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Food Demand Scenarios in 70 World Regions, 2010-2060
Creator
Vinuales, J, University of Cambridge
Pollitt, H, Cambridge Econometrics
Salas, P, University of Cambridge
Study number / PID
855012 (UKDA)
10.5255/UKDA-SN-855012 (DOI)
Data access
Open
Series
Not available
Abstract
This dataset contains food demand and food demand projections by 19 different types in physical tonne for 70 world regions. The scenarios were produced using the intergrated assessment model E3ME. The data for the E3ME food equations is taken from FAO, which captures detailed food supply data and for the purpose it is being used for, at the country level. The data produces forecasts up to 2060 (from 2010) under 2 different scenarios: (i) baseline, based on FAO projections, and (ii) food_tax, a scenario with additional taxes on soy demand in China and Brazil, increasing linearly from 2% in 2025 to 10% by 2030 and held constant thereafter.This proposal aims to develop a framework of analysis and policy engagement to improve the resilience of the Brazilian Food-Water-Energy (FWE) nexus to global environmental and economic change. It will combine established UK expertise and specifically developed, state-of-the-art analytical capacity in socio-economic and environmental modelling to build a robust environmental policy assessment methodology for the Brazilian FWE nexus in the context of global change. The modelling capacity, skills and knowledge will be transferred to relevant actors in Brazil to enable local academics to continue informing and engaging policymakers through a continued sustainability transition during and beyond the end of this project.
Brazilian society faces significant uncertainty due to two significant global contextual factors. On one hand, global environmental change, due to global unsustainable resource use and greenhouse gas emissions, is highly likely to change weather patterns, which will affect detrimentally the land cover and biodiversity in Brazil, with severe impacts on agriculture. On the other hand, without appropriate policies in place, the Brazilian economy and environment, relying heavily on exports of natural resources for prosperity, can be vulnerable to global economic change, where changes in demand for commodities could lead to...
Terminology used is generally based on DDI controlled vocabularies: Time Method, Analysis Unit, Sampling Procedure and Mode of Collection, available at CESSDA Vocabulary Service.
Methodology
Data collection period
01/10/2016 - 30/03/2020
Country
Belgium, Denmark, Germany (October 1990-), Greece, Spain, France, Ireland, Italy, Luxembourg, Netherlands, Austria, Portugal, Finland, Sweden, United Kingdom, Czech Republic, Estonia, Cyprus, Latvia, Lithuania, Hungary, Malta, Poland, Slovenia, Slovakia, Bulgaria, Romania, Norway, Switzerland, Iceland, Croatia, Turkey, Macedonia, United States, Japan, Canada, Australia, New Zealand, Russia, Belarus, China, India, Mexico, Brazil, Argentina, Colombia, Rest of Latin America, South Korea, Taiwan, Indonesia, Rest of Asean, Rest of OPEC excluding Venezuela, Rest of the World, Ukraine, Saudi Arabia, Nigeria, South Africa, North Africa OPEC, Central Africa OPEC, Malaysia, Kazakhstan, Rest of North Africa, Rest of Central Africa, Rest of West Africa, Rest of East Africa, Rest of South Africa, Egypt, Democratic Republic of Congo, Kenya, UAE
Time dimension
Not available
Analysis unit
Geographic Unit
Universe
Not available
Sampling procedure
Not available
Kind of data
Numeric
Data collection mode
Not available
Funding information
Grant number
ES/N013174/1
Access
Publisher
UK Data Service
Publication year
2021
Terms of data access
The Data Collection is available to any user without the requirement for registration for download/access.