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The Geostationary Carbon Cycle Observatory (GeoCarb) was selected as NASA's second Earth Venture Mission (EVM-2). The scientific objectives of GeoCarb were to advance our knowledge of the carbon cycle, in particular, land–atmosphere fluxes of the greenhouse gases carbon dioxide (CO2) and methane (CH4) and the effects of these fluxes on the Earth's radiation budget. GeoCarb would retrieve column-integrated dry-air mole fractions of CO2 (XCO2), CH4 (XCH4) and CO (XCO), important for understanding tropospheric chemistry), in addition to solar-induced fluorescence (SIF), from hyperspectral resolution measurements in the O2 A-band at 0.76 µm, the weak CO2 band at 1.6 µm, the strong CO2 band at 2.06 µm, and a CH4/CO band at 2.32 µm. Unlike its predecessors (OCO-2/3, GOSAT-1/2, TROPOMI), GeoCarb would be in a geostationary orbit with a sub-satellite point centered over the Americas. This orbital configuration combined with its high-spatial-resolution imaging capabilities would provide an unprecedented view of these quantities on spatial and temporal scales accurate enough to resolve sources and sinks to improve land–atmosphere CO2 and CH4 flux calculations and reduce the uncertainty of these fluxes. This paper will present a description of the GeoCarb instrument and the L2 retrieval algorithms which will be followed by simulation experiments to determine an error budget for each target gas. Several sources of uncertainty will be explored, including that from the instrument calibration parameters for radiometric gain, the instrument line shape (ILS), the polarization, and the geolocation pointing, in addition to forward model parameters including meteorology and spectroscopy, although there are some other instrument-related sources of uncertainty that are left out for this study, including that from “smile”, the keystone effect, stray light, detector persistence, and scene inhomogeneity. The results indicate that the errors (1σ) are less than the instrument's multi-sounding precision requirements of 1.2 ppm, 10 ppb, and 12 ppb (10 %), for XCO2, XCH4, and XCO, respectively. In particular, when considering the sources of uncertainty separately and in combination (all sources included), we find overall RMSEs of 1.06 ppm for XCO2, 8.2 ppb for XCH4, and 2.5 ppb for XCO, respectively. Additionally, we find that, as expected, errors in XCO2 and XCH4 are dominated by forward model and other systematic errors, while errors in XCO are dominated by measurement noise. It is important to note that the GeoCarb mission was canceled by NASA; however, the instrument is still in development and will be delivered to NASA, in full, with the hope that it will eventually be adopted in a future mission proposal.

Many forest cover maps have been generated by using optical and/or microwave images, but these forest cover maps have large area and spatial discrepancies. To date, few studies have assessed forest cover maps in terms of two biophysical parameters used in forest definition: canopy height and canopy coverage. We generated annual forest cover maps from 2007 to 2010 and evergreen forest cover maps from 2000 to 2021 in the Brazilian Amazon using the images from the Phased Array type L-band Synthetic Aperture Radar and the time series images from the Moderate Resolution Imaging Spectroradiometer, using the forest definition of the Food and Agriculture Organization of the United Nations (>5 m tree height and >10 % canopy coverage) as the reference. We used the canopy height and canopy coverage datasets from the Geoscience Laser Altimeter System during 2003–2007 to assess annual forest cover maps from 2007 to 2010 and annual evergreen forest cover maps from 2003 to 2007, and the results show high accuracy of these forest cover and evergreen forest cover maps. These annual forest cover maps and annual evergreen forest cover maps provide data support for the analyses of the causes, processes, and consequences of forest cover changes in the Brazilian Amazon (https://doi.org/10.6084/m9.figshare.21445626; Qin and Xiao, 2022a; https://doi.org/10.6084/m9.figshare.21445590; Qin and Xiao, 2022b).

The observing strategy of the Geostationary Carbon Observatory (GeoCarb), which is a “step and stare” approach, can lead to distortions in the instrument spectral response function (ISRF) when there are gradients in brightness across instrument field of view. These distortions induce errors in the retrieved trace gases. In order to minimize these errors, the GeoCarb instrument design was modified to include a “slit homogenizer” whose purpose is to scramble the pattern of the incoming light and effectively remove the ISRF distortions caused by the variations in illumination across the slit. As a risk reduction, GeoCarb procured six different homogenizers and had them tested for performance in a benchtop optical system. The major finding is that the homogenizer performance depends strongly on the polarization of the incoming light, with the sensitivity growing as a function of wavelength. The width of the ISRF is substantially smaller when the light is vertically polarized (orthogonal to the slit length) compared to horizontally polarized (parallel to the slit length), and the throughput is accordingly reduced. These effects are due to the effects of the gold coating and high incidence angles present in the GeoCarb homogenizer design, which was verified using a polarization-dependent model generalized from previous homogenizer modeling work. The results strongly recommend controlling the polarization of the light entering a similar implementation using a polarizer, depolarizer, or polarization scrambler for other instruments attempting to mitigate scene illumination non-uniformity effects, as well as a robust characterization of the polarization sensitivity of all key subsystems.

Column mixing ratio of carbon dioxide (CO2) data alone do not provide enough information for source attribution. Carbon monoxide (CO) is a product of inefficient combustion often co-emitted with CO2. CO data can then provide a powerful constraint on fire emissions, supporting more accurate estimation of biospheric CO2 fluxes. In this framework and using the chemistry transport model TM5, a CO inversion using Measurements of Pollution in The Troposphere (MOPITT) v8 data is performed to estimate fire emissions which are then converted into CO2 fire emissions (called FIREMo) through the use of the emission ratio. These optimized CO2 fire emissions are used to rebalance the CO2 net ecosystem exchange (NEEMo) and respiration (RhMo) with the global CO2 growth rate. Subsequently, in a second step, these rebalanced fluxes are used as priors for a CO2 inversion to derive the NEE and ocean fluxes constrained either by the Orbiting Carbon Observatory 2 (OCO-2) v9 or by in situ (IS) CO2 data. For comparison purpose, we also balanced the respiration using fire emissions from the Global Fire Emissions Database (GFED) version 3 (GFED3) and version 4.1s (GFED4.1s). We hence study the impact of CO fire emissions in our CO2 inversions at global, latitudinal, and regional scales over the period 2015–2018 and compare our results to the two other similar approaches using GFED3 (FIRE3) and GFED4.1s (FIRE4) fires, as well as with an inversion using both Carnegie–Ames–Stanford Approach (CASA)-GFED3 NEE and GFED3 fire priors (priorCMS). After comparison at the different scales, the inversions are evaluated against Total Carbon Column Observing Network (TCCON) data. Comparison of the flux estimates shows that at the global scale posterior net flux estimates are more robust than the different prior flux estimates. However, at the regional scale, we can observe differences in fire emissions among the priors, resulting in differences among the NEE prior emissions. The derived NEE prior emissions are rebalanced in concert with the fires. Consequently, the differences observed in the NEE posterior emissions are a result of the balancing with fires and the constraints provided by CO2 observations. Tropical net flux estimates from in situ inversions are highly sensitive to the prior flux assumed, of which fires are a significant component. Slightly larger net CO2 sources are derived with posterior fire emissions using either FIRE4 or FIREMo in the OCO-2 inversion, in particular for most tropical regions during the 2015 El Niño year. Similarly, larger net CO2 sources are also derived with posterior fire emissions in the in situ data inversion for Tropical Asia. Evaluation with CO2 TCCON data shows lower biases with the three rebalanced priors than with the prior using CASA-GFED3. However, posteriors have average bias and scatter very close each other, making it difficult to conclude which simulation performs better than the other. We observe that the assimilated CO2 data have a strong influence on the global net fluxes among the different inversions. Inversions using OCO-2 (or IS) data have similar emissions, mostly as a result of the observational constraints and to a lesser extent because of the fire prior used. But results in the tropical regions suggest net flux sensitivity to the fire prior for both the IS and OCO-2 inversions. Further work is needed to improve prior fluxes in tropical regions where fires are a significant component. Finally, even if the inversions using the FIREMo prior did enhance the biases over some TCCON sites, it is not the case for the majority of TCCON sites. This study consequently pushes forward the development of a CO–CO2 joint inversion with multi-observations for a possible stronger constraint on posterior CO2 fire and biospheric emissions.

Wind-driven upwelling is an important control on surface nutrients and water properties in stratified lakes and seas. In this study, a high-resolution biophysical coupled model is used to investigate upwelling in the Strait of Georgia on the Canadian Pacific coast. The model is forced with surface winds from a high-resolution atmospheric forecast and has been tuned in previous studies to reproduce extensive observations of water level, temperature, salinity, nutrients and chlorophyll with competitive skill relative to similar models of the study region. A total of 5 years of hourly surface nitrate and temperature fields are analyzed in order to characterize the dominant upwelling patterns of the basin. A prevailing along-axis wind pattern steered by mountainous topography produces episodic upwelling along the western shore during the spring and fall southeasterlies and along the eastern shore during the summer northwesterlies, as indicated by positive nitrate anomalies. Principal component analysis reveals that these cross-axis upwelling patterns account for nearly one-third of the surface nitrate variance during the summer productive season. By contrast, nearly half of the surface temperature variance over the same period is dominated by a single, combined mixing and diurnal heating–cooling pattern. The principal components associated with these patterns correlate with along-axis wind stress in a manner consistent with these physical interpretations. The cross-axis upwelling response to wind is similar to other dynamically wide basins where the baroclinic Rossby deformation radius is smaller than the basin width. However, the nitrate anomaly during upwelling along the eastern shore is stronger in the northern basin, which may be indicative of an along-axis pycnocline tilt or an effect of the background along-axis stratification gradient due to the Fraser River. Our findings highlight an important spatiotemporal consideration for future ecosystem monitoring.

Here Arndt et al. establish rotating-crystal magneto-optical detection (RMOD) as a near-point-of-care diagnostic tool for malaria detection and report a sensitivity and specificity of 82% and 84%, respectively, as validated by analyzing a clinical population in a high transmission setting in Papua New Guinea.

The Geostationary Carbon Cycle Observatory (GeoCarb) will make measurements of greenhouse gases over the contiguous North and South American landmasses at daily temporal resolution. The extreme flexibility of observing from geostationary orbit induces an optimization problem, as operators must choose what to observe and when. The proposed scanning strategy for the GeoCarb mission tracks the sun's path from east to west and covers the entire area of interest in five coherent regions in the order of tropical South America east, tropical South America west, temperate South America, tropical North America, and temperate North America. We express this problem in terms of a geometric set cover problem, and use an incremental optimization (IO) algorithm to create a scanning strategy that minimizes expected error as a function of the signal-to-noise ratio (SNR). The IO algorithm used in this studied is a modified greedy algorithm that selects, incrementally at 5 min intervals, the scanning areas with the highest predicted SNR with respect to air mass factor (AF) and solar zenith angle (SZA) while also considering operational constraints to minimize overlapping scans and observations over water. As a proof of concept, two experiments are performed applying the IO algorithm offline to create an SNR-optimized strategy and compare it to the proposed strategy. The first experiment considers all landmasses with equal importance and the second experiment illustrates a temporary campaign mode that gives major urban areas greater importance weighting. Using a simple instrument model, we found that there is a significant performance increase with respect to overall predicted error when comparing the algorithm-selected scanning strategies to the proposed scanning strategy.

Abstract The pteropod Limacina helicina frequently experiences seasonal exposure to corrosive conditions (Ωar

The development of ultrafast gas electron diffraction with nonrelativistic electrons has enabled the determination of molecular structures with atomic spatial resolution. It has, however, been challenging to break the picosecond temporal resolution barrier and achieve the goal that has long been envisioned—making space- and-time resolved molecular movies of chemical reaction in the gas-phase. Recently, an ultrafast electron diffraction (UED) apparatus using mega-electron-volt (MeV) electrons was developed at the SLAC National Accelerator Laboratory for imaging ultrafast structural dynamics of molecules in the gas phase. The SLAC gas-phase MeV UED has achieved 65 fs root mean square temporal resolution, 0.63 Å spatial resolution, and 0.22 Å−1 reciprocal-space resolution. Such high spatial-temporal resolution has enabled the capturing of real-time molecular movies of fundamental photochemical mechanisms, such as chemical bond breaking, ring opening, and a nuclear wave packet crossing a conical intersection. In this paper, the design that enables the high spatial-temporal resolution of the SLAC gas phase MeV UED is presented. The compact design of the differential pump section of the SLAC gas phase MeV UED realized five orders-of-magnitude vacuum isolation between the electron source and gas sample chamber. The spatial resolution, temporal resolution, and long-term stability of the apparatus are systematically characterized.

The purpose of this study was to describe the normal ocular anatomy and establish reference values for ophthalmic tests in the Barbary sheep or aoudad (Ammotragus lervia). Aoudad eyes are large and laterally positioned in the head with several specialized anatomic features attributed to evolutionary adaptations for grazing. Normal values for commonly used ophthalmic tests were established, Schirmer tear test (STT) - 27.22 ± 3.6 mm/min; Predominant ocular surface bacterial microbiota - Staphylococcus sp.; Corneal esthesiometry- 1.3 ± 0.4 cm; Intraocular pressure by rebound tonometry- 19.47 ± 3.9 mmHg; Corneal thickness- 630.07 ± 20.67 μm, B-mode ultrasonography of the globe- axial eye globe length 29.94 ± 0.96 mm, anterior chamber depth 5.03 ± 0.17 mm, lens thickness 9.4 ± 0.33 mm, vitreous chamber depth 14.1 ± 0.53 mm; Corneal diameter- horizontal corneal diameter 25.05 ± 2.18 mm, vertical corneal diameter 17.95 ± 1.68 mm; Horizontal palpebral fissure length- 34.8 ± 3.12 mm. Knowledge of these normal anatomic variations, biometric findings and normal parameters for ocular diagnostic tests may assist veterinary ophthalmologists in the diagnosis of ocular diseases in this and other similar species.

Remotely sensed observations of atmospheric composition require an estimate of surface pressure. This estimate can either come from an instrument with sensitivity in an O2 absorption feature in the spectrum, or it can be provided by a numerical weather prediction (NWP) model. In this work, the authors outline an information-based methodology for setting measurement requirements for an active lidar measurement of O2 in the context of the Active Sensing of Carbon Emissions over Nights, Days and Seasons (ASCENDS) mission. The results indicate that the impacts of correlations in the environmentally induced vertical weighting function errors between CO2 and O2 measurements are nontrivial and that the choice of CO2 and O2 wavelengths can lead to a stricter or looser requirement than that of surface pressure considerations alone, which would indicate about a 0.1 % precision for 1mb accuracy. Furthermore, the less sensitive the CO2 measurement is to surface pressure errors, the more difficult it will be for an O2 observation to provide a useful measurement.

The interaction of metals and biological materials is of interest for reasons such as metal recovery, toxicity and production of high-value products such as gold and platinum nanoparticles. Understanding the way in which metals interact with the biomass surface and intracellular components provides insights into the biosorption and bioaccumulation processes and increases the potential for process optimisation. Three technologies are available for the qualitative visualisation of metal - biomass interactions in South Africa, namely, micro-PIXE, transmission electron microscopy and scanning electron microscopy coupled with energy-dispersive analysis of X-rays. Each technique provides unique information and has specific shortcomings which should be taken into account when selecting the appropriate technology. This paper focuses on evaluating the various techniques.