Publications Published in Elsevier

1. Identifying futureelectricity–watertradeoffsintheUnitedStates. Benjamin K.Sovacool, KellyE.Sovacool.
   Elsevier: 2009
   DOI: 10.1016/j.enpol.2009.03.012
   Notes
   Researchersfortheelectricityindustry,nationallaboratories,andstateandfederalagencieshavebegun to arguethatthecountrycouldfacewatershortagesresultingfromtheadditionofthermoelectric powerplants,buthavenotattemptedtodepictmoreprecisely where or how severe those shortageswill be. Usingcounty-leveldataonratesofpopulationgrowthcollectedfromtheUSCensusBureau,utility estimates offutureplannedcapacityadditionsinthecontiguousUnitedStatesreportedtotheUS EnergyInformationAdministration,andscientificestimatesofanticipatedwatershortagesprovided from theUSGeologicSurveyandNationalOceanicandAtmosphericAdministration,thispaper highlightsthemostlikelylocationsofsevereshortagesin22countiesbroughtaboutbythermoelectric capacityadditions.Withintheseareasaresome20majormetropolitanregionswheremillionsofpeople live.Afterexploringtheelectricity–waternexusandexplainingthestudy’smethodology,thearticle then focusesonfourofthesemetropolitanareas–Houston,Texas;Atlanta,Georgia;LasVegas,Nevada; New York,NewYork–todeepenanunderstandingofthew terandelectricitychallengestheymay soonbefacing.Itconcludesbyidentifyinganassortmentoftechnologiesandpoliciesthatcould respond totheseelectricity–watertradeoffs.
   
   
   
2. Long-term, wintertime aerosol, cloud and precipitation measurements in the Northern Colorado Rocky Mountains, USA. Edward E. Hindman, Randolph D. Borys, Douglas H. Lowenthal, Neal Phillip.
   Elsevier: 2005
   DOI: 10.1016/j.atmosres.2005.10.006
   Notes
   At Storm Peak Laboratory (SPL) in the northern Colorado Rocky Mountains during the winters of 1983/1984 through 2003/ 2004, significant trends occurred of decreasing cloud droplet concentrations and initially increasing cloud and snow pH values then more recent decreasing values. The decrease in cloud droplet concentrations and a corresponding increase in mean droplet diameters are consistent with liquid water content trends in the long-term record. Decreased condensation nucleus concentrations, and most likely cloud-condensation nucleus concentrations as well, caused the decrease in droplet concentrations. An inverse relationship between cloud pH and condensation nucleus concentrations was identified. However, no relationship between condensation nucleus concentrations and precipitation rates was identified. Thus, the inverse relationship between aerosol concentration and precipitation rate reported by Borys et al. [Borys, R.D., Lowenthal, D.H., Cohn, S.A., Brown, W.O.J., 2003. Mountaintop and radar measure
   
   
   
3. Natural disasters impacting a macroeconomic model with endogenous dynamics. Stéphane Hallegattea Michael Ghilc.
   Elsevier: 2008
   DOI: 10.1016/j.ecolecon.2008.05.022
   Notes
   We investigate the macroeconomic response to natural disasters by using an endogenous business cycle (EnBC) model in which cyclical behavior arises from the investment–profit instability. Our model exhibits a larger response to natural disasters during expansions than during recessions. This apparently paradoxical result can be traced to the disasters amplifying pre-existing disequilibria during expansions, while the existence of unused resources during recessions damps the exogenous shocks. It thus appears that high-growth periods are also highly vulnerable to supply-side shocks. In our EnBC model, the average production loss due to a set of disasters distributed at random in time is highly sensitive to the dynamical characteristics of the impacted economy. Larger economic flexibility allows for a more efficient and rapid response to supply-side shocks and reduces production losses. On the other hand, too high a flexibility can lead to vulnerability phases that cause average production losses to soar. These results raise questions about the assessment of climate change damages or natural disaster losses that are based purely on long-term growth models.
   
   
   
4. The value of multiangle measurements for retrieving structurally and radiatively consistent properties of clouds, aerosols, and surfaces. David J. Diner, Bobby H. Braswell, Roger Davies, Nadine Gobron, Jiannan Hu, Yufang Jin, Ralph A. Kahn, Yuri Knyazikhin, Norman Loeb, Jan-Peter Muller, Anne W. Nolin, Bernard Pinty, Crystal B. Schaaf, Gabriela Seiz, Julienne Stroeve.
   Elsevier: 2005
   DOI: 10.1016/j.rse.2005.06.006
   Notes
   Passive optical multiangle observations make possible the retrieval of scene structural characteristics that cannot be obtained with, or require fewer underlying assumptions than, single-angle sensors. Retrievable quantities include aerosol amount over a wide variety of surfaces (including bright targets); aerosol microphysical properties such as particle shape; geometrically-derived cloud-top heights and 3-D cloud morphologies; distinctions between polar clouds and ice; and textural measures of sea ice, ice sheets, and vegetation. At the same time, multiangle data are necessary for accurate retrievals of radiative quantities such as surface and top-of-atmosphere albedos, whose magnitudes are governed by structural characteristics of the reflecting media and which involve angular integration over intrinsically anisotropic intensity fields. Measurements of directional radiation streams also provide independent checks on model assumptions conventionally used in satellite retrievals, such as the application of -D radiative transfer theory, and provide data required to constrain more sophisticated, 3-D approaches. In this paper, the value of multiangle remote sensing in establishing physical correspondence and self-consistency between scene structural and radiative characteristics is demonstrated using simultaneous observations from instruments aboard NASA’s Terra satellite (MISR, CERES, ASTER, and MODIS). Illustrations pertaining to the remote sensing of clouds, aerosols, ice, and vegetation properties are presented. D 2005 Elsevier Inc. All rights reserved.
   
   
   
5. Use andlimitationsoflearningcurvesforenergytechnologypolicy: A component-learninghypothesis. F.Ferioli, K.Schoots, B.C.C.vanderZwaan.
   Elsevier: 2009
   DOI: 10.1016/j.enpol.2008.10.043
   Notes
   In thispaper,weinvestigatetheuseoflearningcurvesforthedescriptionofobservedcostreductions for avarietyofenergytechnologies.Startingpointofouranalysisistherepresentationofenergy processes andtechnologiesasthesumofdifferentcomponents.Whilewerecognizethatinmanycases ‘‘learning-by-doing’’mayimprovetheoverallcostsorefficiencyofatechnology,wearguethatsofar insufficientattentionhasbeendevotedtostudytheeffectsofsinglecomponentimprovementsthat togethermayexplainanaggregatedformoflearning.Indeed,foranentiretechnologythephenomenon of learning-by-doingmaywellresultfromlearningofoneorafewindividualcomponentsonly.We analyze underwhatconditionsitispossibletocombinelearningcurvesforsinglecomponentstoderive one comprehensivelearningcurveforthetotalproduct.Thepossibilitythatforcertaintechnologies somecomponents(e.g.,theprimarynaturalresourcesthatserveasessentialinput)donotexhibitcost improvementsmightaccountfortheapparenttimedependenceoflearningratesreportedinseveral studies(thelearningratemightalsochangeconsiderablyovertimed pendingonthedataset considered,acrucialissuetobeawareofwhenoneusesthelearningcurvemethodology).Suchan explanationmayhaveimportantconsequencesfortheextenttowhichlearningcurvescanbe extrapolatedintothefuture.Thisargumentationsuggeststhatcostreductionsmaynotcontinue indefinitelyandthatwell-behavedlearningcurvesdonotnecessarilyexistforeveryproductor technology.Inaddition,evenfordiffusingandmaturingtechnologiesthatdisplayclearlearningeffects, market andresourceconstraintscaneventuallysignificantlyreducethescopeforfurtherimprovements in theirfabricationoruse.Itappearslikelythatsometechnologies,suchaswindturbinesand photovoltaiccells,aresignificantlymoreamenablethanotherstoindustry-widelearning.Forsuch technologies weassessthereliabilityofusinglearningcurvesatlargetoforecastenergytechnologycost reductions.