Marzo 11, 2015

beer logiscs for cies. beer cies for logiscs.

Webinar LEDS LAC – Marzo 11, 2015

hp://megacitylab.mit.edu

E.Blanco © 2015 • Do not copy or quote without authorizaon 1 E.Blanco © 2015 • Do not copy or quote without authorizaon 2 E.Blanco © 2015 • Do not copy or quote without authorizaon 3 E.Blanco © 2015 • Do not copy or quote without authorizaon 4 Urbanizaon is here to stay

• Wave of urban growth (2011-2050) – From 7.0 to 9.3 billion – 78% to 86%, developed urban areas – 47% to 64%, less developed urban areas • More cizens, more consumers – 30 to 50 tons of goods per capita – 300 to 400 truck trips per 1000 cizens per day • Urban freight makes up 10%-15% of total miles traveled

Sources: UN(2011), Dablanc(2011), Giuliano et. al. (2013), mashable,com

(1) (5) (78) London ~ 6.5M Tokyo ~ 13M Tokyo ~ 35M Osaka(?), New York ~ 4M New York ~ 12M Mumbai, Mexico City ~ 20M Paris, Berlin ~ 3M Osaka ~ 9M São Paulo, New York ~ 19M Tokyo ~ 1.5 London ~ 8M Shanghai ~ 17M Paris, Shanghai ~ 5M Kolkata, Delhi ~ 16M Beijing, London ~ 15M LA, Buenos Aires ~ 12M Rio, Paris, Manila~ 11M Moscow, Istanbul ~ 10M

Source: E.Blanco (MIT) - MGI, Forbes, University of Cologne .... 45 more

Source: Barbieri, USP, 2012

Source: hp://dailynewsdig.com/high-resoluon-aerial-photos/

Popula'on)Density)0)people)per)sq.km.) 50,000$ 44,000$ 45,000$ 40,000$

35,000$ 32,300$ 30,000$ 25,700$ 25,000$ 22,800$ 19,800$ 20,000$ 16,700$16,600$ 14,400$13,800$ 12,400$12,400$ 15,000$ 11,600$11,300$11,300$11,200$ 10,500$10,100$ 9,900$ 9,800$ 9,800$ 10,000$ 5,000$ 0$

Lima$$ Dhaka$$ Lagos$$ Karachi$$ Bogotá$$Manila$$ Lahore$$ Tehran$$ Istanbul$$ Bandung$$ Singapore$$ Hong$Kong$$ Kolkota,$WB$ Pune,$MAH$ Mexico$City$$ Mumbai$MAH$ Ahmedabad,$GUJ$ Delhi,$DLOHROUP$ (Dem.$Rep.)$Kinshasa$ Korea$SeoulOIncheon$

Source: MIT Megacity Logiscs Lab. Demographia.

People per Store

250

200

150

100

Apaxco Chalco La Paz Acolman Ozumba Tultepec Axapusco Cocotitlán IxtapalucaJilotzingo Tepetlixpa Tezoyuca Nopaltepec Temamatla Zumpango Chicoloapan HuehuetocaHuixquilucan Teotihuacán Tequixquiac ChimalhuacánCuatitlán Izcalli Nezahualcóyotl Tenango del Aire Tlalnepantla de Baz Atizapán de Zaragoza Ecatepec de Morelos Naucalpan de Juárez

Valle de Chaco Solidaridad San Martín de las Pirámides

E.Blanco © 2015 • Do not copy or quote without authorizaon 15 In Summary … • More people, more boxes • More income, more boxes per person • More density, more boxes per km2 • More congeson, more nanostores • More congeson, more home deliveries • More logiscs … same infrastructure…

Good for People Mixed economic acvity, more public transport, less vehicles More public transport, less roads More pedestrian, less roads Bad for Boxes More people, more boxes More consolidaon of logiscs acvies Bigger warehouses, bigger trucks of incoming products Logiscs sprawl

Sources: Giuliano et. al. (2013), Smaller trucks in, with less roads

E.Blanco © 2015 • Do not copy or quote without authorizaon 18 Findings Sanago Case Study Locaon of minimum Loading/Unloading Spaces 4,000 1 1,801 deliveries per km2 2 loading/unloading area establishments/km excludes office supplies & home deliveries • projected at 7,000 for per block Centro Santiago area

Hyphothesized freight parking locaon

Complex urban freight policies

No “blanket” soluons • Diversity of freight needs between economic sectors – Ice cream vs. Computers – Water vs. Cosmecs • Diversity of urban areas

Jurisdiconal Fragmentaon • Metropolitan areas, cies, neighborhoods • Port authories, cies

Image Sources: Pesquisa Origem-Destino 2007 RMSP – Relatório Síntese

Product Planning Proﬁle Driving Pracces Load Customer Engine Expectaons Eﬃciency (Shippers) Equipment Distance Fuel (Carriers) (Network) Congeson types

Fuel Consumpon Infrastructure & CO2

$$$ = D x W x Rate

CO2 = D x W x EF

êRate ≈ êEF

supply chains

urban economy

logiscs system

distribuon network

route delivery or pick-up

driver/city/customer interacons (hours)

last-mile operaons, vehicle ﬂeets (days)

inventory management, facilies, channel management, demand management (months)

mul-company, markets, land-use, infrastructure management, policy (years)

naonal/global economy Regional/Port supply chains planning policy

Local planning urban economy policy logiscs system Oﬀ-hour distribuon network road deliveries LEZ pricing route Rail adaptaon delivery or pick-up

driver/city/customer interacons (hours)

last-mile operaons, vehicle ﬂeets (days)

inventory management, facilies, channel management, demand management (months)

mul-company, markets, land-use, infrastructure management, policy (years)

Source: Winkenbach, Spinler, Blanco (2013)

E.Blanco © 2015 • Do not copy or quote without authorizaon 26 beer logiscs for cies. urban channel strategy excellence in last-mile operaons high-resoluon urban logiscs design beer cies for logiscs. data-driven policy making innovaon in urban freight planning

Thanks!

Edgar E. Blanco • [email protected]

hp://megacitylab.mit.edu