Dynamic distribution of heavy metal fractions in European soils during 2009–2018: spatiotemporal modeling - Tao Hu; Min Zhou; Zirou Liu; Sybil Derrible; Mengting Wu; Chongchong Qi (Journal of Cleaner Production, 2026)

Machine learning and soil spectra enable rapid identification of multiple heavy metals at the continental scale - Chongchong Qi; Tao Hu; Mengting Wu; Ping Zhang; Sybil Derrible; Di Wang; Yong Sik Ok; Zhang Lin (Journal of Environmental Chemical Engineering, 2025)

Corrigendum to “Navigating urban complexity: The transformative role of digital twins in smart city development” [Sustainable Cities and Society 111 (2024) 105583] - Dechen Peldon; Saeed Banihashemi; Khuong Le Nguyen; Sybil Derrible (Sustainable Cities and Society, 2025)

Exploring machine learning models to predict atmospheric water harvesting with an ion deposition membrane - Giulio Barletta; Shashwata Moitra; Sybil Derrible; Alex Mathew; Anoop Muraleedharan Nair; Constantine M. Megaridis (Journal of Water Process Engineering, 2025)

Navigating urban complexity: The transformative role of digital twins in smart city development - Dechen Peldon; Saeed Banihashemi; Khuong LeNguyen; Sybil Derrible (Sustainable Cities and Society, 2024)

Determining causality in travel mode choice - Rishabh Singh Chauhan; Christoffer Riis; Shishir Adhikari; Sybil Derrible; Elena Zheleva; Charisma F. Choudhury; Francisco Câmara Pereira (Travel Behaviour and Society, 2024)

Energy-Material Cycles: A materials-based perspective of vehicle energy systems - John Mulrow; Joe F. Bozeman; Shantanu Pai; Emily Grubert; Sybil Derrible (Resources, Conservation and Recycling, 2023)

Three research priorities for just and sustainable urban systems: Now is the time to refocus - Joe F. Bozeman; Shauhrat S. Chopra; Philip James; Sajjad Muhammad; Hua Cai; Kangkang Tong; Maya Carrasquillo; Harold Rickenbacker; Destenie Nock; Weslynne Ashton; Oliver Heidrich; Sybil Derrible; et al. (Journal of Industrial Ecology, 2023)
Now is the time to refocus efforts in urban research and design. A changing climate and extreme weather events are presenting unique challenges to urban systems around the world. These challenges illuminate the social barriers that accompany disruptive events such as resource inequities and injustices. In this perspective, we provide three research priorities for just and sustainable urban systems that help to address these matters. The three research priorities are: (1) social equity and justice, (2) circularity, and (3) digital twins. Conceptual context and future research directions are provided for each. For social equity and justice, the future directions are mandatory equity analysis and inclusionary practices, understanding and reconciling historical injustices, and intentional integration with diverse community stakeholders. For circularity applications, they are better metrics for integration, more robust evaluation frameworks, and dynamic modeling at multiple spatial and temporal scales. Future directions for digital twins include developing principles to reduce complexity, integrating model and system components, and reducing barriers to data access. These research priorities are core to meeting several of the United Nations Sustainable Development Goals (i.e., 1—No Poverty, 8—Decent Work and Economic Growth, 10—Reduced Inequalities, and 11—Sustainable Cities and Communities). Useful social and technical matters are discussed throughout, where we highlight the importance of prioritizing localized research efforts, provide guidance for community‐engaged research and co‐development practices, and explain how these priorities interact to align with the evolving field of industrial ecology.

Interrelationships between electricity, gas, and water consumption in large‐scale buildings - Ali Movahedi; Sybil Derrible (Journal of Industrial Ecology, 2021)
As cities keep growing worldwide, so does the demand for key resources such as electricity, gas, and water that residents consume. Meeting the demand for these resources can be challenging and it requires an understanding of the consumption patterns. In this study, we apply extreme gradient boosting to predict and analyze electricity, gas, and water consumption in large‐scale buildings in New York City and use SHapley Additive exPlanation to interpret the results. For this, the New York City's local law 84 extensive dataset was merged with the Primary Land Use Tax Lot Output dataset as well as with other socio‐economic datasets. Specifically, we developed and validated three models: electricity, gas, and water consumption. Overall, we find that electricity, gas, and water consumptions are highly interrelated, but the interrelationships are complex and not universal. The main factor influencing these interrelationships seems to be the technology used for space and water heating (i.e., electricity vs. gas). Building type also has a large impact on interrelationships (i.e., residential vs. nonresidential), especially between electricity and water. Moreover, we also find a nonlinear relationship between gas consumption and building intensity. The main results are summarized into seven major findings. Overall, this study contributes to the urban metabolism literature that ultimately aims to gain a fundamental understanding of how energy and resources are consumed in cities.

A text mining analysis of the climate change literature in industrial ecology - Fazle Rabbi Dayeen; Abhinav S. Sharma; Sybil Derrible (Journal of Industrial Ecology, 2020)

The need to adapt sustainability audits to atypical business models - Eva Chancé; Sybil Derrible; Weslynne S. Ashton (Clean Technologies and Environmental Policy, 2018)

Industrial Symbiosis at the Facility Scale - John S. Mulrow; Sybil Derrible; Weslynne S. Ashton; Shauhrat S. Chopra (Journal of Industrial Ecology, 2017)
Summary Industrial symbiosis (IS), as a subfield of industrial ecology, is concerned with cooperation among industrial firms in managing resources, particularly by‐products, such that the waste of one firm becomes the input of another. This “closed‐loop” pattern also lies at the heart of the concept of the circular economy (CE). Both concepts are typically considered at scales ranging from industrial parks to global supply chains, but rarely at the scale of a single facility housing multiple firms. Moreover, both concepts have requirements and implications that reach beyond the tracking and coordination of material flows. These additional requirements include the cultivation of new business models and political support, as well as engagement of local communities and cultures. Thus, both IS and the CE face the challenge of bridging the gap between the technical and sociocultural aspects of industrial development and adapting to the facility scale. We address this challenge by proposing a framework for the development of facility‐scale industrial symbiosis (Facility‐IS). Facility‐IS accounts for the presence of symbiotic interfirm relationships—including, but not limited to, material and knowledge exchange—within a single physical facility. The conditions for planning, facilitating, and growing Facility‐IS are outlined, as well as three approaches to implement such projects. Overall, this research forms a Facility‐IS framework rooted in existing best practices for understanding the CE at the local scale, tracking business sustainability factors and assessing viable strategies that facilitate IS.

Robustness of road systems to extreme flooding: using elements of GIS, travel demand, and network science - Amirhassan Kermanshah; Sybil Derrible (Natural Hazards, 2017)

Complexity in Industrial Ecology: Models, Analysis, and Actions - Gerard P.J. Dijkema; Ming Xu; Sybil Derrible; Reid Lifset (Journal of Industrial Ecology, 2015)

Evolution of Public Supply Water Withdrawal in the USA: A Network Approach - Nasir Ahmad; Sybil Derrible (Journal of Industrial Ecology, 2015)
Summary Water is essential to life, and tracking trends in the withdrawal of water is paramount if we aspire to become more sustainable. Traditional statistical indicators, such as mean and standard deviation, are useful to track these trends, but they can sometimes fail to capture relevant and nontrivial properties. In this work, we first highlight the limits of these traditional statistical tools and we then offer a new network approach to study water withdrawals. Public supply water withdrawal data from the U.S. Geological Survey (USGS) for the years 1985, 1990, 1995, and 2005 were used in gallons of water per capita per day for all U.S. counties. Essentially, a network is formed between counties when they have withdrawal values within a certain range, ± ξ, of one another. A giant cluster rapidly emerges, containing more than 80% of the nodes for a ξ of 1%. The counties with the highest number of connections are associated with the mode of distribution, and we found multimodal patterns for earlier years. Moreover, the average shortest‐path length can be seen as the spread of a distribution. Overall, beyond a possible process of homogenization, water withdrawal patterns do not seem to have evolved much from 1985 to 2005, and no spatial correlation was detected. Though the methodology is yet to be formalized, it manages to give meaningful insights to supplement traditional statistical analyses.

The New Science of Cities, by MichaelBatty. Cambridge, MA, USA: MIT Press, 2013, 520 pp., ISBN 9780262019521, hardcover, $45.00. - Sybil Derrible (Journal of Industrial Ecology, 2015)