In the 20th century, government agencies, such as the US Environmental Protection Agency (EPA), tracked the emergence of important national and international trends by seeking input from reliable outside and internal experts and businesses that had good reasons to stay ahead of trends and by reading mass-media reports and studies produced by not-for-profit organizations. Federal agencies collected their own data, but often something environmentally important occurred before federal agencies found out by scanning their own data.
In the 21st century, the ability to gather, maintain, analyze, and circulate data has improved markedly. Smaller and less expensive environmental monitors have been developed and deployed, so people in EPA and state environmental agencies (such as California’s Emerging Environmental Challenges Program) 1 can quickly scan collected data for notable emerging trends and cross-reference with colleagues anywhere in the world who have similar capabilities.
The ability to identify and understand trends in public preferences and perceptions has also improved markedly. The traditional survey, which uses protocols recommended by the American Association for Public Opinion Research, is one of the best ways to learn about public preferences, perceptions, and values associated with the environment because a representative sample is gathered and confidence limits can be estimated for the results. But it is now feasible to scan data for marked shifts in public perceptions. Joined with standard opinion-poll data and selected longitudinal surveys, social- media data analytics can allow EPA to stay up to date with what the public is thinking; some analytic tools may even assist in predicting public attitudes about specific issues as they emerge. As the 21st century progresses, the United States will probably undergo substantial economic, environmental, and social changes; not only are the expected changes complex, but their occurrence is expected to be rapid. New issues will include substantial uncertainty. The anticipation and prevention of adverse effects, as opposed to detection of and response to them, is growing in its appeal. Earlier recommendations to EPA seem prescient: “that EPA should include among its repertoire of analytical and technical skills, a capability to routinely and systematically study the range of possible environmental futures ahead, and advise the nation on possible actions in response” (EPASAB, 1995). The ability to anticipate, assess, and manage challenges is at the heart of sustainability practices and therefore plays a major role in addressing new issues and evaluating strategies that can minimize potentially deleterious effects.
Regardless of what technologies, tools, methods, or approaches one chooses for assessing and managing emerging issues, data will fuel them (EPA 2013a). Access to high-quality data will be a pivotal determinant of success in applying sustainability approaches to management of new-issues, and it is clear that EPA and other federal agencies have deemed this a signature issue (White House 2014).
This chapter discusses some key considerations regarding the need for EPA to develop science-grounded information more rapidly. It also considers a variety of specific challenges that EPA is likely to face in deciding how to apply sustainability tools and approaches when addressing a new issue.
1See OEHHA 2007.
Informing Regulatory Decision-Making
The regulatory implications of new issues can be informed and guided by the early warning of the existence of the issues through a robust EPA surveillance program and by equally robust sustainability assessments and analytics. However, once an emerging issue has been identified, an initial assessment will be necessary to categorize it in such a way as to determine whether regulatory oversight is necessary and, if so, which regulatory agencies should engage. Given that emerging issues, whether proceeding from societal or natural factors, will probably cut across social, economic, technologic, and environmental risk assessment and management, multiple regulatory agencies often will need to engage and collaborate. The discussion on megatrends in Chapter 2 identified several important drivers of new issues that may confront regulatory agencies in the future.
The rate at which challenges are likely to approach and their increased complexity will afford progressively shorter periods in which to assess them and, if necessary, to devise strategies to address them. An increased technical presence within the staffs of regulatory agencies may be required. And screening assessments, tools, and formal sustainability assessments may need to be further automated to meet the rapid throughput that new-issue management will require.
Given the global nature of many existing environmental and sustainability issues and the likelihood that new issues will have international implications, new-issue identification may promote congruent approaches and regulatory convergence among countries that are attempting to address newly identified issues jointly. The sharing of sustainability tools and approaches could foster such congruent approaches.
Rapid Changes in Information Technology and Resulting Opportunities for Input and Stakeholder Engagement
The stunning pace of advances in information technology (IT), data management, and analytics (Chapter 2) presents opportunities for EPA to engage stakeholders better. The considerable computing research already under way in EPA provides an excellent base for improving many sustainability tools and approaches while providing the capacity to create new approaches, tools, and models to support new-issue identification and assessment. Sustainability and the U.S. EPA, the so-called Green Book (NRC 2011a) recommended the development of a screening tool to assess an emerging issue rapidly to inform the selection of appropriate sustainability tools and approaches.
Social-media platforms and analytics present new and effective forums to engage stakeholders, allowing for the use of analytic approaches to provide rapid analysis and categorization of stakeholder input and to provide transparency to stakeholders on how the agency uses their input in its decision-making. This approach presents an opportunity to derive a substantial increase in value from stakeholder processes already in place in the agency. Additional value could be created in the use of advanced IT capabilities in:
• Benchmarking the potential effects of newly identified issues in the regulated community and other stakeholders.
• Mapping the effects of newly identified issues in demographic or stakeholder categories.
• Setting priorities of newly identified issues for action in multiple stakeholder categories.
• Identifying the socially influential stakeholders to spearhead the communication of emerging issues to a broader citizenry.
• Assessing stakeholder preferences for sustainable and resilient products and technologies through analysis of social-media data.
EPA should leverage and enhance its advanced IT capabilities to assess emerging issues by involving the regulated community and other stakeholders through social analytic tools. (Recommendation 6a)
Incorporating insights from a broad array of stakeholders could markedly improve EPA’s understanding of a new issue’s importance and of the speed with which it is emerging. The insights could also improve the evidence base for the agency’s decision-making process and increase the likelihood of stakeholder acceptance of difficult decisions.
The massive extent to which our world has been instrumented, interconnected, and digitized presents new opportunities to change the way in which decision making is accomplished and government agencies deliver their services. Concepts of e-government, digital government, and digital state include interactions between the government and individuals within a secure, online context. In addition, this new digital age offers opportunities for the government and the governed to conduct a rational and innovative dialog on sustainability. This is especially true when governments are able to discuss sustainability with a focus on what constituents value most, adoption of service design thinking (considering the constituents’ perspectives) and building strong levels of trust with public, academic and business sectors. Extensive digital capabilities and assets, such as the ability to assess massive amounts of public-comment through deep analytics, have the potential to deliver answers rapidly to the public via mobile devices and create effective and trustworthy data security and personal privacy through advanced security solutions. In addition, the advent of machine-to-machine learning and cognitive computing portends, not only the democratization of knowledge, but perhaps also the democratization of insights. Shared insights are a powerful cohesive force in consensus building and decision making within sustainability discussions.
If staff reductions and budget cuts continue, EPA may have neither the time nor the resources to devote to expanding and refining its capability to identify and address emerging environmental challenges. The agency could benefit from strategic interaction with industry and academe in a larger collaboration focused on future method development related to sustainability concepts with joint development of assessment tools and approaches. In fact, future development of all existing or new tools and approaches could benefit from a similar strategic collaboration, perhaps occurring in projects under EPA’s Design for the Environment program.
Unintended Consequences and Sustainability
The concept of unintended consequences is not a new issue for EPA. For example, the Clean Air Act Amendments of 1990 required that gasoline sold in areas of the nation that have poor air quality have a specified oxygen content to reduce tailpipe pollutant emission. In the 1990s, methyl tert-butyl ether (MTBE) was used widely as a gasoline additive to meet that requirement. The now obvious unintended consequence of the widespread use of MTBE was extensive groundwater contamination from leaking underground storage tanks (EPA 1999). Another fuel issue arises from the Renewable Fuel Standard and government support and subsidies for the use of corn-based ethanol as a renewable fuel component of gasoline. As discussed in Chapter 4, increased corn production to meet the demand for corn-based ethanol has raised concern about several sustainability-related consequences, such as hypoxia in the Gulf of Mexico from fertilizer runoff into the Mississippi River and increases in cropland prices (NRC 2011c).
The tools developed by EPA for use in environmental, economic, and social aspects of sustainability practice represent a major investment in sustainability considerations. However, there does not appear to be an overarching capability to integrate the tools in real time in such a way that the outcomes of the combined use of tools or approaches, within or among sustainability considerations, can be assessed and visually represented. Although the futures methods address that need to some extent, it is not a tool set that is able to provide results quickly. Some available cognitive computing systems execute that type of decision analysis in real time. Existing computing capacity (NRC 2012b; EPA 2013a) supplemented with research and development investment to refine sustainability analyses could allow sustainability analysts to run repeated “what if” exercises to reveal aggregate effects in all three pillars of sustainability.
The process of implementing sustainability concepts needs substantial investment in the early discovery of potential unintended consequences because of the concern about optimizing present and future outcomes and intergenerational effects. Unintended consequences are not necessarily unforeseeable; deep
analytics technology, which is available, could be applied to this topic. The addition of a formal learning loop would capture additional value from case histories and lessons learned in sustainability projects undertaken by EPA.
To enhance postdecision assessment of its activities, EPA should identify, track, and address unintended consequences. The agency should create a searchable database of the lessons learned. (Recommendation 6b)
Not only would that provide additional evidence-based support capabilities for future decision-making, but the data could feed advanced cognitive analytics that could be used to test proposed decisions against known unintended cause–effect scenarios developed from past decisions.
Tools and Approaches for Identifying and Addressing New Issues
National Research Council work on this topic (NRC 2011a; EPA 2013a) has emphasized the need for a tiered approach to understand what tools should be applied in sustainability assessments and has provided explicit recommendations about investment in screening capabilities. Applying futures methods will inform and guide the use of other sustainability tools as the scenarios developed become more mature and data-stable.
A tiered approach to identifying and addressing emerging challenges includes:
• Applying approaches to identify possible emerging challenges (EPA 2014r):
o Scanning methods enhanced by deep-analytics tools to provide early detection of even weak signals or patterns.
o Delphi methods involving subject-matter experts.
o Trend-analysis methods for quantitative data and additional analytic tools for assessing unstructured data.
o Future scenarios that use quantitative, qualitative, and unstructured data to fuel real-time and dynamic scenario imaging as data feeds are used to refine and weight potential outcomes.
o The use of crowd sourcing and analytics to detect and predict emerging challenges, particularly for hazardous natural or human-caused areas of concern.
• Organizing and screening emerging challenges for further review by, for example, applying selected screening-level versions of the mature tools now available in each of the three sustainability pillars (NRC 2011a).
• Analyzing emerging challenges:
o Screening-level results drive a rank ordering of emerging challenges for further analysis. The most likely scenarios from the futures methods could be subjected to a more detailed set of assessments for each of the three pillars as more refined data become available.
o Systems-based indicator analysis of likely scenarios from the futures methods could further clarify which projects would benefit most from more refined sustainability assessments.
o Sustainability-assessment tools and approaches will be informed and guided by emerging related issues that are identified and may include environmental-impact assessments, social-impact assessments, benefit–cost analyses (BCAs), risk assessments, resilience and adaptation assessments, segmentation analyses, and collaborative problem-solving (See Appendix D).
• Communication of findings and recommendations—EPA has and continues to develop powerful communication tools and approaches. In addition to briefings, Internet posting, podcasts, articles and brochures for agency staff, legislative staff, and the public, the use of a broad array of social media can be used to communicate with the public rapidly and effectively.
The remainder of this chapter discusses a wide variety of emerging issues that EPA is likely to face with respect to the application of sustainability tools and approaches.
An important milestone was reached in 2008 when it was recorded that more than half the global population was living in cities and towns. The growth of cities is an important emerging trend in the United States and globally, and this poses many challenges in application of sustainability tools and practices. Cities and their associated problems constitute a strong impetus for innovation; and because the urban centers are massive economic engines, they also provide an important opportunity to develop and test new sustainability tools and approaches that can inform decisions on how cities will be designed, built, and managed in the context of local forces in the future. Urban corridors will provide an important test bed for understanding the effects of increasing population density and other societal megatrends on the vulnerability of infrastructure to natural and human-made disasters and on the factors that create urban resilience.
In many evaluations of increased urbanization, discussion of social-ecological system resilience and sustainability usually focuses substantial attention on the negative effects of human-caused changes to urban social-ecological systems (Tidball and Stedman 2013). Such attention can result in an “assumed negativity” regarding humans and nature. However, others point out the positive actions that humans sometimes take in systems in which they live that contribute to virtuous cycles producing, or enhancing production of, positive social and ecological outcomes, such as in ecosystem services (Bartlett, 2005; Tidball and Krasny, 2008; Krasny, et.al. 2009).
As a consequence of the explosion of enabling technologies, many cities in the United States are investing heavily in infrastructure, including investment in instrumentation and sensoring of locations, utilities, and processes and integration of these data inputs into an architecture that allows continuous real-time status awareness, decision support, and management. Increases in urbanization, climate change, and demographic shifts will change cities. The need to improve quality of life, economic competitiveness, and social equity has driven cities to become more resource-efficient and sustainable.
Technologies are major levers and the basis of further sustainable city development. The challenges that arise from cities and megaregions will probably have at their core an increasing population density that will affect virtually every aspect of their economic, social, and environmental quality. Response to those challenges will be constrained by the limitation of the resources that can be applied to an unlimited set of needs.
Many cities in the United States have recently made important efforts in addressing some combination of interconnected problems of urban air quality, efficient energy production and use, urban transportation systems, and climate change (both mitigation and adaptation) by focusing on development and application of sustainability tools and practices (NRC 2013a, 2014).
In the case of large cities, a combination of megatrends of urbanization, climate change, and a recent and rapidly emerging revolution in application of IT, including social media that promote democratization of knowledge and participation by the general public, has provided a fertile landscape for application of sustainability tools and approaches, including BCA, integrated assessment modeling, collaborative problem-solving, futures methods to evaluate alternative future scenarios, and environmental-justice (EJ) analysis (NRC 2014).
Many cities of different sizes—including Portland, Oregon; Philadelphia, Pennsylvania; Phoenix, Arizona; New York, New York; Charleston, South Carolina; and Ft. Lauderdale, Florida—have developed their versions of sustainability plans. Federal-agency partnerships with communities have also promoted urban sustainability (for example, see the discussion in Chapter 2 of the Sustainable Communities Regional Planning Grant Program).And the application of tools available through social networking can be
key to creating sustainable cities because it enables communities to participate in sharing ideas about solutions, such as use of renewable energy, smart transportation choices, and improving air quality through lower per capita energy use. The availability of public portals can inform choices of, for example, transportation modes and provide feedback to the system.
President Clinton’s (EJ) executive order (EO 12898) was the product of considerable evidence that poor and selected minorities were overburdened by hazards and at higher risk caused by exposure to pollution in air, water, and soil. It required federal agencies to prepare and implement EJ strategies for the administration of environmental rules and guidelines. Raising the profile of the EJ issue has, for example, encouraged private organizations to take demographics into account before siting new facilities and expanding existing ones. EPA has developed Plan EJ 2014 to serve as a roadmap for integrating environmental justice into the agency’s programs, policies, and activities. The goals of the plan are to protect health in communities over-burdened by pollution, empower communities to improve their health and environment, and establish partnerships with government organizations to achieve healthy and sustainable communities (EPA 2014s). The plan includes cross-agency focus areas on rulemaking, permitting, compliance and enforcement, community-based programs, and collaborations with other federal agencies. As part of implementing this plan, EPA is developing various assessment tools, including guidelines for cumulative risk assessment, a community-focused exposure and risk screening tool, mapping and analysis tools to elucidate benefits that humans receive from their environment, and a screening tool to identify areas with potential EJ concerns that may warrant further consideration (EPA 2014t).
There is growing awareness of the need to include EJ analysis in a sustainability analytic context. EPA included EJ analysis as one of the tools in its Sustainability Analytics report (EPA 2013a) (see Box 6-1). A special panel of EPA’s Science Advisory Board is reviewing the agency’s draft technical guidance for assessing EJ in regulatory analysis and is considering subjects that are directly and indirectly related to the intersection of EJ and sustainability.2 Clearly, EJ tools and approaches will be required both in the early identification of new issues and in the later stages of analysis and actionable recommendations. A rapid screening tool that could quickly be applied to a newly identified emerging challenge to allow an initial weighting of potential EJ concerns is especially important. Development of the capability for robust EJ analysis is also important, but the rapid emergence of new challenges requires quick screening capability to ensure that EJ issues are included in sustainability considerations.
“Incorporating EJ analysis into the decision-making process promotes sustainability by highlighting the relationships between economy, society, and the environment. However, while scientific and quantitative advancements in EJ analyses have enabled researchers and stakeholders to better grasp disproportionate impacts of environmental stressors and socio-demographic conditions, the complex nature of interactions between these factors is not fully understood. For example, EJ analyses are often required to be performed without the benefit of full-scale epidemiological studies and, hence, while correlations between health impacts and populations may be apparent, analysts should be mindful that the cause and effect may not have been demonstrated.”
Source: EPA 2013a (p. 39).
2EPA asked the Environmental Justice Technical Guidance Review Panel to provide advice and recommendations on the scientific soundness of the agency’s Draft Technical Guidance for Assessing Environmental Justice in Regulatory Analysis (EPA 2013g).
Demand for Unsustainable Materials
With increasing population and increasing demand for consumer goods, the need for materials continues to grow. Curren ly, only 29% of the 70 gigatons (Gt) of materials that the world economy uses annually are recycled (Ashby 2012). Current rates have quadrupled consumption from 50 years ago, creating a demand trend for materials that is unsustainable with current practices. Five key materials make up a substantial fraction of carbon emission into the atmosphere: steel, cement, plastic, paper, and aluminum. Industry accounts for 38% of the total global carbon dioxide emission, and the five key materials listed above account for 56% of industrial carbon emission (IEA 2008). A breakdown of those emissions can be seen in Figure 6-1.
By 2050, the International Energy Agency expects demand for materials to at least double, but the Intergovernmental Panel on Climate Change (IPCC) recommends reducing global emission by 55–85% by that same year (Fisher et al. 2007). Even with an optimistic projection of efficiency, the increased demand makes it impossible to reach the reduced emission targets set by the IPCC (shown in Figure 6-2). Included in the projections are implementation of energy-efficiency measures, future efficiencies in the supply chain, reduction in yield losses, maximum recycling rates, and decarbonization of energy supplies. Substantially increased material efficiency is needed to meet future demand, although much research still needs to be done to balance resource demand with environmental effects and cost.
FIGURE 6-1 Global carbon emissions in 2006 and breakdown of the industrial-source sector. Source: Allwood 2011. Reprinted with permission; copyright 2011, Resources, Conservation and Recycling.
FIGURE 6-2 Optimistic projection of future emissions of five key materials in 2050. None of the materials is expected to reach the 2050 target of a 50% reduction in emission. Source: Allwood et al. 2011. Reprinted with permission; copyright 2011, Resources, Conservation and Recycling.
One of the major sustainability challenges is the scarcity of resources, such as raw materials. Historically, shortages of essential materials usually resulted in various kinds of conflicts. Today, resource scarcity continues to be a controversial emerging challenge that engages all three pillars of sustainability. It touches on many aspects of sustainability, such as intergenerational equity, resilience, adaptability, EJ, and social equity. The prospect of future scarcities of vital natural resources is, in many specific cases, underscored by present shortages in water, food, and strategic minerals.
However, from the heightened concern over resource scarcity seen in 2009–2012 (World Economic Forum 2012), a new view of scarcity has turned the emerging issue into an emerging opportunity in the minds of a growing industrial sector. The fundamental premise of the new view of material scarcity is that it will drive yet another industrial revolution (Heck and Rogers 2014) as a result of the convergence of IT, nanoscale materials science, and bioengineering. This view posits that businesses will capitalize on material scarcity by focusing on resource productivity by using five distinct approaches (Heck and Rogers 2014):
• Substitution—replacement of expensive or scarce materials with less scarce, less expensive, higher-performing materials.
• Optimization—embedding software and IT in resource-intensive industries to improve how the industries produce and use scarce resources.
• Virtualization—moving some processes completely from the physical world (such as digitalization of some processes and the use of cognitive computing capabilities).
• Circularity—finding value in products after their initial intended use.
• Waste elimination—greater efficiency through the redesign of products and services.
Thus, one can imagine that, rather than a spiral of scarcity and rising costs of a shrinking commodity, the challenge that will affect EPA’s programs may be the evolution of a host of new materials and material uses. It will probably be a challenge for EPA to provide the inhouse subject-matter expertise needed to address emerging issues in materials development and use.
EPA should consider using its convening ability to foster academic, business, and government partnerships to develop scientific and technical understanding to inform agency decision-making. (Recommendation 6c)
Horizon Materials (Including New Chemicals)
Horizon materials can be defined as advanced next-generation materials that are likely to have a serious effect on our society and economy. Borne of the convergence of advances in IT, industrial technology, materials sciences, and bioengineering, the development of horizon materials often enables new applications in various industry segments.
In light of the growing number of US and global patents and regulations involving materials, the topic of horizon materials should be on the emerging-challenges radar screen. Technical innovations in discrete fields are continuing to overlap, resulting in nanomedicine, nanobiotechnology, genomic-specific therapeutics, systems biology, and bioengineering. The blurred lines here will also demand vigilance in US regulatory agencies.
Nanotechnologies are set to transform the global industrial landscape and involve US economic sectors as diverse as agriculture, medicine, engineering, biology, and IT. IOM (2005) and NRC (2013c) em-
phasized that—despite stunning advances in nanomaterials, environment, health, and safety—research on nanomaterials is not keeping pace with the evolving applications of nanotechnology, and uncertainties in the environmental, health, and safety aspects of this technology persist (see Figure 6-3).
Characterization of the risks posed by engineered nanomaterials and their applications in commercial and consumer products presents substantial challenges to life-cycle assessments, risk analyses, and governance.
Given the rapidly evolving applications (especially biologic) of nanoscale materials, devices, and systems, EPA should work with other organizations to fund research in risk characterization and develop the infrastructure needed to support data-mining and data-sharing. (Recommendation 6d)
Although much progress has been made, gaps in knowledge of the environmental, health, and safety (EHS) aspects of nanomaterials remain. Better understanding and integration of EHS data will enhance the effective regulation of these materials.
FIGURE 6-3 The nanotechnology environmental, health, and safety research enterprise. The diagram shows the integrated and interdependent research activities that are driven by the production of engineered nanomaterials (ENMs). The production of ENMs is captured by the orange oval, labeled “materials”, which includes reference materials, ENM releases, and inventories. (An inventory is a quantitative estimate of the location and amounts of nanomaterials produced, including the properties of the nanomaterials.) The knowledge commons (red box) is the locus for collaborative development of methods, models, and materials and for archiving and sharing of data. The “laboratory world” and “real world” (green boxes) feed into the knowledge commons. The laboratory world comprises process-based and mechanism-based research that is directed at understanding the physical, chemical, and biologic properties or processes that are most critical for assessing exposures and hazards and hence risk (NRC 2012c, p. 55). The real world includes complex systems research involving observational studies that examine the effects of ENMs on people and ecosystems. The purple boxes capture the range of methods, tools, models, and instruments that support generation of research in the laboratory world, the real world, and the knowledge commons. Source: NRC 2013c, p. 25.
Nanotechnology also offers an archetypal glimpse of the future with regard to the global governance of emerging technologies (Breggin et al. 2009; Falkner and Jaspers 2012). Emerging technologies create unusual, complex, and often fundamental political problems for global governance. Recent international governance coordination mechanisms have been created through the Organisation for Economic Cooperation and Development and the International Organization for Standardization, but the scope of their efforts is limited. Given the lack of harmonization and alignment in global regulatory policies and practices and the great promise inherent in nanotechnology development, the convening nature of sustainability approaches may constitute a logical bridge across the governance divide.
Partially obscured by the attention garnered by nanotechnology, a rapidly advancing convergence is occurring in the biospace. Driven by affordable genomics analyses, next-generation genomics marries the advances in sequencing and modifying of genetic materials with the latest big-data and analytics capabilities and enables synthetic biology (“writing” DNA).
An excellent example of the convergence can be seen in a snapshot of emerging medical advances. High-throughput genomic analyses create a pipeline of raw data that are processed by high-end computing and deep analytics into usable information. That information fuels genomic-data integration and analytics platforms to find relationships between genomes and phenotypes, and this leads to the discovery and development of personalized therapies. Such relationships enable not only personalized heath care but decision support for precision medicine.
However convergence of genomics and deep analytics drives a much more rich and complex constellation of capabilities that enables new potentials in three major disciplines: -omics big data and analytics, systems biology (modeling), and bioengineering (synthetic biology). An important example of an emerging new capability in the biospace convergence is metagenomics (Wooley et al. 2010). Metagenomics is the study of the genetic material recovered directly from environmental samples rather than from cultured microbial samples. This approach has revealed that the vast majority of microbial diversity has been missed by cultivation methods (Breitbart et al. 2002). Metagenomics has become an important predictor as well as a tool for use in addressing futures issues in sustainability.
For instance, the research community is beginning to understand that antibiotic resistance may have strong environmental associations. Through the use of metagenomic tools and deep analytics, antibiotic-resistance genes have been shown to accumulate in wastewater-treatment plants (Yang et al. 2013), as contaminants in manures and other agriculture waste products (Zhu et al. 2013), in the water and sediments of rivers (Luo et al. 2010; Kristiansson et al. 2011), and in reclaimed water (Fahrenfeld et al. 2013). One of the most important factors in the development of antibiotic resistance is the remarkable ability of bacteria to share genetic resources via lateral gene transfer (Stokes and Gillings 2011). The use of activated sludges on farmland and the use of reclaimed water in distribution systems and irrigation may accelerate the spread of antibiotic resistance (Fahrenfeld et al. 2013). The World Health Organization has recently released a report on global surveillance of antimicrobial resistance (WHO 2014), which warns of a coming postantibiotic era without global intervention. Given the broad genetic diversity found in metagenomic studies, there is great potential in finding and using gene sequences that could be immediately useful in industrial applications. Bioengineering and industrial biotechnology often are central in sustainability predictions and require the development of novel enzymes, processes, products, and applications. Metagenomics promises to provide insights into new molecules that have diverse functions, but it is the exploitation of the gene-expression systems that are the key to the economic success of the new molecules.
This brief discussion of the biospace convergence should make it apparent that the new insights enable capabilities in diverse sectors of the economy (see Box 6-2).
Health Care and Genomic Medicine
Personalized and preventive health care
Biosensors and bioelectronics
Accelerated drug discovery, development, and manufacturing
Agriculture and Food
Salt-, drought-, and disease-tolerant crops
Energy, Environment, and Natural Resources
Sustainable biofuel production
Rare-earth and precious-metal collection
Carbon capture and bioremediation of air, water, and soil
Chemical, Pharmaceutical, and Consumer Products
Green-chemistry enabling of bioplastics and enzymes
Functional material enhancements, such as spider silk in tires
Cosmetics and personal-care product enhancements
Clearly, this will be a target-rich space for new and emerging issues that will require sustainability assessments and solutions. Sustainability tools, approaches, and assessments may be crucial if the pros and cons of the emerging innovations are to be understood and acted on.
Closely aligned with the nanotechnology and biospace discussions are a related set of productivity advances and sustainability practices that arise in the manufacturing space. Collectively, these activities and practices are often referred to as advanced manufacturing, which is defined as “a family of activities that: a) depend upon the use and coordination of information, automation, computation, software, sensing, and networking; and/or b) Make use of cutting edge materials and emerging capabilities enabled by the physical and biological sciences (nanotechnology, chemistry, biology)” (PCAST 2011, p. ii). The activities involve new ways to manufacture existing products and advanced technologies to manufacture new products. They affect all five stages of manufacturing: product design, production planning, engineering, production, and service and maintenance.
These capabilities have converged to create a scenario in which an idea can move through design, prototyping, engineering, and production within an hour with 3D computer design, digital prototyping, and additive manufacturing (3D printing that uses polymers or metals). In fact, the ability to model, visualize, and test in the world of virtual-to-real manufacturing is changing the nature of innovation and allowing a new level of efficiency and customization. The United States—with a track record of innovation, software design and development, and university education—is now driving a new era of efficient products by lowering costs and allowing mass customization, extreme scalability, and high speed to market.
The innovative technologies and machinery lead to huge dividends for the environment and economy, such as reductions in material use and waste and in energy use; some manufacturing steps will never again be physical but will remain in the virtual world until translated in final production steps. From this perspective, this represents a major step forward into a more sustainable manufacturing scenario.
It is important to recognize that innovative and disruptive technologies will probably enable the use of new and exotic materials and methods and will enable “manufacturing” to take place not only in modern, clean, tightly controlled facilities but in homes, garages, and schools.
Advanced manufacturing provides new opportunities for material-efficient and energy-efficient processes, but EPA should address this emerging issue as a part of a futures-methods analysis. (Recommendation 6e)
The potential for manufacturing to occur in nonmanufacturing environments might well create new challenges for occupational and environmental regulators. New futures methods will be needed to predict, assess, inform, and guide governance.
Sustainability and Hazardous Events
The scientific consensus is that global climate change is occurring and that weather will trend toward extreme events. Therefore, it is imperative that sustainability factors be considered by planners, engineers, emergency managers, public-health workers, and associated professionals to reduce the vulnerability of people and assets. Sustainability-related activities include removing highly vulnerable land from development and turning it into open space or to less vulnerable uses, siting infrastructure in less vulnerable locations, and prohibiting activities in high-risk areas that have highly vulnerable populations. The activities include retrofitting of structures to be more resistant to hazardous events, providing loans and other inducements to property owners to reduce their vulnerability, and organizing local first responders and community groups that can increase the resilience of a community. Those and many other sustainability activities can be implemented before, during, or after events. It would be prudent to focus on particularly vulnerable populations, such as older people, disabled people, children, and people whose response to hazard events may be hindered by language barriers, lack of transportation options, and other constraints. A great deal of literature is appearing on those subjects in public health, urban planning, and emergency management.
EPA should consider the development of additional futures methods that focus on assessing and predicting vulnerability and resilience of both urban and rural environments. (Recommendation 6f)
More accurate and earlier prediction of emerging issues related to environmental settings would enhance the ability to incorporate resilience strategies into infrastructure design.
Incorporation of resilience in the context of sustainability would have implications for the design and planning of projects, particularly urban infrastructure projects. However, it has been a challenge to accomplish that because no comprehensive tool for quantifying resilience is available. A conceptual tool, the Sustainable and Resilient (SuRe) zone of planning and design, aims to address that issue (see Box 6-3).
Resilience analysis is a tool for evaluating the ability of a system (such as a city’s infrastructure, an ecosystem, or a supply chain) to continue functioning after a disruption. Considering options for increasing resilience can be challenging when narrowly targeted sustainability objectives are also being pursued to reduce material and energy investment, motivate the removal of redundancy from systems, and thus undermine their resilience. An approach is being developed to assess sustainability and resilience of urban infrastructure systems simultaneously. It involves use of traditional benefit–cost analysis to assess the costs associated with the building of a more resilient infrastructure and the benefits of avoiding damages through augmented resilience (Pandit et al. in press).
|Sustainability Focus Area||New Issue||Tools to Identify or Evaluate Issue|
|Energy efficiency||Climate change, rapid urbanization, and air quality||Benefit–cost analysis, environmental-justice analysis, futures methods, exposure assessments, risk assessments, health-impact assessments, integrated assessment modeling, resilience assessments, collaborative problem-solving|
|Sustainable products and purchasing||Advanced manufacturing enabling new products and bioengineered materials||Life-cycle analysis, benefit–cost analysis, green chemistry, green engineering, exposure assessments, health-impact assessments, environmental-footprint analysis, integrated assessment modeling|
|Green infrastructure||Engineered systems for the reuse of water and activated sludges and rising concentration of antibiotic-resistant microorganisms in urban areas||Benefit–cost analysis, environmental-footprint analysis, green engineering, collaborative problem-solving, lifecycle analysis, exposure assessments, risk assessments, health-impact assessments, environmental-justice analysis, resilience analysis, social-impact analysis|
|Sustainable materials management||Horizon materials development and use||Benefit–cost analysis, green chemistry, green engineering, risk assessments, chemical-alternatives assessments, life-cycle assessments, environmental-footprint assessments|
The previous discussions in this chapter reveal a striking relationship: new or emerging issues have substantial intersections with EPA’s four focus areas for sustainability and the tools and approaches described in Table 3-1. It should be noted in this context that new issues are likely not to occur in single occurrences (such as climate change) but rather to arise from an aggregation of issues (such as climate change, energy disruptions, food disruptions, and aridity) (NRC 2013a). Table 6-1 provides a few examples to illustrate the nexus by focus area, new issue, and tools for predicting, detecting, or assessing the issues.
The examples in Table 6-1 are not meant to be exhaustive but rather to stimulate thinking about how sustainability focus areas are affected by new issues and how sustainability tools will have the potential both to identify and to evaluate effects of new or emerging issues. The complexity of new issues and their rate of occurrence will probably place even greater demands on even the most automated and robust tools and approaches in the race to prevent new issues from surging to become old unresolved problems.
Conclusion 6.1: The rate at which future challenges are likely to approach and their increasing complexity will afford less and less time in which to assess them and, if necessary, to devise strategies to address them. A set of screening tools that can be implemented rapidly is essential. It is important to avoid rapidly approaching challenges from becoming historical events before they can be adequately assessed.
Recommendation 6.1.1: EPA should develop screening tools to assess new issues rapidly to support the selection of appropriate sustainability tools and approaches.
Recommendation 6.1.2: Existing screening approaches, tools, and formal sustainability assessments should be automated further for the rapid analysis that responses to new issues will require.
Conclusion 6.2: The tools developed by EPA for use in environmental, economic, and social areas of sustainability practice represent a major investment in sustainability considerations. However, there does not appear to be an overarching capability to integrate the tools, in real time, in such a way that the results of their combined use can be assessed and visually represented. An integrated “big picture” capability would lead to deeper insights, better pattern recognition, and better decision-making through the avoidance of the overweighting or masking that can be caused by the serial use of tools.
Recommendation 6.2: EPA should leverage and enhance its advanced IT capabilities for integrating sustainability tools so that the outcomes of their combined use approaches can be simulated in a sustainability context in real time. (See Recommendation 6a)
To enhance post-decision assessment of its activities, EPA should identify, track, and address unintended consequences. The agency should create a searchable database of these valuable lessons learned. (Recommendation 6b)
Conclusion 6.3: The use of a broad array of social media can be used to communicate rapidly and effectively with the public. Private and public organizations are increasingly leveraging the use of structured and unstructured public input to improve prediction of public preferences and to extract valuable insights into public behavior. Public support for regulatory decision-making could be substantially enhanced by using such approaches.
Recommendation 6.3: EPA should consider piloting “electronic jams” that reach out to the public in monitored on-line chat sessions that allow public input to be analyzed and additional value to be derived from it. In addition to the public-comment aspect of this approach, passive “crowd sourcing” can be useful in identifying new issues. (See Recommendation 6a)
EPA should consider using its convening ability to foster academic, business and government partnerships in this area to develop adequate scientific and technical understanding to inform agency decision making. (See Recommendation 6c)
Given the rapidly evolving applications (especially biologic) of nanoscale materials, devices and systems, EPA should work with other organizations to fund research in the area of risk characterization and develop the infrastructure needed to support data-mining and data-sharing. (Recommendation 6d)
Advanced manufacturing provides new opportunities for material-efficient and energy-efficient processes, but EPA should address this emerging issue as a part of a futures-methods analysis. (Recommendation 6e)
EPA should consider the development of additional futures methods that focus on assessing and predicting vulnerability and resilience of both urban and rural environments. (Recommendation 6f)