Environmental Metrics Research Articles

An agile new product development-based sustainable supply chain framework to improve environmental quality performance: emerging economies perspective

PurposeSustainable supply chain management (SSCM) is a new subfield of supply chain management. The purpose of this research is to develop a framework for assessing the impact of agile new product development (ANPD) practices on the environmental SSCM performance.Design/methodology/approachThe ANPD practices and SSCM environmental performance metrics (SEPMs) are identified through the literature review. The shortlisted ANPD practices are categorized into five major criteria each with an own set of sub-criteria. A four-level conceptual framework is developed. The weights of these ANPD practices are computed using the Pythagorean fuzzy Analytical Hierarchy Process (PFAHP), and the SEPMs are ranked using the Pythagorean fuzzy Combined Compromise Solution (PFCoCoSo).FindingsThe results show that the major criterion “Innovation Aspects” is the most important with a weightage of 0.2368, followed by “Policy Aspects” having 0.2228, “Technology Aspects” with 0.1959, “Organisation Aspects” having 0.1786 and “Executive Aspects” with 0.1658 weightage. The SEPMs “Frequency of NPD” is ranked first with an assessment value (Ki) of 2.5569, followed by “Lead time reduction” and “Number of design iterations” with Ki of 2.4482 and 2.3897, respectively. The research findings show that the ANPD practices like customer need assessment, availability of multidisciplinary team and Industry 4.0 technology usage contribute more to achieving environmental SSCM.Practical implicationsManagers can enhance environmental SSCM performance by adopting the ANPD practices and prioritizing SEPMs. Corporate effectiveness will be increased by the practices that promote SSCM and the use of technological innovations.Originality/valueThis study identified a unique set of 22 performance metrics that quantitatively measure NPD performance as well as environmental SSCM performance by adopting the 31 ANPD practices that were shortlisted. The proposed framework is a novel synthesis of literature from various disciplines such as new product development (NPD), environmental management, SSCM and performance evaluation.

Investigation of building-integrated photovoltaic, photovoltaic thermal, ground source heat pump and green roof systems

Renewable and bioclimatic techniques play a major role in promoting the sustainability of buildings. Therefore, it is important to study the performance of these techniques in various climates to identify the best solutions with optimized configurations in each region for maximum effectiveness, leading to broader adoption of these strategies and a more energy-efficient built environment. The aim of this paper is to investigate the effectiveness of integrating photovoltaic (PV), photovoltaic thermal (PVT) and ground source heat pump (GSHP) systems, and green roof (GR) strategy into a typical residential building in six different Moroccan climates. The performance of these techniques is assessed using key energy, environmental and economic (3E) metrics. To this aim, several simulations are conducted using EnergyPlus software. Furthermore, the impact of carbon taxation on each technique's economic benefits is examined. The results reveal that the PV and PVT technologies exhibit the greatest outcomes for the 3E perspectives in all climates; the excellent performance is achieved in the desert climate while the lowest one is found in the Mediterranean climate. Moreover, GSHP and GR techniques show significant energy and environmental benefits, but they prove to be economically inefficient in all considered climatic zones. Generally, the carbon payback periods are found in the range of 0.59–0.84, 1.07–1.25, 0.67–3.71 and 3.66–6.22 years, whereas the levelized cost of energy are within the range of 0.027–0.039, 0.030–0.035, 0.209–1.149 and 0.226–0.383 $/kWh for PVT, PV, GSHP and GR, respectively. On the other hand, levying a carbon tax of $75/tCO2e could increase the savings-to-investment ratio, on average, by around 61.42%, 60.32%, 59.60% and 51.53%, sequentially, for PVT, PV, GSHP and GR. Besides, the results of this paper could be applied to other locations worldwide with similar climates, energy prices and CO2 emission factors.

Perennial biomass cropping and use: Shaping the policy ecosystem in European countries.

Demand for sustainably produced biomass is expected to increase with the need to provide renewable commodities, improve resource security and reduce greenhouse gas emissions in line with COP26 commitments. Studies have demonstrated additional environmental benefits of using perennial biomass crops (PBCs), when produced appropriately, as a feedstock for the growing bioeconomy, including utilisation for bioenergy (with or without carbon capture and storage). PBCs can potentially contribute to Common Agricultural Policy (CAP) (2023-27) objectives provided they are carefully integrated into farming systems and landscapes. Despite significant research and development (R&D) investment over decades in herbaceous and coppiced woody PBCs, deployment has largely stagnated due to social, economic and policy uncertainties. This paper identifies the challenges in creating policies that are acceptable to all actors. Development will need to be informed by measurement, reporting and verification (MRV) of greenhouse gas emissions reductions and other environmental, economic and social metrics. It discusses interlinked issues that must be considered in the expansion of PBC production: (i) available land; (ii) yield potential; (iii) integration into farming systems; (iv) R&D requirements; (v) utilisation options; and (vi) market systems and the socio-economic environment. It makes policy recommendations that would enable greater PBC deployment: (1) incentivise farmers and land managers through specific policy measures, including carbon pricing, to allocate their less productive and less profitable land for uses which deliver demonstrable greenhouse gas reductions; (2) enable greenhouse gas mitigation markets to develop and offer secure contracts for commercial developers of verifiable low-carbon bioenergy and bioproducts; (3) support innovation in biomass utilisation value chains; and (4) continue long-term, strategic R&D and education for positive environmental, economic and social sustainability impacts.

Optimized modeling of energy and environmental metrics of mixed flow turbofan engine used regional aircraft.

As a kind of gas turbine engines, turbofan engines have powered a number of aero-vehicles in aviation sector. The necessity of turbofan with higher energy efficiency has been greatly drawn attention since these are operating dependent to fossil fuels. In this study, energy and emission metrics of fifty-one mixed flow turbofan engines (MFTE) with different bypass ratio, overall pressure ratio and fuel flow are modeled with multi-regression (MR) method. The obtained models are subjected to metaheuristic approaches involving genetic algorithm (GA) and simulated annealing (SA) so as to decrease error of the models. According to MR findings, rated thrust of MFTEs is estimated with 1.4877 of minimum square error (MSE) whereas GA and SA make it lower as 1.3404 and 1.2524, respectively. On the other hand, NOx emission index of MFTEs is predicted with relatively low coefficient of determination (R2) as 0.8620. However, its accuracy is enhanced to 0.8633 (with GA) and 0.8655 (with SA). Finally, exergy efficiency of MFTEs is estimated the highest model correctness with GA. Namely, R2 of the model is computed as 0.9280 with GA and 0.9277 with SA. Without applying these methods, its R2 is obtained as 0.9263 with MR. When considering these outcomes, thanks to modeling and optimization methods, prediction of performance and emission indexes of mixed flow turbofan engines could be performed with lower error values. It is thought that the study helps in prediction of environmental effect regarding turbofan engines that are utilized at busy airports.

Can a sustainability facts label reduce the halo surrounding organic labels?

AbstractConsumers often form beliefs about credence attributes unsupported by the best available evidence. In particular, prior research has revealed many consumers have overly‐optimistic beliefs about the environmental and nutritional impacts of organic food. We propose and study the effects of a sustainability facts label (SFL), which displays quantitative environmental information related to global warming potential, land use, and energy use per serving size of the product. The SFL is akin to a nutrition facts label (NFL), which we also study. We surveyed a nationally representative sample of milk consumers in the United States (USA) to measure their choices and beliefs about organic vs. conventional milk under one of three different label information treatments; the NFL only, the SFL only, and both labels relative to a control without any nutrition or sustainability information. Unexpectedly, our results show that the SFL increased the likelihood of organic purchases. Facts panels altered beliefs; The participants exposed to the SFL increased their perception that organic performs better on environmental metrics, despite the fact the information contained in the label provided a nuanced picture with organic better in some dimensions and worse in others. Consistent with the information provided, consumers exposed to the NFL decreased their perception that organic had fewer calories and more protein than conventional milk. Prior beliefs about organic were found to be important determinants of choice and information acquisition.

A plan to build a net zero energy building in hydrogen and electricity-based energy scenario in South Korea

As net zero energy buildings (NZEBs) are attracting global attention, possible energy transition scenarios for NZEBs have been proposed in South Korea: (1) hydrogen-based or (2) electricity-based energy supply. Compared with a typical Korean residential building that uses a gas-fired boiler and air conditioner, the buildings in the two scenarios can significantly reduce energy consumption and emissions. In this context, this study aims to evaluate the performance of NZEBs in hydrogen- and electricity-based energy-supply scenarios based on simulation. An NZEB is constructed considering passive designs, active systems, and renewable energy systems. Subsequently, its performance is evaluated in terms of energy, environmental, and economic metrics, considering life cycle performance. The evaluation results confirm that the electricity-based energy scenario has better energy and environmental performance than the hydrogen-based energy scenario, with each scenario showing energy savings of 62% and 53%, respectively. In the electricity-based scenario, application of the passive design, active system, and renewable system accounts for savings of 48.2%, 21.2%, and 7.8%, respectively. Consequently, achieving NZEB requires more than 13 photovoltaic panels. In case of economic feasibility, all scenarios have positive operating cost savings. However, scenario 1 shows insufficient economic feasibility owing to high initial investment cost.

Sustainability analysis of biorefineries based on country socio-economic and environmental context: A step-by-step way for the integral analysis of biomass upgrading processes

A methodological approach to estimate the sustainability performance of biorefineries is proposed as a way to elucidate the best alternative to upgrade biomass under a specific context. This methodology is based on the estimation of technical, economic, environmental, and social metrics. The methodology provides flexibility to design biorefineries using knowledge-based or optimization approaches. The advantage of the optimization approach is the possibility to ensure the economic feasibility of a process configuration without repeating the dimensions analysis for different scenarios. Then, the sustainability index is proposed as an indicator to compare different biorefinery configurations wherever. An avocado case study was analyzed considering a superstructure based on the possible upgrading pathways at a small-scale level. The sustainability index for a biorefinery addressed to producing avocado oil, animal feed, biogas, and electricity was about 54%. This performance suggests the need of improving processing lines and proposing new products. Finally, the sustainability index is proposed as an indicator easy to calculate, analyze, and understand for stakeholders and shareholders (i.e., decision-making groups).

Applying energy-exergy, environmental, sustainability, and exergoeconomic metrics and bi-objective optimization for assessment of an innovative tri-generation system

One of the reasons why renewable energies are so attractive compared to fossil fuels is their low environmental impact. In addition, geothermal power plants contribute tremendously to sustainable energy generation for cities despite their lower energy efficiency than fossil fuel plants. The multi-heat recovery will eliminate the applicability defect mentioned. Therefore, this paper studies a novel tri-generation schema with the maximum use of heat loss through a multi-heat recovery technique in two principal processes, namely waste heat-to-power and power-to-H2 and -purified water. A double-flash binary cycle, Rankine cycle, electrolyzer unit, and reverse osmosis desalination system all play a part in the creation of this system. The technical feasibility of the system is scrutinized based on energy-exergy, environmental, sustainability, and exergoeconomic metrics and bi-objective optimization. Generally, 1st separator pressure made the strongest effect on the measured variables among decision variables. The increase in this parameter led to an upward-and-downward behavior of the net electricity and exergetic efficiency; while the cost of products experienced a converse trend. Also, the produced H2 and purified water together with the tri-generation gain output ratio augmented. Changes were not observed in net electricity and purified water with the change in 2nd separator pressure, but the H2 production rate changed significantly. Through bi-objective optimization, net electricity, purified water production rate, and total investment cost rate also significantly increase. Based on the optimum design mode, the CO2 emission rate and the sustainability index are higher than under the base case design.

Purpose: From theory to practice

AbstractWhile there is abundant discussion in business journals on the “how to” of purpose to achieve social good beyond profitability, academic research addressing the theoretical and practical impact of purpose on an organization's performance is limited. Some management scholars claim that organizations that are not purpose‐driven and fail to consider the needs of their relevant stakeholders will not be able to create long term value for their companies. There is also concern that organizations may use purpose to show intention towards social good but lack tangible actions to demonstrate their commitment. To determine whether purpose impacts the long‐term value creation of organizations, this research paper examined a deeper understanding of the meaning of purpose from both individual and organizational perspectives. With clarity on individual purpose as the ability for humans to consciously set their intentions to achieve good, organizational purpose can be considered as the conscious intentions of individuals to work collectively towards social good beyond the singular goal of profitability. Building on this theoretical understanding of purpose, together with an exploration of the shift occurring in organizational responsibility from a singular focus on shareholder returns towards stakeholder inclusivity, this paper proposes a Stakeholder Purpose Framework which links the impact of purpose to long‐term value creation by aligning an organization's purpose with their stakeholders and measuring the outcomes of relevant environmental, social, and governance (ESG) metrics. Activating this framework will provide analytical data supporting whether (or not) purpose does impact an organization's ability to create long‐term value.

A household-scale life cycle assessment model for understanding the food-energy-water nexus

The household is an important locus of decision-making regarding food, energy, and water (FEW) consumption. Changes in household FEW consumption behaviors can lead to significant reductions in environmental impacts, but it can be difficult for consumers to compare the relative impacts of their consumption quantitatively, or to recognize the indirect impacts of their household consumption patterns. We describe two novel tools designed to address this problem: A hybrid life cycle assessment (LCA) framework to translate household consumption of food, energy, and water into key environmental impacts including greenhouse gas emissions, energy use, and water use; and a novel software application called HomeTracker that implements the framework by collecting household FEW data and providing environmental impact feedback to households. We explore the question: How can a life cycle assessment-based software application facilitate collection and translation of household consumption data to meaningful environmental impact metrics? A case study in Lake County, Illinois is presented to illustrate use of the HomeTracker application. Output data describing environmental impacts attributable to household FEW consumption in the study area are shown in order to illustrate key features and trends observed in the case study population. The framework and its associated output data can be used to support experimental research at the household scale, allowing for examination of what users purchase and consume over an extended period of time as well as increased understanding of household behavior trends and environmental impacts, and as future work.

Interactive impacts of walkability, social vulnerability, & travel behavior on COVID-19 mortality: A hierarchical Bayesian spatial random parameter approach

While existing research highlights the built and social environment impacts on COVID-19 mortality, no empirical evidence exists on how the built and social environments may interact to influence COVID-19 mortality. This study presents a rigorous empirical assessment of the interactive impacts of social vulnerability and walkability on neighborhood-level COVID-19 mortality rates. Based in King County, WA, a unique data infrastructure is created by spatially integrating diverse census tract-level data on COVID-19 mortalities, walkability characteristics, social vulnerability, and travel behavior measures. Advanced Markov Chain Monte Carlo (MCMC) based Full Bayes hierarchical spatial random parameter models are developed to simultaneously capture spatial and unobserved random heterogeneity. Around 46% of the neighborhoods had opposite levels of walkability and social vulnerability. Compared to low walkability and high social vulnerability, neighborhoods with high walkability and low social vulnerability (i.e., best case scenario) had on average 20.2% (95% Bayesian CI: -37.2% to -3.3%) lower COVID-19 mortality rates. Analysis of the interactive impacts when only one of the social and built environment metrics was in a healthful direction revealed significant offsetting effects – suggesting that the underlying structural social vulnerability issues faced by our communities should be addressed first for the infectious disease-related health impacts of walkable urban design to be observed. Concerning travel behavior, the findings indicate that COVID-19 mortality rates may be reduced by discouraging auto use and encouraging active transportation. The study methodologically contributes by simultaneously capturing spatial and unobserved heterogeneity in a holistic Full Bayesian framework.

A deep semi-dense compression network for reinforcement learning based on information theory

Although reinforcement learning (RL) can solve complex tasks after training, it’s difficult to extend trained agents to target environments with perturbations. This lack of generalization ability has caused the dilemma of large-scale application of RL. Rich neural networks have brought huge improvements to deep learning, but these aren’t adapted to RL and even bring negative effects. Therefore, RL algorithms have few choices of neural network, which greatly limits the representation and generalization ability of RL. To overcome these limitations, we propose a deep semi-dense compression network (DSCN) to improve RL generalization ability. First, we perform a structural extension on a general network model for RL. Then based on the information theory, we propose a semi-dense connection to enhance the neural information flow (NIF) of initial features. Finally, drawing on the ideas of course learning, we propose a channel compression approach to filter the redundant information of the deep network. In addition, we innovatively extend the experimental environment and evaluation metrics of the existing platform, which can fully evaluate the performance of DSCN. The experimental results show that our model achieves stable and significant generalization performance improvement.

Microorganisms in Fish Feeds, Technological Innovations, and Key Strategies for Sustainable Aquaculture.

Aquaculture, the world's fastest growing food sector, produces over half of all fish for human consumption. Aquaculture feeds include fishmeal and fish oil, extracted from wild-caught fish such as sardines, and poses ecological, food security, and economic drawbacks. Microalgae, yeasts, fungi, bacteria, and other alternative ingredients show promise as potential ingredients in aquafeeds that provide protein/amino acids, lipids, or omega-3 sources and sources of bioactive molecules. This review article discusses the issues that the literature often lacks data on, such as the recent development of using microorganisms, technological innovation, challenges, and opportunities to develop a low environmental footprint of aquaculture diet. The ingredients often require novel processing technology to improve digestibility and fish growth and reduce antinutritional factors. This is an important gap to fill because microalgae are the most frequently used organism in fish feed, particularly as a dietary supplement or mixed with other ingredients. The production, processing, and formulating steps can affect the nutritional qualities. Stepwise strategies are required to evaluate these ingredients for feed application, and in this article, I articulated the stepwise key approaches of evaluating nutritional and environmental response metrics to develop highly sustainable aquaculture feed using these microorganisms, which would guide a more judicious inclusion of these novel ingredients.

Metrics for measuring industrial sustainability performance in small and medium-sized enterprises

PurposeThis paper aims to identify and empirically analyze useful and applicable metrics for measuring and managing the sustainability performance of small and medium-sized enterprises (SMEs).Design/methodology/approachTo achieve the objective of the paper, potential metrics were adopted from previous research related to industrial sustainability and an empirical analysis was carried to assess the applicability of the metrics by collecting empirical data from Italian footwear SMEs using a structured questionnaire. The SMEs were selected using a convenience sampling method.FindingsThe results of the within-case analysis and the cross-case analysis indicate that the majority of the metrics were found to be useful and applicable to each of the SMEs and across the SMEs, respectively. These metrics emphasized measuring industrial sustainability performance related to financial benefits, costs and market competitiveness for the economic sustainability dimension; resources for the environmental sustainability dimension; and customers, employees and the community for the social sustainability dimension.Research limitations/implicationsApart from the within-case analysis and cross-case analysis, it was not possible to conduct statistical analysis since a small number of SMEs were accessible to collect empirical data.Originality/valueThe findings of the paper have considerable academic, managerial and policy implications and will provide a theoretical basis for future research on measuring and managing industrial sustainability performance. By providing a set of empirically supported metrics based on the triple bottom line approach (i.e. economic, environmental and social metrics), this paper contributes to the existing knowledge in the field of industrial sustainability performance measurement.

Linking Life Cycle and Integrated Assessment Modeling to Evaluate Technologies in an Evolving System Context: A Power-to-Hydrogen Case Study for the United States.

Carbon-neutral hydrogen (H2) can reduce emissions from hard-to-electrify sectors and contribute to a net-zero greenhouse gas economy by 2050. Power-to-hydrogen (PtH2) technologies based on clean electricity can provide such H2, yet their carbon intensities alone do not provide sufficient basis to judge their potential contribution to a sustainable and just energy transition. Introducing a prospective life cycle assessment framework to decipher the non-linear relationships between future technology and energy system dynamics over time, we showcase its relevance to inform research, development, demonstration, and deployment by comparing two PtH2 technologies to steam methane reforming (SMR) across a series of environmental and resource-use metrics. We find that the system transitions in the power, cement, steel, and fuel sectors move impacts for both PtH2 technologies to equal or lower levels by 2100 compared to 2020 per kg of H2 except for metal depletion. The decarbonization of the United States power sector by 2035 allows PtH2 to reach parity with SMR at 10 kg of CO2e/kg H2 between 2030 and 2050. Updated H2 radiative forcing and leakage levels only marginally affect these results. Biomass carbon removal and storage power technologies enable carbon-negative H2 after 2040 at about -15 kg of CO2e/kg H2. Still, both PtH2 processes exhibit higher impacts across most other metrics, some of which are worsened by the decarbonization of the power sector. Observed increases in metal depletion and eco- and human toxicity levels can be reduced via PtH2 energy and material use efficiency improvements, but the power sector decarbonization routes also warrant further review and cradle-to-grave assessments to show tradeoffs from a systems perspective.

Street-view and traditional greenness metrics with adults' sitting time in high-density living in Hong Kong: Comparing associations, air pollution and noise roles, and population heterogeneity

BackgroundEmerging evidence suggests neighborhood greenness is associated with physical activity; however, the sitting-specific associations with multi-source greenness metrics remain unclear, especially in high-density cities. ObjectivesThis cross-sectional study examined: 1) the associations of street-view greenness (SVG) and traditional greenness metrics (i.e., Normalized Difference Vegetable Index (NDVI) and park density) with sitting time; 2) the potential moderating/mediating roles of objective/perceived air pollution and perceived roadside noise; and 3) how the associations vary by demographics and socioeconomic status. MethodsInterview survey data of 1977 adults in Hong Kong from 2014 and 2015 was linked to environmental data. Using an object-based image classification algorithm, SVG was derived from Google Street View images, capturing human-viewed street-level greenery. NDVI was derived from Landsat 8 satellite images using the normalized difference between the near-infrared and red bands. Park density was calculated by point density. In the main analyses including regressions, parallel mediation, interaction, and stratified models, the environmental metrics were measured within a 1000-m Euclidean buffer of residence. ResultsSVG and park density were negatively associated with sitting time after adjusting for covariates including physical activity while NDVI was not significantly associated with sitting time, and results were robust with 800–1800 m Euclidean and 1400–1800 m network distance. Greenness-sitting associations were not moderated/mediated by perceived air pollution/roadside noise while SVG-sitting associations were moderated by objective NO2, O3, and PM2.5 and mediated by O3. SVG-sitting associations differed by age, having under-school-aged children, birthplace, education, and occupation type while associations between traditional greenness metrics and prolonged sitting showed no significant population heterogeneity. ConclusionsSVG appears to be more accurate in estimating exposure than traditional metrics to reflect greenness-sitting associations, objective air pollution moderating and mediating roles, and population heterogeneity, which emphasizes the importance of street-level greenness planning for health promotion in terms of reducing sitting time.

Effects of Landscape, Climate and Hunting on the Occurrence of White-Browed Guan Penelope jacucaca in Central-North Caatinga, Brazil

The White-browed Guan Penelope jacucaca is an endangered member of the family Cracidae endemic to the Caatinga region of northeast Brazil. Hunting and habitat loss are the presumed major threats to the species, however, their impacts on its occurrence have been insufficiently tested. We used field observations and information on hunting activity to assess whether hunting, landscape and/or climate affect the occurrence of the White-browed Guan in the Caatinga. We sampled 23 localities within the Caatinga and recorded the species' occurrence and hunting encounters. For each locality, we extracted three landscape metrics (vegetation cover, patch aggregation, and patch richness); two climate variables (temperature seasonality and mean precipitation of the wettest month); and one topographic variable (mean slope). We then used generalized linear models based on proportion to determine if the species' occurrence was related to these environmental factors. We found a greater likelihood of detecting the species in localities with greater slope, greater heterogeneity of habitats and more stable temperatures, whereas hunting activity presented a trend of negative impact on occurrence. Our results emphasize the relevance of using different environmental metrics to implement conservation programs for this threatened species.

Track and dive-based movement metrics do not predict the number of prey encountered by a marine predator

BackgroundStudying animal movement in the context of the optimal foraging theory has led to the development of simple movement metrics for inferring feeding activity. Yet, the predictive capacity of these metrics in natural environments has been given little attention, raising serious questions of the validity of these metrics. The aim of this study is to test whether simple continuous movement metrics predict feeding intensity in a marine predator, the southern elephant seal (SES; Mirounga leonine), and investigate potential factors influencing the predictive capacity of these metrics.MethodsWe equipped 21 female SES from the Kerguelen Archipelago with loggers and recorded their movements during post-breeding foraging trips at sea. From accelerometry, we estimated the number of prey encounter events (nPEE) and used it as a reference for feeding intensity. We also extracted several track- and dive-based movement metrics and evaluated how well they explain and predict the variance in nPEE. We conducted our analysis at two temporal scales (dive and day), with two dive profile resolutions (high at 1 Hz and low with five dive segments), and two types of models (linear models and regression trees).ResultsWe found that none of the movement metrics predict nPEE with satisfactory power. The vertical transit rates (primarily the ascent rate) during dives had the best predictive performance among all metrics. Dive metrics performed better than track metrics and all metrics performed on average better at the scale of days than the scale of dives. However, the performance of the models at the scale of days showed higher variability among individuals suggesting distinct foraging tactics. Dive-based metrics performed better when computed from high-resolution dive profiles than low-resolution dive profiles. Finally, regression trees produced more accurate predictions than linear models.ConclusionsOur study reveals that simple movement metrics do not predict feeding activity in free-ranging marine predators. This could emerge from differences between individuals, temporal scales, and the data resolution used, among many other factors. We conclude that these simple metrics should be avoided or carefully tested a priori with the studied species and the ecological context to account for significant influencing factors.

Influence of built environment on building energy consumption: a case study in Nanjing, China.

Built environment plays a significant role in optimizing building energy consumption. However, few studies have explored the comprehensive effect between built environment metrics on building energy consumption. Thus, this study aims to explore interrelationships between built environment on building energy consumption focused on moderating effect. In this study, we established a built environment measure system from the perspective of land use and land cover, landscape structure and building configuration. This study explored the correlation between built environment and building energy consumption and analyzed the moderating effect of building configuration emphatically. Results show that: for integrated grids group, normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI) have a positive influence and impervious area (IA) has a negative influence, with NDVI has the greatest impact. Building floor (BF), building coverage ratio (BCR) and aspect ratio can weaken the positive relationship between NDVI and energy use intensity of grid ( ). BCR weakens the positive effect of MNDWI on . The moderating effect of building configuration on EUI varies in the same grid group and among different grid groups. For sample 1, BCR inhibits the negative effect of mean perimeter-area ration (PARA-MN) on . For sample 2, BF promotes the negative effect of number of patches and land use richness index (R) on . And sky view factor inhibits the positive effect of IA on . This study reveals the pathways of built environment on building energy consumption. As a result, the keys of optimizing building energy consumption are the reasonable planning and optimization of the urban built environment of different land cover. The online version contains supplementary material available at 10.1007/s10668-023-02930-w.

Long-Term Thermal Comfort Monitoring via Wearable Sensing Techniques: Correlation between Environmental Metrics and Subjective Perception

The improvement of comfort monitoring resources is pivotal for a better understanding of personal perception in indoor and outdoor environments and thus developing personalized comfort models maximizing occupants' well-being while minimizing energy consumption. Different daily routines and their relation to the thermal sensation remain a challenge in long-term monitoring campaigns. This paper presents a new methodology to investigate the correlation between individuals' daily Thermal Sensation Vote (TSV) and environmental exposure. Participants engaged in the long-term campaign were instructed to answer a daily survey about thermal comfort perception and wore a device continuously monitoring temperature and relative humidity in their surroundings. Normalized daily profiles of monitored variables and calculated heat index were clustered to identify common exposure profiles for each participant. The correlation between each cluster and expressed TSV was evaluated through the Kendall tau-b test. Most of the significant correlations were related to the heat index profiles, i.e., 49% of cases, suggesting that a more detailed description of physical boundaries better approximates expressed comfort. This research represents the first step towards personalized comfort models accounting for individual long-term environmental exposure. A longer campaign involving more participants should be organized in future studies, involving also physiological variables for energy-saving purposes.