PORTLAND STATE

UNIVERSITY

Modeling the Impact of Anthropogenic Heating on Modeling the Impact of Anthropogenic Heating on the Urban Climate of Houstonthe Urban Climate of Houston

David J. Sailor1 and Hongli Fan2

sailor@cecs.pdx.edu

1. Portland State University 2. Tulane University

August 2004

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PORTLAND STATE

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MotivationMotivation

• On average anthropogenic heating (Qf) is small

– peak solar flux is ~1000 W m-2 in summer

– city-scale, daily average Qf is ~ 30 to 50 Wm-2

• Local peaks in anthropogenic heating can be a factor of 10-20 higher than the city-scale average value*.

• In morning/evening Qf may affect boundary-layer transitions and mixing processes with important AQ implications

* Sailor, D.J., and L. Lu, (2004) “A Top-Down Methodology for Developing Diurnal and Seasonal Anthropogenic Heating Profiles for Urban Areas,” Atmospheric Environment, 38 (17), 2737-2748.

time

Q

Qsw

Qf

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A top-down methodology for QA top-down methodology for Qff

)()()()()()( tEEtfEtfDVDEtfttQ mhfhfeevvpopf

(vehicles) (building sector) (metabolism)

hf

hf

e

e

m

v

v

pop

E

f

E

f

E

DVD

E

tf

)(

non-dimensional traffic profile [-]

vehicle energy used per unit distance [W km-1]

distance traveled per person [km]

metabolic heat per person [W]

electricity profile [-]

heating fuel consumption [W]

electricity consumption [W]

heating fuel profile [-]

population density [person/km2]

Determine consumption rates separately for residential, commercial, and industrial sectors.

For further details see poster P3.6

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Estimating population densityEstimating population density

• Census Transportation Planning Package (CTPP*) – Need: population data from the basic census database underestimate

daytime populations by ~ a factor of 2 at the city scale…

– CTPP data available at range of scales (city, census tract, TAZ)

– Residents, non-working residents, workers, time-of-arrival data…

– Estimate nighttime and daytime (workday) populations

– Neglect other visitors to city (hotel/conference/shoppers/etc)

* www.bts.dot.gov

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Anthropogenic Heating in Houston at Various ScalesAnthropogenic Heating in Houston at Various Scales

• Workday population density (centered on CBD)– 1,538 persons/km2 at city scale

– 20,844 persons/km2 at census tract scale

– up to 184,500 persons/km2 at TAZ scale

Qf (W/m2) at various spatial scales of interest (centered on CBD)

Season Temporal Scale of Interest

City Scale

Census tract (~2.5km sq.)

TAZ (~ 0.2km sq.)

Daily average 27.3 51.4 454.8 Winter Hourly maximum 33.3 62.7 554.7 Daily average 38.9 73.2 648.0 Summer Hourly maximum 54.2 102.0 902.9

Annual Average 29.2 55.0 486.5

• Since Qf scales with population density it can vary dramatically depending upon the scale of analysis

Daytime Population Density in Houston

Daytime Population Density in Houston

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Anthropogenic Heating in Houston at TAZ ScalesAnthropogenic Heating in Houston at TAZ Scales

Qfaug12pm.shp1 - 1516 - 3031 - 6061 - 100101 - 250250 - 500501 - 20002001 - 10000

10 0 10 20 Miles

N

EW

S

QfAugnoonDay (summer)

Qfaug8pm.shp1 - 1516 - 3031 - 6061 - 100101 - 250250 - 500501 - 20002001 - 10000

10 0 10 20 Miles

N

EW

S

QfAug8pmNight (summer)

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Anthropogenic Heating Profiles

0

50

100

150

200

250

300

350

400

0 8 16 24

Local Time

Qf

(w/m

^2)

Residential

Comm/Ind

Urban Core

City-Avg.

City-average (low spatial resolution case: Q2)

Houston Summer

In this study… we define 3 categories of urban land use and implement one distinct Qf profile for each category.

High spatial resolution case: Q1

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Simulation OverviewSimulation Overview

MM5 implementation:

• Modified USGS land use with 3 new urban subcategories

• No urban canopy parameterization

• Diurnal land-use-dependent profile for Qf

• Qf input into near-surface air layer as T

• Modified Blackadar PBL scheme

• 4 two-way nests, 1km grid cells in inner domain

Simulation Episodes:

• Aug. 30, 2000

• Sept. 27, 2002

• Q0 – No anthropogenic heating

• Q1 – Land-use specific profiles

• Q2 – Single city-scale avg. profile.

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Nig

ht (

8pm

)M

orn

ing

(6am

)D

ay (

noo

n)

092702092702 083000083000

Temperature Perturbation (Qf - Control)092702

0.0

0.5

1.0

1.5

2.0

2.5

0 8 16 24

Local Time

T

(C

)

Temperature Perturbation (avg. over city)

Q1 – Q0: Near-surface air temperature difference between base case (no Qf) and spatially-

detailed Qf case (~ 2-2.5 0C during night/morning, ~ 0.25-0.5 0C during day)

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092702092702

1010

45

45

Q1 – Q0: Near-surface air temperature difference between base case (no Qf) and spatially-

detailed Qf case (~ 2-2.5 0C during night/morning, ~ 0.25-0.5 0C during day)

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Anthropogenic Heating Profiles

0

50

100

150

200

250

300

350

400

0 8 16 24

Local Time

Qf

(w/m

^2)

Residential

Comm/Ind

Urban Core

City-Avg.

7pm

5pm

Sept. 27, 2002 simulation

Q1 – Q 2: Temp. difference between spatially-detailed Qf case and city-average Qf case:

(T ~ 0.5-2.0 oC during transitions; 0.2-0.4 oC during day )

9am

11am

Vertical cross section (0-2.5km)

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Conclusions and Future WorkConclusions and Future Work

• Qf in Houston is 30-50 W/m2 at the city scale, but may be a factor of 10 to 20 larger in isolated regions within the core of the city.

• CTPP data are useful for population-based analyses of anthropogenic heating (and moisture), but refinements & extensions are possible.

• Addition of Qf in MM5 creates a summer heat island signature in morning and night (~ 2.0 oC ) , with less impact during day ( ~ 0.25-0.5 oC ).

• Including Qf at high spatial resolution can generate local temperature perturbations of up to several degrees C compared with use of city-average profiles. Effect is largely limited to morning/evening transition hours.

• Next steps include:– use improved landuse database and refined surface characteristic definitions– better vertical representation of Qf in MM5– workday vs. non-workday profiles– integration with an urban canopy parameterization– investigate winter episodes sailor@cecs.pdx.edu

www.cecs.pdx.edu/~sailor