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Frontiers in Big Data Journal (2019). Special Issue. Big Data for Food, Energy and Water, edited by Naoki Abe (IBM Research) and Ranga Raju Vatsavai (North Carolina State University). Contact suchi@bu.edu for preprints. 02.png
With the world population projected to grow significantly over the next few decades, and in the presence of additional stress caused by climate change and urbanization, securing the essential resources of food, energy, and water is one of the most pressing challenges the world faces today. There is an increasing priority placed by the UN and US federal agencies on efforts to ensure the index of these critical resources, understand their interactions, and address common underlying agendas. At the heart of the technological challenge is data science applied to environmental data. We describe a research methodology to frame in the Food, Water, and Energy Systems (FEWS) context in Cambodia, including decision tools to aid policymakers and NGOs to tackle specific UN Sustainability Development Goals (SDGs). By conducting this exercise, we aim to improve the ``supply chain`` of FEWS research, from gathering and analyzing data to decision tools to support policymakers in addressing FEWS issues in specific contexts. We describe research in each of the segments to discuss problems and future research directions.


Article: Fueling Global Energy Finance: The Emergence of China in Global Energy Investment Sucharita Gopal, Joshua Pitts, Zhongshu Li, Kevin P. Gallagher, James G. Baldwin, and William N. Kring Global Development Policy Center, Boston University, Boston, MA 02215, USA Energies 2018, 11(10), 2804; https://doi.org/10.3390/en11102804 Abstract: Global financial investments in energy production and consumption are significant since all aspects of a country’s economic activity and development require energy resources. In this paper, we assess the investment trends in the global energy sector during, before, and after the financial crisis of 2008 using two data sources: (1) The Dealogic database providing cross-border mergers and acquisitions (M&As); and (2) The “fDi Intelligence fDi Markets” database providing Greenfield (GF) foreign direct investments (FDIs). We highlight the changing role of China and compare its M&A and GF FDI activities to those of the United States, Germany, UK, Japan, and others during this period. We analyze the investments along each segment of the energy supply chain of these countries to highlight the geographical origin and destination, sectoral distribution, and cross-border M&As and GF FDI activities. Our paper shows that while energy accounts for nearly 25% of all GF FDI, it only accounts for 4.82% of total M&A FDI activity in the period 1996–2016. China’s outbound FDI in the energy sector started its ascent around the time of the global recession and accelerated in the post-recession phase. In the energy sector, China’s outbound cross-border M&As are similar to the USA or UK, located mostly in the developed countries of the West, while their outbound GF investments are spread across many countries around the world. Also, China’s outbound energy M&As are concentrated in certain segments of the energy supply chain (extraction, and electricity generation) while their GF FDI covers other segments (electricity generation and power/pipeline transmission) of the energy supply chain.



Characterizing the Spatial Determinants and Prevention of Malaria in Kenya (paper in review 2019) Sucharita Gopal, Yaxiong Ma, Chen Xin, Joshua Pitts, and Lawrence Were, Abstract: UN's Sustainable Development Goal 3 is to ensure health and well-being for all at all ages with a specific target to end malaria by 2030. About 70 percent of Kenya’s population lives in malaria risk areas, including vulnerable population of children and pregnant women. Kenya is also one of the 15 high-burden countries in sub-Saharan Africa. The primary objective of this study is to determine the effectiveness of utilizing local spatial variations to uncover the statistical relationships between malaria incidence and environmental and behavioral factors across the counties of Kenya. Figure shows statistical hot spots of malaria incidence in 2015.


Materiality analysis is used to identify critical economic, environmental and social issues, which may either reflect a significant impact on the company's business performance or substantively influence the assessments and decisions of its stakeholders. We establish materiality using NAICS codes of associated industries of the fossil fuel supply chain.


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