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The pulp and paper industry faces several challenges linked to climate and environmental impact, resource efficiency, rising energy prices, increased competition for biomass resources, and declining demand for traditional printed paper products. However, these challenges also offer strategic opportunities for the industry to develop into a competitive, resource-efficient, and low-carbon industry in line with a biobased economy. Against this background, this paper aims to analyse current energy strategies in the pulp and paper industry in Sweden. Specifically, the paper analyses how companies combine continuous process efficiency to reduce energy costs with activities that could be developed into new energy-related products to increase revenue. Most of the analysed companies work to various degrees with both these strategies, employing methods that include improving energy efficiency, energy security, and energy conversion, as well as developing a wide range of biobased energy products. However, our study indicates that there is an untapped potential associated with energy product development, and we conclude that energy efficiency measures can free up resources, enabling the development of new energy products. Finally, several potential managerial outcomes and implications are outlined. • The paper analyses the energy strategies in the pulp and paper industry in Sweden. • Energy strategies focus both to improve energy efficiency and develop new energy-products. • The companies' energy strategies combined exploitation and exploration. • A number of managerial implications are presented. [ABSTRACT FROM AUTHOR]

Water removal during paper manufacturing is of primary importance to production rate and cost efficiency for the pulp and paper industry. It is crucial to develop methods to reduce energy consumption by increasing the percent solids in the paper web entering the dryers from the presses. This research aimed to develop a fundamental understanding of the effect of bio-chemo-mechanical pretreatments on a bleached softwood fiber matrix and evaluate the impact on the percent solids of the paper web after pressing. Experiments included enzymatic, refining, and cationic polymer pretreatments on the bleached softwood pulps, followed by laboratory papermaking and determining the equilibrium moisture content (EMC) after pressing and the pulp and paper properties. The combined effect of mild refining, controlled enzymatic pretreatments, and cationic strength aids proved to enhance the water removal during wet pressing (up to 35 % reduction) and increase paper strength (up to 60 % increase). The results of increased solids after pressing were used to calculate the potential reduction in drying energy during paper manufacturing. Energy savings of around 10 % for paper drying could be achieved through fiber matrix modification by bio-chemo-mechanical pretreatment. Enzymatic pretreatments have previously been conventionally applied before refining as an energy-saving method. However, this research shows that synergistic actions of enzymes added after refining modify the fibers and create the optimal conditions for enhancement in drainage, press dewatering, and paper properties. [Display omitted] • Enzyme-assisted fiber modifications improve press dewatering and paper strength. • Enzyme blends can enhance fiber cell wall flexibility and fibrillation. • Synergistically, enzymes increased ∼35% press dewatering and ∼60% tensile strength. • Enzymes, mild refining, and cationic biopolymers enhance paper process efficiency. • This research introduces alternative methods for decarbonizing the paper industry. [ABSTRACT FROM AUTHOR]

Pressure servo control plays a crucial role in the majority of industrial applications that use compressed air as their power source. How to reduce the energy consumption of the pneumatic system while ensuring the high accuracy of pressure control remains a key problem to be solved. This paper proposes a Gaussian Process (GP) 1 model predictive controller (MPC) applied to a pressure servo control system based on high-speed on-off valves. The smallest quantity of collected data is used to create the GP model. The entire model, which includes some predictive data, is produced once the generated model has been optimized. The GP model is combined with the MPC to perform comparative experiments using an industrial controller with a Field Programmable Gate Array (FPGA). The system responds quickly and with little tracking error in steady-state response studies as well as dynamic response experiments. The GP-MPC achieves the best outcomes in the dynamic comparison tests. The root mean square error (RMSE) is just 2.42 kPa, and the overshoot is less than 59.9% of the Proportional-Integral-Derivative (PID) controller and 68.5% of the sliding mode controller (SMC). Although the compressed air consumption of GP-MPC is basically the same as that of PID, it is significantly better than SMC, with a total saving of about 70.2%. All the experiments prove that the controller proposed in this paper can effectively improve the energy efficiency and tracking accuracy of the pressure servo control system. [Display omitted] • A Gaussian process model for the high-speed on-off valve is developed which is able to predict uncollected data. • A model predictive controller is established by combining the Gaussian process model with rolling optimization method. • The pressure tracking and energy-saving performance are intended to be improved by using the objective function. [ABSTRACT FROM AUTHOR]

The new roadmap of the European Union (EU), the European Green Deal, aims at tackling climate adaptation, energy, biodiversity, and pollution challenges. To contribute to such aim, the latest EU Renewable Energy Directive defines for the first time renewable energy communities. Among them, Photovoltaic-Green roof Energy Communities (PGECs) emerge as a potential option in urban areas. This paper investigates whether and under which conditions PGECs are capable to meet the objectives of the European Green Deal in an economically convenient manner. Since some conditions are context-specific, this research is showcased using a case study (Luxembourg). First, European legislation was reviewed to determine the suitable legal model for PGECs. Second, a systematic literature review helped identifying lifecycle costs and benefits of photovoltaic-green roofs and their value ranges. Third, a model for probabilistic social and private cost-benefit analyses was developed and tailored to Luxembourg. Lastly, Scenario Discovery was used to identify the ranges of input values leading to desirable net present values. Results show that PGECs can contribute to achieving multiple objectives of the European Green Deal in an economically convenient manner. From the societal perspective, PGECs are found to be economically convenient for any cost, benefit, and discount rate in the case study. From the private perspective, PGECs remain convenient in 62% of the scenarios, with green roofs' installation cost and electricity generation benefit playing pivotal roles. This paper presents a rare combination of probabilistic cost-benefit analyses and scenario discovery, It supports policymakers designing incentive schemes for PGECs, and can be replicated in other countries. [Display omitted] • Review of European legal models for Photovoltaic-Green Roof Energy Communities─PGECs. • The European Renewable Energy Community is the most suitable legal model for PGECs. • Qualitative and quantitative costs-benefit analysis of photovoltaic-green roofs. • PGECs prove economically convenient from private and social cost-benefit approaches. [ABSTRACT FROM AUTHOR]

As the path of industrial eco-efficiency (IEE) needs to be re-examined from a multi-dimensional perspective, this research opens the internal "black box" of China's industrial eco-economic system driven by sustainable development goals (SDGs) and decomposes IEE into industrial production and sustainable development stages. It further divides the industrial production stage into two parallel subsystems of water use efficiency (WUE) and energy efficiency (EE) and derives SDG6 efficiency (SDG 6 E) and SDG7 efficiency (SDG 7 E) in the sustainable development stage respectively. The paper proposes a meta two-stage parallel entropy dynamic DDF-DEA model to re-measure IEE of 30 provinces in China from 2015 to 2021, discusses the relationship between overall efficiency and stage efficiency, and by using the Tobit model explores various types of influencing factors by subregion. The results show that the modified DDF-DEA model can explore China's IEE more accurately under SDGs. China's IEE is more stable from 2015 to 2021, with the efficiency value always fluctuating between 0.59 and 0.64, the overall level is low, and there is more room for improvement. There are significant inter-provincial differences in IEE and efficiency inertia. In more than 75% of the provinces SDG 7 E constrains IEE improvement, while the dynamic evolution of IEE and its subsystem efficiency varies across regions. Environmental regulation is a common factor affecting IEE across the country and in the east, central, and west regions, whereas the level of economic development, openness to the outside world, and urbanization rate are differential factors affecting IEE across the country and in the three major regions. This study offers new perspectives for exploring the path of IEE enhancement and providing empirical references for the collaborative construction of industrial ecological civilization. [Display omitted] [ABSTRACT FROM AUTHOR]

Adoption and improvement of energy efficiency is one of the recommended pathways to tackle the problems of growing energy demand and greenhouse gas emissions. However, studies show that rebound effects from energy efficiency improvements can erode anticipated energy savings. This paper elucidates the rebound effect arising from energy efficiency initiatives in Kenya. The study uses Index Decomposition Analysis to assess the drivers of Kenya's total primary energy supply. The paper then adopts the neoclassical growth model in the empirical analysis of energy and carbon rebound effects at the macro-economic level. Cobb-Douglas production function is further applied using Solow growth model and energy as a factor of production to approximate technological progress. Results of decomposition of energy supply show that energy intensity and affluence are the drivers with the most significant effect on energy supply while population has less critical effect. Average energy and carbon rebound effects show partial rebounds of 15.64% and 31.41%, respectively. These results imply that there is need to accelerate the pace of transitioning to green energy as the ultimate solution to minimizing environmental impacts arising from energy use and tackling climate change. • Carbon and energy rebound effects of energy efficiency initiatives is studied. • Decomposition analysis is used to investigate drivers of energy supply. • Energy intensity and affluence have most significant influence on energy supply. • Average estimates of carbon and energy rebound effects are partial rebound effects. [ABSTRACT FROM AUTHOR]

The startup performance is crucial to the high-efficient operation of the sustainable power generation system. Current literature usually focuses on catalysts and startup strategy to improve startup performance of the proton exchange membrane fuel cell, which ignores the gas foil bearings-rotor system that directly affects startup response. Therefore, in this paper, the effects of bump foil structure, coating, and nominal clearance on the startup response of the bearings-rotor system are first investigated experimentally. Multi-objectives optimization mathematical model considering simultaneously lower power consumption, takeoff speed, and vibration is presented based on grey relational analysis. The optimal bearings-rotor system with radial trisection bump foil, coating MoS 2 , and nominal clearance of 50 μm is identified. Compared to average values, the power consumption of the optimal system is diminished by 27.2% while the takeoff speed and nonlinear vibration are reduced by 16.2% and 47.3%, respectively. These findings can be used to improve energy efficiency and startup performance for fuel cells. The systematic methodology proposed in this study can be extended to other investigations about the startup. • Bump foil type, coating, and nominal clearance are first considered in PEMFCs. • Multi-objective optimization mathematical model is presented. • Optimal gas foil bearings-rotor system is proposed and verified. • Startup performance of the proposed system is improved. • Power consumption of the proposed system is diminished by 27.2%. [ABSTRACT FROM AUTHOR]

Motor systems are ubiquitous throughout the industrial sector, particularly in fluids applications. It is well known that the efficiency of these operations can be greatly enhanced using variable frequency drive (VFD) controls, but adoption of the technology is far from universal. The goal of this paper is to introduce engineering, economic, and environmental analyses to demonstrate benefits to both individual facilities and the state at large. Individual case studies are presented to describe the variety of opportunities for VFD-enhanced motor control; however, this project seeks to describe the combined impact of VFD implementation at a new scale. Data sourced from a U.S. Department of Energy program is used to perform economic and environmental input output analysis to calculate broad impacts of individual audits and recommendations. Results indicate that widespread implementation of VFD controls on motor systems in the industrial sector will introduce significant economic and environmental benefits. One of the scenarios showed a potential reduction of over 4.7 million tonnes of carbon dioxide from regional manufacturing sector as well as a cascading contribution to the regional economy totaling nearly $1 billion. The results are presented as a demonstration of the magnitude of impact that improving control of industrial motor systems can have, as a guide to industry leaders and policymakers about the value of such investments. [Display omitted] • Variable frequency drive (VFD) modifications to industrial motors are described analytically. • Individual micro-scale carbon and cost savings are combined for input-output analysis. • Leveraging VFD control as a universal practice would result in nearly 5 million avoided tonnes of CO 2. • Similarly, economic benefits across the state of Ohio would total more than $1 billion. [ABSTRACT FROM AUTHOR]

The Sustainable Development Goal (SDG) that emphasizes sustainable and affordable energy presents a practical pathway to achieve sustainable growth. Moreover, this goal aligns with SDG 13, which focuses on climate action. Nonetheless, it is important to consider factors such as political and financial risk, as they can influence climate action efforts and the renewable energy sources adoption. Hence, this study broadens the conversation surrounding CO 2 emission reduction and the achievement of Sustainable Development Goals (SDGs). It accomplishes this by investigating the interplay between renewable energy, political risk, financial risk, and CO 2 emissions in Finland spanning from 1990/Q1 to 2021/Q4. Notably, this research distinguishes itself through its exploration of these complex connections, employing a wavelet-based quantile methodology. Unlike traditional quantile regression, which can only reveal connections between variables within each quantile, the wavelet-based quantile approach enables the simultaneous capture of correlations across quantiles and periods. The results show that in the long-term and across all quantiles (0.01–0.99), energy efficiency, specifically gas and oil efficiency, lessens CO 2. In addition, low financial and political risks improve ecological quality by lessening CO 2 across all periods and quantiles (0.01–0.99). The paper outcomes serve as a basis for formulating a policy framework aimed at achieving SDG 7 and SDG 13 in Finland. • We explore the impact of energy efficiency and country risk on CO 2 emissions. • The role of renewable energy and economic growth are also analyzed. • The Time series data of the Finland is used from 1990/Q1 to 2020/Q4. • Various wavelet-based quantile correlation is applied. • Renewable energy, oil and gas efficiency decrease CO 2 emissions in each quantile and across periods. [ABSTRACT FROM AUTHOR]

Policies targeting energy efficiency and renewable energy are sometimes viewed as more politically feasible than carbon pricing in pursuit of emission reduction goals. This paper assesses underlying drivers of energy policy development. These factors include economic, social, environmental, and institutional variables. The between estimator for panel data is an appropriate method for our focus on some exogenous variables that vary more across countries than over time. We find that larger oil reserves per capita have a negative relationship with renewable energy policy development. Education and political globalisation have strong positive relationships with both energy-efficiency and renewable-energy policy development. These results suggest that greater participation in global political groups can be an indirect approach toward energy policy development, in cases where direct and immediate policies are hard to implement. OECD countries have higher policy scores by 33 and 25 points in energy efficiency and renewable energy respectively. Blinder-Oaxaca decomposition analysis shows that these higher scores are primarily due to social and political institution predictors rather than economics and physical endowments. • Large-n cross country international sample on continuous policy score measurement. • Political globalisation is positively linked with renewables and energy efficiency policies. • Education is positively linked to energy policy development, especially for efficiency. • Higher OECD countries' policy scores are primarily due to social and political predictors. • Higher incomes are unlikely to lead to automatic improvements in energy policies. [ABSTRACT FROM AUTHOR]

Hot embossing is an efficient technology for the fabrication of glass micro- and nanostructures. However, the long cycle time, high energy consumption, and high nitrogen emissions in traditional hot embossing approach hinders sustainable production of glass micro-optics. Therefore, this paper proposes a novel two-stage gravity-assisted hot embossing process that enables the fabrication of high-quality glass micro-pillar arrays in a rapid, green manner. In this approach, the two-stage gravity loading unit provides accurate force on glass preform through a simple control system, and the tailor-made heating module based on Si 3 N 4 ceramic heaters requires an energy consumption of just 700 kJ per molding cycle. As a result, the proposed approach is featured by low energy consumption and high manufacturing efficiency. In this study, the effects of the embossing temperature, force, and time on the replication accuracy of a K9 glass micro-pillar array were investigated through a series of hot embossing experiments. Afterward, the form accuracy, uniformity of microstructures, and warpage of glass replicas under the optimal process parameters were evaluated separately. Finally, repeated hot embossing experiments were conducted to demonstrate the reproducibility of the hot embossing process. The experimental results show that embossing temperature had the most significant effect on the replication accuracy of glass micro-pillars. By optimizing the process parameters, the embossed glass micro-pillars could achieve transfer ratios of 99.00% and 95.14% in height and diameter, respectively. Moreover, the surface roughness of glass micro-pillars was less than 5 nm, and the warpage amplitude of glass replicas in a 3.9 × 3.9 mm area was smaller than 1 μm. The small discrepancy in geometric features of glass replica in the repeated trails reflects the satisfactory reproducibility of this hot embossing process on the micro and nano scales. The results indicate the strong industrialization potential of the proposed two-stage gravity-assisted hot embossing machine and hot embossing process for fabricating high-quality glass microstructures more cleanly and sustainably. • A novel gravity-assisted rapid high-temperature hot embossing apparatus is developed. • A novel hot embossing process is designed for fabricating high-quality glass micro-pillar arrays in a cleaner manner. • Effects of process parameters on the replication accuracy of glass micro-pillar arrays are evaluated. • Form deviation, uniformity of microstructures as well as warpage of glass replica are analyzed. • The reproducibility in replicating geometric features in the novel hot embossing process is demonstrated. [ABSTRACT FROM AUTHOR]

The improvement of energy efficiency of products is a key pillar of climate and energy strategy in the European Union (EU). The first EU product policies were adopted in the late 1970s, and they have evolved to become a coherent set of implementing measures under framework directives that harmonise and refine the regulatory process. After years of weak implementation, considerable progress in terms of scale and ambition has been achieved in the last decade. In 2020, product mandatory measures covered 50% of the EU total final energy consumption, leading to 46 Mtoe energy savings. This paper describes the available policy instruments to promote energy efficiency and remove the market barriers hindering the penetration of the best performing technologies. It offers a review of the progress made over these last 40 years of EU product policies, describing the Energy Labelling, the Minimum Energy Performance Standards (MEPS), the Ecodesign Directive and the voluntary agreements (EU Ecolabel and Green Public Procurement). Moreover, it highlights the remaining challenges and provides policy recommendations to further exploit the EU potential to save energy from products. • Energy efficiency in products is a key pillar of EU climate and energy strategy. • Despite 40 years of EU product policies, their scale has only improved since 2010. • In 2020, mandatory measures covered 50% of the EU final energy consumption. • By 2030, savings expect to reduce the final consumption by 17%. • Policy orientation to further exploit the energy savings of products is provided. [ABSTRACT FROM AUTHOR]

The increasing energy demand in harbour areas, coupled with the need to reduce pollutant emissions, has led to the development of renewable energy-based polygeneration systems to face the carbon footprint of ports and ships at berth. In this way, in the coming years, ports can be converted into modern energy hubs. From this point of view, this paper presents a new dynamic simulation model for assessing and optimizing the energy and economic impact of ports. Here, energy systems and renewable sources can be designed to be connected to national electricity and natural gas grids and can include also alternative fuels (hydrogen, biomethane, etc.) and thermal energy networks, as well as different biomass fluxes (to be exploited for energy aims). Energy availability/demands of near towns and port buildings/infrastructures, as well as on-shore power supply are also included in the dynamic assessments. Hourly weather data and different prices for all the considered energy carriers are taken into account hour by hour. A multi-objective optimization approach is also implemented in the model considering energy and economic indexes to be optimized. The whole model is implemented in a computer tool written in MATLAB. For showing the capability of the developed model, a novel case study referred to the port of Naples (South-Italy) is presented. Here, several renewable energy sources are considered, including an anaerobic biodigester for producing biogas from the organic waste of docked cruise ships. A combined heat and power system (fed by biogas) is implemented in the port energy hub also for supplying absorption chillers. PV panels, and marine power generators are also included. In the conducted analysis, optimization targets are the maximization of system self-consumption and self-sufficiency as well as the minimum simple payback period. The proposed system can effectively contribute to the decarbonization of the port energy demand and reduce harmful pollutant emissions. Results showed that very high rate of renewable energy produced on-site can be exploited (up to 84%) by the considered port facilities, ensuring increasing independency from utility power grid (self-sufficiency index up to 40%). By the obtained results and through the developed simulation/optimization tool, novel design and operating criteria can be achieved for future port energy hubs featured by renewables and bi-directional energy exchange between ships and port. [ABSTRACT FROM AUTHOR]

Public acceptance of sustainable energy innovations and policies is of crucial importance in enabling the transition to decarbonized energy systems necessary to meet the key climate targets of the Paris Agreement. This is particularly important in the context of the European Union, which is the third largest energy-related greenhouse gas emitter in the world. However, achieving acceptance is complex and requires improved understanding of the underlying conditions that are likely to motivate it. To contribute to this understanding and overcome common shortcomings in the literature, this paper presents a multidimensional and cross-national framework for the factors that have the potential to motivate both dimensions of acceptance, namely adoption and support. The innovations of interest are numerous and include electric vehicles, residential solar panels, energy-efficient home insulation, environmental taxes and incentives. The paper employs multilevel regression analysis and combines individual and contextual data from all the European Union nations to demonstrate the significance of various types of predictors in motivating acceptance. It is found that citizens' personal capabilities and attitudes towards life satisfaction, climate change and the environment influence both dimensions of acceptance. Attitudes towards broader socio-political dimensions such as representation, equity and transparency primarily influence support, whereas national environmental and energy policy indicators primarily influence adoption. Overall, this paper provides evidence suggesting governments should simultaneously address both dimensions of acceptance, through a combination of different means: enhancing support through strategies that target attitudes and preferences, and market-based environmental policies that promote adoption at the household level. • A comprehensive framework to explore citizen adoption and support of energy innovations • Both technological and economic innovations are investigated • Combining individual and contextual data from all the European Union nations • Market-based policies and citizen attitudes to climate change affect technology adoption • Attitudes to socio-political dimensions affect support for renewables and environmental taxes [ABSTRACT FROM AUTHOR]

The promotion of modern industrialization has caused heavy environmental pollution. Environmental protection is a basic national policy of China. In 2011, China began to implement the "Twelfth Five-Year Plan for National Environmental Protection" (12th FYP_NEP). Using the survey data of small and medium-sized enterprises (SMEs) in Shandong Province of China, this paper empirically explores the impact of 12th FYP_NEP on the energy utilization and operating efficiencies of SMEs. It is found that the environmental policy "12th FYP_NEP" has a significant incentive effect on both efficiency performance of Chinese SMEs, and has a greater positive impact on operating efficiency. Our heterogeneity analysis showed the following results. The incentive effect is different in different industries and enterprises of different sizes. The policy "12th FYP_NEP" has a greater positive impact on the energy utilization efficiency of SMEs in China's first and second tier cities, but it has no significant impact on their operation efficiency. This shows that SMEs in first and second tier cities are more effective in coping with the national environmental policy reform strategy. It can be seen that the promulgation of China's environmental policies can significantly improve the energy utilization awareness of these SMEs. The incentive effect of the policy on the two efficiency performances of SMEs in cities with "heavy air pollution" is greater, indicating that the implementation effect of "12th FYP_NEP" on SMEs in such cities is better. The enlightenments are as follows: the current situation of Chinese SMEs is that the energy utilization efficiency is low, while the operating efficiency is high. Most enterprises attach great importance to their own operating profits and economic development, and the awareness of energy utilization needs to be greatly strengthened. "12th FYP_NEP" has obvious positive effect on the energy utilization and operating efficiencies of SMEs, but there are slight differences among different types of enterprises. It is suggested that governments can refine their own environmental regulation standards and implement different environmental regulations for different types of enterprises, so as to enhance the performance of domestic enterprises most effectively. • This paper used the China survey data on SMEs over the period 2010–2013. • It is found that the Chinese "12th FYP_NEP" has a significant incentive effect on efficiency performance of Chinese SMEs. • The incentive effect is different in different industries and enterprises of different sizes. • The policy makes for improving the energy efficiency of SMEs in first and second-tier cities and heavy-polluted cities. • Chinese SMEs should attach great importance to energy utilization rather than operating profits only. [ABSTRACT FROM AUTHOR]

This paper aims to develop an optimal real-life energy-efficient design for a production plant within the concept of the circular economy. The problem is to install a Heat Recovery System (HRS) that utilizes the hot oil used by the compressors to heat the water for the central heating system. To achieve the desired level of energy efficiency this design problem must be formulated from both the optimization and sustainability points of view. Additionally, this design problem must also consider the investment cost. In line with this purpose, this paper formulates this design problem as an optimization problem employing a mathematical programming approach as a single objective, and as a multi-objective optimization problem through a goal programming approach. Besides, this paper uses the return on investment as a key performance indicator, since it deals with a real-life design problem with an investment cost. The related design problem is solved with the single objective and multi-objective versions of the developed mathematical programming model via a commercial solver to identify different design alternatives and hence giving the decision-maker to make a selection option. Finally, the capability of the developed mathematical programming model is tested on a set of randomly generated problems. The obtained results indicate that the developed mathematical programming model is a successful decision support system since its single and multi-objective versions are capable of identifying energy-efficient production designs within the context of the real-life problem on hand and the circular economy. • A real-life energy-efficient design problem for a production plant is undertaken. • A heat recovery system is proposed within the concept of a circular economy. • The problem is modelled from both the optimization and sustainability aspects. • The problem is formulated as multi-objective models using goal programming. • The models are solved to minimize investment costs and maximize energy efficiency. [ABSTRACT FROM AUTHOR]

High-efficiency buildings do not only save energy but also have multiple further impacts or co-benefits. These impacts are often excluded from the policy evaluation partly because their quantification and integration into cost-evaluations have challenges. Thus, the purpose of this paper is to develop a method to quantify labour productivity which is one of the key multiple impacts, as well as demonstrate the use of the method for calculating the productivity impacts of high-efficiency buildings. The paper uses Germany and Hungary as examples to conduct the quantifications. The result of the study shows that high-efficiency buildings can result in substantial health and labour productivity benefits. Concretely, a German worker can gain 5.2 productive days a year, while a Hungarian 2.2 days by avoiding sick days, after living in high-efficiency buildings. Similarly, through high-efficiency retrofits or high-efficiency new constructions in the tertiary building sector, German and Hungarian workers can gain 2.4 and 1 productive days a year, respectively, by avoiding sick days. The monetary equivalent of the total number of days gained would be as high as 337 million and 7 million Euros/year only from the residential building sector, and 398 million and 3 million Euro/year from the tertiary building sector for Germany and Hungary respectively. In addition to the productive workdays gain, by avoiding mental stress, the German and Hungarian workforce can gain 95 and 2 million Euro respectively in a year by improving work performance from working in high-efficiency tertiary buildings. Furthermore, this paper shows that along with more workdays and improved work performance, both Germany and Hungary can gain 1870 and 3849 healthy life years/million population which is equivalent to 277 and 134 million Euros per year respectively. The findings of this study would provide a strong motivation to the policymakers to design policies that promote construction and renovation of buildings at the passive-house or NZEB standards. The substantial productivity impacts of high-efficiency buildings can be an entry-point for the policymakers as any policy that promote high-efficiency buildings would fit in well in the multi-objective policy framework of the European Union. • High-efficiency buildings can obtain substantial health and productivity benefits. • A novel methodological approach to quantify labour productivity is demonstrated. • High-efficiency buildings result in more active workdays by minimizing health risk. • Substantial monetary gain can be obtained from the productivity benefits. • Findings can motivate policies to implement more high-efficiency buildings. [ABSTRACT FROM AUTHOR]

Interactions between government and industry have the characteristics of leader-follower games. To protect the environment, the government uses regulations and economic instruments to indirectly influence operational and investment decisions in industry. The government needs to calibrate its policies while considering industry's self-interested, cost-minimizing reactions. In this paper, a leader-follower model is developed as a bilevel mixed integer linear program for the selection of carbon emissions mitigation measures. It is assumed that the government sets the emissions reduction target, percentage subsidy for mitigation measures, and economic penalty for excess carbon emissions; in response to these policies, industry then chooses mitigation measures to be implemented. The model is demonstrated with a case study on maritime shipping emissions, where a heuristic solution is identified using a fuzzy interactive optimization algorithm. The solution achieves 11.5% reduction in emissions through the implementation of six mitigation measures, of which only one is subsidized. General implications of these results for decarbonization policy are also discussed. [Display omitted] • A bilevel optimization model for industrial decarbonization portfolios is developed. • Government-industry interaction is modelled as a Stackelberg game. • The model is demonstrated on a maritime carbon emissions reduction case study. • Implications for policy development and engineering decision-making are discussed. [ABSTRACT FROM AUTHOR]

Operations of Automated Guided Vehicles (AGVs) are desired to be more energy-efficient while maintaining high transport productivity, motivated by the green production requirements. This paper investigates a new energy-efficient planning problem for determining conflict-free paths of the AGVs in its transport roadmap. In this problem, the vehicle path and transport time in the roadmap are jointly optimized, based on a flexible time–space network (FTSN). We provide the mathematical problem formulation of the energy-efficient path planning problem. The resulting optimization problem is proved to be a non-convex mixed-integer nonlinear programming which is computationally intractable. We further propose a hybrid metaheuristic that integrates the genetic algorithm and estimation of the distribution algorithm to improve its computational efficiency. Numerical results show the effectiveness of the developed algorithm based on the FTSN framework, compared to the existing metaheuristics, the conventional path planning method, and a commercial solver. The proposed method has a wide application in improving energy use of material handling, providing a guiding significance on promoting cleaner production of flexible manufacturing systems. • We investigate conflict-free and energy-efficient path planning of AGVs. • We propose an MINLP model to optimize productivity and energy consumption jointly. • A customized hybrid metaheuristic is developed to improve computational efficiency. • The proposed method reduces energy consumption without decreasing productivity. [ABSTRACT FROM AUTHOR]

Transformations in the agri-food system since the early 19th century have led to an unprecedented increase in food production. However, the structure of this system has generated many negative environmental and social impacts that threaten the sustainability at the local, regional and global scale. This situation entails the need for an agroecological transition that leads to an agri-food model that is aware of the planetary boundaries and guarantees the reproduction of human and all other forms of life. Agroecology is crucial for the Mediterranean, where the negative environmental and social impacts of industrial agriculture are particularly evident. The aim of this paper is to present a best practice viticulture farming that is in an advanced level of agroecological transition in the region. The results show that the energy efficiency of this agroecosystem is greater to conventional farms in the region, while generating similar financial returns but more equally distributed than the big agro-industrial companies in the sector. Based on this best practice case study, we provide several methodological and practical insights on the energy balance of the farm system, supplemented by data on the value-added distribution from wholesaler selling back to the industrial winemaking and vine-growing incomes, and the final financial returns of the company. The results highlight the need of multifactorial analyses that contribute to a systemic perspective on the synergic elements and leverage points for scaling-up the agroecological transition of Mediterranean viticulture. • Mediterranean best practice viticulture farming towards agroecological transition. • Circular economy of this farm system is greater to conventional farms in the region. • Practical insights contribute to the global debate on the agroecological transition. • These insights refer to both the energy and the cash balances of the farm system. [ABSTRACT FROM AUTHOR]

Nowadays, China's economy and energy structure are deeply adjusting to the direction of low-carbonization and non-carbonization with unprecedented efforts. This paper considered carbon emissions and energy endowments, adopted SBM-Undesirable model and spatial Durbin model to calculate the energy efficiency of 30 provinces and municipalities in China from 2015 to 2019 and analyze the direct effect, indirect effect and total effect on energy efficiency of 7 variables. Empirical results show that: Energy efficiency has spatial positive correlation and agglomeration characteristics; The main influencing factor of China's energy efficiency is energy consumption structure; Regions with strong energy endowment bear the environmental pollution cost of energy consumption areas in China; Environment Kuznets Curve (EKC) exists in China, but different provinces and municipalities are distributed in disparate stages; Research and development (R&D) investment only affects local energy efficiency, and has no spillover effect on surrounding areas in China; Foreign direct investment (FDI) has negative impacts on China's energy efficiency, and there is a phenomenon of pollution paradise. The valuable conclusions obtained in this study deepens the insights about the influencing factors of China's energy efficiency under the constraints of carbon emission and energy endowment. Energy efficiency has spatial positive correlation and agglomeration characteristics; The main influencing factor of China's energy efficiency is energy consumption structure; Regions with strong energy endowment bear the environmental pollution cost of energy consumption areas in China; Environment Kuznets Curve (EKC) exists in China, but different provinces and municipalities are distributed in disparate stages; Research and development (R&D) investment only affects local energy efficiency, and has no spillover effect on surrounding areas in China; Foreign direct investment (FDI) has negative impacts on China's energy efficiency, and there is a phenomenon of pollution paradise. [Display omitted] • Energy efficiency has spatial positive correlation and agglomeration characteristics. • Energy consumption structure mainly affects energy efficiency. • Environment Kuznets Curve exists in China. • "Pollution paradise hypothesis" exists in foreign direct investment. • Environmental pollution is transferred to surrounding provinces through resource trades. [ABSTRACT FROM AUTHOR]

Interactive data visualization tools for residential energy data are instrumental indicators for analyzing end user behavior. These visualizations can be used as continuous home feedback systems and can be accessed from mobile devices using touch-based applications. Visualizations have to be carefully selected in order for them to partake in the behavioral transformation that end users are encouraged to adopt. In this paper, six energy data visualizations are evaluated in a randomized controlled trial fashion to determine the optimal data visualization tool. Conventional visualizations, namely bar, line, and stacked area, are compared against enhanced charts, namely spiral, heatmap, and stacked bar, in terms of effectiveness, aesthetic, understandability, and three analysis questions. The study is conducted through a questionnaire in a mobile application. The application, created through React Native, is circulated to participants in multiple countries, collecting 133 responses. From the received responses, conventional plots scored higher understandability (by 22.74%), effectiveness (by 13.44%), and aesthetic (by 10.54%) when compared with the enhanced visualizations. On the flipside, enhanced plots generated higher correct analysis questions' responses by 8% compared to the conventional counterparts. From the 133 collected responses, and after applying the unpaired t-test, conventional energy data visualization plots are considered superior in terms of understandability, effectiveness, and aesthetic. • Distributed a questionnaire about energy data visualization built in a mobile app. • Enhanced charts in the energy field have been created. • Comparison between enhanced and conventional energy visualization charts is applied. • Quantitative and qualitative questions asked in the questionnaire. • Received 133 participants' responses from multiple countries. [ABSTRACT FROM AUTHOR]

Compressed air systems have a high energy transfer capacity. They are widely used in the manufacturing industry due to being clean, dependable, and simple-to-use. On the other hand, these systems are among the most significant energy consumers in the manufacturing sector because they are inefficient with high electricity usage and high CO 2 emissions. As a result, all kinds of the energy efficiency enhancements in these systems promote cleaner production by lowering total energy consumption and CO 2 emissions in factories. In this paper, the energy-saving potential and carbon emissions of Compressed Air Systems are investigated using data from in-situ energy audits. A simple set of equations is proposed to calculate the mass flow rate of air leakage. The sound intensity (dB) obtained from ultrasonic flow measurements were used as the input of the equation set. Furthermore, two new Energy Performance Indicators have been proposed to guide energy audit evaluation and continuous monitoring of the energy efficiency of Compressed Air Systems in industrial facilities. The new evaluation criteria "Specific Compressed Air Savings" and "Specific Leakage Savings" provide a comparison tool to help decision-makers with their compressed air system investment decisions. Using the "Specific Compressed Air Savings" and "Specific Leak Savings" parameters, the analysis method is demonstrated for an example industrial plant. The facility's specific compressed air and leakage savings are calculated as 0.0067 TOE/ton and 0.0035 TOE/ton, respectively. [ABSTRACT FROM AUTHOR]

In the natural stone sector, rock blocks are cut as a plate using block-cutting machines (BCM), and the plates are polished in the polishing machines. Energy consumption is the primary operating cost in both the cutting and polishing processes. The energy consumption of BCMs is affected by many factors, with the most influential being traverse speed. The energy efficiency of BCMs can be improved by regulating the traverse speed throughout the cutting process, and the roughness of the cut surface can be reduced by keeping the ratio between the traverse speed and peripheral speed constant as an additional benefit. This also reduces energy consumption and waste production in the polishing process. In this paper, two controllers used for the regulation of traverse and peripheral speeds are applied to a laboratory-scale BCM, one of which regulates only the traverse speed, while the other regulates both the traverse and peripheral speeds. A limped hierarchical fuzzy logic controller (LHFLC) approach is used in the design of the controllers for the first time on the BCM. In the proposed LHFLC method, the design procedure of the controller is simplified, and its memory usage, computational load, and response time are decreased. The performance of the controllers (a three-input/one-output (3I1O) FLC, 3I1O LHFLC, and a three-input/two-output (3I2O) LHFLC) was tested with cutting experiments performed on three rock samples (Bilecik Beige limestone, Uşak Green marble, and Afyon travertine), and the acquired results reveal that the proposed controllers (3I1O LHFLC and 3I2O LHFLC) are more efficient than the previous controller (3I1O FLC), with over 21%. A statistical analysis shows that to improve the energy efficiency of the BCM, the 3I1O LHFLC could be used rather than the 3I1O FLC. It is further noted that statistically, the cutting rate can be kept more constant with the 3I2O LHFLC than with the 3I1O LHFLC, meaning that the surface roughness of the plates produced by the BCM can be reduced using the 3I2O LHFLC. [Display omitted] • The energy efficiency of the block-cutting machine (BCM) was improved by regulating traverse speed throughout the process. • A limped hierarchical fuzzy logic controller (LHFLC) was used to regulate the traverse speed for the first time on a BCM. • With the LHFLC, the energy consumption of the BCM was reduced by at least 20%. • The cutting rate of the BCM was kept constant through the regulation of both the traverse and saw blade speeds. • Energy consumption and waste production can be reduced in the polishing process keeping the constant cutting rate of the BCM. [ABSTRACT FROM AUTHOR]

In the German industry Heating, Ventilation and Air Conditioning (HVAC) systems account for 11 %–20 % of the final energy consumption. Usually HVAC systems are dimensioned based on static extreme values and thus during most of the operation time, HVAC systems tend to be overdimensioned. In addition, the extensive literature review of 40 papers shows that often topics on model-based energy efficiency improvement are commonly performed for office or residential buildings, but rather rarely for production environments. Furthermore, the performance of control schemes for energy efficiency improvement are rarely compared with each other or incompletely compared with each other. In this publication, we use the framework of a Cyber–Physical Production System (CPPS) to compare the performance of four main control schemes, ranging from simple time-based control to model-predictive control, which has not been done in the context of battery production before. Over a fixed observation period, the four control schemes are transparently compared with each other in a case study using the example of the Battery LabFactory Braunschweig (BLB). Compared to the initial state, a significant reduction in final energy demand can be achieved with all examined control approaches, which is even up to 37.29% in case of the model-predictive control. Surprisingly, even simple control approaches, without any predictions, have a good energetic saving potential of up to 20.22% compared to the initial state, which is why they are initially recommended for practical implementation. Moreover, we publish all source code of the control schemes, in order to encourage the implementation of energy efficiency measures in further applications not restricted to battery production. • Comparison of control schemes for energy efficiency improvement of HVAC systems. • Considering scheduled to model-predictive control applied to battery production. • Best control scheme achieves energetic reduction of up to 37.29% in case study. • Control scheme approaches transferable to other cases outside of battery production. • Publication of source code to encourage implementation of efficiency measures. [ABSTRACT FROM AUTHOR]

Room air conditioners (RACs) are one of the high energy-consuming home appliances. Developing a smart solution to evaluate and track the efficiency of RACs is essentially useful for residents to make necessary maintenance or replacement decisions. While smart meters are increasingly installed to monitor electricity use, the application of smart meter data to evaluate the RAC efficiency remains inadequate. In this paper, we present a data-driven framework to identify non-inverter window RACs with low energy efficiency by analyzing smart meter data from the university student hall rooms. In this framework, we first applied the extreme gradient boosting (XGBoost) method to predict a RAC's hourly electricity consumption. Then we measured the effect of outdoor temperature on the XGBoost prediction of hourly RAC electricity consumption using the Shapley Additive Explanation method to interpret the RAC's efficiency. We conjectured that the RAC efficiency is normal if the predicted hourly electricity consumption is significantly correlated with the outdoor temperature. In contrast, the RAC efficiency is low if the outdoor temperature changes have little impact on the predicted electricity consumption. Finally, we applied the K-Means clustering algorithm to separate the RACs into the "low efficiency" and "normal efficiency" categories based on each's pattern of outdoor temperature's impact on electricity consumption. Our cross-validation result showed that the XGBoost model can achieve an average R2 score of 0.50 and an average root mean squared error of 0.20 kWh. We used RAC replacement records to validate our framework of interpreting the RAC's efficiency. On average, RACs having low efficiency consumed 25.69% more electricity per hour. Overall, our data-driven framework can contribute to extending the value of smart meters for RAC efficiency evaluation. Meanwhile, the smart meter data-driven framework can be improved, and more validation is needed in the future. • We created a data-driven framework to assess the room air conditioner's efficiency. • An XGBoost model was developed for hourly electricity consumed by air conditioners. • We clustered air conditioners based on Shapley value of outdoor temperature. • Air conditioners with low efficiency were identified and validated from clustering. • Identifying air conditioners with low efficiency can save electricity. [ABSTRACT FROM AUTHOR]

Energy efficiency based on behavioral change has attracted increasing interest in recent years, although, solutions in this area lack much needed techno-economic analysis. That is due to the absence of both prospective studies and consumer awareness. To close such gap, this paper proposes the first techno-economic assessment of a behavioral change-based building energy efficiency solution, to the best of the authors' knowledge. From the one hand, the technical assessment is conducted through (i) introducing a novel edge-based energy efficiency solution; (ii) analyzing energy data using machine learning tools and micro-moments, and producing intelligent, personalized, and explainable action recommendations; and (iii) proceeding with a technical evaluation of four application scenarios, i.e., data collection, data analysis and anomaly detection, recommendation generation, and data visualization. On the other hand, economic assessment is performed by examining the marketability potential of the proposed solution via a market and research analysis of behavioral change-based systems for energy efficiency applications. Also, various factors impacting the commercialization of the final product are investigated before providing recommended actions to ensure its potential marketability via conducting a Go/No-Go evaluation. In conclusion, the proposed solution is designed at a low cost and can save up to 28%–68% of the consumed energy, which results in a Go decision to commercialize the technology. • Techno-economic assessment of behavioral based energy saving systems. • Edge-based energy saving using artificial intelligence and micro-moments. • Anomaly detection and explainable recommender systems for energy monitoring. • Market assessment and commercialization strategy considerations. • Market barriers and market drives of buildings energy efficiency solutions. [ABSTRACT FROM AUTHOR]

This paper investigates the energy service companies (ESCOs) in China from the perspective of technological capability (TC) development. The conventional capability development model of manufacturing in emerging economies has been adapted to examine the four dimensions of TC (investment, production, linkage and innovation) through a qualitative analysis of multiple case studies. Small and medium-sized private ESCOs can perform well based on investment and production capabilities to develop energy management software competence. Large state-owned ESCOs can develop more advanced linkage and innovation capabilities and serve large-scale businesses with more specialist services. For small and medium-sized ESCOs, competitiveness, customers and related business strategy are the primary drivers of TC development. These drivers are essential for large ESCOs, but government support and pressure are also important. The framework developed can be used to research ESCOs and other service providers in other developing countries. • Energy Service Companies have different levels of technological capabilities. • The development of these capabilities is driven mainly by internal factors. • The basic technology level depends on investment and production capabilities. • Development starts with the investment and production of simple technologies. • The advanced technology level requires linkage and innovation capabilities. [ABSTRACT FROM AUTHOR]

The increasing global consumption of energy and its negative impacts on the environment has been an issue discussed both by academics and practitioners, including in the health sector. Hospitals are major consumers of energy, which leads to increased operating costs, decreased competitiveness, and negative environmental impacts. Energy management in hospitals must be understood as a way to contribute to environmental sustainability and as a way to improve competitiveness. Therefore, the objective of this paper is to propose guidelines for efficient and sustainable energy management in hospitals, developed based on the literature review, the challenges faced and the good practices of sustainable energy management in the hospitals studied, the cross analysis of the case studies, and the authors' expertise. As a result, the eight proposed guidelines are related to culture change, energy consumption management, energy management standard, purchase of renewable energy, green technologies, sustainable hospital buildings, social responsibility programs focused on energy use, and sustainable energy public policies. These guidelines contribute in an applied/managerial way to help managers of public and private hospitals overcome the challenges of energy management and contribute to UN's SDG7 due to its potential to improve energy efficiency and environmental performance, therefore, being a movement towards clean energy. This study also theoretically/scientifically contributes to the academic debate since the empirical findings found in the hospitals studied and the proposition of guidelines deepen and expand the key elements identified in the literature on efficient energy management in hospitals, providing the basis for developing new research on the subject. Energy management in hospitals is discussed from the perspective of sustainability. Challenges need to be overcome for sustainability benefits to be achieved. This work can assist public and private hospitals in developing sustainability. Guidelines for sustainable energy management in hospitals are proposed. [ABSTRACT FROM AUTHOR]

The super efficiency slack-based measure (SBM) with undesirable outputs was used in this paper to determine the energy efficiency of the service industry in various provinces from 2007 to 2017. The different characteristics of the energy efficiency of service industry in different provinces were obtained from the perspective of heterogeneous resource endowment. The findings show that: ⅰ) China's service industry's overall energy efficiency fluctuates in a 'W' shape. Provinces with varying resource endowments demonstrated significant variation in energy efficiency. Provinces with a high concentration of technology and energy had the highest and lowest levels, respectively, indicating an upward and downward trend. ⅱ) Energy efficiency improvements in China's service sector were primarily a result of technological advancements. Technological advancement and technical efficiency were the primary causes in technology- and labor-intensive provinces, respectively, whereas the combined effect of both factors was the primary cause in energy-intensive provinces. ⅲ) Foreign investment and environmental regulation may both contribute to the improvement of energy efficiency in the service industry, while energy structure and government intervention may work against it. Additionally, a U-shaped relationship was observed between the service industry's development level and energy efficiency. As a result, policymakers should develop targeted promotion strategies based on the resource endowment and development stage of the service industry in various provinces. • Undesirable super efficiency SBM model and Malmquist–Luenberger index are used. • China's service industry's overall energy efficiency fluctuates in a 'W' shape. • Static and dynamic analysis of the service industry's energy efficiency is provided. • The service industry's energy efficiency in provinces with different resource endowment is heterogeneous. [ABSTRACT FROM AUTHOR]

Given their increasing number and the implementation of more energy-intensive treatment methods, wastewater treatment plants (WWTPs) expect to increase energy consumption. In addition, climate change presents new challenges to the operation of these facilities, thus being critical to understand how to improve their energy performance and environmental sustainability while ensuring the quality of service provided. This paper reviews the latest publications on the energy performance of municipal WWTPs, particularly on the different phases of the treatment process and the impacting factors. The contextual and underlying factors that influence energy performance were identified, categorized, and analyzed through a broad survey. The most significant factors are the plant size, load factor (plant capacity utilization), and dilution factor. The implementation of anaerobic-anoxic-oxic systems is considered suitable in sensitive areas requiring high pollutant and nutrient removal rates, presenting, in some cases, moderate energy consumption (0.267 kWh/m3), being similar to the conventional activated sludge (0.269 kWh/m3). In more stringent effluent quality requirements, such as wastewater reuse, membrane bioreactors are advised, despite higher consumption (0.33 kWh/m3). Energy improvements can also be achieved by implementing automatization, inverters, and strategies that increase flexibility and adaptability in the operational process. Lastly, given the multidimensional characteristics of the WWTPs assessment, further improvements may be identified if the energy performance of these plants is compared using holistic and multi-criteria approaches, integrating multiple inputs and outputs simultaneously. • Long-term operation of low installed power equipment deserves more attention. • Energy intensity is mainly influenced by plant's size, load, and influent dilution. • Anaerobic-anoxic-oxic systems are a good option for impoverished areas. • Energy performance must be assessed in a holistic and multi-criteria approach. [ABSTRACT FROM AUTHOR]

Buildings contribute to about 40% of direct and indirect greenhouse gas emissions and more than a third of energy consumption globally. Sustainable building standards and efficiency standards are two measures to reduce such emissions and energy consumption in buildings. While better standards improve the sustainability of new buildings, the impact of these actions depends on the ability to improve the existing building stock. Understanding the dynamics of adopting efficiency and sustainable building measures is essential for setting policy targets and mechanisms. This paper proposes a system dynamics model for assessing the energy savings potential from adopting sustainable building and energy efficiency measurements in buildings in systems with incomplete and uncertain information, using prospective scenarios. The model combines a dynamic diffusion model with an aggregate model for the building stock. The model is calibrated for estimating energy savings in the residential and commercial building stock of the four main metropolitan areas of Colombia: Bogotá, Medellín, Cali, and Barranquilla. Simulation results show that the maximum energy savings potential is approximately 12% but could be below 8% if rebound effects are considered. Results show that energy savings are limited if there are no policies for existing old buildings. [Display omitted] • We developed a system dynamics model for adoption of sustainable buildings standards. • The model estimates the potential energy savings at the city level. • We used the model for testing different scenarios in four Colombian cities. • Current Colombian standards should be extended to consider an old-buildings policy. • Colombian policies require city-specific incentives and planning. [ABSTRACT FROM AUTHOR]

Improving the efficiency of building energy systems is crucial to reach a goal related to the high – performance building, particularly in the space heating and air - cooling domain, which are considered as leading energy consumption systems in buildings. Current trends in the smart building paradigm allowed efficient implementation of user-centric approach in personal thermal comfort modelling. The potential technological solutions in that sense can bring various benefits leading towards improvement of the building energy performance. Existing papers published in the Scopus and Web of Science database have been reviewed in order to investigate a state of the art related to experimental practices in the development and application of monitoring technologies for personal thermal comfort. Consequently, the work brings insights in some of the main research findings in the area focusing on (I) inputs that affect personal thermal comfort, (II) smart technologies and methods used for sensing and the detection of defined inputs and (III) insights into the approaches of collected data processing. Parameters considered in reviewed literature rely on environmental and personal variables. Based on the conducted review, it can be indicated that room air temperature, relative humidity, air velocity and mean radiant temperature (MRT) are frequently used environmental parameters in thermal comfort modelling. Among user – related indicators in the considered literature, skin temperature (hands, face) and metabolic rate (MET) are found to be the most common, followed by clothing insulation (CLO) and heart rate data. Some additional parameters are also found to be influenced by thermal comfort of individual (skin conductance, brain activity, heat flux, sweat rate, aural temperature, body core temperature). Subjective response from users is still unavoidable and recorded through questionnaires. The results of review indicated that technological solutions for detection of thermal comfort parameters in data-driven models are mainly based on network of connected sensors, and can be divided into camera-based technologies, wearable devices and connected sensor systems. Finally, open questions and gaps that inquire further research were also detected and discussed in detail. [Display omitted] • Personal thermal comfort monitoring relies on connected sensors, recording and wearable devices. • The readings from sensing devices highly sensitive on specific position on the human body. • Skin temperature and metabolic rate direct indicators of personal thermal comfort. • Data processing methods request further investigation towards proper categorization. [ABSTRACT FROM AUTHOR]

The mitigation of climate change is the main issue for environmental policymakers. A large number of authors analysed the impact of various factors on greenhouse gas (GHG) emissions. In this paper, we proposed a multiplicative approach to use 2- and 3-way interactions simultaneously in order to analyse the effects of energy efficiency, renewable energy and sector mix as the moderators that shape the economic activity – environmental degradation nexus. The results encompassing global panel data show that the turning point increased from 1990 to 1995 to 2002–2007 and decreased afterwards. Considering the analysis of moderators, a high share of agriculture and industry sectors make the curve flat with a positive slope and a high level of economic activity was associated with more GHG emissions with no turning point. The marginal effect of energy efficiency to reduce the negative impact of agriculture and industry sectors was growing. Meanwhile, the marginal effect of renewables to reduce the negative impact of agriculture and industry sectors was diminishing. Service sector and energy efficiency, service sector and renewables worked as the substituting forces reducing GHG emissions with a diminishing marginal rate of substitution. Therefore, this study confirms that the economic activity – environmental degradation relationship is very complex and further studies should consider the role of the moderators of this nexus. [Display omitted] • Technique, composition effects should be considered as moderators of HGH emissions. • The multiplicative approach was applied to model interactions of GHG factors. • Agriculture, industry sectors made the economic activity GHG emissions curve flat. • Marginal effect of renewables to reduce GHG emissions was diminishing. • Service sector and renewables worked as substituting forces reducing emissions. [ABSTRACT FROM AUTHOR]