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457 results on '"Chalabi, Zaid"'

14. Estimating the Health Effects of Greenhouse Gas Mitigation Strategies: Addressing Parametric, Model, and Valuation Challenges

Author

Remais, Justin V, Hess, Jeremy J, Ebi, Kristie L, Markandya, Anil, Balbus, John M, Wilkinson, Paul, Haines, Andy, and Chalabi, Zaid

Subjects
Biomedical and Clinical Sciences, Environmental Sciences, Health Sciences, Climate Action, Climate Change, Environmental Monitoring, Greenhouse Effect, Humans, Models, Theoretical, Medical and Health Sciences, Toxicology, Biomedical and clinical sciences, Environmental sciences, Health sciences
Abstract

BackgroundPolicy decisions regarding climate change mitigation are increasingly incorporating the beneficial and adverse health impacts of greenhouse gas emission reduction strategies. Studies of such co-benefits and co-harms involve modeling approaches requiring a range of analytic decisions that affect the model output.ObjectiveOur objective was to assess analytic decisions regarding model framework, structure, choice of parameters, and handling of uncertainty when modeling health co-benefits, and to make recommendations for improvements that could increase policy uptake.MethodsWe describe the assumptions and analytic decisions underlying models of mitigation co-benefits, examining their effects on modeling outputs, and consider tools for quantifying uncertainty.DiscussionThere is considerable variation in approaches to valuation metrics, discounting methods, uncertainty characterization and propagation, and assessment of low-probability/high-impact events. There is also variable inclusion of adverse impacts of mitigation policies, and limited extension of modeling domains to include implementation considerations. Going forward, co-benefits modeling efforts should be carried out in collaboration with policy makers; these efforts should include the full range of positive and negative impacts and critical uncertainties, as well as a range of discount rates, and should explicitly characterize uncertainty. We make recommendations to improve the rigor and consistency of modeling of health co-benefits.ConclusionModeling health co-benefits requires systematic consideration of the suitability of model assumptions, of what should be included and excluded from the model framework, and how uncertainty should be treated. Increased attention to these and other analytic decisions has the potential to increase the policy relevance and application of co-benefits modeling studies, potentially helping policy makers to maximize mitigation potential while simultaneously improving health.

Published
2014

26. A multistakeholder participatory Life Cycle Sustainability Assessment framework for the options appraisal of social housing regeneration schemes.

Author

Nava, Sahar, Chalabi, Zaid, Bell, Sarah, and Burman, Esfandiar

Subjects
PRODUCT life cycle assessment, SUSTAINABILITY, ENVIRONMENTAL impact analysis, MULTIPLE criteria decision making, PHYSICAL sciences
Abstract

We propose a simple MCDA approach for a panel-based weight elicitation of selected indicators and evaluation of the results of the LCIA studies. How Multi-Criteria Decision Analysis (MCDA) is aiding Life Cycle Assessment (LCA) in results interpretation. To enable sustainable growth in housing provision, the socioeconomic impacts of social housing regeneration schemes alongside their life cycle environmental impacts should be assessed. [Extracted from the article]

Published
2023
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30. Dynamic visualizations for violence prevention

Author

Demarest, Luke, McAlpine, Alys, Chalabi, Zaid, Kiss, Ligia, Demarest, Luke, McAlpine, Alys, Chalabi, Zaid, and Kiss, Ligia

Abstract

This poster documents the use of dynamic visualizations and data interfaces for an ongoing complex systems-based violence prevention intervention case study. The scope of project visualizations used span the development, implementation, and evaluation of a social simulation that models a ‘safer migration’ intervention in the context of low-wage labor migration between Myanmar and Thailand. This project employed dynamic visualizations at various stages, including, participatory social network data collection, mixed-methods social network analysis, conceptualization of violence and migration systems theory, generating and analyzing system and intervention simulations using agent-based modelling, and disseminating web-accessible outputs and findings for a wide audience. Preliminary findings from this ongoing work suggest that using dynamic visual representations of complex systems as a research tool can lead to more pluralistic and interdisciplinary methodological approaches to knowledge production in the field of violence intervention research. Dynamic visualizations can serve as a conduit for empirical richness, a touchpoint for interdisciplinary collaboration, a visual check for model verification, and a supporting tool to assist with stakeholder validation of causal inference, and an instrument to inform intervention development through scenario testing.

Published
2022

35. An Inquiry into Model Validity When Addressing Complex Sustainability Challenges

Author

Scrieciu, Şerban, Varga, Liz, Zimmermann, Nici, Chalabi, Zaid, Freeman, Rachel, Dolan, Tom, Borisoglebsky, Dmitry E., and Davies, Mike

Subjects
Article Subject
Abstract

Scientific modelling is a prime means to generate understanding and provide much-needed information to support public decision-making in the fluid area of sustainability. A growing, diverse sustainability modelling literature, however, does not readily lend itself to standard validation procedures, which are typically rooted in the positivist principles of empirical verification and predictive success. Yet, to be useful to decision-makers, models, including their outputs and the processes through which they are established must be, and must be seen to be “valid.” This study explores what model validity means in a problem space with increasingly interlinked and fast-moving challenges. We examine validation perspectives through ontological, epistemic, and methodological lenses, for a range of modelling approaches that can be considered as “complexity-compatible.” The worldview taken in complexity-compatible modelling departs from the more standard modelling assumptions of complete objectivity and full predictability. Drawing on different insights from complexity science, systems thinking, economics, and mathematics, we suggest a ten-dimensional framework for progressing on model validity when investigating sustainability concerns. As such, we develop a widened view of the meaning of model validity for sustainability. It includes (i) acknowledging that several facets of validation are critical for the successful modelling of the sustainability of complex systems; (ii) tackling the thorny issues of uncertainty, subjectivity, and unpredictability; (iii) exploring the realism of model assumptions and mechanisms; (iv) embracing the role of stakeholder engagement and scrutiny throughout the modelling process; and (v) considering model purpose when assessing model validity. We wish to widen the debate on the meaning of model validity in a constructive way. We conclude that consideration of all these elements is necessary to enable sustainability models to support, more effectively, decision-making for complex interdependent systems.

Published
2022
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46. Use of an agent-based model to explore urban transitions in commuter cycling

Author

Abbas, SMA, Aldred, Rachel, Chalabi, Zaid, and Woodcock, James

Subjects
Agent-based model, Social simulation, Commuter cycling, Computational social science
Abstract

Encouraging a cycling culture while reducing car usage can lead to substantial health and environmental benefits. In this exploratory work, we use an agent-based model of commuter cycling focusing on the emergence of social norms due to interactions between agents and their environment (including their social networks). The overall goal is to develop an understanding of change and continuity in cycle commuting, and how this is shaped by dynamic relationships between social expectations and individual attributes. Initial characteristics of agents and the distribution of cycling in the population come from the Census and secondary quantitative data. The theoretical basis of our work comes from qualitative studies on cycling and from 'Theories of Practice', which see practices as enrolling individuals, depending on whether they have the material and cultural resources required to participate. Thus, rather than treating humans as rational individuals who, for example, follow the precepts of utility maximization, we explore how changes in norms surrounding cycling practices (such as social expectations around clothing and accessories) shape uptake, and how uptake then affects social norms relating to cycling., We test policies for increasing cycling usage based on provision of cycling stuff and improvements to the environment.

Published
2021

47. Catastrophic Health Impacts of Spiraling Climate Change: How Certain Can We Be About Their Magnitudes?

Author

Chalabi, Zaid and Foss, Anna M

Abstract

Recently, there has been a strong interest in the climate emergency and the human health impacts of climate change. Although estimates have been quoted, the modeling methods used have either been simplistic or opaque, making it difficult for policy makers to have confidence in these estimates. Providing central estimates of health impacts, without any quantification of their uncertainty, is deficient because such an approach does not acknowledge the inherent uncertainty in extreme environmental exposures associated with spiraling climate change and related health impacts. Furthermore, presenting only the uncertainty bounds around central estimates, without information on how the uncertainty in each of the model parameters and assumptions contribute to the total uncertainty, is insufficient because this approach hides those parameters and assumptions which contribute most to the total uncertainty. We propose a framework for calculating the catastrophic human health impacts of spiraling climate change and the associated uncertainties. Our framework comprises three building blocks: (A) a climate model to simulate the environmental exposure extremes of spiraling climate change; (B) a health impact model which estimates the health burdens of the extremes of environmental exposures; and (C) an analytical mathematical method which characterizes the uncertainty in (A) and (B), propagates the uncertainty in-between and through these models, and attributes the proportion of uncertainty in the health outcomes to model assumptions and parameter values. Once applied, our framework can be of significant value to policy makers because it handles uncertainty transparently while taking into account the complex interactions between climate and human health.

Published
2020

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