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Machine learning based climate projections for sustainable potato production in Prince Edward Island
No full textPrince Edward Island (PEI) is the largest potato-producing province in Canada, and most of its croplands are rainfed. Climate change impacts all fields of life, including agriculture. Thus, there is a need to understand better the historical variations and future projections of climate change and its patterns for PEI. Climate change and its impacts on potato tuber yield have been evaluated in this thesis under three objectives. For the first objective, twenty climate extreme indices were computed with the help of ClimPACT2 software for 30 years (1989-2018) to assess their impacts on the potato tuber yield.
The average of daily mean temperature, mean daily minimum temperature (TNm), and the occurrence of continuous dry days (CDD) significantly increased, while daily temperature range (DTR), frost days, cold days, cold nights, and warmest days (TXx) showed decreasing trends during the potato growing seasons (May-October) for the past three decades. The principal component analysis results showed that DTR, TXx, CDD, and TNm were the main indices, defining ~39% variations in tuber yield. However, DTR, TXx, CDD, and TNm individual contributions to the variations in tuber yield were recorded to be 21, 19, 16, and 4%, respectively. For the second objective, the Hargreaves method was used to calculate reference evapotranspiration (ET0) for western, central, and eastern parts of PEI using their two input parameters: daily maximum temperature (Tmax) and daily minimum temperature (Tmin). The Tmax and Tmin from the Canadian Earth System Model Second Generation (CanESM2) were downscaled with the help of statistical downscaling model (SDSM) for three future periods, i.e., the 2020s (2011-2040), 2050s (2041-2070), and 2080s (2071-2100) under three representative concentration pathways (RCP’s) including RCP2.6, 4.5, and 8.5. Temporally, there were major changes in Tmax, Tmin, and ET0 for the 2080s under RCP8.5. In the next steps, a one-dimensional convolutional neural network (1D-CNN), long-short term memory (LSTM), and multilayer perceptron (MLP) were used for estimating ET0 for historical and future periods. High coefficient of correlation (r > 0.95) values for both calibration and validation periods showed the potential of the artificial neural networks in ET0 estimation. For the third objective, SDSM, MLP, random forest (RF), and support vector regression (SVR) were used to downscale Tmax, Tmin, and precipitation at eight meteorological stations located in PEI. The comparison results depicted the better performance of MLP to downscale the climatic parameters (Tmax, Tmin, and precipitation). Therefore, the MLP algorithm was used to project the climatic parameters for the future period (2006-2100) under RCP2.6, 4.5, and 8.5. The linear scaling method was used to reduce the biases in the projected data and get real results. The results of the analysis of the data from the annual and the growing season showed that Tmax and Tmin continually increased in the future under all the RCPs, but maximum increment was noticed under RCP8.5. The spatial patterns of average annual precipitation in the growing season showed high, moderate, and low precipitation at the PEI’s eastern, central, and western parts for the historical (1976-2003) and future periods. This study will help the decision-makers and farmers to understand better the variations and patterns of the climatic parameters for the historical and future periods in relation to agriculture. The results may also help to develop irrigation scheduling in response to climate change to meet sustainable development goals
Environmental systems modelling and analysis under changing conditions
No full textEnvironmental systems models are essential for understanding the dynamics and mechanisms of various environmental issues (e.g., air pollution, water pollution, floods, droughts, and climate change). Most importantly, they are widely used to predict future outcomes of environmental systems in support of effective decision making and policy development. However, most of the models are based on a stationary condition which by default assumes that no significant changes will occur in the future. It has been reported frequently in recent years that such a stationary assumption no longer holds in the context of global climate change and intensive human activities. Many boundary conditions and internal parameters in these models have been changed over time, which leads to considerable uncertainty in future prediction. Therefore, addressing the changing conditions in the process of environmental system modelling and analysis is becoming one of the most challenging issues in the field.
This special issue aims to collect recent advances in methodologies, models, tools, and applications for environmental systems modelling and analysis under changing and/or uncertain conditions, such as increasing temperature, changing precipitation patterns, sea-level rise, land cover/use change, urbanization, and policy changes. In this special issue, we have published 6 papers which involve a variety of modelling approaches to address the changing and uncertain conditions in environmental systems. A brief introduction for each paper is provided as follows.
The paper entitled “Dynamic Evolution of Public’s Positive Emotions and Risk Perception for the COVID-19 Pandemic: A Case Study of Hubei Province of China” by Zhang et al. investigates how the COVID-19 dynamic situation affects the public’s risk perception and emotions. The social risk amplification framework is first used as the theoretical basis to collect and analyze the COVID-19 data in Hubei Province, China from January 20, 2020, to April 8, 2020. The autoregressive integrated moving average based time-series prediction model is then adopted to analyze the dynamic evolution and fluctuation trends of public positive emotion and risk perception during the initial development of the pandemic. The methodological framework introduced in this study can be potentially used for understanding the rapid and dynamic evolution of public emotion and risk perception in similar catastrophic and uncertain situations.
The paper entitled “Ecosystem-Based Adaptation for the Impact of Climate Change and Variation in the Water Management Sector of Sri Lanka” by Khaniya et al. aims to showcase the effectiveness and benefits of utilizing the ecosystem-based adaptation approach to help protect the water sector in Sri Lanka from the changing climate. In particular, a wide range of benefits in water supply regulation, water quality regulation, and moderation of extreme events have been identified through the implementation of ecosystem-based adaptation approach in the water management sector in Sri Lanka. This case study for Sri Lanka can provide an important scientific reference for other nations around the world to develop adaptative water management measures in the context of climate change.
The paper entitled “A Study on Evaluating Water Resources System Vulnerability by Reinforced Ordered Weighted Averaging Operator” by Suo et al. proposes a reinforced ordered weighted averaging operator by incorporating the extended ordered weighted average operator and principal component analysis into a multicriteria decision analysis framework. The proposed method is applied for assessing the vulnerability of a water resources system in Handan, China, in order to demonstrate its effectiveness in solving multicriteria decision analysis problems in environmental systems which usually involve multiple indictors and different weights.
The paper entitled “A Birandom Chance-Constrained Linear Programming Model for CCHP System Operation Management: A Case Study of Hotel in Shanghai, China” by Bao et al. proposes a birandom chance-constrained linear programming (BCCLP) model to help identify the optimal operation strategies for the combined cooling, heating, and power (CCHP) system under random uncertainties. The effectiveness of the proposed BCCLP model in handling the random uncertainties associated with the operation management of energy systems is demonstrated through a case study for a hotel-based gas-fired CCHP system in Shanghai, China.
The paper entitled “Pricing Decisions in Closed-Loop Supply Chains with Competitive Fairness-Concerned Collectors” by Shu et al. proposes a fairness concern utility system to help address the pricing issues in a closed-loop supply chain with one manufacturer, one retailer, and two competitive collectors. The influence of competitive strength and the degree of fairness-concerned collectors on the pricing decisions are studied through one centralized and four decentralized models. The methodological framework proposed in this study can be potentially used to help gain some managerial insights into the pricing decisions in environmental systems.
The paper entitled “An Inexact Inventory Theory-Based Water Resources Distribution Model for Yuecheng Reservoir, China” by Suo et al. proposes an inexact inventory theory-based water resources distribution model to help optimize the water allocation management practices. The proposed model integrates the techniques of inventory model, inexact two-stage stochastic programming, and interval-fuzzy mathematics programming into a general modelling framework to deal with multiple uncertainties and policy scenarios related to reservoir-based water allocation issues. A case study for the Yuecheng Reservoir in the Zhanghe River Basin, China, is conducted to demonstrate the effectiveness of the proposed model.
We hope that the readers will find this special issue interesting and the published papers will stimulate further research advancement in environmental systems modelling and analysis under changing and uncertain conditions
Contextual factors and mechanisms that influence sustainability: A realist evaluation of two scaled, multi-component interventions
No full textBackground
In 2012, Alberta Health Services created Strategic Clinical NetworksTM (SCNs) to develop and implement evidence-informed, clinician-led and team-delivered health system improvement in Alberta, Canada. SCNs have had several provincial successes in improving health outcomes. Little research has been done on the sustainability of these evidence-based implementation efforts.
Methods
We conducted a qualitative realist evaluation using a case study approach to identify and explain the contextual factors and mechanisms perceived to influence the sustainability of two provincial SCN evidence-based interventions, a delirium intervention for Critical Care and an Appropriate Use of Antipsychotics (AUA) intervention for Senior’s Health. The context (C) + mechanism (M) = outcome (O) configurations (CMOcs) heuristic guided our research.
Results
We conducted thirty realist interviews in two cases and found four important strategies that facilitated sustainability: Learning collaboratives, audit & feedback, the informal leadership role, and patient stories. These strategies triggered certain mechanisms such as sense-making, understanding value and impact of the intervention, empowerment, and motivation that increased the likelihood of sustainability. For example, informal leaders were often hands-on and influential to front-line staff. Learning collaboratives broke down professional and organizational silos and encouraged collective sharing and learning, motivating participants to continue with the intervention. Continual audit-feedback interventions motivated participants to want to perform and improve on a long-term basis, increasing the likelihood of sustainability of the two multi-component interventions. Patient stories demonstrated the interventions’ impact on patient outcomes, motivating staff to want to continue doing the intervention, and increasing the likelihood of its sustainability.
Conclusions
This research contributes to the field of implementation science, providing evidence on key strategies for sustainability and the underlying causal mechanisms of these strategies that increases the likelihood of sustainability. Identifying causal mechanisms provides evidence on the processes by which implementation strategies operate and lead to sustainability. Future work is needed to evaluate the impact of informal leadership, learning collaboratives, audit-feedback, and patient stories as strategies for sustainability, to generate better guidance on planning sustainable improvements with long term impact.Alberta Health ServicesStrategic Clinical Networks
Long-term projection of water cycle changes over China using RegCM
No full textThe global water cycle is becoming more intense in a warming climate, leading to extreme rainstorms and floods. In addition, the delicate balance of precipitation, evapotranspiration, and runoff affects the variations in soil moisture, which is of vital importance to agriculture. A systematic examination of climate change impacts on these variables may help provide scientific foundations for the design of relevant adaptation and mitigation measures. In this study, long-term variations in the water cycle over China are explored using the Regional Climate Model system (RegCM) developed by the International Centre for Theoretical Physics. Model performance is validated through comparing the simulation results with remote sensing data and gridded observations. The results show that RegCM can reasonably capture the spatial and seasonal variations in three dominant variables for the water cycle (i.e., precipitation, evapotranspiration, and runoff). Long-term projections of these three variables are developed by driving RegCM with boundary conditions of the Geophysical Fluid Dynamics Laboratory Earth System Model under the Representative Concentration Pathways (RCPs). The results show that increased annual average precipitation and evapotranspiration can be found in most parts of the domain, while a smaller part of the domain is projected with increased runoff. Statistically significant increasing trends (at a significant level of 0.05) can be detected for annual precipitation and evapotranspiration, which are 0.02 and 0.01 mm/day per decade, respectively, under RCP4.5 and are both 0.03 mm/day per decade under RCP8.5. There is no significant trend in future annual runoff anomalies. The variations in the three variables mainly occur in the wet season, in which precipitation and evapotranspiration increase and runoff decreases. The projected changes in precipitation minus evapotranspiration are larger than those in runoff, implying a possible decrease in soil moisture.Natural Sciences and Engineering Research CouncilNational Natural Science Foundation of ChinaNational Key Research and Development Program of Chin
Children's folklore in the academic library: Reorganization for context and collection management
No full textTraditional literature (including folk tales, fairy tales, and fables) is valued in academic children's literature collections for its value in both direct use (real or hypothetical) with children and the historical, cultural, and anthropological study of folklore. The “timeless” feel of these works, along with their distinctively liminal place between fiction and nonfiction, can lead them to be perceived as indefinitely useful, even beyond their unusually long standard retention period. Nevertheless, in a non-archival academic children’s literature collection, routine assessment of traditional literature is necessary and even valuable. This article situates traditional literature in the context of children’s literature and its academic study, then describes how the children’s folklore collection in one academic library was bifurcated to improve access, browsing ability, context, and use of shelf space. Considerations, including thoughts on developing assessment and weeding criteria, are spelled out for collections considering a similar undertaking
Analyses of contact networks of community dogs on a university campus in Nakhon Pathom, Thailand
No full textFree-roaming dogs have been identified as an important reservoir of rabies in many countries including Thailand. There is a need for novel insights to improve current rabies control strategies in these countries. Network analysis is commonly used to study the interactions between individuals or organizations and has been applied in preventive veterinary medicine. However, contact networks of domestic free-roaming dogs are mostly unexplored. The objective of this study was to explore the contact network of free-roaming dogs residing on a university campus. Three one-mode networks were created using co-appearances of dogs as edges. A two-mode network was created by associating the dog with the pre-defined area it was seen in. The average number of contacts a dog had was 6.74. The normalized degree for the weekend network was significantly higher compared to the weekday network. All one-mode networks displayed small-world network characteristics. Most dogs were observed in only one area. The average number of dogs which shared an area was 8.67. In this study, we demonstrated the potential of observational methods to create networks of contacts. The network information acquired can be further used in network modeling and designing targeted disease control programs
Advanced Heat Transfer
No full textThe book provides a valuable source of technical content for the prediction and analysis of advanced heat transfer problems, including conduction, convection, radiation, phase change, and chemically reactive modes of heat transfer. With more than 20 new sections, case studies, and examples, the Third Edition broadens the scope of thermal engineering applications, including but not limited to biomedical, micro- and nanotechnology, and machine learning. The book features a chapter devoted to each mode of multiphase heat transfer. FEATURES Covers the analysis and design of advanced thermal engineering systems Presents solution methods that can be applied to complex systems such as semi-analytical, machine learning, and numerical methods Includes a chapter devoted to each mode of multiphase heat transfer, including boiling, condensation, solidification, and melting Explains processes and governing equations of multiphase flows with droplets and particles Applies entropy and the second law of thermodynmaics for the design and optimization of thermal engineering systems
Exergo‐economic assessment by a specific exergy costing method for an experimental thermochemical hydrogen production system
No full textIn this article, an exergo-economic study of an experimental lab-scale integrated copper-chlorine (Cu-Cl) cycle of hydrogen production is conducted. The analysis is performed based on a specific exergy costing (SPECO) method to determine the influences of various design criteria on the costs and then identify possible improvements for more cost effective approaches. The article includes an exergy analysis, economic study, exergy costing and exergo-economic evaluation. Also, a scale-up analysis is performed to predict the cost of a larger scale facility of 1000 kg per day of hydrogen production. The results of the exergo-economic and scale-up analysis are expected to assist in the design, optimization and improvement of a scaled-up Cu-Cl thermochemical cycle. Furthermore, the results of this study show that for a large-scale Cu-Cl cycle plant with a capacity of 1000 kg/day H2, the cost of hydrogen production, excluding the treatment of side reactions, is predicted at about 3.91 $/kg H2
Genetic diversity of the cardiopulmonary canid nematode Angiostrongylus vasorum within and between rural and urban fox populations
No full textAngiostrongylus vasorum is an emerging parasitic cardiopulmonary nematode of dogs, foxes, and other canids. In dogs, the infection causes respiratory and bleeding disorders along with other clinical signs collectively known as canine angiostrongylosis, while foxes represent an important wildlife reservoir. Despite the spread of A. vasorum across various countries in Europe and the Americas, little is known about the genetic diversity of A. vasorum populations at a local level in a highly endemic area. Thus, in the present study, we investigated the genetic diversity of 323 adult A. vasorum nematodes from 64 foxes living in the canton of Zurich, Switzerland. Among those, 279 worms isolated from 20 foxes were analyzed separately to investigate the genetic diversity of multiple worms within individual foxes. Part of the mitochondrial cytochrome c oxidase subunit I (mtCOI) gene was amplified and sequenced. Overall, 16 mitochondrial haplotypes were identified. The analysis of multiple worms per host revealed 12 haplotypes, with up to 5 different haplotypes in single individuals. Higher haplotype diversity (n = 10) of nematodes from foxes of urban areas than in rural areas (n = 7) was observed, with 5 shared haplotypes. Comparing our data with published GenBank sequences, five haplotypes were found to be unique within the Zurich nematode population. Interestingly, A. vasorum nematodes obtained from foxes in London and Zurich shared the same dominating haplotype. Further studies are needed to clarify if this haplotype has a different pathogenicity that may contribute to its dominance. Our findings show the importance of foxes as a reservoir for genetic parasite recombination and indicate that high fox population densities in urban areas with small and overlapping home ranges allow multiple infection events that lead to high genetic variability of A. vasorum.Bayer Animal Health GmbH, Leverkusen, German