Parallel adjustments in vegetation greenness and ecosystem CO2 exchange in response to drought in a Southern California chaparral ecosystem

Some form of the light use efficiency (LUE) model is used in most models of ecosystem carbon exchange based on remote sensing. The strong relationship between the normalized difference vegetation index (NDVI) and light absorbed by green vegetation make models based on LUE attractive in the remote sensing context. However, estimation of LUE has proven problematic since it varies with vegetation type and environmental conditions. Here we propose that LUE may in fact be correlated with vegetation greenness (measured either as NDVI at constant solar elevation angle, or a red edge chlorophyll index), making separate estimates of LUE unnecessary, at least for some vegetation types. To test this, we installed an automated tram system for measurement of spectral reflectance in the footprint of an eddy covariance flux system in the Southern California chaparral. This allowed us to match the spatial and temporal scales of the reflectance and flux measurements and thus to make direct comparisons over time scales ranging from minutes to years. The 3-year period of this study included both “normal” precipitation years and an extreme drought in 2002. In this sparse chaparral vegetation, diurnal and seasonal changes in solar angle resulted in large variation in NDVI independent of the actual quantity of green vegetation. In fact, one would come to entirely different conclusions about seasonal changes in vegetation greenness depending on whether NDVI at noon or NDVI at constant solar elevation angle were used. Although chaparral vegetation is generally considered “evergreen”, we found that the majority of the shrubs were actually semi-deciduous, leading to large seasonal changes in NDVI at constant solar elevation angle. LUE was correlated with both greenness indices at the seasonal timescale across all years. In contrast, the relationship between LUE and PRI was inconsistent. PRI was well correlated with LUE during the “normal” years but this relationship changed dramatically during the extreme drought. Contrary to expectations, none of the spectral reflectance indices showed consistent relationships with CO₂ flux or LUE over the diurnal time-course, possibly because of confounding effects of sun angle and stand structure on reflectance. These results suggest that greenness indices can be used to directly estimate CO₂ exchange at weekly timescales in this chaparral ecosystem, even in the face of changes in LUE. Greenness indices are unlikely to be as good predictors of CO₂ exchange in dense evergreen vegetation as they were in the sparse, semi-deciduous chaparral. However, since relatively few ecosystems are entirely evergreen at large spatial scales or over long time spans due to disturbance, these relationships need to be examined across a wider range of vegetation types.     

MODIS spectral signals at a flux tower site: Relationships with high-resolution data, and CO2 flux and light use efficiency measurements

In this study, spectral indices were calculated from single date HyMap (3 m; 126 bands), Hyperion (30 m; 242 bands), ASTER (15/30 m; 9 bands), and a time series of MODIS nadir BRDF-adjusted reflectance (NBAR; 1 km, 7 bands) for a study area surrounding the Tumbarumba flux tower site in eastern Australia. The study involved: a) the calculation of a range of physiologically-based vegetation indices from ASTER, HyMap, Hyperion and MOD43B NBAR imagery over the flux tower site; b) comparison across scales between HyMap, Hyperion and MODIS for the normalized difference water index (NDWI) and the Red-Green ratio; c) analysis of relationships between tower-based flux and light use efficiency (LUE) measurements and seasonal and climatic constraints on growth; and d) examination of relationships between fluxes, LUE and time series of NDVI, NDWI and Red-Green ratio. Strong seasonal patterns of variation were observed in NDWI and Red/Green ratio from MODIS NBAR. Correlations between fine (3 and 30 m) and coarse (1 km) scale indices for a small region around the flux tower site were moderately good for Red/Green ratio, but poor for NDWI. Hymap NDWI values for the understorey canopy were much lower than values for the tree canopy. MODIS NDWI was negatively correlated with CO₂ fluxes during warm and cool seasons. The correlation indicated that surface reflectance, affected by a spectrally bright grassland understorey canopy, was decoupled from growth of trees with access to deep soil moisture. The application of physiologically-based indices at earth observation scale requires careful attention to applicability of band configurations, contribution of vegetation components to reflectance signals, mechanistic relationships between biochemical processes and spectral indexes, and incorporation of ancillary information into any analysis.     

Development of SAW-based multi-gas sensor for simultaneous detection of CO2 and NO2

A 440 MHz wireless and passive surface acoustic wave (SAW)-based multi-gas sensor integrated with a temperature sensor was developed on a 41° YX LiNbO₃ piezoelectric substrate for the simultaneous detection of CO₂, NO₂, and temperature. The developed sensor was composed of a SAW reflective delay lines structured by an interdigital transducer (IDT), ten reflectors, a CO₂ sensitive film (Teflon AF 2400), and a NO₂ sensitive film (indium tin oxide). Teflon AF 2400 was used for the CO₂ sensitive film because it provides a high CO₂ solubility, with good permeability and selectivity. For the NO₂ sensitive film, indium tin oxide (ITO) was used. Coupling of mode (COM) modeling was conducted to determine the optimal device parameters prior to fabrication. Using the parameters determined by the simulation results, the device was fabricated and then wirelessly measured using a network analyzer. The measured reflective coefficient S₁₁ in the time domain showed high signal/noise (S/N) ratio, small signal attenuation, and few spurious peaks. The time positions of the reflection peaks were well matched with the predicted values from the simulation. High sensitivity and selectivity were observed at each target gas testing. The obtained sensitivity was 2.12°/ppm for CO₂ and 51.5°/ppm for NO₂, respectively. With the integrated temperature sensor, temperature compensation was also performed during gas sensitivity evaluation process.     

Normalized difference spectral indices for estimating photosynthetic efficiency and capacity at a canopy scale derived from hyperspectral and CO2 flux measurements in rice

We explored simple and useful spectral indices for estimating photosynthetic variables (radiation use efficiency and photosynthetic capacity) at a canopy scale based on seasonal measurements of hyperspectral reflectance, ecosystem CO₂ flux, and plant and micrometeorological variables. An experimental study was conducted over the simple and homogenous ecosystem of an irrigated rice field. Photosynthetically active radiation absorbed by the canopy (APAR), the canopy absorptivity of APAR (fAPAR), net ecosystem exchange of CO₂ (NEE_CO2) gross primary productivity (GPP), photosynthetic capacity at the saturating APAR (P_max), and three parameters of radiation use efficiency (ε_N: NEE_CO2/APAR; ε_G: GPP/APAR; φ: quantum efficiency) were derived from the data set. Based on the statistical analysis of relationships between these ecophysiological variables and reflectance indicators such as normalized difference spectral indices (NDSI[i,j]) using all combinations of two wavelengths (i and j nm), we found several new indices that would were more effective than conventional spectral indices such as photochemical reflectance index (PRI) and normalized difference vegetation index (NDVI = NDSI[near-infrared, red]). ε_G was correlated well with NDSI[710, 410], NDSI[710, 520], and NDSI[530, 550] derived from nadir measurements. φ was best correlated with NDSI[450, 1330]. NDSI[550, 410] and NDSI[720, 420] had a consistent linear relationships with fAPAR throughout the growing season, whereas conventional indices such as NDVI showed very different relationships before and after heading. Off-nadir measurements were more closely related to the efficiency parameters than nadir measurements. Our results provide useful insights for assessing plant productivity and ecosystem CO₂ exchange, using a wide range of available spectral data as well as useful information for designing future sensors for ecosystem observations.     

Sea-air flux of CO2 in the Caribbean Sea estimated using in situ and remote sensing data

Empirical relationships between sea surface carbon dioxide fugacity (fCO₂^sw) and sea surface temperature (SST) were applied to datasets of remotely sensed SST to create fCO₂^sw fields in the Caribbean Sea. SST datasets from different sensors were used, as well as the SST fields created by optimum interpolation of bias corrected AVHRR data. Empirical relationships were derived using shipboard fCO₂^sw data, in situ SST data, and SST data from the remote sensing platforms. The results show that the application of a relationship based on shipboard SST data, on fields of remotely sensed SST yields biased fCO₂^sw values. This bias is reduced if the fCO₂^sw-SST relationships are derived using the same SST data that are used to create the SST fields. The fCO₂^sw fields found to best reproduce observed fCO₂^sw are used in combination with wind speed data from QuikSCAT to create weekly maps of the sea-air CO₂ flux in the Caribbean Sea in 2002. The region to the SW of Cuba was a source of CO₂ to the atmosphere throughout 2002, and the region to the NE was a sink during winter and spring and a source during summer and fall. The net uptake of CO₂ in the region was doubled when potential skin layer effects on fCO₂^sw were taken into account.     

APL and FORTRAN programs for a new equation of state for H2O,CO2, and their mixtures at supercritical conditions

APL and FORTRAN programs utilizing a new modified hard-sphere Redlich-Kwong equation calculate volumes and fugacity coefficients for pure H₂O and CO₂, and activities in H₂O-CO₂ mixtures, throughout most of the crustal and upper mantle P?T conditions. The new modification allows the term of the equation representing attractive intermolecular forces to vary as a function of both temperature and pressure, in contrast to earlier versions where this term was considered a function of temperature only. Compared with previous modified Redlich-Kwong (MRK) equations, this equation predicts thermodynamic properties for pure H₂O and CO₂ which are in better agreement with those derived from experimental P?V?T data. These programs are versatile and can be incorporated into existing routines which calculate mixed-volatile (H₂O–CO₂) phase equilibria for petrologic systems.     

考虑CO2排放量的能量枢纽运行配置优化

多能源系统通过电、热、气等不同形式能源在生产、传输、消费等多个环节进行协同优化为解决能源与环境问题提供了新方案.能量枢纽(EH)作为多能源系统的耦合环节,其配置方案对多能源系统的优化运行至关重要.在此背景下,本文提出了一种考虑CO2排放量的含电力、热能、天然气等不同形式能源的能量枢纽优化运行配置方案.在考虑CO2排放量的基础上,提出一个多目标优化问题,并采用遗传算法(GA)求解整体优化问题,从而实现社会效益最大化,CO2排放量最小化的目标.最后通过不同配置算例的分析比较验证所提方法的有效性,为能量枢纽的建设和运行提供理论和技术支撑.     

Ground and space spectral measurements for assessing the semi-arid ecosystem phenology related to CO2 fluxes of biological soil crusts

This paper reports on ranges of carbon dioxide (CO₂) activity in biological soil crusts (BSC) correlated with different ranges of the BSC's spectral reflectance throughout the phenological cycle of the year. Methodology is based on surface CO₂ exchange measurements, ground spectral measurements, and satellite images interpretation. Thirty-nine field campaigns, each of duration of 3 days, were conducted over the course of 2 years at a sand dunes and a loess environment of the northwestern Negev desert in Israel, in order to relate the CO₂ fluxes and the spectral signals to the seasonal phenology. The Normalized Difference Vegetation Index (NDVI) was derived from ground measurements of the BSC's reflectance and correlated with their CO₂ exchange data. A linear mixture model, incorporating the different contributions of the sites' ground features, was calculated and compared with SPOT-HRV data. From the ground measurements, fairly good correlations were found between the NDVI and the CO₂ fluxes on a seasonal scale. Hence, the NDVI successfully indicates the potential magnitude and capacity of the BSC's assimilation activity. The linear mixture model successfully describes the phenological cycles of the BSC, annual, and perennial plants and corresponds well to the satellite data. Moreover, the model enables annual changes of the phenology cycle and the growing season length to be distinguished. Both the linear mixture model and the derived NDVI values recorded the recovery of the BSC at the beginning of the wet season before annuals had germinated. Finally, it is concluded that a combination of CO₂ exchange measurements, linear mixture model, and NDVI values is suitable for monitoring BSC's productivity in arid regions.     

Reflectance assessment of seasonal and annual changes in biomass and CO2 uptake of a Mediterranean shrubland submitted to experimental warming and drought

We aimed to evaluate how the remote sensing vegetation indices NDVI and PRI responded to seasonal and annual changes in an early successional stage Mediterranean coastal shrubland canopy that was submitted to experimental warming and drought simulating predicted climate change for the next decades. These conditions were obtained by using a new non-intrusive methodological approach that increases the temperature and prolongs the drought period by using roofs that automatically cover the vegetation after the sunset or when it rains. On average, warming increased air temperature by 0.7 °C and soil temperature by 1.6 °C, and the drought treatment reduced soil moisture by 22%. We measured spectral reflectance at the canopy level and at the individual plant level seasonally during 4 years. Shrubland NDVI tracked the community development and activity. In control and warming treatments, NDVI increased with the years while it did not change in the drought treatment. There was a good relationship between NDVI and both community and individual plant biomass. NDVI also decreased in summer seasons when some species dry or decolour. The NDVI of E. multiflora plant individuals was lower in autumn and winter than in the other seasons, likely because of flowering. Shrubland PRI decreased only in winter, similarly to the PRI of the most dominant species, G. alypum. At this community scale, NDVI was better related than PRI to photosynthetic activity, probably because photosynthetic fluxes followed canopy seasonal greening in this complex canopy, which includes brevideciduous, annual and evergreen species and variable morphologies and canopy coverage. PRI followed the seasonal variations in photosynthetic rates in E. multiflora and detected the decreased photosynthetic rates of drought treatment. However, PRI did not track the photosynthetic rates of G. alypum plants which have lower LAIs than E. multiflora. In this community, which is in its early successional stages, NDVI was able to track biomass, and indirectly, CO₂ uptake changes, likely because LAI values did not saturate NDVI. Thus, NDVI appears as a valid tool for remote tracking of this community development. PRI was less adequate for photosynthetic assessment of this community especially for its lower LAI canopies. PRI usefulness was also species-dependent and could also be affected by flowering. These results will help to improve the interpretation of remote sensing information on the structure and physiological status of these Mediterranean shrublands, and to gain better insight on ecological and environmental controls on their ecosystem carbon dioxide exchange. They also show the possibility of assessing the impacts of climate change on shrubland communities.     

Controller design for extending periodic dynamics of a chaotic CO2 laser

The paper considers a single-mode CO₂ laser that exhibits a cascade of period doubling bifurcations leading to chaos when it is driven by a sinusoidal signal of increasing amplitude. The requirement of a proper working of the laser, for relatively large amplitude of the forcing signal, naturally leads to the control problem of stabilizing periodic motions. Two control schemes are designed: the first one is based on delayed control signals for stabilizing unstable periodic orbits embedded in the chaotic attractor, while the second one relies on the cancellation of subharmonic components of the chaotic motions. Simulations and experimental tests are presented to show the control performance.     

Estimation of monthly air-sea CO2 flux in the southern Atlantic and Indian Ocean using in-situ and remotely sensed data

Empirical relationships between the sea surface partial pressure of carbon dioxide (pCO₂), sea surface chlorophyll-a concentration (Chl-a), and sea surface temperature (SST), were derived from shipboard pCO₂ measurements in sea water and atmosphere, in-situ Chl-a, and SST data along cruise tracks between Zhongshan Station in East Antarctica and Changcheng Station on the Antarctic Peninsula in December 1999, January 2000, December 2004 and January 2005 during the CHINARE XVI and XXI campaigns. These relationships were then applied to datasets of remotely sensed Chl-a and SST to estimate the monthly air-sea carbon flux and the uptake of atmospheric CO₂ in the southern Atlantic and Indian Ocean. The results show significant spatial and temporal variability of carbon flux in the southern Atlantic and Indian Ocean. The monthly uptakes of atmospheric CO₂ in the region from 50°S to the ice edge between 60°W and 80°E are − 0.00355 GtC, − 0.00573 GtC in December 1999 and January 2000, and − 0.00361 GtC, − 0.00525 GtC in December 2004 and January 2005, respectively.     

Nonlinear model identification and adaptive control of CO2 sequestration process in saline aquifers using artificial neural networks

In recent years, storage of carbon dioxide (CO₂) in saline aquifers has gained intensive research interest. The implementation, however, requires further research studies to ensure it is safe and secure operation. The primary objective is to secure the CO₂ which relies on a leak-proof formation. Reservoir pressure is a key aspect for assessment of the cap rock integrity. This work presents a new pressure control methodology based on a nonlinear model predictive control (NMPC) scheme to diminishing risk of carbon dioxide (CO₂) back leakage to the atmosphere due to a fail in the integrity of the formation cap rock. The CO₂ sequestration process in saline aquifers is simulated using ECLIPSE-100 as black oil reservoir simulator while the proposed control scheme is realized in MATLAB software package to prevent over-pressurization. A modified form of growing and pruning radial basis function (MGAP-RBF) neural network model is identified online for prediction of reservoir pressure behaviors. MGAP-RBF is recursively trained via extended Kalman filter (EKF) and unscented Kalman filter (UKF) algorithms. A set of miscellaneous test scenarios has been conducted using an interface program to exchange ECLIPSE and MATLAB in order to demonstrate the capabilities of the proposed methodology in guiding saline aquifer to follow some desired time-dependent pressure profiles during the CO₂ injection process.     

Global biomass mapping for an improved understanding of the CO2 balance—the Earth observation mission Carbon-3D

Understanding global climate change and developing strategies for sustainable use of our environmental resources are major scientific and political challenges. In response to an announcement of the German Aerospace Center (DLR) for a national Earth observation (EO) mission, the Friedrich-Schiller University Jena and the JenaOptronik GmbH proposed the EO mission Carbon-3D. The data products of this mission will for the first time accurately estimate aboveground biomass globally, one of the most important parameters of the carbon cycle. Simultaneous acquisition of multiangle optical with Light Detection and Ranging (LIDAR) observations is unprecedented. The optical imager extrapolates the laser-retrieved height profiles to biophysical vegetation maps. This innovative mission will reduce uncertainties about net effects of deforestation and forest regrowth on atmospheric CO₂ concentrations and will also provide key biophysical information for biosphere models.     

A workflow for handling heterogeneous 3D models with the TOUGH2 family of codes: Applications to numerical modeling of CO2 geological storage

This paper is addressed to the TOUGH2 user community. It presents a new tool for handling simulations run with the TOUGH2 code with specific application to CO₂ geological storage. This tool is composed of separate FORTRAN subroutines (or modules) that can be run independently, using input and output files in ASCII format for TOUGH2. These modules have been developed specifically for modeling of carbon dioxide geological storage and their use with TOUGH2 and the Equation of State module ECO2N, dedicated to CO₂-water-salt mixture systems, with TOUGHREACT, which is an adaptation of TOUGH2 with ECO2N and geochemical fluid-rock interactions, and with TOUGH2 and the EOS7C module dedicated to CO₂-CH₄ gas mixture is described. The objective is to save time for the pre-processing, execution and visualization of complex geometry for geological system representation. The workflow is rapid and user-friendly and future implementation to other TOUGH2 EOS modules for other contexts (e.g. nuclear waste disposal, geothermal production) is straightforward. Three examples are shown for validation: (i) leakage of CO₂ up through an abandoned well; (ii) 3D reactive transport modeling of CO₂ in a sandy aquifer formation in the Sleipner gas Field, (North Sea, Norway); and (iii) an estimation of enhanced gas recovery technology using CO₂ as the injected and stored gas to produce methane in the K12B Gas Field (North Sea, Denmark).     

Enhanced room temperature response of SnO2 thin film sensor loaded with Pt catalyst clusters under UV radiation for LPG

The room temperature response characteristics of SnO₂ thin film sensor loaded with platinum catalyst clusters are investigated for LPG under the exposure of ultraviolet radiation. The SnO₂-Pt cluster sensor structures have been prepared using rf sputtering. Combined effect of UV radiation exposure (λ = 365 nm) and presence of Pt catalyst clusters (10 nm thick) on SnO₂ thin film sensor surface is seen to lead to an enhanced response (4.4 × 10³) for the detection of LPG (200 ppm) at room temperature whereas in the absence of UV illumination a comparable response (∼5 × 10³) could be obtained but only at an elevated temperature of 220 °C. The present study therefore investigates the effect of UV illumination on LPG sensing characteristics of SnO₂ sensors loaded with Pt clusters of varying thickness values. Results indicate the possibility of utilizing the sensor structure with novel dispersal of Pt catalyst clusters on SnO₂ film surface for efficient detection of LPG at room temperature under the illumination of UV radiations.