ّ سيناريوهات النمو ال َح رضي المملكة األردنية الهاشمية 2018

Korea WORLD BANK GROUP Green Growth Trust Fund Urban Growth Scenarios for The Hashemite Kingdom of

This is a project developed in coordination with the Ministry of Planning and International Cooperation (MoPIC) and the Ministry of Municipal Affairs (MoMA) to outline sustainable development paths for five Jordanian cities: , , Mafraq, Russeifa and .

Duration: April to December 2017.

2 Objective To compare the environmental, social and economic impacts of different urban growth paths for five Jordanian cities to guide the identification, preparation and implementation of sustainable urban investment projects.

Through the completion of the project, governments are expected to: • Create consensus with stakeholders. • Request funding from cooperation agencies. • Disseminate the potential benefits of their projects. • Test rough ideas and present solid proposals. • Convince others by providing numerical data. Land GHG Infrastructure Municipal consumption Energy emissions costs services costs

2 JD / capita

km kWh/capita/annum kgCO2eq/capita/annum Millions of JD BAU

2

km kWh/capita/annum kgCO2eq/capita/annum Millions of JD JD / capita MODERATE

2 kWh/capita/annum Millions of JD JD / capita

km kgCO2eq/capita/annum

GROWTH COMPACT

2

km kWh/capita/annum kgCO2eq/capita/annum Millions of JD JD / capita VISION

4 Three steps in our methodology Identify problems and solutions, estimate indicators and disseminate the results

Decision makers explain the A multidisciplinary team models Decision makers use the outputs to: problems that their city is the possible outcomes from the * Create consensus facing and the solutions that implementation of such * Request funding they are currently exploring. solutions in a palette of * Disseminate potential benefits indicators. 5 A long process with a large team Technical staff of the five municipalities and LTRC, DOS, DLS, MoMA and MoPIC were involved. 10 workshops meetings months

Urban concerns

Policy levers Source: CAPSUS photo archive 2017. 6 Data sources Data from local governments was adapted and complemented with international sources.

Local sources: International sources: • Population and Housing Census, DOS 2015 • Global Human Settlements Built-up Grid, • Population projections, DOS 2017 European Commission JRC 2015 • Urban Master Plans, MoMA 2010 and GAM • Gross Domestic Product spatial distribution derived from night-lights satellite data, • Shp files with public transport routes, LTRC 2010 NOAA 2010 • Shp files with location of urban amenities, MoMA • Open Street Maps 2017 and Municipalities • Jordan Water Sector Facts & Figures, MoWI 2015 • NEPCO Annual Report, NEPCO 2016

Policy levers 7 https://ngdc.noaa.gov/eog/dmsp/download_gdp.html http://export.hotosm.org/en/ http://ghslsys.jrc.ec.europa.eu/datasets.php Clean Green Efficient Public Landmarks Solid energy Building public Reduce Scenarios transport waste generation Code lighting hazards

Situation in 2015

No policy levers. The city grows following historical trend.

Growth according to the Master Plan

Growth Planned Planned Transfer according to the routes station 14% 100% Master Plan +

Compact growth

Planned + Planned + 70-90% Compact Transfer 10-16 alternative alternative New 100% growth routes parks station MW dwellings + Urban expansion modeling – BAU scenario Machine learning algorithms predicted the expansion for the BAU scenario.

Three machine learning methods were used to model the expansion of the cities if past trends continue: • Random Forest • Extratrees • Logistic Regression

TN: True negative TP: True PositivePolicy leversFP: False Positive FN: False negative 9 Urban expansion modeling – alternative scenarios Programmatic modeling was used to create alternative urban growth paths.

Moderate scenario • Human settlement is allowed only in zoned areas (no irregular settlement)

Compact growth scenario • Vacant-housing rate is reduced (24% to 8%) • New housing is prioritized near employment and transit

10 Indicators calculation methods Calculation methods are designed considering the key variables modified in the different scenarios.

Energy for public lighting To estimate the energy saving due to replacing public lighting bulbs with LED bulbs, the key variable in the calculation method was the percentage of light bulbs that are LED. But, to reflect also how much energy will be needed to illuminate the expansion area of the city by 2030, the method should consider the kilometers of streets as one variable that could change depending on how much the city grows in each scenario. Non-LED bulbs number (num_bulb)

Kilowatts hour per person per year LED number (num_led) [kWh/person per yr] Total built-up area (footprint_km2) Policy levers 11 Land GHG Infrastructure Municipal consumption Energy emissions costs services costs 17.19 4,039 1,217 97.38 71 2 JD / capita

km kWh/capita/annum kgCO2eq/capita/annum Millions of JD BAU

2030 9 bus Planned 7.06 3,895 1,177 40.01 60 2 14% km kWh/capita/annum kgCO2eq/capita/annum Millions of JD JD / capita 1 TS 100%

MODERATE Artisanal

0.00 3,573 1,077 11.09 58 2 kWh/capita/annum Millions of JD JD / capita

km kgCO2eq/capita/annum

inhabitants inhabitants by

IRBID

GROWTH COMPACT

9 bus Planned 0.00 3,487 1,056 10.93 54 70% 2 km kWh/capita/annum kgCO2eq/capita/annum Millions of JD JD / capita

1,040,898 1 TS

VISION 100% Artisanal 16MW 12 up.technology/up_jr

13 Future plans from local stakeholders We expected a request for scaling-up the tool. But they found applications beyond our expectations.

At the end of the project, local stakeholders were particularly interested in: • Developing a national-level tool to assess the sustainability of future Master Plans. • Creating a geoportal, a web-based open platform for spatial data sharing which would foster collaboration and evidence-based urban planning.

Policy levers 14 Thanks!

Ricardo Ochoa Sosa CAPSUS S.C. www.capsus.mx [email protected]

Korea Green Growth مجموعة البنك الدولي Trust Fund 15