Retail Carbon Footprints: Measuring Impacts From Real .
Retail CarbonFootprints:MeasuringImpacts fromReal Estate andTechnology
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CARBON FOOTPRINTS AND RETAIL BEHAVIORSOF CONSUMERS21st century consumers face unprecedentedchoice when purchasing goods and services. Agrowing body of research has been investigatingwhat impact consumer choices have on carbonuse, GhG emissions, and climate change. Theresearch has a shared concensus, consumerdecisions are carbon emitting. However, someconsumer decisions, choices by logistics andsupply chain providers, transportation and eventechnological solutions contribute to more GhGemissions than less.As a real estate group, our goal was to focus onhow real estate, urban planning and technologyimpacts the total GhG emissions that a retailconsumer initiates when they make a purchase.We present in our research where all decisionmakers can make a contribution to minimizethe carbon footprint from their business andretail behaviors.“Our goal is tounderstand the carbonfootprints of consumerretail behavior. As thepurchase and deliveryof goods has expandedto include numerouschannels, we want tomeasure the role of realestate, transportation,and technology. Theobjective is to helpthose involved in thesupply, delivery, andreception of goodsto minimize carbonfootprints.”DR. ANDREA CHEGUTMIT REAL ESTATE INNOVATION LAB3
WHICH RETAIL STRATEGY PROVIDES THE LOWESTGHG EMISSIONS OUTPUT?Over the last quarter of a century, no asset classin real estate has seen more transformationthan the retail sector, due to advances intechnology, innovations in the supply chain andever-advancing changes in consumer behavior.Where once consumers flocked to suburbanshopping malls and the brick-and-mortar storesof city streets, ecommerce - combined withnext-day delivery capability - has completelyaltered how we purchase all forms of goods.Coinciding with this transformation, climatechange across the globe has now reacheda point where it is unquestionably impactingour environment, economy and resiliency as asociety. The question we must now ask is whichof these forms of consumer behavior leads tolower carbon emissions, and is better for theworld in which we live. This analytical studyaims to investigate and measure consumers’Greenhouse Gas (GhG) emissions whileengaging in either ecommerce purchasing orthe more traditional purchasing from brick-andmortar stores.Identification StrategyOur study began by reviewing previous researchconducted in this area and focused on the majorfactors that have had the most impact on carbonemissions, such as transportation. However,as the retail ecosystem has expanded, it hasbecome clear that there are numerous otherfactors that are having a major impact on GhGemission levels. These include the real estatefootprint of buildings, logistical systems, theproduction of packaging and boxes, and newtechnologies.4
PRECEDENT STUDIESThe question of which system has a greater impact on GhG emissions has led to research on howthese different types of retail behaviors are impacting GhG emissions, and numerous articles andpublications have been generated in recent years. Previous research takes into account variousassumptions about consumer behavior, the logistics ecosystem and consumer transport. Notably,these studies suggest that carbon emissions are generally lower for consumer retail strategiesthat engage in ecommerce. Our goal within this study is to dig further into these findings, expandon previous assumptions and introduce a number of increasingly significant ntal analysis of usonline shopping‘pure players’ of ecommerce havefewer emissions on average thathybrid models with in-personshopping trips by car2017Green LogisticsPresents a systematic methodologyfor measuring carbon footprint impact.2017Estimating the CO2 intensityof intermodal freighttransportationSuggests employing public transportinfrastructure for logistics parceldelivery.2018Changes in Online ShoppingBehavior During the LastDecadeDetermines that a specific sectorof the population is more drawntowards online shopping. Presentsrelationships between shoppercharacteristics.2018The Modern Supply Chain:A New Model for DefiningLogistics Real EstateFramework for determining thedevelopment criteria of new last-mileproperties.2019Product carbon footprintacross sustainable supplychainPresents a comprehensive studyof the constituent parts of thesupply chain and how to make a fullassessment.2020Comparative GreenhouseGas Footprinting of Onlineversus Traditional Shoppingfor Fast-Moving ConsumerGoods: A StochasticApproachAnalyzes data from multiple countriesto determine that e-commerce is notalways the least carbon-intensive formof retail.MIT, EPFLBlanco, SheffiUnitedStates,MITBlancoUnitedStates,MITPineda BlancoUnitedStates,UC DavisPrologisUnitedStates,PrologisResearchHe et. al.PR China,ShanghaiUniversityShahmohammadi,Van Loon, et. al.UnitedStates,ES&TMagazineTable 1. Precedent Studies.5
“The question is not whetherecommerce or brick-and-mortar retailis better or worse for GHG emissions.It is more about what decisionsconsumers, retailers, ecommerceand logistics stakeholders can maketo minimize GHG emissions. There issomething that everyone in the supplychain can do to help mitigate climatechange.”JAMES SCOTTMIT REAL ESTATE INNOVATION LAB6
RESEARCH APPROACHWhat are the Carbon Footprints of ConsumerRetail StrategiesDoes the carbonfootprint vary overe-commerce,brick-and-mortar,and hybrid retailstrategies?How can variousinterventionsreduce carbonfootprints?As outlined, this study aims to measure thecarbon footprint of consumer behaviors inecommerce by assembling the relevantvariables and then simulating scenarios wherea range of parameters can be modified. Toaid in this research, a Monte Carlo simulationwas executed using 10,000 trials to producemeasurable results which were then plotted foranalysis to illustrate which strategy producedthe lowest GHG emissions. In total, we did closeto 48 different simulations for a total of 480,000trials. Furthermore, it gave us the opportunity toconstruct opinions on which solutions have thegreatest chance to succeed in this context.Are thereconditionalstrategies whereecommerce andbrick-and-mortarresult in differentemissions? What proportionof carbonfootprint comesfrom real estate,transportation,logistics andconsumers?Are there conditional strategies whereecommerce and brick-and-mortar result indifferent emissions?What proportion of our carbon footprintcomes from real estate, transportation,logistics and consumers?For the purpose of establishing a measurableframework, and to help look at the big pictureof the supply chain while getting a betterunderstanding of the carbon footprint of eachfulfilled order, we also developed a system maptaking into account the logistics, consumer, realestate, packaging and transportation elementsof the process. Finally, it should also be notedIn order to help focus our research we also that we focused primarily on the aspects of theconstructed four essential questions which we final part of the supply chain, or the last-mileportion of the overall process, as this is theaimed to answer in the course of our analysis:most distinct and where the true differencesbetween traditional purchasing and ecommerce Does the carbon footprint vary overecommerce, brick-and-mortar and hybridpurchasing happen.retail strategies? How can various interventions reducecarbon footprints?7
BREAKING DOWN FURTHER RETAIL CARBONFOOTPRINTPortTraditional Retail rRetailStoreCustomer raditional Ecommerce ReturnsBoth ChannelsFig 1. Retail Supply Chain Model: Brick-and-Mortar and Ecommerce.Retail Supply Chain Model: Sources of EmissionsThe port facility serves as a placeholder titlefor the origin of the product. The product thenbegins its trip through the supply chain bytraveling to the Consolidation Center, which is thefirst layer of property, common to all channels.property called a Regional Distribution Center.In the traditional retail channel, once items haveleft the Consolidation Facility, they arrive at aDistribution Center and are then shipped to theRetail Store, where individual shoppers head toThe path then forks for both channels. In the in order to pick up the product and bring home,ecommerce channel, the next step for the traveling in a vehicle of their own choosing.parcel becomes the Last-Mile facility, wherethe product is handled for the final time before Beginning at the customer address in all retailgetting shipped to the end customer address. In channels, the returns are sent back to an alternatethe non-coastal state markets (these are, as the distribution center or retail store, depending onname implies, states without direct access to the channel. Reverse logistics GhG emissionseither the Pacific or Atlantic oceans), the product are conceptualized.passes through one additional preceding8
ASSESSING CARBON FOOTPRINTSLogistics LegConsumer andProductTransportationPackagingLAST MILEReal EstateAggregationCarbon Footprint perOrder FulfilledNote: our unitof interest forunderstandingcarbon footprintsDeliveryFig 2. Model of Carbon Footprints per order.While this analysis found similar conclusionsto previous studies, the research showcaseshow important the role of real estate and, moreimportantly, its location is in helping mitigateconsumers’ GhG emissions. We illustratethat when consumers increase the numberof their purchases - whether by isolatinghousehold shopping trips into one large tripto gather as many goods as possible in onepickup, or by consolidating many purchasesinto the e-commerce logistics ecosystem there is a principal of scale that consumersare tapping into. However, consumer behaviordoes not generally work this way. The averageU.S. consumer makes at least 300 shoppingtrips per annum1, and these individual trips areunable to consolidate enough to compete withthe reduction of carbon emissions that thee-commerce system brings. It is also importantto remember there is another layer of complexitywhen factoring in that consumers can makespecific choices that impact their own GhGemission footprint.1. Statista. (n.d.). Consumers’ weekly grocery shopping trips in theUnited States from 2006 to 2019. Retrieved January 2021, ld/9
“In traditional brick-and-mortar,ecommerce, and combined retailstrategies, boxes account for someof the largest carbon pollutants in theecosystem.”DIEGO FERNÁNDEZ BRISEÑOMIT REAL ESTATE INNOVATION LAB10
SIMPLE MODELEcommerce Average Emissions bySources2%KgCO2e / Item15%25%13%45%Traditional Retail Average Emissionsby Sources4%7%1%18%TrialsFig 3. GHG Emissions by Brick-and-Mortar vs. Ecommerce.Base Case ScenarioThe primary findings are shown on the basecase simulation results, which will be used asa benchmark to compare the different interventions’ impact. By using our standard method ofsubtracting ecommerce values from traditionalretail ones, the marginal results range from amaximum of 3.400 kgCO2e/product to a minimum of 0.880 kgCO2e/product. These are theextremes. However, the mean sits closer to0.440, which is where a large concentration ofthe trials are.70%Return RatesExcedentLogistics sProperty-LevelEmissionsFig 4. GHG emissions Breakdown by Sources.11
KgCO2e / ItemKgCO2e / ItemFig 5. Breakdown of Carbon Footprints by Ecommerce and Brick-and-Mortar Retail.The figures above illustrate the leading factors of GhG emissions for both ecommerce and brickand-mortar retail. For ecommerce, property-level emissions are the greatest contributor to overallemissions, while transport-level emissions contribute the most significantly in traditional retail.12
INTERVENTIONS IN THE SIMULATION:WAYS TO DECREASE THE CARBON FOOTPRINT“Location,Location, Location”Optimize real estatelocation selectionand urban planningpermitting to limitGHG emissionsfor supply chainoperations.“Change the Tech”“Shift the Scale”Technologicalchange will havean impact for bothconsumers andfirms as they switchout their technology.What becomes thelargest efficiency ischanging the scaleof goods that can bedelivered or broughtat one time.Technology can help reduce the carbonfootprintIn the coming years, we will see a number of newtechnologies being developed and deployed tohelp lower GhG emissions. Among these areelectric fleets, drones and autonomous vehicles.However, these technological advances will notbe a solution until frictions in the ecosystem arefundamentally addressed. For example, dronesmay help with rural delivery carbon emissions,but in the meantime existing carrier servicessuch as the U.S. Post Office already provide aninvaluable service of delivery packages everyday. In contrast, clean energy solutions, jobgrowth, decreased GhG emissions and costefficient electricity sources for electric andautonomous vehicles are a far more importantinvestment.“Nudge theBehavior”Investing intechnology thatdisrupts theexisting modes offdelivery will helpthe system removecarbon emissionssubstantially.Packages and Returns contribute to GhGemissionsFurthermore, we’ve established that someof the greatest investments we can make inlimiting our GhG emissions are in respect tohow packages are boxed or returned to stores.In both traditional e-commerce and combinedretail strategies, boxes account for some of thelargest carbon pollutants in the ecosystem.Removing layers of packaging, changingboxing dimensions to be more efficient, oreven removing boxes altogether can reducecarbon emissions by up to 36% percent.Moreover, free returns have led consumers tofeel more comfortable adopting ecommerceas a viable retail option, which then leads to anincrease in GhG emissions. Further investmentin alternative materials, as well as advancedtechnologies like Reality Capture and ImageRecognition – possibly leading to a reduction inreturns - can lead to decreased trips and moreintelligent packaging.13
INTERVENTIONS IN THE SIMULATION: DETAILSIntervention: “Delivery fleet electification.”Description: All supply trucks are electrified. Passenger cars are the only vehicles left without electrifying.Intervention: “Everybody electrifies.”Description: All vehicles are electric, passenger and supply.Intervention: “I own a Prius.”Description: All passenger vehicles are hybrid (tailpipe GHG is less than 256).Intervention: “I own a Tesla.”Description: All passenger vehicles are electric (GHG is equal to mileage * jurisdiction electricity GHG intensity).Intervention: “Bundle Packages.”Description: Average product per shipped box is 2.0.Intervention: “Let’s go shopping.”Description: Average basket size for the traditional retail consumer is 10.0 products on average per shopping trip(base case uses 2.60 on average).Intervention: “Locker use.”Description: Last-delivery vehicle does not deliver to individual addresses, but rather to a centralized location(reduces the distance of the last portion of the drop trip for ecommerce).Intervention: “Region 1 Hyperurban.”Description: Uses only urban metro jurisdictions such as NYC Metro, LA Metro, Chicago Metro, South FloridaMetro, etc.Intervention: “Region 2 Coastal.”Description: Uses only state-level jurisdictions which have a direct access to an ocean. Examples includeFlorida, Texas, Oregon and Maine.Intervention: “Region 3 Noncoastal.”Description: Uses only state-level jurisdictions which do not have direct access to an ocean. Such as Ohio,Wyoming, Michigan, Nevada, etc.Intervention: “LastTouchTM Facility.”Description: Utilizes Q-zero (minimum distance) for the second distance quartile of the properties trip to anaddress. In other words, last-mile facilities are shifted to have the same average distance as traditional retailstores.Intervention: “No boxes.”Description: Reduces 80% of cardboard boxes for ecommerce and replaces them with the GHG emissions ofpaper bags.Intervention: “Out for a hyperurban walk.”Description: Uses only urban metro jurisdictions and reduces all emissions for the passenger vehicle, as thiselement is replaced by a zero-emissions transport mode. Such as walking or biking.Intervention: “Restrict Returns.”Description: Reduces 50% of ecommerce excess-GHG attributed to returns. This intervention reducesecommerce returns to approximately 15% overall. Traditional retail has an average of 7.5%.14
AVERAGE AND OUTLIER TRIAL OUTCOMES FROMSIMULATIONSIn the “Urban Last-Mile Facility” scenario, the location improvement accounts for a50% decrease in all emissions coming from the transportation source. This strategy,combined with making vehicles more efficient, can bring the urban shopper furtherfrom the point of indifference between choosing ecommerce or driving to the neareststore, helping cement the advantages of the former.In an extreme case, the savings from “Urban Last-Mile Facility” could be so importantas to even render shopping trips using public transport equivalent to ecommerce.In the “I Own An Electric” scenario, on average, increasing the efficiency of the personalshopper vehicle effectively enables the brick and mortar shopper to engage in personaltrips over ordering online because the emissions lower by such a substantial amountthat it makes the shopper indifferent to both strategies, from a carbon emission pointof view.Moreover, in an extreme case where the shopper belongs to a jurisdiction with alow fossil fuel component in electricity, it could even result in surplus emissions forecommerce, when comparing. This effectively unburdens the shopper from anyinefficiencies in the system.In an “Everybody Electrifies” average scenario, ecommerce will not be able to competewith brick and mortar if the shopper electrifies, unless a more efficient alternativedelivery vehicle contender appears. Or, unless the composition of electricity countrywide is cleaner.In the case that the carbon-conscious shopper does not wish to purchase an EV, theyshould know that they can always increase the amount of products purchased in asingle click. In the “Bundles Packages” scenario, on average, a shopper can makesignificant reductions that can result in 30% less total emissions when ordering two ormore products that fit inside the same box.However, it also turns out that bundling items in brick-and-mortar shopping has amuch more impactful effect than bundling in ecommerce. As emissions get reducedby 50% in total when purchasing 10 or more products in a single car trip.According to the “No Boxes” scenario, a retailer who is willing to eliminate a significantportion of the boxes will see 36% of the total ecommerce emissions reduced. This isan easy target to achieve by ecommerce retailers that can substantially tilt the balancein their favor.15
In the “Restrict Returns” scenario, a shopper can become more informed about thesizing and qualities of the product they are ordering and restrain from returning items.By doing so, they improve the overall efficiency of the system and the carbon footprint.In an extreme scenario, where an online retailer uses augmented reality capture toreduce almost all returns while maintaining the same volume of orders, the shopperwill achieve similar revenue margins to those of brick and mortar with a much morecarbon-clean operation.Lastly, the “Out For A Walk” scenario has the lowest footprint for traditional retail, lessthan ecommerce in 100% of the cases. As transportation carries such a consequentialweight for the brick and mortar channel, this means that any effort to aminorate thispart will yield great results.Only in the extreme event that fulfilment can also be done from within the same urbanarea, and using efficient EVs for delivery, will ecommerce pose competition for brickand mort
Beginning at the customer address in all retail channesl , the returns are sent back to an atel rnate distribution center or retail store, depending on the channel. Reverse logistics GhG emissions are conceptualized. Retail Supply Chain Model: Sources of Emissions Port Start Start End End Traditional Retail Returns Ecommerce Returns
Footprints map energy flow and carbon emissions in the U.S. manufacturing sector, from energy supply to end use. The footprints show where energy is used and lost—and the associated greenhouse gases (GHGs) that are emitted. Each footprint visualizes the flow of energy (in the form of fuel, electricity, or steam) to major end
environmental footprints were compared to the use of neat polypropylene and composites containing glass fibers. The assessment of carbon, ecological, and water footprints was conducted from the raw materials stage, which takes into account their acquisition and production, to the final product obtained by injection molding technology.
Calculate your carbon footprint and make changes to reduce it Students will explore the concept of a carbon footprint, calculate their yearly carbon footprint and create a picture informing others how to reduce or offset their carbon footprints. Learning outcomes By the end of this activity, students will: calculate their carbon footprint and .
Core-Retail Sales: n/a Number of Stores: 182 Jobs in Retail: 3,345 YUKON Total Retail Sales: 799.8 million Core-Retail Sales: 508.8 million Number of Stores: 186 Jobs in Retail: 3,630 BRITISH COLUMBIA Total Retail Sales: 84.3 billion Core-Retail Sales: 54.0 billion Number of Stores: 20,398
Core-Retail Sales: n/a Number of Stores: 182 Jobs in Retail: 3,345 YUKON Total Retail Sales: 799.8 million Core-Retail Sales: 508.8 million Number of Stores: 186 Jobs in Retail: 3,630 BRITISH COLUMBIA Total Retail Sales: 84.3 billion Core-Retail Sales: 54.0 billion Number of Stores: 20,398
September 2015 Executive Summary This project compared the carbon footprints of using traditional metallurgical coke relative to using Pennsylvania produced anthracite in two applications in the iron and steel industry: use as a fuel and reducing agent in blast furnaces, and use as an injection carbon in electric arc furnaces.
could pre-cut the letters of a message and paint footprints onto them. You could use masking tape to write a message on a large sheet of paper and then make footprints all over the paper. Once the paint has dried, peel off the masking tape to reveal a message. Make footprints on large sheets of paper or
Creating an economy that harnesses artificial intelligence (AI) and big data is one of the great opportunities of our age. This Sector Deal is the first commitment from government and industry to realise this technology’s potential, outlining a package of up to 0.95bn of support for the sector, which includes government, industry and academic contributions up to 603m in newly allocated .
