More than one million barriers fragment Europe's rivers.

Rivers support some of Earth's richest biodiversity1 and provide essential ecosystem services to society2, but they are often fragmented by barriers to free flow3. In Europe, attempts to quantify river connectivity have been hampered by the absence of a harmonized barrier database. Here we show that there are at least 1.2 million instream barriers in 36 European countries (with a mean density of 0.74 barriers per kilometre), 68 per cent of which are structures less than two metres in height that are often overlooked. Standardized walkover surveys along 2,715 kilometres of stream length for 147 rivers indicate that existing records underestimate barrier numbers by about 61 per cent. The highest barrier densities occur in the heavily modified rivers of central Europe and the lowest barrier densities occur in the most remote, sparsely populated alpine areas. Across Europe, the main predictors of barrier density are agricultural pressure, density of river-road crossings, extent of surface water and elevation. Relatively unfragmented rivers are still found in the Balkans, the Baltic states and parts of Scandinavia and southern Europe, but these require urgent protection from proposed dam developments. Our findings could inform the implementation of the EU Biodiversity Strategy, which aims to reconnect 25,000 kilometres of Europe's rivers by 2030, but achieving this will require a paradigm shift in river restoration that recognizes the widespread impacts caused by small barriers.

Global-scale human impact on delta morphology has led to net land area gain.

River deltas rank among the most economically and ecologically valuable environments on Earth. Even in the absence of sea-level rise, deltas are increasingly vulnerable to coastal hazards as declining sediment supply and climate change alter their sediment budget, affecting delta morphology and possibly leading to erosion1-3. However, the relationship between deltaic sediment budgets, oceanographic forces of waves and tides, and delta morphology has remained poorly quantified. Here we show how the morphology of about 11,000 coastal deltas worldwide, ranging from small bayhead deltas to mega-deltas, has been affected by river damming and deforestation. We introduce a model that shows that present-day delta morphology varies across a continuum between wave (about 80 per cent), tide (around 10 per cent) and river (about 10 per cent) dominance, but that most large deltas are tide- and river-dominated. Over the past 30 years, despite sea-level rise, deltas globally have experienced a net land gain of 54 ± 12 square kilometres per year (2 standard deviations), with the largest 1 per cent of deltas being responsible for 30 per cent of all net land area gains. Humans are a considerable driver of these net land gains-25 per cent of delta growth can be attributed to deforestation-induced increases in fluvial sediment supply. Yet for nearly 1,000 deltas, river damming4 has resulted in a severe (more than 50 per cent) reduction in anthropogenic sediment flux, forcing a collective loss of 12 ± 3.5 square kilometres per year (2 standard deviations) of deltaic land. Not all deltas lose land in response to river damming: deltas transitioning towards tide dominance are currently gaining land, probably through channel infilling. With expected accelerated sea-level rise5, however, recent land gains are unlikely to be sustained throughout the twenty-first century. Understanding the redistribution of sediments by waves and tides will be critical for successfully predicting human-driven change to deltas, both locally and globally.

Microalgae are not an umbrella solution for power industry waste abatement but could play a role in their valorization.

Microalgae have long been regarded as a promising solution for biological carbon abatement from the power industry, offering renewable biomass without competing for land or water resources used for food crops. In this study, we extensively examined the application of photosynthetic microorganisms for closing carbon, nitrogen, and micronutrient loops in the power industry. Subsequently, we explored the bottom-up integration of algal biorefineries into power industry waste streams for increased economic benefits and reduced environmental impacts. Analysis of the available data indicated that microalgae integration with the power industry is primarily performed using flue-gas-assisted cultivation. This approach allows for carbon sequestration typically below one gram per liter per day, too low to significantly impact carbon abatement at achievable scales of microalgae cultivation. Alternative approaches are also being explored. For example, soluble bicarbonate platforms allow for higher biomass productivity and temporary carbon storage. Meanwhile, the use of ashes and waste heat and thermophilic strains can result in lower cultivation costs and better control of cultivation conditions. These approaches offer further incremental improvement to microalgae-based carbon abatement systems in the power industry but are unlikely to be an umbrella solution for carbon reduction. Consequently, in the near term, microalgae-based carbon valorization systems are likely to be limited to niche applications involving the synthesis of high-value products. For microalgae to truly transform carbon abatement processes radical improvements in both biology and engineering approaches are urgently needed.

Virtual Water Embodied in Interregional Energy Trade in China: A City-Level Analysis.

Large volumes of water are used in energy production for both primary (e.g., fuel extraction) and secondary energy (e.g., electricity). In countries such as China, with a large internal trade in fuels and long-distance transmission grids, this can result in considerable water inequalities. Previous research focused on the water impacts of energy production at the national and provincial levels, which is too coarse to identify the spatial differences and make specific case studies. Here, we take the next step toward a spatially explicit economically integrated water-use for energy assessment by combining a bottom-up assessment approach with a city-level multiregional input-output model. Specifically, we examine the water consumption of energy production in China, distinguishing between water for primary and secondary energy at the level of coal mines, oil and gas fields, and power plants for the first time. Of the total energy-related freshwater consumption of 4.9 Gm3 in 2017, primary energy accounted for 19% (940 Mm3) and secondary energy accounted for 81% (3955 Mm3). Coal was the largest water consumer for both primary and secondary energy (540 and 3880 Mm3, respectively), with both oil (361, and 0.5 Mm3, respectively) and gas (7 and 69 Mm3, respectively) also consuming large amounts. Intercity virtual water, that is, water embodied in energy trade across cities, reached 54% (2.6 Gm3) of energy-related freshwater consumption. Across China, 32% of cities see a bilateral trade in secondary- and primary-energy-related virtual water (e.g., Daqing city exports virtual water embodied in primary fuel to other cities that is then used to produce electricity in those cities, part of which is used back in Daqing via transmission). For these 32% of cities, 73% export more virtual water than import and 27% import more virtual water than export. This study reveals significant differences in city-level virtual water patterns (e.g., scale and direction) between primary and secondary energy to provide information for cities about their virtual water inflow and outflow and the potential collaboration partners for water management.

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.

Designing Retirement Strategies for Coal-Fired Power Plants To Mitigate Air Pollution and Health Impacts.

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system operations and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO2 emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and Rest of PJM, leading to scenario-varying changes in the plant-level release of air pollutants. Considering pollution transport and the size of the exposed population, these emissions changes, in turn, give rise to a reduction of 6-136 PM2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Among our designed scenarios, those that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, comparing across the six scenarios evaluated in this study, vulnerable populations─in both PA and Rest of PJM─benefit most in scenarios that prioritize plant closures near Environmental Justice Areas in PA. These results demonstrate the importance of considering cross-regional linkages and sociodemographics in designing equitable retirement strategies.

Subsidizing Grid-Based Electrolytic Hydrogen Will Increase Greenhouse Gas Emissions in Coal Dominated Power Systems.

Clean hydrogen has the potential to serve as an energy carrier and feedstock in decarbonizing energy systems, especially in "hard-to-abate" sectors. Although many countries have implemented policies to promote electrolytic hydrogen development, the impact of these measures on costs of production and greenhouse gas emissions remains unclear. Our study conducts an integrated analysis of provincial levelized costs and life cycle greenhouse gas emissions for all hydrogen production types in China. We find that subsidies are critical to accelerate low carbon electrolytic hydrogen development. Subsidies on renewable-based hydrogen provide cost-effective carbon dioxide equivalent (CO2e) emission reductions. However, subsidies on grid-based hydrogen increase CO2e emissions even compared with coal-based hydrogen because grid electricity in China still relies heavily on coal power and likely will beyond 2030. In fact, CO2e emissions from grid-based hydrogen may increase further if China continues to approve new coal power plants. The levelized costs of renewable energy-based electrolytic hydrogen vary among provinces. Transporting renewable-based hydrogen through pipelines from low- to high-cost production regions reduces the national average levelized cost of renewables-based hydrogen but may increase the risk of hydrogen leakage and the resulting indirect warming effects. Our findings emphasize that policy and economic support for nonfossil electrolytic hydrogen is critical to avoid an increase in CO2e emissions as hydrogen use rises during a clean energy transition.

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.

Considering Embodied Greenhouse Emissions of Nuclear and Renewable Power Plants for Electrolytic Hydrogen and Its Use for Synthetic Ammonia, Methanol, Fischer-Tropsch Fuel Production.

Recent concerns surrounding climate change and the contribution of fossil fuels to greenhouse gas (GHG) emissions have sparked interest and advancements in renewable energy sources including wind, solar, and hydroelectricity. These energy sources, often referred to as "clean energy", generate no operational onsite GHG emissions. They also offer the potential for clean hydrogen production through water electrolysis, presenting a viable solution to create an environmentally friendly alternative energy carrier with the potential to decarbonize industrial processes reliant on hydrogen. To conduct a full life cycle analysis, it is crucial to account for the embodied emissions associated with renewable and nuclear power generation plants as they can significantly impact the GHG emissions linked to hydrogen production and its derived products. In this work, we conducted a comprehensive analysis of the embodied emissions associated with solar photovoltaic (PV), wind, hydro, and nuclear electricity. We investigated the implications of including plant-embodied emissions in the overall emission estimates of electrolysis hydrogen production and subsequently on the production of synthetic ammonia, methanol, and Fischer-Tropsch (FT) fuels. Results show that average embodied GHG emissions of solar PV, wind, hydro, and nuclear electricity generation in the United States (U.S.) were estimated to be 37, 9.8, 7.2, and 0.3 g CO2 e/kWh, respectively. Life cycle GHG emissions of electrolytic hydrogen produced from solar PV, wind, and hydroelectricity were estimated as 2.1, 0.6, and 0.4 kg of CO2 e/kg of H2, respectively, in contrast to the zero-emissions often used when the embodied emissions in their construction were excluded. Average life cycle emission estimates (CO2 e/kg) of synthetic ammonia, methanol, and FT-fuel from solar PV electricity are increased by 5.5, 16, and 49 times, respectively, compared to the case when embodied emissions are excluded. This change also depends on the local irradiance for solar power, which can result in a further increase of GHG emissions by 35-41% in areas of low irradiance or reduce GHG emissions by 21-25% in areas with higher irradiance.

Cleaning up while Changing Gears: The Role of Battery Design, Fossil Fuel Power Plants, and Vehicle Policy for Reducing Emissions in the Transition to Electric Vehicles.

Plug-in electric vehicles (PEVs) can reduce air emissions when charged with clean power, but prior work estimated that in 2010, PEVs produced 2 to 3 times the consequential air emission externalities of gasoline vehicles in PJM (the largest US regional transmission operator, serving 65 million people) due largely to increased generation from coal-fired power plants to charge the vehicles. We investigate how this situation has changed since 2010, where we are now, and what the largest levers are for reducing PEV consequential life cycle emission externalities in the near future. We estimate that PEV emission externalities have dropped by 17% to 18% in PJM as natural gas replaced coal, but they will remain comparable to gasoline vehicle externalities in base case trajectories through at least 2035. Increased wind and solar power capacity is critical to achieving deep decarbonization in the long run, but through 2035 we estimate that it will primarily shift which fossil generators operate on the margin at times when PEVs charge and can even increase consequential PEV charging emissions in the near term. We find that the largest levers for reducing PEV emissions over the next decade are (1) shifting away from nickel-based batteries to lithium iron phosphate, (2) reducing emissions from fossil generators, and (3) revising vehicle fleet emission standards. While our numerical estimates are regionally specific, key findings apply to most power systems today, in which renewable generators typically produce as much output as possible, regardless of the load, while dispatchable fossil fuel generators respond to the changes in load.

Multimedia Mercury Recovery from Coal-Fired Power Plants Utilizing N-Containing Conjugated Polymer Functionalized Fly Ash.

To recover multimedia mercury from coal-fired power plants, a novel N-containing conjugated polymer (polyaniline and polypyrrole) functionalized fly ash was prepared, which could continuously adsorb 99.2% of gaseous Hg0 at a high space velocity of 368,500 h-1 and nearly 100% of aqueous Hg2+ in the solution pH range of 2-12. The adsorption capacities of Hg0 and Hg2+ reach 1.62 and 101.36 mg/g, respectively. Such a kind of adsorbent has good environmental applicability, i.e. good resistance to coexisting O2/NO/SO2 and coexisting Na+/K+/Ca2+/Mg2+/SO42-. This adsorbent has very low specific resistances (6 × 106-5 × 109 Ω·cm) and thus can be easily collected by an electrostatic precipitator under low-voltage (0.1-0.8 kV). The Hg-saturated adsorbent can desorb almost 100% Hg under relatively low temperature (<250 °C). Characterization and theoretical calculations reveal that conjugated-N is the critical site for adsorbing both Hg0 and Hg2+ as well as activating chlorine. Gaseous Hg0 is oxidized and adsorbed in the form of HgXClX(ad), while aqueous Hg2+ is adsorbed to form a complex with conjugated-N, and parts of Hg2+ are reduced to Hg+ by conjugated-N. This adsorbent can be easily large-scale manufactured; thus, this novel solid waste functionalization method is promising to be applied in coal-fired power plants and other Hg-involving industrial scenes.

Risk factors for SARS-CoV-2 infection at a UK electricity-generating company: a test-negative design case-control study.

OBJECTIVES: Identify workplace risk factors for SARS-CoV-2 infection, using data collected by a UK electricity-generating company. METHODS: Using a test-negative design case-control study, we estimated the OR of infection by job category, site, test reason, sex, vaccination status, vulnerability, site outage and site COVID-19 weekly risk rating, adjusting for age, test date and test type. RESULTS: From an original 80 077 COVID-19 tests, there were 70 646 included in the final analysis. Most exclusions were due to being visitor tests (5030) or tests after an individual first tested positive (2968).Women were less likely to test positive than men (OR=0.71; 95% CI 0.58 to 0.86). Test reason was strongly associated with positivity and although not a cause of infection itself, due to differing test regimes by area, it was a strong confounder for other variables. Compared with routine tests, tests due to symptoms were highest risk (94.99; 78.29 to 115.24), followed by close contact (16.73; 13.80 to 20.29) and broader-defined work contact 2.66 (1.99 to 3.56). After adjustment, we found little difference in risk by job category, but some differences by site with three sites showing substantially lower risks, and one site showing higher risks in the final model. CONCLUSIONS: In general, infection risk was not associated with job category. Vulnerable individuals were at slightly lower risk, tests during outages were higher risk, vaccination showed no evidence of an effect on testing positive, and site COVID-19 risk rating did not show an ordered trend in positivity rates.

Solar photovoltaic panel production in Mexico: A novel machine learning approach.

This study examines the potential for widespread solar photovoltaic panel production in Mexico and emphasizes the country's unique qualities that position it as a strong manufacturing candidate in this field. An advanced model based on artificial neural networks has been developed to predict solar photovoltaic panel plant metrics. This model integrates a state-of-the-art non-linear programming framework using Pyomo as well as an innovative optimization and machine learning toolkit library. This approach creates surrogate models for individual photovoltaic plants including production timelines. While this research, conducted through extensive simulations and meticulous computations, unveiled that Latin America has been significantly underrepresented in the production of silicon, wafers, cells, and modules within the global market; it also demonstrates the substantial potential of scaling up photovoltaic panel production in Mexico, leading to significant economic, social, and environmental benefits. By hyperparameter optimization, an outstanding and competitive artificial neural network model has been developed with a coefficient of determination values above 0.99 for all output variables. It has been found that water and energy consumption during PV panel production is remarkable. However, water consumption (33.16 × 10-4 m3/kWh) and the emissions generated (1.12 × 10-6 TonCO2/kWh) during energy production are significantly lower than those of conventional power plants. Notably, the results highlight a positive economic trend, with module production plants generating the highest profits (35.7%) among all production stages, while polycrystalline silicon production plants yield comparatively lower earnings (13.0%). Furthermore, this study underscores a critical factor in the photovoltaic panel production process which is that cell production plants contribute the most to energy consumption (39.7%) due to their intricate multi-stage processes. The blending of Machine Learning and optimization models heralds a new era in resource allocation for a more sustainable renewable energy sector, offering a brighter, greener future.

Review on magnetic adsorbents for removal of elemental mercury from coal combustion flue gas.

Under the influence of human activities, atmospheric mercury (Hg) concentrations have increased by 450% compared with natural levels. In the context of the Minamata Convention on Mercury, which came into effect in August 2017, it is imperative to strengthen Hg emission controls. Existing Air Pollution Control Devices (APCDs) combined with collaborative control technology can effectively remove Hg2+ and Hgp; however, Hg0 removal is substandard. Compared with the catalytic oxidation method, Hg0 removal through adsorbent injection carries the risk of secondary release and is uneconomical. Magnetic adsorbents exhibit excellent recycling and Hg0 recovery performance and have recently attracted the attention of researchers. This review summarizes the existing magnetic materials for Hg0 adsorption and discusses the removal performances and mechanisms of iron, carbon, mineral-based, and magnetosphere materials. The effects of temperature and different flue gas components, including O2, NO, SO2, H2O, and HCl, on the adsorption performance of Hg0 are also summarized. Finally, different regeneration methods are discussed in detail. Although the research and development of magnetic adsorbents has progressed, significant challenges remain regarding their application. This review provides theoretical guidance for the improvement of existing and development of new magnetic adsorbents.

The mortality impacts of current and planned coal-fired power plants in India.

We examine the health implications of electricity generation from the 2018 stock of coal-fired power plants in India, as well as the health impacts of the expansion in coal-fired generation capacity expected to occur by 2030. We estimate emissions of SO2, NOX, and particulate matter 2.5 µm (PM2.5) for each plant and use a chemical transport model to estimate the impact of power plant emissions on ambient PM2.5 Concentration-response functions from the 2019 Global Burden of Disease (GBD) are used to project the impacts of changes in PM2.5 on mortality. Current plus planned plants will contribute, on average, 13% of ambient PM2.5 in India. This reflects large absolute contributions to PM2.5 in central India and parts of the Indo-Gangetic plain (up to 20 µg/m3). In the south of India, coal-fired power plants account for 20-25% of ambient PM2.5 We estimate 112,000 deaths are attributable annually to current plus planned coal-fired power plants. Not building planned plants would avoid at least 844,000 premature deaths over the life of these plants. Imposing a tax on electricity that reflects these local health benefits would incentivize the adoption of renewable energy.

Ecological risk assessment of heavy metals in desulfurized seawater discharged from a coal-fired power plant in Qingdao.

Despite the prevalence of discharge of large volumes of heavy-metal-bearing seawater from coal-fired power plants into adjacent seas, studies on the associated ecological risks remain limited. This study continuously monitored concentrations of seven heavy metals (i.e. As, Cd, Cr, Cu, Hg, Pb, and Zn) in surface seawater near the outfall of a coal-fired power plant in Qingdao, China over three years. The results showed average concentrations of As, Cd, Cr, Cu, Hg, Pb, and Zn of 2.63, 0.33, 2.97, 4.63, 0.008, 0.85, and 25.00 µg/L, respectively. Given the lack of data on metal toxicity to local species, this study investigated species composition and biomass near discharge outfalls and constructed species sensitivity distribution (SSD) curves with biological flora characteristics. Hazardous concentrations for 5% of species (HC5) for As, Cd, Cr, Cu, Hg, Pb, and Zn derived from SSDs constructed from chronic toxicity data for native species were 3.23, 2.22, 0.06, 2.83, 0.66, 4.70, and 11.07 µg/L, respectively. This study further assessed ecological risk of heavy metals by applying the Hazard Quotient (HQ) and Joint Probability Curve (JPC) based on long-term heavy metal exposure data and chronic toxicity data for local species. The results revealed acceptable levels of ecological risk for As, Cd, Hg, and Pb, but unacceptable levels for Cr, Cu, and Zn. The order of studied heavy metals in terms of ecological risk was Cr > Cu ≈ Zn > As > Cd ≈ Pb > Hg. The results of this study can guide the assessment of ecological risk at heavy metal contaminated sites characterized by relatively low heavy metal concentrations and high discharge volumes, such as receiving waters of coal-fired power plant effluents.

Cancer Incidence Among Residents Near Coal-Fired Power Plants Based on the Korean National Health Insurance System Data.

BACKGROUND: Cancer is a leading cause of death worldwide, posing a significant threat to human health and life expectancy. Numerous existing studies explored the correlation between coal-fired power plants and cancer development. Currently, Chungcheongnam-do Province hosts 29 coal-fired power plants, constituting half of the total 58 plants across South Korea. METHODS: This study assessed the cancer incidence by proximity to coal-fired power plants in Chungcheongnam-do Province, Korea. In this study, the exposed group comprised individuals residing within a 2-km radius of the coal-fired power plants, whereas the control group comprised individuals who had no prior residency within the 2-km radius of such plants or elsewhere in the province. Standardized incidence ratios were calculated using the cancer incidence cases retrieved from the National Health Insurance System data from 2007 to 2017. RESULTS: The study found that exposed men had a 1.11 (95% confidence interval [CI], 1.09-1.21) times higher risk of developing all cancer types and a 1.15 (95% CI, 1.09-1.22) times higher risk of developing cancers excluding thyroid cancer compared with control men. Exposed women had a 1.05 (95% CI, 1.00-1.14) times higher risk of developing all cancer types and a 1.06 (95% CI, 0.98-1.13) times higher risk of developing cancers excluding thyroid cancer than did control women. The colorectal, liver, prostate, and bladder cancer incidence rates were significantly higher in exposed men than that in all control groups. The incidence of esophageal, stomach, liver, and lung cancers were significantly higher in exposed women compared with all control groups. CONCLUSION: The residents near coal-fired power plants had a higher risk of developing cancer than did those living in other areas. In the future, long-term follow-up investigations in residents living in the vicinity of power plants are warranted.

Short-Term Wind Power Interval Forecasting Based on Hybrid Modal Decomposition and Improved Optimization.

Accurate wind power prediction can effectively alleviate the pressure of the power system peak frequency regulation, and is more conducive to the economic dispatch of the power system. To enhance wind power forecasting accuracy, a hybrid approach for wind power interval prediction is proposes in this study. Firstly, an Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) is applied to decompose the initial wind power sequence into multiple modes, and Variational Mode Decomposition is used to further decompose the high-frequency non-stationary components. Next, Fuzzy Entropy (FE) is utilized to assess the complexity of the post-decomposed Intrinsic Mode Functions (IMFs), and different forecasting methods are employed accordingly, the point predictions were obtained by linearly summing the component predictions.Additionally, an improved sparrow search algorithm (ISSA) is used to seek the optimal hyperparameters of the prediction algorithm. Finally, the prediction intervals are constructed using the point prediction results based on kernel density estimation (KDE). The root mean square errors (RMSE) of deterministic predictions are 2.8458 MW and 1.8605 MW, with uncertainty coverage rates of 95.83% and 97.92% at a 95% confidence level.

Assessment of phytodiversity and phytoremediation potential of plants in the vicinity of a thermal power plant.

A study was carried out to evaluate phytodiversity along with the metal accumulation potential of native plants growing in the vicinity of a thermal power plant (TPP). We documented 26 tree species, six shrubs, and 35 herbs. Importance value index (IVI), which measures the extent to which a species dominates in an area, was found highest for Senna siamea (95.7) followed by Tectona grandis (56.5), and Pithecellobium dulce (19.6). Soil was acidic (pH 5.4) in nature with higher concentrations of Al and Fe. The pH of ground water was found acidic while pH of nearby river was found slightly alkaline. Values of PM2.5 and PM10 were slightly higher than NAAQS standards for industrial areas. The concentration of metals was found higher in aquatic plants than in terrestrial plants. In general, herbs and shrubs showed more metal accumulation potential than trees. Our results suggest that Senna siamea could be used for revegetation purposes in FA landfills. Further, terrestrial and aquatic plants such as Ageratina adenophora and Stuckenia pectinata could be used for reclamation of Mn, Zn, Al, and Fe from contaminated soils. Hydrilla verticillata (Ni and Mn), Nelumbo nucifera, and Ipomoea aquatica (Cr) can be used for metal removal from contaminated water.

The study focuses on the assessment of phytodiversity, soil and water analysis, ambient air quality, and bioaccumulation of heavy metals in plants growing in and around a thermal power plant. The study assumes significance as more than 65% of India's electricity generation is still by coal-fired power plants, having major implications for air, soil, and water pollution. By selecting native plant species adapted to the region, we can enhance biodiversity, restore habitats, and contribute to the overall ecological health of the area surrounding the power plant.

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.