Mesoscaleandmeso‐urbanmeteorologicalandphotochemicalmodelingofheatislandmitigationinCalifornia

2ndInternationalConferenceonCountermeasurestoUrbanHeatIslands

September20‐23,2009Berkeley,California

HaiderTahaAltostratusInc.(925)228‐1573

haider@altostratus.com–www.altostratus.com

AcknowledgementsCaliforniaEnergyCommission–PIER

SacramentoMetropolitanAQMD–UFFCAProject

Urbanizationand land‐use/ land‐coverchanges,andassociatedchanges inemissionsandmeteorology, have the potential to impact a region’s attainment status – in theshorttermandunderfutureclimates

UHIcontrolcanhelpmaintain/improveairquality:nationalinterestinincorporationofUHI mitigation into regulatory frameworks (direct / indirect, energy / atmosphericpathways)

Coolroofs–CaliforniaTitle24

ARB: climate change early action: high‐albedo materials (buildings, automotive coolpaints’portionoftheAB32EarlyActionPlan)

WhyconsiderUHIcontrolinairqualityregulations

2

-300 -200 -100 0 100 200 300

-200

-100

0

100

200

300

400

CCOS Domain and

proposed 1km tree measure modeling domain

4km Domain:

(-376.0, -292.0; 185 x 185)

1km Domain:

(-100.0, 136.0; 80 x 80)

LCP Definition:

(-120.5, 37.0; 60//30)

4km domain1km domain

3

IncorporatingUHImitigationinSIP(sofar)

PerEPA/OAQPS:Avoluntarymeasureisameasureorstrategythatisnotenforceableagainstan individual source.Anemergingmeasure isameasureor strategy thatdoesnot have the same high level of certainty as traditional measures for quantificationpurposes.

Anemergingand/orvoluntarymeasure(suchasUHIcontrol),requiresstate‐of‐sciencetechnologicalassessment.Inadditiontodirectmeasurements,coupledmeteorological‐emissions‐photochemicalmodeling isoneofthebestoptionsavailabletodemonstrateeffectivenessofcontrolstrategy.

EPAbelievesitisappropriatetolimitthesemeasurestoasmallportionoftheSIPgiventheuntestednatureofthecontrolmechanisms.Thelimitis6%ofemissionsshortfalltoreachattainmentorformaintenancepurposes.

SacramentoUFFCAproject(SMAQMD):SFNAVOCshortfall=12tpd(from2018levels)6%ofshortfall=0.72tpd(ifnotshared)Programtobeachievedwithreplacement(low‐emissionsmix)andnetcoverincreaseModelingneededtosupportorrevisefindingstodateincontrolmeasure

4

Thusongoingmodelsanddataimprovements:

Surfacecharacterization,urbanmorphology, land‐use/land‐cover–spatial/categoricalresolutionsUseofnewparametersinmodelsandtailorforUHIstudiesMeteorologicalmodelurbanization,photochemicalmodelurbanization–fineresolutionMoreresolvedparameterizations–multi‐directional(windapproach)Modelperformancetomeet/exceedskill‐demonstrationbenchmarksConversionofAQ/CTMmodelingresultsintoemissionequivalentsMulti‐episodic,seasonal,annualevaluationsofimpacts

TROG (…,T) + NOx (…,T) + hν O3 + …..

“Conventional” (e.g., emission reduction)

UHI control

Direct effect: impact on emission ratesIndirect effect: impact on reaction rates, PBL, V, deposition

UHIcontrol:

inanutshell

5

Vegetative-cover changes

Latentheatflux

Solarradiationextinction

Roughnesslength

Deposition&re‐entrainment

Soilmoisture/Runoff

Vegetationalbedo

Bowenratio

Surfacetemperature

Airtemperature

BNO

ISOP,TERP,MBO(biogenicHC)

Windspeed

Energyuse

Emissions

Photochemicalreactionrates

TKE

Mixingheight

Ozoneconcentrations

Vegetative-species changes

Surface albedochanges

AirQuality

UHIcontrol:Surfacemodification

Meteorology

Accountingforvariousdirect/indirectphysicalpathways

andinteractions

Radiativeforcing

Energy

Land use / Land coverSurface Properties

6

-- Met ic / bc / analyses-- LULC characterization

-- Fine-resolution morphology-- Resolved surface properties-- Detail canopy representation: vegetative cover, geometry, PAD, FAD, TAD , etc.

-- UHI control strategies

-- Morphology-based perturbations-- Surface properties / albedo and canopy perturbations

mesoscale modeling

MM5 3.7.6 / WRF)

urbanized modeling

uMM5 (DA-SM2-U)/ WRF-urban

Emission correctionsBEIS3 / MEGAN / BEIGIS

EMS-95 / SMOKE

Photochemical modeling

CAMx 4.51 / CMAQ

Fine resolution photochemical modeling

CAMx 4.51 (5) / CMAQ

Air quality

A

A: Power plant emissions – utility modelB: Building energy simulation models

B

Emission inventories

-- Future-year controlled emissions

Meteorology

Emissions

Radiative transfer modeling

STREAMER

Utilizationoflatestandnewmodelingsystems

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Source: Taha 2008b. Boundary-Layer Meteorology

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Introducingmeso‐urbanmodelingcapabilities,e.g.,

DA‐SM2‐U/uMM5

Mesoscale(O~4km+)modelingdomainsMeso‐urban(O~1km)modelingdomains

12km12km

4km4km

15km15km

45km45km

5km5km

36km36km

8

APPLICATIONSCaliforniaexample

Southern California

Central California

9

Source: Taha 2008a.Atmospheric Environment.

Meso‐urbanmodelingbase‐casesimulationresults:heatisland,coolisland,flowconvergence

Sacramento,August1st,2000

10

SelectedTKEbudgetcomponents(m2s‐3)foralocationinDowntownSacramento.AlsoshownisbuildingFAD(m2m‐3).

Source: Taha 2008a.Atmospheric Environment

Meso‐urbanmodelingbase‐casesimulationresults:TKEbudgetcomponents

11

Meso‐urbanmeteorological andphotochemicalsimulations:modelperformance

Source: Taha 2008c.Atmospheric Environment

July

31

Aug

ust 1

Aug

ust 2

Meso‐urban/fine‐resolutionphotochemicalmodeling:Example(base)resultsforCentralCAandSacramento

12

Impacts of increased albedo at the mesoscale (4km)

ΔTa 2m

Sacramento

San Jose Fresno

Bakersfield

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Increased control

ΔT max

SouthernCalifornia

ChangesinO3averagedoverurbangridcellsinSouthernCalifornia:SimulatedUHIcontrolforAugust5th.Notethresholdeffect

Case##

albedo ∈ 0,1,2

veg cover ∈ 0,1,2

0: none1: moderate2: high

Evaluating impacts of UHI control

13

BuildingPA

Dand

Δα

DevelopmentofUHIcontrolscenariosandevaluatingimpactsatthemeso‐urbanscale,e.g.,increasedurbanalbedo

• Albedo (NOTE: > 0.37 µm)

• Vegetation (NOTE: BVOC emissions)

• Anthropogenic heat flux

• Storage heat flux / thermal mass

• Moisture and runoff

• Urban geometry

Meso-urban model (1km)

ΔTa 3m

ΔTs

Sacramento

Sacramento

14

Changesin[O3]attimeofbase‐casepeakoneach day of episode in the SacramentouMM5 domain (resulting from increasedurban albedo), corresponding to a decreaseofupto2‐3Cinairtemperature.Exceptforlarge localized decreases (or increases, e.g.,on1August),averagereductionsaffectlargeareas

Impactsofincreasedurbanalbedoonpeak[O3]:Sacramentoexample

July 31 August 1 August 2

Source: Taha 2008.Atmospheric Environment

Base-case peak (simulated) Δ [O3] (ppb) at location of peakTime of peak

(LST)Location of

peak(see previous

figure)

At time ofpeak

Max Δ [O3] at anytime

P e a k(ppb)

Albedo -basecase

Albedo - basecase

July 29 103 1500 A -8.7 -8.7 (at1500)July 30 113 1500 B -10.9 -11.1 (at 1600)July 31 96 1300 C -8.1 -10.6 (at 1200)

August 1 117 1400 D -22.2 -22.2 (at 1400)August 2 101 1500 E -6.7 -9.2 (at 1600)

Potentialair‐qualityimprovementsfromincreasedurbanalbedo

15

Source: Taha 2008. Atmospheric Environment

August 1st, simulated ozone at alocation in Sacramento (top of graph)and changes resulting from increasedalbedo (bottom of graph)

A: Simulated 8-hour average for base and high-albedo scenarios at Folsom-Natoma (FLN); B:simulated daily maximum 8-hour average ozone(at FLN); and C: reduction (%) in daily 8-hrmaximum as RRF resulting from increasedalbedo.

A

B

C

8‐houraverage 1‐houraverage

• Eachregion/airshedmustbemodeledonitsownduetospecificities(e.g.,thresholdeffectsweshowedearlier)

• Multi‐episodic,seasonal,annualmodelingneededtocaptureeffectivenessofmitigationduringavarietyofozonemeteorologies(currentCECPIERproject)

• Variousclimatesubzones–thresholdsaffectsagainorlocaleffects(currentCECPIERproject)

• Conversiontoemissionreductionequivalentsandemissioncredits

Someimplicationsforfuture(regulatory)modeling

17

THANK YOU!

REFERENCES CITED IN PRESENTATION

Dupont S., Otte T., Ching J., 2004. “Simulation of meteorological fields within and above urban and rural canopies with a mesoscalemodel (MM5)”, Boundary-Layer Meteorology, 113, pp. 111-158.

Taha, H. 2008a. "Meso-urban meteorological and photochemical modeling of heat island mitigation". Atmospheric Environment, Vol.42, No. 38 (December 2008), pp. 8795-8809. doi:10.1016/j.atmosenv.2008.06.036.

Taha, H. 2008b. "Episodic performance and sensitivity of the urbanized MM5 (uMM5) to perturbations in surface properties inHouston TX". Boundary-Layer Meteorology, Vol. 127, No. 2 (May 2008), pp. 193-218. doi:10.1007/s10546-007-9258-6.

Taha, H. 2008c. "Urban surface modification as a potential ozone air-quality improvement strategy in California: A mesoscalemodeling study". Boundary-Layer Meteorology, Vol. 127, No. 2 (May 2008), pp. 219-239. doi:10.1007/s10546-007-9259-5