1. David J. Sailor1 and Hongli Fan2 1. Portland State University
Modeling the Impact of Anthropogenic Heating on the Urban Climate of Houston
David J. Sailor1 and Hongli Fan2
1. Portland State University
2. Tulane University
August 2004
Introduction…
In prior research we have (1) established a methodology for generating Qf profiles for cities; (2) evaluated the impact of Qf on mesoscale model simulations of Philadelphia.
In this work we (1) apply the methodology at very fine spatial scales; (2) evaluate impact of various spatial and temporal scales of Qf profiles in mesoscale model simulaitons of Houston.

2. Motivation On average anthropogenic heating (Qf) is small
time Q
Qsw Qf
Motivation
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 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),

3. A top-down methodology for Qf
(vehicles) (building sector) (metabolism)
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

4. Estimating 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) *

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

6. Anthropogenic Heating in Houston at TAZ Scales
Day (summer)
Night (summer)

7. 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
Houston Summer
City-average (low spatial resolution case: Q2)

8. Simulation Overview MM5 implementation: Simulation Episodes:
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 DT
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.

9. Q1 – Q0:
Near-surface air temperature difference between base case (no Qf) and spatially-detailed Qf case (~ C during night/morning, ~ C during day)
Night (8pm)
Morning (6am)
Day (noon)
092702
083000
Temperature Perturbation (avg. over city)

10. Q1 – Q0:
Near-surface air temperature difference between base case (no Qf) and spatially-detailed Qf case (~ C during night/morning, ~ C during day) 45 10 10
092702 45

11. (DT ~ 0.5-2.0 oC during transitions; 0.2-0.4 oC during day )
Q1 – Q 2:
Temp. difference between spatially-detailed Qf case and city-average Qf case:
(DT ~ oC during transitions; oC during day )
Vertical cross section (0-2.5km)
9am
11am
7pm
5pm
Sept. 27, 2002 simulation

12. Conclusions and Future Work
Qf in Houston is 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 ( ~ 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