Adapting COVID-19 Contact Tracing Protocols to Accommodate Resource Constraints, Philadelphia, Pennsylvania, USA, 2021.

Because of constrained personnel time, the Philadelphia Department of Public Health (Philadelphia, PA, USA) adjusted its COVID-19 contact tracing protocol in summer 2021 by prioritizing recent cases and limiting staff time per case. This action reduced required staff hours to prevent each case from 21-30 to 8-11 hours, while maintaining program effectiveness.

Smoothing the Phosphorus Resource Stress under the Socioeconomic Development in China.

Phosphorus (P) is the key in maintaining food security and ecosystem functions. Population growth and economic development have increased the demand for phosphate rocks. China has gradually developed from zero phosphate mining to the world's leading P miner, fertilizer, and agricultural producer since 1949. China released policies, such as designating phosphate rock as a strategic resource, promoting eco-agricultural policies, and encouraging the use of solid wastes produced in mining and the phosphorus chemical industry as construction materials. However, methodological and data gaps remain in the mapping of the long-term effects of policies on P resource efficiency. Here, P resource efficiency can be represented by the potential of the P cycle to concentrate or dilute P as assessed by substance flow analysis (SFA) complemented by statistical entropy analysis (SEA). P-flow quantification over the past 70 years in China revealed that both resource utilization and waste generation peaked around 2015, with 20 and 11 Mt of mined and wasted P, respectively. Additionally, rapidly increasing aquaculture wastewater has exacerbated pollution. The resource efficiency of the Chinese P cycle showed a U-shaped change with an overall improvement of 22.7%, except for a temporary trough in 1975. The driving force behind the efficiency decline was the roaring phosphate fertilizer industry, as confirmed by the sharp increase in P flows for both resource utilization and waste generation from the mid-1960s to 1975. The positive driving forces behind the 30.7% efficiency increase from 1975 to 2018 were the implementation of the resource conservation policy, downstream pollution control, and, especially, the circular agro-food system strategy. However, not all current management practices improve the P resource efficiency. Mixing P industry waste with construction materials and the development of aquaculture to complement offshore fisheries erode P resource efficiency by 2.12% and 9.19%, respectively. With the promotion of a zero-waste society in China, effective P-cycle management is expected.

Decarbonizing the global steel industry in a resource-constrained future-a systems perspective.

Decarbonizing the global steel industry hinges on three key limited resources: geological carbon storage, zero-emission electricity and end-of-life scrap. Existing system analysis calls for an accelerated expansion of the supply of these resources to meet the assumed ever-increasing steel demand. In this study, we propose a different view on how to decarbonize the global steel industry, based on the principle that resource supply can only expand in line with historical trends and actual construction plans. Our analysis shows that global steel production cannot grow any further within a Paris-compatible carbon budget, resulting in a shortfall of approximately 30% against 2050 demand. This trajectory involves the phasing out of blast furnaces, along with strong growth in scrap recycling and hydrogen-based production. These findings highlight critical yet often overlooked challenges: (i) reducing excess demand while providing essential services, (ii) producing high-grade steel through upcycling scrap, and (iii) ensuring an equitable distribution of limited production across the globe. These perspectives contrast with those of the current agenda, which largely emphasizes the need to invest in new production technologies. Grounded in a physical basis, this analysis offers a complementary perspective for a more balanced debate in policymaking and industrial strategy. This article is part of the discussion meeting issue 'Sustainable metals: science and systems'.

From bits to green: Unraveling the digital economy's influence on natural resource efficiency.

This study explores the impact of the digital economy (DE) on natural resource efficiency (NRE) across 275 Chinese cities between 2011 and 2021. Through a comprehensive empirical analysis, we find that the DE significantly positively affects NRE. A key moderating factor in this relationship is green technological innovation (GTI), focusing on the quality rather than the quantity of green technology. Our study also uncovers regional variations of moderating effect. Additionally, we identify several mechanisms through which the DE contributes to enhanced NRE, including the transformation of industrial structure and improvements in green total factor productivity. A detailed heterogeneity analysis shows that the DE's impact on NRE varies according to city-specific factors such as natural resource endowment, city size, environmental regulations, and administrative levels. These findings provide a more nuanced understanding of how the DE influences NRE at the urban level, contributing to the broader discourse on sustainable development in the digital age. Our research offers policy recommendations and potential pathways for cities to leverage the DE for greater natural resource efficiency.

Resource-Efficient Parallelized Random Access for Reliable Connection Establishment in Cellular IoT Networks.

The role of various internet-of-things (IoT) devices responsible for data collection and reporting becomes more important in the era of Industry 4.0. Due to the various advantages (e.g., wide coverage, robust security, etc.), the cellular networks have been continuously evolved to accommodate IoT scenario. In IoT scenario, connection establishment is essential and primary for enabling IoT devices to communicate with centralized unit (e.g., base station (BS)). This connection establishment procedure in cellular networks, random access procedure, is generally operated in a contention-based manner. So, it is vulnerable to simultaneous connection requests from multiple IoT devices to the BS, which becomes worse as the contention participants increase. In this article, we newly propose a resource-efficient parallelized random access (RePRA) procedure for resource-efficiently ensuring reliable connection establishment in cellular-based massive IoT networks. Key features of our proposed technique are twofold: (1) Each IoT device simultaneously performs multiple RA procedures in parallel to improve connection establishment success probability, and (2) the BS handles excessive use of radio resources based on newly proposed two types of redundancy elimination mechanisms. Through extensive simulations, we evaluate the performance of our proposed technique in terms of connection establishment success probability and resource efficiency under various combinations of control parameters. Consequently, we verify the feasibility of our proposed technique for reliably and radio-efficiently supporting a large number of IoT devices.

How robust are current narratives to deal with the urban energy-water-land nexus?

Current energy, water, and land (EWL) nexus research treats all resources equally, causing bias in complicated nexus studies. To make the analysis robust, we consider resource endowment and significance. Here, we provide a methodological framework where the urban industrial resource nexus strength is constructed and assign weights to resources according to policies, describing resource efficiency and representing it in ternary diagrams to assess the urban industrial nexus innovatively. Results showed that energy drives urban development under all weights, with energy resource efficiency exceeding 60%. From consumption-based accounting, energy continues to dominate most industries under physical weightings but emphasizes the significance of water and land. While, under economic weightings, land supplants energy's dominance in specific sectors. Setting weights helps understand resource interaction, establish synergy based on urban development objectives, and minimize robustness. Our findings provide quantitative evidence for assessing urban resource efficiency to highlight priority sectors for intervention in urban decision-making.

Resource efficiency analysis through planetary boundary-based life cycle assessment: a case study of sugarcane in Pakistan.

Purpose: Extensive agriculture activities for crop production have led to increasing environmental impacts that threaten to exceed environmentally safe limits. The purpose of this study is to analyze resource efficiency of the agri-food industry, considering the case of sugarcane production in Pakistan. Methods: A holistic approach has been applied by determining the relevant impact categories and Sustainable Development Goals (SDGs), and linking them with Planetary Boundary-based Life Cycle Assessment (PB-LCA). Both the spatially generic and spatially resolved approaches were considered with application of different sharing principles. Results and discussion: Application of different sharing principles showed high variations in the assigned share of the safe operating space values. When taking a spatially generic approach, most of the impacts (except marine eutrophication and water consumption) were within the safe operating space for equal per capita, economic, caloric, and grandfathering sharing principles. However, all the impacts exceeded their limits considering the agri-land sharing and land use impact surpassed its budget considering the grandfathering sharing. In the spatially resolved approach, most of the impact values surpassed the available budgets. Furthermore, the failure to attain the pertinent SDG targets from a PB-LCA perspective is indicated by the exceeding of safe operating space for relevant impact categories. Conclusions: Overall, the production of sugarcane was found to be unsustainable, requiring urgent action to promote resource improvement and contain the impacts within safe limits. The developed framework enabled the evaluation of the SDGs using PB-LCA at the product level. The target-driven impact reduction values would help in achieving the targets and prioritizing the efforts by making informed decisions for reducing impacts within safe limits. Supplementary Information: The online version contains supplementary material available at 10.1007/s11367-023-02185-7.

Food production and resource use of urban farms and gardens: a five-country study.

There is a lack of data on resources used and food produced at urban farms. This hampers attempts to quantify the environmental impacts of urban agriculture or craft policies for sustainable food production in cities. To address this gap, we used a citizen science approach to collect data from 72 urban agriculture sites, representing three types of spaces (urban farms, collective gardens, individual gardens), in five countries (France, Germany, Poland, United Kingdom, and United States). We answered three key questions about urban agriculture with this unprecedented dataset: (1) What are its land, water, nutrient, and energy demands? (2) How productive is it relative to conventional agriculture and across types of farms? and (3) What are its contributions to local biodiversity? We found that participant farms used dozens of inputs, most of which were organic (e.g., manure for fertilizers). Farms required on average 71.6 L of irrigation water, 5.5 L of compost, and 0.53 m2 of land per kilogram of harvested food. Irrigation was lower in individual gardens and higher in sites using drip irrigation. While extremely variable, yields at well-managed urban farms can exceed those of conventional counterparts. Although farm type did not predict yield, our cluster analysis demonstrated that individually managed leisure gardens had lower yields than other farms and gardens. Farms in our sample contributed significantly to local biodiversity, with an average of 20 different crops per farm not including ornamental plants. Aside from clarifying important trends in resource use at urban farms using a robust and open dataset, this study also raises numerous questions about how crop selection and growing practices influence the environmental impacts of growing food in cities. We conclude with a research agenda to tackle these and other pressing questions on resource use at urban farms. Supplementary Information: The online version contains supplementary material available at 10.1007/s13593-022-00859-4.

Commitment of European SMEs to resource efficiency actions to achieve sustainability transition. A feasible reality or an elusive goal?

The European Union has built an interdependent framework to promote sustainability transition through commitment in resource efficiency (RE) actions as echoed in the European Green Deal. Although the factors affecting firms' decision to adopt a green strategy have been extensively explored, those affecting commitment remain unexplored. Thus, we study whether commitment of European SMEs to RE actions fosters sustainability transition and, what drives such commitment. Data includes more than 37,000 European SMEs from 2013 through 2017, combined with country-specific characteristics explored via a probit model with sample selection. Findings indicate that during the study period there has been a change in the structure of incentives of the firms, as in the beginning of the period, adoption of RE actions and future engagement were considered as independent decisions. We document that commitment is driven RE enhancers such as the implementation of new technological paradigms, cooperation, and specialized business advice while resource productivity, green energy, and competitiveness further foster commitment. Findings advocate that commitment in RE actions to achieve sustainability transition is a feasible reality. Efforts of policymakers should focus on further enabling RE committed firms by reducing policy red tape.

Supporting decision making to achieve circularity via a biodegradable waste-to-bioenergy and compost facility.

Bioproducts, such as energy and fertilizers, are strongly interrelated with the biodegradable waste treatment processes, within a holistic management strategy. Although different forms of biological treatment technologies are available, anaerobic digestion represents a process of major importance in the overall management strategy of biodegradable waste. This paper presents a methodology to support decision making for efficient management of biodegradable waste. The decision support framework provides the background towards the selection and design of a biodegradable waste installation with emphasis on the recovery of energy and organic fertilizer. The discrete steps are analytically defined and illustrated to assist managers and policy makers to organize their decision making in the whole spectrum of procedures required to promote sustainable biodegradable waste management programs. The methodological approach developed can be generically applied by public authorities, producers and stakeholders following essential basic steps regarding safe and environmentally friendly production of high-quality final product. Moreover, a demonstration is performed for a real-case study for the Region of Serres, Greece. The proposed installation is expected to manage 3,285 t of biodegradable waste and generate approximately 160,000 m3/a of biogas, 400 MWhel/a and 450 MWhthermal/a. The final bioproduct exceeds 3 kt of digestate that will be valorized in arable land close to the installation. Crucial interactions and managerial insights are also highlighted. The decision support framework aims to assist the research community, the private sector and decision makers to produce affordable and sustainable compost/digestate recovered from waste, also supporting the transition to a low carbon future and sustainable -circular- development.

'Unlocking circular economy for prevention of marine plastic pollution: An exploration of G20 policy and initiatives'.

Marine plastic pollution (MPP) is an urgent environmental and socio-economic problem. MPP amounts to 300 million tons annually, originates largely from land-based sources and severely impacts marine ecosystem, harms livelihoods and causes costs for businesses and governments. Plastics permeate the whole width and depth of seas and oceans, near well-developed coastal zones and equally in remotest corners. This undermines economic and social value of the oceans, particularly in terms of fisheries productivity and tourism. The G20 members, responsible for about two-thirds of global plastic waste, recognize the problem and undertake preventive measures - individually and collectively. Yet, are there efficient, effective and sufficient given the urgency of MPP and the contribution of G20 countries. This article highlights existing policies and identifies further policy options using a custom framework for MPP policy that merges Circular Economy (CE) and life-cycle perspectives.

Production of diverse PET probes with limited resources: 24 18F-labeled compounds prepared with a single radiosynthesizer.

New radiolabeled probes for positron-emission tomography (PET) are providing an ever-increasing ability to answer diverse research and clinical questions and to facilitate the discovery, development, and clinical use of drugs in patient care. Despite the high equipment and facility costs to produce PET probes, many radiopharmacies and radiochemistry laboratories use a dedicated radiosynthesizer to produce each probe, even if the equipment is idle much of the time, to avoid the challenges of reconfiguring the system fluidics to switch from one probe to another. To meet growing demand, more cost-efficient approaches are being developed, such as radiosynthesizers based on disposable "cassettes," that do not require reconfiguration to switch among probes. However, most cassette-based systems make sacrifices in synthesis complexity or tolerated reaction conditions, and some do not support custom programming, thereby limiting their generality. In contrast, the design of the ELIXYS FLEX/CHEM cassette-based synthesizer supports higher temperatures and pressures than other systems while also facilitating flexible synthesis development. In this paper, the syntheses of 24 known PET probes are adapted to this system to explore the possibility of using a single radiosynthesizer and hot cell for production of a diverse array of compounds with wide-ranging synthesis requirements, alongside synthesis development efforts. Most probes were produced with yields and synthesis times comparable to literature reports, and because hardware modification was unnecessary, it was convenient to frequently switch among probes based on demand. Although our facility supplies probes for preclinical imaging, the same workflow would be applicable in a clinical setting.

Evaluation of microclimates and assessment of thermal comfort of Panthera leo in the Masai Mara National Reserve, Kenya.

Quantifying comfort levels of lions within the Masai Mara National Reserve in Kenya is the main focus of this study. Its discourse delineates step by step the process of quantifying comfort levels of lions within the Mara. Resource-efficient measures for humans in the built environment have long been developed through the creation of passive zones and modulated ventilation. In an analogous manner, new procedures are being adapted for creating optimized microclimates in natural game reserves. This involves CFD (computational fluid dynamics)-inspired landscaping. It is seen that the predicted mean vote (PMV) values-measures of thermal comfort-exceed the expected comfortable ranges suitable for normal functioning of lions in the reserve. This calls for a detailed exploration on sustainable development of this sanctuary. The paper illustrates how modern tools in computational fluid dynamics can be used along with standard ecological models to ascertain the optimal extent of airflow, levels of hydration, and land use pattern changes affecting the prevailing microclimate.

Single-Board-Computer Clusters for Cloudlet Computing in Internet of Things.

The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the standard computing paradigm for latency-sensitive real-time IoT workloads, since it addresses the aforementioned limitations related to centralised cloud-computing models. Such a paradigm relies on bringing computation close to the source of data, which presents serious operational challenges for large-scale cloud-computing providers. In this work, we present an architecture composed of low-cost Single-Board-Computer clusters near to data sources, and centralised cloud-computing data centres. The proposed cost-efficient model may be employed as an alternative to fog computing to meet real-time IoT workload requirements while keeping scalability. We include an extensive empirical analysis to assess the suitability of single-board-computer clusters as cost-effective edge-computing micro data centres. Additionally, we compare the proposed architecture with traditional cloudlet and cloud architectures, and evaluate them through extensive simulation. We finally show that acquisition costs can be drastically reduced while keeping performance levels in data-intensive IoT use cases.

Secure Smart Cameras by Aggregate-Signcryption with Decryption Fairness for Multi-Receiver IoT Applications.

Smart cameras are key sensors in Internet of Things (IoT) applications and often capture highly sensitive information. Therefore, security and privacy protection is a key concern. This paper introduces a lightweight security approach for smart camera IoT applications based on elliptic-curve (EC) signcryption that performs data signing and encryption in a single step. We deploy signcryption to efficiently protect sensitive data onboard the cameras and secure the data transfer from multiple cameras to multiple monitoring devices. Our multi-sender/multi-receiver approach provides integrity, authenticity, and confidentiality of data with decryption fairness for multiple receivers throughout the entire lifetime of the data. It further provides public verifiability and forward secrecy of data. Our certificateless multi-receiver aggregate-signcryption protection has been implemented for a smart camera IoT scenario, and the runtime and communication effort has been compared with single-sender/single-receiver and multi-sender/single-receiver setups.

Analysis and recommendations for European carbon dioxide utilization policies.

Due to lower-cost energy supplies elsewhere, Europe needs resource efficient technologies to safeguard the competitiveness of its energy-intensive industries. The technical feasibility of the CCU value chain components (carbon capture, transportation and utilization) has been widely studied in literature. However infrastructural, regulatory and business strategic issues have received less attention. A review of the relevant policies (e.g. European Emissions Trading Scheme, Renewable Fuels and Waste Directives) has been performed. Stakeholder engagement and the stakeholder influence mapping was used to examine potential climate change, circular economy, renewable energy and regional industrial development policies that can support CO2 utilization value chains. The main contribution of the paper is to outline potential benefits of policies to foster the production and uptake of CO2-derived products such as methanol, polyurethane and mineral construction aggregates. Another outcome is to illustrate the role of key policy-making stakeholders in assessing the suitability of current statutes and the impact of potential changes. An important finding was that the development of connectivity infrastructure is a key missing enabler and more attention to policy on infrastructure is required. Finally, the work examines the justification for a CO2 Utilization Directive, comparable to the Carbon Capture and Storage Directive, but considering the current complexity of the European Union (EU) policy landscape.

Japanese surgical resource utilization in 2016.

PURPOSE: The purpose of this paper is to examine from the viewpoint of resource utilization the Japanese surgical payment system which was revised in April 2016. DESIGN/METHODOLOGY/APPROACH: The authors collected data from surgical records in the Teikyo University electronic medical record system from April 1 till September 30, 2016. The authors defined the decision-making unit as a surgeon with the highest academic rank in the surgery. Inputs were defined as the number of medical doctors who assisted surgery, and the time of operation from skin incision to closure. An output was defined as the surgical fee. The authors calculated each surgeon's efficiency score using output-oriented Charnes-Cooper-Rhodes model of data envelopment analysis. The authors compared the efficiency scores of each surgical specialty using the Kruskal-Wallis and the Steel method. FINDINGS: The authors analyzed 2,558 surgical procedures performed by 109 surgeons. The difference in efficiency scores was significant (p = 0.000). The efficiency score of neurosurgery was significantly greater than obstetrics and gynecology, general surgery, orthopedics, emergency surgery, urology, otolaryngology and plastic surgery (p<0.05). ORIGINALITY/VALUE: The authors demonstrated that the surgeons' efficiency was significantly different among their specialties. This suggests that the Japanese surgical reimbursement scales fail to reflect resource utilization despite the revision in 2016.

Enhanced Clean-In-Place Monitoring Using Ultraviolet Induced Fluorescence and Neural Networks.

Clean-in-place (CIP) processes are extensively used to clean industrial equipment without the need for disassembly. In food manufacturing, cleaning can account for up to 70% of water use and is also a heavy user of energy and chemicals. Due to a current lack of real-time in-process monitoring, the non-optimal control of the cleaning process parameters and durations result in excessive resource consumption and periods of non-productivity. In this paper, an optical monitoring system is designed and realized to assess the amount of fouling material remaining in process tanks, and to predict the required cleaning time. An experimental campaign of CIP tests was carried out utilizing white chocolate as fouling medium. During the experiments, an image acquisition system endowed with a digital camera and ultraviolet light source was employed to collect digital images from the process tank. Diverse image segmentation techniques were considered to develop an image processing procedure with the aim of assessing the area of surface fouling and the fouling volume throughout the cleaning process. An intelligent decision-making support system utilizing nonlinear autoregressive models with exogenous inputs (NARX) Neural Network was configured, trained and tested to predict the cleaning time based on the image processing results. Results are discussed in terms of prediction accuracy and a comparative study on computation time against different image resolutions is reported. The potential benefits of the system for resource and time efficiency in food manufacturing are highlighted.

Resource-Efficient Pet Dog Sound Events Classification Using LSTM-FCN Based on Time-Series Data.

The use of IoT (Internet of Things) technology for the management of pet dogs left alone at home is increasing. This includes tasks such as automatic feeding, operation of play equipment, and location detection. Classification of the vocalizations of pet dogs using information from a sound sensor is an important method to analyze the behavior or emotions of dogs that are left alone. These sounds should be acquired by attaching the IoT sound sensor to the dog, and then classifying the sound events (e.g., barking, growling, howling, and whining). However, sound sensors tend to transmit large amounts of data and consume considerable amounts of power, which presents issues in the case of resource-constrained IoT sensor devices. In this paper, we propose a way to classify pet dog sound events and improve resource efficiency without significant degradation of accuracy. To achieve this, we only acquire the intensity data of sounds by using a relatively resource-efficient noise sensor. This presents issues as well, since it is difficult to achieve sufficient classification accuracy using only intensity data due to the loss of information from the sound events. To address this problem and avoid significant degradation of classification accuracy, we apply long short-term memory-fully convolutional network (LSTM-FCN), which is a deep learning method, to analyze time-series data, and exploit bicubic interpolation. Based on experimental results, the proposed method based on noise sensors (i.e., Shapelet and LSTM-FCN for time-series) was found to improve energy efficiency by 10 times without significant degradation of accuracy compared to typical methods based on sound sensors (i.e., mel-frequency cepstrum coefficient (MFCC), spectrogram, and mel-spectrum for feature extraction, and support vector machine (SVM) and k-nearest neighbor (K-NN) for classification).

Accounting for the environmental benefits of remanufactured products: Method and application.

Although the importance of reusing products has been stated frequently, both in legislation and by academics, the scientific literature does not provide comprehensive and systematic methods of assessing the reuse of a generic product from an environmental point of view. Moreover, the definitions of reuse provided in the literature and legislation are not always consistent. This article introduces an original classification of different types of reuse, including some suggested definitions. It then focuses on remanufacturing, a type of reuse in which a used product (or its components) is returned to at least its original performance level. The article describes the development of a method for assessing, from a life-cycle perspective, the potential environmental benefits of remanufacturing energy-related products. The method includes several novel aspects: it helps to analyse possible trade-offs between potential environmental impacts and energy efficiency; it allows the independent modelling of some parameters that influence product reuse; and it can be applied even at the early stages of the design process, when some specifications may not yet have been defined. The environmental impacts of a product's life-cycle stages are used as input parameters for the assessment. The method is then applied to an enterprise server, a case-study product for which remanufacturing is a current market practice. A sensitivity analysis is included to check how uncertainties could affect the overall results. The results of the case study show that remanufactured servers, even those that are less energy efficient, can have lower environmental impacts than new ones. For example, reusing some components (e.g. hard disk drives and memory cards) is environmentally beneficial even if the remanufactured server consumes up to 7% more energy than a newly manufactured server. The case study also demonstrates how the method proposed could be used in the context of product policy discussions.