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The purpose of this paper is to identify the impact of traditionally unmonitored energy sources and sinks on assessment of the as-built thermal performance of occupied homes. The analysis aims to demonstrate the potential scale of uncertainties introduced in a heat balance estimation of the heat transfer coefficient (HTC) when using in-use monitored data.

Energy flows for two UK homes – one a 1930s dwelling with high heat loss, the second a higher-performing 2014-built home – are predicted using the UK Government’s standard assessment procedure (SAP) and visualised using Sankey diagrams. Selected modelled energy flows are used as inputs in a quasi-steady state heat balance to calculate in-use HTCs as if from measured data sets gathered in occupied homes. The estimated in-use HTCs are compared against SAP-calculated values to illustrate the impact of including or omitting various heat sources and sinks.

The results demonstrate that for dwellings with low heat loss, the increased proportion of heating demand met by unmetered internal and solar gains informs a greater sensitivity of a heat balance estimation of the HTC to their omission. While simple quasi-steady state heat balance methods may be appropriate for dwellings with very high heat loss, alternative approaches are likely to be required for those with lower heat loss.

A need to understand the impacts of unmetered heat flows on the accuracy with which a building’s thermal performance may be inferred from in-use monitored data is identified: this paper illustrates the scale of these impacts for two homes at opposite ends of the energy performance scale.

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

This paper focuses on the unconditionally optimal error estimates of a linearized second-order scheme for a nonlocal nonlinear parabolic problem. The first step of the scheme is based on Crank–Nicholson method while the second step is the second-order BDF method.

A rigorous error analysis is done, and optimal L² error estimates are derived using the error splitting technique. Some numerical simulations are presented to confirm the study’s theoretical analysis.

Optimal L² error estimates and energy norm.

The goal of this research article is to present and establish the unconditionally optimal error estimates of a linearized second-order BDF finite element scheme for the reaction-diffusion problem. An optimal error estimate for the proposed methods is derived by using the temporal-spatial error splitting techniques, which split the error between the exact solution and the numerical solution into two parts, that is, the temporal error and the spatial error. Since the spatial error is not dependent on the time step, the boundedness of the numerical solution in L∞-norm follows an inverse inequality immediately without any restriction on the grid mesh.

Background: The COVID-19 pandemic has impacted global food systems and consumer eating habits. The current study explores how country of origin and ethical status information impacts attitudes toward food.

Methods: A within-subjects survey design explored how perceptions of food safety/risk, animal welfare, deliciousness, purchase intention, energy density, carbon footprint of three foods (chicken, pasta, apples) are influenced by country of origin and ethical status information (UK, EU, China, USA, Fairtrade, Organic). Data were collected from 701 UK-based participants using an online survey from the 25-30th March, following the UK lockdown (23 March 2020).

Results: Perceptions of food safety, animal welfare, purchase intention, deliciousness and carbon footprint are influenced by origin and ethical status information. Chicken from the USA and China is perceived to be higher risk and have lower animal welfare standards. Apples from the USA and China are perceived to be higher risk. Pasta from China is perceived to be higher risk. Energy density estimations are not influenced by origin and ethical status information.

Conclusions: Consumer perceptions are influenced by country of origin and ethical information; foods from China are perceived least favourably, followed by foods from the USA; foods from the UK, EU, Organic or Fairtrade are perceived more favourably. The impact of origin and ethical information varies by food type with the perception of some foods appearing less susceptible to influence. These findings have implications for post COVID-19 (and post Brexit) food system, trade policy and public trust, and highlight the need for communication of food safety.

The purpose of this paper is to develop an integrated theoretical framework for energy security concept and to shed light on the policies and strategies applied by the European Union countries to confront the challenges that faces them.

The research paper uses Regional Security complexes theory, which mainly developed in Copenhagen school for security studies, that founded by Barry Buzan. This school tried to clarify the untraditional security aspects, through expanding its scope by adding new dimensions than military perspective.

Despite the consolidated efforts exerted by the European Union to assure safe levels of energy security, and their continuous pursuit to be liberated from Russian energy over dependence, but the results are still limited.

The value of this research paper stems from the fact that it encompass the theoretical aspect by shedding light on all the developments occurred to energy security concept, in addition to the Empirical side, by analyzing various European energy security challenges and their confrontation strategies.

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

Egypt has set plans to transform into a green economy which requires major reforms in the waste sector as one of the most vital sectors crucial for this transformation. This study aims at inspecting the current status of the Egyptian waste sector to highlight the major policy reforms needed. Furthermore, it assesses the economic viability of establishing waste-to-energy (WtE) projects under the current regulations that govern the sector.

The study employed an inductive analytical approach to scrutinize the institutional and regulatory framework of the waste and WtE sectors. Furthermore, a novel techno-economic analysis was conducted to assess the profitability of a WtE plant that employs moving grate incineration technology.

The analysis of the waste sector revealed its deteriorating state and the dire need for immediate restructuring through more stringent regulations to establish an integrated waste management system (IWMS) that incorporates WtE technologies as well as a number of corrective actions that would help enhance the sector. Additionally, the techno-economic analysis revealed the need to amend the current WtE regulation to comprise a gate fee as an indispensable revenue stream for WtE projects.

This study is one of a few studies that uses a new technique of analysis to explore the potential role that WtE projects can play in Egypt as a part of an IWMS that aims at transforming the waste sector into a resource sector while providing a renewable and sustainable source of energy.

Presentation of the different industrial carbon linkages of India. The purpose of this paper is to understand the direct and indirect impact of these industrial linkages.

This study uses a hypothetical extraction method with its various extensions. Under this method, different carbon linkages of a block are removed from the economy, and the effects of carbon linkages are determined by the difference between the original and the post-removal values. Energy and non-energy carbon linkages are also estimated.

“Electricity, gas and water supply (EGW)” at 655.61 Mt and 648.74 Mt had the highest total and forward linkages. “manufacturing and recycling” at 231.48 Mt had the highest backward linkage. High carbon-intensive blocks of “EGW” plus “mining and quarrying” were net emitters, while others were net absorbers. “Fuel and chemicals” at 0.08 Mt had almost neutral status. Hard coal was the main source of direct and indirect emissions.

Net emitting and key net forward blocks should reduce direct emission intensities. India should use its huge geographical potential for industrial accessibility to cheaper alternative energy. This alongside with technology/process improvements catalyzed by policy tools can help in mitigation efforts. Next, key net-backward blocks such as construction through intermediate purchases significantly stimulate emissions from other blocks. Tailored mitigation policies are needed in this regard.

By developing an understanding of India’s industrial carbon links, this study can guide policymakers. In addition, the paper lays out the framework for estimating energy and non-energy-based industrial carbon links.

The purpose of this paper is to examine the effectiveness of an improved dummy variables control grey model (DVCGM) considering the hysteresis effect of government policies in China's energy intensity (EI) forecasting.

Energy consumption is considered as an important driver of economic development. China has introduced policies those aim at the optimization of energy structure and EI. In this study, EI is forecasted by an improved DVCGM, considering the hysteresis effect of energy-saving policies of the government. A nonlinear optimization method based on particle swarm optimization (PSO) algorithm is constructed to calculate the hysteresis parameter. A one-step rolling mechanism is applied to provide input data of the prediction model. Grey model (GM) (1, N), DVCGM (1, N) and ARIMA model are applied to test the accuracy of the improved DVCGM (1, N) model prediction.

The results show that the improved DVCGM provides reliable results and works well in simulation and predictions using multivariable data in small sample size and time-lag virtual variable. Accordingly, the improved DVCGM notes the hysteresis effect of government policies and significantly improves the prediction accuracy of China's EI than the other three models.

This study estimates the EI considering the hysteresis effect of energy-saving policies in China by using an improved DVCGM. The main contribution of this paper is to propose a model to estimate EI, considering the hysteresis effect of energy-saving policies and improve forecasting accuracy.

China is a major energy import powerhouse, its trade deals have significant impact on international energy trade and global energy markets. The purpose of this paper is to explore the role of energy in China’s preferential trade agreements (PTAs) and their impact on Chinese imports of oil, gas and coal.

An extended trade gravity model framework is applied to explore the dynamics of China’s annualized energy import flows from the 22 economies that have PTAs with it for the period 1995–2015.

The effect of PTAs on trade patterns varies across the product groups and agreement clauses. The dominant factor affecting trade flows of coal, crude oil and oil products is the average tariff level. Its impact is less significant for gas imports, which are more affected by policy arrangements represented by a PTA variable. The depth and scope of a PTA do not affect Chinese energy imports patterns.

This paper is focused on exploring the effect of China’s trade and foreign relations strategies on its energy imports through the prism of its PTAs. Estimating the direct impact of China’s initiatives in the areas of trade, investment, security, culture, etc., on its trade flows of energy products and other product groups using the methodological framework proposed in this study would contribute to better understanding of the issue.

The findings can assist both China and energy exporting countries that target Chinese market in better understanding the drivers of trade flows of energy products and design their PTA strategies accordingly.

This study applies the trade gravity model framework to assess the impact of specific components of preferential trade agreements – tariff reduction and depth and scope of agreement – on energy trade flows differentiated by product group.