Pre-industrial Levels Research Articles

Conferencia sobre cambio climático COP27: se necesita una acción urgente para África y el mundo

Wealthy nations must step up support for Africa and vulnerable countries in addressing past, present and future impacts of climate change. The 2022 report of the Intergovernmental Panel on Climate Change (IPCC) paints a dark picture of the future of life on earth, characterised by ecosystem collapse, species extinction, and climate hazards such as heatwaves and floods (1). These are all linked to physical and mental health problems, with direct and indirect consequences of increased morbidity and mortality. To avoid these catastrophic health effects across all regions of the globe, there is broad agreement—as 231 health journals argued together in 2021—that the rise in global temperature must be limited to less than 1.5oC compared with pre-industrial levels.

Development of a Control-Oriented Ignition Delay Model for GCI Combustion

Increasingly stringent pollutant emission limits and CO2 reduction policies are forcing the automotive industry toward cleaner and decarbonized mobility. The goal is to achieve carbon neutrality within 2050 and limit global warming to 2 °C (possibly 1.5 °C) with respect to pre-industrial levels as stated in both the European Green Deal and the Paris Agreement and further reiterated at the COP26. With the aim of simultaneously reducing both pollutants and CO2 emissions, a large amount of research is currently carried out on low-temperature highly efficient combustions (LTC). Among these advanced combustions, one of the most promising is Gasoline Compression Ignition (GCI), based on the spontaneous ignition of a gasoline-like fuel. Nevertheless, despite GCI proving to be effective in reducing both pollutants and CO2 emissions, GCI combustion controllability represents the main challenge that hinders the diffusion of this methodology for transportation. Several works in the literature demonstrated that to properly control GCI combustion, a multiple injections strategy is needed. The rise of pressure and temperature generated by the spontaneous ignition of small amounts of early-injected fuel reduces the ignition delay of the following main injection, responsible for the torque production of the engine. Since the combustion of the pre-injections is chemically driven, the ignition delay might be strongly affected by a slight variation in the engine control parameters and, consequently, lead to misfire or knocking. The goal of this work was to develop a control-oriented ignition delay model suitable to improve the GCI combustion stability through the proper management of the pilot injections. After a thorough analysis of the quantities affecting the ignition delay, this quantity was modeled as a function of both a thermodynamic and a chemical–physical index. The comparison between the measured and modeled ignition delay shows an accuracy compatible with the requirements for control purposes (the average root mean squared error between the measured and estimated start of combustion is close to 1.3 deg), over a wide range of operating conditions. As a result, the presented approach proved to be appropriate for the development of a model-based feed-forward contribution for a closed-loop combustion control strategy.

Transitional Climatic Risk Assessment of Indian Firms Listed in BSE 100

The global economies are battling the global climatic change, and so is India. By signing the Paris Agreement in 2015, India is one among the 196 countries trying to reduce greenhouse gas (GHG) emissions and reach the desired climatic temperature of 2°C above pre-industrial levels. During this global transition, the role of the financial sector is crucial and cannot be undermined. The purpose of this study is (a) to analyse the sustainable finance practices in India, (b) to analyse the physical climatic risk exposure that India is into, (c) to analyse the transitional climatic risk exposures faced by Indian firms, (d) to analyse the policy initiatives by Indian government and global reporting standards on sustainability and, finally, (e) to perform a climate scenario analysis using the Paris Agreement Climate Transition Assessment (PACTA) model to materialize the transitional climatic risks faced by Indian firms in BSE 100. The study uses an inductive approach for its analysis. The study addresses few issues related to sustainable finance practices in India and questions the credibility of the sustainable reporting practices. The findings of this study evidently proves that Indian firms are not prepared to align themselves with climate-oriented investment plans for the future and insists for strong mandatory climate-relevant disclosure standards in India.

Change of Global Ocean Temperature and Decadal Variability under 1.5 °C Warming in FOAM

The rise in atmospheric CO2 concentration is regarded as the dominant reason for observed warming since the mid-20th century. Based on the Paris Agreement target, this research designs three conceptual pathways to achieve the warming target of 1.5 °C above the pre-industrial level by using the Fast Ocean Atmosphere Model. The three different scenarios contain one equilibrium experiment (equilibrium, EQ) and two transient experiments (never-exceed pathway, NE; overshoot pathway, OS). Then, we choose a ten year average that achieves 1.5 °C warming to calculate the climatology of the warming situation. Since OS achieves 1.5 °C twice, we obtain four warming situations to explore the response of ocean temperature. In 2100, the global ocean temperature increases over the global region, except the surface of the Southern Ocean. The difference in heat content mainly depends on the cumulative force of CO2 concentration. It is worth pointing out that during the increase in warming, the ocean surface temperature and heat content start to respond in different hemispheres. The weakening of decadal variability in the North Pacific and North Atlantic is robust in all three scenarios. However, there is a tremendous growth in the low-pass ocean surface temperature standard deviation in the Southern Ocean in EQ, which is different to NE and OS, and causes the increase in global mean total standard deviation. The shortening of decadal variability can only be seen from the EQ power spectrum, while NE and OS have similar power spectra with pre-industrial runs. It suggests that all previous studies that use equilibrium experiments data may have overestimated the shortening of decadal variability under global warming.

Population and GDP Exposure to Extreme Precipitation Events on Loess Plateau under the 1.5 °C Global Warming Level

To mitigate the adverse effects of climate warming, the Paris Agreement proposed the goal to reduce global warming up to an increase of 1.5 °C above the preindustrial level. Study of the population and GDP exposure to precipitation extreme events under the 1.5 °C warming target is fundamental for disaster risk mitigation and adaptation on the Loess Plateau. This study projected the population and GDP exposure to extreme precipitation events under the 1.5 °C global warming level on the Loess Plateau using daily precipitation data from CMIP6 outputs and population and GDP data under a Shared Socioeconomic Pathway 1(SSP1) 2.6 scenario. The population and GDP exposure were evaluated by combing the frequency and the areal coverage of the extreme precipitation events. Results show that population and GDP exposure to extreme precipitation events on the Loess Plateau will increase under the 1.5 °C global warming level. The population exposure was projected from 1.32 × 106 to 2.68 × 106 person-year. The population exposure of eastern and southern Loess Plateau is significantly higher than that of the northern region. The annual exposure of GDP ranges from USD 2.9 to 12.3 billion, and the regions with the highest GDP exposure are Zhengzhou, Xi’an, Taiyuan, and Lanzhou. Our results reveal that limiting the increase of global mean temperature to 1.5 °C warming level is of great significance to reduce the social and economic exposure to extreme precipitation events on the Loess Plateau.

The Paris Target, Human Rights, and IPCC Weaknesses: Legal Arguments in Favour of Smaller Carbon Budgets

The Paris Climate Agreement (PA) provides an overall target which limits global warming to “well below 2 °C above pre-industrial levels” and “pursuing efforts to limit the temperature increase to 1.5 °C above pre-industrial levels” (Art. 2 para. 1 PA). This article assesses the extent to which new insights can be derived from recent IPCC reports for the interpretation of Art. 2 para. 1 PA from a legal perspective. To this end, the article analyses the contributions of Working Groups I and III of the sixth assessment report. Methodologically, we compare the findings with previously published IPCC reports, namely the 1.5 °C report and the fifth assessment report. A legal interpretation of the Paris Agreement and of core concepts of human rights follows. Several empirical indications show that current global greenhouse gas budget calculations are quite generous. We provide five empirical arguments that clearly point in that direction. These empirical arguments, combined with legal arguments, demonstrate that the budgets must be smaller than those estimated by the IPCC. The legal arguments are based on Art. 2 of the Paris Agreement, as well as on human rights and the precautionary principle. These norms contain an obligation to minimise the risk of significant damage, i.e., to take rapid and drastic climate protection measures. This implies: 1.5 °C is the legally binding temperature target; adherence requires a very high probability of achieving the target; temperature overshoot and geoengineering tend to be prohibited, and budget calculations must be based on sceptical factual assumptions. These findings have also been confirmed by recent rulings of supreme courts, such as the ground-breaking climate decision of the German Federal Constitutional Court. The Paris Agreement and human rights underline a legally binding obligation for smaller global greenhouse gas budgets as those estimated in the greenhouse gas budgets of the IPCC—even compared to the 83 percent scenario in the latest assessment. Thus, climate policy will have to raise its ambitions towards zero fossil fuels and a drastic reduction of livestock farming in times of the Ukraine war.

Climate-driven range shifts of a rare specialist bee, Macropis nuda (Melittidae), and its host plant, Lysimachia ciliata (Primulaceae)

Earth's climate is on track to surpass the proposed mean global temperature change limit of 1.5ºC above pre-industrial levels, threatening to disrupt ecosystems globally. Yet, studies on temperate bee response to climate change are limited, with most studies of non- Apis bees focusing on the eusocial genus Bombus . Here, we assess the response of a rare habitat and host plant specialist bee, Macropis nuda , to projected climate change scenarios. We use species distribution models of M. nuda and its host plant, Lysimachia ciliata , trained on publicly available occurrence records, to evaluate bee distribution and habitat suitability changes under four climate change scenarios. We find that the bee and host plant distributions respond synchronously to increased greenhouse gas emissions, which result in range-wide habitat suitability loss and a northward range shift. These results provide an important example of a temperate solitary bee's response to climate change and help inform conservation efforts to preserve pollinator biodiversity and pollinator-host plant relationships.

Quantification of meteorological drought risks between 1.5 °C and 4 °C of global warming in six countries

We quantify the projected impacts of alternative levels of global warming upon the probability and length of severe drought in six countries (China, Brazil, Egypt, Ethiopia, Ghana and India). This includes an examination of different land cover classes, and a calculation of the proportion of population in 2100 (SSP2) at exposed to severe drought lasting longer than one year. Current pledges for climate change mitigation, which are projected to still result in global warming levels of 3 °C or more, would impact all of the countries in this study. For example, with 3 °C warming, more than 50% of the agricultural area in each country is projected to be exposed to severe droughts of longer than one year in a 30-year period. Using standard population projections, it is estimated that 80%-100% of the population in Brazil, China, Egypt, Ethiopia and Ghana (and nearly 50% of the population of India) are projected to be exposed to a severe drought lasting one year or longer in a 30-year period. In contrast, we find that meeting the long-term temperature goal of the Paris Agreement, that is limiting warming to 1.5 °C above pre-industrial levels, is projected to greatly benefit all of the countries in this study, greatly reducing exposure to severe drought for large percentages of the population and in all major land cover classes, with Egypt potentially benefiting the most.

Nitrogen and sulfur deposition reductions projected to partially restore forest soil conditions in the US Northeast, while understory composition continues to shift with future climate change.

Human activities have dramatically increased nitrogen (N) and sulfur (S) deposition, altering forest ecosystem function and structure. Anticipating how changes in deposition and climate impact forests can inform decisions regarding these environmental stressors. Here, we used a dynamic soil-vegetation model (ForSAFE-Veg) to simulate responses to future scenarios of atmospheric deposition and climate change across 23 Northeastern hardwood stands. Specifically, we simulated soil percent base saturation, acid neutralizing capacity (ANC), nitrate (NO3 -) leaching, and understory composition under 13 interacting deposition and climate change scenarios to the year 2100, including anticipated deposition reductions under the Clean Air Act (CAA) and Intergovernmental Panel on Climate Change-projected climate futures. Overall, deposition affected soil responses more than climate did. Soils recovered to historic conditions only when future deposition returned to pre-industrial levels, although anticipated CAA deposition reductions led to a partial recovery of percent base saturation (60 to 72%) and ANC (65 to 71%) compared to historic values. CAA reductions also limited NO3 - leaching to 30 to 66% above historic levels, while current levels of deposition resulted in NO3 - leaching 150 to 207% above historic values. In contrast to soils, understory vegetation was affected strongly by both deposition and climate. Vegetation shifted away from historic and current assemblages with increasing deposition and climate change. Anticipated CAA reductions could maintain current assemblages under current climate conditions or slow community shifts under increased future changes in temperature and precipitation. Overall, our results can inform decision makers on how these dual stressors interact to affect forest health, and the efficacy of deposition reductions under a changing climate.

What can the Glasgow Declaration on Forests bring to global emission reduction?

What can the Glasgow Declaration on Forests bring to global emission reduction?

A global meta-analysis of woody plant responses to elevated CO2: implications on biomass, growth, leaf N content, photosynthesis and water relations

BackgroundAtmospheric CO2 may double by the year 2100, thereby altering plant growth, photosynthesis, leaf nutrient contents and water relations. Specifically, atmospheric CO2 is currently 50% higher than pre-industrial levels and is projected to rise as high as 936 μmol mol−1 under worst-case scenario in 2100. The objective of the study was to investigate the effects of elevated CO2 on woody plant growth, production, photosynthetic characteristics, leaf N and water relations.MethodsA meta-analysis of 611 observations from 100 peer-reviewed articles published from 1985 to 2021 was conducted. We selected articles in which elevated CO2 and ambient CO2 range from 600–1000 and 300–400 μmol mol−1, respectively. Elevated CO2 was categorized into < 700, 700 and > 700 μmol mol−1 concentrations.ResultsTotal biomass increased similarly across the three elevated CO2 concentrations, with leguminous trees (LTs) investing more biomass to shoot, whereas non-leguminous trees (NLTs) invested to root production. Leaf area index, shoot height, and light-saturated photosynthesis (Amax) were unresponsive at < 700 μmol mol−1, but increased significantly at 700 and > 700 μmol mol−1. However, shoot biomass and Amax acclimatized as the duration of woody plants exposure to elevated CO2 increased. Maximum rate of photosynthetic Rubisco carboxylation (Vcmax) and apparent maximum rate of photosynthetic electron transport (Jmax) were downregulated. Elevated CO2 reduced stomatal conductance (gs) by 32% on average and increased water use efficiency by 34, 43 and 63% for < 700, 700 and > 700 μmol mol−1, respectively. Leaf N content decreased two times more in NLTs than LTs growing at elevated CO2 than ambient CO2.ConclusionsOur results suggest that woody plants will benefit from elevated CO2 through increased photosynthetic rate, productivity and improved water status, but the responses will vary by woody plant traits and length of exposure to elevated CO2.

Ocean negative carbon emissions: A new UN Decade program

Ocean negative carbon emissions: A new UN Decade program

Investigating detection probability of mobile survey solutions for natural gas pipeline leaks under different atmospheric conditions

The 2015 Paris agreement aims to cut greenhouse gas emissions and keep global temperature rise below 2 °C above pre-industrial levels. Reducing CH4 emissions from leaking pipelines presents a relatively achievable objective. While walking and driving surveys are commonly used to detect leaks, the detection probability (DP) is poorly characterized. This study aims to investigate how leak rates, survey distance and speed, and atmospheric conditions affect the DP in controlled belowground conditions with release rates of 0.5–8.5 g min−1. Results show that DP is highly influenced by survey speed, atmospheric stability, and wind speed. The average DP in Pasquill–Gifford stability (PG) class A is 85% at a low survey speed (2–11 mph) and decreases to 68%, 63%, 65%, and 60% in PGSC B/C, D, E/F, and G respectively. It is generally less than 25% at a high survey speed (22–34 mph), regardless of stability conditions and leak rates. Using the measurement data, a validated DP model was further constructed and showed good performance (R2: 0.76). The options of modeled favorable weather conditions (i.e., PG stability class and wind speed) to have a high DP (e.g., >50%) are rapidly decreased with the increase in survey speed. Walking survey is applicable over a wider range of weather conditions, including PG stability class A to E/F and calm to medium winds (0–5 m s−1). A driving survey at a low speed (11 mph) can only be conducted under calm to low wind speed conditions (0–3 m s−1) to have an equivalent DP to a walking survey. Only calm wind conditions in PG A (0–1 m s−1) are appropriate for a high driving speed (34 mph). These findings showed that driving survey providers need to optimize the survey schemes to achieve a DP equivalence to the traditional walking survey.

Does green technology advancement and renewable electricity standard impact on carbon emissions in China: role of green finance.

Renewable energy growth should be accelerated in order to meet our goal of carbon neutrality and peak carbon emissions. Laws like the Renewable Electricity Standard (RES) are becoming increasingly important in producing renewable energy. Using green technology advancements is seen as balancing economic growth with environmental security. Though the connection between green technology advancements and CO2 emissions is poorly understood, empirical research is lacking, especially in developing countries. Climate change action now falls under a single overarching contract, signed in Paris on November 4, 2016. Global warming mitigation aims to keep temperature increases to no more than 2°C above preindustrial levels. By 2060, China intends to reach carbon neutrality by developing green technologies (GTI). Because of these interconnections, this research explores the relationship between green technology innovation (GI) and renewable energy investment (REI) in selected Chinese provinces from 2005 to 2019. GI, REI, urbanization, industrial value-added, and income per capita were all considered in the STIRPAT model. We used a panel of chosen regions to test two relatively new panel estimation methods empirically: "continuously updated fully modified" (Cup-FM) and "continuously updated bias-corrected" (Cup-BC). According to our findings, urbanization and green technological developments positively impact CO2 emission reduction. The panel also finds that investments in renewable energy and the industrial sector fail to reduce pollution levels. A positive and negative coefficient of income per capita indicates that the inverted U-shaped EKC hypothesis is valid for the Chinese provinces. The results provide vital strategy insights and recommendations for the panel of experts and countries worldwide.

A framework for future-oriented environmental impact assessment of companies considering Science-Based Targets

The irreversible impacts of human activities on the Earth have led to the introduction of planetary boundaries that define a safe operating space for humanity to act within. Subsequently, Science-Based Targets (SBTs) have been set for companies as Greenhouse Gas (GHG) emissions reduction targets consistent with the required decarbonisation level to limit the temperature rise to less than 2 °C above the pre-industrial level. On the other hand, Life Cycle Assessment (LCA) has been applied as a suitable decision-making tool to integrate the environmental impacts of products in strategic and long-term planning. Many Future-oriented LCA approaches with relatively short-term perspectives have been published. However, the operationalisation of SBTs requires quantification of companies' Environmental Impacts in the far future. There are a few studies on the future-oriented Environmental Impact Assessment of companies with SBTs consideration. This paper aims to develop a framework for future-oriented Environmental Impact assessment of companies towards operationalisation of SBTs. The proposed framework employs scenario analysis and SBTs for Future-oriented Environmental Impact Assessment of product families and companies. Accordingly, it quantifies companies’ Environmental Impact Reduction Requirement (EIRR) to provide Environmental impact Targets (ETs) for product families and proposes pathways for product families to reach SBTs. In this research, Apple Inc. is considered as the case study and the application of the proposed methodology. It is concluded that the 86.51% Environmental Impact Reduction Requirement (EIRR) of Apple Inc. will not be satisfied considering different scenarios.

Design of a 100 MW concentrated solar power Linear Fresnel plant in Riyadh, Saudi Arabia: A comparison between molten salt and liquid sodium thermal energy storage

The investment in renewable energies like solar power became a priority in order to protect the world from an environmental crisis caused by greenhouse gas emissions. Over the past few decades, human activities like burning fossil fuels for energy have increased greenhouse emissions to an unprecedented level which warn to increase the global average temperature up to 1.5 °C above pre-industrial levels. Such increase in global temperature would cause massive environmental damage and affect people’s lives. Currently, around 65% of the total CO2 emissions are related to fossil fuel burning activities, thus it is necessary to find alternative sources of energy that are environmentally friendly. Renewable energy like solar power is considered one of the most reliable sources of energy as it covers a wide range of the earth’s surface and is constantly available. Several research studies focused on concentrated solar power (CSP) which revealed its high performance in producing electric power. Thus, this paper aims to study the feasibility of constructing a100 MW CSP Linear Fresnel solar power in Riyadh city to support meeting the energy demand in Saudi Arabia and reduce the dependence on fossil fuels. In this study, the National Renewable Energy Laboratory (NREL) System Advisor Model (SAM) was used to design, simulate, and analyze the system. The system was designed based on CSP LF technology, and it was tested with two types of thermal fluid namely molten salt and liquid sodium to examine the potential of each fluid to generate competitive energy at a lower cost. The thermal fluids serve as heat transfer fluids (HTF) and thermal energy storage (TES), where TES supplies the power cycle with needed energy during sunset time. The system simulation shows the capability to produce enough solar power throughout the year. The model achieved a high level of energy production with a capacity factor exceeding 90% during summer for both operating fluids. It was also found that liquid sodium yields higher energy as compared to molten salt with a capacity factor exceeding 0.5–1.2%. During the summertime, it was shown that Saudi Arabia has a high potential to adopt the CSP LF technology to produce sustainable solar power.

Significance of a 1 °C increase in global temperature

The Intergovernmental Panel on Climate Change reports indicate that the global mean temperature is about 1 °C higher than pre-industrial levels, that this increase is anthropogenic, and that there is a causal relationship between this higher temperature and an increase in frequency and magnitude of extreme weather events. This causal relationship seems at odds with common sense, and may be difficult to explain to non-experts. Thus to appreciate the significance of a one degree increase in global mean temperature, we perform back-of-the-envelope calculations relying on simple physics. We estimate the excess thermal energy trapped in the climate system (oceans, land, atmosphere) from a 1 °C increase in global mean temperature, and show that it is thousands of times larger than the estimated energy required to form and maintain a hurricane. Our estimates show that global warming is forming a very large pool of excess energy that could in principle power heatwaves, heavy precipitation, droughts, and hurricanes. The arguments presented here are sufficiently simple to be presented in introductory physics classes, and can serve as plausibility arguments showing that even a seemingly small increase in global mean temperature can potentially lead to extreme weather events.

Recent progress of catalytic methane combustion over transition metal oxide catalysts.

Methane (CH4) is one of the cleanest fossil fuel resources and is playing an increasingly indispensable role in our way to carbon neutrality, by providing less carbon-intensive heat and electricity worldwide. On the other hand, the atmospheric concentration of CH4 has raced past 1,900 ppb in 2021, almost triple its pre-industrial levels. As a greenhouse gas at least 86 times as potent as carbon dioxide (CO2) over 20 years, CH4 is becoming a major threat to the global goal of deviating Earth temperature from the +2°C scenario. Consequently, all CH4-powered facilities must be strictly coupled with remediation plans for unburned CH4 in the exhaust to avoid further exacerbating the environmental stress, among which catalytic CH4 combustion (CMC) is one of the most effective strategies to solve this issue. Most current CMC catalysts are noble-metal-based owing to their outstanding C–H bond activation capability, while their high cost and poor thermal stability have driven the search for alternative options, among which transition metal oxide (TMO) catalysts have attracted extensive attention due to their Earth abundance, high thermal stability, variable oxidation states, rich acidic and basic sites, etc. To date, many TMO catalysts have shown comparable catalytic performance with that of noble metals, while their fundamental reaction mechanisms are explored to a much less extent and remain to be controversial, which hinders the further optimization of the TMO catalytic systems. Therefore, in this review, we provide a systematic compilation of the recent research advances in TMO-based CMC reactions, together with their detailed reaction mechanisms. We start with introducing the scientific fundamentals of the CMC reaction itself as well as the unique and desirable features of TMOs applied in CMC, followed by a detailed introduction of four different kinetic reaction models proposed for the reactions. Next, we categorize the TMOs of interests into single and hybrid systems, summarizing their specific morphology characterization, catalytic performance, kinetic properties, with special emphasis on the reaction mechanisms and interfacial properties. Finally, we conclude the review with a summary and outlook on the TMOs for practical CMC applications. In addition, we also further prospect the enormous potentials of TMOs in producing value-added chemicals beyond combustion, such as direct partial oxidation to methanol.

VaclavSmilHow the World Really Works: A Scientist's Guide to Our Past, Present and FuturePenguin, 2022, 325 p., $28.00.

VaclavSmilHow the World Really Works: A Scientist's Guide to Our Past, Present and FuturePenguin, 2022, 325 p., $28.00.

A data-driven household electricity synthesiser for South Africa using enveloped sum of Gaussians

Accurate modelling of household electricity on a large scale is a cornerstone for demand management and decarbonisation efforts. This paper introduces a data-driven model for South African households. According to the Paris Agreement, a 50 % reduction in global CO2 emissions is required to ensure the global average temperature does not surpass 2 °C above pre-industrial levels. In this context, 26 % of the overall European energy consumption is used by the residential sector and the global energy consumption is estimated to increase by 1.3 % on average per year until 2050. In the last decade, the development and implementation of smart grid technologies have grown to efficiently and cost-effectively meet the electricity demands of the grid and mitigating greenhouse gas emissions. We present a data-driven, enveloped sum of Gaussians-based model and residential household synthesiser that statistically models the household's electricity usage demand based on smart meter data and generates synthetic data that accurately represents the actual demand profile, load peaks, and daily variances for an individual or aggregate group of households. The measured data was gathered over a one year period for 1200 households in South Africa. Our model accounts for temporal variations such as seasonality and the day of week, household uniqueness, and is fully autonomous. Our results show that the root mean square error between the aggregated measured and synthetic electricity profiles is 0.181 A (5.68 %) and the total energy of each profile is 75.9 and 76.3 A·h, respectively.