High Emission Research Articles

Effective hydrogen supply chain management framework considering nonlinear multi-stage process uncertainties

The large amount of carbon emitted due to industrial development is posing serious climate change. Under these circumstances, hydrogen energy is being used as a major energy source and is attracting attention as an alternative energy to fossil fuels, characterized by high carbon emissions. While the use of hydrogen has the obvious benefit of a low carbon footprint, the hydrogen production process possesses a high carbon footprint difference depending on the source of utilized electricity. This study considers several situations arising in an electrolysis-based hydrogen supply chain network (HSCN). A multi-stage stochastic programming (SP) is modeled to consider the uncertainty of demand and transportation capacity generated in HSCN. Moreover, a typical stochastic model has a chain rule between the decision variables resulting from nonlinearity and uncertainty, and these features make it difficult to derive an effective solution. Thus, in this study, a new methodology, Weighted Scenario Sample Average Approximation (WSSAA), is proposed to derive an effective solution for the multistage SP model considering various scenarios under the hydrogen supply chain. While a general stochastic programming approach fails to generate feasible solutions with volatile HSCN uncertainties, the proposed WSSAA framework provides feasible decisions considering multiple scenarios. The effectiveness of the proposed model applied with WSSAA is demonstrated through comparative experiments over the models used in existing studies.

The stimulating effects of international emission price fluctuations on bioenergy development of an energy-importing economy

An increase in emission price creates economic incentives because bioenergy producers could sell bioenergy and realize values attached to emission offset. Recently, the termination of the short-term goal of carbon neutrality in some European countries has skyrocketed, and demand for fossil energy has increased, as has the emission price. This situation brings challenges and opportunities to an energy-importing economy like Taiwan, which relies on fossil imports and is vulnerable to price distortions but also gets a chance to develop low-carbon energy domestically. This study proposes a mathematical programming model to investigate how such variations in emission price would affect bioenergy development from energy crops and how bioenergy producers with different production possibilities would behave in uncertain market conditions. Some insightful results are explored. First, bioenergy producers would change their production strategies from energy-focused technologies to emission-oriented ones because the gain from co-products would make emission offset more profitable. At a high emission price, biopower production declines from 11,492 GWh to about 3315 GWh. Still, more than 8.73 million tons of biochar is produced, and the total offset from bioenergy and biochar sequestration expands to 33.7 million tons of CO2. Second, the production pattern of energy crops varies substantially under market conditions. Energy crop plantation at low energy prices is 227,000–263,000 ha but expands to 638,000–798,000 ha when energy and emission prices increase. Third, reducing bioenergy production does not necessarily minimize social welfare because the gain from carbon sequestration may outweigh the loss from reduced bioenergy production at high emission prices. Potential policies that can be applied to adjust production strategies are also discussed in detail.

Radio properties of green pea galaxies

Green peas (GPs) are young, compact, star-forming dwarf galaxies, and local (\(z analogues of the early galaxies (\(z 6\)) considered to be mainly responsible for the reionisation of the Universe. Recent X-ray observations of GPs led to the detection of high excess emission, which cannot be accounted for by star formation alone and implies the presence of an active galactic nucleus (AGN). We employ radio observations to study the radio properties of GPs, build their radio spectral energy distributions, and verify the presence of AGNs. We performed new radio observations of three GPs with the Karl G. Jansky Very Large Array (JVLA) in the L, C, and X bands (1.4, 6 and 10 GHz resp.) and analysed them alongside data from archival observations and large radio surveys. We also analysed the archival radio data for a larger sample of GPs and blueberry (BBs) galaxies, which are lower-mass and lower-redshift analogues of the GPs. To understand the significance of the radio observations, we assess the detectability of these sources, and compare the detected radio luminosities with expectations from theoretical and empirical relations. Two of the three targeted GPs are strongly detected (\(>10 in the JVLA observations and their fluxes are consistent with star formation, while the third source is undetected. Although archival radio surveys have the sensitivity to detect a large fraction (\( 75<!PCT!>\)) of the sources from the larger archival sample of GPs and BBs we only detect a small number (\(< 40<!PCT!>\)) of them and their radio luminosity is significantly lower than the expectation from empirical relations. Our results show that the majority of the dwarf galax ies in our sample are highly underluminous. The radio luminosity star formation rate (SFR) relation deviates from the empirical relations, especially towards the lower end of galaxy mass and SFR, suggesting that the relations established for larger galaxies may not hold towards the low-mass end.

The productivity paradox in carbon‐intensive companies: How eco‐innovation affects corporate environmental and financial performance

AbstractEmpirical studies analyzing the relationship between strategies to reduce greenhouse gas (GHG) emissions and firms' environmental and financial performance often fail to find significant effects when firms invest in innovative green technologies. Indeed, as efficiency and productivity gains of new technologies can often be reaped only after a certain time gap, cross‐sectional studies are bound to ignore the time component, thus becoming subject to the productivity paradox. Employing an integrative approach, drawing on eco‐efficiency theory, productivity paradox, and innovation diffusion principles, this longitudinal study observes companies with high GHG emissions during and after the first two European Union Emission Trading Scheme (EU ETS) trading periods (2005–2019). It analyzes (1) the dynamics of carbon reduction practices over time, (2) the impact of GHG reduction strategies on environmental performance, (3) the positive effect of GHG‐related efficiency improvements on firm performance, while considering (4) the moderating effect of GHG emissions type on the latter relationship.

Feasibility of Electric Fishing Boats based on Evaluation of Hydrostatic Forces and Resistance

Conventional gasoline engine fishing boats have several disadvantages, such as high exhaust emissions, high fuel consumption, and low service life. The disadvantages of the gasoline engine can be resolved by using the electrical engine. Electrical fishing boats is an improvement on conventional boat to reduce the fuel consumption and emissions. In realizing an electric fishing boat, a feasibility analysis of the design, shape and weight that can be accommodated is required. The feasibility of an electric fishing boat has been successfully carried out by simulating the boat on Maxsurf Software. The aim of this research is to analyze feasibility of conventional boats by designing electric fishing boats. Improving feasibility is carried out by calculating hydrostatic forces and resistance. Electric fishing boats design using the simulation model in Maxsurf Modeller and simulation of resistance in Maxsurf Resistance at speeds of 1, 3 and 5 knots, with Wyman method. The modeling results show that the electric fishing boat design has a pointed front configuration with a V-shaped bottom. Main dimensions LoA 3.49 m, width 0.8 m; height 0.5 m; and a draft of 0.2 m, the boat produces a hydrostatic force which includes a displacement of 301.5 kg, a midship draft and submerged area of 0.2 m, a wet area of 3.08 m2, and a waterline of 0.5 – 1.5 m. Testing 1, 3, and 5 knots, the boat experienced resistance of 26.11 N, 234.96 N, and 652.73 N respectively. The power required for the boat to operate was 13,43 W, 362.66 W, and 1678,97 W. The feasibility of designing an electric fishing boat is the main key to developing an electric fishing boat.

Large-eddy simulation investigation on the effects of inlet swirl/Reynolds number and fuel heating value on a turbulent kerosene spray flame

To progress toward the high efficiency and low emission aviation engine technology, it is mandatory to understand the complex phenomena including kerosene spray atomization, evaporation, turbulent mixing and combustion in the engine combustor. Nowadays with the rapid growth of computational capacity over the world, large-eddy simulation (LES) performs a more and more important role in understanding the complex multi-phase combustion process of kerosene fuels in aviation engine configuration. In the present work, LES is employed to investigate a swirling kerosene spray jet flame in a model combustor, which has been studied experimentally. The turbulent combustion is modeled by the flamelet generated manifold (FGM) approach with a 3-component surrogate kerosene skeletal mechanism. The averaged gas velocity and temperature predicted by LES generally agrees well with the experimental measurements. Local extinction is observed at the inner shear layer of the swirling spray flame, due to droplet-turbulence-flame interactions. A parametric study with 11 cases is then performed to investigate the effects of inlet swirl/Reynolds number and fuel heating value on the kerosene flame. As the swirl number increases, the enhanced turbulent mixing between kerosene fuel and air facilitates the combustion process, but combustion instabilities may occur if the swirl number is too high. A higher Reynolds number can promote the turbulent combustion via a stronger recirculation zone, but it also has strong dilution effects on the combustion field. Variations in the fuel heating value directly impact the temperature field, but the flow field, major species concentrations and droplet phase statistics are only slightly affected. These LES results give clues to achieve optimal combustion performance in realistic aviation engine configurations via better arrangements of fuel and air injections.

Environmental challenges and air pollution in Bac Lieu, Vietnam: assessing sources and impacts

AbstractBac Lieu, a region with diverse industries like handicrafts, agriculture, tourism, and a thriving marine economy, faces environmental challenges from climate change, resource exploitation, and rising air pollution due to vehicular, industrial, and agricultural emissions, along with waste management issues. The materials and methods employed in this study encompassed various phases critical for assessing air quality and devising an Air Quality Management Plan (AQMP) for Bac Lieu province. The AQMP framework involved activities such as baseline assessments, emission inventories, air quality monitoring, and modeling using dispersion models like AERMOD. The study proposed the application of the AirQ + model to analyze the correlation between air quality and human health, emphasizing the short-term effects of pollutants on respiratory and cardiovascular diseases, and estimating potential avoidable cases in Bac Lieu province. The emissions inventory in Bac Lieu province categorizes sources into point, mobile, and area. Major CO emissions come from waste burning, cooking, and mixed sources, while traffic significantly impacts CO levels. Residential areas show significant PM10, PM2.5, and NO2 emissions. Point sources impact nearby areas, notably in districts like Hong Dan and Phuoc Long. Cooking activities lead to high PM10 and CO emissions, especially in Bac Lieu city. Traffic emissions, particularly in urban hubs, significantly contribute to pollution, notably in Bac Lieu City, Vinh Loi, and Hoa Binh districts. Transportation emissions in urban zones contribute significantly to air pollution, while rural areas are influenced by various activities like burning, construction, and cooking, shaping diverse local air quality.

Structural and Spectroscopic properties of Eu3+ doped SiO2–TiO2 nanoparticles for photonic applications

The Eu3+-doped TiO2 nanoparticles in sol gel silicate glasses of composition (80-x)SiO2 + 20TiO2 + 0.5xEu2O3, (SiTiEu) where x = 0.0 0.5, 1.5, 2.5 and 3.5 mol%, have been prepared by sol-gel technique. The glass samples were investigated by thermos-gravimetric analysis (TGA/DTA), ATR-FTIR, XRD, SEM, TEM, EDX, optical absorption and photoluminescence emission spectroscopy at room temperature (RT). The absorption wavelength of TiO2 doped sol-gel silicate glass were red shifted due to a reduction in band gap energy with increasing annealing temperatures. According to the TEM images, all of the particles were spherical and had an average diameter is around 10 nm. The visible spectra of the Eu3+ doped TiO2 nanoparticles in sol-gel silicate glasses displayed characteristic PL emission 5D0→7FJ (J = 0, 1, 2, 3, 4, 5) transitions of Eu3+ ions at 370 nm excitation. The anatase TiO2:1.5Eu3+ nanocomposite showed high photoluminescence emission at 370 nm excitation, which was attributed to the f-f transitions of Eu3+. The hypersensitive 5D0→7F2 transition was responsible for the major red emission. From the recorded spectra, radiative parameters and Judd-Ofelt (JO) intensity parameters were computed. The Eu3+ co-doped TiO2 nanoparticles in sol-gel silicate glasses displayed emissions mostly in the red regions realized from a CIE chromaticity diagram. The results suggested that materials may be used as an optical material of technological importance such as display devices and also for optical amplifier.

Low-Carbon Ecological Tea: The Key to Transforming the Tea Industry towards Sustainability

The realization of the value of ecological products has led to an economic means for reducing carbon emissions in China. Tea is one of the most important cash crops and one of the most popular beverages in the world. Due to the complex the tea industrial chain, it is considered to be an industry with high carbon emissions. Ecological tea products with low-carbon attributes can be considered a linkage of ecology, economy, and society. Based on this, this paper presents research on low-carbon ecological tea (LCT). Herein, we construct the formational logic of low-carbon ecological products, explore the connotations of LCT, and form a conceptual pathway for realizing LCT to contribute to climate change mitigation and adaptation. This paper starts from the upstream, midstream, and downstream of the industrial chain; it establishes three value realization pathways that keep, as a priority, the promotion of ecological industrialization, focus on restoration to improve the ecology of the industrial chain, and innovate technology to expand the industrial chain. The pathways are a set of low-emission production solutions that use techniques to enhance carbon sequestration in soil, reduce the use of fertilizers and pesticides, and help shift to clean energy from low-emission sources in the stages of plantation, processing, and distribution. In the process of realizing LCT, the government plays an important role, and its support and guidance are needed. Based on stakeholder theory, this paper builds an implementation mechanism that focuses on the micro perspective (users, organizations), integrates the mesoscopic perspective (industry), and relies on the macro perspective (government).

Projected poleward migration of the Southern Ocean CO2 sink region under high emissions

The Southern Ocean is a major region of ocean carbon uptake, but its future changes remain uncertain under climate change. Here we show the projected shift in the Southern Ocean CO2 sink using a suite of Earth System Models, revealing changes in the mechanism, position and seasonality of the carbon uptake. The region of dominant CO2 uptake shifts from the Subtropical to the Antarctic region under the high-emission scenario. The warming-driven sea-ice melt, increased ocean stratification, mixed layer shoaling, and a weaker vertical carbon gradient is projected to together reduce the winter de-gassing in the future, which will trigger the switch from mixing-driven outgassing to solubility-driven uptake in the Antarctic region during the winter season. The future Southern Ocean carbon sink will be poleward-shifted, operating in a hybrid mode between biologically-driven summertime and solubility-driven wintertime uptake with further amplification of biologically-driven uptake due to the increasing Revelle Factor.

Reinforcement learning-driven proximal policy optimization-based voltage control for PV and WT integrated power system

The depletion of conventional fuel reserves and the high carbon emissions have alarmed the energy sector drivers. The integration of renewable energy resources (RERs) towards power system transformation is an obvious approach for a new-zero future. However, this integration also brings challenges in terms of voltage stability and power losses due to the variable output of RERs. To address these challenges, this work proposes a novel approach utilizing photovoltaic (PV) inverters and static var compensators (SVCs) for reactive power control in power distribution networks (PDNs). It enhances voltage stability and minimizes power losses. The proposed study deploys a proximal policy optimization (PPO) algorithm for real-time communication and control between reactive power devices. Performance evaluation was made on an IEEE-33 Bus system to demonstrate the effectiveness of the proposed scheme in integrating RER-based distributed generators (DGs). The proposed system achieved 68 % voltage control, keeping the voltage within a certain range of ±5 % while minimizing power losses. The proposed system also reduced the voltage out-of-control ratio to 0.044, which indicates minimum voltage deviation from the standard value. The proposed study provides a promising solution for controlling the voltage of DGs integrated PDN, which can potentially enhance the efficiency and reliability of the power system.

High reflectivity and high emissivity integrated double layer coating on the flexible alumina fiber fabric with enhanced heat-dissipation efficiency

High emissivity coatings on hypersonic vehicle surfaces dissipate heat by emitting thermal radiation. While the difficulty of increasing emissivity limits the performance of coatings to improve heat-dissipation of the thermal insulation felt. Herein, a novel high-reflectivity and high-emissivity integrated double-layer coating was developed to enhance the thermal insulation performance of the alumina fiber fabric. The coating comprised of TiO2@SiO2 (T@S) as reflective agent and ZrO2/SiCw (ZSC) as emittance agents, was applied on the surface of alumina fiber fabric (AFF). The reflecting effect of radiation heat from the high reflective agent enhanced the thermal insulation properties of the double-layer coating. In the wavelength range of 0.4–2.5 μm, the average emissivity of the ZSC coating was 0.83 and the average reflectivity of the T@S coating was 0.63. With continuous heating at 1400 °C for 10 min with a butane torch, the temperature on the backside of the T@S–ZSC-coated AFF remained relatively stable at 225 °C, which is notably decreased by 80 °C compared to that of the single-layer ZSC-coated AFF. The tensile strength of AFF with T@S–ZSC coating reached 35 MPa after being heat treated at 1200 °C. Moreover, the bonding strength between the coating and the AFF substrate was measured to be 0.15 MPa. The double-layer coating with high emissivity and reflectivity, along with a flexible AFF substrate, offers a promising solution for addressing the challenging of surface heat-dissipation in hypersonic vehicles.

How does market-incentive environmental regulation affect enterprises green growth? The mediating role of R&D investment and innovation output

Manufacturing enterprises is a country's economic mainstay. However, their longtime extensive growth pattern of “high growth and high emission” has brought huge environment pollution and restricted sustainable development. Under the circumstance of carbon reduction and global green development, market-incentive environmental regulation (MER) has attracted the attention of scholars and become a kind of important methods of encouraging manufacturing enterprises green growth. Presently, two fairly distinct viewpoints of “Follow Cost” and “Porter Hypothesis” both have their own supportive research results, and the explanation for the role of MER is completely opposite. What's more, empirical research at the enterprise level is scarce. Therefore, this study makes a further analysis from the perspective of enterprises heterogeneous innovation ability. Guided by the classic theory of “Follow Cost” and “Porter Hypothesis”, this study aims to evaluate the applicable conditions of MER's environmental improvement effect, and testing the differential impact mechanism of MER on enterprise Green Total Factor Productivity (GTFP), enterprise Green Technological Change (GTC) and enterprise Green Efficiency Change (GEC). All these give theoretical and empirical supplementation for the rationality of related theories. This study examines the hypotheses and mechanism according to 1220 Chinese manufacturing listed companies data 2011–2020. The empirical results indicate that: (1) In short term, MER has a significant positive impact on GTC, and a significant negative impact on GTFP and GEC. (2) As innovation driven factors, both enterprise R&D investment and innovation output play the mediating role. (3) Heterogeneity analysis indicates that the impact mechanism varies depending on enterprise industry-type, location and digital level. Thus, policymakers should develop appropriate MER policies, and manufacturing enterprises should strengthen technological innovation to help achieve environmental sustainability and profit performance.

Agricultural sustainability assessment and national policy-making using an axiomatic mathematical model

Agriculture is a basic activity of human survival and its sustainability is of the utmost importance. In this paper, we present a novel mathematical model for the assessment of agricultural sustainability, based on certain intuitive and fundamental postulates. The resulting mathematical framework generalizes most existing models. We then rank 148 countries according to their agricultural sustainability, using data from the period 1995 to 2022 and pinpoint those aspects with the highest potential of improving sustainability using sensitivity analysis. Our findings demonstrate that farming is mostly unsustainable worldwide. The most crucial factors are connected with bad water use, destruction of biodiversity, and the prevalence of conventional chemical farming. As expected, poor countries make the bottom of the sustainability list. Surprisingly, several advanced countries such as Belgium, Japan, the Netherlands and Norway also occupy the bottom of the list because of very high emissions and bad performance concerning land and biodiversity. Finally, the highest score worldwide is of the order of only 70% and the median 50%, which exhibit a rather unsatisfactory farming state of affairs. Such findings ought to guide immediate action to make agriculture more sustainable.

Analysis of night behavior and negative running for PVT system

High absorption of PV benefits heat collection in the daytime, but the heat loss to the space/environment because of its high emissivity also should be noticed. Although there are many papers investigating PVT, few of them cover the night behavior and negative running during late afternoon. This paper supplements detailed studies on related content to draw people’s attention to the night and late-afternoon operation that helps better strategy establishment and less heat loss. From experiments, the clouds help hinder the PV radiant heat exchange with space. Under clear night, the PV bottom temperature can be 6.88°C lower than air temperature and the water tank’s bottom temperature drops 2.8°C. Because of the fluid viscosity, no apparent temperature stratification and flow occur in the PVT water pipe, causing even PV temperature. The higher the water temperature, the easier the negative running occurs during late afternoon, although the irradiation is still high at 521W/m2. Heat loss power and energy are -199W and 1791KJ from 15:10 to 17:40. Based on different regressed linear correlations of different PVT systems, the effect of water temperature, irradiation, and ambient temperature on the negative performance is also comparatively studied.

Compound successive dry-hot and wet extremes in China with global warming and urbanization

Global warming has accelerated the interregional hydrological cycle, resulting in a significant increase in the frequency and intensity of extreme events worldwide. These events often involve a combination of spatial and temporal factors, giving rise to compound events. Among them are rapid transitions from dry and hot conditions to wet (DHW) events, which can have more severe impacts on human societies and ecosystems than individual extreme events. Urbanization not only heightens the likelihood of disasters but also exacerbates the exposure of affected populations. However, there has been insufficient attention given to understanding the connections between these successive compound events and the heightened risks posed by the increasing urbanization. In this study, we used bias-corrected daily precipitation and maximum temperature data simulated by the Coupled Model Intercomparison Project Phase 6 (CMIP6) model, along with historical and future daily runoff data simulated by the Variable Infiltration Capacity (VIC) model. We systematically investigated the spatiotemporal changes (i.e., frequency, duration, intensity, and compound probability) in DHW events in China during the upper historical period (1979–2014) and under two medium and high emission scenarios (2015–2100) − Shared Socioeconomic Pathways (SSP245 and SSP585). Furthermore, we examined how extreme runoff responds to variations in maximum temperature and daily precipitation during DHW events. We also evaluated the potential population and urban exposure to DHW events using dynamic future population and urban expansion data to assess the potential risks. Our results indicate that the multi-model ensemble predicts varying spatial patterns of future DHW events under SSP245 and SSP585 scenarios. The frequency and duration of these events are expected to decrease by approximately 20–25% in the Northwest region under both scenarios. At the same time, the middle and lower plains of the Yangtze and Yellow River Basins experience increased occurrence, broader geographical impact, and higher DHW event intensity alongside urban expansion and population growth in these regions. Specifically, event intensity is anticipated to increase by a factor of approximately 7–11. Temporally, we expect short-duration, high-intensity DHW events to occur in the Yangtze and Yellow River basins around 2023, 2038, and 2058, respectively. The primary driver for the future rise in population exposure to DHW events is the expected increase in event frequency in the middle and lower plains of the Yangtze and Yellow River basins, concurrent with population growth in these regions. Under the medium emission scenario, the total exposed population to DHW events in China is predicted to be 1.61 times higher than the historical baseline. In contrast, the high-emission scenario estimates a total population of 2.41 times higher than the historical baseline period. Most of the DHW events occurred in regions that exhibit a positive dependence between high temperature and high runoff events, serving as the primary driver of DHW events. Urbanization has a positive impact on DHW events, with the effect under high emissions being approximately 30% higher than during the historical base period. Additionally, it is indicated that future DHW events will exhibit higher sensitivity to global warming, with intensity projected to increase approximately fourfold and the exposed population to rise by about 1.5 times for every 1 °C of global warming. This research enhances our understanding of forecasting future compound hydrometeorological extreme events under different scenarios and provides insight into the role of climate change and urbanization in shaping these events in China.

A strategy to assess the use-phase carbon footprint from energy losses in electric vehicle battery

The electric vehicles are not completely emission-free. The vehicles consume power and the power generation processes involve carbon emissions, resulting in indirect vehicle usage carbon emissions. A use-phase carbon emissions assessment can help electric vehicle designers and manufacturers analyze the onboard carbon footprint and mitigate vehicle-related carbon emissions through energy consumption optimization. In this article, we focus on the use-phase carbon footprint based on the energy losses in electric vehicle battery packs. A battery pack energy loss model is established to examine the carbon footprint of four main subsystems of the battery pack, including the energy storage system, thermal management system, and battery junction box. We use the proposed method to evaluate the battery pack use-phase carbon emissions in four different cities from four main continents. The results show that the highest emissions appear in Tokyo (436.2 kgCO2) due to the relatively high greenhouse gas factor on the grid, the London has the lowest 207.5 kgCO2 emissions due to the massive adoption of sustainable energy during power generation. With a similar high greenhouse gas factor, but Sydney shows lower emissions (347.5 kgCO2) compared to Tokyo, which illustrates the closer the annual average temperature to the battery suitable operation range, the lower energy loss happens inside the battery pack due to the low thermal management load and resistance energy loss in the cells. This electric vehicle has the highest energy loss rate (20.8%) in New York, 343.6 kgCO2 emissions, and the highest thermal management system energy losses show the high seasonal temperature difference causing the high thermal management load to maintain the battery temperature. The proposed method can be used for different battery pack configurations and vehicle uses, providing researchers with a robust and versatile use-phase carbon emissions assessment strategy.

Analysis and prediction on carbon emissions from electrical and electronic equipment industry in China

This research employs the IPCC methodology to assess carbon emissions from China's Electrical and Electronic Equipment (EEE) industry for 2012–2020, utilizing the GM (1) model to predict emissions for the next decade. Six scenarios evaluate emissions, guiding strategies for reduction. Key findings reveal the usage phase as the highest emitter, while WEEE dismantling incurs the lowest. In 2020, emissions from production, sales, transportation, usage, recycling transportation, dismantling, and recycling were projected. Scrapping imported EEE from 2012 to 2020 results in 1.88 million tons of emissions. Projected 2030 emissions, under current policies or low-carbon measures, are 136 million tons and 72 million tons, respectively. Urgent actions, especially in Extended Producer Responsibility (EPR) and stakeholder roles, are essential. The study advocates for consumer awareness on energy conservation and reducing dependence on imported products. Manufacturing emissions highlight the need for eco-design, emphasizing sustainable practices. Recycling and dismantling phases also contribute emissions, necessitating optimized routes and advanced technologies. In addition, the study explores the potential for carbon reduction by incorporating the organic combination of carbon trading markets, evaluating the carbon emission reduction potential of recycling enterprises. The proposal suggests replacing government subsidies with the sale of carbon credits, not only to stimulate companies to actively promote green dismantling but also to address the current inadequacy of subsidies. Establishing a comprehensive life cycle management system is crucial to minimizing the EEE industry's carbon footprint and promoting a sustainable future.

Impact of absorber surface coatings on the thermal performance of non-concentrating solar thermal collectors: An overview

In this critical evaluation, the impact of absorber surface coating on the thermal efficiency (%) of non-concentrating solar thermal collectors (STCs) is examined and discussed. Absorber surface coatings enable an almost instantaneous conversion of solar radiation into heat. To achieve high sunlight absorption capacity and low solar emittance, several types of selective solar coatings are continually being developed. This review article offers a novel aspect based on extensive research that has been published in the past related to the impact of absorber surface coating on the thermal performance of non-concentrating STCs. The article demonstrates the commonalities in the results by thoroughly evaluating all the coating types that have the potential to influence STC's performance. An exhaustive examination of the available research from several studies shows that absorber surface coating enhances the STC absorber's capacity to absorb heat.

A systematic analysis of energy-saving potential of spectrum-selective radiative cooling materials in buildings

Passive cooling of buildings through radiative cooling (RC) is considered an effective method for reducing the energy consumption of air conditioning. In recent years, spectrum-selective RC materials (RCMs) have received extensive attention owing to their low solar absorptivity and high thermal emissivity in the atmospheric window. The energy-saving performance of RCMs is related to their own properties and local meteorological conditions, building type, building form, and energy use patterns. Although several studies have explored the performance of RCMs, most existing studies have considered a single building type and meteorological condition, and simple building forms that differ significantly from real buildings. Hence, the application analyses of RCMs to buildings are not sufficiently comprehensive. This study focused on the energy-saving potential of RCMs for building applications, and presented a systematic framework to analyze the energy-saving potential of RCMs under different conditions. DeST, which is embedded with a long-wave radiative heat transfer calculation module based on the equivalent sky temperature, was adopted as the simulation software. It can accurately calculate the radiative heat transfer in different wavelength bands, thus making the simulation results more accurate. Based on the calculation results of large-scale cases considering four major factors, namely climate, building type, construction year, and installation location of RCMs, the energy-saving performance of RCMs in different cases was analyzed, and the return on investment is performed, and more comprehensive suggestions were provided for applying RCMs in future buildings.