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1 Roles and Opportunities for Information Technology in Meeting Sustainability Challenges Innovation in computing, information, and communications tech- nology is at the heart of nearly every large-scale socioeconomic system. Computing underlies and enables systems that affect our lives every day—from financial and health systems to manufacturing, transportation, and energy infrastructures. One important consequence is that advances in computing are critical enablers of change for addressing the grow- ing sustainability challenges facing the United States and the world. A key finding of this report is that information technology (IT)1 will play a vital role in achieving a more sustainable future and that research and innovation in computing, information, and communications technologies are consequently critical to addressing the broad range of sustainability challenges (Box 1.1). The critical global challenges in sustainability are deep, and solutions will require input from many disciplines. Fortunately, there are numerous opportunities to apply IT innovations in ways that will have a profound influence on sustainability efforts across many areas, including the eco- logical and environmental sciences, numerous engineering fields, public policy and administration, and many other areas. The National Research Council’s (NRC’s) Committee on Computing Research for Environmental and Societal Sustainability is aware that there is significant effort aimed at making IT itself “greener” and recognizes that these efforts are important. 1The committee uses the familiar acronym “IT” (information technology) to encompass computing, information, and communications technologies broadly. 13
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14 COMPUTING RESEARCH FOR SUSTAINABILITY BOX 1.1 A Note on the Definition of “Sustainability” and the Focus of the Committee An often-cited definition of “sustainability” comes from the Brundtland Com- mission of the United Nations (UN): “[S]ustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs.”1 The UN expanded this definition at the 2005 world summit to incorporate three pillars of sustainability: its social, envi- ronmental, and economic aspects.2 This report takes a similarly broad view of the term. Although much focus in sustainability has been on mitigating climate change, with efforts aimed at managing the carbon dioxide cycle and increasing sustainable energy sources, the committee recognizes that there are numerous additional sustainability challenges that could be assisted by advances in comput- ing and information technology and computing3 research. The committee’s focus is on addressing medium- and long-term challenges in a way that has significant and ideally, measurable, impact. 1United Nations General Assembly (March 20, 1987). Report of the World Commission on Environment and Development: Our Common Future; transmitted to the General Assembly as an Annex to document A/42/427—Development and International Co-operation: Environment; Our Common Future, Chapter 2: Towards Sustainable Development; Paragraph 1. United Nations General Assembly. Available at http://www.un-documents.net/ocf-02.htm. 2United Nations General Assembly, 2005 World Summit Outcome, Resolution A/60/1, adopted by the General Assembly on September 15, 2005. 3The term “computing” is used generally in this report and is meant to encompass informa- tion and communications technologies (ICTs). Thus “computing” and “ICTs” are used inter- changeably throughout the report. The greening of IT, through efforts such as reducing data-center energy consumption and electronic waste, should be and is an important goal of the computing community and IT industry.2 However, the focus of this report is on what could be termed “greening through IT,” the use of 2The 2010 OECD report “Greener and Smarter: ICTs, the Environment and Climate Change” (in OECD, OECD Information Technology Outlook 2010, OECD Publishing) notes that impacts from ICT life cycles (including not just use but also production and end of life) need to be considered in order to understand complete impacts. A recent McKinsey Quarterly article, “Clouds, Big Data, and Smart Assets: Ten Tech-Enabled Business Trends to Watch,” by Jacques Bughin, Michael Chui, and James Manyika, offered some cause for optimism regarding green IT: “Electricity produced to power the world’s data centers gener- ates greenhouse gases on the scale of countries such as Argentina or the Netherlands, and these emissions could increase fourfold by 2020. McKinsey research has shown, however, that the use of IT in areas such as smart power grids, efficient buildings, and better logistics planning could eliminate five times the carbon emissions that the IT industry produces.” McKinsey Quarterly 5(3):1-14.
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ROLES AND OPPORTUNITIES FOR INFORMATION TECHNOLOGY 15 computing and IT across disciplines to promote sustainability in areas and systems in which advances in information and communications technol- ogy (ICT) could have significant positive impact.3 The committee believes that some of the most profound fundamen- tals within the field itself are suggestive of the unique contributions that computer science (CS) and ICTs can make to sustainability. For instance, the very notion of automated “query-able” structured data is at the heart of much of computer science. The scope and scale of the sustainability challenge are coupled with vast amounts of relevant data, which makes deep insights into the challenges of collecting, structuring, and under- standing those data essential. Computational thinking is critical to solv- ing almost any large problem. The committee’s focus is on problems that are intellectually challenging, grounded in IT and CS, and important for sustainability—that is, a kind of “Pasteur’s octant.” See Figure 1.1. Despite the profound technical challenges presented by sustainabil- ity and the huge potential role for IT and CS, the committee recognizes that sustainability is not, at its root, a technical problem, nor will merely technical solutions be sufficient. Instead, solutions ultimately will require deep economic, political, and cultural adjustments, as well as major, long- term commitment in each sphere in order to put technical advancements and enablers in operation at scale. Nevertheless, technological advances and enablers can be developed and shaped to support such change, while continuing to support enduring human values in the process. Information technology can serve as a bridge between technical and social solutions 3The community has already begun addressing this challenge. Bill Tomlinson’s book Greening Through IT: Information Technology for Environmental Sustainability (Cambridge, Mass.: MIT Press, 2010) explores how IT can address sustainability challenges at scale. A 2009 article by Carla Gomes, “Computation Sustainability: Computational Methods for a Sustainable Environment, Economy, and Society” in The Bridge 39(4):5-13, provides examples of computational research being applied to domain fields (biodiversity and renewable en- ergy sources). Gomes’s work is an important component of computational sustainability; the present report explores the broader potential for research and innovation in CS and IT to have an impact on sustainability. Additionally, the National Science Foundation’s Directorate for Computer and Information Science and Engineering and the Computing Community Consortium (CCC) jointly sponsored a workshop on the Role of Information Sciences and Engineering in Sustainability. The full report of the workshop, Science, Engineering, and Education of Sustainability: The Role of Information Sciences and Engineering, which discusses research directions for IT as it relates to sustainability, is available at http://cra.org/ccc/ docs/RISES_Workshop_Final_Report-5-10-2011.pdf. This report is well aligned, in terms of research areas, with the CCC report. Additionally, the committee concurs with the CCC report Section 4, titled “The Power of Use-Inspired (Collaborative) Fundamental Research.” The present report expands on this theme in Chapter 3, especially in regard to the strength of computer science as a discipline and what it can contribute to sustainability objectives.
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16 COMPUTING RESEARCH FOR SUSTAINABILITY FIGURE 1.1 The committee’s focus is on problems at the intersection of sig- nificant intellectual merit, relevance to computer science (CS), and importance to sustainability. by enabling improved communication and transparency for fostering the necessary economic, political, and cultural adjustments.4 Furthermore, sustainability problems are typically heterogeneous in nature—there is almost never just one variable contributing to the chal- lenge or one avenue to a solution. Inputs, solutions, and technologies that can be brought to bear on any given problem vary themselves a great deal. Most sustainability challenges emerge in part due to interconnection—a result of multiple interlocking pieces of a system all having effects (some expected, some not) on other pieces of the system. Solutions to sustain- ability challenges typically involve finding near-optimal trade-offs among competing goals, typically under high degrees of uncertainty in both the systems and the goals. In addition to noting the crosscutting nature of many sustainability challenges, it is important to recognize the emergent qualities that typify the sorts of systems being discussed here. Some projections of what might 4E.Ostrom. A general framework for analyzing sustainability of social-ecological systems, Science 325:419-422 (2009).
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ROLES AND OPPORTUNITIES FOR INFORMATION TECHNOLOGY 17 be accomplished with the savvy application of known technologies or near-term research are straightforward, even in systems and domains as complex as these. However, in such complex systems and domains there are likely to be emergent behaviors and properties as well—both toward and away from desired outcomes. IT practitioners have proven remark- ably adept at innovating flexibly when previously unanticipated systems behaviors have demanded responses. The complexity and unpredictability of the results of unsustainable human activities require an innovative and flexible approach to solving or mitigating sustainability problems and their impacts, and IT researchers and practitioners are skilled at innovat- ing and developing flexible solutions in dynamic environments. The com- mittee believes that computing researchers and research approaches will be essential to grappling with current and future systems challenges in sustainability. This report has three chapters. Chapter 1 elaborates on domains of potential impact in order to illustrate the role and the available oppor- tunities of IT on the broader path toward sustainability. It address the question, In what ways and where can computing research have measur- able, significant impact? Chapter 2 describes methods and approaches in discussing the questions, How do fundamental research questions and approaches in computing intersect with sustainability challenges, and how can problem solving and research methodologies in computing research and IT innovation be brought to bear on sustainability? In par- ticular, the committee views one important goal of computer science in sustainability as informing, supporting, facilitating, and sometimes auto- mating decision making—decision making that leads to actions that will have significant impacts on achieving sustainability objectives. Aimed primarily at computer science researchers, Chapter 3 articulates why the interplay between addressing sustainability challenges and computer science research merits attention, and how that interplay offers deep and compelling opportunities for progress in multiple dimensions. Appen- dix A summarizes presentations and discussions at the Workshop on Innovation in Computing and Information Technology for Sustainability, organized by the committee. Biographies of the committee members are presented in Appendix B. OPPORTUNITIES TO ACHIEVE SIGNIFICANT SUSTAINABILITY OBJECTIVES Forward-looking IT innovations and sustained research can have significant positive impact for sustainability across many areas. For the purposes of this report, the areas are clustered as follows: built infra- structure and systems, ecosystems services and the environment, and
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18 COMPUTING RESEARCH FOR SUSTAINABILITY sociotechnical systems.5 Each of these is described briefly below. There are obvious multiple intersection points in these three distinct areas of opportunity. For example, eco-feedback devices (tools that provide instant information on environmental impact) within the home, a sociotechni- cal system,6 interact with the larger smart grid system, part of the built infrastructure; personal mobile devices, relying on built infrastructure and deployed in a sociotechnical context, provide data that feed into more robust modeling, a crosscutting methodology, and so on. In all of these domains, as potential solutions are deployed, careful attention will need to be paid to iterate over and evaluate solutions to ensure that progress made in one dimension of a given sustainability problem is not later off- set by an unanticipated outcome or side effect in another dimension. The next major section, “Illustrative Examples in Information Technology and Sustainability,” provides crosscutting examples of domains in which IT can support and strengthen sustainability efforts. Built Infrastructure and Systems Built infrastructure and systems include buildings (residential and commercial), transportation systems (personal, public, and commercial), and consumed goods (commodities, utilities, and foodstuffs). The Climate Group’s SMART 2020 report examined the use of information and com- munication technology in built infrastructure in several key areas, includ- ing smart buildings, smart logistics, and smart electric grids. According to that report, these three areas alone provide a potential reduction in greenhouse gas (GHG) emissions of 15 percent of global “business as usual” emissions in 2020.7 Buildings account for up to 40 percent of energy use in industrialized countries and 40 percent of GHG emissions; in the United States they con- sume more than 70 percent of the electricity produced.8 Smart buildings use IT systems to make better use of energy while maintaining indoor health and comfort. The embedded IT monitors and controls environ- 5Other clusterings are of course possible. The choice of these three was inspired in part by Global e-Sustainability Initiative, SMART 2020: Enabling the Low Carbon Economy in the Information Age (2008). Available at http://www.smart2020.org/publications/. 6“Sociotechnical systems” encompass society, organizations, and individuals, and their behavior as well as the technological infrastructure that they use. 7Global e-Sustainability Initiative, SMART 2020: Enabling the Low Carbon Economy in the Information Age (2008). Available at http://www.smart2020.org/publications/. 8World Business Council for Sustainable Development, Energy Efficiency in Buildings: Facts and Trends—Full Report (2008). Available at http://www.wbcsd.org/pages/edocument/ edocumentdetails.aspx?id=13559&nosearchcontextkey=true. See also http://www.eesi.org/ buildings.
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ROLES AND OPPORTUNITIES FOR INFORMATION TECHNOLOGY 19 mental and electrical systems in the building by means of computerized, intelligent networks of sensors and electronic devices.9 According to the SMART 2020 report, smart buildings could reduce carbon dioxide emis- sions by an estimated 15 percent in 2020.10 The sustainability of structures generally goes well beyond energy, and involves the reuse and recycling of materials, sustainable construction processes, improved indoor air quality, effective water use, and so on.11 Smart logistics use IT for more effective supply chains (those deal- ing with journey and load planning and with personal transportation), both in daily operational use and in long-term planning. Examples of IT contributions include better geographic information systems and design software to promote more effective transport networks, collaborative multi-nstitutional planning tools to lower the logistical demands asso- i ciated with desired lifestyles, and better inventory-management tools. Computing innovation can also lead to better management of consumed resources. Smart electric grids use IT tools throughout the power networks to enable optimization. (Potential smart grid applications are described in greater detail in the section “Toward a Smarter Electric Grid,” below.) In addition to reductions that can be achieved in energy consumption, smarter water- and sewage-management systems in the built infrastruc- ture can decrease water consumption and waste. Furthermore, large-scale agriculture necessitates water and supply-chain management; advanced IT can enhance precision agriculture, including the incorporation of tech- nologies to predict crop yields more accurately.12 (See the section “Sus- tainable Food Systems,” below, for more on food systems broadly.) Transportation and city and regional planning also provide impor- tant opportunities for more sustainable development; computation and IT will be needed to enable significantly more complex planning for the optimizing of investment in new infrastructure. And, changes to manu- facturing itself (which incorporates logistics, sensing, transportation, and manipulation) can help with sustainability goals by reducing environ- mental impacts, conserving energy and resources, and improving safety 9National Research Council, Achieving High-Performance Federal Facilities: Strategies and Ap- proaches for Transformational Change, Washington, D.C.: The National Academies Press (2011). 10Global e-Sustainability Initiative, SMART 2020: Enabling the Low Carbon Economy in the Information Age (2008). Available at http://www.smart2020.org/publications/. 11For an introduction to some of the issues related to achieving high-performance “green” buildings, see National Research Council, Achieving High-Performance Federal Facilities: Strate- gies and Approaches for Transformational Change, Washington, D.C.: The National Academies Press (2011). 12National Research Council, Toward Sustainable Agricultural Systems in the 21st Century, Washington, D.C.: The National Academies Press (2010).
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20 COMPUTING RESEARCH FOR SUSTAINABILITY for the individuals and communities affected by it. IT has a central role in these efforts. Ecosystems and the Environment Assessing, understanding, and positively affecting (or not affecting) the environment and particular ecosystems are crosscutting challenges for many sustainability efforts.13 The scale and scope of such efforts range from local and regional activities examining species habitats, to watershed management, to efforts to increase understanding of the impacts of global climate change. The range of challenges itself poses a problem: how best to assess the relative importance of various sustainability activities with an eye toward significant impact. Nonetheless, in virtually every activity related to meeting sustainability challenges, a critical role is required of data, information, and computation. Climate science, for example, has been able to take huge leaps forward due to advances in computing research.14 Computational modeling and simulation of Earth, the atmosphere, oceans, and biota and of their many interactions have long been at the heart of understanding how changes in carbon cycles and hydrological cycles give rise to global climate change and the estimating of future impacts. Sensing, data management, and model formation connect these computational analyses to a vast body of empirical observation and to one another. Such tools allow for the contin- ual improvement of fidelity and can help improve the basic understand- ing of flows of carbon, nitrogen, and other emissions of interest. These tools also improve the understanding of water and resource usage, of species distributions and biodiversity, and of ways in which human activ- ity perturbs these. Analyses of environmental and ecosystem responses to disturbances (those from GHGs, fire, invasive species, disease) are important to meeting a range of sustainability objectives. Modeling also plays a crucial role in guiding decision makers, by connecting ecological science and research to ongoing ecosystem policy and management. For 13A recent National Research Council report “capture[s] some of the current excitement and recent progress in scientific understanding of ecosystems, from the microbial to the global level, while also highlighting how improved understanding can be applied to im- portant policy issues that have broad biodiversity and ecosystem effect.” National Research Council, Twenty-First Century Ecosystems: Managing the Living World Two Centuries after Dar- win, Washington, D.C.: The National Academies Press (2011), p. ix. 14D.A. Randall, R.A. Wood, S. Bony, R. Colman, R. Fichefet, J. Fyfe, V. Kattsov, A. Pittman, J. Shukla, J. Srinivasan, R.J. Stouffer, A. Sumi, and K.E. Taylor. The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, S. Solomon D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.), Cambridge, United Kingdom: Cambridge University Press (2007). Available at http://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch1s1-5-3.html.
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ROLES AND OPPORTUNITIES FOR INFORMATION TECHNOLOGY 21 example, models that jointly capture the interrelationships of multiple variables and their joint uncertainty can support improved understanding and more robust decision making. Sociotechnical Systems Large and long-lived impacts on sustainability will require enabling, encouraging, and sustaining desired human behavior—that of indi iduals, v organizations, municipalities, and nation-states—over the long term. Socio- technical systems designed to aid in behavioral assistance and reinforce- ment and to provide information about progress are a critical element for global sustainability efforts. Such systems and associated tools are needed at every scale and can be applied to a range of problems, from enabling effective response in times of acute crisis management, to urban planning, to promoting the understanding of behavioral impacts (sometimes referred to as footprint analysis) on carbon, water, and biodiversity. Institutional behaviors will need to shift in order to realize continu- ous, long-term environmental changes. Marketing and public education initiatives are important and can contribute to individual and institutional knowledge on best practices. However, real-time information and tools can better equip individuals and organization to make daily, ongoing, and significant changes in response to a constantly evolving set of cir- cumstances. Information dashboards accessible to key decision makers are an example of how IT can be used to collect, analyze, curate, and informatively present critical information quickly to those who need it most. For example, if the financial incentives for energy utilities shift from an emphasis on delivering more power more cheaply to an empha- sis on improving the GHG emissions efficiency of a given level of ser- vice, new information will be needed. Gathering such information will require greater visibility and understanding of the dynamics of customer demand, grid capacity, and supply availability. In addition, each of the stakeholders will need more effective means of communicating needs and trade-offs. Similarly, in order for urban planning to promote, say, the reduction of liquid fuel consumption for personal transportation, the processes of street design, zoning, planting, business development, water and waste management, and public transportation need to be coordinated across multiple governing bodies and constituencies. Personal devices, most notably sensor-rich smartphones, not only provide information and services to their users, but also can provide scientists and researchers with information that may have been missed by traditional operational networks. Furthermore, citizen scientists are increasingly engaged in scientific problem solving, for example by docu-
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22 COMPUTING RESEARCH FOR SUSTAINABILITY menting species locations, air quality, and other indicators.15 In addition, environmental challenges—those caused by damage to the environment from rising ocean water levels and temperatures or those created by the search for and extraction of materials—can be monitored, assessed, and tracked. Information about environmental challenges can also be dissemi- nated using smarter IT. Further advances in the ability to analyze data collected by a wide array of sources will facilitate a better understanding of how environmental crises begin and how to avoid them in the future. ILLUSTRATIVE EXAMPLES IN INFORMATION TECHNOLOGY AND SUSTAINABILITY This section contains three illustrative examples of sustainability- related domains in which IT can have significant impact and in which there is both some current activity as well as prospects for significant progress and impact in the future. This set of examples is not meant to be comprehensive and does not reflect a prioritization. Rather, these examples were chosen to illustrate how IT—both currently understood technologies as well as new ones—could be brought to bear on sustain- ability challenges and also to show the range and variability of what is meant by sustainability. Each example area listed below cuts across the three broad areas outlined above. • The smart grid. In this first example, the grid is clearly part of built infrastructure, but it also has the potential to affect regional ecosystems dramatically as new sources of renewable energy are brought online (for example, solar facilities deployed in deserts will affect the desert ecosys- tem). Managing the smart grid, from both the supply and the consump- tion side (which may not be as easily separable in any event) will require sociotechnical systems, such as data management, for humans and human organizations. • Food systems. This second example also encompasses built envi- ronments (including the transportation system), the environment, and ecosystems (in various aspects from macro effects on watersheds to strate- gies for precision agriculture), and, like the smart grid, it requires sophis- ticated tools and data management to be most effective. • The development of sustainable and resilient infrastructures. This third example poses crosscutting sustainability challenges, especially when considering a broad view of sustainability that encompasses economic 15W. Willett, P. Aoki, N. Kumar, S. Subramanian, and A. Woodruff, Common sense com- munity: Scaffolding mobile sensing and analysis for novice users, pp. 301-318 in Proceedings of the 8th International Conference on Pervasive Computing (Pervasive ‘10) (May 2010).
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ROLES AND OPPORTUNITIES FOR INFORMATION TECHNOLOGY 23 and social issues. These challenges include planning and modeling infra- structure and anticipating and responding to increasingly frequent natu- ral and human-made disasters. Toward a Smarter Electric Grid Being able to meet the planet’s energy needs in a sustainable fash- ion is fundamentally interwoven with foundational transformations in the design, deployment, and operation of the world’s electric grids. The problem is large and complicated, and the committee’s framing in this discussion is for descriptive purposes, and is not meant to be complete, to be prescriptive, or to conflict deliberately with other approaches to char- acterizing the problem.16 With regard to the electric grid, most analyses of potential paths to stabilizing GHG concentrations involve three interre- lated advances: deep efficiency gains, electrifying the demand, and decar- bonizing the supply.17 As a prime example, the United States currently consumes roughly 100 quadrillion British thermal units (Btu) (about 100 exajoules) of energy per year, with flows from supply to demand as illus- trated graphically in Figure 1.2. Roughly half of the energy supply goes into the production of electricity. Of that, the largest share is provided by coal, which has the worst GHG intensity of the supplies and is the cheapest and fastest way to increase supply in developing economies. By contrast, essentially all of the renewable and zero-emission supplies also go into electricity production, but these account for a tiny fraction of the energy mix. Their share must increase substantially in order to 16For instance, a survey paper developed by IBM Research on the computational chal- lenges of the evolving smart grid is oriented around the challenges of data, grid simulation, and economic dispatch: J. Xiong, E. Acar, B. Agrawal, A. Conn, G. Ditlow, P. Feldmann, U. Finkler, B. Gaucher, A. Gupta, F-L. Heng, J. Kalagnanam, A. Koc, D. Kung, D. Phan, A. Sing- hee, and B. Smith, Framework for Large-Scale Modeling and Simulation of Electricity Systems for Planning, Monitoring, and Secure Operations of Next Generation Electricity Grids, Special Report in Response to Request for Information: Computation Needs for the Next-Generation Elec- tric Grid, DOE/LBNL Prime Contract No. DE-AC02-05CH11231, Subcontract No. 6940385 (2011); M. Ilic, Dynamic monitoring and decision systems for enabling sustainable energy services, Proceedings of the IEEE 99:58-79 (2011), notes the fundamental role of a man-made power transmission grid and its IT in enabling sustainable socioecological energy systems. J. Kassakian, R. Schmalensee, K. Afridi, A. Farid, J. Grochow, W. Hogan, H. Jacoby, J. Kirtley, H. Michaels, I. Pérez-Arriaga, D. Perreault, N. Rose, and G. Wilson, The Future of the Elec- tric Grid: An Interdisciplinary MIT Study, available at http://web.mit.edu/mitei/research/ studies/the-electric-grid-2011.shtml#report, aims to provide an objective description of the grid today and makes recommendations for policy, research, and data for guiding the evo- lution of the grid. 17California Council on Science and Technology, California’s Energy Future: A View to 2050, Sacramento (2011). Available at http://www.ccst.us/publications/2011/2011energy.pdf.
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40 COMPUTING RESEARCH FOR SUSTAINABILITY tem. At the farm itself, individual farms can combine crop and livestock production so as to reduce the need for synthetic fertilizers. Traditional agriculture has focused on controlling the farm ecosystem by simplifying it (e.g., through monoculture) and applying external inputs (e.g., water, fertilizer, pesticides, and herbicides). The systems view seeks to reduce or eliminate those external inputs (and their associated carbon and pollu- tion emissions) by, for instance, designing and managing a more complex ecosystem involving a larger variety of species.36 A systems view can provide guidance on how to develop ways to make the system as a whole more sustainable. For instance, rather than viewing a farm (or farms) in isolation and having inputs and outputs, one could view the entire cycle of food production and consumption as providing natural resources for growing food that is consumed by people. This cycle includes land, water, and other farm inputs, crops, transportation, processing, retailing, con- sumption, and recycling or waste. At each stage, there are effects on the environment and society; thus it is important to consider the connections between farms, the ecosystem, and communities (local, regional, and global). An important role for IT is to enable farmers to manage these more complex systems through mechanisms such as sensing, predictive modeling, and precision machinery. Methodology for Measuring Costs, Benefits, and Impacts There is a substantial need for the development of methods and tools to measure the total costs, benefits, and impacts of different agricultural systems. For example, comparative studies of GHG emissions from different field-management practices for animal wastes would allow for better quantification of the environmental impacts of agricultural systems and, just as with the smart grid scenario, allow for prices to reflect costs and value better. In general, evaluating different farming systems will require assessing how each system balances productivity and efficiency with environmental and societal impacts and will require analyzing the behavior of complex high-dimensional and highly interactive systems. In addition to the technical challenges of developing such measures, there are also significant challenges in helping them to be seen as accurate and legitimate by both producers and consumers. Novel visualization techniques, explanation facilities, interactive simulations, and other tech- niques may help here. 36The control of pests provides an example of moving from a traditional view to a sys- tems view. The traditional way of controlling pests is to apply pesticides, which requires little knowledge of the pests. A more sustainable approach may be to use benign control measures, which require an understanding of the pest’s life cycle and its interaction with other parts of the farm ecosystem.
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ROLES AND OPPORTUNITIES FOR INFORMATION TECHNOLOGY 41 Precision Agriculture The use of information and computing technol- ogy in agriculture has greatly increased in the past 50 years. It has allowed farmers to assess variation within fields and to generally maintain or increase yields while reducing inputs (particularly water, nutrient, and pesticide application). Technologies used here include the Global Positioning System, real-time kinematics, and geographic infor- mation systems, especially satellites. IT already plays a substantial role in this area and will continue to play a critical role in the future. There is also a connection with methodologies for measuring costs and ben- efits: if the cost of water for agricultural use reflects its true cost, there may be much more incentive to use precision agriculture to reduce the consumption of water. Information for Informed Consumption Increasing the information available to individuals regarding the nature of the food that they buy and how it was produced can assist them in making sustainable choices about food. Already there is an emerging market for foods that have been produced in a sustainable manner.37 An important method by which such information is currently conveyed is through the development of stan- dards, certifications, or other eco-label programs. Each of these programs outlines a set of criteria for food producers and distributors in an effort to address various environmental, sustainability, or health goals.38 Perhaps the most well-established food standard in the United States is the organic agriculture certification, which focuses primarily on health and environ- mental goals and does not address the broader goals of sustainable agri- culture. Food-labeling requirements in the United States provide some information, for example, on the country of origin of meats and fruits, but general information about sustainability and food transport (which has implications for fossil fuel usage) is not available. Current standards and certifications are typically communicated using logos or other print labeling on food packaging. However, potential exists for providing much richer information regarding sustainability and information to help con- sumers sort through the proliferation of eco-labels in the market. The wider adoption of smartphones may allow for easier dissemination of this information, as users could search for sustainability information at the point of purchase. One example of empowering individuals with information is the Monterey Bay Aquarium’s Seafood Watch guide39 that 37National Research Council, Toward Sustainable Agricultural Systems in the 21st Century, Washington, D.C: The National Academies Press (2010). Chapter 6. 38Ecolabel Index. Available at http://www.ecolabelindex.com/. 39The Monterey Bay Aquarium’s Seafood Watch guide is available at http:// www.montereybayaquarium.org/cr/seafoodwatch.aspx. The guide provides a list
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42 COMPUTING RESEARCH FOR SUSTAINABILITY provides detailed and up-to-date information about what types of seafood are caught or farmed in a sustainable manner. In addition to a web site, the guide also is available as a smartphone application so that consumers can have portable access to its vast database. Social Networks for Local Food Sourcing IT could be used to increase networking among individuals and organizations, encouraging locally and regionally sourced food consumption. Community-supported agri- culture (CSA) already benefits from the organizing power of online net- works to distribute relevant information, create markets for local farm producers, make it easier to place orders, and help connect consumers with local food. Generally, IT could be used to help make a more effective market for local foods.40 Beyond efficiency, there is little argument that humans have emotional connections to food; techniques to strengthen the farmer/consumer connection could also be valuable. IT could also be useful for gathering information on regional surpluses or deficits, allow- ing fresh foods to be allocated to areas where they are most needed and diminishing reliance on processed foods with longer shelf lives. The Role of Information Technology and Computer Science in Achieving a Sustainable Food System As with the smart electric grid, information and data management are essential to making progress toward a smarter, more sustainable, global food system. Computer science research and methodological approaches will be needed at all levels to address the broad systems challenges— encompassing the environment and ecosystems, social and economic factors, and personal and organizational behaviors—affecting food pro- duction, distribution, and consumption. Three critical areas are described briefly below: information integration; education and reform; and systems modeling, prediction, and optimization. Information Integration Information integration can help individuals and organizations on both the demand and the supply side of the food system of sustainable choices and the least sustainable choice of fish to consume. Legal Sea Foods has questioned the value of the guide. See http://www.nrn.com/article/ legal-sea-foods-defies-aquarium%E2%80%99s-watch-list. 40As one example of an effort in this area, see http://www.urbaninformatics.net/projects/ food/ regarding a project exploring “ubiquitous technology for sustainable food culture in the city.” Another example is LocallyGrown.net, which seeks to provide an online in- frastructure and organizational capacity for local farmers’ markets and CSAs, particularly small-scale growers with few or no employees.
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ROLES AND OPPORTUNITIES FOR INFORMATION TECHNOLOGY 43 make sustainable choices regarding the production and consumption of food. Providing consumers with information about the sustainability of food production, in addition to other aspects of sustainable food sys- tems such as health and environmental impacts, will require the sharing and integration of information across producer and consumer platforms. Developing and optimizing the infrastructure and architecture for such information integration will be an important contribution of IT. More gen- erally, areas in which IT could be of substantial help include the creation of databases of information and the maintenance of the currency of that information as well as connecting farmers and consumers through social networks and the Internet. The development of analytical software for optimizing sustainable food purchasing choices for both consumers and large-scale purchasers (such as supermarkets) is another rich area of IT contributions. Education and Reform Tools are needed to help both consumers and pol- icy makers understand the trade-offs posed by the global food system and to navigate those trade-offs toward increased sustainability. The role of IT here is not just in providing information on availability and techniques, but also in allowing access to communities of individuals with simi- lar interests. There are numerous opportunities to effect change through demand-side modification of food consumption.41 Efforts to encourage the preparation and even the growing of food at home could have a sig- nificant impact on overall distribution needs. Increasing the availability of fresh, healthful foods in certain communities (e.g. low-income communi- ties) would also help. Additional challenges exist in predicting the infor- mation that purchasers and individuals will need, displaying information that will encourage more sustainable consumption habits, educating con- sumers about sustainable choices without overwhelming them, and so on. Systems Modeling, Prediction, and Optimization Improving the effi- ciency of the food system in general will require modeling a complex and interactive system and methods for predicting food shortages and sur- pluses in order to help ensure that food is available in different regions at 41Andrea Grimes, Martin Bednar, Jay David Bolter, and Rebecca E. Grinter, EatWell: Sharing nutrition-related memories in a low-income community, Proceedings of the 2008 ACM Conference on Computer Supported Cooperative Work (2008); Andrea Grimes and Rich- ard Harper, Celebratory technology: New directions for food research, Proceedings of the Twenty-Sixth Annual SIGCHI Conference on Human Factors in Computing Systems (2008); and T. Aleahmad, A. Balakrishnan, J. Wong, S. Fussel, and S. Kiesler, Fishing for sustainability: The effects of indirect and direct persuasion, Extended Abstracts from Conference on Human Factors in Computing Systems (2008).
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44 COMPUTING RESEARCH FOR SUSTAINABILITY reasonable costs. In addition, the transportation of food to various markets could be optimized according to sustainability cost functions if a compre- hensive model of the food system were available. Given a model of the food system, one could also assess the costs and benefits of various agricultural and farming strategies, the design of food sheds, and distribution systems. Sustainable and Resilient Infrastructures The resilience of the nation’s societal and physical infrastructures poses deep and crosscutting sustainability challenges, especially when one takes a broad view of sustainability that encompasses economic and social issues. For example, although transportation is a major source of GHG emissions and urban sprawl consumes open space and farmland, competing incentives in the realm of societal sustainability include the need for workers to commute to jobs, for people to have access to whole foods, and for available space that allow businesses to change and adapt over time. Contributing to the challenges of resilience of societal and physical infrastructures is the increasing risk of natural and human-made disasters. Sustainability concerns related to climate change, resource con- sumption, and land use are closely linked to natural and human-made disasters.42 There will inevitably be more disasters, and enhancing soci- ety’s resilience and ability to cope with them will contribute to sustain- ability. Even apart from climate and resource consumption, the sheer magnitude of the world’s population means that crises, when they hap- pen, will be at larger scale. This section examines the sustainability chal- lenges around planning and modeling infrastructure and anticipating and responding to increasing disasters and the ways in which information technology can assist with developing sustainable and resilient infrastruc- tures. The section focuses on cities as centers of large human populations, but many of the issues discussed apply generally. Challenges to Developing More Sustainable and Resilient Infrastructures Cities are highly complex, evolving systems, involving the interaction of numerous people and processes, as well as natural and built infrastruc- ture, legal and regulatory frameworks, and much else. The diversity of use within the systems adds another level of complexity. Each building’s use and design are unique within a particular city; each city’s infrastructure has distinctive characteristics. The heterogeneity of structures within any 42NationalResearch Council, Adapting to the Impacts of Climate Change, Washington, D.C.: The National Academies Press (2010).
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ROLES AND OPPORTUNITIES FOR INFORMATION TECHNOLOGY 45 given city poses challenges—and because cities are often quite different from one another, the extrapolation of lessons learned is also challenging. Just as cities are increasingly complicated, the challenges of coping with disasters are compounded by their heterogeneity. There are acute natural disasters (such as hurricanes, earthquakes, and floods), acute engineering and other human-made disasters (such as the 2010 Deepwa- ter Horizon Gulf oil spill), as well as “slow” or chronic disasters (such as droughts, refugee crises, and rising sea levels). In addition, whether acute or chronic, there are the ongoing processes of cleanup and recovery from disasters. Many situations are best described as combinations of natural and human-made disasters with both acute and chronic time frames. 43 The problems associated with the resilience of societal and physical infrastructures have complicated time lines. For instance, urban, sub- urban, and rural areas are developed over long periods of time and are almost constantly being shifted into new uses. These long time lines create legacy systems that may not be compatible with newer systems or that could be costly to update. Planning becomes increasingly complicated as new infrastructure, often costly and time-consuming to implement, must anticipate the future needs of a particular area. Similarly, the time needed and the ability to prepare an area for poten- tial emergencies vary and depend not just on characteristics of the area, but also on the anticipated types of disasters and crises. Some disasters, like hurricanes, come with at least some advance warning, and others, like earthquakes, strike at unpredictable times. Some events cause intense damage only in limited areas, while others affect enormous geographical regions. An additional challenge is that the frequency of disastrous events is such that recovery after one event (itself a major sustainability challenge) may well not be complete before the next major disaster strikes—either in the same region, as happened with Hurricane Katrina and the Deepwater Horizon oil spill, or different regions competing for resources and attention, as in the earthquake in Haiti in 2010 that was followed by severe flooding in Pakistan. The Role of Information Technology in Developing Sustainable and Resilient Infrastructures Information and communications technologies offer a range of meth- odologies, approaches, applications, and tools that will be integral to the 43Author Bruce Sterling coined the term “Wexelblat Disaster” to refer to disasters caused by the interaction of natural disasters and failures of human-engineered technology. The 2011 earthquake and tsunami that destroyed a nuclear power plant in Japan leading to core meltdowns is an example.
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46 COMPUTING RESEARCH FOR SUSTAINABILITY development of sustainable and resilient infrastructure and to coping with disasters when they occur. Several such technologies are highlighted below. Modeling and Simulation Urban regions can be modeled with varying degrees of spatial detail and behavioral realism. For a highly disaggre- gate, behaviorally realistic model,44 the process of modeling a new region is time-consuming, often requiring person-years of effort. A major factor is difficulties in collecting and readying the needed data. Further, prob- lems of missing data—common in U.S. metropolitan regions and even more so in developing countries—make the task much more challenging. Modeling the development of cities over periods of 20 or more years, under different alternatives, can provide important information to inform public deliberation and debate about alternate plans and possible futures. Transportation modeling, and more comprehensively integrated model- ing of urban land use, transportation, and environmental impacts, have a substantial history and are in operational use in many regions. Neverthe- less, there are major limitations in current knowledge, and new research is needed to address the coming challenges adequately. In addition to the scientific challenges of the modeling itself, it is important to consider how the modeling work fits into the larger political and organizational process of making major decisions (often a contentious process), and to shape the technology to respond to these contextual challenges. Turning from simulations of long-term development to immediate support for coping with disasters: during a disaster copious amounts of information can be collected; however, more does not always mean bet- ter or more helpful information.45 Sorting out how to manage and use IT capabilities at hand most effectively and, perhaps even more importantly, the vast amounts of data that can be made available by those capabilities, is a non-trivial exercise.46,47 44For example, UrbanSim (http://www.urbansim.org), currently the most widely em- ployed land use model in the United States. 45Bruce Lindsay, Social Media and Disasters: Current Uses, Future Options, and Policy Consid- erations, Congressional Research Service (2010). Available at http://www.fas.org/sgp/crs/ homesec/R41987.pdf. 46See “Disaster Relief 2.0: The Future of Information Sharing in Humanitarian Emergen- cies,” available at http://www.unocha.org/top-stories/all-stories/disaster-relief-20-future- information-sharing-humanitarian-emergencies, for an early assessment of crowdsourcing information and data flows in a humanitarian crisis. In this case the Haiti earthquake of 2010 was a primary example. 47Dan Reed, vice president of Microsoft Research, discussed some of the computational chal- lenges posed by the 2010 Gulf oil spill, noting that the disaster stemmed from a “complex multidisciplinary system with emergent behaviors across a wide range of temporal and spatial
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ROLES AND OPPORTUNITIES FOR INFORMATION TECHNOLOGY 47 In addition to modeling the effects of current disasters, IT offers opportunities for in-depth simulation of potential disasters and for indi- viduals to exercise and manage a given organization’s response to a crisis to hone and refine their skills and approach. Communication IT provides the communications capabilities before, during, and after a crisis for coordinating activities and for delivering alerts and warnings to affected populations. IT provides critical capabili- ties for the other phases of crisis response as well, such as modeling and simulation to predict likely consequences or to contribute to the under- standing of the effectiveness of particular mitigation measures. As dis- cussed in a 2007 NRC report, IT provides capabilities that can help people make better sense of information, grasp the dynamic realities of a disaster more clearly, and help them formulate better decisions more quickly. IT provides the tools to capture knowledge and share it with disaster- management professionals and the public. IT can help keep better track of the myriad details involved in all phases of disaster management. 48 The Role of Information Technology and Computer Science Research in Developing Sustainable Infrastructure and Fostering Resilience Advances will be needed in IT and computer science research and methodological approaches to enable better simulations and better under- standing of the uncertainties associated with achieving more sustainable development that is also more resilient in the face of disaster. Advances are also needed in the areas of encouraging citizen participation, devel- oping indicators of resilience and future outcomes, and improving IT infrastructures themselves. Performance Running a simulation for a high-end, behaviorally realistic model for a major metropolitan region is a slow process, currently often requiring days, even on today’s fast computers. Similarly, the process of constructing a new scenario (i.e., a package of infrastructure improve- ments, zoning changes, tax incentives, and perhaps such things as tolling scales.” He described some of the challenges in modeling such a system: “we lack the software engineering and programming methodologies to assemble, test and verify an integrated solution . . . the computational demands of an integrated, fully multidisciplinary, parametric simulation study of the oil spill and its effects would make accurate climate modeling seem like child’s play on an abacus by comparison.” Dan Reed, Lessons from the Gulf of Mexico (2010), available at http://www.hpcdan.org/reeds_ruminations/2010/08/lessons-from-the-gulf-of-mexico.html. 48National Research Council, Improving Disaster Management: The Role of IT in Mitigation, Preparedness, Response, and Recovery, Washington, D.C.: The National Academies Press (2007).
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48 COMPUTING RESEARCH FOR SUSTAINABILITY or congestion pricing) can require months of work by experts in trans- portation, land use modeling, and other disciplines. Creating far more efficient algorithms for modeling systems that are increasingly complex presents an important challenge. One natural approach is parallelizing the algorithms. In a number of cases this is quite feasible: for example, when modeling residential location choice (where will people decide to live, given characteristics both of the household and the possible dwellings), one can use massive parallelism, with each household making its decisions independently. One must then undo some assignments if two households attempt to move into the same place simultaneously (perhaps mirroring what happens in real life with several people all trying to rent or buy the same dwelling). However, new or improved algorithms are likely a richer source of performance gain, which will be important because many of the applications envisioned require huge performance increases (for example, using a simulation in real time in a meeting, or running a simulation many, many times to compute information about uncertainty). The precomputing of key scenarios and interpolating among the results (when the changes are smooth rather than abrupt), rather than computing the results from each scenario from scratch, should also be investigated. In terms of algorithms, one class of new algorithms that should be investigated is multiscale mod- els, in which the simulation is first run at a relatively coarse grain (e.g., a zonal level), and the results from this are fed to further simulation runs within each zone, and so forth. (See Chapter 2 for more on modeling.) In this case the reason for using a multiscale model is performance. Hetero- geneous models are also relevant for urban simulation—for example, cou- pling UrbanSim (a regional-scale model) with statewide freight mobility models. This could be further optimized by simulating only within zones that have changed significantly from the prior simulation period or that are of particular policy interest, and otherwise remaining at the coarser level. Managing Uncertainties Urban modeling is rich with uncertainties on many levels, including future population, global economic conditions, the price of energy, the impact of climate change, and many others. There have been some successes in propagating uncertainty through the model- ing process and capturing it in the indicators that the system produced, 49 but much more needs to be done in terms of both statistical techniques and effective presentation of the results. 49Hana Ševcíková, A. Raftery, and P. Waddell, Assessing uncertainty in urban simulations using Bayesian melding, Transportation Research Part B: Methodology 4:652-659 (2007).
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ROLES AND OPPORTUNITIES FOR INFORMATION TECHNOLOGY 49 Citizen Participation To date, citizen science (or citizen information gathering) is being used for such activities as open mapping projects, but much of this type of activity has not been integrated with modeling work. Harnessing the energies and interests of citizen scientists has strong potential, both as a source of additional data and as an avenue for public participation and the legitimation of the modeling activity. Leveraging existing technology (such as mobile applications, cloud services, mapping and location services, microcommunications platforms, social media, and so on) offers numerous opportunities to improve approaches to emer- gency and disaster management.50 Some organizations are experimenting with gathering situational awareness from citizens, and in particular citizen use of social media. 51 At the same time, there are significant challenges with regard to data qual- ity, coverage, and institutional acceptance, among other things. Technical approaches here may include reputation systems that let staff at institu- tions build up confidence in particular observers, and ways to correlate data from multiple observers and to detect outliers. During disasters, more attention should be paid to the information and resources held by the public because members of the public col- lectively have a richer view of a disaster situation, may possess increas- ingly sophisticated technology to capture and communicate information, and are an important source of volunteers, supplies, and equipment. Again, the information provided by the public will not always be correct; further, making full use of it may require considerable changes to exist- ing practices. It is likely that the development of new, automated, and mixed-initiative techniques to manage and process the potential flood of information will be needed. Another important factor is how to engage the entire population, given the existence of groups with cultural and language differences and other special needs. Indicators of Future Outcomes Simulations already produce indicators of such outcomes as GHG emissions, consumption of open space, and comparative measures of compact versus low-density development, all for multiple years and under different scenarios. However, as discussed above, it is also necessary to anticipate disruptions and potentially even disasters, due to climate change, mass movement of refugees, and other 50National Research Council, Public Response to Alerts and Warnings on Mobile Devices: Sum- mary of a Workshop on Current Knowledge and Research Gaps, Washington, D.C.: The National Academies Press (2011). 51Sarah Vieweg, Amanda Hughes, Kate Starbird, and Leysia Palen, Microblogging during two natural hazards events: What Twitter may contribute to situational awareness, Proceed- ings of the 2010 ACM Conference on Computer Human Interaction, pp. 1079-1088.
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50 COMPUTING RESEARCH FOR SUSTAINABILITY factors. A research challenge is to develop indicators of community resil- ience in the face of such events.52 These might include the percentage of electrical energy generated locally (or that could be generated locally if need be), the redundancy of the transportation system and the food sup- ply chain and their ability to cope with a sharp increase in fuel prices or even rationing, the ability to cope with sea-level rise (if relevant), the ability to walk to the most significant destinations if need be, the avail- ability of food produced nearby, and so forth. These indicators need to be accepted by decision makers and the community to be useful in the political process. More abstract and much more difficult, if not impossible, to incorporate into a predictive model (but nevertheless important) are the civic capital and connectedness of the community. IT Infrastructure Improvements Large disasters upset physical infra- structure, such as the electric grid, transportation, and health care—as well as IT systems. IT infrastructures themselves need to be more resilient; IT can also improve the survivability and can speed the recovery of other infrastructure by providing better information about the status of systems and advance warning of impending failures. Finally, IT can facilitate the continuity of disrupted societal functions by providing new tools for reconnecting families, friends, organizations, and communities. CONCLUSION IT and computer science could have a major impact in a wide diver- sity of sustainability challenges. The examples above illustrate some of the efforts that are needed. Individual problems are highly multidimensional, requiring innovation in different areas of computing as well as deep domain knowledge. FINDING: Although sustainability covers a broad range of domains, most sustainability issues share challenges of architecture, scale, heterogeneity, interconnection, optimization, and human interac- tion with systems, each of which is also a problem central to CS research. The next chapter explores more specifically the potential for comput- ing and IT research and innovation to help address these challenges. 52An example of this is the Climate Change Habitability Index. For a description, see Yue Pan, Chit Meng Cheong, and Eli Blevis, The Climate Change Habitability Index, Interactions 17(6):29-33 (2010).