Unit Of Output Research Articles

Cleaner production promotion law and pollution: Firm level evidence from China

Using the formulation and implementation of China's Cleaner Production Promotion Law (CPPL) in 2003 as a quasi-natural experiment and a unique combined dataset of Annual Survey of Industrial Production Database and China Industrial Enterprise Pollution Emissions Database over 1998–2013, we investigate the impact of ex-ante prevention policies on firm pollution emissions. Our DID and DDD results show that: 1) The CPPL has significantly reduced firm's per unit of output emissions of SO2 and COD; 2) China's CPPL reduced firm pollution emissions intensity by reducing resource consumption, increasing firms' TFP and the number of green patents (Porter effect), and increasing the total amount of pollutants removal per unit of output; 3) The impact of CPPL on pollution shows modest firm heterogeneity, with larger effects on SOEs and on large-scale enterprises. The conclusions of this paper reveal that China's CPPL, as a formal rule of law regulation and ex-ante prevention policy, not only reduces the pollution intensity of enterprises from the input side, but also stimulate the Porter effect, and reduces the pollution removal level.

Markov decision process framework of optimal energy dispatch in a smart data center with uninterruptible power supplies

This paper examines the use of an Uninterruptible Power Supply (UPS) to enhance the operational efficiency of data centers. It focuses on developing an optimal energy scheduling strategy for a data center equipped with UPS, using the Markov decision process (MDP) framework. The MDP framework simulates the decision-making process involved in minimizing energy costs. Each unit’s available power output in the data center is treated as a Markov state, taking into account the uncertainty associated with renewable distributed generation. This uncertainty drives the system to transition to other Markov states in subsequent decision times. A recursive optimization model is established for each Markov state at each decision time to guide state-based operations, which includes determining the unit output while considering both current and future costs. The challenge of dealing with high dimensionality, arising from a substantial number of states and actions in the model, is effectively addressed by adopting an approximate dynamic programming (ADP) method. This approach incorporates decision-state and forwards dynamic algorithms to tackle the complexity of the MDP-based model. By employing ADP, the computational burden is reduced, enabling efficient and practical solutions to be obtained.

Decomposition Analysis of CO2 Emissions in Greece from 1996 to 2020

To meet Greece’s commitments under the Kyoto Protocol (KP) and the UN Framework Convention on Climate Change (UNFCCC), it’s crucial to dissect the primary influencers of its greenhouse gas emissions. This study utilized the logarithmic mean Divisia index method in its additive form to delve into the main drivers behind carbon dioxide emissions in Greece from 1996 to 2020. The analysis revealed that the primary catalyst for the rise in CO2 emissions was the growth in GDP. Conversely, advancements in energy efficiency, as indicated by a decrease in energy intensity, played a significant role in reducing CO2 emissions. While population growth contributed to an increase in emissions, a decline in emissions intensity showcased a reduction in emissions per unit of output or consumption. The period from 1996 to 2020 witnessed a 38% change in emissions, demonstrating the effectiveness of Greece’s environmental policies. These findings highlight the pressing need for a sustained focus on enhancing renewable energy sources (RES) penetration and ensuring comprehensive attention across all sectors to further reduce emissions.

Tax versus regulations: Polluters’ incentives for loosening industry emission targets

We investigate the political incentives of a polluter in affecting industry emission targets (relaxing emission restrictions) imposed by the government in a monopoly market. Specifically, we compare three typical environmental policies—two command-and-control regulations (an emission cap regulation that restricts total emissions and an emission intensity regulation that restricts emissions per output unit), and an emission tax. We presume a policy to be most robust when a less strict emission target (i.e., an increase in the targeted emission level) imposed by the government on the industry increases the firm’s profit least significantly among the three policies. This is because the firm has the least incentives for affecting emission targets. We find that the emission tax is the most robust if the government aims for a net-zero emission society. However, the emission tax is the least robust if the emission target is not ambitious or the government has weak resolve against political pressures from polluters.

Making Decisions on the Development of County-Level Agricultural Industries through Comprehensive Evaluation of Environmental and Economic Benefits of Agricultural Products: A Case Study of Hancheng City

This study aims to provide a scientific basis for the development of county-level agricultural industries through a comprehensive evaluation of the environmental and economic benefits of agricultural products. Focusing on Hancheng City in Shaanxi Province, this paper calculates and analyzes the carbon emission intensity per unit output value and the economic benefits of major agricultural products, assessing their comprehensive advantage indices. The research methods include data collection, data processing, and model construction, utilizing a bi-factor matrix analysis to explore the balance between environmental sustainability and economic profitability of different agricultural products. The results indicate that pepper and vegetables have the highest comprehensive advantages, demonstrating significant economic and environmental benefits, while soybeans show lower comprehensive advantages, requiring improvements in cultivation techniques and management practices. Based on the research findings, this paper proposes policy and management recommendations for different agricultural products, including focusing on the development of high-comprehensive-advantage products, improving cultivation techniques for low-comprehensive-advantage products, promoting green agricultural technologies, establishing a carbon footprint monitoring system for agricultural products, and strengthening agricultural infrastructure construction. The study’s conclusions provide theoretical support and practical guidance for the agricultural development strategies of Hancheng City and similar regions, contributing to the achievement of sustainable agricultural development and carbon reduction goals.

Study on the influence of guide vane - blade number matching relationship (20-9) on the phase resonance risk coefficient of pumped storage units

Abstract In this paper, 19 pumped storage units put into operation or under construction in China (the matching relationship between the number of guide vanes and blades is 20-9, and the rated output of a single unit is not less than 200MW) were taken as the research object. Considering the risk of phase resonance caused by pressure wave propagation in the spiral casing of the unit, the phase resonance risk coefficients of units with different rotational speeds were analyzed. The concept of perimeter equivalent coefficient was proposed, and the design criteria for controlling the phase resonance risk coefficient within 25% was obtained, which provided references for optimal hydraulic design of pumped storage units.

Robust optimization scheduling of microgrid considering a tiered carbon trading mechanism and flexible loads

Abstract Considering the comprehensive demand response, stepwise carbon trading, and uncertainty of wind power output for cogeneration microgrids, relevant optimization scheduling research will be carried out. The electric heating load is divided into non-dispatchable electric heating load and dispatchable electric heating load. By introducing electric heating demand and tiered carbon trading, the economic and low-carbon operation of microgrids can be achieved. The fluctuation of the output of new energy units is reflected using probability scenario sets in statistics, and a robust optimization model with related distributions is constructed using the C&CG algorithm to calculate and solve the established model. The simulation and comparison of numerical examples show that the microgrid energy management scheme formulated by the model established in this paper has good economic and environmental friendliness, and it also simultaneously validated the superiority of distributed robust optimization methods over traditional optimization methods

Study on phase resonance risk coefficient of pumped-storage units

Abstract In this paper, 48 pumped-storage units (rated output of a single unit is not less than 100MW) put into operation or under construction in China were taken as the research object, and the risk of phase resonance caused by pressure wave propagation in the spiral casing of the unit was studied. The risk coefficient of phase resonance under the matching relationship between different rotational speeds and the number of guide vanes and blades was analyzed, and the advantages and disadvantages of the matching relationship between different rotational speeds and the number of guide vanes and blades were compared. The fitting formulas of the circumferential Mach number with rated head due to the pressure wave propagating along the spiral casing under two equivalent diameters were proposed, which provided references for the optimal hydraulic design of pumped-storage units.

A family of quantum von Neumann architecture

Abstract In this work, we develop universal quantum computing models that form a family of quantum von Neumann architectures, with modular units of memory, control, CPU, and internet, besides input and output. This family contains three generations characterized by dynamical quantum resource theory, and it also circumvents no-go theorems on quantum programming and control. Besides universality, such a family satisfies other desirable engineering requirements on system and algorithm design, such as modularity and programmability, hence serves as a unique approach to build universal quantum computers.

PERANGKAT EKSTRAKSI JAHE TERINTEGRASI BERBASIS ARDUINO UNO DENGAN PENGUJIAN METODE SPEKTROFOTOMETRI VISIBEL

The Automatic Ginger Extractor Based on Arduino Uno consists of three main units: the input unit, the processing unit, and the output unit. The input unit is equipped with Up, Down, and Ok buttons for navigation, as well as a phototransistor sensor that detects the presence of ginger samples (ginger simplicia) to be extracted. The processing unit uses an Arduino Uno microcontroller to process signals from the sensor and control the output unit. The output unit includes a motor driver, a power window motor for operating the grinder to crush the samples, a 12V DC motor for operating the stirrer to mix the samples with the solvent, an electric solenoid valve for dispensing the extract, and an LCD to display the process status. The working principle of this device is that when the phototransistor sensor detects a sample, the sensor signal activates the power window motor to grind the ginger. The user can then manually set the dissolution time using the navigation buttons. The longer the dissolution time, the better the extraction result. The final product is a liquid containing curcumin, which is measured using a curcumin content meter to determine its concentration. The device shows an error rate of 2.74% compared to manual methods. With this design, the Arduino Uno-based automatic ginger extractor offers a more efficient and consistent extraction process. The automation system allows for better control and optimal results with minimal manual intervention.

Peak-shaving cost of power system in the key scenarios of renewable energy development in China: Ningxia case study

Renewable energy has developed rapidly in Ningxia, and it has become the first provincial power system in China whose renewable energy power generation output exceeds the power load of the whole region. The access of a high proportion of renewable energy puts forward higher requirements for the peak-shaving capacity of the Ningxia power system. In order to solve the problem of calculating the peak-shaving cost in the key scenarios of renewable energy development in Ningxia, a quantitative model of the peak-shaving cost of the power system considering time-of-use price is proposed. We take Ningxia power system as an example to study. First, the key scenarios of the Ningxia power system peak-shaving are obtained, and the technical cost characteristic boundaries of various peak-shaving resources are determined. Second, according to the characteristics of typical daily renewable energy and load in Ningxia, the quantification model of the power system peak-shaving cost is established. The model takes the minimum total cost of the power system as the objective function and considers the constraints such as technical output of thermal power units, charge-discharge characteristics of energy storage and time-of-use price mechanism. Finally, the model is solved and the peak-shaving cost and unit output under the optimal scheme are obtained. This example shows that the model can effectively evaluate the peak-shaving cost and unit output of the Ningxia power system under the key scenarios of peak-shaving.

A two-tier bidding model considering a multi-stage offer‑carbon joint incentive clearing mechanism for coupled electricity and carbon markets

To facilitate the coupling of electricity and carbon markets, a two-layer bidding model considering a multi-stage offer‑carbon joint incentive clearing mechanism is proposed. The upper layer models the bidding strategies of renewable energy units and thermal power generating units, and the lower layer is the market clearing layer. A multi-stage offer‑carbon joint incentive clearing mechanism is proposed. In the pre-clearing stage, the environmental benefit factor of the carbon market is introduced to adjust the bidding strategy of the units, the carbon emission intensity enters the market in the form of price, the environmental benefit of the generating units is fully considered, and the carbon quota allocation model of units is established; in the second stage, carbon trading cost is added based on the pre-clearing model to further optimize the unit output; in the third stage, the clearing model with the minimum cost of electricity energy is established for tracking the clearing price. Under this mechanism, the carbon trading cost is traded on the market and unit offers are combined with carbon element to participate in market trading. Three bidding models with different clearing mechanisms are set up, and the results of the arithmetic example show that the proposed model can realize the balance between the economic and low-carbon goals of market clearing, and can achieve the maximum carbon emission reduction based on no increase in the total cost of electric-carbon coupling. As the share of renewable energy increases, the clearing price will decrease. A reasonable offer from renewable energy sources can avoid their interests being jeopardized. Concurrently, increasing the initial carbon price can effectively guide the electricity market to develop in a cleaner direction.

Sign language recognition based on dual-path background erasure convolutional neural network

Sign language is an important way to provide expression information to people with hearing and speaking disabilities. Therefore, sign language recognition has always been a very important research topic. However, many sign language recognition systems currently require complex deep models and rely on expensive sensors, which limits the application scenarios of sign language recognition. To address this issue, based on computer vision, this study proposed a lightweight, dual-path background erasing deep convolutional neural network (DPCNN) model for sign language recognition. The DPCNN consists of two paths. One path is used to learn the overall features, while the other path learns the background features. The background features are gradually subtracted from the overall features to obtain an effective representation of hand features. Then, these features are flatten into a one-dimensional layer, and pass through a fully connected layer with an output unit of 128. Finally, use a fully connected layer with an output unit of 24 as the output layer. Based on the ASL Finger Spelling dataset, the total accuracy and Macro-F1 scores of the proposed method is 99.52% and 0.997, respectively. More importantly, the proposed method can be applied to small terminals, thereby improving the application scenarios of sign language recognition. Through experimental comparison, the dual path background erasure network model proposed in this paper has better generalization ability.

Study of dynamic performance of PEMFC-based CCHP system in a data center based on real-time load and a novel synergistic control method with variable working conditions

In this paper, the dynamic performance of Proton Exchange Membrane Fuel Cell-based Combined Cooling Heating and Power (PEMFC-based CCHP) system combined with a data center real-time load is studied. A novel synergistic control method is proposed to achieve optimization of energy flow between system units under fluctuating load. First, the off-design working condition models of PEMFC-based CCHP system are constructed. The delay in the changes of data center temperature is considered because of the thermal inertia under dynamic conditions. Second, the dynamic performance of PEMFC-based CCHP system to step changes of data center load is analyzed. Third, to further reveal the energy flow between units, the units output under varying load conditions are compared under the constraints of power and refrigeration supply. Finally, the dynamic performance of PEMFC-based CCHP system under the traditional control method of following electric load are revealed. A novel synergistic control method for the PEMFC-based CCHP system is proposed by refining the traditional method to optimize the energy flow between units. The result presents that the average energy efficiency reaches 78.29 %. Compared with the following electric load method, the energy efficiency is increased by 6.02 %. The response time of synergistic control method is 27.0 ms. Improved energy efficiency and fast response have been achieved.

Reducing energy and carbon footprint through diversified rainfed cropping systems

Agriculture is the second largest contributor (20 %) to total anthropogenic greenhouse gas (GHG) emissions in the world. There is a need to identify energy and carbon efficient cropping systems that reduce GHG emission and improve environmental quality. Using life cycle assessment (LCA), we evaluated the four cropping systems namely fallow – chickpea (F–C); Sesbania – mustard (Ses–M); blackgram – chickpea (B–C); sorghum + cowpea – mustard (S + C–M) cultivated during the 2018–2022 period. The energy use pattern and the input-output relationship were analysed. Three measures were utilized to quantify carbon footprints: CFa, which denotes emissions per unit area; CFb, indicating emissions per kilogram of yield; and CFe, representing emissions per unit of economic output. The result indicates that non-renewable sources of energy (diesel and fertilizer) contributed more than ∼80 % of the total energy consumed in the different cropping systems. The total energy requirement was the highest for S + C–M (16,972 MJ ha–1), followed by Ses–M (14,365 MJ ha–1), B–C (11,132 MJ ha–1) and F–C (8679 MJ ha–1) cropping systems. The S + C–M cropping system also had the highest energy use efficiency (9.13) followed by F–C (6.03), B–C (5.41) and Ses–M (5.41). The fallow–chickpea cropping system had the lowest values of CFa, CFb, and CFe however, the highest carbon efficiency (10.7) and the carbon sustainability index (9.7) were computed in S + C–M cropping system. Our findings indicate that thoughtfully structured, varied crop systems that integrate legumes and forage crops have the potential to significantly reduce energy consumption and carbon emissions, while sustaining or potentially improving overall productivity within these systems.

Multi-agent cooperative optimal scheduling strategy of integrated energy system in urban area under extreme events

Because the global climate change intensifies as well as the natural disasters frequently occur, extreme events have caused serious impacts on the energy system in urban areas, and at the same time, they have brought great challenges to the supply and scheduling of urban energy systems. Therefore, in order to better integrate and manage various energy resources in urban areas, a Deep Q-Leaning Network-Quasi Upper Confidence Bound model is innovatively constructed using deep reinforcement learning technology to learn the state and behavior mapping relationship of energy system. Use deep learning to fit complex nonlinear models to optimize the entire energy system. Compare and verify the experiment with the real energy system. The improved Deep reinforcement learning algorithm is compared with Q-learning model, PDWoLF PHC algorithm model, Quasi Upper Confidence Bound algorithm model and deep Q-Leaning Network algorithm model. The results show that the research algorithm has the smallest instantaneous error value and absolute value of frequency deviation for area control, and the average value of the research algorithm in the absolute value of the frequency deviation is reduced by 45%–73% compared to other algorithms; over time, the unit output power of the research algorithm is able to flexibly track the stochastic square wave loads. Therefore, the proposed system strategies can provide feasible solutions to meet the challenges of extreme events and promote the sustainable development and safe operation of urban energy systems.

Female executive and energy consumption intensity: The role of green innovation

We widely explore the positive effect of female executives on ECI, the energy consumption per unit of output. We find that female executives will promote ECI reduction of corporate. And the result holds after a series of robustness and endogeneity tests. Further analysis indicates that the positive effect will be stronger in enterprises with lower level of environmental regulation, in heavily polluting industry, and whose executives with more environmental background. Moreover, female executives will reduce ECI by promoting green innovation, both in quantity and quality. Our results enrich the study of female executives on corporate environmentally friendly development, focusing on green innovation as underlying channel.

Weight-restricted approach on constant returns to scale DEA models: Efficiency of internet banking in Turkey

The performance measurement of decision-making units (DMUs) can be optimised by strategically choosing the optimal input and output weights. This approach circumvents the potential complexities associated with establishing a common basis for ranking homogeneous units and managing the results from multiple efficient frontiers. Efficient frontier ranking is simplified by limiting the weights based on the intrinsic or technical connections between relevant inputs and outputs. It also creates a coherent framework that coordinates various considerations across all under-evaluated DMUs and variables. This method effectively examines the complexities related to the inputs and outputs of homogeneous units using conventional data envelopment analysis (DEA) models to evaluate the efficiency of these units.In the banking sector, the relationship between inputs and outputs is complex. This complexity requires careful attention, particularly in cases where the existence of one input or output is conditional on the existence of another. This dynamic is accentuated by the integration of advanced fintech solutions, which inherently provide significant benefits to banking operations. The use of appropriate analytical models for banking data is important. The synergy between advanced financial technologies and analytical methods has reached its peak in reducing losses and strengthening profits. This, in turn, facilitates the optimal allocation of financial resources to growth-oriented projects.The empirical application of weight-restricted DEA models to Turkey's mobile-internet-banking sector underscores their efficacy. These modified models contrast with the standard DEA versions, which often encounter challenges stemming from the allocation of weights to pivotal variables. This study demonstrates the tangible benefits of our approach and its potential to revolutionise the efficiency assessment landscape in the banking sector.The proposed unconventional model which is applied to Turkish Internet banking for the period extending from 2006 to 2018 and which takes a comprehensive weight restriction approach to DEA and encompasses all relevant input and output variables, resulted in strictly positive weights and a reduced count of inflated efficient units along with their scores. This is practically beneficent to banking sector in so far as it facilitates decision-making and related economic and financial planning, and as it proves to be a reliable benchmark by local or international banks intending to provide or develop Internet banking services.

Profit analysis of native chicken farming business in Kakas District, Regency of Minahasa, Indonesia

The study aims to determine the profit of farmers from native chicken farming businesses and some influencing factors in Kakas District, Minahasa Regency, North Sulawesi Province. The research site was in Kayuwatu Village and Tounelet Village, Kakas District. The sample of this research was selected purposively, while the data collection technique was conducted in April – May 2023. Further, the study employed a survey method with interview techniques for 60 farmers, using a list of questions. The obtained data was tabulated and analyzed to obtain the total profit. Then, the data were analyzed using the unit output price of profit function (UOP-PF) technique with a regression analysis model. The results of the study show that the total profit from selling native chickens which was an average of 68 chickens per farmer was IDR 2,742,127.60 per year. Based on multiple regression analysis, the coefficient of determination was 0.583, which meant that native chickens’ business profits could be explained by the cost variable of chicken purchasing, corn feed, bran, drug and vitamin, labor, and electricity of 58.3%. Meanwhile, the remaining 41.7% was caused by other factors that were not included in the regression model. The partial test analysis demonstrated that the variable cost of chicken purchasing, electricity, and corn feed had significantly affected the profit of native chicken business (p<0.05), while the factors of bran feed, medicine or vitamin, and labor costs had not a significant effect on the profit of native chickens

Implementation Of Wage Unit Results In Meeting The Decent Living Needs (KHL) Of Batik Workers

Wage based on unit of output is a wage paid based on the production or quantity of goods produced by the worker, in this research, the amount of batik produced by the batik maker. This study aims to determine the implementation of piece-rate wages for batik workers, Pekalongan (Batang) area in Central Java and Cirebon, West Java to see the welfare of batik workers. This research uses qualitative methods with data collection instruments in the form of interviews and field observations. The magnitude of the poverty line and the average monthly per capita expenditure of the community at the provincial and city levels are indicators in determining the welfare level of workers. The results show that the piece-rate wages received by batik workers are higher than the city and provincial poverty lines, but still low when compared to the average monthly per capita expenditure at the provincial and city levels. Nevertheless, employers can determine the amount of wages below the government's decision if employers and workers have agreed. In conclusion, the wages received by the batik workers have not been able to fulfill the KHL of the batik workers optimally. However, batik makers are considered prosperous because they have fulfilled Article 36 Paragraph (2) of Government Regulation No. 36 of 2021 where wages in Small and Medium Enterprises, especially batik, have fulfilled at least 50% of the average consumption of the provincial community and at least 25% above the poverty line at the provincial level.