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Megaquarry versus decentralized mineral production: network analysis of cement production in the Great Lakes region, USA

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Megaquarry versus decentralized mineral production: network analysis of cement production in the Great Lakes region, USA
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  See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/248452829 Megaquarry versus decentralized mineralproduction: network analysis of cementproduction in the Great...  Article   in  Journal of Transport Geography · March 2010 DOI: 10.1016/j.jtrangeo.2009.06.007 CITATION 1 READS 86 3 authors , including: Some of the authors of this publication are also working on these related projects: Porphyry copper exploration   View projectAlissa KendallUniversity of California, Davis 59   PUBLICATIONS   950   CITATIONS   SEE PROFILE Stephen E. KeslerUniversity of Michigan 235   PUBLICATIONS   5,258   CITATIONS   SEE PROFILE All content following this page was uploaded by Stephen E. Kesler on 13 January 2017. The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the srcinal documentand are linked to publications on ResearchGate, letting you access and read them immediately.  Megaquarry versus decentralized mineral production: network analysisof cement production in the Great Lakes region, USA Alissa Kendall a, * , Stephen E. Kesler b , Gregory A. Keoleian c a Department of Civil and Environmental Engineering, University of California, One Shields Ave., Davis, CA 95616, United States b Center for Sustainable Systems, University of Michigan School of Natural Resources and Environment, Dana Building, 440 Church Street, Ann Arbor, MI 48109, United States c Department of Geological Sciences, University of Michigan, 2534 C. C. Little Building, 1100 North University Ave., Ann Arbor, MI 48109, United States a r t i c l e i n f o Keywords: MegaquarryCementMultimodal freight transportationNetwork analysisEnergyCost optimization a b s t r a c t Thegeographyofmineralresourcesandhumansettlementinfluencestheproduction–consumptioncycleof cement and other mined construction materials, and affects the energy, cost and environmental bur-den associated with these materials. Although mines that supply most construction products have tradi-tionally been located near major points of consumption, population pressures have raised the possibilitythat these small, widely scattered operations might be replaced by large, megaquarry operations. Thisstudy uses network analysis to compare transportation-related energy and cost for cement productionfrom highly centralized facilities, or megaquarries, to that from smaller production facilities dispersedthroughout the Great Lakes region of the United States. Results show that a transition to megaquarriescan increase transport-related energy and associated environmental impacts by almost 50%. This sug-gests that decisions involving the location of mining operations for construction products are best madeon a regional rather than local basis.   2009 Elsevier Ltd. All rights reserved. 1. Introduction Construction materials constitute the largest flow of non-fuel,non-foodrawmaterialsintheUS(UnitedStates Geological Survey,1998). Many of these materials such as cement, gravel, and sandsrcinate at quarries, are processed near or at the quarry site, andthen are transported to their point of consumption. Current trendsin construction mineral resource extraction show increasing cen-tralization at large production sites, known as megaquarries, andconsequent longer transport distances. This trend stands in con-trast to traditional industrial location theory, which from its earli-est established the importance of transportation-related costs onthe location of industrial sites (Weber, 1909). This trend is partic- ularly surprising because construction materials are heavy andhave a relatively low value on a per-mass basis.Thisresearchusesnetworkanalysismethodstoquantifythein-creased transportation-related energy consumption and costs tothe cement industry for adopting megaquarry production strate-gies. The freight transportation energy and cost of megaquarry ce-ment production is compared to that of the existing configurationof plants in the Great Lakes region of the US. Results show thatfrom the perspective of transportation energy and costs alone,the existing configuration and production capacities of cementplants in the region is suboptimal. Moreover, despite the existingsuboptimalconfiguration,atrendtowardsmegaquarryproduction,even when developed at an optimized site, will lead to greatertransportation-related energy consumption and cost.Although this study focuses on one region, its results supportbroader critiques of industrial location theory that emphasize theinfluence of environmental factors (McCann and Sheppard, 2003). Factors of potential importance to the location of cement plant in-clude the spatial distribution of high quality mineral resources,complexity of environmental permitting, and community opposi-tion to new sites or site expansion. These factors can create highbarriers to siting at new locations or even significant expansionsat preferred existing sites that might account for the currentsuboptimal configuration of plants that has remained largelyunchanged for decades. 2. Background  2.1. Megaquarries The primary raw material used in cement manufacture is lime-stone, which is extracted from a quarry typically located at thesame site as the cement production plant. The site and size of aquarry, whether for cement manufacturing or aggregate produc-tion, will depend on physical constraints such as the dimensionsof the mineral resource, availability of suitable transportation, 0966-6923/$ - see front matter   2009 Elsevier Ltd. All rights reserved.doi:10.1016/j.jtrangeo.2009.06.007 *  Corresponding author. Tel.: +1 530 752 5722; fax: +1 530 752 7872. E-mail address:  amkendall@ucdavis.edu (A. Kendall). Journal of Transport Geography xxx (2009) xxx–xxx Contents lists available at ScienceDirect  Journal of Transport Geography journal homepage: www.elsevier.com/locate/jtrangeo ARTICLE IN PRESS Please cite this article in press as: Kendall, A., et al. Megaquarry versus decentralized mineral production: network analysis of cement production in theGreat Lakes region, USA. J. Transp. Geogr. (2009), doi:10.1016/j.jtrangeo.2009.06.007  and permitting and operational regulations. The size of a quarry isalso affected by trade-offs between economies of scale achievablewithinafacilityasproductionlevelsincrease,andthecostoftrans-porting materials farther to reach a broader customer base.Theaggregatesindustryalreadyexhibitsatrendtowardsmega-quarry production, and experts and producers alike see increas-ingly consolidated operations as the likely future of production(Bliss et al., 2002). Megaquarries have been defined as sites pro-ducingatleastfivemillionmetrictonsperannum(Mtpa)withsuf-ficient reserves to permit 50–100years of production(Bliss, 2003).Megaquarries are attractive to aggregate and crushed stone pro-ducers, inpart, becausetheycanrealizeeconomiesof scaleintheirquarryactivities,andmayfindothereconomiesofscaleinprocess-inganddeliveryoperations.Cementproducerswouldseethesamebenefits in megaquarry production sites as aggregates producers.Because cement plants and quarries are often co-located, cementproducers may realize additional economies of scale in their man-ufacturing operations. The Great Lakes region, here defined as theUS states of Michigan, Ohio, Indiana, Illinois, and Wisconsin, is anexcellent candidate for megaquarry development due to relativelyabundant limestone resources and access to an extensive water-based transport network.As of 2004 three sand-and-gravel (aggregate) quarries in theUnitedStates mettheproductionrequirement of 5Mtpanecessaryto be considered megaquarries (Bolen, 2004). And, in 2005, 17crushed-stone quarries met the production level for megaquarrystatus (Bolen, 2004; Willet, 2005). Estimates of reserves are notavailable for any of these operations, however, so only some maytechnically qualify as megaquarries.While finding a site with enough reserves to support at least5Mtpa of production for upwards of 50years might be difficult,obtainingapproval tosite afacilityfromsurroundingcommunitiesis also a significant barrier to megaquarry development. For in-stance, the Glensanda, Scotland megaquarry was permitted in thelate1980s, but hassincefacedoppositiontoexpansion(BBCNews,2005). In Harris, Scotland, another effort to set up a megaquarrythat would extract 9Mtpa with reserves for 60years of operationalso failed. Despite years of negotiation and investment, the oper-ation was cancelled in the face of local opposition (BBC News,2004). While we cannot quantify this aspect of megaquarry devel-opment, it is noted here as an additional important variable thatinfluences the siting of industrial facilities.  2.2. Economies of scale in cement production Norman (1979) estimated the economies of scale in US cementplants, and also reported on other studies performed in the Euro-pean cement industry. Fig. 1 shows Norman’s modeling results,as well as values from a 1971 European analysis (Pratten, 1971).Norman’s estimate suggests that the largest economies of scalearerealizeduptoabout1Mtpa,withsmallerincreasesuptoabout2Mtpaand essentially noreductionsin averagecost at higher pro-duction levels. Both cases evaluated production only, and did notaccount for effects related to transportation and distribution of ce-ment to market. Although these studies are relatively old and theeconomiesofscaleachievableinmoderncementplantshaveprob-ablyincreased, they provide a basis for evaluationof existing plantcapacity as a lower bound for potential economies of scale. Withrespect to the Great Lakes region, this comparison suggests that,withthe exceptionof Lafarge’s Alpena plant in Michgian, all plantscould benefit from increasing production levels.McBride (1981) estimated the minimumefficient size (MES) forcement plants to realize all potential economies of scale, transpor-tation and distribution aside, based on data reported between theyears 1949 and 1971. The MES increased steadily over that timeperiod due to improvements in technology. Since 1971 improve-ments have continued in kilns, process control technologies, andother manufacturing components, indicating that economies of scale might be achievable at even higher production capacities.McBride (1981) states that the MES will always be larger thantheoptimalsizewhenthecostofdistributionistakenintoaccount,becauseunlessaverylargemarketisproximal,theMESusuallyex-ceeds the local demand for cement. Thus, efficient and cost effec-tive transportation is a key factor in determining the practicalMES for a plant. The data shown in Fig. 2 may support this theory.The Alpena plant, whichis located on the Great Lakes and can takeadvantage of efficient water transport, is the only plant operatingat a rate of more than 2Mtpa.  2.3. Transportation in the cement industry Domestic freight transportation alone accounts for approxi-mately 7.6% of all US energy consumption (Energy InformationAdministration, 2006; Federal Highway Administration, 2005).Fossil fuels provide most of the energy used for transportation of freight. Thus, freight transport is a concern for greenhouse gasemissions, other air pollution, and non-renewable resource deple-tion. If greater consolidation leads to greater distances for cementshipments, environmental burdens associated with freight trans-portation are likely to increase.The cement industry uses three transportation modes to moveits product to market; truck, rail, and barge or boat. In many casesan intermediate point, or terminal, is used to stockpile and storecement closer to consumers. Terminals also provide facilities fortransferring cement from one transport mode to another, such asbargetorailandrailtotruck.IntheGreatLakesregionlargetermi-nals are also attractive because of seasonal constraints on bothconsumption and shipping. Most cement is used during the war-merspring, summerandfall months, andshippinglanesareclosedby ice during the winter. Cement is non-perishable and requireslittle energy and cost to store, so seasonality in consumption andshipping can be accommodated simply by large terminal facilitieswith extra storage.The Great Lakes states support thirteen active cement plants(Fig. 2) with a total production capacity of approximately12.5Mtpa, approximately 14% of total US production. However,the region is a net importer of cement, some of which arrives inthe form of clinker, the precursor to cement (van Oss, 2006). Thelargest plants in the Great Lakes region are located on the shoresof the Great Lakes and have access to efficient water-based trans-port. The Alpena (Michigan) plant is by far the largest plant inthe region, followed by the Charlevoix (Michigan) plant, and bothuse barges as their primary transport mode to cement terminals. 50607080901001100 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 Capacity (million tonnes p.a.)    I  n   d  e  x  e   d   A  v  e  r  a  g  e   C  o  s   t NormanPratten Fig. 1.  Economies of scale in cement production. ( Sources:  Norman (1979) andPratten (1971) in Norman (1979).) 2  A. Kendall et al./Journal of Transport Geography xxx (2009) xxx–xxx ARTICLE IN PRESS Please cite this article in press as: Kendall, A., et al. Megaquarry versus decentralized mineral production: network analysis of cement production in theGreat Lakes region, USA. J. Transp. Geogr. (2009), doi:10.1016/j.jtrangeo.2009.06.007  Many factors control how and why barge, rail, and truck trans-port modes are utilized. Barge routes are limited by the location of navigablewatersandportfacilities.Railislimitedbothbytheloca-tion and connectivity of active tracks and the ownership of thosetracks. Trucks are not as limited because most highways in theUS are open to truck traffic and many local roads and routes areopen to commercial traffic for short-haul deliveries. The cost of these different modes of transport is a function of fuel consump-tion, facility and labor costs, and the cost of infrastructure mainte-nance, all of which vary greatly.These transport modes vary in their costs and impacts, withbargetransportmoreefficientthanrail,andrailmoreefficientthantruck. The US Department of Transportation (USDOT) estimatesthat one metric ton of material can be transported about 87km(54miles) by truck, 295km (183miles) by rail, and 750km(466miles)bybargeon3.8L(onegallon)offuel(MaritimeAdmin-istration, 1994). On this basis, rail is about 3.4 times more efficientthat truck, whereas barge is 2.5 times more efficient than rail, and8.7 times more efficient than truck. 3. Network analysis methods  3.1. Previous work in the field The 1960s heralded the first significant steps towards modernlogisticsforconsumergoodsandproducts.Companiesbegantode-sign strategies and integrate their divisions responsible for han-dling storage, management, and transport of products.Companies increased their savings compared to their prior ap-proach of disjointed and uncoordinated storage and shipment of their products (McKinnon, 2001).Since the development of logistics as a field and the develop-ment of the modern computer, countless optimization models,fromgeneticalgorithms, toagent-basedmodels, toneural networkmodels, have been developed to optimize logistics problems. Asearlyasthemid-1970s,investigatorsbeganresearchingtheimpactof size and location of plants on the cost of producing and distrib-uting products (Karnarni, 1983).Some recent work has focused on the mechanics of modelingfreight movement through networks, especially intermodal freight(Southworth and Peterson, 2000). And, more recently, the geogra- phy of freight logistics has become a focus of study (Hesse andRodrigue,2004).Ourstudycontributestothisareaofinvestigation,combining network analysis methods with questions of the geog-raphy of freight movements by testing the energy use and eco-nomic costs associated with changes in the spatial distribution of production.Our work differs from previous studies in two ways; it is spe-cific to a single commodity, cement, whereas previous work fo-cused on more general questions of geography and freightlogistics, and it tests the effects of a trendtowards larger and morecentralizedproductionsitesintheindustry.Thisresearchalsoteststhe effects of freight transportation optimized for cost versus en-ergy consumption. The most cost-effectivetransport strategy is of-ten equated with minimum energy consumption, and this studycan help evaluate this assertion. Comparisons of this type areessential to intelligent regional scale, land-use decisions.  3.2. The freight transportation network The cement transportation network is multi-modal because itinvolves paths that utilize more than one transport mode. Eachtransport mode participating in the network requires a spatial Fig. 2.  Map of network nodes, includingconsumption centroids, transfer terminals, and cement plants andtheir productioncapacity. This map area includes the US states of MI, WI, IL, IN, and OH.  A. Kendall et al./Journal of Transport Geography xxx (2009) xxx–xxx  3 ARTICLE IN PRESS Please cite this article in press as: Kendall, A., et al. Megaquarry versus decentralized mineral production: network analysis of cement production in theGreat Lakes region, USA. J. Transp. Geogr. (2009), doi:10.1016/j.jtrangeo.2009.06.007  dataset that is a virtual map of all possible paths for each mode.Fig.3showsthemodalnetworksforbarge,rail,andtrucktransportmodes (Vanderbilt Engineering Center for Transportation Opera-tions and Research, 1999; Federal Highway Administration, 2003;Federal Railroad Administration, 2003).In addition to the network lines representing transportationmodes, three types of network nodes are needed: plants that pro-duce cement; terminals that store and transfer cement, and pointsof consumption (Fig. 2). Cement plant locations are based on data-sets from the USGS (United States Geological Survey, 2003).Consumption of cement is modeled by consumption-weightedgeographic centroids for polygons consisting of one to seven coun-ties depending on size and population density. Centroids areweighted using the combined population of all the counties thatthey include and the per-capita average cement consumption forthe host state.Cement terminal locations and the transport modes they areequipped to serve are derived from addresses of terminals forcement companies as listed in an annual industry publication(CementAmericas,2005). ThesenodaldatasetsareshowninFig. 2. Allpathsevaluatedinthestudybeginatacementplantandendat a consumption centroid. Access and egress links from all points,such as cement plants, cement terminals, and consumption cen-troidsmustbeaddedtothenetworkinordertocreateconnectivitybetween the layers. Transfers between modes are restricted to ce-ment terminal nodes. Fig. 4 shows a schematic representation of how the different network datasets can interact and a possiblepath for cement delivery.Network analysis identifies the most efficient path from onepoint to another by performing least-cost path calculations. Thesecalculations depend on the impedance factor assigned to each partof the path. Impedance is a measure of the resistance encounteredwhen traversing a node or line segment. If the parameter of inter-estistime,forexample,thentheaveragetimeoveradistance(e.g.,h/km) for each segment of the path will be the impedance value.Under these conditions fast roads have less impedance and willbe selected over slow ones, all else equal. However, because theobjective is to identify the overall route with the least impedance,in this example of time as the parameter of interest, selection of apath is a function of both road speed and total distance traveled.Economic cost, energy consumption, pollution emissions, or timeare all parameters that can be modeled by appropriate impedancefactors.  3.3. Transportation costs: monetary and energy costs of freight transport  Transportation costs were estimated from two main sources.The first are from the Bureau of Transportation Statistics (BTS),which produces average revenue data for all freight transportationbytruck, class I rail, and barge (Bureauof Transportation Statistics,2004). Average revenue values for 2003 were brought forward to2005 dollars using the Consumer Price Index (CPI) for transporta-tion. The results in per ton-km are costs of 20.54¢ for truck,1.73¢ for class I rail, and 0.55¢ for barge. As these are revenue fig-ures, they can only be considered the upper boundary of transportcost for each mode assuming each industry is operating at-cost orat a profit. Additionally, because profitability between modes mayvary, the relative costs between modes can only be considered arough estimate.The second source of data is a cost study performed for theWashingtonState Department of Transportation (WDOT) to exam-ine options for the transport of wheat ( Jessup and Casavant, 1998). Broughtforwardto2005dollars,theWDOTstudyreportedcostsof about 0.65¢ per ton-km for barge transport, 2.06¢ for rail, and 4–7.5¢ for truck. These estimates are close to the BTS estimates forbarge and rail, but significantly lower for truck. This might be ex- Fig. 3.  Maps of freight transportation modes, including barge/boat routes, roads and highways, and active rail tracks. z z    CentroidTerminalNavigable WaterwaysTransfer TerminalRail LinesRoads and Highways z z    PlantTerminalTransfer TerminalEnd: Consumption Centroid z z    CentroidTerminalNavigable WaterwaysTransfer TerminalRail LinesRoads and Highways z z    PlantTerminalTransfer TerminalEnd: Consumption Centroid Fig. 4.  Example of network dataset connectivity used in this study.4  A. Kendall et al./Journal of Transport Geography xxx (2009) xxx–xxx ARTICLE IN PRESS Please cite this article in press as: Kendall, A., et al. Megaquarry versus decentralized mineral production: network analysis of cement production in theGreat Lakes region, USA. J. Transp. Geogr. (2009), doi:10.1016/j.jtrangeo.2009.06.007
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