Article
Environmental Sciences
Edoardo Bertone, Benny Zuse Rousso, Dapo Kufeji
Summary: A data-driven Bayesian Network (BN) model was developed for a large Australian drinking water treatment plant, which can predict the probability of different incoming raw water quality ranges during wet weather events. The model relies on expert consultation and historical data of different types and amounts. It can be used to assess different dam water release scenarios for mitigating water quality challenges in drinking water treatment.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Environmental Sciences
Adrian Hickey, Lalantha Senevirathna
Summary: Climate change is causing more frequent extreme weather events, such as floods, droughts, and heatwaves, which are impacting water supply systems globally. Water agencies and utilities need to develop resilient and adaptable systems to cope with these challenges. Case studies, like the one on water quality and supply management in New South Wales, demonstrate the importance of effective water treatment processes and collaboration among local governments to ensure a secure and reliable water supply during extreme weather events.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Edoardo Bertone, Sara Peters Hughes
Summary: A Bayesian network-based modelling framework was proposed to predict the probability of exceeding critical thresholds for chlorophyll-a and turbidity in an Australian subtropical drinking water reservoir. The model achieved satisfactory accuracy despite limited poor water quality events in the dataset. The graphical output of the model provides an effective means for the user to evaluate predictions and uncertainty.
Article
Automation & Control Systems
Martha Arbayani Zaidan, Naser Hossein Motlagh, Pak Lun Fung, Abedalaziz S. Khalaf, Yutaka Matsumi, Aijun Ding, Sasu Tarkoma, Tuukka Petaja, Markku Kulmala, Tareq Hussein
Summary: Air quality low-cost sensors (LCSs) are affordable and scalable for high-resolution air pollution monitoring, but face challenges in accuracy, especially for extreme events. We propose a Bayesian calibration method that effectively corrects LCSs measurements and detects calibration drift. Experimental results on smoking events show accurate estimation of aerosol mass concentration. Black-box calibrators outperform white-box ones, but may drift during new events, while white-box calibrators remain robust. Implementing both calibrators enables strength extraction and drifting monitoring for calibration models. The method can be applied to other LCSs with accuracy issues.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Mathematics, Applied
Peng-Hui Yang, Yao Yu, Feng Gu, Meng-Jie Qu, Jia-Ming Zhu
Summary: This study assesses the frequency and spatiotemporal regularity of extreme weather events, establishes a joint trivariate distribution model for weather events, determines the spatial and temporal patterns using a geographically weighted regression model, and suggests adding Bayesian information to improve model accuracy. A wavelet neural network model is constructed for predicting the probability of extreme weather events throughout the Americas.
JOURNAL OF FUNCTION SPACES
(2022)
Review
Geosciences, Multidisciplinary
Xing-Yun Zou, Xin-Yu Peng, Xin-Xin Zhao, Chun-Ping Chang
Summary: The research reveals that extreme weather events have a negative impact on water quality, which persists for both the current year and the next 10 years. Floods have a greater influence on water quality than droughts, particularly in non-high-income countries and countries with low technology innovation related to water resources.
Review
Development Studies
Vinussa Rameshshanker, Sara Wyngaarden, Lincoln L. Lau, Warren Dodd
Summary: The study focuses on how health systems in the Asia-Pacific region demonstrate resilience in the face of extreme weather events. The analysis of 49 sources highlights both the strengths and weaknesses of health system activities in managing EWE risks, with a focus on countries like the Philippines, India, and Thailand.
CLIMATE AND DEVELOPMENT
(2021)
Article
Geosciences, Multidisciplinary
Jonathan M. Frame, Frederik Kratzert, Daniel Klotz, Martin Gauch, Guy Shalev, Oren Gilon, Logan M. Qualls, Hoshin Gupta, Grey S. Nearing
Summary: The most accurate rainfall-runoff predictions are currently based on deep learning, but there is concern about their reliability in predicting extreme events. This study used LSTM networks and a mass-conserving LSTM variant to test this hypothesis, and found that these models remained relatively accurate in predicting extreme events compared to traditional models.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Medicine, General & Internal
Erik Haapatalo, Elina Reponen, Paulus Torkki
Summary: Implementing Kaizen in healthcare can improve productivity, but maintaining long-term results is challenging. This study analyzed Kaizen events in a large academic hospital system in Finland and identified 15 factors that explain the persistence or decline of long-term results. Factors such as work culture and motivation for continuous improvement were found to be important for sustaining results, while lack of time and high workload hindered performance improvements.
Article
Engineering, Environmental
Sanaz Moghim, Ali Takallou
Summary: This study uses different schemes in the Weather Research and Forecasting (WRF) model to simulate heavy rainfall events and Cyclone Sidr in Bangladesh. The results show that the WRF model can accurately predict the cyclone track, intensity, and landfall position. Additionally, a probabilistic framework and proper indices based on distributions are used to evaluate hazards and uncertainties.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2023)
Article
Multidisciplinary Sciences
Aidin Jabbari, Josef D. Ackerman, Leon Boegman, Yingming Zhao
Summary: Climate change leads to increasing surface-water temperature and wave power in the Laurentian Great Lakes, which are influenced by atmospheric phenomena. The interbasin coupling in Lake Erie is predicted by analyzing wave power patterns in response to extreme winds, causing the upwelling of hypolimnetic water with high total phosphorus concentration. This interbasin exchange has led to a rise in hypoxic events in the western basin, affecting the water quality of the Great Lakes and fisheries.
SCIENTIFIC REPORTS
(2021)
Article
Medicine, General & Internal
Heiko Brennenstuhl, Manuel Will, Elias Ries, Konstantin Mechler, Sven Garbade, Markus Ries
Summary: The study found that while cold waves were the most frequent events recorded in EM-DAT, heat waves were responsible for the vast majority of temperature-related deaths. The most severe heat waves occurred in various European countries, with a total of 135089 deaths across five major events. The findings suggest the importance of addressing resiliency and vulnerability in at-risk populations and age groups to better protect public health.
Article
Multidisciplinary Sciences
Hassan Anjileli, Laurie S. Huning, Hamed Moftakhari, Samaneh Ashraf, Ata Akbari Asanjan, Hamid Norouzi, Amir AghaKouchak
Summary: The increasing frequency and severity of heatwaves due to climate change have led to significant impacts on the terrestrial biosphere. Studies have shown that during heatwaves, soil respiration rates increase by approximately 26% on average. Failure to capture these high frequency extreme heatwave events may underestimate the terrestrial feedback to the carbon cycle.
SCIENTIFIC REPORTS
(2021)
Article
Environmental Sciences
Quanliang Chen, Yujing Liao, Xin Zhou, Ting Duan, Xiaotian Xue, Ziqi Zhang, Dandan Dong, Wuhu Feng
Summary: The impact of El Nino on the moisture in the tropical lower stratosphere has been extensively studied. The unprecedented hydration during the extreme El Nino in 2015/2016 provides an opportunity to distinguish the response of water vapor to extreme and moderate El Nino events.
Article
Engineering, Mechanical
S. Dinesh Vijay, K. Thamilmaran, A. Ishaq Ahamed
Summary: In this paper, we investigate extreme events in a second-order nonautonomous nonlinear dynamical system based on a memristor, which exhibits nonhyperbolic chaos, abnormal amplitude oscillations, and multistability.
NONLINEAR DYNAMICS
(2023)
Article
Green & Sustainable Science & Technology
Jayden Hyman, Rodney A. Stewart, Oz Sahin, Michael Clarke, Malcolm R. Clark
Summary: This study identifies the drivers, barriers, and enablers to deep-sea polymetallic nodule mining and develops an environmental management framework to support good industry practice and guide future research.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Engineering, Multidisciplinary
Ben Herring, Tony Sharp, Tim Roberts, Jarred Fastier-Wooller, Greg Kelly, Oz Sahin, David Thiel, Dzung Dao, Peter L. Woodfield
Summary: The paper focuses on the feasibility and survivability of an underground LoRaWAN bushfire temperature sensing node, and experimentally demonstrates its durability under a fire.
Article
Green & Sustainable Science & Technology
M. Alipour, Elnaz Irannezhad, Rodney A. Stewart, Oz Sahin
Summary: This study examines the adoption decisions of home batteries and PV systems in South East Queensland, Australia. The findings indicate that early and late adopters of PV, as well as non-adopters, have similar sociodemographic attributes, while battery users represent the characteristics of innovators. Lower electricity bills and interest in the system are critical factors in PV adoption, while system cost is the main barrier. Financial factors drive battery adoption, but non-economic factors play a larger role for those who have already adopted the storage system.
Article
Energy & Fuels
Mohammad Alipour, Firouzeh Taghikhah, Elnaz Irannezhad, Rodney A. Stewart, Oz Sahin
Summary: This study explores the relationship between the acceptance of residential rooftop solar PV systems and the adoption of home battery energy storage systems. It finds that the past behavior of PV systems can influence the decision to adopt battery systems, leading to attitudinal changes such as regret or despair. The study also suggests that perceived attitudes towards financial and nonfinancial benefits play a key role in attitude change. Failure to recognize these dynamics may lead to late adoption or rejection of battery systems.
Article
Environmental Sciences
Liam Vaughan, Muyang Zhang, Haoran Gu, Joan B. Rose, Colleen C. Naughton, Gertjan Medema, Vajra Allan, Anne Roiko, Linda Blackall, Arash Zamyadi
Summary: Wastewater-based epidemiology (WBE) is a useful tool for public health monitoring and early warnings of outbreaks. This study explored the challenges of using machine learning for WBE analysis and COVID-19 forecasting. Random Forest (RF) algorithms were used on WBE datasets from different regions, and the forecasting performance was evaluated. The study found that RF performed poorly in some regions but had stronger performance in others, with factors such as sampling frequency and training set size affecting accuracy.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Editorial Material
Green & Sustainable Science & Technology
Oz Sahin, Edoardo Bertone
Editorial Material
Public, Environmental & Occupational Health
Jane Taylor, Anne Roiko, Leanne Coombe, Susan Devine, John Oldroyd, Jonathan Hallett, Zoe Murray, Francis Nona, Condy Canuto, Dionne Amato Ali, Gemma Crawford, Tracy Gurnett
AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH
(2023)
Article
Multidisciplinary Sciences
Joanne K. Garrett, Mathew P. White, Lewis R. Elliott, James Grellier, Simon Bell, Gregory N. Bratman, Theo Economou, Mireia Gascon, Mare Lohmus, Mark Nieuwenhuijsen, Ann Ojala, Anne Roiko, Matilda van den Bosch, Catharine Ward Thompson, Lora E. Fleming
Summary: This study tested a conceptual model integrating mental health with ecosystem services by analyzing data on subjective mental well-being from an 18-country survey. The results showed that subjective mental well-being outcomes were dependent upon a complex interplay of environmental type and quality, visit characteristics, and individual factors. These findings have implications for public health and environmental management, as they can help identify factors that may impact well-being and recreational demand on fragile aquatic ecosystems.
SCIENTIFIC REPORTS
(2023)
Review
Green & Sustainable Science & Technology
Madeleine Hohenhaus, Jennifer Boddy, Shannon Rutherford, Anne Roiko, Natasha Hennessey
Summary: Young people are increasingly involved in programs promoting climate action and sustainability. A scoping review was conducted to understand the nature of these programs and their successes. The review found that external factors such as the social environment, place, knowledge, leadership, and goal setting development contribute to behavior change in young people, along with internal factors like self-efficacy, identity, agency, and action competence, as well as systems thinking. Learning from these programs is crucial for improving the capabilities of young people to respond to the climate challenge.
Article
Environmental Sciences
Lewis R. Elliott, Tytti Pasanen, Mathew P. White, Benedict W. Wheeler, James Grellier, Marta Cirach, Gregory N. Bratman, Matilda van den Bosch, Anne Roiko, Ann Ojala, Mark Nieuwenhuijsen, Lora E. Fleming
Summary: The role of neighbourhood nature in promoting good health is recognised, but there is a lack of consistent evidence for the mechanisms. This study used international survey data to examine the pathways linking different types of neighbourhood nature with general health. The results show that the linkages operate primarily through recreational contact with natural environments, emphasizing the importance of supporting the use of local green/blue spaces for health promotion and disease prevention.
ENVIRONMENT INTERNATIONAL
(2023)
Article
Green & Sustainable Science & Technology
Edoardo Bertone, Sara Peters Hughes
Summary: A Bayesian network-based modelling framework was proposed to predict the probability of exceeding critical thresholds for chlorophyll-a and turbidity in an Australian subtropical drinking water reservoir. The model achieved satisfactory accuracy despite limited poor water quality events in the dataset. The graphical output of the model provides an effective means for the user to evaluate predictions and uncertainty.
Review
Public, Environmental & Occupational Health
Katharina Nieberler-Walker, Cheryl Desha, Caryl Bosman, Anne Roiko, Savindi Caldera
Summary: This review examines the role of purposefully designed and well-integrated therapeutic hospital gardens (THGs) in improving the well-being of patients, their families, and staff. Through a thorough analysis of literature and synthesis of current thinking, the authors establish a working definition of THGs to guide stakeholders in implementing health promoting gardens.
HERD-HEALTH ENVIRONMENTS RESEARCH & DESIGN JOURNAL
(2023)
Article
Ecology
Yongbo Liu, Anne Cleary, Kelly S. Fielding, Zoe Murray, Anne Roiko
Summary: This study examines the mediation effects of nature contact on the relationship between nature connection and wellbeing, and between nature connection and pro-environmental behaviours. The results showed that nature contact accounts for a significant portion of the positive association between nature connection and wellbeing, as well as between nature connection and pro-environmental behaviour.
LANDSCAPE AND URBAN PLANNING
(2022)
Article
Ecology
Angela J. Dean, Helen Ross, Anne Roiko, Kelly S. Fielding, Emily Saeck, Kim Johnston, Amanda Beatson, James Udy, Paul Maxwell
Summary: The utilization patterns of blue space are influenced by subjective perceptions and environmental constraints. A survey conducted in South East Queensland identified three frequent users and two low users of blue spaces. Proximity to coastal areas and the availability of diverse activities were found to support frequent use, while increased distance from the coast limited use.
LANDSCAPE AND URBAN PLANNING
(2022)
Article
Management
Emiliya Suprun, Oz Sahin, Rodney Anthony Stewart, Kriengsak Panuwatwanich
Summary: This study examined different scenarios and policy interventions for the construction innovation system in Russia, and provided policy recommendations for enhancing innovativeness in the industry.
INTERNATIONAL JOURNAL OF CONSTRUCTION MANAGEMENT
(2022)
Article
Green & Sustainable Science & Technology
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION
(2024)