This course provides an introduction to the major themes of sustainability science with a focus on the application of science to the practice of sustainability. Basic research, especially in the environmental and social sciences, explores the Earth as a system of systems, wherein the physical, chemical and biological systems interact with each other as well as human systems to affect our future. The results of this research are often difficult to apply in practice unless the research in translated into actionable advice for individuals, governments and private enterprise. Even so, the actual or perceived complexities of interactions between human and “natural” systems are often seen by decision makers as barriers to long-term planning, an essential element of pursuing sustainability. A simple definition of sustainability is based on intergenerational equity. Thus, the relationships between the here-and-now and possible global futures need to be understood. Students enrolled in this course will discuss: Definitions of sustainability, including environmental, cultural and socio-economic components; Technologies for observing natural systems and their impacts on human systems; Summaries of scientific understanding of global-scale climate dynamics, natural hazards, biodiversity, environmental stressors and anthropogenic inputs to coupled human-natural systems; An overview of the strengths and weaknesses of science-based prediction; An introduction to geoengineering; Developing the evidence base for sustainability decisions; An introduction to risk assessment, perception and management; Decision making under uncertainty; General principles of sustainability management. An undergraduate background in any field of science or engineering and mathematics through statistical and time-series analysis is required. An interest in coupled natural-human systems is desirable.
Both human and natural systems are growing more vulnerable to climate variability (e.g., the anomalous weather induced by the El Nino-Southern Oscillation, or the increase in hurricanes that occurs when ocean currents warm the Atlantic) and to human-induced climate change, which manifests itself primarily through increases in temperature, precipitation intensity, and sea level, but which can potentially affect all aspects of the global climate. This course will prepare you to estimate climate hazards in your field thereby accelerating the design and implementation of climate-smart, sustainable practices. Climate models are the primary tool for predicting global and regional climate variations, for assessing climate-related risks, and for guiding adaption to climate variability and change. Thus, a basic understanding of the strengths and limitations of such tools is necessary to decision makers and professionals in technical fields.
This course will provide a foundation in the dynamics of the physical climate system that underpin climate models and a full survey of what aspects of the climate system are well observed and understood and where quantitative uncertainties remain. Students will gain a fundamental understanding of the modeling design choices and approximations that distinguish Intergovernmental Panel on Climate Change (IPCC)-class climate models from weather forecasting models and that create a diversity of state-of-the-art climate models and climate projections.
This course will provide an overview of the ways in which climate model output and observations can be merged into statistical models to support applications such as seasonal and decadal projections of climate extremes, global and regional climate impacts, and decision-making. Students will develop the skills to visualize, analyze, validate, and interpret climate model output, calculate impact-relevant indices such as duration of heat waves, severity of droughts, or probability of inundation, and the strategies to characterize strengths and uncertainties in projections of future climate change using ensembles of climate models and different emission scenarios.
Natural hazards, naturally occurring phenomena, which can lead to great damage and loss of life, pose a great challenge for the sustainability of communities around the world. This course aims to prepare students to tackle specific hazards relevant to their life and work by providing them the scientific background and knowledge of the environmental factors that combine to produce natural disasters. The course will also train students about the methods used to study certain aspects of natural hazards and strategies for assessing risk and preparing communities and businesses for natural disasters. The course will cover a range of natural hazards, including geological, hydro-meteorological, and biological. The course will emphasize the driving physical, chemical and biological processes controlling the various hazards, and the observation and modeling methods used by scientists to assess and monitor events. Many case examples, including hurricanes, earthquakes and volcanic eruptions that occurred in the last five years, will be given and analyzed for the characteristics of the event, the preparation, and the response.
By providing students with a solid understanding of past natural disasters, the course prepares them to think more critically about creating more resilient communities, which can resist catastrophic events. Students will be studying the underpinning scientific principles of natural disasters but will also learn specific strategies for planning, mitigation, and response. During the course, students will master cutting-edge tools and technologies that will prepare them to work in the complex and demanding field of disaster management. After completing the course, students will be able to understand past events, communicate risk, and make critical decision related to disaster and preparedness. In increasingly unpredictable times, there is a need for more resilient and connected communities, and this particular course will train students in both the knowledge and skills needed to lead and strengthen those communities and resilience efforts at scale.
Advising Note:
Students are expected to have taken college-level Calculus, Physics, and Introductory Statistics. Students are expected to have experience with computer based data analysis (Excel, R, Matlab or Python).
Students in the Master of Science in Sustainability Science will encounter a range of scientific problems throughout their Science-specific courses that require a strong foundational level of mathematical and statistical knowledge. In addition, course-work will involve computer coding to read, analyze, and visualize data sets. This course provides an overview of essential mathematical concepts, an introduction to new concepts in statistics and data analysis, and provides computer coding skills that will prepare students for coursework in the Master of Science in Sustainability Science program as well as to succeed in a career having a sustainability science component. In addition to an overview of essential mathematical concepts, the skills gained in this course include statistics, and coding applied to data analysis in the Sustainability Sciences. Many of these skills are broadly applicable to science-related professions, and will be useful to those having careers involving interaction with scientists, managing projects utilizing scientific analysis, and developing science-based policy. Students enrolled in this course will learn through lectures, class discussion, and hands-on exercises that address the following topics: Review of mathematical concepts in calculus, trigonometry, and linear algebra; Mathematical concepts related to working on a spherical coordinate system (such as that for the Earth); Probability and statistics, including use of probability density functions to calculate expectations, hypothesis testing, and the concept of experimental uncertainty; Concepts in data analysis, including linear least squares, time-series analysis, parameter uncertainties, and analysis of fit; Computer coding skills, including precision of variables, arrays and data structures, input/output, flow control, and subroutines, and coding tools to produce basic X-Y plots as well as images of data fields on a global map.
Students are expected to have completed a year of high school physics and chemistry. It would be best to have also taken college level physics and chemistry.
Renewable energy is generated from natural processes that are continuously replenished. Aside from geothermal and tidal power, solar radiation is the ultimate source of renewable energy. In order to have a sustainable environment and economy, CO2 emissions must be reduced (and eventually stopped). This requires that the fossil fuel based technologies underlying our present electricity generation and transportation systems be replaced by renewable energy. In addition, the transition to renewable technologies will move nations closer to energy independence and thereby reduce geopolitical tensions associated with energy trading. This course begins with a review of the basics of electricity generation and the heat engines that are the foundation of our current energy systems. This course will emphasize the inherent inefficiency associated with the conversion of thermal energy to electrical and mechanical energy. The course then covers the most important technologies employed to generate renewable energy. These are hydroelectric, wind, solar thermal, solar photovoltaic, geothermal, biomass/biofuel, tidal and wave power. The course ends with a description of energy storage technologies, energy markets and possible pathways to a renewable energy future.
This course will lead participants through a series of case studies of environmental contamination of water and soil, both natural and man-made, from a perspective of their contribution to the global burden of disease. Participants will critically examine datasets documenting toxic exposure in developing countries and around New York City. Participants will have the opportunity to deploy some field kits and compare their results to laboratory measurements. An emphasis on empowerment through measurement, mapping, and sharing of information will lead to a discussion of regulation, policies, and mitigation.
In this course, students will first be provided with a global perspective on the current status of environmental problems and the leading environmental contributors to the burden of diseases. Students will then introduce how air pollutants are produced, transported, and what are their environmental fates. This course will cover how air pollutants are measured and monitored, including government monitoring networks, NASA remote sensing techniques, and research tools for fixed site monitoring (indoor and outdoor) and personal level monitoring. Students will be able to learn basic concepts about the toxicity and target organs of different pollutants, both of which are important to understand dose-response and health outcomes. Building on knowledge of exposure and toxicity, Students will then introduce risk assessment and the Global Burden of Disease (GBD) associated with air pollution. Their usage in evaluating sustainability as well as their limitations will be introduced.
The course will provide students with the methods and tools to understand, monitor, and analyze current environmental health threats in air, and explore strategies for policy interventions for solving these at times complex challenges. Students will leave the course with a stronger sense of the power, and limitations, of environmental data and better equipped to evaluate and communicate the effectiveness of new interventions. After completing the course, students will more confidently be able to apply core scientific concepts to evaluating and addressing public health challenges posed by, for instance, fine particulate (PM2.5) contamination.
Aquatic systems are critical for provisioning ecosystem services that have sustained human civilization as evidenced by the establishment of the earliest civilizations on banks of rivers or along a coast. Apart from regulating climate, aquatic systems provide food and transportation services, fresh water lakes and reservoirs provide water for consumption and irrigation, and coastal systems offer recreational services. But growing human population, especially along the coast, has endangered the quality of ecosystem services. The primary finding of the Millennium Ecosystem Assessment was that 15 out 24 ecosystem services examined are being degraded or being used unsustainably (MEA 2005). Monitoring the aquatic ecosystem and understanding how to distinguish between anthropogenic and natural variability is an essential aspect of sustainability science. This course will provide an introduction to the use of remote sensing techniques that can be used to study the aquatic environment. There are several space-based sensors that provide information relevant to sustainable management of aquatic resources. Depending on the sensor, observations are made as frequently as every day and spatially covering the entire globe. Understanding the spatial and temporal context around an issue can help discriminate between local and far field effects and time series of remote sensing data can be constructed to investigate causes and consequences of environmental events. Thus knowledge of the basic science of remote sensing, understanding how to select the appropriate sensor to answer a question, where to find the data and how to analyze this data could be critical tools for anyone interested in oceanic, coastal, and freshwater resource management. The course will follow active learning techniques and will consist of a lecture to introduce concepts followed by a discussion and lab time for hands on activities to learn and use tools for analysis of remote sensing data. After the introduction of the basic principles of remote sensing, a series of case studies will be used to explore concepts in sustainability such as water quality, nutrient loading and hypoxia, coral reefs. Remote sensing tools that are used to investigate and address environmental questions such as the effects of shutting down a sewage treatment plant, mapping of suspended sediment concentrations will be demonstrated and used by the students. Each case study will be briefly introduced at the end of the pre
This course will present students with the architecture, data, methods, and use cases of environmental indicators, from national-level indices to spatial indices. The course will draw on the instructor’s experience in developing environmental sustainability, vulnerability and risk indicators for the Yale/Columbia EPI as well as for a diverse range of clients including the Global Environmental Facility, UN Environment, and the US Agency for International Development. Guest lecturers will provide exposure to Lamont experience in monitoring the ecological and health impacts of environmental pollution and the use of environmental indicators in New York City government. Beyond lecture and discussion, classroom activities will include learning games, role play and case study methods.
The course will explore alternative framings of sustainability, vulnerability and performance, as well as design approaches and aggregation techniques for creating composite indicators (e.g., hierarchical approaches vs. data reduction methods such as principal components analysis). The course will examine data sources from both in-situ monitoring and satellite remote sensing, and issues with their evaluation and appropriateness for use cases and end users. In lab sessions, the students will use pre-packaged data and basic statistical packages to understand the factors that influence index and ranking results, and will construct their own simple comparative index for a thematic area and region or country of their choice. They will learn to critically assess existing indicators and indices, and to construct their own. In addition, students will assess the impacts of environmental performance in several developing and developed countries using available data (e.g., pollutant levels in soils and air in Beijing and NYC), and project future changes based on the trends they see in their assessments. The course will also examine theories that describe the role of scientific information in decision-making processes, and factors that influence the uptake of information in those processes. The course will present best practices for designing effective indicators that can drive policy decisions.
Advising Note:
Students are required to have had prior coursework in descriptive and inferential statistics.
This course will explore ways in which the shifting relationship between the human economy and our physical environment drive divergent, often conflicting, responses from different segments of society, including distinct economic classes, communities, nations, industries, etc. For the sustainability professional, such conflicts are important in the development of equitable solutions. They are also critical pragmatic issues in implementation of any new policies. The relative strength of different stakeholders, and the tactics they deploy to pursue their goals can determine what actually happens “on the ground”. We will take a case study approach, looking at how specific socio-economic impacts of environmental change generate calls for social change, shift alignments, deepen stakeholder entrenchment, and influence sustainability policy. Our cases include impacts of global warming, land-use changes, and expanded material throughputs as a result of growing demand in agriculture, fishing, forestry, mining and manufacturing.
Students study the sustainability science behind a particular sustainability problem, collect and analyze data using scientific tools, and make recommendations for solving the problem. The capstone course is a client-based workshop that will integrate each element of the curriculum into an applied project, giving students hands-on experience.