Prediction of net energy of feeds for broiler chickens

Net energy (NE) enables the prediction of more accurate feed energy values by taking into account the heat increment which is approximately 25% of apparent metabolizable energy (AME) in poultry. Nevertheless, application of NE in poultry industry has not been practiced widely. To predict the NE values of broiler diets, 23 diets were prepared by using 13 major ingredients (wheat, corn, paddy rice, broken rice, cassava pellets, full-fat soybean, soybean meal, canola meal, animal protein, rice bran, wheat bran, palm kernel meal and palm kernel oil). The diets were formulated in order to meet the birds' requirements and get a wide range of chemical compositions (on DM basis; 33.6% to 55.3% for starch; 20.8% to 28.4% for CP, 2.7% to 10.6% for ether extract [EE] and 7.0% to 17.2% for NDF), with low correlations between these nutrients and low correlations between the inclusion levels of ingredients allowing for the calculation of robust prediction equations of energy values of diets or ingredients. These diets were fed to Ross 308 broilers raised in 12 open-circuit respiratory chambers from 18 to 23 d of age (4 birds per cage) and growth performance, diet AME content and heat production were measured, and dietary NE values were calculated. The trial was conducted on a weekly basis with 12 diets measured each week (1 per chamber), 1 of the 23 diets (reference diet) being measured each week. Each diet was tested at least 8 times. In total, 235 energy balance data values were available for the final calculations. Growth performance, AME (15.3 MJ/kg DM on average) and AME/GE (79.4% on average) values were as expected. The NE/AME value averaged 76.6% and was negatively influenced by CP and NDF and positively by EE in connection with efficiencies of AME provided by CP, EE and starch for NE of 73%, 87% and 81%, respectively. The best prediction equation was: NE = (0.815 × AME) - (0.026 × CP) + (0.020 × EE) - (0.024 × NDF) with NE and AME as MJ/kg DM, and CP, EE and NDF as % of DM. The NE prediction equations from this study agree with other recently reported equations in poultry and are suitable for both ingredients and complete feeds.

Re-evaluation of recent research on metabolic utilization of energy in poultry: Recommendations for a net energy system for broilers

Different energy systems have been proposed for energy evaluation of feeds for domestic animals. The oldest and most commonly used systems take into account the fecal energy loss to obtain digestible energy (DE), and fecal, urinary and fermentation gases energy losses to calculate metabolizable energy (ME). In the case of ruminants and pigs, the net energy (NE) system, which takes into account the heat increment associated with the metabolic utilization of ME, has progressively replaced the DE and ME systems over the last 50 years. For poultry, apparent ME (AME) is used exclusively and NE is not yet used widely. The present paper considers some important methodological points for measuring NE in poultry feeds and summarizes the available knowledge on NE systems for poultry. NE prediction equations based on a common analysis of three recent studies representing a total of 50 complete and balanced diets fed to broilers are proposed; these equations including the AME content and easily available chemical indicators have been validated on another set of 30 diets. The equations are applicable to both ingredients and complete diets. They rely primarily on an accurate and reliable AME value which then represents the first limiting predictor of NE value. Our analysis indicates that NE would be a better predictor of broiler performance than AME and that the hierarchy between feeds is dependent on the energy system with a higher energy value for fat and a lower energy value for protein in an NE system. Practical considerations for implementing such an NE system from the commonly used AME or AMEn (AME adjusted for zero nitrogen balance) systems are presented. In conclusion, there is sufficient information to allow the implementation of the NE concept in order to improve the accuracy of feed formulation in poultry.

Development of a nano-size off-grid energy system using renewables and IoT technologies at the Meteoria visitor center: A Finnish case study

The increased utilization of non-renewable energy during the last century has influenced the climate, with increased carbon dioxide emissions and elevated temperature as a result. Thus, the need to develop and demonstrate new sustainable solutions regarding both energy supply and consumption, but also energy system optimization, is obvious. This case study presents the nano-size off-grid energy system at the Meteoria visitor center in Ostrobothnia, Finland, and the real-time measuring techniques that have been installed to follow up the energy production and consumption. The Meteoria consists of several buildings, which are open to the public from April to October. The case site is operated by energy derived from wind power, solar power, and a diesel generator (as a backup), with batteries for energy storage. The Internet of Things (IoT) has been retrofitted to the existing energy system to enable energy measurements and follow various electrical parameters in real-time. In addition, a graphical visualization platform open to the public has been developed. In this study, the completeness of data sampling and the IoT system was checked, and the results show high availability of data. Furthermore, various errors/limitations regarding the IoT system were identified. The energy supply/demand at the Meteoria in 2021 was monitored and the challenges regarding the existing energy system in a cold climate zone are discussed as well as the potential role of the Meteoria to function as a living lab.

Structural emission reduction in China's industrial systems and energy systems: an input-output analysis

China is committed to achieving the goals of "peak carbon and carbon neutrality," and the carbon dioxide emissions generated in the energy utilization process mainly come from industrial and energy systems. This paper used structural decomposition analysis (SDA) and input-output analysis to study the structural emission reductions in China's industrial and energy systems in 2007-2015. The results revealed that the final demand effect was the main factor promoting the growth of energy-related CO₂ emissions and that the energy intensity effect played a weak role in promoting the growth of energy-related CO₂ emissions. However, the energy structure effect and input structure effect reduced energy-related carbon emission growth. We found that for energy systems, the emission reduction effects of blast furnace gas, raw coal, refinery dry gas, and natural gas were obvious, while those of crude oil, gasoline, fuel oil, and kerosene were not obvious. For industrial systems, the tertiary industry played a major role in the final demand effect, followed by the secondary industry, and the primary industry in turn. This paper provides a theoretical basis and practical guidance for the carbon peak and carbon neutrality goals of China's energy systems and industrial systems.

Sustainable approach on removal of toxic metals from electroplating industrial wastewater using dissolved air flotation

This research paper concentrates on the removal of heavy metal from wastewater which was produced from an electroplating industry. Here, the Dissolved Air Flotation (DAF) treatment process is carried out to remove toxic metals such as chromium, cadmium, nickel, lead, and copper using Sodium Dodecyl Sulfate (SDS) as a collector. The best-optimized conditions for the maximum removal of all the metal ions about 97.39% was achieved at pH 8, contact time of 60 min, surfactant dosage of 0.2 g, and the pressure of 137.89 kPa. At optimized conditions, the treated water consists of 2.71 mg/L of chromium, 1.13 mg/L of cadmium, 10.24 mg/L of nickel, 0.06 mg/L of lead, and 1.14 mg/L of copper. The used surfactant SDS was found as an environmentally friendly compound as prescribed by the Environmental Protection Agency. It is inferred that the flotation kinetics that manifests the rate of recovery and time for all the metal ions follow first-order kinetics. Further, the removal rate constant (k) increases with decreasing the initial metal ion concentration. Overall, the result of this work propounds that the DAF process plays as a promising technique to eliminate noxious pollutants from the wastewater.

A global inventory of electricity infrastructures from 1980 to 2017: Country-level data on power plants, grids and transformers

Electricity infrastructures are crucial for economic prosperity and underpin fundamental energy services. This article provides global datasets on installed power plant capacities, transmission and distribution grid lengths as well as transformer capacities. A country-level dataset on installed electricity generation capacities during 1980 to 2017, comprising 14 types of power plants and technologies, is obtained by combining data from three different online databases. Transmission grid lengths are derived from georeferenced data available from OpenStreetMap, augmented with data from national and international statistics. Data gaps are filled and historical developments estimated by applying a linear regression model. Statistical data on distribution grids lengths are collected for 31 countries that make up almost 50% of the global electricity consumption. Estimates for distribution grid lengths in the remaining countries are again obtained through linear regression. Data on installed transformer capacities are sparsely available from market intelligence reports and specialist journals. For most countries, they are estimated from typical transformer-to-generator ratios, i.e. based on power plant capacities. Global generation capacity expansion since 1980 was dominated by coal-fired (mainly China and India) and gas-fired plants (mainly industrialized countries and Middle East). Solar and wind power accounted for the second and third largest capacity additions since 2010 (after coal-fired plants). The total length of transmission circuits worldwide is estimated at 4.7 million kilometres, and the length of distribution grids between 88 and 104 million km. China accounts for 41% of the expansion of global transmission grids, and 32% of the expansion of distribution grids since 1980. In 2017, China's electricity grids were approximately as large as the grids of all western industrialized countries combined. The globally installed capacity of transformers is estimated between 36 and 45 Teravolt-Ampere, with transmission and distribution transformers accounting for above 40% each, and generator step-up transformers for the rest. The data provided in this article are used for estimating global material stocks in electricity infrastructures in the related research paper [1] and can be used in energy system models, for econometric analyses or development indices on country level and many more purposes.

Energy system transformations and carbon emission mitigation for China to achieve global 2 °C climate target

The Paris Agreement calls for countries to pursue efforts to limit global-mean temperature rise to 2 °C compared to the pre-industrial level. To achieve this, it is essential to accelerate the low-carbon transition of energy system. China is the largest carbon emitter and plays a decisive role in mitigating global climate change. The transition pathways for China to contribute to meeting the global 2 °C target, however, have not been extensively explored. Here we develop a bottom-up national energy technology model (C³IAM/NET), a linear optimization model, to reveal the energy consumption, carbon emissions and technology pathway at the national and sectoral levels in line with the 2 °C climate target. Results show that China's carbon emissions need to peak at the year 2023 and reduce to 3.56 GtCO₂ by mid-century. During the 2020-2050 planning horizon, the remaining carbon budget is estimated to be controlled within 234 GtCO₂, with a cumulative emission reduction of 165.3 GtCO₂, of which the power sector bearing the largest share of responsibility, followed by the industry, transportation and building sectors. We project that China's primary energy consumption needs to peak before 2040 and the proportion of non-fossil energy in energy structure needs to reach 76% by 2050, and about 88.4% of electricity production comes from renewables and nuclear energy.

Script for resilience analysis in energy systems: Python programming code and partial associated data of four cogeneration plants

This article presents a script developed to evaluate resilience in energy systems. The files corresponding to the system description, simulation and metrics calculation are included in the dataset, as well as partial raw and processed data from the associated paper [1]. The model was developed focusing on covering all cogeneration and power plants, being the user responsible for describing the system, simulating and processing the data in the files here available. In the present work, the steps for the simulation are presented in detail, which contributes to other researchers that are interested in either adopting resilience as one of the possible system analyses or understanding the processes of metrics calculation of the associated paper.

Thailand's long-term GHG emission reduction in 2050: the achievement of renewable energy and energy efficiency beyond the NDC

The sources of greenhouse gas (GHG) emissions in Thailand come from the energy sector, including power generation, transport, industries, buildings, and households. In 2016, the energy sector contributed 77 percent of total GHG emissions. Thailand's energy policies are the essential instrument to deal with GHG emission reduction under the United Nations Framework Convention on Climate Change (UNFCCC). The renewable energy (RE) plans aim at increasing the share of RE in final energy consumption while the energy efficiency (EE) plans aim at improving energy efficiency as well as reducing fossil-fuel consumption. GHG emission mitigation will result in several co-benefits such as increasing energy security and decreasing local air pollutants. Therefore, this study analyzes potentials of GHG emission reduction during 2015–2050 from utilization of renewable energy and increasing energy efficiency using the Long-range Energy Alternative Planning system (LEAP) model. Results include potentials of domestic RE and EE measures to achieve Thailand's nationally determined contribution (NDC). Moreover, it was found that to meet Thailand's first NDC of 20 percent GHG emission reduction target in 2030, targets in the RE plan and the EE plan must be achieved by at least 50 percent and 75 percent, respectively, or targets in the RE plan and the EE plan must be achieved by at least 75 percent and 50 percent. In addition, the extended NDC scenario in 2050 is analyzed in the long-term perspective of Thailand showing 30.4 percent reduction when compared to the BAU. The policy implication includes promotion of energy efficiency, acceleration of the deployment of renewable energy and advanced technologies such as CCS, completion of transmission network for renewable electricity, zoning of biomass sources, and public awareness in climate changes.

Life Cycle Inventories datasets for future European electricity mix scenarios

Datasets concerning the European electricity mix, built employing the Ecoinvent database v.3.3 processes, are reported in this paper. Foreseen future scenarios are modelled based on acknowledged projections for energy market in Europe in 2050. These electricity mix data inventories could be useful for any academic or stakeholder interested in performing long-term prospective assessment of innovative generation technologies in the future European energy market.

Design, optimisation and reliability allocation for energy systems based on equipment function and operating capacity

Designers of energy systems often face challenges in balancing the trade-off between cost and reliability. In literature, several papers have presented mathematical models for optimizing the reliability and cost of energy systems. However, the previous models only addressed reliability implicitly, i.e., based on availability and maintenance planning. Others focused on allocation of reliability based on individual equipment requirements via non-linear models that require high computational effort. This work proposes a novel mixed-integer linear programming (MILP) model that combines the use of both input-output (I-O) modelling and linearized parallel system reliability expressions. The proposed MILP model can optimize the design and reliability of energy systems based on equipment function and operating capacity. The model allocates equipment with sufficient reliability to meet system functional requirements and determines the required capacity. A simple pedagogical example is presented in this work to illustrate the features of proposed MILP model. The MILP model is then applied to a polygeneration case study consisting of two scenarios. In the first scenario, the polygeneration system was optimized based on specified reliability requirements. The technologies chosen for Scenario 1 were the CHP module, reverse osmosis unit and vapour compression chiller. The total annualized cost (TAC) for Scenario 1 was 53.3 US$ million/year. In the second scenario, the minimum reliability level for heat production was increased. The corresponding results indicated that an additional auxiliary boiler must be operated to meet the new requirements. The resulting TAC for the Scenario 2 was 5.3% higher than in the first scenario.

The impact of climate variability and change on the energy system: A systematic scoping review

The energy system is a vital infrastructure which can be vulnerable to climate variability and change (CV&C) impacts. Understanding the impacts can prevent disruption and inform policy decision making. This study applied a scoping review in a systematic manner following the Joanna Briggs Institute guidelines to identify consistent patterns of CV&C impacts on the energy system, map and locate research gaps in the literature. A total of 176 studies were identified as eligible for inclusion in the review. This study found evidence of consistent increase in energy demand for Africa, the Americas and Asian continent. Consistent decrease was found in Northern and Eastern Europe, while increase in residential demand was projected in Oceania. There was evidence of consistent decrease in thermal power plant output globally. Solar photovoltaic showed a robust consistent pattern of increase in the Caribbean and Central America, Northern and Southern Africa and Oceania. As the global climate is changing in a future that is highly uncertain, the energy system should also evolve in order to adapt to the changing climate. Future impact assessment must integrate the impact of CV&C on power demand and supply while consider socioeconomic dynamics, cross-sectoral linkages and back-loops in a complete energy system model.

Energy Portfolio Assessment Tool (EPAT): Sustainable energy planning using the WEF nexus approach - Texas case

The paper introduces a holistic framework that identifies the links between energy and other systems (water, land, environment, finance, etc.), and measures the impact of energy portfolios, to offer a solid foundation for the best sustainable decision making in energy planning. The paper presents a scenario-based holistic nexus tool, Energy Portfolio Assessment Tool (EPAT) that provides a platform for energy stakeholders and policymakers to create and evaluate the sustainability of various scenarios based on the water-energy-food (WEF) nexus approach. The tool is applied to a case study in Texas, USA. Scenarios considered are set by the U.S. Energy Information Administration (EIA): EIA Reference Case - 2015, EIA Clean Power Plan (CPP) & Reference Case - 2030, and EIA No-CPP & Reference Case - 2030. In the presence of the CPP, total water withdrawal is expected to decrease significantly, while total water consumption is projected to experience a slight decrease due to the increase in water consumption in electricity generation caused by the new electricity mix. The CPP is successful in decreasing emissions, but is accompanied by tradeoffs, such as increased water consumption and land use by electricity generation. The absence of the CPP will lead to an extreme surge in total water withdrawn and consumed, and in emissions. Therefore, conservation policies should move from the silo to the nexus mentality to avoid unintended consequences that result in improving one part of the nexus while worsening the other parts.

Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA

Integrated Assessment Models (IAMs) characterize the interactions among human and earth systems. IAMs typically have been applied to investigate future energy, land use, and emission pathways at global to continental scales. Recent directions in IAM development include enhanced technological detail, greater spatial and temporal resolution, and the inclusion of air pollutant emissions. These developments expand the potential applications of IAMs to include support for air quality management and for coordinated environmental, climate, and energy planning. Furthermore, these IAMs could help decision makers more fully understand tradeoffs and synergies among policy goals, identify important cross-sector interactions, and, via scenarios, consider uncertainties in factors such as population and economic growth, technology development, human behavior, and climate change. A version of the Global Change Assessment Model with U.S. state-level resolution (GCAM-USA) is presented that incorporates U.S.-specific emission factors, pollutant controls, and air quality and energy regulations. Resulting air pollutant emission outputs are compared to U.S. Environmental Protection Agency 2011 and projected inventories. A Quality Metric is used to quantify GCAM-USA performance for several pollutants at the sectoral and state levels. This information provides insights into the types of applications for which GCAM-USA is currently well suited and highlights where additional refinement may be warranted. While this analysis is specific to the U.S., the results indicate more generally the importance of enhanced spatial resolution and of considering national and sub-national regulatory constraints within IAMs.

The Emergy Perspective of Sustainable Trends in Puerto Rico from 1960 to 2013

Emergy analysis quantifies the direct and indirect contributions of nature to human systems providing a sustainability assessment framework, which couples economic growth within biophysical constraints. In this study, Puerto Rico's sustainability was assessed with emergy flow dynamics from 1960 to 2013. During this period, the island shifted from an agriculture-based economy to an industrial base of manufacture and services (1960-1970). The emergy analysis indicated an exponential decline in sustainability during this period. From 1975 to 1992, the island became more industrialized and imported more goods and services. Since 1998, although more renewable production such as forest regeneration occurred, the rapid industrialization heavily relied on imported fossil fuels, goods, and services, resulting in a system that has not been self-sufficient, nor sustainable. The latest economic crisis and the most recently passed financial rescue bill represent an opportunity to redirect Puerto Rico towards a sustainable path with policies that decrease the ratio of imported y to exported emergy, and strategies that encourage efficient use of resources and local production based on the utilization of renewable sources within this U.S. territory.

Role of natural gas in meeting an electric sector emissions reduction strategy and effects on greenhouse gas emissions

With advances in natural gas extraction technologies, there is an increase in the availability of domestic natural gas, and natural gas is gaining a larger share of use as a fuel in electricity production. At the power plant, natural gas is a cleaner burning fuel than coal, but uncertainties exist in the amount of methane leakage occurring upstream in the extraction and production of natural gas. At higher leakage levels, the additional methane emissions could offset the carbon dioxide emissions reduction benefit of switching from coal to natural gas. This analysis uses the MARKAL linear optimization model to compare the carbon emissions profiles and system-wide global warming potential of the U.S. energy system over a series of model runs in which the power sector is required to meet a specific carbon dioxide reduction target across a number of scenarios in which the availability of natural gas changes. Scenarios are run with carbon dioxide emissions and a range of upstream methane emission leakage rates from natural gas production along with upstream methane and carbon dioxide emissions associated with production of coal and oil. While the system carbon dioxide emissions are reduced in most scenarios, total carbon dioxide equivalent emissions show an increase in scenarios in which natural gas prices remain low and, simultaneously, methane emissions from natural gas production are higher.

Future waste treatment and energy systems--examples of joint scenarios

Development and use of scenarios for large interdisciplinary projects is a complicated task. This article provides practical examples of how it has been carried out in two projects addressing waste management and energy issues respectively. Based on experiences from the two projects, recommendations are made for an approach concerning development of scenarios in projects dealing with both waste management and energy issues. Recommendations are given to develop and use overall scenarios for the project and leave room for sub-scenarios in parts of the project. Combining different types of scenarios is recommended, too, in order to adapt to the methods and tools of different disciplines, such as developing predictive scenarios with general equilibrium tools and analysing explorative scenarios with energy system analysis tools. Furthermore, as marginals identified in differing future background systems determine the outcomes of consequential life cycle assessments (LCAs), it is considered advisable to develop and use explorative external scenarios based on possible marginals as a framework for consequential LCAs. This approach is illustrated using an on-going Danish research project.