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The Mapocho River's upper basin (Chilean Central Andes) was studied as a proxy of a high-mountainous hydrothermally-altered (HMHA) system comprised by three sub-basins developed over very different rocks and submitted to different anthropic pressure: 1) a natural acid rock drainage (i.e., Yerba Loca), 2) a creek with mining activity in its headwaters and hydrochemically classified as non-affected by acid mine drainage (i.e., San Francisco), and 3) a low metal concentration creek (i.e., Molina). In general terms, the geochemical composition of the clastic sediments was consistent with the geochemistry inferred from the mineralogical study. However, sediments with a smaller grain size showed higher concentrations than the bigger grain size counterparts for elements such as Fe, S, Cu and As. This behavior was particularly evident in the Yerba Loca basin and it was attributed to the seasonal appearance of Fe- and Al-rich precipitates as constituents of the finer sediments. Different methodologies for the calculation of geochemical backgrounds (Tukey's inner fence, TIF; Median + 2*Median Absolute Deviation, MAD; and 95th percentile) were tested. Results suggest that the 95th percentile-method was the most appropriate for this type of mountainous systems. Using the selected methodology, three different geochemical backgrounds were calculated: 1) Yerba Loca basin, 2) Molina basin, and 3) Mapocho Upper basin. When the generated background levels were compared with the Consensus-Based (CB) Sediment Quality Guidelines; Fe, Mn, Zn, Pb, Cu, Cr, Ni and As showed background values that were consistently higher than the values set by the CB Threshold Effect Concentration and, even higher than the CB Probable Effect Concentration for Fe (MUB Background : 6.78 wt% vs CB PEC: 4.00 wt%; and Cu (MUB Bacground : 3387 mg kg -1 vs CB PEC: 149 mg kg -1 ). The present study clearly states the paramount importance of having a solid geochemical background before any attempt of a sediment risk assessment is made at HMHA regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

After several decades' development of retrieval techniques in aerosol remote sensing, no fast and accurate analytical Radiative Transfer Model (RTM) has been developed and applied to create global aerosol products for non-polarimetric instruments such as Ocean and Land Colour Instrument/Sentinel-3 (OLCI/Sentinel-3) and Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager (MSG/SEVIRI). Global aerosol retrieval algorithms are typically based on a Look-Up-Table (LUT) technique, requiring high-performance computers. The current eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm also utilizes the LUT method. In order to have a near-real time retrieval and achieve a quick and accurate "FIRST-LOOK" aerosol product without high-demand of computing resource, we have developed a Fast and Accurate Semi-analytical Model of Atmosphere-surface Reflectance (FASMAR) for aerosol remote sensing. The FASMAR is developed based on a successive order of scattering technique. In FASMAR, the first three orders of scattering are calculated exactly. The contribution of higher orders of scattering is estimated using an extrapolation technique and an additional correction function. The evaluation of FASMAR has been performed by comparing with radiative transfer model SCIATRAN for all typical observation/illumination geometries, surface/aerosol conditions, and wavelengths 412, 550, 670, 870, 1600, 2100 nm used for aerosol remote sensing. The selected observation/illumination conditions are based on the observations from both geostationary satellite (e.g. MSG/SEVIRI) and polar-orbit satellite (e.g. OLCI/Sentinel-3). The percentage error of the top of atmosphere reflectance calculated by FASMAR is within  ± 3% for typical polar-orbit/geostationary satellites' observation/illumination geometries. The accuracy decreases for solar and viewing zenith angles larger than 70 ∘ . However, even in such cases, the error is within the range  ± 5%. The evaluation of model performance also shows that FASMAR can be used for all typical surfaces with albedo in the interval [ 0 - 1 ] and aerosol with optical thickness in the range [ 0.01 - 1 ] ., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2020 Elsevier Ltd. All rights reserved.)

We investigate the distribution of volatile organic compounds (VOCs) over Indian subcontinent during a winter month of January 2011 combining the regional model WRF-Chem (Weather Research and Forecasting model coupled with Chemistry) with ground- and space-based observations and chemical reanalysis. WRF-Chem simulated VOCs are found to be comparable with ground-based observations over contrasting environments of the Indian subcontinent. WRF-Chem results reveal the elevated levels of VOCs (e. g. propane) over the Indo-Gangetic Plain (16 ppbv), followed by the Northeast region (9.1 ppbv) in comparison with other parts of the Indian subcontinent (1.3-8.2 ppbv). Higher relative abundances of propane (27-31%) and ethane (13-17%) are simulated across the Indian subcontinent. WRF-Chem simulated formaldehyde and glyoxal show the western coast, Eastern India and the Indo-Gangetic Plain as the regional hotspots, in a qualitative agreement with the MACC (Monitoring Atmospheric Composition and Climate) reanalysis and satellite-based observations. Lower values of R GF (ratio of glyoxal to formaldehyde <0.04) suggest dominant influences of the anthropogenic emissions on the distribution of VOCs over Indian subcontinent, except the northeastern region where higher R GF (∼0.06) indicates the role of biogenic emissions, in addition to anthropogenic emissions. Analysis of HCHO/NO 2 ratio shows a NO x -limited ozone production over India, with a NO x -to-VOC transition regime over central India and IGP. The study highlights a need to initiate in situ observations of VOCs over regional hotspots (Northeast, Central India, and the western coast) based on WRF-Chem results, where different satellite-based observations differ significantly., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Underwater light field characterization is of importance for understanding biogeochemical processes and heat budget of the global oceans, which are impacting and reacting to climate change. Vibrational Raman Scattering (VRS) was retrieved from backscattered radiances measured by three different hyperspectral satellite sensors, SCIAMACHY, GOME-2, and OMI, using Differential Optical Absorption Spectroscopy (DOAS). Diffuse attenuation coefficient (Kd) in the blue spectral range (390 to 426 nm) was derived from the VRS signal via a look-up-table established through ocean-atmosphere coupled radiative transfer modeling. We processed one year of data, representative of the overlapping period of optimal operation for all three sensors. Resulting data sets were evaluated by comparison with Kd at 490 nm from Ocean Colour Climate Change Initiative (OC-CCI) which was first converted to Kd at 390 to 426 nm. Good agreement with the OC-CCI Kd product was achieved for all three sensors when Kd was limited to below 0.15 m -1 . Differences among the hyperspectral sensors and to OC-CCI were attributed to particular instrumental effects on the DOAS retrieval leading to temporal and spatial biases. This is in addition to the fact that the spatial and temporal resolution of the hyperspectral sensors data differ among themselves and are much lower then for the OC-CCI Kd-product. Further corrections (e.g., empirical) are necessary before these data sets can be merged in order to obtain a long-term Kd product for the blue spectral range.

Currently, modeling studies tend to significantly underestimate observed space-based glyoxal (CHOCHO) vertical column densities (VCDs), implying the existence of missing sources of glyoxal. Several recent studies suggest that the emissions of aromatic compounds and molar yields of glyoxal in the chemical mechanisms may both be underestimated, which can affect the simulated glyoxal concentrations. In this study, the influences of these two factors on glyoxal amounts over China were investigated using the RAMS-CMAQ modeling system for January and July 2014. Four sensitivity simulations were performed, and the results were compared to satellite observations. These results demonstrated significant impacts on glyoxal concentrations from these two factors. In case 1, where the emissions of aromatic compounds were increased three-fold, improvements to glyoxal VCDs were seen in high anthropogenic emissions regions. In case 2, where molar yields of glyoxal from isoprene were increased five-fold, the resulted concentrations in July were 3-5-fold higher, achieving closer agreement between the modeled and measured glyoxal VCDs. The combined changes from both cases 1 and 2 were applied in case 3, and the model succeeded in further reducing the underestimations of glyoxal VCDs. However, the results over most of the regions with pronounced anthropogenic emissions were still underestimated. So the molar yields of glyoxal from anthropogenic precursors were considered in case 4. With these additional mole yield changes (a two-fold increase), the improved concentrations agreed better with the measurements in regions of the lower reaches of the Yangtze River and Yellow River in January but not in July., (Copyright © 2018. Published by Elsevier B.V.)

The MEdium Resolution Imaging Spectrometer (MERIS) instrument on board ESA Envisat made measurements from 2002 to 2012. Although MERIS was limited in spectral coverage, accurate Aerosol Optical Thickness (AOT) from MERIS data are retrieved by using appropriate additional information. We introduce a new AOT retrieval algorithm for MERIS over land surfaces, referred to as eXtensible Bremen AErosol Retrieval (XBAER). XBAER is similar to the "dark-target" (DT) retrieval algorithm used for Moderate-resolution Imaging Spectroradiometer (MODIS), in that it uses a lookup table (LUT) to match to satellite-observed reflectance and derive the AOT. Instead of a global parameterization of surface spectral reflectance, XBAER uses a set of spectral coefficients to prescribe surface properties. In this manner, XBAER is not limited to dark surfaces (vegetation) and retrieves AOT over bright surface (desert, semiarid, and urban areas). Preliminary validation of the MERIS-derived AOT and the ground-based Aerosol Robotic Network (AERONET) measurements yield good agreement, the resulting regression equation is y = (0.92 × ± 0.07) + (0.05 ± 0.01) and Pearson correlation coefficient of R = 0.78. Global monthly means of AOT have been compared from XBAER, MODIS and other satellite-derived datasets.

The SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) aboard the Envisat satellite provided measurements from August 2002 until April 2012. SCIAMACHY measured the scattered or direct sunlight using different observation geometries. The limb viewing geometry allows the retrieval of water vapour at about 10-25 km height from the near-infrared spectral range (1353-1410 nm). These data cover the upper troposphere and lower stratosphere (UTLS), a region in the atmosphere which is of special interest for a variety of dynamical and chemical processes as well as for the radiative forcing. Here, the latest data version of water vapour (V3.01) from SCIAMACHY limb measurements is presented and validated by comparisons with data sets from other satellite and in situ measurements. Considering retrieval tests and the results of these comparisons, the V3.01 data are reliable from about 11 to 23 km and the best results are found in the middle of the profiles between about 14 and 20 km. Above 20 km in the extra tropics V3.01 is drier than all other data sets. Additionally, for altitudes above about 19 km, the vertical resolution of the retrieved profile is not sufficient to resolve signals with a short vertical structure like the tape recorder. Below 14 km, SCIAMACHY water vapour V3.01 is wetter than most collocated data sets, but the high variability of water vapour in the troposphere complicates the comparison. For 14-20 km height, the expected errors from the retrieval and simulations and the mean differences to collocated data sets are usually smaller than 10 % when the resolution of the SCIAMACHY data is taken into account. In general, the temporal changes agree well with collocated data sets except for the Northern Hemisphere extratropical stratosphere, where larger differences are observed. This indicates a possible drift in V3.01 most probably caused by the incomplete treatment of volcanic aerosols in the retrieval. In all other regions a good temporal stability is shown. In the tropical stratosphere an increase in water vapour is found between 2002 and 2012, which is in agreement with other satellite data sets for overlapping time periods.