[Bayesian network prediction study on the impact of occupational health psychological factors on insomnia among thermal power generation workers].

Objective: To explore the risk factors of insomnia among employees in the thermal power generation industry and the network relationships between their interactions, and to provide scientific basis for personalized interventions for high-risk groups with insomnia. Methods: In November 2022, 860 employees of a typical thermal power generation enterprise were selected as the research subjects by cluster sampling. On-site occupational health field surveys and questionnaire surveys were used to collect basic information, occupational characteristics, anxiety, depression, stress, occupational stress, and insomnia. The interaction between insomnia and occupational health psychological factors was evaluated by using structural equation model analysis and Bayesian network construction. Results: The detection rates of anxiety, depression and stress were 34.0% (292/860), 32.1% (276/860) and 18.0% (155/860), respectively. The total score of occupational stress was (445.3±49.9) points, and 160 workers (18.6%) were suspected of insomnia, and 578 workers (67.2%) had insomnia. Structural equation model analysis showed that occupational stress had a significant effect on the occurrence of insomnia in thermal power generation workers (standardized load coefficient was 0.644), and occupational health psychology had a low effect on insomnia (standardized load coefficient was 0.065). However, the Bayesian network model further analysis found that anxiety and stress were the two parent nodes of insomnia, with direct causal relationships, the arc strength was-8.607 and -15.665, respectively. The model prediction results showed that the probability of insomnia occurring was predicted to be 0 in the cases of no stress and anxiety, low stress without anxiety, and no stress with low anxiety. When high stress with low anxiety and low stress with high anxiety occurred, the predicted probability of insomnia occurring were 0.38 and 0.47, respectively. When both high stress and high anxiety occurred simultaneously, the predicted probability of insomnia occurring was 0.51. Conclusion: Bayesian network risk assessment can intuitively reveal and predict the insomnia risk of thermal power generation workers and the network interaction relationship between the risks. Anxiety and stress are the direct causal risks of insomnia, and stress is the main risk of individual insomnia of thermal power generation workers. The occurrence of insomnia can be reduced based on scientific intervention of stress conditions.

Ecological and human health impact assessments based on long-term monitoring of soil PAHs near a coal-fired power plant.

The combustion of coal in power plants releases significant amounts of polycyclic aromatic hydrocarbons (PAHs), which are highly toxic and carcinogenic. This study assesses the ecological and human health impacts of PAHs contamination from a coal-fired power plant over 8 years. The monitoring site selection considered the distance from the power plant and the prevailing wind direction in the investigated area. The results reveal that, during the monitoring period, PAH levels increased on average by 43%, 61%, and 37% in the zone of the prevailing wind direction, in the area proximate to the power plant, and the zone distant from it, respectively. The site, which has a radius of 4.5 km in the prevailing wind direction, exhibited the highest ecological and human health impacts. Additionally, a strong correlation was observed between environmental and human health impacts, depending on the distance from the power plant, particularly in areas with the prevailing wind direction. These insights contribute to a comprehensive understanding of the intricate dynamics linking power plant emissions, PAHs contamination, and their far-reaching consequences on the environment and human health.

Cross-efficiency analysis of energy sector using stochastic DEA: Considering pollutant emissions.

Undesirable outputs can be challenging to avoid in the production of goods and services, often overlooked. Pollution is generally regarded as a negative externality and is taken into account during the production process. The novelty of this study lies in introducing CO2 as an economic "bad" in the energy sector's efficiency measure through a stochastic data envelopment analysis (DEA) cross-efficiency model. Unlike pollution and economic goods, where increased production leads to more pollution, CO2 is weakly disposable, meaning that higher CO2 values lead to a decrease in the number of good outputs produced. The study proposes a new stochastic model based on an extension of the cross-efficiency model and applies it to measure the energy efficiency of 32 thermal power plants in Angola in the presence of undesirable outputs. This will help promote better environmental management. The study's findings offer vital policy insights for the energy sector. The introduction of new stochastic models enables more accurate efficiency measurement under uncertain conditions, aiding policymakers in resource allocation decisions. Additionally, the adoption of stochastic cross-efficiency methods enhances performance assessments, facilitating targeted interventions for underperforming units. These findings contribute to evidence-based policymaking, promoting sustainability and competitiveness within the energy sector.

Detection and validation of common noctule bats (Nyctalus noctula) with a pulse radar and acoustic monitoring in the proximity of an onshore wind turbine.

This paper presents the results of bats detected with marine radar and their validation with acoustic detectors in the vicinity of a wind turbine with a hub height of 120 m. Bat detectors are widely used by researchers, even though the common acoustic detectors can cover only a relatively small volume. In contrast, radar technology can overcome this shortcoming by offering a large detection volume, fully covering the rotor-swept areas of modern wind turbines. Our study focused on the common noctule bats (Nyctalus noctula). The measurement setup consisted of a portable X-band pulse radar with a modified radar antenna, a clutter shielding fence, and an acoustic bat detector installed in the wind turbine's nacelle. The radar's detection range was evaluated using an analytical simulation model. We developed a methodology based on a strict set of criteria for selecting suitable radar data, acoustic data and identified bat tracks. By applying this methodology, the study data was limited to time intervals with an average duration of 48 s, which is equal to approximately 20 radar images. For these time intervals, 323 bat tracks were identified. The most common bat speed was extracted to be between 9 and 10 m/s, matching the values found in the literature. Of the 323 identified bat tracks passed within 80 m of the acoustic detector, 32% had the potential to be associated with bat calls due to their timing, directionality, and distance to the acoustic bat detector. The remaining 68% passed within the studied radar detection volume but out of the detection volume of the acoustic bat detector. A comparison of recorded radar echoes with the expected simulated values indicated that the in-flight radar cross-section of recorded common noctule bats was mostly between 1.0 and 5.0 cm2, which is consistent with the values found in the literature for similar sized wildlife.

Homology and heterogeneity of soil trace elements of coal power production bases in arid and semi-arid areas of Northwest China.

Coal power activities could cause regional fluctuations of trace elements, but the distribution information of these trace elements in arid and semi-arid areas is insufficient. In this study, the soil trace elements (As, B, Be, Cd, Co, Cr, Cu, Fe, Ga, Ge, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Ti, Tl, and Zn) of Ningdong Coal Power Production Base in China were monitored. Results showed that the concentrations of B, Tl, Mn, Pb, Cr, K, Cu, and Co exceeded background values. The maximum risk index reached 265.66, while the trace elements posed a cancer risk to children. Combining correlation analyses (CA), principal component analysis (PCA), and positive matrix factorization (PMF) techniques, it indicated that trace elements were mainly coming from coal combustion (34.15%), livestock farming (17.44%), traffic emissions (12.42%), and natural factors (35.99%). This study reveals the sources and potential ecological risks of soil trace elements in the Ningdong Coal and Power Production Base. It provides a scientific basis for developing targeted environmental management measures and reducing human health risks.

Mathematical modeling and performance evaluation of Ducted Horizontal-axis Helical Wind Turbines: Insights into aerodynamics and efficiency.

With the escalating demand for energy, there is a growing focus on decentralized, small-scale energy infrastructure. The success of new turbines in this context is notable. However, many of these turbines do not follow many of the basic ideas established to evaluate their performance, leaving no precise technique or mathematical model. This research developed a Ducted Horizontal-axis Helical Wind Turbine (DHAHWT). The DHAHWT is a duct-mounted helical savonius turbine with a venturi and diffuser to improve flow. Unlike a vertical axis helical savonius turbine, DHAHWT revolves roughly parallel to the wind, making it a horizontal turbine. This complicates mathematical and theoretical analysis. This study created a DHAHWT mathematical model. COMSOL simulations utilizing Menter's Shear Stress Transport model (SST) across an incoming velocity range of 1m/s to 4m/s were used to evaluate the turbine's interaction with the wind. MATLAB was used to train an artificial neural network (ANN) utilizing COMSOL data to obtain greater velocity data. The Mean Average Percentage Error (MAPE) and Root Mean Square Error (RMSE) of ANN data were found to be 3%, indicating high accuracy. Further, using advanced statistical methods the Pearson's correlation coefficient was calculated resulting in a better understanding of the relationship of between incoming velocity and velocity at different sections of the wind turbine. This study will shed light on the aerodynamics and working of DHAHWT.

Survival of biomass and waste power generation: A global overview.

Biomass and waste power generation holds the promise to secure electricity supply for a growing population and mitigate global warming simultaneously. Along with the increasing commission and installation of biomass/waste power units (BWPUs) across the globe, some BWPUs failures have been observed, including the cancellation of planned/commissioned BWPUs and the termination of those in operation before reaching their natural retirement. While empirical evidence suggests that factors like feedstock accessibility and policy instruments might affect the feasibility and performance of BWPUs, there is a lack of comprehensive investigation about why some BWPUs failed at the global scale. To fill this knowledge gap, this study quantifies the hazard ratio of BWPUs via a parametric survival analysis using a panel dataset covering a total of 12,829 BWPUs (relying on woody, non-woody, and waste biomass as raw feedstocks) located in 164 countries/regions worldwide for the period of 2001-2021. The analytical results suggest that large unit size is conducive to BWPUs failure, while feedstock accessibility and the implementation of policy instruments (including Feed-in-Tariff and carbon pricing) could largely reduce the hazard ratio of BWPUs, with varying impacts on BWPUs at the planned/commissioned stage or the operation stage, located in developed or developing countries. Our findings not only shed additional light on the fate of BWPUs, which is crucial to enriching our understanding about the development of the bioenergy sector worldwide, but also provide salient empirical evidence for policy-making in terms of ensuring feedstock accessibility, overcoming diseconomies of scale, and making fiscal instruments available and transparent to boost the confidence of investors and entrepreneurs in support of BWPUs development.

Gas flaring: technicalities, challenges, and the economic potentials.

Gas flaring has been identified as a major contributor to global warming and climate change. It is used either as a safety measure or as a means of disposal for technical or economic reasons. Over 250 toxins have been directly/indirectly associated with gas flaring and its associated emissions. Most of these toxins have been known to have significant inimical impacts on humans' health, plant biodiversity, and the environment. With the recent rise in global energy insecurity, several EU countries have either returned to coal power generation or extended the lifetime of their coal-fired plants thereby increasing anthropogenic carbon emissions. This increase in carbon emission has necessitated the re-evaluate of gas flare practices vis-à-vis the environmental challenges and the financial potentials. This paper presents a holistic review of gas flaring, its types, composition, systems design, estimation methods, social and environmental challenges, the abatement measures, and the re-utilization strategies. It identified the potential to save a minimum of US$10.4 billion globally if more stringent gas flare abatement measures were pursued. Furthermore, the paper highlights the recent trends in flare gas re-utilization technologies such as the production of bioproducts which has been reported to hold a potential for an annual production of about 148 million bbl of biocrude and 67 million metrics of algae protein from 140 bcm of globally flared gas. Finally, it explored the possible way forward and stringent measures that can be pursued to disincentivize gas flare and also increase investments in gas processing technologies.

Industry star or production elite: evidence from total factor productivity of Chinese electricity sector's green transformation.

China is constantly seeking rapid, high-quality growth in order to meet its carbon peaking and neutrality goals. Approximately 40% of China's carbon emissions come from the electric power industry, which is beset by issues of poor efficiency and excessive emissions. Thus, it is essential to determine if environmental restrictions increase economic benefits total factor productivity while still preserving the environment. We use the Quasi-DID method to examine the impact of carbon emissions trading scheme on firm-level total factor productivity of electric power companies. The findings demonstrate the following: (1) carbon emissions trading scheme considerably impedes total factor productivity development; (2) the primary cause of this detrimental impact is the need for additional improvements in marketization since green innovation is still in its infancy; (3) additional study indicates that law enforcement's heterogeneity is what affects this restriction. Our research may both enhance the Chinese carbon emissions trading scheme's effectiveness assessment framework and point out several potential avenues for high-quality growth.

Water Scarcity Assessment of Hydropower Plants in China under Climate Change, Sectoral Competition, and Energy Expansion.

Hydropower plays a pivotal role in low-carbon electricity generation, yet many projects are situated in regions facing heightened water scarcity risks. This research devised a plant-level Hydropower Water Scarcity Index (HWSI), derived from the ratio of water demand for electricity generation to basin-scale available runoff water. We assessed the water scarcity of 1736 hydropower plants in China for the baseline year 2018 and projected into the future from 2025 to 2060. The results indicate a notable increase in hydropower generation facing moderate to severe water scarcity (HWSI >0.05), rising from 10% in 2018 to 24-34% of the national total (430-630 TWh), with a projected peak in the 2030s-2040s under the most pessimistic scenarios. Hotspots of risk are situated in the southwest and northern regions, primarily driven by decreased river basin runoff and intensified sectoral water use, rather than by hydropower demand expansion. Comparative analysis of four adaptation strategies revealed that sectoral water savings and enhancing power generation efficiency are the most effective, potentially mitigating a high of 16% of hydropower risks in China. This study provides insights for formulating region-specific adaptation strategies and assessing energy-water security in the face of evolving environmental and societal challenges.

Incineration-source fingerprints and emission spectrums of dioxins with diagnostic application.

Despite increasing waste-to-energy (WtE) capacities, there remain deficiencies in comprehension of 136 kinds of tetra- through octa-chlorinated dibenzo-p-dioxin and dibenzofurans (136 PCDD/Fs) originating from incineration sources. Samples from twenty typical WtE plants, encompassing coal-fired power plants (CPP), grate incinerators (GI), fluidized bed incinerators (FBI), and rotary kilns (RK), yielded extensive PCDD/F datasets. Research was conducted on fingerprint mapping, formation pathways, emission profiles, and diagnostic analysis of PCDD/Fs in WtE plants. Fingerprints revealed a prevalence of TCDF, followed by PeCDF, while CPP and RK respectively generated more PCDD and HxCDD. De novo synthesis was the predominant formation pathway except one plant, where CP-route dominated. DD/DF chlorination also facilitated PCDD/F formation, showing general trends of FBI > GI > CPP > RK. The PCDD/F emission intensities emitted in air pollution control system inlet (APCSI) and outlet (APCSO) followed the statistical sequence of RK > FBI > GI > CPP, with the average I-TEQ concentrations in APCSO reaching 0.18, 0.08, 0.11, and 0.04 ng I-TEQ·Nm-3. Emission spectrum were accordingly formed. Four clusters were segmented for diagnosis analysis, where PCDD/Fs in GI and FBI were similar, grouped as a single cluster. PCDD/Fs in CPP and RK demonstrated distinctive features in TCDD, HxCDD, and HxCDF. The WtE plants exceeding the limit value tended to generate and retain fewer TCDD and TCDF yet had higher fractions of HxCDD and HxCDF. The failure of APCS coupled with the intrinsic source strength of PCDD/Fs directly led to exceedance, highlighting safe operational practices. This study motivated source tracing and precise evaluation of 136 PCDD/Fs based on the revealed fingerprint profiles for WtE processes.

Study of the differences in collection scope of raw materials of biomass CHP plants caused by regional factors.

Combined heat and power (CHP) plants fueled by biomass can collect and utilize waste straw resources in a productive way. This paper considers the impact of regional factors on biomass energy potential and the energy needs of the population, so as to study the differences in construction of biomass CHP plants and the collection scope of raw materials, and proposes evaluating suitability for biomass energy development based on scope of resource collection. Taking five counties in China as its study areas, this paper assesses biomass energy potential. A topology system of biomass CHP plants has been reasonably established in different counties through ArcGIS, the required installed capacity has been calculated according to the number of persons served by such plants. Finally, the collection length and corresponding value range of raw materials of CHP plants along roads has been obtained based on biomass energy potential and energy demand. The result shows that the differences in area, straw yield and biomass fuelization rate depending on regions have a great impact on biomass energy potential, while the residue-to-product ratio of straw and biomass calorific value have less of an impact. When the biomass energy per capita of a region reaches 9.75GJ/person, it is suitable for biomass energy development. The installed capacity in the biomass CHP plant system of each study area is mostly within the scope of 3-59 MW, and the collection length of corresponding biomass resources of such plants along roads is mostly within the scope of 5.09-25.23 km.

Estimated greenhouse gas emissions in the Mbalmayo thermal power plant between 2016-2020 using the genetic-Gaussian algorithm coupling.

The greenhouse gas (GHG) emissions inventories in our context result from the production of electricity from fuel oil at the Mbalmayo thermal power plant between 2016 and 2020. Our study area is located in the Central Cameroon region. The empirical method of the second level of industrialisation was applied to estimate GHG emissions and the application of the genetic algorithm-Gaussian (GA-Gaussian) coupling method was used to optimise the estimation of GHG emissions. Our work is of an experimental nature and aims to estimate the quantities of GHG produced by the Mbalmayo thermal power plant during its operation. The search for the best objective function using genetic algorithms is designed to bring us closer to the best concentration, and the Gaussian model is used to estimate the concentration level. The results obtained show that the average monthly emissions in kilograms (kg) of GHGs from the Mbalmayo thermal power plant are: 526 kg for carbon dioxide (CO2), 971.41 kg for methane (CH4) and 309.41 kg for nitrous oxide (N2O), for an average monthly production of 6058.12 kWh of energy. Evaluation of the stack height shows that increasing the stack height helps to reduce local GHG concentrations. According to the Cameroonian standards published in 2021, the limit concentrations of GHGs remain below 30 mg/m3 for CO2 and 200 µg/m3 for N2O, while for CH4 we reach the limit value of 60 µg/m3. These results will enable the authorities to take appropriate measures to reduce GHG concentrations.

Study on the habitat evolution after dam removal in a habitat-alternative tributary of large hydropower station.

The establishment of large hydropower stations in the main stream poses a threat to fish habitats. Selecting suitable tributaries as alternative habitats is a practical measure for ecological environment protection during large hydropower station's construction. The small dams constructed on certain tributaries need to be removed in order to restore river connectivity. The removal of dams will activate hydro-sedimentary dynamics and change the original habitat in terms of topography and hydrodynamics. To explore the evolution of fish habitats following the removal of small dams, a dam-removed reach of a habitat-alternative tributary was selected as the research object, and the model of water-sediment transport and riverbed evolution in strongly disturbed dam-removed reaches and the model of fish habitat suitability evaluation were established. The key parameters calibration and model verification were completed by field monitoring results. The simulation results showed dramatic evolution in the reservoir riverbed in the initial stage after dam removal and during the high discharge period. One year after dam removal, there was a noticeable 4.0 m incision in front of the dam, along with a decrease in channel slope at the dam site from about 4.8% to approximately 1.5%. Downstream of the dam, alterations to the riverbed were mainly concentrated near the dam, and sedimentary bodies with a height of around 2.0 m have formed on the left bank following the high discharge period. The fish habitat in most areas of the dam-removed reach was suitable, except for the downstream high-velocity area. To compare the evolution process of fish habitat under two dam removal periods in wet and dry seasons, two dam removal schemes were implemented in March and June. The results showed that the riverbed evolved more gradually in the March scheme, creating a larger and continuous suitable habitat for fish. Therefore, the March scheme was recommended. By revealing the evolutionary pattern of fish habitat after dam removal, this research provides a reliable model for assessing and restoring habitats in dam-removed reaches, and enjoys significant implications for protecting river ecology in hydropower development reaches.

Optimization of offshore wind farm inspection paths based on K-means-GA.

As global demand for offshore wind energy continues to rise, the imperative to enhance the profitability of wind power projects and reduce their operational costs becomes increasingly urgent. This study proposes an innovative approach to optimize the inspection routes of offshore wind farms, which integrates the K-means clustering algorithm and genetic algorithm (GA). In this paper, the inspection route planning problem is formulated as a multiple traveling salesman problem (mTSP), and the advantages of the K-means clustering algorithm in distance similarity are utilized to effectively group the positions of wind turbines, thereby optimizing the inspection schedule for vessels. Subsequently, by harnessing the powerful optimization capability and robustness of genetic algorithms, further refinement is conducted to search for the optimal inspection routes, aiming to achieve cost reduction objectives. The results of simulation experiments demonstrate the effectiveness of this integrated approach. Compared to traditional genetic algorithms, the inspection route length has been significantly reduced, from 93 kilometers to 79.36 kilometers. Simultaneously, operational costs have also experienced a notable decrease, dropping from 141,500 Chinese Yuan to 125,600 Chinese Yuan.

Prediction analysis of carbon emission in China's electricity industry based on the dual carbon background.

The electric power sector is the primary contributor to carbon emissions in China. Considering the context of dual carbon goals, this paper examines carbon emissions within China's electricity sector. The research utilizes the LMDI approach for methodological rigor. The results show that the cumulative contribution of economies scale, power consumption factors and energy structure are 114.91%, 85.17% and 0.94%, which contribute to the increase of carbon emissions, the cumulative contribution of power generation efficiency and ratio of power dissipation to generation factor are -19.15% and -0.01%, which promotes the carbon reduction. The decomposition analysis highlights the significant influence of economic scale on carbon emissions in the electricity industry, among the seven factors investigated. Meanwhile, STIRPAT model, Logistic model and GM(1,1) model are used to predict carbon emissions, the average relative error between actual carbon emissions and the predicted values are 0.23%, 8.72% and 7.05%, which indicates that STIRPAT model is more suitable for medium- to long-term predictions. Based on these findings, the paper proposes practical suggestions to reduce carbon emissions and achieve the dual carbon goals of the power industry.

Research of biomimetic corrugation on the blade flutter suppression in large-scale wind turbine systems.

Aiming at the blade flutter of large horizontal-axis wind turbines, a method by utilizing biomimetic corrugation to suppress blade flutter is first proposed. By extracting the dragonfly wing corrugation, the biomimetic corrugation airfoil is constructed, finding that mapping corrugation to the airfoil pressure side has better aerodynamic performance. The influence of corrugation type, amplitudeλ, and intensity on airfoil flutter is analyzed using orthogonal experiment, which determines that theλhas the greatest influence on airfoil flutter. Based on the fluctuation range of the moment coefficient ΔCm, the optimal airfoil flutter suppression effect is obtained when the type is III,λ= 0.6, and intensity is denser (n= 13). The effective corrugation layout area in the chord direction is determined to be the leading edge, and the ΔCmof corrugation airfoil is reduced by 7.405%, compared to the original airfoil. The application of this corrugation to NREL 15 MW wind turbine 3D blades is studied, and the influence of corrugation layout length in the blade span direction on the suppressive effect is analyzed by fluid-structure interaction. It is found that when the layout length is 0.85 R, the safety marginSfreaches a maximum value of 0.3431 Hz, which is increased 2.940%. The results show that the biomimetic corrugated structure proposed in this paper can not only improve the aerodynamic performance by changing the local flow field on the surface of the blade, but also increase the structural stiffness of the blade itself, and achieve the effect of flutter suppression.

Environmental reporting in Italian thermal power plants: insights from a comprehensive analysis of EMAS environmental statements.

The global energy sector heavily relies on fossil fuels, significantly contributing to climate change. The ambitious European emissions' reduction targets require sustainable processes and alternatives. This study presents a comprehensive analysis of 73 Italian thermal power plants registered to the European Eco-Management and Audit Scheme (EMAS) aimed at assessing EMAS effectiveness in addressing and quantifying the environmental impacts of this relevant industrial sector. The analysis was based on EMAS environmental statements, publicly disclosing verified and certified data, with the secondary objective of evaluating if EMAS could be an efficient tool to improve the plants' environmental performances. An inventory of technical and environmental aspects, adopted indicators, and allocated budgets was based on 2023 data. A strong correlation was found between the significance of the environmental aspects and the number of adopted indicators. Gaps were observed in describing aspects like "biodiversity" and "local issues". Improvement objectives and budget allocation showed discrepancies and lacked correlation with the significance of the related environmental aspects. "Energy production" accounted for 68% of the total allocated budget; "environmental risks", "emissions to air", "electricity consumption", and "local issues" were also key focus areas. Insufficient information on emission control technologies and progress tracking of improvement objectives was detected. This study highlights the need for thermal power installations to improve the selection of appropriate indicators and to better relate allocated budget to improvement objectives when implementing EMAS. Such measures would facilitate the quantification of the effective environmental impacts of the energy production sector, supporting future research on this topic, allowing stakeholders a better comparison among plants, and driving industry-wide improvements.

Air Quality and Health Implications of Coal Power Retirements Attributed to Industrial Electricity Savings in China.

The coal-dominated electricity system, alongside increasing industrial electricity demand, places China into a dilemma between industrialization and environmental impacts. A practical solution is to exploit air quality and health cobenefits of industrial energy efficiency measures, which has not yet been integrated into China's energy transition strategy. This research examines the pivotal role of industrial electricity savings in accelerating coal plant retirements and assesses the nexus of energy-pollution-health by modeling nationwide coal-fired plants at individual unit level. It shows that minimizing electricity needs by implementing more efficient technologies leads to the phaseout of 1279 hyper-polluting units (subcritical, <300 MW) by 2040, advancing the retirement of these units by an average of 7 years (3-16 years). The retirements at different locations yield varying levels of air quality improvements (9-17%), across six power grids. Reduced exposure to PM2.5 could avoid 123,100 pollution-related cumulative deaths over the next 20 years from 2020, of which ∼75% occur in the Central, East, and North grids, particularly coal-intensive and populous provinces (e.g., Shandong and Jiangsu). These findings provide key indicators to support geographically specific policymaking and lay out a rationale for decision-makers to incorporate multiple benefits into early coal phaseout strategies to avoid lock-in risk.

Biomass Ppower generation: A pathway to carbon neutrality.

In light of the pressing need to reduce carbon emissions, the biomass power generation industry has gained significant attention and has increasingly become a crucial focus in China. However, there are still considerable gaps in the historical background, status, and prospects of biomass power generation. Herein, the historical and current status of biomass power generation in China are systematically reviewed, with a particular emphasis on supportive policies, environmental impacts, and future projections. By 2022, the newly installed capacity for biomass power generation reached 3.34 MW with a total installed capacity of 41 MW. The power produced from biomass power generation is 182.4 billion kWh in China. The total installed capacity and generated power in 2022 were 1652 and 1139 folds higher than in 2006 when the first biomass generation plant was established. However, disparities in the distribution of biomass resources and power generation were observed. Key drivers of the industry development include tax, finance, and subsidy policies. Under the implementation of the 14th Five-Year Plan for renewable energy development and the goal of carbon neutrality, biomass power generation may achieve great success through more targeted policy support and advanced technologies that reduce air pollutant emissions. If combined with Bioenergy with Carbon Capture and Storage (BECCS) technology, biomass power generation will make its contribution to carbon neutrality in China.