Flux Observer Research Articles

Multi-scale temporal variation in CH4 and CO2 exchange and associated biophysical controls from two wetlands in Northeast China

Quantifying net CO2 exchange (NEE) and CH4 emissions of northern wetlands and their responses to biophysical controls are central to understanding the role of wetlands in global climate change. This study presents two growing seasons of observations of CO2 and CH4 fluxes by eddy covariance technique from a permafrost peatland and an inundated marsh in northeast China. Wavelet analysis was used to explore the temporal multi-scale variations of NEE and CH4 fluxes and their biophysical controls. NEE showed prominent variations at the diel and the seasonal scales. However, most CH4 variance was distributed at time scales longer than one day. At the permafrost peatland wavelet analysis revealed strong spectral coherency and alternating coherence between soil temperature and CH4 fluxes during the spring and summer seasons and between thaw depth and CH4 fluxes in the late growing season, with the suggestion of an as yet unknown coherence at longer timescales than could be resolved with just growing season records. At the marsh, soil temperature and CH4 flux showed strong spectral coherency throughout the growing seasons and gross ecosystem production (GEP) additionally imposed its influence on CH4 mainly during the most active part of the growing season.The growing season average CH4 emission from the peatland (0.7 g CCH4 m−2) was quite small and was negligible compared to its growing season NEE (−74.2 g CCO2). In contrast, the growing season CH4 emission from the marsh (average 31.1 g CCH4 m−2) was considerably higher and accounted for about 16.2 % of its NEE (−191.7 g CCO2 m−2). Although the two wetlands were net carbon sinks during the growing seasons and the permafrost peatland had a negative radiative forcing (i.e., cooling effect), the high CH4 emissions from the marsh resulted in a net positive radiative forcing (i.e., warming effect). To understand the function of northern wetlands in the global carbon cycle, continuous field observations of these greenhouse gases are vital.

Performance Improvement of Nonlinear Flux Observer for Sensorless Control of PMSM

The effectiveness of nonlinear flux observer has been validated in practical application. However, it is not easy to tune the gradient search gain. The observer is sensitive to the parameter variation and also the stability can be greatly affected by the gradient search gain. This paper proposes an improved nonlinear flux observer to enhance the performance. The proposed method utilizes the gradient search for both magnitude and phase of the rotor, which changes the error dynamic equations. Further, it brings the benefits of smaller estimation error and quicker dynamic responses, since the convergence path is more reasonable. In addition, it has the advantages of better steady-state performance, robustness against parameter variation and stronger stability against larger observer gain value. By comparisons of simulations and experiments, the superiority is demonstrated.

Flux Observer Based on Enhanced Second-Order Generalized Integrator With Limit Cycle Oscillator for Sensorless PMSM Drives

Flux Observer Based on Enhanced Second-Order Generalized Integrator With Limit Cycle Oscillator for Sensorless PMSM Drives

Speed-Sensorless Control of Induction Motor Drives With a STA-FLL Speed Estimation Scheme

Speed-sensorless control (SSC) techniques enhance the overall reliability while reducing the cost, and thus become attractive in induction motors (IMs). Simplicity and flexibility are the main features that make phase-locked loop (PLL)- and frequency-locked loop (FLL)-based speed estimation schemes stand out among considerable estimation methods. However, many PLL and FLL schemes exhibit a poor estimation accuracy in the cases of acceleration and deceleration (AaD). Accordingly, an adaptive second-order generalized integrator-FLL (SOGI-FLL)-based scheme is introduced. While, the issue of the estimated speed feedback (ESF) in the adaptive SOGI-FLL scheme remains an obstacle. With the above, a speed estimation scheme that combines the super-twisting algorithm with an FLL (STA-FLL) is proposed for the SSC of IM drives in this paper. In the proposed STA-FLL scheme, an STA-based quadrature signal generator (STA-QSG) is properly designed, in which the ESF is cancelled to further ensure speed estimation. Moreover, a closed-loop flux observer is adopted in the implementation to enhance the proposed STA-FLL scheme in terms of disturbance mitigation. Experimental tests are performed to validate the proposed STA-FLL scheme.

Intra-annual carbon fluxes and resource use efficiency of subtropical urban forests: insights from Chongming Island ecological observatory

Understanding the carbon budget within cities is crucial in the context of carbon peaking and carbon neutrality. This study investigates the carbon source-sink dynamics of urban forest ecosystems using carbon flux observations from the Chongming Island Ecological Observatory in Shanghai. The study aims to reveal the intra-annual variations of carbon fluxes and explore the changes in resource use efficiency of urban forest ecosystems within the framework of the big-leaf model. The results reveal distinct patterns in temperature (Tair), relative humidity (RH), radiation, and vapor pressure deficit (VPD). Diurnal cycles of net ecosystem exchange (NEE), gross primary production (GPP), and ecosystem respiration (Reco) exhibit seasonal variations, with higher amplitudes observed from April to September. The observed forest ecosystem acts as a moderate carbon sink (318.47 gC m−2 year−1), with the highest carbon uptake occurring in May and the highest carbon emission in February. During the growing season, the total carbon sink was 225.37 gC m−2, composed of GPP 1337.01 gC m−2 and Reco 1111.64 gC m−2. Water-use efficiency (WUE) and light-use efficiency (LUE) exhibit seasonal variations, while carbon-use efficiency (CUE) declines after May. These findings contribute to our understanding of urban forest carbon dynamics and their potential role in carbon management strategies.

A new, global optical sediment trap calibration

AbstractAutonomous sensors for gravitational carbon flux in the ocean are critically needed, because of uncertainties in the projected response of the biological carbon pump (BCP) to climate change, and the proposed, engineered acceleration of the BCP to sequester carbon dioxide in the ocean. Optical sediment trap (OST) sensors directly sense fluxes of sinking particles in a manner that is independent of, and complementary to, other autonomous, sensor‐derived estimates of BCP fluxes. However, limited intercalibrations of OSTs with traditional sediment traps and uncharacterized, potential biases have limited their broad adoption. A global field data set spanning three orders of magnitude in carbon flux was compiled and used to develop empirical models predicting particulate organic carbon flux from OST observations, and intercalibrating different sensor designs. These data provided valuable constraints on the uncertainty in the predicted carbon flux and showed a quantitative, theoretically consistent relationship between observations from OSTs with collimated and diffuse optical geometries. While not designed for this purpose, commercial beam transmissometers have been used as OSTs, so two models were developed quantifying the biases arising from the transmissometer's housing geometry and optical beam diameter. Finally, an algorithm for the quality control of beam transmissometer‐derived OST data was optimized using sensitivity tests. The results of this study support the expansion of OST‐based gravitational carbon flux measurements and provide a framework for interpretation of OST measurements alongside other gravitational particle flux observations. These findings also suggest key features that should be included in designs of future, purpose‐built OST sensors.

Non-linear correlations exist between solar-induced chlorophyll fluorescence and canopy photosynthesis in a subtropical evergreen forest in Southwest China

Solar-induced fluorescence (SIF) provides an exciting opportunity for quantifying terrestrial gross primary production (GPP); however, little attention has been paid to subtropical evergreen forests. Previous research has predominantly concentrated on the linear relationship between SIF and GPP, while more recent studies have gradually reported non-linear relationships and aimed to uncover the underlying mechanism. A year-long synergistic observation of tower-based fluorescence and carbon flux was conducted in the subtropical forest of Southwest China. The SIF and GPP generally exhibited comparable dynamic patterns in subtropical evergreen forests at different scales. However, SIF peaked earlier than GPP in 30-min, daily, and monthly scales. Strongly non-linear relationships existed between SIF and GPP on both 30-min (R2 = 0.42) and daily (R2 = 0.51) scales, which could also extend to different seasons and weather conditions. In particular, the SIF-GPP relationship was stronger on cloudy days than on sunny days, whereas the relationship gradually decoupled as the vapor pressure deficit (VPD) rose. These findings can help to better understand the relationship between canopy-level SIF and GPP in subtropical evergreen forests and emphasize how environmental controls affect the SIF-GPP relationship.

Climate-shaped vegetation dominated the spatial pattern of the Bowen ratio over terrestrial ecosystems in China

The Bowen ratio (β), which is the ratio of sensible heat (H) to latent heat (LE), reflects the energy balance and partitioning processes among soil, vegetation, and the atmosphere. Although the spatial patterns of β have been clearly delineated, the importance of vegetation in the spatial variation of β is frequently underestimated. Revealing the spatial patterns of β would improve the understanding of the variation in energy partitioning in terrestrial ecosystems and its reciprocal relationship with environmental change. Here, we calculated β by integrating H and LE flux values from 80 flux observation sites based on the eddy-covariance method in ChinaFLUX to analyze the spatial pattern and mechanism of β in China. Terrestrial ecosystems in China had an average β of 0.64 ± 0.47. β varied significantly among ecosystem types. Deserts had the highest β (2.08 ± 0.17), while wetlands had the lowest β (0.37 ± 0.11). The β values of terrestrial ecosystems exhibited a significant latitudinal pattern, increasing linearly with latitude. This pattern also existed in forest and cropland ecosystems. The spatial pattern of β was dominated by climate-shaped vegetation factors, including leaf area index (LAI) and fractional vegetation cover (FVC). Nevertheless, as water and thermal conditions decline, the contribution of vegetation factors gradually wanes. These findings demonstrated the spatial variations and driving mechanisms of terrestrial ecosystem β and provided insights into the mitigation of future climate change by vegetation.

Copper Catalysis-Based Amperometric Microsensors for Carbon Dioxide Monitoring.

A fast response microsensor that can detect the distribution of CO2 at the microscale level is essential for the observation of biophysiological activity, carbon flux, and carbon burial. Inspired by the previous success of Cu catalysis, we attempted to use this metal Cu material to develop an amperometric microsensor that can meet the requirements. Specifically, the ambient gases diffuse through a silicone membrane into a trap casing filled with an acidic CrCl2 solution, where the otherwise interfering O2 interferent is removed by a redox with Cr2+. The gases then diffuse through a second silicone membrane into an electrolyte, where CO2 is selectively reduced to methanol (CH3OH) at a Cu cathode through a carbon monoxide (CO) pathway. Due to the use of Cu catalysis at the WE tip, CO2 can be reduced at a less negative polarization (-470 mV) instead of the previously reported -1200 mV, thus avoiding hydrogen-evolution interference due to water from the byproduct or from water diffusion through the silicone membrane. This moderate polarization results in a stable baseline, making the microsensor suitable for long-term monitoring. Interferences from other gases, such as N2O, which may be of much concern in environmental monitoring, can be ignored. Applications and limitations are also discussed with a view to further improvement in the future.

A Compact Particle Detector for Space-Based Applications: Development of a Low-Energy Module (LEM) for the NUSES Space Mission

NUSES is a planned space mission aiming to test new observational and technological approaches related to the study of relatively low-energy cosmic rays, gamma rays, and high-energy astrophysical neutrinos. Two scientific payloads will be hosted onboard the NUSES space mission: Terzina and Zirè. Terzina will be an optical telescope readout by SiPM arrays, for the detection and study of Cerenkov light emitted by Extensive Air Showers generated by high-energy cosmic rays and neutrinos in the atmosphere. Zirè will focus on the detection of protons and electrons up to a few hundred MeV and to 0.1–10 MeV photons and will include the Low Energy Module (LEM). The LEM will be a particle spectrometer devoted to the observation of fluxes of relatively low-energy electrons in the 0.1–7-MeV range and protons in the 3–50 MeV range along the Low Earth Orbit (LEO) followed by the hosting platform. The detection of Particle Bursts (PBs) in this Physics channel of interest could give new insight into the understanding of complex phenomena such as eventual correlations between seismic events or volcanic activity with the collective motion of particles in the plasma populating van Allen belts. With its compact sizes and limited acceptance, the LEM will allow the exploration of hostile environments such as the South Atlantic Anomaly (SAA) and the inner Van Allen Belt, in which the anticipated electron fluxes are on the order of 106 to 107 electrons per square centimeter per steradian per second. Concerning the vast literature of space-based particle spectrometers, the innovative aspect of the LEM resides in its compactness, within 10 × 10 × 10 cm3, and in its “active collimation” approach dealing with the problem of multiple scattering at these very relatively low energies. In this work, the geometry of the detector, its detection concept, its operation modes, and the hardware adopted will be presented. Some preliminary results from the Monte Carlo simulation (Geant4) will be shown.

Impacts of heat and drought on the dynamics of water fluxes in a temperate deciduous forest from 2012 to 2020

Temperate deciduous forests play a significant role in the regional and global water cycles. However, climate change and associated extreme weather events are affecting the growth, water use, and survival of these forests. This study examined nine years of water flux measurements made using the eddy covariance (EC) technique in a temperate deciduous forest in eastern North America from 2012 to 2020 and assessed the impacts of heat and drought events on forest evapotranspiration (ET) and water use efficiency (WUE). Study results showed that the highest annual evapotranspiration (ET) of 521 mm yr−1 was observed in 2020, while the lowest annual ET of 359 mm yr−1 was recorded in 2014. Photosynthetically active radiation (PAR, lmg = 0.33) and air temperature (Tair, lmg = 0.33) were the primary drivers of ET, while vapor pressure deficit (VPD, lmg = 0.41) was the primary regulator of WUE. Over the nine-year study period, observed mean annual ET and precipitation (P) values were 367 ± 40 mm yr−1 and 1148 ± 262 mm yr−1, respectively, while mean annual P-ET value was 729 ± 272 mm yr−1. Annual ET accounted for 38% of P over the study period. Mean growing season WUE, which is an indicator of water utilization by the forest for growth and carbon assimilation, was 3.8 ± 0.4 g C Kg H2O−1, with the highest WUE of 4.4 g C Kg H2O−1 observed in 2014 (cool year), and the lowest values of 3.0 and 3.1 g C Kg H2O−1observed in 2012 (hot-dry year) and 2020 (dry year), respectively. We found an increasing trend in WUE values from 2012 to 2014 and then a decreasing trend from 2015 to 2020, when every year experienced extreme weather conditions (e.g. hot, dry or hot-dry), except 2019. This long-term flux observation study will help to enhance our understanding of water exchanges and water use in temperate deciduous forests in Eastern North America and develop strategies for managing forest water resources and ensuring water security in the region in changing climate.

Induction motor torque closed-loop vector control system based on flux observation and harmonic current suppression

As for the torque control system of induction motors, there are generally two technical problems. One is the torque feedback error caused by the low accuracy of the flux observer, and the other is the torque ripple caused by insufficient harmonic current suppression. In order to provide accurate electromagnetic torque feedback information, an improved voltage and current hybrid model-based flux observer is designed, which improves the effectiveness of flux observation and the accuracy of electromagnetic torque feedback. Furthermore, an improved quasi-resonant linear active disturbance rejection-based current loop control method is proposed to suppress the harmonic current and reduce the torque ripple. And the disturbance observation characteristics, parameter influence, and self-stability of the control system are analyzed based on the frequency domain method. Finally, to verify the effectiveness of the proposed method, simulation, and physical experiments are designed in this paper. The experimental results show that the proposed method can effectively reduce the flux observation error and the current harmonic component, and thus greatly improve the torque tracking control performance.

An Improved Method of Permanent-magnet Flux Observer for Interior Permanent Magnet Synchronous Motor Based on Adaptive Theory

Permanent magnet synchronous motor is often used as drive motors for electric vehicles. It is prone to demagnetization failure, and the change of permanent magnet flux link is an important basis for diagnosing demagnetization failure of the motor. First, the study establishes a permanent magnet flux adaptive observer and ensures its stability. Then the sensitivity analysis of the main parameters in the observer is carried out. For the parameter with high sensitivity and a large range of variation during motor operation, the expression of flux observation error caused by this parameter change is derived, and the gain matrix in the observation model is optimized. Through simulation verification, the observer can be used for the demagnetization fault diagnosis of the motor.

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET‐CH4 Sites Using Wavelet Analyses

AbstractProcess‐based land surface models are important tools for estimating global wetland methane (CH4) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site‐level patterns of freshwater wetland CH4 fluxes (FCH4) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model‐observation disagreements are mainly at multi‐day time scales (<15 days); (b) most of the models can capture the CH4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH4 production). Our evaluation suggests the need to accurately replicate FCH4 variability, especially at short time scales, in future wetland CH4 model developments.

Dynamics of carbon budget and meteorological factors of a typical maize ecosystem in Songnen Plain, China

Aim of study: Understanding the carbon budget and meteorological factor impacts of farmland ecosystems is helpful for scientific assessment of carbon budget and low-carbon agricultural production practices. Area of study: The Songnen Plain, NE China, in 2019. Material and methods: Based on eddy-related flux and soil heterotrophic respiration observations from a typical maize farmland ecosystem, using mathematical statistics and carbon balance equation methods, were analyzed. Main results: Soil respiration rate (Rs) and composition were influenced and controlled by the synergistic effect of surface soil temperature (Ts) and water content (Wcs). Ts played a leading role, while Wcs played an important role. Ts and Wcs had the greatest influence on the heterotrophic respiration rate (Rh), followed by Rs and autotrophic respiration rate (Ra). Daily variations of net ecosystem productivity were correlated with daily mean air temperature, latent heat flux, and sensible heat flux. Annual carbon revenue was 1139.67 g C m-2, annual carbon expenditure was 456.14 g C m-2, and annual carbon budget was -683.53 g C m-2 in 2019. While considering that maize grain yield (-353.44 g C m-2) was moved out of the field at harvest, the net ecosystem carbon balance was -330.09 g C m-2; then it was carbon sink in 2019. By fully utilizing climate resources and improving agricultural managements, carbon sink is increased in farmland ecosystems. Research highlights: Soil respiration rate and composition were influenced and controlled by the synergistic effect of soil temperature and water content; the maize farmland ecosystem is carbon sink.

Simultaneous NICER and NuSTAR Observations of the Ultracompact X-Ray Binary 4U 0614+091

We present the first joint NuSTAR and NICER observations of the ultracompact X-ray binary 4U 0614+091. This source shows quasiperiodic flux variations on the timescale of ∼days. We use reflection modeling techniques to study various components of the accretion system as the flux varies. We find that the flux of the reflected emission and the thermal components representing the disk and the compact object trend closely with the overall flux. However, the flux of the power-law component representing the illuminating X-ray corona scales in the opposite direction, increasing as the total flux decreases. During the lowest flux observation, we see evidence of accretion disk truncation from roughly 6 gravitational radii to 11.5 gravitational radii. This is potentially analogous to the truncation seen in black hole low-mass X-ray binaries, which tends to occur during the low/hard state at sufficiently low Eddington ratios.

Management practices regulate the response of canopy and ecosystem water use efficiency in cropland ecosystems

ContextWith rising global temperature and frequent drought events, water resource supply is facing to great challenge. Understanding the effects of different management practices on cropland water use efficiency (WUE) is crucial to promote effective allocation of water resources and food security. ObjectiveThe objective of this study was to reveal the contrasting effects of different farm management practices including continuous and rotational, tillage and no-till, irrigated and rainfed on cropland water use efficiency from canopy (WUET) to ecosystem (WUEET) scales, respectively. MethodsOn the basis of 26 site-years eddy covariance-based carbon and water flux observations, this study used the underlying WUE (uWUE) model to partition evapotranspiration (ET) across maize and soybean ecosystems. Three control groups were used to compare the effects of different management practices on the coupling relationships between terrestrial carbon and water cycles, respectively. ResultsCompared with the rotational maize-soybean site, both WUET and WUEET at the continuous maize site were larger, which was mainly ascribed to stronger gross primary productivity (GPP) for the C4 crop. But over the maize-planting years, both WUET and WUEET at the rotational site were higher than the continuous site owing to the nitrogen fixation by rhizobia for preceding year, especially for WUET. Under conventional tillage and no-till management, multi-year mean WUEET and WUET were contrasting. WUEET under no-till was apparently larger than WUEET under till, because of similar GPP but relatively lower ET. Meanwhile, more water was consumed by crop transpiration (T) under no-till, which led to lower WUET in comparison with WUET under till. In comparison with the rainfed farming, GPP, ET and T all increased apparently after irrigation. However, both WUET and WUEET at the irrigated site were not improved owing to more water lost with relatively fewer GPP increase. ConclusionsThe study suggested that the crop rotation system can improve both WUEET and WUET apparently. Meanwhile, fewer water resource was consumed by cropland under no-till management. Finally, irrigation farming improved the cropland GPP but reduced WUEET and WUET. ImplicationsOur results provide valuable management implications for understanding the mechanisms that can enhance water use efficiency and result in significant water savings and high yield.

Comprehensive evaluation of terrestrial evapotranspiration from different models under extreme condition over conterminous United States

Terrestrial evapotranspiration (ET) is a key process in the water, energy, and carbon cycles. ET products are becoming more widely accessible with the development of remotely sensed inversions and availability of land surface assimilation information. However, the response of these products to extreme weather is not yet clear and challenging to evaluate. This study evaluated and compared the consistency and uncertainty of nine evaporation products (including GLEAM3.6b, reliability ensemble averaging (REA), CLSM, ERA5-Land (ERA5), MOD16A2, PML-V2 (PML), NOAH, FLDAS, and Synthesized (Syn)) for the period 2003–2015. Eddy covariance (EC) flux observations and the three-cornered hat (TCH) method were used to validate and assess the uncertainty of these products at both the point-scale and grid-scale under normal climatic conditions. More importantly, we conducted uncertainty assessments of ET products at daily and monthly scales under extreme climatic conditions (including high temperature (Temp), high vapor pressure deficit (VPD), and drought), referencing 50 EC measurements over the conterminous United States (COUNS). The results showed that the accuracy of different ET products varied with cover type. Compared to other products, GLEAM3.6b, REA, and Syn showed superior results for most land cover types. Specifically, GLEAM3.6b showed higher performance for the grasslands; REA showed improved performance in mixed forests, open shrubs, and wetlands, and Syn fared better in forests and croplands. The point-scale indicated that the lowest root mean square deviations (RMSD) come from Syn grid products (mean 16.13 mm/month), followed by GLEAM3.6b (mean 18.53 mm/month) and REA (mean 19.42 mm/month). The highest RMSD (mean 49.49 mm/month) originated from ERA5, while the lowest R was found in MOD16A2. The uncertainty ranking calculated using the TCH method is similar to the findings of the point-scale evaluation based on EC measurements, with Syn recording the lowest uncertainty of 5.13 mm/month, after GLEAM3.6b (5.72 mm/month), followed by REA (6.24 mm/month), and ERA5 (12.26 mm/month) with the largest uncertainty. When extreme weather conditions were encountered, the uncertainty of the nine ET products showed an increasing trend, and their consistency varied. Under high-temperature and high-VPD conditions, the consistency decreased, while during drought, the consistency showed a slight increase. Among the ET products, GLEAM3.6b performed best under high-temperature and high-VPD conditions, closely followed by REA. However, ERA5 exhibited the largest error in its estimations. On the other hand, when drought conditions occurred, GLEAM3.6b, REA, and Syn showed better performance, while CLSM, NOAH, and FLDAS ranked second, ERA5 had the largest uncertainty, and MOD16A2 and PML exhibited the worst consistency. The findings of this study offer a foundation for selecting appropriate ET products for hydrologic analysis and agricultural water resource management in the CONUS and give developers suggestions for lowering the uncertainty of ET products in the face of extreme climatic conditions.

Drought-induced resource use efficiency responses in an alpine meadow ecosystem of northern Tibet

Drought is a threat universally faced by global terrestrial ecosystems under global climate change. The habitat of alpine ecosystems is harsh, and they necessitate to use the limited resources efficiently to survive. However, drought occurred frequently during the short growing season, which greatly affected their resource use efficiency (RUE). In this study, based on long-term flux and microclimate observations in a typical alpine meadow ecosystem in northern Tibet, the effects of drought on RUE, including water use efficiency (WUE), light use efficiency (LUE), and carbon use efficiency (CUE), were studied. The results indicate that droughts could change the driving paths of abiotic and biotic factors on carbon and water fluxes and hence affect RUE. When vegetation exhibits robust physiological activity, droughts could enhance the control effects of biotic factors. The droughts that occurred at different periods of the growing season showed divergent effects on RUE. In the early-growing season, the strong photosynthetic capacity of the nascent leaves facilitated enhancements in WUE and LUE in response to drought conditions. However, the CUE did not increase significantly due to the heightened consumption of organic matter by respiration. The mid-growing season droughts led to a sharp decrease in gross primary productivity (GPP), consequently leading to a decline in WUE, LUE and CUE. During the late-growing season, droughts together with the decomposition of chlorophyll reduced the photosynthetic capacity and led to a significant decrease in LUE. The diminished physiological activity of the senescent leaves led to insensitive responses of WUE and CUE to droughts. These findings indicate that RUE might primarily be regulated by factors affecting GPP rather than others. This study would be beneficial for assessing the responses and adaptation characteristics of alpine meadow ecosystems to future climate change and could help accurately predict their possible evolution trends.

Volatile organic compound fluxes in the agricultural San Joaquin Valley – spatial distribution, source attribution, and inventory comparison

Abstract. The San Joaquin Valley is an agricultural region in California that suffers from poor air quality. Since traffic emissions are decreasing, other sources of volatile organic compounds (VOCs) are gaining importance in the formation of secondary air pollutants. Using airborne eddy covariance, we conducted direct, spatially resolved flux observations of a wide range of VOCs in the San Joaquin Valley during June 2021 at 23–36 ∘C. Through land-cover-informed footprint disaggregation, we were able to attribute emissions to sources and identify tracers for distinct source types. VOC mass fluxes were dominated by alcohols, mainly from dairy farms, while oak isoprene and citrus monoterpenes were important sources of reactivity. Comparisons with two commonly used inventories showed that isoprene emissions in the croplands were overestimated, while dairy and highway VOC emissions were generally underestimated in the inventories, and important citrus and biofuel VOC point sources were missing from the inventories. This study thus presents unprecedented insights into the VOC sources in an intensive agricultural region and provides much needed information for the improvement of inventories, air quality predictions, and regulations.