Genotoxic and Cytotoxic Studies of Beta-Sitosterol and Pteropodine in Mouse

Beta-sitosterol (BS) and pteropodine (PT) are constituents of various plants with pharmacological activities potentially useful to man. The chemicals themselves possess biomedical properties related to the modulation of the immune and the nervous systems, as well as to the inflammatory process. Therefore, safety evaluation of the compounds is necessary in regard to their probable beneficial use in human health. The present study evaluates their genotoxic and cytotoxic potential by determining the capacity of the compounds to induce sister chromatid exchanges (SCE), or to alter cellular proliferation kinetics (CPK) and the mitotic index (MI) in mouse bone marrow cells. Besides, it also determines their capacity to increase the rate of micronucleated polychromatic erythrocytes (MNPE) in peripheral mouse blood, and the relationship polychromatic erythrocytes/normochromatic erythrocytes (PE/NE) as an index of cytotoxicity. For the first assay, four doses of each compound were tested: 200, 400, 600, and 1000 mg/kg in case of BS, and 100, 200, 300, and 600 mg/kg for PT. The results in regard to both agents showed no SCE increase induced by any of the tested doses, as well as no alteration in the CPK, or in the MI. With respect to the second assay, the results obtained with the two agents were also negative for both the MNPE and the PE/NE index along the daily evaluation made for four days. In the present study, the highest tested dose corresponded to 80% of the LD(50) obtained for BS and to 78% in the case of PT. The results obtained establish that the studied agents have neither genotoxic nor cytotoxic effect on the model used, and therefore they encourage studies on their pharmacological properties

Drivers of column-average CO_2 variability at Southern Hemispheric Total Carbon Column Observing Network sites

We investigate factors that drive the variability in total column CO_2 at the Total Carbon Column Observing Network sites in the Southern Hemisphere using fluxes tagged by process and by source region from the CarbonTracker analysed product as well as the Simple Biosphere model. We show that the terrestrial biosphere is the largest driver of variability in the Southern Hemisphere column CO_2. However, it does not dominate in the same fashion as in the Northern Hemisphere. Local- and hemispheric-scale biomass burning can also play an important role, particularly at the tropical site, Darwin. The magnitude of seasonal variability in the column-average dry-air mole fraction of CO_2, X_CO_2, is also much smaller in the Southern Hemisphere and comparable in magnitude to the annual increase. Comparison of measurements to the model simulations highlights that there is some discrepancy between the two time series, especially in the early part of the Darwin data record. We show that this mismatch is most likely due to erroneously estimated local fluxes in the Australian tropical region, which are associated with enhanced photosynthesis caused by early rainfall during the tropical monsoon season

Using XCO₂ retrievals for assessing the long-term consistency of NDACC/FTIR data sets

Within the NDACC (Network for the Detection of Atmospheric Composition Change), more than 20 FTIR (Fourier-transform infrared) spectrometers, spread worldwide, provide long-term data records of many atmospheric trace gases. We present a method that uses measured and modelled XCO2 for assessing the consistency of these NDACC data records. Our XCO2 retrieval setup is kept simple so that it can easily be adopted for any NDACC/FTIR-like measurement made since the late 1950s. By a comparison to coincident TCCON (Total Carbon Column Observing Network) measurements, we empirically demonstrate the useful quality of this suggested NDACC XCO2 product (empirically obtained scatter between TCCON and NDACC is about 4‰ for daily mean as well as monthly mean comparisons, and the bias is 25‰). Our XCO2 model is a simple regression model fitted to CarbonTracker results and the Mauna Loa CO2 in situ records. A comparison to TCCON data suggests an uncertainty of the model for monthly mean data of below 3‰. We apply the method to the NDACC/FTIR spectra that are used within the project MUSICA (multi-platform remote sensing of isotopologues for investigating the cycle of atmospheric water) and demonstrate that there is a good consistency for these globally representative set of spectra measured since 1996: the scatter between the modelled and measured XCO2 on a yearly time scale is only 3‰

Comparison of XH₂O retrieved from GOSAT short-wavelength infrared spectra with observations from the TCCON network

Understanding the atmospheric distribution of water (H$_{2}$O) is crucial for global warming studies and climate change mitigation. In this context, reliable satellite data are extremely valuable for their global and continuous coverage, once their quality has been assessed. Short-wavelength infrared spectra are acquired by the Thermal And Near-infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS) aboard the Greenhouse gases Observing Satellite (GOSAT). From these, column-averaged dry-air mole fractions of carbon dioxide, methane and water vapor (XH$_{2}$O) have been retrieved at the National Institute for Environmental Studies (NIES, Japan) and are available as a Level 2 research product. We compare the NIES XH$_{2}$O data, Version 02.21, with retrievals from the ground-based Total Carbon Column Observing Network (TCCON, Version GGG2014). The datasets are in good overall agreement, with GOSAT data showing a slight global low bias of -3.1%± 17.7%, reasonable consistency over different locations (station bias of -3.1%±9.5%) and very good correlation with TCCON (R = 0.95). We identified two potential sources of discrepancy between the NIES and TCCON retrievals over land. While the TCCON XH$_{2}$O amounts can reach 6000–6500ppm when the atmospheric water content is high, the correlated NIES values do not exceed 5500 ppm. This could be due to a dry bias of TANSO-FTS in situations of high humidity and aerosol content. We also determined that the GOSAT-TCCON differences directly depend on the altitude difference between the TANSO-FTS footprint and the TCCON site. Further analysis will account for these biases, but the NIES V02.21 XH$_{2}$O product, after public release, can already be useful for water cycle studies

An unprecedented arctic ozone depletion event during spring 2020 and its impacts across Europe

The response of the ozone column across Europe to the extreme 2020 Arctic ozone depletion was examined by analyzing ground-based observations at 38 European stations. The ozone decrease at the northernmost site, Ny-Ålesund (79°N) was about 43% with respect to a climatology of more than 30 years. The magnitude of the decrease declined by about 0.7% deg−1 moving south to reach nearly 15% at 40°N. In addition, it was found that the variations of the ozone column at each of the selected stations in March-May were similar to those observed at Ny-Ålesund but with a delay increasing to about 20 days at mid-latitudes with a gradient of approximately 0.5 days deg−1. The distributions of reconstructed ozone column anomalies over a sector covering a large European area show decreasing ozone that started from the north at the beginning of April 2020 and spread south. Such behavior was shown to be similar to that observed after the Arctic ozone depletion in 2011. Stratospheric dynamical patterns in March–May 2011 and during 2020 suggested that the migration of ozone-poor air masses from polar areas to the south after the vortex breakup caused the observed ozone responses. A brief survey of the ozone mass mixing ratios at three stratospheric levels showed the exceptional strength of the 2020 episode. Despite the stronger and longer-lasting Arctic ozone loss in 2020, the analysis in this work indicates a similar ozone response at latitudes below 50°N to both 2011 and 2020 phenomena

Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm

Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO2 (XCO2) for the roughly 100&thinsp;000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25&thinsp;%, is required in order to accurately infer carbon sources and sinks from XCO2, significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20&thinsp;% over land and 40&thinsp;% over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand.</p

Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) XCO2_{CO_{2}} measurements with TCCON

NASA\u27s Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dry-air mole fraction, X$_{CO_{2}}$, in the Earth\u27s atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and X$_{CO_{2}}$ from OCO-2\u27s primary ground-based validation network: the Total Carbon Column Observing Network (TCCON). The OCO-2 X$_{CO_{2}}$ retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 X$_{CO_{2}}$ data quality throughout its mission