Low Irradiance Conditions Research Articles

Supraharmonic Distortion at the Grid Connection Point of a Network Comprising a Photovoltaic System

Grid-connected photovoltaic (PV) systems inject nonsinusoidal currents into the grid at the point of their connection. The technology of the inverter utilized for the conversion of DC power into AC is directly associated with distortion characteristics. Even though pulse-width-modulated (PWM) converters generate considerably lower harmonic distortion than their predecessors, they are responsible for the emergence of a new power quality issue in distribution grids known as supraharmonics, which can cause problems such as overheating and malfunctions of equipment. PV systems are known sources of supraharmonics, but their impact has not yet been thoroughly researched. Due to the multitude of parameters affecting their performance, a more rigorous treatment is required compared to more common nonlinear devices. In this paper, emissions from a three-phase grid-connected PV system are examined by means of a dedicated simulation tool taking into account the specifics of inverter switching action without overly increasing computational cost. The impact of environmental parameters as well as factors affecting the switch control of the converter is investigated. The dependence of the supraharmonic emission of the PV system on the converter characteristics rather than environmental conditions is demonstrated. Furthermore, simulation studies on a network comprising the PV system and an additional supraharmonic-emitting system in simultaneous operation are conducted. Their combined effect on the distortion at the connection point of the network to the grid is assessed by means of a power flow-based approach, capable of quantifying interactions within this network. From the viewpoint of the grid, an increase of supraharmonic-related disturbance at low irradiance conditions is revealed.

Visual System Inspired Algorithm for Enhanced Visibility in Coronary Angiograms (VIAEVCA).

Numerous efforts have been invested in previous algorithms to expose and enhance blood vessel (BV) visibility derived from clinical coronary angiography (CAG) procedures, such as noise reduction, segmentation, and background subtraction. Yet, the visibility of the BVs and their luminal content, particularly the small ones, is still limited. We propose a novel visibility enhancement algorithm, whose main body is inspired by a line completion mechanism of the visual system, i.e., lateral interactions. It facilitates the enhancement of the BVs along with simultaneous noise reduction. In addition, we developed a specific algorithm component that allows better visibility of small BVs and the various CAG tools utilized during the procedure. It is accomplished by enhancing the BVs' fine resolutions, located in the coarse resolutions at the BV zone. The visibility of the most significant clinical features during the CAG procedure was evaluated and qualitatively compared by the consensus of two cardiologists (MM and JE) to the algorithm's results. These included the visibility of the whole frame, the coronary BVs as well as the small ones, the main obstructive lesions within the BVs, and the various angiography interventional tools utilized during the procedure. The algorithm succeeded in producing better visibility of all these features, even under low-contrast or low-radiation conditions. Despite its major advantages, the algorithm also caused the appearance of disturbing vertebral and bony artifacts, which could somewhat lower diagnostic accuracy. Yet, viewing the processed images from multiple angles and not just from a single one and evaluating the cine mode usually overcomes this drawback. Thus, our novel algorithm potentially leads to a better clinical diagnosis, improved procedural capabilities, and a successful outcome.

Analytic modeling of sensitivity in diffusion-limited type-II superlattice mid-wave infrared nBn photodetectors for design optimization for low-irradiance conditions

An analytical model for diffusion-limited detector sensitivity under low-irradiance conditions is derived from carrier continuity equations and verified with Silvaco TCAD drift-diffusion software. The model is used to determine the optimal design parameters for a mid-wave infrared InAs/InAsSb type-II superlattice nBn photodetector for maximum sensitivity under both topside- and backside-illumination conditions. A minimum attainable noise-equivalent irradiance of 4.5 × 1010 photons/cm2 s is found for InAs/InAsSb nBn at 130 K, roughly 2.4× higher than a detector exhibiting Rule 07 dark current density and unity quantum efficiency. A design heuristic, offering a simple and practical approach to designing a high-sensitivity detector, is then developed and performance is found to be comparable to the optimally designed structures. Finally, an evaluation of the impact of each material parameter on noise-equivalent irradiance is performed, revealing that the intrinsic carrier concentration, effective minority carrier lifetime, and absorption coefficient exhibit the largest impacts on sensitivity for diffusion-limited detectors.

Study on the performance and mechanism of photocatalytic hydrogen production by NiO/ZnO-graphene composite materials under low irradiation conditions

Using different mass ratios of NiO, ZnO, and corn stover-based graphene (GR), NiO/ZnO-graphene (NZGR) composite photocatalytic materials, which demonstrated photocatalytic water splitting for hydrogen production under low irradiation, were prepared by an in-situ deposition method. The microstructure and optoelectronic properties of the NZGR materials were characterized. The heterostructure formed by NiO and ZnO in the photocatalytic NZGR material was coupled with the graphene-like structure of GR, resulting in the rapid transfer of electrons to the graphene surface, causing electron accumulation and ensuring the ability of the material to produce hydrogen by the photocatalytic decomposition of water under low irradiation. Under the optimal mixing ratio of the components of the NZGR photocatalyst with a graphene mass fraction of 30 %, hydrogen production exhibited the highest rate and was 350 times faster than the photocatalytic hydrogen production of NiO/ZnO under the same conditions. This study provides a new approach to producing hydrogen by the photocatalytic decomposition of water under low irradiation conditions.

Photosynthetic efficiency of three C4 species is maintained under low light and high vapour pressure deficit

The photosynthetic efficiency of C4 plants could be impaired in environments with low light and high vapour pressure deficit (VPD). However, the interactive effect of low light and high VPD on C4 photosynthetic efficiency remains unexplored. We grew three C4 species, Setaria viridis L., Sorghum sudanense (Piper) Stapf., and Zea mays L., under controlled high and low irradiance and VPD conditions in growth chambers. Gas exchange and chlorophyll fluorescence parameters were measured to estimate apparent maximum quantum yield (QYmax), and 13C discrimination of leaf dry mass (ΔDM) was measured to estimate bundle-sheath leakiness (BS-leakiness). Averaged over VPD levels, net CO2 assimilation rate at saturating light (Asat) decreased in S. viridis and S. sudanense but not Z. mays under low irradiance. High VPD decreased Asat of S. viridis but increased Asat of Z. mays. QYmax was not significantly affected by low light, high VPD or their interaction, which was associated with the unchanged photochemical efficiency of photosystem II. Low light did not significantly influence BS-leakiness, while high VPD only increased BS-leakiness of Z. mays by 0.08 compared with low VPD at low irradiance. The insignificant interaction of low light and high VPD on QYmax and BS-leakiness indicates that these C4 species could maintain photosynthetic efficiency under these unfavourable conditions.

Multifactorial effects of warming, low irradiance, and low salinity on Arctic kelps

Abstract. The Arctic is projected to warm by 2 to 5 °C by the end of the century. Warming causes melting of glaciers, shrinking of the areas covered by sea ice, and increased terrestrial runoff from snowfields and permafrost thawing. Warming, decreasing coastal underwater irradiance, and lower salinity are potentially threatening polar marine organisms, including kelps, that are key species of hard-bottom shallow communities. The present study investigates the physiological responses of four kelp species (Alaria esculenta, Laminaria digitata, Saccharina latissima, and Hedophyllum nigripes) to these environmental changes through a perturbation experiment in ex situ mesocosms. Kelps were exposed for 6 weeks to four experimental treatments: an unmanipulated control; a warming condition under the CO2 emission scenario SSP5-8.5; and two multifactorial conditions combining warming, low salinity, and low irradiance reproducing the future coastal Arctic exposed to terrestrial runoff under two CO2 emission scenarios (SSP2-4.5 and SSP5-8.5). The physiological effects on A. esculenta, L. digitata, and S. latissima were investigated, and gene expression patterns of S. latissima and H. nigripes were analyzed. Across all species and experimental treatments, growth rates were similar, underlying the acclimation potential of these species to future Arctic conditions. Specimens of A. esculenta increased their chlorophyll a content when exposed to low irradiance conditions, suggesting that they may be resilient to an increase in glacier and river runoff with the potential to become more dominant at greater depths. S. latissima showed a lower carbon : nitrogen (C : N) ratio under the SSP5-8.5 multifactorial conditions' treatment, suggesting tolerance to coastal erosion and permafrost thawing. In contrast, L. digitata showed no response to the conditions tested on any of the investigated physiological parameters. The down-regulation of genes coding for heat-shock proteins in H. nigripes and S. latissima underscores their ability to acclimate to heat stress, which portrays temperature as a key influencing factor. Based on these results, it is expected that kelp communities will undergo changes in species composition that will vary at local scale as a function of the changes in environmental drivers.

Advanced extraction of PV parameters’ models based on electric field impacts on semiconductor conductivity using QIO algorithm

This article presents a novel approach for parameters estimation of photovoltaic cells/modules using a recent optimization algorithm called quadratic interpolation optimization algorithm (QIOA). The proposed formula is dependent on variable voltage resistances (VVR) implementation of the series and shunt resistances. The variable resistances reduced from the effect of the electric field on the semiconductor conductivity should be included to get more accurate representation. Minimizing the mean root square error (MRSE) between the measured (I–V) dataset and the extracted (V–I) curve from the proposed electrical model is the main goal of the current optimization problem. The unknown parameters of the proposed PV models under the considered operating conditions are identified and optimally extracted using the proposed QIOA. Two distinct PV types are employed with normal and low radiation conditions. The VVR TDM is proposed for (R.T.C. France) silicon PV operating at normal radiation, and eleven unknown parameters are optimized. Additionally, twelve unknown parameters are optimized for a Q6-1380 multi-crystalline silicon (MCS) (area 7.7 cm2) operating under low radiation. The efficacy of the QIOA is demonstrated through comparison with four established optimizers: Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Salp Swarm Algorithm (SSA), and Sine Cosine Algorithm (SCA). The proposed QIO method achieves the lowest absolute current error values in both cases, highlighting its superiority and efficiency in extracting optimal parameters for both Single-Crystalline Silicon (SCS) and MCS cells under varying irradiance levels. Furthermore, simulation results emphasize the effectiveness of QIO compared to other algorithms in terms of convergence speed and robustness, making it a promising tool for accurate and efficient PV parameter estimation.

Effect of proton irradiation dose rate and implanted hydrogen ions on spinodal decomposition in thermally aged EQ308L stainless steel weld metal

Abstract Stainless steel welds with a ferritic phase are extensively utilized in nuclear power plants. Spinodal decomposition stands as the primary factor contributing to the degradation of their service performance. Ion irradiation has been widely employed to investigate the damage behavior of materials. However, varying irradiation parameters, such as dose rate and implanted ions, are believed to result in significant differences in the extent of spinodal decomposition. In this paper, proton irradiation experiments were conducted at different dose rates on thermally aged EQ308L stainless steel welds. Spinodal decomposition within the ferrite at various radiation depths was compared and analyzed by using atom probe tomography to unveil the effects of dose rate and implanted hydrogen ions. The results reveal that, under conditions of high dose rate irradiation, spinodal decomposition can be partially alleviated when compared to the initial thermally aged state. Conversely, under low dose rate irradiation conditions, spinodal decomposition exhibits an enhancement trend. This difference may be attributed to the interplay between irradiation-enhanced diffusion and atomic mixing. Therefore, the dose rate significantly influences the progression of spinodal decomposition. Furthermore, implanted hydrogen ions may also inhibit spinodal decomposition within the ferrite, potentially by promoting the recombination of irradiation defects.

Applications of different types of heat pipes in solar desalinations: A comprehensive review.

Desalination processes are energy consuming and it is required to apply clean energy sources for supplying them to prevent environmental issues. Solar energy is one of the attractive clean energy sources for desalination. In solar thermal desalination systems, different thermal components could be used for heat transfer purpose. In solar desalination technologies, heat pipe as efficient heat transfer mediums could be employed to transfer absorbed and/or stored thermal energy. The objective of this study is to review applications of heat pipes in solar energy desalination systems. Regarding the performance dependency of these thermal systems on the variety of factors, scholars have investigated these systems by consideration of the effect of different influential factors. Based on the results, it is concluded that use of heat pipes could lead to proper performance of solar desalination systems. Aside from direct transfer of absorbed heat from solar radiation, heat pipes can be applied in the storage units of solar desalination systems to keep the systems active in night-hours or low solar irradiation conditions. The overall performance of the solar desalinations systems with heat pipes can be influenced by some factors such as filling ratio and operating fluid that affect the performance of heat pipes.

Effective-diode-based analysis of industrial solar photovoltaic panel by utilizing novel three-diode solar cell model against conventional single and double solar cell.

Currently, the majority of the country has moved to renewable energy sources for electricity generation, and power companies are concentrating their efforts on renewable resources. Solar, wind, hydropower, and biomass are examples of renewable resources; of these, due to a lack of non-renewable resources, the solar industry is expanding. All year long, solar electricity is available, and it creates a calm, quiet atmosphere. The majority of large and small companies, as well as individual consumers, have shifted to PV solar cells for electricity generation. A trustworthy and precise simulation design of a photovoltaic system prior to installation is required to predict a photovoltaic system's performance. The current research aims to build models for solar PV systems with one, two, and three diodes and determine which model is most appropriate for each environmental circumstance to forecast performance accurately. By contrasting the experimental data of solar panel with simulated results of single-, double-, and triple-diode models, this study examines the accuracy of each model. These models' comparative performance study has been done using the MATLAB/Simulink, taking into account the influence of changing model parameters and the performance of the models under varying climatic circumstances. These models, despite their simplicity, are quite sensitive and react to even a little change in temperature and irradiance. Under conditions of low solar irradiance or shading conditions, three-diode photovoltaic models are shown to be more accurate. We can forecast the power output of solar photovoltaic systems under changeable input circumstances by understanding the I-V curves with the help of the performance assessment of the models used in this work.

Improved reference condition independent method for output performance estimation of PV modules under varying operating conditions

Traditional methods for estimating output property of the photovoltaic (PV) modules are strongly influenced by the selection of reference condition and transforming equations, which determine the calculated physical parameters under real operating conditions. The differences in the carrier transport properties of PV cells under varying operating conditions, such as the number and velocity of minority carriers at the junction edge and their recombination speed, lead to large deviations in the estimation of the output characteristics, especially under low irradiance conditions. To enhance the accuracy of performance estimation, we propose an improved method that is independent of reference condition. This method eliminates the impact of reference conditions and improves the transformation equations under all irradiance levels. Transformation equations of single diode model are established in different irradiance intervals based on the dependence of physical parameter on irradiance and temperature. Especially in the low irradiance range, all effects of irradiance and temperature are considered for each physical parameter in improved transformation equations. To optimize the unknown parameters in the transformation equations, the artificial hummingbird algorithm is used to fit experimental I–V data. The experimental results of six different types PV modules under a wide range of operating conditions are used to verify the effectiveness of the proposed method. The proposed method offers immediate benefits, including independence from reference condition and a more precise relationship between physical parameters and environmental factors in the estimation of PV output properties. Comparing the results to the traditional method by Laudani, the proposed method demonstrates superior capability in estimating I–V characteristics and accurately identifies the maximum power point under various operating conditions, which is of significant value for engineering applications.

Measurement of the Current-Voltage Curve of Photovoltaic Cells Based on a DAQ and Python

The renewable energy has grown extensively in the last decades. The photovoltaic panels have been playing a significant role in the technologies used to produce this kind of energy. This tendency is expected to continue in the future, because the cost of the solar panels has been gradually reduced. Systems providing information of the performance of the solar cells can be helpful for technicians and researchers. In this paper a system to measure the I-V curves of photovoltaic cells is presented. This is composed by a data acquisition board (DAQ) and a personal computer (PC). The program to control the DAQ is written in Python. With this system a polycrystalline silicon solar cell was tested under low irradiance conditions (less than 100 W/m2) with an artificial light source. The repeatability of the I-V curves obtained has less than 5 % error.

Analysis of water and refrigerant-based PV/T systems with double glass PV modules: An experimental and computational approach

Water and refrigerant-based photovoltaic/thermal (PV/T) systems have substantial promise as sustainable energy solutions for commercial and residential buildings. Integrated photovoltaic and solar thermal systems outperform discrete systems in conversion efficiency and space utilization. There is a dearth of quantitative comparative studies on these systems despite their functional similarities. This study offers a comparative analysis of PV/T systems employing water and refrigerant as heat transfer fluids. Both systems are characterized by identical size and collector design. Prototypedevelopment, experimental research, and parametric assessments using computer models are used to attainthis target. Furthermore, the design of the PV/T collector in this research study involved the utilization of a double glass PV module instead of a tedlar back sheet PV module. Based on ambient conditions, refrigerant-based PV/T systems can reach a final water temperature of 7 °C to 14.9 °C higher than water-based systems. In low irradiance conditions, the refrigerant-based system generates hot water more reliably than the water-based system.

Two combined model MPPT algorithms for stand alone photovoltaic systems

Maximum Power Point Trackers (MPPT’s) play an important role in stand alone photovoltaic systems. MPPT’s find and maintain operation at the maximum power point, using an MPPT algorithm. Many MPPT algorithms have been proposed in the literature. The MPPT techniques using microprocessors are favored because of their flexibility and compatibility with different PV module. The efficiency of these MPPT algorithms is drops in cases of rapidly changing atmospheric conditions. The incremental conductance solves this problem. In the other way, we find that the constant voltage algorithm is the simplest and is more effective than the incremental conductance in case of low solar irradiance condition. This paper combines the two models MPPT control algorithm, the constant voltage and the incremental conductance under different solar irradiance levels. Firstly, a novel model is proposed to predict the PV module performance for engineering applications and compared with the Walker model. A MSX60 PV, BPSX150 PV and PB585 PV modules are selected to proof the performance of the proposed model. Next, the combined two model MPPT algorithm is applied at various irradiations solar. Finally, a model of Cuk converter is built in order to verify the performance of proposed MPPT algorithm.

Thermodynamic analysis and optimization of liquid air power plant integrated with parabolic trough solar collectors

ABSTRACT As to investigate the impact of parabolic trough collector optical characteristics on the comprehensive performance of solar-driven liquid-gas energy storage power plants, this study establishes a mathematical analysis model for a liquid-gas energy storage power plant with a parabolic trough collector. The effects of direct irradiance, collector tracking mode, and component configuration on collector efficiency, round-trip efficiency, and exergy efficiency are analyzed. The results show that when the direct irradiance exceeds 400 W/m2, the round-trip efficiency of the system decreases while the exergy efficiency increases. For every 100 W/m2 increase in irradiance, the round-trip efficiency decreases by 1.54%, and the exergy efficiency increases by 2.36%. The north-south axis tracking mode is superior to the east-west axis tracking mode and dual-axis tracking mode. The component configuration improves the collector efficiency and round-trip efficiency but decreases the thermal efficiency. In low irradiance conditions (direct irradiance less than or equal to 400 W/m2), the system performance is optimal when the collector optical efficiency is maintained at 74%. Under these conditions, the system achieves a maximum net energy output of 495.12 kW·s/kg, the exergy efficiency of 54.5%, and the round-trip efficiency of 18.96%. In high irradiance conditions (direct irradiance greater than 400 W/m2), a 10% increase in collector optical efficiency leads to a 1.94 kW·s/kg decrease in net energy output, a 3.14% decrease in exergy efficiency, and a 0.05% decrease in round-trip efficiency.

Enhancement method for high colour polarization region under low irradiance condition

Due to the significant impact of low illumination environments on polarization imaging, polarization information is heavily influenced by noise interference. To address this issue, we propose a fusion method to enhance the high colour polarization area in low irradiance conditions. Firstly, we obtain the colour degree of linear polarization (DoLP) image, the colour angle of polarization (AoP) image, and the colour intensity (S0) image by the colour polarization camera. We normalize the S0 image. Subsequently, we map the colour AoP information in combination with the colour DoLP threshold to the H channel. The visual saliency information and brightness information of the colour DoLP image and the colour S0 image are mapped to the S channel and V channel, respectively. Finally, the data is transferred to the RGB space. Experiments show that our method surpasses several existing methods in both visual quality and quantitative measurement.

Optimizing PV Power Output with Higher-Voltage Modules: A Comparative Analysis with Traditional MPPT Methods

Summary. The dynamically rising demand for electricity must be satiated by both conventional and unconventional power sources. PV electricity generation is essential. The installed PV sources are not used to their full potential due to low irradiance and poor weather. The goal of many research publications was to maximize PV power using different MPPT approaches. In order to extract the most power under the aforementioned circumstances, this study introduces a novel notion of using a voltage boosting PV panels. Additional PV panels are used in the suggested way to provide enough voltage and current. Using a voltage-boosting PV panel, a 20 kW panel is examined for low irradiance and unfavorable weather conditions. In a proposed method, results are compared with the previous INC MPPT method using a 20-kW panel. Through the power analysis, the proposed method extracted 1277.5 kW of power per year that is more than the INC MPPT method, and Rs. 10,220 per year was benefited during low irradiation alone. The power extraction and cost benefits are similar in cloudy and misty conditions. With power, cost, and efficiency analyses, the new method is contrasted with the traditional incremental conductance method and perturb and observe methods. Simulations were run using the MATLAB/Simulink programme, and experimental results were assessed using the appropriate hardware setup.

Environmental irradiance and nitrogen source variability trigger the intracellular carbon and nitrogen reallocation of Gracilariopsis lemaneiformis (Rhodophyta)

A rhodophyte Gracilariopsis lemaneiformis is widely cultivated for food, carbon sequestration and bioproducts, and commonly experiences changing irradiance levels and nitrogen sources that might influence the productivity and biochemical composition of the alga. To explore optimal culture conditions or manipulations to gain best yield of carbohydrates and amino acids of G. lemaneiformis during mariculture, we cultured G. lemaneiformis in four conditions including high irradiance and low irradiance coupled with nitrate and ammonium (denoted as HI-NO3−, LI-NO3−, HI-NH4+ and LI-NH4+). The results showed that irradiance, nitrogen source and their interactions significantly regulated the intracellular carbon and nitrogen metabolism of G. lemaneiformis and the influence of irradiance was greater than of nitrogen source. High irradiance promoted more carbon accumulation of G. lemaneiformis, which was confirmed by higher growth rate, net photosynthesis rates and contents of soluble carbohydrate, carbon and C/N ratios. In contrast, low irradiance is conductive to nitrogen accumulation, as revealed by high contents of nitrogen, phycoerythrin, soluble protein and amino acids. Furthermore, we found nitrate coupled with high irradiance significantly promoted carbon sequestration of G. lemaneiformis, and the ammonium combined with low irradiance significantly promoted nitrogen assimilation and transformation. In addition, arginine exhibited a higher nitrogen storage capacity than phycoerythrin, as evidenced by the higher content of arginine and correspondingly higher nitrogen reserves in G. lemaneiformis under low light coupled with ammonium and nitrogen- enriched environments. Moreover, the content of proline was higher under low irradiance conditions, but its proportion among the eighteen free amino acids was upregulated by high irradiance, indicating its important role in responding to high-light aquaculture environments. These findings demonstrate that irradiance and nitrogen source influence the carbon and nitrogen reallocation of G. lemaneiformis and that the combination of these two variables can induce the production of chemical products for biotechnological, aquaculture, and nutraceutical industry.

Exploring the Feasibility of Battery Electric and Fuel Cell Electric Vehicles as Peaker Plant Substitutes at Low Wind and Irradiation Conditions

In this paper a comparison between the use of Battery Electric Vehicles (BEVs) and Fuel Cell Electric Vehicles (FCEVs) to span cold dark doldrums (“Dunkelflaute”) in a future energy system with a high penetration of renewable energy supply is presented. A big problem with the cold dark doldrums is the rareness of the situation. Any power plant built to specifically be used during those special weather conditions will be operated only 0.1 % of the time according to a study on the energy demand in Germany in 2050 Aurora (2021) even though 10 GW are required to meet the demand. A prototype FCEV docking station to measure power transfer efficiencies was built. By this, we investigated supplying a district with energy via FCEVs by simulating a district with varying amounts of BEVs present. It is possible to supply a district with a low number of FCEVs although a stationary hydrogen connection would be beneficial. The efficient transfer of energy from a FCEV to a building requires a careful design of the plate heat exchangers and depends on the temperature level of the supplied building.

Short- and long-term responses of leaf day respiration to elevated atmospheric CO2.

Evaluating leaf day respiration rate (RL), which is believed to differ from that in the dark (RDk), is essential for predicting global carbon cycles under climate change. Several studies have suggested that atmospheric CO2 impacts RL. However, the magnitude of such an impact and associated mechanisms remain uncertain. To explore the CO2 effect on RL, wheat (Triticum aestivum) and sunflower (Helianthus annuus) plants were grown under ambient (410 ppm) and elevated (820 ppm) CO2 mole fraction ([CO2]). RL was estimated from combined gas exchange and chlorophyll fluorescence measurements using the Kok method, the Kok-Phi method, and a revised Kok method (Kok-Cc method). We found that elevated growth [CO2] led to an 8.4% reduction in RL and a 16.2% reduction in RDk in both species, in parallel to decreased leaf N and chlorophyll contents at elevated growth [CO2]. We also looked at short-term CO2 effects during gas exchange experiments. Increased RL or RL/RDk at elevated measurement [CO2] were found using the Kok and Kok-Phi methods, but not with the Kok-Cc method. This discrepancy was attributed to the unaccounted changes in Cc in the former methods. We found that the Kok and Kok-Phi methods underestimate RL and overestimate the inhibition of respiration under low irradiance conditions of the Kok curve, and the inhibition of RL was only 6%, representing 26% of the apparent Kok effect. We found no significant long-term CO2 effect on RL/RDk, originating from a concurrent reduction in RL and RDk at elevated growth [CO2], and likely mediated by acclimation of nitrogen metabolism.