Biomass Energy Research Articles

Assessment of Bioenergy Potential in Vindhya Plateau, Madhya Pradesh

Evaluating agricultural residue availability is crucial for assessing sustainable biomass energy production. Crop waste, a byproduct of agricultural production, can be used for soil amendment, animal feed, and energy generation. A survey in seven districts of central India (Bhopal, Damoh, Guna, Raisen, Sagar, Sehore, and Vidisha) was conducted to assess the availability of agricultural residue in the Vindhya Plateau, which comprises about 16% of Madhya Pradesh's geographical area. Agricultural residue availability was determined by selecting a crop, gathering data on yield and generated biomass (including surplus), and estimating the bioenergy potential. The cultivable areas in the selected districts have bioenergy potentials of 19.91, 15.19, 7.88, 21.89, 13.71, 15.09, and 17.21 kJ ha-1 for crops like soybean, rice, wheat, gram, and maize, respectively. The total residue potential, surplus residue potential, and bioenergy potential of the Vindhya Plateau were assessed as 6.08 MT, 2.42 MT, and 40 GJ, respectively. Vindhya Plateau's Raisen district offers the highest biomass potential, making it ideal for bioenergy development and fuel production from biomass.

Exploring the Design of Financial Instruments and Tax Incentives to Upscale Renewable Energy Generation in South Africa

South Africa is at the precipice of an existential energy crisis. Notably, the country’s endowment comprises vast stores of biomass, wind and solar energy potential that provide the country with a comparative advantage. Transiting from coal to renewable energy sources can stimulate the green economy and mitigate the country’s power shortages. Moreover, by advocating for the decarbonization of the energy sector, a significant contributor to greenhouse gas emissions, this research underscores the potential for advancing South Africa’s decarbonization objectives. This paper explores the design of financial instruments and tax incentives to promote the upscale of renewable energy development in South Africa. A qualitative appraisal is conducted on South Africa’s incentive regime. The study contributes to the scholarship on policy design to stimulate renewable energy generation.

Altered Lignin Accumulation in Sorghum Mutated in Silicon Uptake Transporter SbLsi1.

Sorghum [Sorghum bicolor (L.) Moench] has been receiving attention as a feedstock for lignocellulose biomass energy. During the combustion process, the ash containing silicon (Si) can be produced, which causes problems in furnace maintenance. Hence, lowering Si content in the plants is crucial. Nevertheless, limiting Si supply to crops is difficult in practice because Si is abundant in soil. Previously, a Si uptake transporter (SbLsi1) has been identified, and the Si-depleted mutant has also been generated in the model sorghum variety BTx623. In this study, we aim to investigate the change induced by the mutation of SbLsi1 on the accumulation and the structure of lignin in cell walls. Through chemical and NMR analyses, we demonstrated that the lsi1 mutation resulted in a significant increase in lignin accumulation levels as well as a significant reduction in Si content. At least some of the modification was induced by transcriptional changes, as suggested by the upregulation of phenylpropanoid biosynthesis-related genes in the mutant plants. These findings derived from the model variety would be useful for the future development of practical cultivars with high biomass and less Si content for bioenergy applications.

Sustainable commercially-scaled greenhouse building cooling solution: Integrating PCM storage, desiccant wheels, and absorption chillers powered by dual-source solar/biomass energy

This research aims to address the critical need for sustainable cooling systems in greenhouses, particularly relevant in mitigating global warming impacts and enhancing food security worldwide. The urgency becomes more pronounced in locations experiencing high ambient temperature and humidity. The study introduces an innovative cooling system integrating Phase Change Material, a desiccant wheel, and an absorption chiller, powered by solar and biomass energy. This novel system aims to efficiently regulate temperature and humidity in greenhouse environments. The performance of this system is examined in Abu Dhabi, Doha, and Riyadh during the summer months, utilizing TRNSYS software for a medium-scale greenhouse model. Additionally, a comprehensive Life Cycle Assessment is carried out to quantify the environmental impacts of the proposed system. Results indicate that in Abu Dhabi, the system yields a Coefficient of Performance (COP) of 1.108, effectively maintaining indoor climate conditions. Similarly, Doha and Riyadh exhibit COPs of 1.015 and 0.827, respectively. In terms of solar energy utilization, Abu Dhabi demonstrates a solar fraction of 40.4, corresponding to the lowest Global Warming Potential (GWP) at 0.106 kg CO2eq per 1 kW of provided cooling capacity. Conversely, Riyadh records the highest GWP at 0.149 kg CO2eq, followed by Doha at 0.118 kg CO2eq. The Energy Payback Time (EPBT) for the system in Abu Dhabi is calculated to be 3.96 years, the shortest among the examined cities. In comparison, Doha and Riyadh present longer EPBTs of 4.48 and 5.83 years, respectively. These findings suggest that the proposed system offers a viable and environmentally friendly alternative to conventional greenhouse cooling approaches.

Adsorption and C-C bond cleavage of benzene on hematite α-Fe2O3 surfaces: a DFT mechanistic study.

Reforming tar molecules into smaller gaseous molecules has been a critical challenge for biomass energy utilization. Hematite (α-Fe2O3) has been demonstrated as an effective catalyst for the catalytic reforming of tar, nevertheless, the detailed mechanism of α-Fe2O3 catalyzed tar reforming remains unclear. In this work, we apply the density functional theory method to investigate this problem. Specifically, we study both (0001) and (01[Formula: see text]2) surface structures of α-Fe2O3 and then use the structures to investigate the adsorption and C-C bond cleavage of benzene on these surfaces. Our results show that the dominant interactions between benzene and a single Fe-terminated (0001) surface are van der Waals forces, yet benzene could be chemisorbed on the Fe and O co-exposed (01[Formula: see text]2) surface via strong C-O interactions. As a result, the (0001) surface is not active towards benzene cleavage, whereas the (01[Formula: see text]2) surface can promote the aromatic C-C bond breaking. Furthermore, our calculations indicate that chain-like alkene species and carbonyl species are the two types of potential products that form after the C-C bond cleavage of benzene on the α-Fe2O3 (01[Formula: see text]2) surface, with the activation energy of 1.78eV and 2.62eV, respectively. In summary, we reveal the importance of co-adsorption on both Fe and O centers and oxidative addition on C-C bond cleavage of aromatic compounds on the α-Fe2O3 surface, which provides novel insights into the mechanisms of tar cracking on oxide catalysts.

The role of the pulp and paper industry in achieving net zero U.S. CO2 emissions in 2050

The pulp and paper industry is energy-intensive, making up about 9 % of total United States industrial energy consumption and 2.5 % of U.S. industrial greenhouse gas emissions. The pulp and paper industry is unique among industrial sectors due to its existing reliance on waste biomass to generate energy for mill operations. Pulp and paper mills could theoretically offer opportunities for negative emissions through carbon capture and storage (CCS) technologies along with use of biomass. In addition, the paper sector's use of low-temperature industrial heat creates opportunities for CO2 reductions through electrification technologies.We employ the Global Change Analysis Model (GCAM) to evaluate decarbonization pathways for the pulp and paper sector in the United States, as well as the sector's role in a net zero scenario and impacts on the energy, land, and water sectors. The version of GCAM used in this study includes detailed representation of major industrial sectors, including the pulp and paper industry. Representation of the linkage between forest products and paper production allow us to account for upstream carbon emissions, sequestration, and land-use impacts.Preliminary results under a pathway to net zero U.S. CO2 emissions in 2050 show that the pulp and paper industry can reach net zero CO2 emissions before 2050, earlier than the overall energy system, and contribute negative emissions thereafter. Use of fossil fuels is significantly reduced by 2050, shifting to increased electricity use in process heat generation. Consumption of biomass energy in process heat also increases compared to the reference scenario. Though paper production decreases in the policy scenario in response to higher prices of wood products, a high carbon price can incentivize increased use of biomass with CCS and thus paper production. Negative emissions opportunities in the paper industry have impacts on the land sector. Increasing use of biomass accelerates the shift from unmanaged to managed forests, with associated tradeoffs between technological carbon sequestration and natural ecosystem services.

Soc Trang residents’ willingness to payfor renewable energy development projects

In Vietnam, electricity production has been growing strongly and is expected tocontinue increasing in the future. However, heavy reliance on fossil fuels is putting significant pressure on the environment and national energy security. The public's awareness of the potential and benefits of renewable energy is still limited. The lackof understanding about the positive impacts of renewable energy compared to fossil fuels may lead to a lack of community support for the green energy transition process.This studyappliesthe approachof choice modelling (CM) or choice experiment (CE) toevaluatethe willingness to pay (contribute) of residents in Soc Trang province for renewable energy development projects. The results indicate that the majority of Soc Trang residents have some knowledgeabout common renewable energy sources such as solar, wind, and biomass energy. They demonstrate a willingness to contribute to the benefits that renewable energydevelopment projectscan bring, includingimproving the environmental landscape, protecting wildlife habitats, reducing air pollution, and creating new job opportunities. Among these benefits, they are particularly interested in the potential for job creation through renewable energydevelopment projects

Prioritization of investment order in Brazil among renewable energy sources: an analysis using the SWARA-MOORA-3NAG method

Purpose This paper aims to comprehensively analyze renewable energy alternatives in Brazil, focusing on identifying the most suitable option for investment in the country’s sustainable development. Design/methodology/approach The study adopts the step-wise weight assessment ratio analysis-multiobjective optimization by ratio analysis −3NAG (a combination of three normalization methods) methodology, a multicriteria decision-making approach, to evaluate and rank renewable energy sources based on key criteria such as resource availability, cost-effectiveness, job creation potential and environmental impact. Findings The analysis reveals that solar energy emerges as the preferred choice for Brazil, offering significant advantages over other alternatives such as hydroelectric, wind and biomass energy. Solar energy’s distributed generation capability, cost reduction trends and positive environmental impact contribute to its favorable position in meeting Brazil’s energy needs. Research limitations/implications While the study provides valuable insights into renewable energy selection, there are limitations regarding the criteria’ scope and the exclusion of specific renewable energy options. Future research could explore sensitivity analyses and incorporate additional criteria to enhance the study’s comprehensiveness. Originality/value This research contributes to the existing literature by thoroughly analyzing renewable energy alternatives in Brazil using a robust multicriteria decision-making methodology. The study’s findings provide actionable guidance for policymakers, businesses and stakeholders seeking to promote sustainable energy development in the country.

Rearing of Black Soldier Fly Larvae with Corn Straw and the Assistance of Gut Microorganisms in Digesting Corn Straw.

Corn straw is considered a renewable biomass energy source, and its unreasonable disposal leads to resource waste and environmental pollution. Black soldier fly (Hermetia illucens L.) larvae (BSFL) facilitate the bioconversion of various types of organic wastes. In this study, we found that 88% of BSFL survived, and 37.4% of corn straw was digested after 14 days of feeding with corn straw. Contrary to expectations, the pretreatment of corn straw with alkaline hydrogen peroxide did not promote its digestion but rather reduced the growth and survival rates of BSFL. Acinetobacter, Dysgonomonas, and unclassified Enterobacteriaceae were the abundant genera in the BSFL gut fed with corn straw. Compared with the standard diet, the relative abundances of carbohydrate metabolism genes, such as the gene abundances of β-glucosidase and α-glucosidase, were higher with corn straw as the substrate. These results suggested that the gut microbial community could regulate suitable and functional microorganisms in response to the substrates. Furthermore, four cellulase-producing strains, namely Klebsiella pneumoniae, Proteus mirabilis, Klebsiella oxytoca, and Providencia rettgeri, were isolated from the guts of corn straw BSFL. These four strains helped increase the conversion rates of corn straw, the weights of BSFL, and survival rates. In summary, we reared BSFL with corn straw and discovered the functions of gut microorganisms in adapting to the substrates. We also isolated four cellulase-producing strains from the BSFL guts and declared the benefits of BSFL digesting corn straw.

Performance evaluation of sustainable energy alternatives to obtain efficient hybrid energy investments

This study evaluates the synergy of coalition for hybrid renewable energy (RWB) system alternatives. In this context, the alternative sources of hybrid RWB system are examined to illustrate the impact-relation directions among them with multi SWARA based on q-ROFs and golden cut. Next, the performances of renewable alternatives are measured in terms of the synergy of coalition with game theory and Shapley value. It is concluded that solar energy is the most suitable RWB alternative for synergy to increase efficiency in investments. However, biomass does not have a significant influence on providing synergy in energy investments. Therefore, solar energy should be prioritized for hybrid energy investments. Especially with the effect of technological developments, the efficiency of solar energy investments increases significantly. Thus, solar energy investments have become quite suitable for increasing the synergy in hybrid energy projects. Furthermore, necessary research should be conducted to make biomass energy more efficient.

Comprehensive evaluation of rural regional integrated clean energy systems considering multi-subject interest coordination with pythagorean fuzzy information

In the development of a comprehensive clean energy system in rural areas, how to evaluate it scientifically and effectively is an urgent problem to be solved. Artificial intelligence has already been widely applied in the field of energy technology, but its application in the comprehensive benefit evaluation is still insufficient. The purpose of this study is to conduct a comprehensive evaluation of the rural, regional integrated clean energy system with coordinated multi-subject interests. Firstly, the interest relationship between the subjects of the participating rural regional comprehensive clean energy system is analyzed. And, the comprehensive benefit evaluation index system is established based on farmers, rural grid, new energy investment operators, government and interest subject reciprocity partners. Secondly, Sugeno-Weber aggregation operators are more flexible and used to acquire smooth aggregated outcomes from a group of information in a single set. Moreover, an algorithm of the multi-attribute decision-making process also reveals the supremacy and reliability of the research work. A case study is established to evaluate the rural integrated clean energy system with coordinated multi-subject interests. The results are as follows. The index system reflects the characteristics of the comprehensive clean energy system in rural areas, such as environmental characteristics, economic characteristics, safety characteristics and clean energy characteristics. The advantages and validity of developed research work are proved by comparing the findings of pioneered approaches with existing mathematical operators. The ranking of suitable energy sources is Solar power > Biomass energy > Geothermal energy > Wind and hydropower based integrated clean energy system.

Hot Topics at the 18th SDEWES Conference in 2023: A Conference Report

The present paper reviews the hot topics at the 18th Conference on Sustainable Development of Energy, Water, and Environment Systems (SDEWES) held from 24 to 29 September 2023 in Dubrovnik, Croatia. The selected papers, including aspects of biomass energy application, energy saving in building, low-carbon development and climate change adaptation, hybrid application of sustainable energy, energy storage system, and other measures in sustainable development, are published in this Special Issue of Energies. The 12 selected papers in Energies and corresponding literature that relates to the above topics and has been published in the most recent year are reviewed. In particular, diversifying energy applications are trending towards comprehensive integration with more efficient clean energy capacities for global energy procurement, which can also offer increased resilience and sustainability, reduce reliance on fossil fuels, mitigate environmental impacts, and enhance energy security through a mix of renewable sources and innovative technologies. Meanwhile, energy storage has become increasingly important, which can manage the intermittent of renewable energy, stabilize the grid, and improve energy security and resilience against disruptions. In addition to conventional solar energy storage, biomass energy storage, building energy storage, water storage, etc., can also reduce the overall energy costs, deferring investments in additional transmission infrastructure.

Enhancing prediction of elemental composition through machine learning decision tree models for biomass gasification optimization

Abstract The worldwide transition to cleaner, sustainable energy sources, prompted by population growth and industrialization, responds to uncertain fossil fuel prices and environmental concerns, highlighting the substantial benefits of renewable energy in reducing greenhouse gas emissions and addressing climate change. Derived from non-fossilized organic materials, biomass emerges as a significant and sustainable contributor to renewable energy. Its diverse nature is complemented by a range of conversion technologies, encompassing combustion, pyrolysis, gasification, and liquefaction, providing versatile avenues for biomass energy transformation. Gasification, the transformative process of converting organic matter into combustible gases under controlled oxygen levels, is accomplished through direct oxygen supply or pyrolysis. This method yields a dependable gaseous fuel versatile for heating, industrial processes, power generation, and liquid fuel production. Machine learning employs advanced statistical techniques for modeling across diverse industries, showcasing particular efficacy in optimizing thermochemical processes by precisely identifying the optimal operating conditions required for achieving desired product properties. These models utilize proximate biomass data to predict the elemental compositions of N2 and H2. Assessment of both single and two hybrid models indicated that the introduced optimizers significantly enhanced the estimation of N2 and H2 when combined with Decision Tree (DT), with Decision Tree Coupled with Artificial Hummingbird Algorithm (DTAH) proving particularly effective. Notably, DTAH demonstrated outstanding performance with remarkable R 2 values of 0.990 for N2 and 0.992 for H2. Additionally, the minimal Root Mean Square Error (RMSE) values of 1.291 and 1.550 for N2 and H2 predictions respectively underscore the precision of DTAH, establishing it as a suitable choice for practical real-world applications.

Harnessing the Power of Renewable Energy: A Study of Sustainable Sources and Technologies

This research investigates the capacity of renewable energy technologies to fulfill global energy requirements while mitigating environmental effects, concentrating on primary sources like sun, wind, hydropower, biomass, and geothermal energy. It evaluates the efficacy of various technologies for energy production, efficiency, economic viability, and reduction of carbon emissions. The findings underscore notable progress in solar and wind energy, demonstrating considerable efficiency enhancements (5% for solar PV, 10% for wind turbines) and cost reductions (67% and 64%, respectively) during the last decade. Hydropower is the most efficient energy source, converting 90% of available energy, albeit it is geographically constrained. The research highlights the environmental advantages, noting that renewable technologies substantially decrease CO₂ emissions—hydropower and wind energy prevent 250,000 and 120,000 metric tons of CO₂ annually, respectively. Nonetheless, obstacles such as the variability of solar and wind energy, elevated expenses associated with biomass and geothermal energy, and regional variations in implementation persist as substantial impediments. The research highlights the need for further developments in energy storage, grid modernization, and legislative assistance to expedite the worldwide shift towards renewable energy. This study synthesizes current statistics and trends, emphasizing the vital role of renewable energy in attaining a sustainable, low-carbon future, while also tackling ongoing economic and infrastructural problems.

Electrooxidation of glycerol to formic acid coupled with Energy-Saving hydrogen production over ruthenium doped Cobalt-Based nanosheet arrays

The utilization of small molecule oxidation reactions as a substitute for the sluggish oxygen evolution reaction (OER) in traditional water electrolysis represents an innovative approach to achieve efficient hydrogen production while concurrently generating value-added chemicals. Herein, we report an energy-saving H2 production system utilizing electrooxidation of glycerol to generate valuable formate. Cobalt–ruthenium oxide nanosheet arrays (CoRuO/CF) and cobalt–ruthenium bimetallic nanoparticles wrapped by nitrogen-doped carbon nanosheet arrays (CoRuCN/CF) were synthesized for glycerol oxidation reaction (GOR) and hydrogen evolution reaction (HER), respectively, using Co-ZIF nanosheets precursor material supported on copper foam (Co-ZIF/CF) as the substrate. Remarkably, the hybrid electrolysis system can achieve a current density of 10 mA cm−2 with only 1.19 V, which is significantly lower than that required by traditional water-splitting systems. This work demonstrates the promising potential of efficiently utilizing biomass energy and achieving a sustainable production process for fine chemical products.

Unveiling energy transition strategy: A deep dive into China's ambitious renewable energy policy and its impact on carbon emission dynamics

Over the past 70 years, China has issued approximately 20,000 renewable energy (RE) policies. How to interpret China's ambitious RE strategy through these policy documents and assess its effectiveness has been a question of interest. Therefore, based on 15,603 Chinese RE policy documents from 1975 to 2022, this study employs text mining, Latent Dirichlet Allocation (LDA), Policy Modeling Consistency-Text Encoder (PMC-TE), and System-Generalized Method of Moments (SYS-GMM). It assesses the policy input intensity (PII) for different energy types, regions, and time periods, while also investigating the impact of PII about RE on carbon emissions. The study findings are as follows: (1)The PII is not uniform, with hydropower having the highest PII at 80,591, followed by solar (25,839) and biomass energy (18,903). The PII of wind (11,377) and geothermal energy (11,340) is similar, while hydrogen energy exhibits the weakest PII at 3488. (2)There are regional disparities in PII, with solar and wind energy being most prominent in northern regions, solar and hydropower being most significant in eastern regions, and wind and biomass energy aligning with local resources in southern regions. (3)RE policies have driven China's energy transition through four distinct phases. (4)Policy effectiveness varies, with solar, wind, and hydropower policies having the most significant impact on carbon emissions reduction, followed by biomass and geothermal energy. (5)China's government role in the RE strategy has shifted from a dominant role to a regulatory one.

Optimizing biomass energy production in the southern region of Iran: A deterministic MCDM and machine learning approach in GIS

This study employs a deterministic approach, distinguishing itself from other renewable energy evaluations, to assess the potential of electrical energy derived from biomass sources in the southern region of Iran. The primary objectives include pinpointing optimal locations for maximal biomass production and subsequent energy generation within distinct climates and topographies, using fuzzy- Analytic Hierarchy Process (AHP). Additionally, Principal Component Analysis (PCA) identify key factors influencing biomass and energy production. The study quantifies electrical and thermal energy derived from biomass sources across various climates. The findings indicate that regions with lower altitudes and humid climates (1530 km2) demonstrate superior biomass performance, leading to increased electrical and thermal energy production. The feature selection process highlights the significant impact of climate and soil characteristics on biomass production and energy output. Analysis of biomass energy production reveals maximum electrical energy production ranging from 674.88 kWh/ha to 711.36 kWh/ha. The results of the Long Short-Term Memory (LSTM) method confirm its high accuracy in estimating electrical energy, with a significant correlation coefficient of 0.98. We conclude that by identifying locations with the best biomass sources based on climate, it is possible to increase the derived electrical energy. These insights are critical for informing energy policies aimed at optimizing biomass energy production and its integration into sustainable power grids.

Increasing Fertilization Efficiency of Biomass Ash by the Synergistically Acting Digestate and Extract from Water Plants Sequestering CO2 in Sorghum Crops.

The utilization of biomass ash in sustainable agriculture and increasing its fertilizing efficiency by biological agents, potentially sequestering CO2, have become important issues for the global economy. The aim of this paper was to investigate the effects of ash from sorghum (Sorghum bicolor L. Moench) and Jerusalem artichoke (Helianthus tuberosus L.) biomass, a biogas plant digestate, and a Spirodela polyrhiza extract, acting alone or synergistically, on soil fertility and the development, health and physiological properties of sorghum plants. The results show novel information concerning differences in the composition and impact of ash, depending on its origin, soil properties and sorghum plant development. Sorghum ash was more effective than that from Jerusalem artichoke. Ash used alone and preferably acting synergistically with the digestate and Spirodela polyrhiza extract greatly increased soil fertility and the growth, biomass yield and health of sorghum plants. These improvements were associated with an increased chlorophyll content in leaves, better gas exchange (photosynthesis, transpiration, stomatal conductance), greater enzyme activity (acid and alkaline phosphatase, RNase, and total dehydrogenase), and a higher biomass energy value. The developed treatments improved environmental conditions by replacing synthetic fertilizers, increasing the sequestration of CO2, solving the ash storage problem, reducing the need for pesticides, and enabling a closed circulation of nutrients between plant and soil, maintaining high soil fertility.

Analysis of renewable energy resources based on frank power aggregation operators and EDAS method for circular bipolar complex fuzzy uncertainty

The model of circular bipolar complex fuzzy (Cir-BCF) sets computed based on the membership function, non-membership function, and radius among both functions for each value of the universal set. The technique of the Cir-BCF set is the modified or extended form of fuzzy sets, complex fuzzy sets, bipolar fuzzy sets, bipolar complex fuzzy sets, and simple circular bipolar fuzzy sets to cope with uncertain and vague information. In this manuscript, we describe the novel technique of frank operational laws based on Cir-BCF values for frank t-norm and frank t-conorm. Further, we simplify the model of Cir-BCF frank power averaging (Cir-BCFFPA), Cir-BCF frank power weighted averaging (Cir-BCFFPWA), Cir-BCF frank power geometric (Cir-BCFFPG), Cir-BCF frank power weighted geometric (Cir-BCFFPWG) operators, and highlighted their valuable properties, called idempotency, monotonicity, and boundedness. Moreover, analysis of renewable energy resources is very awkward and complicated, but it is natural sources of energy that are refilled constantly or relativeness quickly on a human timescale. Further, solar energy, hydroelectric energy, geothermal energy, biomass energy, and wind energy are five major sources of energy, but it is complex to find which one is the best and which one is worst. For evaluating the above problems, we construct the technique of evaluation based on the distance from the average solution (EDAS) method under the presence of the Cir-BCF numbers (Cir-BCFNs). At the end, we arrange the comparison between proposed and existing techniques based on some numerical examples to describe the validity and proficiency of the initiated information.

Effects of Biophysical Factors on Light Use Efficiency at Multiple Time Scales in a Chinese Cork Oak Plantation Ecosystem

Light use efficiency (LUE) characterizes the efficiency of vegetation in converting photosynthetically active radiation (PAR) into biomass energy through photosynthesis and is a critical parameter for gross primary productivity (GPP) in terrestrial ecosystems. Based on the eddy covariance measurements of a Chinese cork oak plantation ecosystem in northern China, the temporal variations in LUE were investigated, and biophysical factors were examined at time scales ranging from hours to years. Our results show that diurnal LUE first increased sharply before 8:30 and then decreased gradually until 12:00, thereafter increasing gradually and reaching the maximum value at sunset during the growing season. The daily and monthly LUE first increased and then decreased within a year and showed a substantial drop around June. The annual LUE ranged from 0.09 to 0.17 g C mol photon−1, and the multiyear mean maximal LUE was 0.30 g C mol photon−1 during 2006–2019. Only GPP (positive) and clearness index (CI) (negative) had consistent effects on LUE at different time scales, and the effects of the remaining biophysical factors on LUE were different as the time scale changed. The effects of air temperature, vapor pressure deficit, precipitation, evaporative fraction, and normalized difference vegetation index on LUE were mainly indirect (via PAR and/or GPP). When CI decreased, an increased ratio of diffuse PAR to PAR produced a more uniform irradiance in the canopy, which ultimately resulted in a higher LUE. Due to climate change in our study area, the annual LUE may decrease in the future but improving management practices may slow or even reverse this trend in the annual LUE in the studied Chinese cork oak plantation.