Production Unit Research Articles

Analysis of Decision-Making in a Green Supply Chain under Different Carbon Tax Policies

With the growing severity of global environmental issues, the international community has reached a consensus on the importance of reducing and controlling carbon emissions. As a result, an increasing number of consumers are opting to purchase green products in order to reduce the emission of greenhouse gases. This trend has prompted supply-chain enterprises to invest in green innovation. Simultaneously, carbon tax policies have gained significant attention from governments worldwide due to their dual role as environmental laws and fiscal-policy tools. Considering consumers’ preference for green products and the risk of R&D failure associated with them, this study focuses on the effects on emissions reductions and profits associated with different carbon tax policies for a green supply chain consisting of a manufacturer and a retailer. The results reveal that (1) increases in the carbon tax per unit of product motivate the manufacturer to increase R&D efforts; (2) wholesale and retail prices follow a pattern of initial increase and subsequent decrease as the carbon tax per unit of product rises; (3) higher carbon taxes per unit of product generally lead to lower manufacturer profits, while both carbon emissions and retailer profits can increase with a per-unit carbon tax under certain circumstances; and (4) the increase in the proportion of the population with green preferences can yield long-term benefits for both the retailer and the manufacturer, yielding an inverted U-shaped relationship with carbon emissions.

Multi-objective optimization, comparison of using different biomass fuels in hybrid energy system for electricity-distilled water production based on supercritical CO2 and humidification and dehumidfication cycles

Biomass-derived power generation presents various potential benefits compared to conventional fossil fuel-based power generation. Also, efficient integration of energy systems leads to higher sustainability and effectiveness. This paper presents a biomass-fueled energy system with two open and closed Brayton cycles in the waste heat, of which a humidification and dehumidification system is implemented. The usage of four different biomasses as the fuel of the gasifier is tested and put to comparison from the aspects of thermodynamics, economics, and environment. The Grassman diagram for each layout is presented to signpost the exact point of highest exergy destruction and irreversibility. The optimization based on machine learning techniques is conducted to pinpoint the exact optimum operational conditions. The results indicate that wood offers more sustainability compared to other biomasses, and the amount of energy efficiency, exergy efficiency, and freshwater flow rate produced for Wood biomass in the proposed system are 75.81 %, 36.98 %, and 0.4091 kg/s, respectively. Also, two optimization scenarios have been done for this study. In the initial optimal solution finding, effectivness, unit product cost, and carbon dioxide emission index are equal to 45.9 %, 12.6 $/GJ, and 0.7161 kg/kWh, correspondingly. In the latter scenario, the effectiveness, net power production, and production unit cost of products are equal to 45.9 %, 6580 kW, and 12.61 $/GJ, respectively.

An applicable multi-generation system for different climates from energy, exergy, exergoeconomic, economic, and environmental (5E) perspectives

Proposing a practical multi-generational system for different climates can be the key for setting up renewable-based systems as an alternative to fossil fuels in different countries. This paper introduced a flexible renewable energy system that is capable of generating multiple forms of energy using solar energy and hydrogen storage, and can operate under diverse weather conditions across four cities in Iran. The system was equipped with a solar unit, photovoltaic panels (PV), heating and cooling units, a desalination technology, a hydrogen production unit, and a fuel cell to supply heating, cooling, electricity and freshwater loads for a residential building. Mashhad (normal), Tabriz (cold), Bandar Abbas (humid), and Yazd (hot and dry) cities were considered as different climates in Iran to suggest the best city based on the present system. Analysis and simulation were conducted, taking into account five perspectives, namely energy, exergy, exergoeconomic, economic, and environmental (5E). This was done utilizing the TRNSYS and Engineering Equation Solver (EES) packages. Multi-objective optimization was carried out to achieve the best performance using the TOPSIS method for the four cities mentioned. The system was grid-connected to sell excess power when there is no need for electricity and receive power when it is needed. Optimization showed that Bandar Abbas has the highest exergy efficiency of the system by 26.3 % and the lowest total cost rate of the whole components by 6.08 $/h. Moreover, the maximum net output power of 28.72 kW was reported in Tabriz. Environmental analysis revealed that the system had the ability to lower CO2 emissions through the generation of clean electricity and avoiding the use of natural gas. This was particularly significant in Bandar Abbas and Yazd, where the maximum reductions in CO2 emissions were obtained at 23.3 tons and 4.4 tons, respectively. In conclusion, the payback period for Mashhad, Tabriz, Bandar Abbas, and Yazd cities was obtained at 6.5 years, 5.8 years, 5.5 years, and 5 years, respectively.

Вклад Фан Сяньтина в изучение проблем индустриализации Китая (1920-е – 1930-е гг.)

The article examines the history of the searches for China’s industrialization strategy in the writings of Fang Xianting. The experience of studying the history of the industrial development of England and the influence of the German historical school became important components of his understanding of China’s economic prospects in the first half of the 20th century. The starting point for the study of Chinese economy was Bücher’s classification of types of industrial organization in their historical evolution. Analysis of data collected by Fang Xianting on the socio-economic characteristics of a number of industries (carpet industry, cotton industry) made it possible to identify the obstacles to industrialization. The scholar recommended focusing on the development of rural industry while avoiding following the Western model of concentration of large enterprises in the cities. Rural industry needed no large investments, resources and sophisticated equipment, it could use the labor of peasants and was not under the control of foreign powers. Although China’s rural industry suffered from reduction in sales to foreign markets during the global crisis, Fang Xianting hoped for its revival and transformation into a driving force for industrialization. In the development of small-scale decentralized production, he saw the possibility of counteracting foreign dumping, preserving the family as a production unit and maintaining social stability. The scholar recommended developing a system of rural cooperatives that can protect the economic interests of producers and increase the competitiveness of Chinese goods. It is concluded that Fang Xianting’s research has become an important part of the advancement of Chinese economists towards a deeper understanding of the prospects of China’s industrialization that take into account national specifics. His research method combined the collection of objective economic information with the study of political, social and legal institutions for the sake of identifying the impact of industrialization on Chinese society. Emphasis on the priority of rural industry reveals the historical origins of the economic strategy in the initial stage of Chinese reforms in the 1980s that was aimed at improving the living standards of peasants through the development of rural industries.

A heat source self-supplied thermodynamic system using liquefied natural gas: Performance evaluation and three-objective optimization

In recent years, growing concerns have arisen due to the tight energy supply and escalating demand have driven the research on energy-efficient polygeneration systems. Liquefied natural gas (LNG) is highly regarded as a clean fossil fuel, capable of both cooling and serving as a heat source. This makes it a favored choice for thermodynamic system design. LNG gasification at −162 °C under standard pressure releases substantial cold energy. To avoid its waste, a novel self-supplying thermodynamic system was devised to recover this energy, incorporating a specific cold storage module that combines power generation and heating systems. This approach offers insights into creating polygeneration systems using LNG as the sole energy source. In light of the intricate energy exchanges within the system, based on the energy parameters of each stream, a comprehensive evaluation of its engineering feasibility is conducted through the analysis of energy, exergy, exergoeconomic, and exergoenvironmental parameters. Additionally, key parameters like R1150 mass flow rate, pump 3 outlet pressure, compressor 2 outlet pressure, LNG pump outlet pressure, and R23 liquefaction temperature are examined. Finally, the non-dominated sorting genetic algorithm II (NSGA-II), particle swarm optimization (PSO) and the multi-objective artificial hummingbird algorithm (MOAHA) rooted in hummingbird foraging behavior, are applied to optimize the proposed system. The results show that the energy utilization efficiency, exergy efficiency, product unit exergoeconomic cost, and product unit exergoenvironmental impact are 72.08%, 45.45%, 98.04 $/GJ, and 1.478 × 10−2 mpt/kJ, respectively. These excellent performance indicators demonstrate that the system is developable in the field of LNG utilization, filling a gap in the joint research of cold storage, power generation and heating for LNG cold energy utilization. Enhancing system performance can be achieved by increasing the mass flow rate of R1150 and the output pressure of compressor 2, reducing the output pressure of pump 3 and the liquefaction temperature of R23. When increasing the output pressure of LNG pump, can only increase exergy efficiency, while the energy utilization efficiency, product unit exergoeconomic cost and product unit exergoenvironmental impact all go down. Compared with the initial condition, after the application of MOAHA optimization, the exergy efficiency increased by 2.8%, the product unit exergoeconomic cost decreased by 3.47 $/GJ and the product unit exergoenvironmental impact decreased by 0.047 × 10−2 mpt/kJ. These results outperform those of NSGA-II and PSO, indicating that MOAHA can lead to superior system performance by overcoming multi-objective conflicts. This study provides valuable insights for designing and optimizing LNG cold energy utilization systems in situations without nearby heat sources or when power generation, heating, and cold storage are required.

Development of a novel power and freshwater cogeneration plant driven by hybrid geothermal and biomass energy

The reliable supply of electricity and potable water has crucial importance on achieving higher level of human welfare, where the primary energy source to provide these requirements is fossil fuels at present. Since the combustion of fossil fuels has irreparable environmental impacts, thus utilization of clean and renewable energy resources is a promising alternative to overcome the energy-related environmental issues. In this regard, present research aims at development of an effective co-generation of electricity and freshwater plant driven by hybrid geothermal and biomass renewable energy sources. To make a comprehensive system assessment, thermodynamic, exergy, environmental and economic aspects are considered and appraised in detail and multi-objective optimization is used to detect the best performance of the plant. The results indicated feasibility of hybridization of biomass and geothermal resources for efficient co-production of potable water and electricity. Under optimized operation, the plant exergetic efficiency, unit product cost, exergo-environmental index, and CO2 emission are found to be 44.12 %, 66.97 $/MWh, 0.5114 and 0.7105 kg/kWh, respectively. The second law analysis revealed that, from 18302 kW of input exergy, a value of 9357 kW is destructed within the components, where the gasifier owns the largest portion with 3569 kW.

42 Environmental Impacts of Improving Forage Use Efficiency in Beef Cattle

Abstract As population grows, so does the demand for high quality protein, and beef ranks among the greatest in terms of nutrient density per caloric intake. Maintaining the sustainability of beef cattle production systems has been one of the main priorities of researchers worldwide. Because the global demand for beef production is projected to increase, the contribution of beef production to greenhouse gas emissions will increase. One of the most useful tools available to researchers to reduce the carbon footprint of beef production is the selection for more feed efficient cattle. The use of residual feed intake as a criterion for selection has been demonstrated to have potential impact on the carbon footprint of beef systems, by reducing emissions intensity. Greenhouse gas emissions intensity involves the carbon footprint per unit of product (e.g., beef or milk produced) and it is the main metric to be considered when assessing the environmental impact of production systems. Great advances have been made in terms of improving the digestibility of forage resources. However, because of the impact that fiber digestion has on enteric methane production, these improvements in forage digestibility need to be considered in the context of emissions intensity. Advances in forage breeding such as the incorporation of brown mid-rib traits, have undoubtedly led to improvements in fiber digestion and animal productivity. Fewer studies have examined the impact of this technology on greenhouse gas emissions. A great opportunity exists to begin assessing the impact of new technologies such as the use or fibrolytic enzymes and prebiotics, with the potential of enhancing fiber digestibility. Global beef production will continue to rely heavily on high-forage diets for at least some segments of the production system. Assessing the impact of new technologies to enhance fiber digestion in the context of greenhouse gas emissions per unit of product will be essential to maintain the sustainability of beef production systems.

The impact of technological innovation for emission reduction on decision-making for intertemporal carbon trading

Trading carbon emissions is a common strategy for reducing emissions around the world. But its flawless and methodical parameter adjustments and coping strategies nonetheless lack a theoretical grounding when faced with the prospect of uncertainty. To analyze how the enterprise emission path might be made compatible with the social emission path by policy adjustment, this study illustrates the impact of the uncertainty of technical innovation for emission reduction on the decision to engage in intertemporal carbon trading. The findings demonstrate that the decision to engage in intertemporal carbon trading is significantly impacted by the uncertainty of technological innovation for emission reduction. Enterprise productivity is directly correlated with technological innovation for emission reduction. When a policy instrument is used for adjustment, the probability of technological innovation for emission reduction is inversely related to the intertemporal trading banking rate and the price of carbon tax per unit product, whereas it is proportional to the intertemporal trading borrowing rate. This is taking the goal of maximizing social welfare as the constraint. The results serve as a guide for creating more logical parameters for intertemporal carbon trading legislation.

Behavioral and Morphological Traits of Nellore Cattle That Can Influence Calf Survival and Performance from Birth to Weaning

This study aimed to identify behavioral and morphological traits of Nellore cattle that can influence calves’ survival and pre-weaning performance. It was performed in two units of a large-scale cow–calf operation farm located in the Central-West region of Brazil, with 975 cow–calf dyads, by scoring cows’ maternal protective behavior, body condition, horns, udder suspension (US), teat size (TS) and calves’ vigor. TS was used to determine teat symmetry (TSm). The production unit where calves were born, their birth date, sex, and birth (BW) and weaning weights were also recorded. Cow ages at calving and production units were used to categorize the cows into twelve classes (Cage). The Shapiro–Wilk test alongside tables of frequencies were used to determine if continuous and categorical variables followed a normal distribution, respectively. Two datasets were considered in statistical analyses: (i) 975 dyad records were used to identify potential factors influencing calf survivability and (ii) 936 records of weaned calves were used to assess pre-weaning performance. Generalized linear models were used to assess the effect of target traits on the calves’ weight adjusted for 210 days of age (W210, kg) and pre-weaning average daily gain (preADG, kg/day). Tukey’s test was used to compare W210 and preADG means. Pearson’s correlation coefficients were estimated between BW, W210 and preADG. Cage, US and the TSm significantly affected pre-weaning calf performance (p < 0.01). Older cows (independently of the production unit) and those with intermediate US and symmetrical teats weaned heavier calves. As expected, positive and significant correlation was observed between BW and preADG (r = 0.35), which, in turn, was highly correlated with W210 (r = 0.99). We concluded that none of the behavioral and morphological traits influenced calf survivability, but cow age, US and TSm impacted pre-weaning performance, with 8- to 11-year-old cows and those with intermediate US and symmetric teats leading to better calf performance at weaning.

A Necessity-Based Optimization Approach for Closed-Loop Logistics Considering Carbon Emission Penalties and Rewards under Uncertainty

The recycling of waste products can bring enormous economic and environmental benefits to supply chain participants. Under the government’s reward and punishment system, the manufacturing industry is facing unfolded pressure to minimize carbon emissions. However, various factors related to the design of closed-loop logistics networks are uncertain in nature, including demand, facility capacity, transportation cost per unit of product per kilometer, landfill cost, unit carbon penalty cost, and carbon reward amount. As such, this study proposes a new fuzzy programming model for closed-loop supply chain network design which directly relies on fuzzy methods based on the necessity measure. The objective of the proposed optimization model is to minimize the total cost of the network and the sum of carbon rewards and penalties when selecting facility locations and transportation routes between network nodes. Based on the characteristics of the problem, a genetic algorithm based on variant priority encoding is proposed as a solution. This new solution encoding method can make up for the shortcomings of the four traditional encoding methods (i.e., Prüfer number-based encoding, spanning tree-based encoding, forest data structure-based encoding, and priority-based encoding) to speed up the computational time of the solution algorithm. Several alternative solution approaches were considered to evaluate the proposed algorithm including the precision optimization method (CPLEX) and priority-based encoding genetic algorithm. The results of numerous experiments indicated that even for large-scale numerical examples, the proposed algorithm can create optimal and high-quality solutions within acceptable computational time. The applicability of the model was demonstrated through a sensitivity analysis which was conducted by changing the parameters of the model and providing some important management insights. When external parameters change, the solution of the model maintains a certain level of satisfaction conservatism. At the same time, the changes in the penalty cost and reward amount per unit of carbon emissions have a significant impact on the carbon penalty revenue and total cost. The results of this study are expected to provide scientific support to relevant supply chain enterprises and stakeholders.

The Monitoring of Abnormal Fluid Properties Based on PCA Technique as an Alternative Strategy to Support Autonomous Drilling Operations

Summary The well drilling process requires constant monitoring to ensure that the properties of the drilling fluids remain within acceptable ranges for safe and effective operation of the well drilling process. The present work developed a principal component analysis (PCA)-based methodology for diagnosing anomalies in drilling fluids, and detecting and identifying abnormal drilling fluid properties during well drilling operations. The main novelty of the present work regards the application of multivariate techniques for diagnosing anomalies (faults) in drilling fluids, increasing the literature on fault diagnosis techniques applied to the petroleum industry, and producing a promising methodology for field applications. The proposed technique was implemented and validated in a pilot drilling fluid production unit through continuous online monitoring of the conductivity, density, and apparent viscosity of drilling fluids. Model training was carried out with data collected during assisted normal operation, allowing detection of abnormal conditions with less than 1% of false positives and less than 0.5% of false negatives. Additionally, the proposed methodology also allowed the correct diagnosis of the observed faults. The results indicated that PCA-based approaches can be used for the online monitoring of drilling fluid properties and fault diagnosis in real well drilling operations.

Jakson Green to build methanol production unit at NTPC[StQuote]s Vindhyachal plant

Jakson Green to build methanol production unit at NTPC[StQuote]s Vindhyachal plant

THE ROLE OF MATTOANGING FARMER GROUP IN INCREASING MAIZE (Zea mays) PRODUCTION IN MASSEPE VILLAGE

This study aims to determine the role of the Mattoanging farmer group in increasing maize production in the Massepe Village. This quantitative descriptive research uses a non-experimental approach with a survey type. The research using a questionnaire obtained an average percentage in learning classes 72.3%, in collaboration vehicles of 75.8%, and production units of 81.2%. After being analyzed using the Rank-Spearman Correlation, the correlation coefficient in the learning class was 0.678. In cooperative vehicles, it is 0.683; in production units, it is 0.654. These three values indicate a strong relationship with a positive direction. The significance value obtained from the three variables is below 0.05 (α = 5%). This means that H0 is rejected and H1 is accepted, which means that there is a significant relationship between the role of the Mattoanging farmer group as a learning class, a vehicle for cooperation, and a production unit in increasing maize production in Massepe Village, Tellu Limpoe District, Sidenreng Rappang Regency.

Integration of vanadium-chlorine thermochemical cycle with a nano-particle aided solar power tower for power and hydrogen cogeneration

The adverse environmental impacts of fossil fuels is becoming a major concern considering the climate changes. In this respect, the H2 as a carbon-free energy carrier has absorbed interest of researchers and policy makers to pay more attention to this field. In this regard, the solar energy driven frameworks are of major importance due to the abundance of solar energy as well as being a clean energy resource. However, the solar based systems suffer from lower efficiency compared to conventional fossil fuel-based systems due to large exergy destructions. One way to solve this problem and to enhance solar-based system performance is employment of nanoparticles for improving heat transfer characteristics of solar thermal loop. Present research is an attempt in this regard in which effects of employment nanofluid instead of the pure solar salt is investigated in a solar power tower system. The solar power tower unit supplies required energy to run a steam cycle for power generation and a thermochemical H2 production unit for co-generation of power and H2. Feasibility evaluations are carried out based on thermodynamic laws and exergy-based analyses as well as economic investigations are conducted to assess the system performance and multi-objective optimization is conducted to specify the optimum operation of system. A parametric evaluation is carried out to consider how design variables affect the system performance, prior to implementation of multi-objective optimization. The results have revealed positive effect of nanofluid application instead of pure solar salt and indicated enhancement of 4−5% on technical performance. In addition considering the economic investigations, the nanofluid employment bring about a reduction by around 3−4% in unit cost of product of cogeneration plant, depending on the operating conditions.

Modeling of diagrams of hardenability of steels with using machine learning methods.

One of the production’s main stages of pipes from low-carbon and medium-carbon steel grades is heat treatment. During the hardening process, the structure of the metal changes and, as a result, the mechanical properties change. Comparing various indicators, for example, hardness, strength, plasticity, etc., it is possible to judge how successful the heat treatment regimes have been selected. Therefore, it is important to pre-establish optimal conditions in order to obtain a metal with the necessary mechanical properties. Standard approximations that allow predicting the values of mechanical properties are usually not adaptive for use in different production conditions due to the fact that in most cases they are either inaccurate or tied to a specific production unit and, as a result, are not suitable for use in other (different) conditions. The purpose of this work is to construct steel hardenability diagrams using modern machine learning methods. The choice for the study is a complex of aggregated experimental data, which includes diagrams of the decomposition of super cooled austenite, tabular values and other types of data obtained from various sources. This article describes in detail the stage of preliminary data processing, model construction and validation. Special emphasis is placed on the process of processing the initial data for modeling and comparing the fundamental features of the model with the experimental ones. The analysis of the significance of signs with real physical prerequisites is carried out in a complex. In addition, the simulation results are compared with real cal inability diagrams

A Bi-Level Optimization Model for Inter-Provincial Energy Consumption Transfer Tax in China

The serious energy crisis and environmental problems resulting from fossil energy excessive consumption have caused severe challenges to the control of energy consumption and intensity (dual controls) and the sustainable development of China’s economy and society. The current territorial management model (TMM) of energy consumption “dual control” needs urgent improvement. Therefore, this study proposes an inter-provincial energy consumption transfer tax model (ECTTM) based on the Stackelberg game and bi-level optimization theory. In this model, the central government is the leader at the upper-level, and provincial governments are the lower-level followers. An optimization algorithm based on NSGA-II was designed to solve this model to obtain the optimal transfer tax rate and provincial energy consumption. The ECTTM aims to maximize the socioeconomic benefits of energy consumption overall and in each province under the premise of achieving the dual control target. The model’s effectiveness and superiority were illustrated through an empirical study of electricity consumption in Shanghai, Zhejiang, Shaanxi, and Guizhou. Compared with the TMM, the socioeconomic benefits under the ECTTM increased by 14.67%, and the electricity consumption per unit of gross domestic product decreased by 12.8%. Policy suggestions on the ECTTM’s implementation are proposed to promote further improvements in dual controls.

Optimal Sizing of Renewable Energy Communities: A Multiple Swarms Multi-Objective Particle Swarm Optimization Approach

Renewable energy communities have gained popularity as a means of reducing carbon emissions and enhancing energy independence. However, determining the optimal sizing for each production and storage unit within these communities poses challenges due to conflicting objectives, such as minimizing costs while maximizing energy production. To address this issue, this paper employs a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm with multiple swarms. This approach aims to foster a broader diversity of solutions while concurrently ensuring a good plurality of nondominant solutions that define a Pareto frontier. To evaluate the effectiveness and reliability of this approach, four case studies with different energy management strategies focused on real-world operations were evaluated, aiming to replicate the practical challenges encountered in actual renewable energy communities. The results demonstrate the effectiveness of the proposed approach in determining the optimal size of production and storage units within renewable energy communities, while simultaneously addressing multiple conflicting objectives, including economic viability and flexibility, specifically Levelized Cost of Energy (LCOE), Self-Consumption Ratio (SCR) and Self-Sufficiency Ratio (SSR). The findings also provide valuable insights that clarify which energy management strategies are most suitable for this type of community.

Efficiency of Using Heat Pumps in a Hydrogen Production Unit at Steam-Powered Thermal Power Plants

The need to increase the level of beneficial recycling of municipal solid waste (MSW) and the focus on low-carbon energy are increasing interest in the production of hydrogen from MSW. The presence of free space and excess capacity makes thermal power plants (TPPs) the most rational objects for the integration of units that produce hydrogen from MSW. The use of heat pumps (HP) will make it possible to use waste heat, increase heat output, and optimize the TPPs’ operating modes. The purpose of the study is to analyze the effectiveness of using HPs in the scheme for producing hydrogen from MSW at TPPs. The integration of a hydrogen-generating unit into the thermal circuit of a TPP will provide the necessary amount of vapor for the production of hydrogen but will lead to a decrease in the thermal efficiency of the plant. The use of HP will partially compensate for this decrease. For plants with a turbine of type T-100/120-130, when using HPs to heat network water, the reduction in electricity generation will be 1.9–32.0%, and the increase in heat supply will be 1.7–14.2%. The reduction in specific fuel consumption for an electricity supply will be 0–1.2%, an increase in marginal profit of 0.1–6.4%, with the MSW disposal of 10–90 t/h, and the hydrogen generation of 0.8–18.9 t/h.

The contribution of short food supply chains in the formation of agricultural income from different production systems in Brazil

Modern agri-food systems are complex and involve understanding nutritional, productive, institutional, and socioeconomic factors. This study aimed to measure the participation of short food supply chains in the formation of income generated from different production systems on the northern border of Rio Grande do Sul, Brazil. We used production systems as a methodological reference to analyze the internal and external relations at the production unit level, and based on the developed activities, we economically estimated the respective sales channels. Thirty-one farmers were interviewed between October and November 2019. The farmers considered in the sample developed more than one productive activity and accessed more than one marketing channel. According to the production carried out, we identified three production systems: vegetables, agro-industrial, and mixed. Each system has different specificities and contribution percentages to the total agriculture income. In the market, farmers mobilize conventional and alternative markets. The first was mainly used to commercialize of products such as commodities. Alternative channels were used to sell alternatively and/or traditionally produced food. Alternative systems and/or short channels allowed the elimination and appropriation of a higher percentage of generated wealth, contributing to the viability of smallholder farmers. A striking feature of the production systems analyzed was the diversification in production and sales. Although the product plays the greatest role in the income generated, other activities are important and contribute to the production unit’s productivity and economic stability.

Energy efficiency in the South African mining sector: A case study at a coal mine in Mpumalanga

Energy efficiency is a cost-effective way of both bolstering energy security and limiting the harmful effects of energy use on the environment. Mining is an inherently energy-intensive activity, and the 2008 revision of South Africa's National Energy Efficiency Strategy (NEES) set a target of a 10% reduction in energy consumption by 2015 for the mining sector. In this study, we investigate the effectiveness of the NEES in improving energy efficiency in the South African coal mining sector by surveying energy intensity at a number of operations, and analysing energy efficiency trends and energy use by process and energy carrier at an underground coal mine in Mpumalanga. Most mines surveyed exhibit an increase in energy intensity over time. At the case study mine, the increase was primarily due to increased energy use in the beneficiation and discard reclaiming processes. Trends in energy consumption are a poor reflection of trends in energy intensity, as a decline in energy consumption is most easily achieved by reducing production. A more appropriate metric for energy efficiency at coal mines is energy intensity, defined as energy use per unit of saleable product, relative to a multi-year baseline. The evidence suggests that the NEES has been ineffective in promoting energy efficiency in South African coal mines. We propose that greater success could be achieved by monitoring and reporting on energy intensity at the process level, and by incentivizing energy efficiency gains.