using as input the values ofISC, VOC and PM under STC. The superscript * in thisstudy will be used to refer to STC (irradiance: 1000 W/m2; spectrum: AM1.5 and cell temperature: 25 �C).

The characteristic I–V of a solar cell can be written as

I ¼ ISC 1� expV � V OC þ IRS

V t

� �� �ð7Þ

The voltage Vt is described by the expression,

V t ¼ 0:025T c þ 273:15

300ð8Þ

The series resistance (Rs) can be calculated directly usingEq. (7) if I�M and V �M are available in the PV module spec-ifications. Otherwise, another method [4] can be used toobtain RS. The series resistance is considered as a propertyof the solar cells, unaffected by the operating conditions.

The short circuit current of a solar cell depends linearlyon the irradiance,

ISCðGÞ ¼I�SC

G�G ð9Þ

The open circuit voltage of a module depends exclu-sively on the temperature of the solar cells Tc.

V OCðT cÞ ¼ V �OC þ ðT c � T �cÞdV OC

dT c

ð10Þ

The temperature of the PV panel significantly affects theoutput voltage and, therefore, the power produced by thepanel. In the Luque model [4], Tc is obtained from the rela-tion that the operating temperature of the solar cell aboveambient is roughly proportional to the incident irradiance.In this study, to obtain better temperature prediction, thethermal model of a PV cell mounted on an open rack isderived according to the heat balance method. The follow-ing expression can be obtained:

CpvdT c

dt¼ aIA� P max � qw � qra ð11Þ

where Cpv is determined from Ref. [26].The long wave radiation portion of the heat balance is

split into three parts: exchange with air temperature,exchange with sky temperature and exchange with groundtemperature,

qra ¼ ed½F aðT 4a � T 4

soÞ þ F skyðT 4sky � T 4

soÞ þ F gðT 4g � T 4

soÞ�ð12Þ

It is assumed that the surface ground temperatureTg equals the air temperature and Tso is the PV module

temperature Tc. The calculation of three view factors isdescribed in detail in Ref. [27]. The convection coefficientdue to wind is given by [27],

hw ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffih2

n þ ð2:38V 0:89Þ2q

ð13Þ

The natural convection component is taken as

hn ¼ 9:482

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffijT so � T aj3

p7:328� j cos hj ð14Þ

when the heat flow is up and

hn ¼ 1:810

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffijT so � T aj3

p1:382þ j cos hj ð15Þ

when the heat flow is down.Based on Eqs. (7)–(15), the PV electricity Pmax can be

determined under real operation conditions.

3.3. Hourly electrical output of PV with spectral

response – Model C

In order to calculate the spectral influence of solar irra-diation on the PV module, Martin and Ruiz [28] proposeda model based on the atmosphere parameters of clearnessindex and air mass, and this considers independently thespectrum of each radiation component: direct (B); diffuse(D); and albedo (R). The short circuit current of solar cellscan be expressed by modifying Eq. (9) as

I sc ¼I�SC

G�ðBefffB þ Deff fD þ RefffRÞ ð16Þ

where f obeys the general form,

f ¼ c� exp½aðKT � 0:74Þ þ bðAM� 1:5Þ� ð17Þwhere a, b and c are empirically adjusted factors for eachmodule type and for each radiation component [28].

The air mass results from the expression,

AM ¼ PP 0

� 1

cos hZ

ð18Þ

The clearness index is defined as the ratio of terrestrialand extraterrestrial radiation,

KT ¼GH

B0 � cos as

ð19Þ

4. Results and discussion

Models A, B and C are employed to evaluate the perfor-mance of monocrystalline silicon modules mounted on anopen rack with both surfaces exposed to ambient air,respectively, at urban and rural sites. The modules havethe following characteristics under STC: I�SC ¼ 3 A,V �OC ¼ 19:8 V and P �M ¼ 44:5 W and the PV generator ismade of 40 modules arranged 10 in series and 4 in parallel.The other parameters used in the simulation are listed inTable 2. In the following Sections 4.1 and 4.2, the urbanand rural climatic data in Mexico City, which includes

Table 2Values of parameters used in simulations

Parameters Value Parameters Value

A 0.9 b 0.0045E 0.9 c 0.12H Local latitude A 13.4 m2

Tr 25 �C gr 0.13

0 2 4 6 8 10 12

12

16

20

24

28

32

Rural Urban S

olar

irra

dian

ce(M

J/m

2)

Month

Fig. 2. Monthly mean daily global solar radiation of urban and ruralareas in Mexico City for 2003.

0 2 4 6 8 10 12

2.0

2.4

2.8

3.2

3.6

Rural Urban

PV

out

put (

MJ/

m2 )

Month

Fig. 3. PV power output of urban and rural areas in Mexico City for 2003.

W. Tian et al. / Energy Conversion and Management 48 (2007) 1–8 5

global solar radiation, wind speed and air temperature, isprovided by Dr. E. Jauregui and E. Luyando. The urbanclimate data of Section 4.3 is from the IAG-USP Meteoro-logical Platform, Sao Paulo, Brazil. The descriptions of thesites, instrumentations and accuracies of the climate dataare presented in detail in Refs. [16,23,29].

4.1. Monthly performance of PV module in urban andrural areas – Model A

The monthly performance differences of PV in urbanand rural environments are compared based on Model Ausing the monthly mean daily meteorological data at a sta-tion in the downtown area of Mexico City relative to theobserved values of rural areas at a site 8 km from down-town for year 2003. The monthly ambient temperatureand wind speed in Mexico City for 2003 are shown inFig. 1. The monthly heat islands have an intensity of�0.1–1.9 �C. During all the year, the monthly wind speedin the rural areas is approximately 1.9 times more than inthe urban sectors areas. As can be seen from Eq. (13),the high wind speed means a high convective heat transfercoefficient between the PV and the ambient environment.Figs. 2 and 3, respectively, show the global solar radiationand simulated PV DC power in the urban and rural envi-ronments of Mexico City for year 2003. The variations ofPV output have the same tendency as the global solar radi-ation. The reduction of PV output in urban areas in com-parison with rural areas is slightly lower than the dimmingof global solar radiation in Mexico City. According to thesimulation results, the urban PV conversion efficiency isslightly higher than in the rural areas because the influenceof global solar radiation on the PV temperature is greater

0 2 4 6 8 10 1210

12

14

16

18

20

22

24

Am

bien

t tem

pera

ture

(o C

)

Rural Urban

Month(a)

Fig. 1. Monthly average ambient temperature

than other factors, which include air temperature and windspeed.

4.2. Hourly Performance of PV module – Model B

In this section, Model B is used to calculate the hourlyPV power output of urban and rural sites in Mexico Cityin March, 2003. Fig. 4 shows the diurnal evolution ofmonthly mean values of ambient temperature and windspeed in March 2003. It can be seen that the most notablefeature is the reduced cooling governed by the rates of

0 2 4 6 8 10 121.0

1.5

2.0

2.5

3.0

3.5 Rural Urban

Win

d sp

eed

(m/s

)

Month(b)

and wind speed in Mexico City for 2003.

0 4 8 12 16 20 24

8

12

16

20

24

28

Rural Urban

Am

bien

t te

mpe

ratu

re (

o C)

Hour

0 4 8 12 16 20 24

1

2

3

4

5

6

Rural Urban

Win

d sp

eed

(m/s

)

Hour(a) (b)

Fig. 4. Diurnal evolution of monthly mean values of air temperature and wind speed in March, 2003.

6 W. Tian et al. / Energy Conversion and Management 48 (2007) 1–8

radiative exchange and heat storage in the city in the lateafternoon and evening that contributes to the high noctur-nal temperature in the urban area. Similarly, the warm upafter sunrise is also slower. The hourly wind speed in theurban sector is always lower than the rural wind speed.As is shown in Fig. 5, the global solar radiation in urbanenvironments is obviously lower than that in rural areas.Fig. 6 represents the hourly variation of simulated PV tem-perature and PV power in urban and rural areas. In therural environment, the high solar radiation may result in

6 8 10 12 14 16 18 200

200

400

600

800

1000

Sol

ar r

adia

tion

(W/m

2)

Hour

Rural Urban

Fig. 5. Diurnal variation of monthly mean values of global solar radiationin March, 2003.

0 5 10 15 20 25

10

20

30

40

50

Rural Urban

PV

tem

pera

ture

(o C

)

Hour(a)

Fig. 6. PV temperature and P

high PV temperature, but the low ambient temperatureand high wind speed cause low PV temperature. The com-bination of these factors leads to the PV temperature in therural setting being slightly higher than in the urban settingduring the daytime. At night, the urban PV temperaturebecomes lower than that at rural sites due to the combina-tion of low air temperature and high wind speed with nosolar radiation. It should be realized that the PV tempera-ture differences between the urban and rural settings in theevening are meaningless for PV power output, but it can be

0 4 8 12 16 20 24

0

20

40

60

80

100

120

PV

out

put (

W/m

2)

Hour

Rural Urban

(b)

V output in March, 2003.

4 6 8 10 12 14 16 18 200

20

40

60

80

100

120

PV

out

put (

W/m

2 )

Hour

Model C (clear) Model C (cloudy) Model B (clear) Model B (cloudy)

Fig. 7. Spectral response of PV for clear day and cloudy day.

4 6 8 10 12 14 16 18 20

0

20

40

60

80

PV

out

put (

W/m

2)

Hour

Model C(Mar) Model B(Mar)

4 6 8 10 12 14 16 18 20

0

20

40

60

80

PV

out

put (

W/m

2)

Hour

Model C(Nov) Model B(Nov)

(a) (b)

Fig. 8. Hourly electrical output of PV in March (a) and November (b), 2004, using Models B and C.

W. Tian et al. / Energy Conversion and Management 48 (2007) 1–8 7

concluded that BIPV may change building surface temper-atures and heat balance. A detailed discussion of this effectis presented in the literature [10]. The reductions of urbanglobal solar radiation and urban PV power output in con-trast to rural areas are 22.4% and 20.2%, respectively. It isevident that the power output of the PV is directly relatedto the incident solar radiation, and the urban PV conver-sion efficiency is higher than that of the rural PV system.

The PV power output in rural areas is regarded as thecontrol group. By changing only one factor at a time, theinfluence of three variables (solar radiation, wind speed,air temperature) on PV power is investigated, respectively.A decrease of PV power output in comparison with thecontrol group by 1.7% was found using the urban hourlywind speed. The PV output using the urban global solarradiation may be reduced by 19.1%. The reduction of PVoutput under the urban air temperature is less than 1%.Urban pollution reduces the solar radiation to the PV sur-face but, to some extent, improves the PV conversion effi-ciency because the low solar radiation means low PVtemperature. The urban wind speed and urban air temper-ature have obviously negative effects on the PV efficiency.

4.3. Spectral response in urban areas – Models B and C

Not only the irradiance but also the spectral distributionof the irradiance has an important influence on the effi-ciency of the solar cell. Based on Models B and C, themeteorological data of the cities of Sao Paulo for year2004 is used to investigate the spectral response of PV mod-ules in urban areas.

Fig. 7 illustrates the electrical output of PV modules thatis calculated using Models B and C for clear days andcloudy days. The results of Model B are slightly higherthan the calculated values of Model C on November 3,2004 (clear day), but the difference between Models Band C is significant on cloudy days (November 11, 2004),and the latter is higher than the former. Fig. 8 shows theelectrical output of PV using Models B and C in Marchand November based on the monthly mean daily climatedata. The calculation results from Model B are less than

the values of Model C in Fig. 8, and the differences betweenthe two models are less than 6%. Figs. 7 and 8 indicate thatthe DC power output of PV seems to be underestimatedif the spectral response of PV module in the urban environ-ment is not taken into account. Martiz et al. [28] also foundthat on cloudy days, the spectral losses of crystalline siliconPV modules turn to negative values.

5. Conclusions

Because the change of PV power is almost linear withsolar radiation, the solar radiation attenuation in urbanareas leads to less PV output. The reasons that affect thePV conversion efficiency in the urban environment can besummarized under the following four aspects. Firstly, thespectral distributions in the urban areas have more diffusesolar radiation, so the spectral losses turn to gains for crys-talline silicon PV modules on cloudy days. Secondly, theurban air temperatures are higher than the rural ambienttemperature. Thirdly, the wind speed in urban areas is usu-ally lower than in the rural areas, which causes a low con-vective heat transfer coefficient between the PV module andthe ambient. Lastly, more global solar radiation in the sur-rounding country side means higher PV module tempera-ture. In this study, the urban PV conversion efficiency ishigher than the rural PV system because PV module tem-perature in the urban areas is slightly lower than in therural areas. To predict accurately the electrical output ofPV in urban and rural settings and design better BIPV sys-tems, the solar radiation and other climatic data should becarefully selected according to the appropriate meteorolog-ical station.

Acknowledgements

The authors would like to thank Dr. Ernesto Jaureguiand Elda Luyando (Centro de Ciencias de la Atmosfera,Universidad Nacional Autonoma de Mexico Circuito) forproviding the hourly climatic data of urban and rural sitesin Mexico City for year 2003. They also gratefullyacknowledge Amauri Pereira de Oliveira and Antonio

8 W. Tian et al. / Energy Conversion and Management 48 (2007) 1–8

Jaschke Machado from the Department of AtmosphericSciences, University of Sao Paulo, for the valuable supportthat provided the urban hourly meteorological data of SaoPaulo for year 2004.

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