Environmental Emissions Research Articles

Occurrence, removal, and fate of benzothiazoles (BTHs) and benzotriazoles (BTRs) in two wastewater treatment plants in New York State, USA

Benzothiazoles (BTHs) and benzotriazoles (BTRs) are widely used in various consumer products. However, their occurrence and fate in wastewater treatment plants (WWTPs) in the United States remain poorly understood. In this study, wastewater and sludge samples were collected from two WWTPs from the Albany area of New York State (WWTPA and WWTPB) and the concentrations of three BTH derivatives (BTH, 2-OH-BTH, and 2-Me-S-BTH) and five BTR derivatives (1-OH-BTR, XTR, 4-OH-BTR, TTR, and BTR) were determined. The geometric mean (GM) concentrations of Σ(BTHs) and Σ(BTRs) in influent were in the range of 7550–8690 and 4590–6240 ng/L, whereas those in effluent were 6650–7150 and 4620–6800 ng/L, respectively. In the influent of two WWTPs, BTH, BTR, and TTR were identified as the major chemicals at respective GM concentrations of 8440, 4200, and 1280 ng/L in WWTPA, and 7300, 1180, and 2090 ng/L in WWTPB. The removal efficiencies of BTHs and BTRs following activated sludge treatment were < 80 %, and Σ(BTRs) showed a negative removal in both WWTPs. The respective mass loadings of Σ(BTHs) and Σ(BTRs) were 7240 and 5200 mg/d/1000 individuals in WWTPA, and 3530 and 2140 mg/d/1000 individuals in WWTPB. The environmental emissions of Σ(BTHs) and Σ(BTRs) from WWTP discharges were estimated at 3110–6030 and 2160–5700 mg/d/1000 individuals, respectively. Overall, BTHs and BTRs are not efficiently removed in WWTP processes. This study provides baseline information regarding the loading, fate, and discharge of BTHs and BTRs from WWTPs in the USA.

Influence of mandatory waste classification on environmental and economic impacts of residual waste treatment in Xiamen, China.

Mandatory waste classification has been widely considered as an effective solution for reducing the production and treatment amount of municipal solid waste. However, there is limited evidence regarding whether and how waste classification can affect the composition of residual waste (RW) and its environmental economic impacts. Here, an accounting method recommended by the Intergovernmental Panel on Climate Change, field surveys and cost-benefit analysis was utilized to investigate the changes in RW composition, environmental impacts and economic benefits under the waste classification policies implementation in Xiamen, China. This study found that: (1) The implementation of waste classification policies led to a significant increase in recyclable content from 17% to 51% and a decrease in organic content from 56% to 32%. (2) Waste classification effectively reduces greenhouse gas emissions from landfilling and incineration by an additional 0.34 tCO2-eq t-1 RW. (3) The introduction of mechanical recycling achieves a saving of 0.47 tCO2-eq t-1 RW at 40% recycling efficiency, a 4.5-fold increase compared to business as usual (BAU). (4) The operational benefits (900 yuan t-1 RW) from the recyclables sorting system offset the total expenses of investment, operation and waste disposal. The study successfully demonstrated that RW source-classified management can optimize the structure of waste composition, reduce environmental emissions and offer detailed guidance for the development of solid waste management systems in other cities in China.

Co-emissions of fluoride ion, fluorinated greenhouse gases, and per- and polyfluoroalkyl substances (PFAS) from different fluorochemical production processes

Fluorochemical industry is an emerging industry leading to environmental emissions of fluoride ion, fluorinated greenhouse gases (GHGs) and per- and polyfluoroalkyl substances (PFASs) globally. Chlorofluorocarbon (CFCs) and hydrochlorofluorocarbon (HCFCs) are the primary causes of ozone layer depletion, and together with hydrofluorocarbons (HFCs), they contribute to global climate warming. PFAS are emerging persistent organic pollutants, comprising thousands of materials including perfluoroalkyl acids (PFAAs), perfluoroalkane sulfonamides (FASAs), and fluoropolymers.As the implementation of the Montreal Protocol and the Stockholm Convention makes progress, fluorochemical industry is searching for alternatives like HFCs, perfluoroalkyl ether carboxylic acids (PFECAs) and etc. Even though studies on chemical processes and environmental influences of the fluorochemical industry are plentiful, research on emissions of fluorine chemicals from different fluorochemical industry is still scarce. In this study, we conducted on-site sampling to analyze the distribution of fluorine chemicals in the surrounding environment of the fluorochemical industrial sites. The sampling sites represent different stages of fluorochemical industry production, including fluorite mining, synthesis of fluorochemical raw materials like fluorocarbons, and fine fluorine product processing which is mostly PFAS. Results show that at the fluorite mining stage, concurrent emissions of fluoride ion and CFC-12 contribute to the primary environmental issue. Perfluorooctanoic acid (PFOA) and some short-chain PFASs like perfluorobutanoic acid (PFBA), perfluoropentanoic acid (PFPeA), perfluoroheptanoic acid (PFHpA), and perfluorobutanesulfonic acid (PFBS) are the main pollutants from fluocarbons production, accompanied by emissions of fluorinated GHGs such as HFC-32, and HCFC-22. At the fine fluorine product synthesis stage where produces fluoropolymers, perfluoropolyethers and fluorinated surfactants, PFAS especially for emerging alternatives PFECAs like hexafluoropropylene oxide dimer acid (HFPODA) and Perfluoro-4-oxapentanoic acid (PF4OPeA), as well as fluorinated GHGs like HFC-23 and HFC-227ea, require increasing attention.

Do Technological Innovation and Environmental Regulation Reduce Carbon Dioxide Emissions? Evidence from China

&lt;p style="text-indent:0cm; text-align:justify"&gt;&lt;span style="font-size:12pt"&gt;&lt;span style="line-height:150%"&gt;&lt;span style="font-family:&amp;quot;Times New Roman&amp;quot;,serif"&gt;The Chinese industry holds a significant position in the national economy. However, industrial carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) emissions account for a large proportion of the total CO&lt;sub&gt;2&lt;/sub&gt; emissions, which has a negative impact on the environment. To identify the factors affecting industrial CO&lt;sub&gt;2&lt;/sub&gt; emissions, a vector autoregressive (VAR) model system is established to empirically test the factors influencing industrial CO&lt;sub&gt;2&lt;/sub&gt; emissions, using data on industrial technology innovation (TI), environmental regulation, and CO&lt;sub&gt;2&lt;/sub&gt; emissions from 2000 to 2023 in China. The results show that there is a cointegration relationship between industrial technological innovation, environmental regulation and CO&lt;sub&gt;2&lt;/sub&gt; emissions. Each unit increase in environmental regulation will reduce 2.132 units of CO&lt;sub&gt;2&lt;/sub&gt; emissions. Meanwhile, each unit increase in technological innovation results in a decrease of 0.067 units of CO&lt;sub&gt;2&lt;/sub&gt; emissions. Compared with TI, environmental regulation has a greater impact on CO&lt;sub&gt;2&lt;/sub&gt; emission reduction. The effects of the impulses of the stochastic perturbation terms of industrial TI, environmental regulation, and CO&lt;sub&gt;2&lt;/sub&gt; emissions on the current and future values of industrial TI, environmental regulation, and CO&lt;sub&gt;2&lt;/sub&gt; emissions in the VAR system are de-picted through the VAR impulse response function. The contribution of each new interest shock to the change of industrial TI, environmental regulation and CO&lt;sub&gt;2&lt;/sub&gt; emissions is analyzed by variance decomposition. This paper enriches the application of institutional theory and technological in-novation theory in CO&lt;sub&gt;2&lt;/sub&gt; emission reduction and also provides a reference for relevant departments to formulate emission reduction policies and industrial technological innovation.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;

Environmental Exhaust Emissions reduction and Performance Improvement Analysis of biodiesel operated Diesel Engine Performance Using Operating Parameters

&lt;p style="margin-top:3px; margin-bottom:3px; text-align:justify; text-indent:31.5pt"&gt;The present investigation aims to study the performance and emission characteristics of a CI DI diesel engine using biodiesel blends derived from Jatropha seed feedstock. Four blends, namely B25, B50, B75, and B100, are employed as fuels to run the diesel engine at a rated speed of 1500 rpm, and their performance and emission characteristics are determined under different operating conditions in the first phase. The blend B25 of JME is found to be the optimum blend, and the optimum compression ratio is found to be 18.5.The optimum blend exhibits better performance in terms of brake specific fuel consumption (BSFC) and brake thermal efficiency (BTHE), along with a decline in the emissions of carbon monoxide (CO) and hydrocarbons (HC), except for the emission of nitrogen oxides (NOX) at the optimum compression ratio of 18.5. At maximum load, with a compression ratio of 18.5, the optimum blend results in better BSFC and BTHE, which are 0.255 kg/kW-hr and 31.87%, respectively.&lt;/p&gt;

Greenwashing or Going Green? An Empirical Analysis of the Drivers and the Effects of Carbon Offsets and Renewable Energy Certificates on Firm Performance

Carbon offsets and renewable energy certificates (RECs) are widely used instruments that help firms mitigate their greenhouse gas emissions (GHG). This paper investigates which internal firm characteristics are associated with investments in carbon offsets or RECs and how these purchases impact firms’ performance. Based on data from publicly traded firms in North America and Europe from 2012-2022, this paper uses a propensity score matching approach to analyze the effects of these investments on firms’ environmental scores, GHG emissions, and financial performance. Additionally, this paper employs an instrumental variable approach to examine whether board gender diversity increases carbon offset or REC purchases. The findings reveal that firms that purchase carbon offsets or RECs face higher environmental scores and higher GHG emissions, suggesting corporate greenwashing behavior. This paper also demonstrates that these purchases lead to higher sales, profitability, and assets, but lower Tobin’s Q for REC buyers. Lastly, this paper finds that a greater presence of women on the board does not lead to greater purchases of carbon offsets or RECs.

Interplay between economic progress, carbon emissions and energy prices on green energy adoption: Evidence from USA and Germany in context of sustainability

In contemporary times, where most academic research mainly focuses on the factors of economic and environmental sustainability and emissions reduction. Yet, very little attention has been paid to the identification of the factors of renewable energy, which requires appropriate policy-level attention. Consequently, this research investigated two developed economies, i.e., Germany and the USA, from 1991 to 2021 where, the objective of the study includes using novel and robust empirical methods to test the causal relationship between renewable energy and CO2 emissions, economic growth, technological innovations and oil prices. Using the normality and unit root estimators, this study observed that non-normal data distribution, yet all the variables are stationary. Using time-series and panel cointegration tests, the results validate the cointegration between economic growth, oil prices, carbon emission, technological innovation, and renewable energy adoption in the United States whereas Germany does not show cointegration between the variables. This study employ ‘s the Morlet-Wavelet approaches and key findings show that all these variables have a significant role in improving renewable energy adoption in both the region. Furthermore, results show a unidirectional and bidirectional causal association between the variables via the panel-stacked Granger causality test. This study recommends effective policy ramifications concerning improved investment in technological innovation, improved low-carbon production, and diverting economic growth to renewable energy transition. Use of improved new time-series method of wavelet coherence show the key contribution in this paper with new evidence of time frequency analysis on how external variables affect renewable energy consumption in developed countries of US and Germany. The objective includes understanding the effects of CO2 emissions, economic growth, technological innovations and oil prices on renewable energy which would give evidence to policy makers and environmentalists on how developed countries should improve clean energy adoption.

A study on supply chain information sharing strategy for emission reduction investment in electronic products based on game theory

By analyzing the competition between electronic product manufacturers and retailers in pricing, a dynamic game model is constructed. Using backward induction, the optimal choices and maximum profits under equilibrium conditions are determined. Finally, the constructed model is subjected to data simulation by setting numerical values for relevant parameters to analyze the effects of environmental emission reduction value on the supply chain and the information sharing value of each member. The following conclusions are drawn: when the emission reduction efficiency of manufacturers or the sensitivity of the market to environmental protection is high, the improvement effect of information sharing will outweigh its bilateral marginal effect. Retailers will voluntarily share all demand information and achieve a win-win situation in the supply chain.

Life cycle assessment and comparison of energy supply system technical innovation: A case study

As the key sector of energy consumption in China, the industrial sector contributes the most to environmental pollution and CO2 emissions. With the goals of reaching the peak of CO2 emissions by 2030 and achieving carbon neutrality by 2060, optimizing the energy supply system of industrial enterprises is significant to achieve low-carbon development. In this study, the case of system upgrading concerning waste heat utilization in a manufacturing unit is applied. The total environmental impact of the energy supply system before and after transformation is quantified and compared based on life cycle assessment method, with “cradle to gate” as the system boundary and one year of system operation as the functional unit. It can be found that the environmental impact of the energy supply system is reduced from 4.54 to 4.14 through technical innovation. The key processes contributing to the environmental impact of the system are the refrigeration system, soft water system and boiler system. Electricity consumption of refrigeration system, NaCl of the soft water system and natural gas of the boiler system are identified as key substances. Sensitivity analysis reveals that the environmental benefits of reducing electricity consumption will be more effective than that of NaCl and natural gas. With the transformation of waste heat utilization and the increase of photovoltaic power generation, the environmental impact of the system is reduced obviously, which is significant for the low-carbon transformation of the manufacturing industry.

Analyzing sustainability in bread production: a life cycle assessment approach to energy, exergy and environmental footprint.

Bread production is a pivotal component of global nutrition. However, its extensive production imposes significant strain on resources and energy, resulting in substantial environmental consequences. This study focuses on a multidimensional assessment of the environmental sustainability of the bread life cycle as a case study in Iran. By integrating four life cycle assessment (LCA) methods, this research demonstrates a comprehensive analysis of environmental effects, energy consumption, and exergy demand in bread production. It also identifies the hotspot stages and inputs within the bread production chain. Eventually, it proposes strategies for mitigating the environmental impacts in line with sustainable development goals. Data collection involved questionnaires by face-to-face interviews. The LCA evaluation was conducted using SimaPro software. Sustainability analysis was assessed using four different methods: CML, ReCiPe, cumulative energy demand (CED), and cumulative exergy demand (CExD) method, from cradle to bakery gate. The CML method results indicate that the highest environmental impacts are associated with marine aquatic ecotoxicity (157.04 to 193.36 kg 1,4-DB eq), fossil fuel depletion (11.05 to 12.73 MJ), eutrophication (4.20 × 10-3 to 4.70 × 10-3 kg PO4-3eq), acidification (8.09 × 10-3 to 9.16 × 10-3 kg SO2 eq), and global warming (0.61 to 0.69 kg CO2 eq). The ReCiPe method highlights wheat production stages and gas consumption as the most significant contributors to damage in terms of human health, ecosystems, and resource consumption indicators. The CED method reveals that fossil energy accounts for over 97% of the energy consumed during the bread life cycle. Energy consumption per kilogram of bread ranges from 12.07 to 13.93 MJ. The CExD method for producing 1 kg of traditional bread falls between 32.25 and 35.88 MJ. More than 60% of this value is attributed to renewable resources of water used in irrigation during the wheat farming stage, while over 35% is linked to non-renewable fossil resources, primarily due to the consumption of natural gas in bakery operations. To assess the potential decrease in environmental emissions, a sensitivity analysis was performed, considering the effects of substituting natural gas with biogas and grid electricity with photovoltaic electricity in the bakery. Then, three improved scenarios were developed, each demonstrating effective reductions in environmental impacts, with the most remarkable decreases observed in marine aquatic ecotoxicity (55%) and fossil fuel depletion (44%). Overall, the findings demonstrate that Sangak bread production exhibits a more environmentally friendly profile than other types of bread. These results can guide decision-makers in the bread production industry towards implementing sustainable practices that prioritize resource efficiency and environmental conservation. Also, stakeholders can develop strategies to reduce the environmental impacts and work towards a more sustainable future.

Determinants of the Willingness to Use Autonomous Mobility as a Service in Germany

Fully autonomous vehicles, once legally and technically feasible and widely available, have numerous advantages compared to human-driven vehicles, from greater availability and shorter travel times to lower negative environmental emissions and fewer accidents. This, combined with a usage-based form of payment, can massively increase the usage rate of vehicles without the need for high initial investments. This study explores the determinants affecting the willingness to adopt Autonomous Mobility as a Service (AMaaS) in Germany. Utilizing a mobile cross-sectional survey via Pollfish, 400 complete responses of German speakers aged 18 years or older in Germany were collected to assess influential factors. The survey data were analyzed using binary logistic regression analysis. Age, possession of a driving license, and the quality of public transport were identified as significant predictors. Younger people and driving license holders showed a higher willingness to use AMaaS, while low-quality public transport reduced their willingness to use it. This study concludes that targeted strategies for AMaaS implementation should consider these key demographic and infrastructural factors to maximize market penetration and acceptance in Germany.

Ecological Costs of A Microbrewery in The Brazilian Northeast

Objective: The aim of this study is to investigate the environmental and economic impacts of craft beer production in the Brazilian Northeast, to evidence the main hotspots and propose mitigation alternatives. Theoretical Framework: Life Cycle Thinking proposes a way of thinking that aggregates systems and preserves their interrelationships, to understand the whole of production systems and identify critical points in their subsystems, processes and flows. Here, environmental analysis was carried out through Life Cycle Assessment and economic analysis through Life Cycle Cost Assessment and Ecological Costs. Method: The methodology adopted for this research includes the use of Life Cycle Assessment to quantify environmental emissions, and Life Cycle Cost Assessment and Ecological Costs to quantify economic impacts in a microbrewery located in the Northeast of Brazil. Data was collected through interviews and questionnaires with those responsible for specific sectors of the brewery. Results and Discussion: The results showed that the main environmental hotspot was the local and regional distribution of beer using a gasoline-powered light commercial vehicle. In terms of economics, beer packaged in stainless steel kegs had the lowest cost and beer in aluminum cans had the highest manufacturing cost. When environmental costs were taken into account, beer packaged in a PET growler obtained the best result and beer packaged in a stainless-steel keg obtained the worst economic result. With the implementation of electric vehicle distribution, in addition to the environmental benefits, there were also economic benefits, especially in terms of environmental costs (ecocosts). Research Implications: The practical implications of this research have shown that the use of electric vehicles to distribute the final product (beer) can mitigate environmental emissions, bringing environmental and economic benefits to the company studied. Originality/Value: This study contributes to the literature by being the first Brazilian study to quantify the environmental and economic impacts of craft beer production and distribution. The relevance and value of this research is evidenced by the fact that it proposes tangible solutions to the hotspots identified.

The impact of renewable portfolio standards and land-use governance on CO2 and gross total emissions in four U.S. regions

This study's findings underscore the significant role of policies such as renewable portfolio standards (RPS) and court land-use decisions (CLD) in promoting environmental quality. The study, conducted between 2000 and 2021 in four US regions—Northeast, Midwest, West, and South—using the FGLS and PCSE methods, reveals that RPS and CLD are instrumental in reducing CO2 and gross total emissions (GTE). However, their effectiveness varies across regions. The Midwest, West, and South regions showed statistically significant improvements after implementing the RPS. The impact of land-use court decisions in the Northeast and Midwest states is statistically nonsignificant. RPS and CLD effectively decrease GTE in the Western and Southern states. The study also highlights the adverse effects of energy intensity and economic growth on the environment in all regions. However, it strongly emphasizes that clean energy sources like hydropower are critical in mitigating emissions. To achieve environmental sustainability and emissions reduction goals across the US, the study suggests a nuanced policy approach that prioritizes strengthening renewable and sustainable energy initiatives such as RPS, improving land utilization regulations, and promoting clean energy practices. It concludes that significant progress can be made towards these goals by adopting region-specific strategies and enhancing policy instruments like RPS and CLD.

Examining multiscale built environment interventions to mitigate travel-related carbon emissions

While established studies have explored interventions in the built environment (BE) and transportation sector to mitigate travel carbon emissions (TCE), planners still struggle to determine the most effective units of intervention, identify key variables, and determine their optimal values. This study addresses the gap by employing the extreme gradient boosting (XGBoost) model to create a multi-scale comparative framework. This study revealed that the relationship between the built environment and travel-related carbon emissions varies depending on the zoning and scale of the BE measurement unit. The explanatory power of TCE varies across different geographic units, with the 15-min walk distance buffer of residents being the most effective in explaining TCE. Most variables were nonlinearly associated with TCE, and the precise threshold of the association between BE attributes and TCE was quantified. Based on these findings, we provide precise and nuanced insights into BE interventions to reduce TCE.

Exploring drivers of behavioral willingness to use clean energy to reduce environmental emissions in rural China: An extension of the UTAUT2 model

In the context of the dual-carbon target, the adoption of clean energy in rural areas is an important basis for achieving effective carbon reduction in rural areas. On the basis of the Unified Theory of Technology Acceptance and Use (UTAUT2), this study uses structural equation modeling to investigate the influencing factors of rural clean energy adoption behavior. The results are as follows: (1) Both the expected effect of rural clean energy's adoption and adoption behavior are positively correlated with intention to adopt rural clean energy, whereas the rest are negatively correlated. The willingness to adopt clean energy has the greatest impact on clean energy adoption behavior in rural areas. (2) The expected effect of clean energy's adoption, subjective norms related to clean energy's adoption, facilitation of clean energy adoption support, and habits related to clean energy adoption have partial mediating effects on the impact of clean energy adoption intention. The reliability of clean energy's adoption has a full mediating effect on the impact of clean energy adoption intention. The perceived value of clean energy adoption has no significant mediating effect on the intention to adopt clean energy. (3) Age has a significant moderating effect on perceived value, related behaviors, and intention related to adopting clean energy; education level has no significant moderating effects on facilitation support or intention to adopt clean energy; and region has no significant moderating effects on facilitation support or adoption intention.

Demand-pull and technology-push environmental innovation: a policy mix analysis on EU ETS and EU Cohesion Policy

ABSTRACT Existing literature on the sustainability transition towards a low-carbon economy provides conceptual frameworks for designing combinations of policy interventions but lacks empirical evidence regarding their application. This paper aims to test whether a mix of policy instruments represents a potential valid solution to manage carbon abatement effectively. We refer to the European Union Emissions Trading System (EU ETS) as an example of demand-pull environmental policy, while we include the Structural and Cohesion Funds (SCFs) and the Horizon 2020 funds as examples of technology-push policies. Through the application of a panel event study, we find that the EU ETS generates a positive impact on environmental patent applications in the light manufacturing sector during the period 2013–2020, while EU ETS participation and financial support contribute to environmental innovation and CO2 emission reduction in the energy sector. Hence, those sectors where market dynamics allow avoidance of complete internalization of the carbon price may benefit from financial support to re-direct the technological change towards the sustainability transition. We demonstrate that the analysed policy mix contributed to a reduction of about 2.2% of total emissions produced by energy firms in the EU ETS during Phase III, which is in line with EU climate targets. Overall, our work may support policymakers in understanding the relevant factors that affect the impact of the policy mix on the environmental transition.

Reinforcement learning-based optimization for power scheduling in a renewable energy connected grid

Power scheduling is an NP-hard optimization problem that demands a delicate equilibrium between economic costs and environmental emissions. In response to the growing concern for climate change, global environmental policies prioritize decarbonizing the electricity sector by integrating renewable energies (REs) into power grids. While this integration brings economic and environmental benefits, the intermittency of REs amplifies the uncertainty and complexity of power scheduling. Existing optimization approaches often grapple with a limited number of units, overlook critical parameters, and disregard the intermittency of REs. To address these limitations, this article introduces a robust and scalable optimization algorithm for renewable integrated power scheduling based on reinforcement learning (RL). In this proposed methodology, the power scheduling problem is decomposed into Markov decision processes (MDPs) within a multi-agent simulation environment. The simulated MDPs are used to train a deep reinforcement learning (DRL) model for solving the optimization. The validity and effectiveness of the proposed method are validated across various test systems, encompassing single-to tri-objective problems with 10–100 generating units. The findings consistently demonstrate the superior performance of the proposed DRL algorithm compared to existing methods, such as multi-agent immune system-based evolutionary priority list (MAI-EPL), binary real-coded genetic algorithm (BRCGA), teaching learning-based optimization (TLBO), quasi-oppositional teaching learning-based algorithm (QOTLBO), hybrid genetic-imperialist competitive algorithm (HGICA), three-stage priority list (TSPL), real-coded grey wolf optimization (RCGWO), multi-objective evolutionary algorithm based on decomposition (MOEAD), and non-dominated sorting algorithms (NSGA-II and NSGA-III). Regarding the experimental results, it is important to highlight the importance of integrating RESs into larger power systems. In a 10-unit system with 2.81 % RE penetration, reductions of 3.42 %, 4.03 %, and 3.10 % were observed in costs, CO2 emissions, and SO2 emissions, respectively. Similarly, in a 100-unit system with a RE penetration rate of only 0.28 %, reductions of 3.75 % in cost, 4.42 % in CO2, and 3.34 % in SO2 were observed. These findings emphasize the effectiveness of RES integration, even at lower penetration rates, in larger-scale power systems.

Numerical simulation of the effect of coaxial and cross-axis injection modes on pulverized coal combustion in the raceway of blast furnace tuyere

The aim of this study is to investigate the influence of the angle of the pulverized coal (PC) injection lance on the combustion characteristics of fuel in the raceway of blast furnace tuyeres. Using FLUENT software, a Euler-Lagrange three-dimensional numerical model was constructed to analyze the influence of different positions of blast furnace tuyere coal powder injection lance (coaxial and cross-axis) on key parameters such as temperature distribution, gas flow, and combustion efficiency. The results demonstrate that adjusting the angle of the injection lance significantly modifies the average and peak temperatures in the raceway, while the composition of gas components remains relatively stable. When the injection lance angle is 10°, the average temperature and peak temperature in the raceway are 2294 K and 2747 K, respectively. When the injection lance angle is 12°, the combustion efficiency of the PC reaches 80.8%. This study reveals the significant impact of the injection lance angle on the combustion process. Especially at an angle of 12°, the combustion efficiency of the blast furnace significantly improves. With coaxial injection, the combustion rate increases as the distance between the injection lance tip and the tuyere increases. This paper is instructive for the optimization of the blast furnace combustion system, which improve fuel utilization efficiency and reduce environmental emissions. This paper provides practical recommendations for adjusting blast furnace operational parameters, offering insights for achieving more efficient and environmentally friendly industrial production.

Numerical analysis of heat gain to geothermal heat exchangers with moisture evaporation in the structure

Relevance. Provisions on the need to transition to alternative energy sources and energy security, reduction of environmental emissions and energy conservation in various industries can largely rely on the use of geothermal energy. A separate area in the field of modeling geothermal technologies is the study of thermal regimes of geothermal heat exchangers. The need to ensure reliable thermal contact between the geothermal heat exchanger and its environment leads to the use of a variety of backfills, including pre-moistened ones. Aim. Study of the intensification of heat supply to geothermal heat exchangers, taking into account the influence of moisture evaporation in its backfill, its characteristics and operating conditions of the systems under consideration. Methods. The solution to the problem was obtained by the finite difference method. An implicit difference scheme and sweep algorithm were used. The coordinate step ranged from 1 to 10 mm. Results and conclusions. Study was carried out for six months of continuous operation of a geothermal heat exchanger. When analyzing the thermal conditions of the system under consideration, the main attention was paid to the study of the intensification of heat supply to the geothermal heat exchanger, taking into account the influence of moisture evaporation in its backfill, its characteristics and operating conditions of the systems under consideration. It has been established that an increase in the humidity of the sand backfill of a geothermal heat exchanger leads to a growth in heat inflows by 3.2–7.8%. A significant influence of the unsteadiness of transfer processes on the intensification of heat transfer in the system under consideration was revealed. It was shown that the increase in heat flow to the geothermal heat exchanger due to the presence of evaporation is about 22%. The conclusion is substantiated that when choosing an option for regulating the thermal conditions of geothermal heat exchangers, the volumetric humidity of the sand backfill should be primarily changed.

Environmental performance of Penaeus vannamei shrimp production in intensive and super-intensive biofloc systems

Shrimp farms worldwide have been responsible for a series of social and environmental issues that affect their surrounding regions. Modern aquaculture seeks to achieve sustainable growth that offers a balance between environmental, economic, and social perspectives, and new aquaculture technologies have been developed and improved in recent decades. One such innovation is the biofloc technology (BFT) system, which is considered an alternative to conventional aquaculture because it allows for aquatic organism production with minimal water exchange, high stocking densities, and the possibility of high levels of productivity. Life Cycle Assessment (LCA) is one of the most common methodologies used to compare the environmental performance of different systems, considering resource consumption and the emission of pollutants during the productive life cycle. The present study uses LCA to compare the environmental performance of Penaeus vannamei shrimp production in two BFT systems, an intensive system in a pond and a super-intensive system in a greenhouse. The Functional Unit used was 1.0 ton of shrimp (animals with an average final weight of 12 g). The boundaries of the system were defined as from the cradle to the farm gate. Input data related to the use of natural resources, energy consumption, and environmental emissions were obtained over eight cycles of intensive and super-intensive production. The following results were obtained for intensive and super-intensive systems, respectively: global warming (GWP100a) 5691.12 and 5512.42 kg CO2 eq; acidification 59.57 and 59.05 kg SO2-eq; eutrophication 25.96 and 25.80 kg PO4 eq; ozone layer depletion (OLP) 0.000319 and 0.000311 kg CFC-11 eq; human toxicity 1165.98 and 1233.33 kg 1.4-DB-eq; aquatic ecotoxicity 1344.13 and 1925.96 kg 1.4-DB eq; marine ecotoxicity 1881,643.65 and 2070,517.23 kg 1.4-DB eq; terrestrial ecotoxicity 24.26 and 33.54 kg 1.4-DB eq; photochemical oxidation 2.10 and 2.03 kg C2H4 eq; abiotic depletion 0.006487 and 0.008359 kg Sb eq; abiotic depletion of fossil fuels 35,612.80 and 34,504.39 MJ. Among the eleven evaluated impact categories, the intensive system showed better results in five categories, while the super-intensive system showed better performance in six categories. Feed (reference diet) was the most significant factor in the environmental performance of the evaluated systems. Based on these results, we conclude that feed and electricity had the most environmental impact in both systems. In general, when comparing the use of production factors and productivity between the systems, it becomes more evident that the SS is more efficient than the SI.