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Development of sustainable solar desalination modeling platforms and proposed application in climate change scenarios in the US
No full textWater demand in the United States is projected to increase by up to 140% by 2050 and 220% by 2070 while climate change will reduce the availability of freshwater in large parts of the country. Climate change threatens existing freshwater supplies, increases drought severity, and destabilizes the water cycle. About 44 percent of the U.S. is experiencing some level of drought with almost 10 percent under “severe to extreme drought.” Desalination technologies offer the potential to substantially reduce water scarcity by converting the almost inexhaustible supply of seawater and the apparently vast quantities of brackish groundwater into new sources of freshwater, although for inland regions the desalination brine management is a big roadblock for such applications, making zero-liquid-discharge (ZLD) desalination an important topic.
This Thesis describes the development of desalination models and simulation platforms that integrate solar energy and water desalination technologies. Furthermore, the Thesis investigates the potential of desalination powered with renewable energy in alleviating projected water scarcity in specific regions. The modeling platform development uses solar generation techno-economic models from NREL’s SAM platform and desalination models from Plataforma Solar de Almeria (PSA) in Spain and Trevi Systems, enhancing the utility of these models by converting them in a Python open-access platform and verifying their results with comparisons with pilot plant and field data. Geographical information system (GIS) databases and tools were integrated with the process modeling platform and created a Solar Energy Desalination Analysis Tool (Sedat) for identifying and characterizing locations with strong prospects for solar-enabled desalination. In a subsequent stage of this research, desalination pretreatment models were integrated in the Water treatment Technoeconomic Assessment Platform (WaterTAP) in a joint project with the National Energy Laboratory (NREL) and New Mexico State University (NMSU). In addition, this research culminated to a new model of multi-effect crystallization for ZLD applications and a US supply-demand analysis which is informed by IPCC projections of water scarcity. an innovative multi-component crystallization approach is proposed for desalination brine management, to greatly reduce the volume of brine and recover marketable salts.
This approach incorporates a multi-effect crystallization system for sodium chloride (NaCl) recovery, and a reactive crystallization process that selectively recovers magnesium (Mg) and calcium (Ca) salts. The new model is used in conjunction with an enhanced reverse osmosis and a membrane distillation model operating in a batch mode, to investigate the potential of renewable-energy-driven desalination with ZLD in response to dry and hot climate IPCC scenarios. This analysis was informed with established brackish water and consumption data layers and showed that desalination using emerging technologies such as low-salt-rejection reverse osmosis (LSRRO), and batch membrane distillation (batch-MD), powered by mainly solar power, can sustainably satisfy projected, due to climate change, deficits in fresh-water supply and demand in the United States
How best to minimize conflicts between the Global Anti-Base Erosion tax rules and international investment agreements
No full textThis Perspective focuses on the thorny interplay between the global minimum tax regime and the global investment regime. Within that ‘niche’ of a high level of complexity and thus specialization, the Perspective answers the question: how best to minimize conflicts between those regimes
Making FDI in extractives work for communities: what role for community benefit agreements?
No full textCommunity benefit agreements (CBAs) have the potential to promote more sustainable resource development by aligning investor-community interests. Governments must decide whether to mandate, support or replace CBAs with alternative policies designed to protect resource-adjacent communities. A proposed model contract clause offers guidance on structuring CBAs—covering funding, governance and enforcement
Tradeoffs between Information, Tractability, and Fairness in Large Matching Markets
No full textMatching theory is one of the cornerstones of modern algorithmic market design, and is therefore heavily studied by communities in operations research, economics, and theoretical computer science. Such models arise whenever a central planner is tasked with pairing together agents of two distinct types but cannot use money to clear the market; and where each agent has idiosyncratic preferences over the agents of the other type. Natural applications of matching markets are found in the allocation of indivisible goods such as school assignment, medical residency matching, and the allocation of government subsidized housing.
Matching theory and in particular stable matching has seen significant research effort since seminal work by Gale and Shapley algorithmically established the existence of a condition called , which guarantees that a matching can be found with the property that no participant is incentivized to deviate from it. Many centralized mechanisms for two-sided matching markets have since been shown to enjoy strong theoretical properties, which , justifies their use in the real world.
However, due to practical constraints---commonly due to the size and complexity of the market at hand---real world applications often resort to simplified models that do not faithfully capture reality. These simplifications lead to the central planner operating without perfect information about the participants or their preferences.
In this thesis, we present three interconnected branches of research exploring tradeoffs between information, tractability, and fairness in large matching markets. We investigate how various limitations on information acquisition and exchange affect the mechanisms, outcomes, and fairness of matching markets.
We are motivated by the matching mechanism that assigns students to public schools in New York City. The unified school district---which encompasses all five boroughs---has since 2003 employed the theory of stable matching to perform this assignment, with students as one side of the market and schools as the other. Consisting of over 1.1 million students, the size and diversity of the market presents a massively interesting real-world object of study.
In the first chapter, we investigate a model where students are restricted in the length of preference lists that they may submit to the market operator. In particular, we study such random instances of the Serial Dictatorship mechanism where students choose schools uniformly at random from schools as their preference list, and each school has exactly one seat. Our main result is that if the students primarily care about being matched to any school of their list (as opposed to ending up unmatched), then all students in position ≤ will prefer markets with longer lists when is large enough, whereas students after some cutoff > (that quickly approaches as the list length grows) prefer markets with shorter lists. This suggests that markets that are well-approximated by our hypothesis and where the demand of schools does not exceed supply, should be designed with preference lists as long as reasonable.
In the second chapter, we study the impact of systemic bias in school matching by investigating the admissions process to the eight elite public schools (called the Specialized High Schools) in New York City. These schools admit students solely based on their score on a standardized test, but we observe a clear distributional shift in the test scores of disadvantaged students (as defined by the city). To study this shift, we present a stylized model where all students have a true potential (representing their innate ability) sampled independently from the same distribution. While non-disadvantaged students always perform at their true potential, disadvantaged students appear at a perceived potential strictly below their innate ability due to some systemic bias. We investigate both theoretically and empirically the impact of such bias on the admissions process, then turn to studying interventions to counter it. These interventions are in the form of vouchers targeted at certain disadvantaged students, which we assume give that student the resources they need to perform at their true potential. We measure aggregate mistreatment under various metrics, first investigating optimal deterministic voucher distribution, and then turning to randomized voucher distribution. We additionally present extensive numerical experiments both on a real dataset from New York, as well as on simulated data. We then confirm that our results hold under various relaxations to our stylized model, including moderate levels of model misspecification. Our key takeaway is that resources should be targeted at slightly above average performers instead of the absolute top performers.
In the third chapter, we take the schools' side. Currently the city allows schools to only specify their preferences using a strict preference list over students. While this leads to a simple algorithm, stable matching models may be extended to allow schools to communicate much more rich preference via choice functions. We discuss the impact of using general choice functions in the offline model of stable matching, establishing that general path-independent and quota-filling choice functions are too large a class to be used in this setting. We propose the class of Kuhn choice functions, that arise as maximum-weight matchings in an auxiliary bipartite graph, as a tractable yet rich subclass. We show that such choice functions are amenable to use in the offline model and possess many desirable properties. We further discuss the hierarchy of choice and approximability of various classes of choice functions. Theoretical proofs are complemented by computational results and a discussion on various practical aspects of using choice functions in stable matching
What Remains
No full textThe second thing they tell you at a vicarious trauma workshop is to turn the audio off while watching the videos. The first thing is to not try to be a hero, and the more content you stoically expose yourself to the more insidiously it will take root. Of course I was too arrogant to listen. Spent hours at work combing through graphic material, listening to every gunshot and scream. Over and over again. I became more withdrawn, cried privately. Over and over again. The visuals are haunting, but they fade eventually. The sounds are ghosts that still live with me.
I used science to intellectualize my troubles. I researched the relationship between sound and memory, a lot of papers about remembering patterns. I researched the relationship between sound and violence, a lot of papers about vets and PTSD. I researched the relationship between violence and memory, a lot of papers about mice and their cortisol levels. And while I now understand why I get auditory hallucinations, I don’t know how to get rid of them.
So now, I use art to romanticize my deteriorating mental health. I journaled to log my thoughts, nagging daydreams, and irrepressible emotions. I want to share a translation of these ramblings, three poems expressed in video. The result is a collage of open-source video, 3D models, and diegetic sound; a quick peek into my quotidian, a chaotic tour through the real, unreal, and ultrareal.
Notes on Contributor
Gauri Bahuguna is a computational designer and researcher dedicated to exploring intersections of art, human rights, and emerging technologies. With over five years of experience investigating complex human rights cases, Gauri has collaborated with practitioners across the domains of advocacy, law, and art to create compelling narratives that are accessible to wider audiences.
As Deputy Director and Senior Researcher at SITU Research, she has led investigations into human rights violations in Sudan, surveillance along the U.S. Southern Border, and short form films for the UN mapping evidence of ISIL’s crimes in Iraq. She has also served as a researcher and curatorial adviser on “Patterns of Life” a collaboration with artist Mona Chalabi for the Cooper Hewitt Design Triennial. Additionally, Gauri has taught electives like “Spaces of Accountability / Models of Justice” and studios at the Cooper Union School of Art, given lectures at Carnegie Mellon, NYU, The New School, and participated in the inaugural Biennale College Architettura in Venice, 2023
“From Chaos to Calm”: Schizophrenic Listening and Hong Kong’s New Infrastructural Acoustic
No full textInfrastructure enables modes of politics to come into being and gives rise to an apparatus of governmentality. Through sensing and “listening in” (LaBelle 2019) to the city, the urban “acoustic habitus” (Feld 1982) emerges out of the city’s governmentality; it comprises ways of listening that define a biopolitical “sonic citizenship” (Western 2021). Governance in Hong Kong’s new “lawscape” (LaBelle 2021) reorients one’s acoustic being in urban spaces, resounding an aural monopoly, which I call the infrastructural acoustic. In the new environment, the “semi-authoritarian” system (Tai 2020) has muted the cacophony of raging roars and unintelligible protests, infusing the city’s atmosphere with an affective entanglement of tear gas and bodies during upheavals in the passé “semi-democratic” (Tai 2020) spaces. Together with Hong Konger self-reflexive poetry, this short film juxtaposes photos, footage, interviews, and field recordings of Hong Kong’s urban spaces during and after years of pro-democracy protests in the old and new Hong Kong to reveal an invisibilized “sphere of appearance” in the “inhabitable ground” (Butler 2016). Insisting on the significance of sound and listening in making sense of the affective spheres that circulate in a transforming environment, this combined work crafts an intermedial space where the audience can sense these forces and attunements through a mode of schizophrenic listening and discern the dynamics between sounds, collective memories, and infrastructural matters to reimagine the possibilities of the counter-infrastructural acoustics where sounds of freedom attempt to retrench state violence.
Notes on Contributor
Winnie Lai is an (ethno)musicologist, multimodal artist and returning singer-songwriter working as an Andrew W. Mellon Postdoctoral Fellow in Music (2024–2026) at Dartmouth College. She earned a Ph.D. in Music Studies (Ethnomusicology) from the University of Pennsylvania in 2024. Her work crosses disciplinary and methodological boundaries by integrating ethnographic materials with historical archives and employing critical theoretical tools with cutting-edge intermedial methods. At Dartmouth, she is developing her first monograph, Unsounding Hong Kong: From Protests to Silence, to study the sonic and affective currents circulating through local and transnational protests. A Hong Kong–born and raised, classically trained mezzo-soprano (who usually sings pop), she is developing new multimodal research: Theorizing R&B Ad-libs: Intercultural Soul Aesthetics, Racialized Listening, and Singing Virtuosity in Sinophone Pop and Cantopop
Building a Green Jobs Corps for Equitable Environmental Planning in Belo Horizonte
No full textThis case study explores the creation of a Green Jobs Corps in Belo Horizonte to link climate resilience with inclusive economic development. While the city’s Local Climate Action Plan and Master Plan advance emissions reduction, sustainable mobility, and ecosystem restoration, green job training programs remain fragmented and lack strong ties to vulnerable communities. A coordinated cross-sector alliance could expand training, job placements, and accountability, turning climate action into equitable opportunity. By investing in green skills for residents of informal settlements, Belo Horizonte can strengthen adaptation, reduce inequalities, and reinforce its leadership in the global green economy
State Policy for Expanding Access to High-Demand Jobs: The Role of G3, GO Virginia, and Virginia’s Community Colleges
No full textThis ARCC Network brief examines two statewide workforce-focused initiatives, G3 and GO Virginia. The authors present a snapshot of how these initiatives interact on the ground and describe opportunities for more deliberate and strategic efforts to better align their goals and investments
Perceived racial discrimination during COVID-19 and psychological distress among East and Southeast Asian American young adults: Examining the roles of ethnic identity and social support
No full textThe COVID-19 pandemic amplified anti-Asian racism in the United States, heightening mental health risks for Asian Americans. This study examined associations between perceived racial discrimination and psychological distress—depression, anxiety, and posttraumatic stress disorder (PTSD)—and tested whether ethnic identity (exploration and commitment) and social support (family, friends) moderated these associations among East and Southeast Asian American young adults. Participants were 429 adults (ages 20–33) from Wave 4 of the COVID-19 Adult Resilience Experiences Study (February–June 2022). Validated self-report measures and moderation analyses (PROCESS in SPSS) were used.
Discrimination was positively associated with depression, anxiety, and PTSD. Ethnic identity exploration correlated with greater distress, whereas commitment was linked to lower distress. Exploration amplified the discrimination–anxiety link, highlighting the emotional toll of identity exploration in a discriminatory society. Guided by self-categorization and rejection sensitivity frameworks, individuals actively exploring ethnicity may become more attuned to racial stressors, increasing vulnerability during an inherently uncertain process. Interventions fostering critical consciousness and community connection may transform exploration into an empowering experience.
Social support from family and friends predicted lower distress overall and buffered the effects of discrimination on depression and anxiety—but more so at lower than higher discrimination levels. Under severe racial stress, interpersonal support may be insufficient, underscoring the need for systemic change. These findings call for interventions that not only bolster individual resilience but also confront structural conditions sustaining anti-Asian racism
Pedagogical Moves and Decision-Making in Undergraduate Mathematics Instruction
Get PDFTeachers require knowledge of content and pedagogy in order to do their jobs effectively. This fact has led researchers throughout the history of the study of education to create many frameworks through which we may understand teachers’ mental processes, knowledge, beliefs, and competencies. However, most of this research has focused on primary and secondary education, much less so on the undergraduate level.
This study focuses on the pedagogical moves and decision-making processes used by award-winning undergraduate mathematics instructors. Participants are four award-winning undergraduate mathematics instructors in the Northeast. I observed and interviewed each participant. Observations and interviews were audio- and video-recorded. The interview consisted of questions about why the instructor did what they were observed doing in their classroom. Observational data were analyzed using an existing protocol for undergraduate STEM classes. Interview data were transcribed and analyzed using grounded theory.
The first line of inquiry of the study is about what pedagogical moves award-winning undergraduate instructors use. The findings are that award-winning instructors use, on average, more student-centered moves and fewer teacher-centered moves than general undergraduate instructors. The second line of inquiry of the study is about the factors influencing the decision-making of award-winning undergraduate instructors. The findings here are that the participants used factors of Repositioning Student and Professor, Creating Positive Student Experiences, and Considering Future Use. The third and final line of inquiry is about the aspects of knowledge and belief being relied upon in that decision-making process.
The findings are that award-winning instructors rely on beliefs regarding improving student experiences, what will best serve students in the future, and conversation as part of the learning process. They rely on knowledge regarding students in general, their specific students, and mathematical content