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In 2020, a total of 66 papers were published in JKSEE. A total of 126 dedicated reviewers carefully reviewed the papers of this journal. Their constructive reviews assisted both the authors to improve the works and the editors to produce timely high-quality articles. Many reviewers answered the review request multiple times. Once a year I would like to thank these anonymous reviewers for their willingness and readiness.The Korean Society of Environmental Engineers (KSEE) has established “Reviewer Award” since 2018 and awards the best reviewer every year. The Reviewer Award of 2020 is given to Dr. Jaewook Myung (Korea Advanced Institute of Science and Technology, KAIST). I sincerely appreciate the reviewers listed below for their time and contribution.

An ability to accurately detect convective regions is essential for initializing models for short-term precipitation forecasts. Radar data are commonly used to detect convection, but radars that provide high-temporal-resolution data are mostly available over land, and the quality of the data tends to degrade over mountainous regions. On the other hand, geostationary satellite data are available nearly anywhere and in near-real time. Current operational geostationary satellites, the Geostationary Operational Environmental Satellite-16 (GOES-16) and Satellite-17, provide high-spatial- and high-temporal-resolution data but only of cloud top properties; 1 min data, however, allow us to observe convection from visible and infrared data even without vertical information of the convective system. Existing detection algorithms using visible and infrared data look for static features of convective clouds such as overshooting top or lumpy cloud top surface or cloud growth that occurs over periods of 30 min to an hour. This study represents a proof of concept that artificial intelligence (AI) is able, when given high-spatial- and high-temporal-resolution data from GOES-16, to learn physical properties of convective clouds and automate the detection process. A neural network model with convolutional layers is proposed to identify convection from the high-temporal resolution GOES-16 data. The model takes five temporal images from channel 2 (0.65 µm) and 14 (11.2 µm) as inputs and produces a map of convective regions. In order to provide products comparable to the radar products, it is trained against Multi-Radar Multi-Sensor (MRMS), which is a radar-based product that uses a rather sophisticated method to classify precipitation types. Two channels from GOES-16, each related to cloud optical depth (channel 2) and cloud top height (channel 14), are expected to best represent features of convective clouds: high reflectance, lumpy cloud top surface, and low cloud top temperature. The model has correctly learned those features of convective clouds and resulted in a reasonably low false alarm ratio (FAR) and high probability of detection (POD). However, FAR and POD can vary depending on the threshold, and a proper threshold needs to be chosen based on the purpose.

In this paper, the continuous online measurements of isoprene in the atmosphere have been carried out by using differential optical absorption spectroscopy (DOAS) in the band of 202.71–227.72 nm for the first time. Under a zero optical path in the laboratory, different equivalent concentrations of isoprene were measured by the combination of known concentrations of gas and series calibration cells. The correlation between the measured concentrations and the equivalent concentrations was 0.9995, and the slope was 1.065. The correlation coefficient between DOAS and the online volatile organic compound (VOC) instrument observed from 23 d of field observations is 0.85 with a slope of 0.86. It was estimated that the detection limit of isoprene with DOAS is approximately 0.1 ppb at an optical path of 75 m, and it was verified that isoprene could be measured in the ultraviolet absorption band using the DOAS method with high temporal resolution and a low maintenance cost.

Cloud optical properties such as optical thickness along with surface albedo are important inputs for deriving the shortwave radiative effects of clouds from spaceborne remote sensing. Owing to insufficient knowledge about the snow or ice surface in the Arctic, cloud detection and the retrieval products derived from passive remote sensing, such as from the Moderate Resolution Imaging Spectroradiometer (MODIS), are difficult to obtain with adequate accuracy – especially for low-level thin clouds, which are ubiquitous in the Arctic. This study aims at evaluating the spectral and broadband irradiance calculated from MODIS-derived cloud properties in the Arctic using aircraft measurements collected during the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE), specifically using the upwelling and downwelling shortwave spectral and broadband irradiance measured by the Solar Spectral Flux Radiometer (SSFR) and the BroadBand Radiometer system (BBR). This starts with the derivation of surface albedo from SSFR and BBR, accounting for the heterogeneous surface in the marginal ice zone (MIZ) with aircraft camera imagery, followed by subsequent intercomparisons of irradiance measurements and radiative transfer calculations in the presence of thin clouds. It ends with an attribution of any biases we found to causes, based on the spectral dependence and the variations in the measured and calculated irradiance along the flight track. The spectral surface albedo derived from the airborne radiometers is consistent with prior ground-based and airborne measurements and adequately represents the surface variability for the study region and time period. Somewhat surprisingly, the primary error in MODIS-derived irradiance fields for this study stems from undetected clouds, rather than from the retrieved cloud properties. In our case study, about 27 % of clouds remained undetected, which is attributable to clouds with an optical thickness of less than 0.5. We conclude that passive imagery has the potential to accurately predict shortwave irradiances in the region if the detection of thin clouds is improved. Of at least equal importance, however, is the need for an operational imagery-based surface albedo product for the polar regions that adequately captures its temporal, spatial, and spectral variability to estimate cloud radiative effects from spaceborne remote sensing.

This article aims to study the interest of spent coffee grounds (SCG) valorization through caffeine recovery. In an original way, this study takes into account all the parameters such as (i) the brewing coffee methods (household, coffee shops, etc.), (ii) the storage conditions, in particular the drying step, (iii) the solid/liquid extraction parameters such as the nature of solvent, the temperature, the extraction time and the solid/liquid ratio, and (iv) the liquid/liquid purification parameters such as the nature, the volume and the pH of extraction medium. Results have shown that spent coffee grounds from coffee-shops obtained by percolation contain a higher amount of caffeine than spent coffee grounds from households obtained from spent pods or filters. A drying treatment is not required when extraction is performed under one week after the spent coffee grounds collection with 96.4% of not degraded caffeine. Solid/liquid extraction performed with 25 mL.g−1SCG of hydroalcoholic solvent (water/EtOH, v/v 60/40) at 60 °C during 15 min have given a caffeine yield up to 4.67 mg.g−1SCG. When using ethyl acetate, 93.4% of the caffeine has been selectively recovered by liquid/liquid extraction. Finally, the extraction of caffeine for the valorization of spent coffee grounds is a promising and easy way, which fits with an already important and well established market.

In atmospheric chemistry retrievals and data assimilation systems, observation errors associated with satellite radiances are chosen empirically and generally treated as uncorrelated. In this work, we estimate inter-channel error covariances for the Infrared Atmospheric Sounding Interferometer (IASI) and evaluate their impact on ozone assimilation with the chemistry transport model MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle). The method used to calculate observation errors is a diagnostic based on the observation and analysis residual statistics already adopted in many numerical weather prediction centres. We used a subset of 280 channels covering the spectral range between 980 and 1100 cm−1 to estimate the observation-error covariance matrix. This spectral range includes ozone-sensitive and atmospheric window channels. We computed hourly 3D-Var analyses and compared the resulting O3 fields against ozonesondes and the measurements provided by the Microwave Limb Sounder (MLS) and by the Ozone Monitoring Instrument (OMI). The results show significant differences between using the estimated error covariance matrix with respect to the empirical diagonal matrix employed in previous studies. The validation of the analyses against independent data reports a significant improvement, especially in the tropical stratosphere. The computational cost has also been reduced when the estimated covariance matrix is employed in the assimilation system, by reducing the number of iterations needed for the minimizer to converge.

We have developed in situ and flask sampling systems for airborne measurements of variations in the O2/N2 ratio at the part per million level. We have deployed these instruments on a series of aircraft campaigns to measure the distribution of atmospheric O2 from 0–14 km and 87∘ N to 86∘ S throughout the seasonal cycle. The National Center for Atmospheric Research (NCAR) airborne oxygen instrument (AO2) uses a vacuum ultraviolet (VUV) absorption detector for O2 and also includes an infrared CO2 sensor. The VUV detector has a precision in 5 s of ±1.25 per meg (1σ) δ(O2/N2), but thermal fractionation and motion effects increase this to ±2.5–4.0 per meg when sampling ambient air in flight. The NCAR/Scripps airborne flask sampler (Medusa) collects 32 cryogenically dried air samples per flight under actively controlled flow and pressure conditions. For in situ or flask O2 measurements, fractionation and surface effects can be important at the required high levels of relative precision. We describe our sampling and measurement techniques and efforts to reduce potential biases. We also present a selection of observational results highlighting the individual and combined instrument performance. These include vertical profiles, O2:CO2 correlations, and latitudinal cross sections reflecting the distinct influences of terrestrial photosynthesis, air–sea gas exchange, burning of various fuels, and stratospheric dynamics. When present, we have corrected the flask δ(O2/N2) measurements for fractionation during sampling or analysis with the use of the concurrent δ(Ar/N2) measurements. We have also corrected the in situ δ(O2/N2) measurements for inlet fractionation and humidity effects by comparison to the corrected flask values. A comparison of Ar/N2-corrected Medusa flask δ(O2/N2) measurements to regional Scripps O2 Program station observations shows no systematic biases over 10 recent campaigns (+0.2±8.2 per meg, mean and standard deviation, n=86). For AO2, after resolving sample drying and inlet fractionation biases previously on the order of 10–100 per meg, independent AO2 δ(O2/N2) measurements over six more recent campaigns differ from coincident Medusa flask measurements by -0.3±7.2 per meg (mean and standard deviation, n=1361) with campaign-specific means ranging from −5 to +5 per meg.

The exploration of aerosol retrieval synergies from diverse combinations of ground-based passive Sun-photometric measurements with collocated active lidar ground-based and radiosonde observations using versatile Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm is presented. Several potentially fruitful aspects of observation synergy were considered. First, a set of passive and active ground-based observations collected during both day- and nighttime was inverted simultaneously under the assumption of temporal continuity of aerosol properties. Such an approach explores the complementarity of the information in different observations and results in a robust and consistent processing of all observations. For example, the interpretation of the nighttime active observations usually suffers from the lack of information about aerosol particles sizes, shapes and complex refractive index. In the realized synergy retrievals, the information propagating from the nearby Sun-photometric observations provides sufficient constraints for reliable interpretation of both day- and nighttime lidar observations. Second, the synergetic processing of such complementary observations with enhanced information content allows for optimizing the aerosol model used in the retrieval. Specifically, the external mixture of several aerosol components with predetermined sizes, shapes and composition has been identified as an efficient approach for achieving reliable retrieval of aerosol properties in several situations. This approach allows for achieving consistent and accurate aerosol retrievals from processing stand-alone advanced lidar observations with reduced information content about aerosol columnar properties. Third, the potential of synergy processing of the ground-based Sun-photometric and lidar observations, with the in situ backscatter sonde measurements was explored using the data from KAUST.15 and KAUST.16 field campaigns held at King Abdullah University of Science and Technology (KAUST) in the August of 2015 and 2016. The inclusion of radiosonde data has been demonstrated to provide significant additional constraints to validate and improve the accuracy and scope of aerosol profiling. The results of all retrieval setups used for processing both synergy and stand-alone observation data sets are discussed and intercompared., Atmospheric Measurement Techniques, 14 (3), ISSN:1867-1381, ISSN:1867-8548

We demonstrate the capability of the Sentinel-2 MultiSpectral Instrument (MSI) to detect and quantify anomalously large methane point sources with fine pixel resolution (20 m) and rapid revisit rates (2–5 d). We present three methane column retrieval methods that use shortwave infrared (SWIR) measurements from MSI spectral bands 11 (∼ 1560–1660 nm) and 12 (∼ 2090–2290 nm) to detect atmospheric methane plumes. The most successful is the multi-band–multi-pass (MBMP) method, which uses a combination of the two bands and a non-plume reference observation to retrieve methane columns. The MBMP method can quantify point sources down to about 3 t h−1 with a precision of ∼ 30 %–90 % (1σ) over favorable (quasi-homogeneous) surfaces. We applied our methods to perform high-frequency monitoring of strong methane point source plumes from a well-pad device in the Hassi Messaoud oil field of Algeria (October 2019 to August 2020, observed every 2.5 d) and from a compressor station in the Korpezhe oil and gas field of Turkmenistan (August 2015 to November 2020, observed every 5 d). The Algerian source was detected in 93 % of cloud-free scenes, with source rates ranging from 2.6 to 51.9 t h−1 (averaging 9.3 t h−1) until it was shut down by a flare lit in August 2020. The Turkmen source was detected in 40 % of cloud-free scenes, with variable intermittency and a 9-month shutdown period in March–December 2019 before it resumed; source rates ranged from 3.5 to 92.9 t h−1 (averaging 20.5 t h−1). Our source-rate retrievals for the Korpezhe point source are in close agreement with GHGSat-D satellite observations for February 2018 to January 2019, but provide much higher observation density. Our methods can be readily applied to other satellite instruments with coarse SWIR spectral bands, such as Landsat-7 and Landsat-8. High-frequency satellite-based detection of anomalous methane point sources as demonstrated here could enable prompt corrective action to help reduce global methane emissions.

The subgrid spatial variability of water vapor is an important geophysical parameter for modeling tropical convention and cloud processes in atmospheric models. This study maps sub-kilometer spatial structures in total atmospheric column water vapor with visible to shortwave infrared (VSWIR) imaging spectroscopy. We describe our inversion approach and validate its accuracy with coincident measurements by airborne imaging spectrometers and the AERONET ground-based observation network. Next, data from NASA's AVIRIS-NG spectrometer enable the highest-resolution measurement to date of water vapor's spatial variability and scaling properties. We find second-order structure function scaling exponents consistent with prior studies of convective atmospheres. Airborne lidar data show that this total column measurement provides information about variability in the lower troposphere. We conclude by discussing the implications of these measurements and paths toward future campaigns to build upon these results.

The main goal of the article is to share some experimental view onto VR training applications, that allows for adaptation of the directed training scenario to a user being trained. The resulted application allows to the three scenarios being selected in any combination of ones, as well as the tasks modification through the input files, before a test starts. The program was developed in the Unity engine, using the modern UnityXR framework providing extensive support for leading virtual reality hardware. The resulting solution presents the possibility of an efficient training in Virtual Reality while modifying the course of training without any needs to recompile the program, and also it shows some positive values of using VR technology as a didactic solution.

Magnetoelectric multiferroics are solid-state materials which exhibit a coupling between ferroelectric and magnetic orders. This phenomenon is known as the magnetoelectric (ME) effect. Multiferroic materials possess a wide range of potential applications in such fields as metrology, electronics, energy harvesting & conversion, and medicine. Multiferroic research is facing two main challenges. Firstly, scientists are continuously trying to obtain a material with sufficiently strong, room-temperature ME coupling that would enable its commercial application. Secondly, the measurement techniques used in multiferroic research are often problematic to implement in a laboratory setting and fail to yield reproducible results. The aim of the present work is to discuss three most commonly used methods in multiferroic studies; the lock-in technique, the Sawyer-Tower (S-T) circuit and dielectric constant measurements. The paper opens with a general description of multiferroics which is followed by mathematical representation of the ME effect. The main body deals with the description of the aforementioned measurement techniques. The article closes with a conclusion and outlook for future research.

The paper presents the methods for fire identification using low-resolution space images obtained from Terra Modis and NOAA satellites. There are lots of algorithms to identify potentially "fire pixels" (PF). They are based on the assessment of temperature in spectral ranges from 3.5–4 to 10.5–11.5 microns. One of the problematic aspects in the Fire Detection Method using low-resolution space images is "Cloud and Water Masking". To identify "fire pixels", it is important to exclude from the analysis fragments of images that are covered with clouds and occupied by water objects. Identification of pixels in which one or more fires are actively burning at the time of passing over the Earth is the basis of the algorithm for detecting potentially "fire pixels". The algorithm requires a significant increase in radiation in the range of 4 micrometers, as well as on the observed radiation in the range of 11 micrometers. The algorithm investigates each pixel in a scene that is assigned one of the following classes as a result: lack of data, cloud, water, potentially fire or uncertain. The pixels that lack actual data are immediately classified as "missing data (NULL)" and excluded from further consideration. Cloud and water pixels, defined by the cloud masking technique and water objects, belong to cloud and water classes, respectively. The fire detection algorithm investigates only those pixels of the Earth's surface that are classified as potentially fire or uncertain. The method was implemented using the Visual Programming Tool PowerBuilder in the data processing system of Erdas Imaging. As a result of the use of the identification method, fires in the Chornobyl exclusion zone, steppe fires and fires at gas wells were detected. Using the method of satellite fire identification is essential for the prompt detection of fires for remote forests or steppes that are poorly controlled by ground monitoring methods.

Parameters of a fire-quenching system based on explosive water-aerosol production and spreading are presented. Such a system with correctly tailored amounts of the water and the explosive material produces water-aerosol with high fire-quenching efficiency due to the small radii of the droplets and at the same time secures that shock-wave pressures are safe for the human body at distances exceeding 30 m from the explosion axis.

Short-lived highly reactive atmospheric species, such as organic peroxy radicals (RO2) and stabilized Criegee intermediates (SCIs), play an important role in controlling the oxidative removal and transformation of many natural and anthropogenic trace gases in the atmosphere. Direct speciated measurements of these components are extremely helpful for understanding their atmospheric fate and impact. We describe the development of an online method for measurements of SCIs and RO2 in laboratory experiments using chemical derivatization and spin trapping techniques combined with H3O+ and NH4+ chemical ionization mass spectrometry (CIMS). Using chemical derivatization agents with low proton affinity, such as electron-poor carbonyls, we scavenge all SCIs produced from a wide range of alkenes without depleting CIMS reagent ions. Comparison between our measurements and results from numeric modeling, using a modified version of the Master Chemical Mechanism, shows that the method can be used for the quantification of SCIs in laboratory experiments with a detection limit of 1.4×107 molecule cm−3 for an integration time of 30 s with the instrumentation used in this study. We show that spin traps are highly reactive towards atmospheric radicals and form stable adducts with them by studying the gas-phase kinetics of the reaction of spin traps with the hydroxyl radical (OH). We also demonstrate that spin trap adducts with SCIs and RO2 can be simultaneously probed and quantified under laboratory conditions with a detection limit of 1.6×108 molecule cm−3 for an integration time of 30 s for RO2 species with the instrumentation used in this study. Spin trapping prevents radical secondary reactions and cycling, ensuring that measurements are not biased by chemical interferences, and it can be implemented for detecting RO2 species in laboratory studies and potentially in the ambient atmosphere.

Methods for synthesis a structural diagram of the processes for detecting and locating technical information leakage channels are analysed. Software for defining a controlled room zone was also presented. A proprietary approach to search the electromagnetic environment under radio interference has been developed to detect devices for unauthorized control of acoustic information using microphones and transmission of this information using a radio channel.

Global navigation satellite systems (GNSS) have been proved to be an excellent technology for retrieving precipitable water vapor (PWV). In GNSS meteorology, PWV at a station is obtained from a conversion of the zenith wet delay (ZWD) of GNSS signals received at the station using a conversion factor which is a function of weighted mean temperature (Tm) along the vertical direction in the atmosphere over the site. Thus, the accuracy of Tm directly affects the quality of the GNSS-derived PWV. Currently, the Tm value at a target height level is commonly modeled using the Tm value at a specific height and a simple linear decay function, whilst the vertical nonlinear variation in Tm is neglected. This may result in large errors in the Tm result for the target height level, as the variation trend in the vertical direction of Tm may not be linear. In this research, a new global grid-based Tm empirical model with a horizontal resolution of 1∘ × 1∘ , named GGNTm, was constructed using ECMWF ERA5 monthly mean reanalysis data over the 10-year period from 2008 to 2017. A three-order polynomial function was utilized to fit the vertical nonlinear variation in Tm at the grid points, and the temporal variation in each of the four coefficients in the Tm fitting function was also modeled with the variables of the mean, annual, and semi-annual amplitudes of the 10-year time series coefficients. The performance of the new model was evaluated using its predicted Tm values in 2018 to compare with the following two references in the same year: (1) Tm from ERA5 hourly reanalysis with the horizontal resolution of 5∘ × 5∘; (2) Tm from atmospheric profiles from 428 globally distributed radiosonde stations. Compared to the first reference, the mean RMSEs of the model-predicted Tm values over all global grid points at the 950 and 500 hPa pressure levels were 3.35 and 3.94 K, respectively. Compared to the second reference, the mean bias and mean RMSE of the model-predicted Tm values over the 428 radiosonde stations at the surface level were 0.34 and 3.89 K, respectively; the mean bias and mean RMSE of the model's Tm values over all pressure levels in the height range from the surface to 10 km altitude were −0.16 and 4.20 K, respectively. The new model results were also compared with that of the GTrop and GWMT_D models in which different height correction methods were also applied. Results indicated that significant improvements made by the new model were at high-altitude pressure levels; in all five height ranges, GGNTm results were generally unbiased, and their accuracy varied little with height. The improvement in PWV brought by GGNTm was also evaluated. These results suggest that considering the vertical nonlinear variation in Tm and the temporal variation in the coefficients of the Tm model can significantly improve the accuracy of model-predicted Tm for a GNSS receiver that is located anywhere below the tropopause (assumed to be 10 km), which has significance for applications requiring real-time or near real-time PWV converted from GNSS signals.

The article considers the methods of calculating radio signal power. The main factors influencing the distribution and their connection with the error in the calculations of the indicators' peak values are analyzed. The regularities of signal propagation and the correlation between the distance from the radio signal source and the ratio of noise to useful information are determined. These patterns allow us to develop a model of artificial intelligence, which improves the prediction of results compared to existing calculation methods. The obtained results present the efficiency of the offered method.

The Orbitrap mass spectrometer has recently been proved to be a powerful instrument to accurately measure gas-phase and particle-phase organic compounds with a greater mass resolving power than other widely used online mass spectrometers in atmospheric sciences. We develop an open-source software tool (Orbitool, https://orbitrap.catalyse.cnrs.fr, last access: 4 February 2021) to facilitate the analysis of long-term online Orbitrap data. Orbitool can average long-term data while improving the mass accuracy by re-calibrating each mass spectrum, assign molecular formulae of compounds and their isotopes to measured signals, and export time series and mass defect plots. The noise reduction procedure in Orbitool can separate signal peaks from noise and reduce the computational and storage expenses. Chemical ionization Orbitrap data from laboratory experiments on ozonolysis of monoterpenes and ambient measurements in urban Shanghai were used to test Orbitool. For the test dataset, the average mass accuracy was improved from to ppm by mass calibrating each spectrum. The denoising procedure removed 97 % of the noise peaks from a spectrum averaged for 30 min while maintaining the signal peaks, substantially helping the automatic assignment of unknown species. To illustrate the capabilities of Orbitool, we used the most challenging and complex dataset we have collected so far, which consists of ambient gas-phase measurements in urban Shanghai. These tests showed that Orbitool was able to automatically assign hundreds of molecular formulae as well as their isotopes with high accuracy.

O presente trabalho teve como objetivo simular o rompimento hipotético da barragem de Jucazinho no estado de Pernambuco (Brasil). Para o desenvolvimento do estudo, foram utilizados o modelo matemático HEC-RAS 5.0.6, imagens de perfilamento a laser e dados disponíveis da barragem. Os cenários foram simulados utilizando os tempos de formação da brecha (0,1h e 0,5h), buscando avaliar os impactos sobre as ocupações ribeirinhas das cidades Salgadinho e Limoeiro. Como resultado, foi possível obter a distribuição espacial e temporal da inundação, mapas com indicadores e índices de perigo, bem como estimar a quantidade de pessoas e domicílios que podem ser atingidos. Espera-se com esse trabalho poder contribuir com os órgãos gestores na adoção de medidas estruturais e/ou não estruturais para as cidades Salgadinho e Limoeiro, caso a barragem se rompa. Palavras-chave: HEC-RAS. Perfilamento a laser. Mapa de perigo.

As ETEs desempenham papel crucial na manutenção da saúde da população. Porém, geram quantidade considerável de lodo de esgoto. Os custos relacionados ao manejo do lodo podem representar 50% dos custos operacionais da ETE. Além disso, o lodo pode ser prejudicial à saúde humana e os trabalhadores que atuam no seu manejo estão expostos a diversos riscos ocupacionais. Esta pesquisa tem como objetivo examinar a relação entre o manejo do lodo e os riscos ocupacionais associados, por meio de processos de gestão de riscos, baseados na ISO 31000, em duas ETEs de médio porte do interior paulista que utilizam tecnologias diferentes, lodos ativados convencionais e reatores anaeróbios UASB. Dentre os principais riscos ocupacionais avaliados, foram considerados críticos a exposição a microrganismos patogênicos dispersos no ar e no contato direto acidentale o risco de acionamentos acidentais de equipamentos durante a manutenção. Percebe- se que ainda há muita resistência, tanto dos trabalhadores como dos empregadores, em relação à saúde e segurança do trabalho. Muito se deve a fatores culturais e sociais, e, portanto, sempre haverá a necessidade da atualização dos instrumentos legais e intensificação da fiscalização. Além disso, é necessário promover, de forma frequente, a conscientização dos trabalhadores e, principalmente, dos empregadores, discutindo o papel dos gestores dos serviços de saneamento básico, em especial no tratamento de esgotos, no processo de desenvolvimento de cultura de segurança do trabalho nas empresas. Palavras-chave: Manejo de lodo de Esgoto. Lodo de Esgoto. Gestão de Riscos Ocupacionais. Saúde e Segurança do Trabalho. ISO 31000.

O lodo granular aeróbio (LGA) é uma promissora alternativa para o tratamento de águas residuárias municipais e industriais. Entretanto, foram relatadas dificuldades nessa nova tecnologia, como longo período de start-up, instabilidade da granulação em longo prazo e incompleta remoção de nutrientes. Além disso, o gerenciamento do lodo descartado necessita ser aprimorado. As características do Brasil, como o clima, composição do esgoto sanitário e qualificação da mão de obra, devem ser levadas em conta na adoção desse tipo de tratamento. Desse modo, este trabalho apresenta as características do LGA e os processos bioquímicos envolvidos, associando-os aos benefícios e desafios a serem superados. Uma análise comparativa entre o reator em bateladas sequenciais com lodo granular e o reator com lodo apenas floculado é apresentada, assim como algumas características do esgoto brasileiro e do sistema de LGA que podem influenciar a escolha dessa alternativa. Palavras-chave: Lodo granular aeróbio. Reator em bateladas sequenciais. Tratamento de esgoto sanitário.

Os indicadores de perdas de água nos sistemas de abastecimento são ferramentas úteis para a gestão e avaliação da sustentabilidade dos serviços de saneamento ambiental. Por meio de metodologia investigativa do tipo estudo de caso, o presente artigo analisa o potencial do Programa de Gestão e Controle da Perdas de Água (PGCP) da Sociedade de Abastecimento de Água e Saneamento S.A. de Campinas-SP como instrumento de gestão sustentável dos serviços de abastecimento. Os resultados demonstraram se tratar de um PGCP que atende grande parte das boas práticas recomendadas pela literatura especializada. Contudo, sugerem que esforços sejam direcionados ao fortalecimento da dimensão ética da sustentabilidade, notadamente influenciada pelas ações de comunicação social. Ademais, reforçam a importância de um plano de contingência para rápida atuação em casos de escassez hídrica, num contexto de cooperação setorial (entre setores usuários ou não) e governamental (de diferentes jurisdições territoriais). Palavras-chave: Programa de gestão e controle. Sustentabilidade. Serviços de saneamento.

Dentre as tecnologias disponíveis para realizar o desaguamento dos resíduos gerados no tratamento de água (RETA), a filtração em tubo geotêxtil se tornou uma opção bastante viável, sendo usada em diversas ETAs no Brasil. Entretanto, algumas dúvidas sobre certos fatores dessa tecnologia não foram totalmente abordadas na literatura, como o efeito de mudanças nas características dos RETAs no desempenho da filtração em tubo geotêxtil. Assim, o presente trabalho, por meio de ensaios de bancada em filtro pressurizado de geotêxtil, buscou responder a tais questionamentos. Os ensaios de desaguamento foram realizados com dois tipos de RETAs gerados em escala piloto a partir de fontes de água bruta com características distintas: o RETA tipo I, preparado com suspensão da argila caulinita, e o RETA tipo II, de manancial superficial com turbidez elevada. Os resultados dos ensaios de desaguamento mostraram que o tipo da água bruta teve efeito direto na eficiência de desaguamento do resíduo no tubo geotêxtil, tendo o RETA tipo II resultando em teor de sólidos após desaguamento de 15%, e o RETA tipo I (com características inorgânicas) alcançado teor de sólidos mais elevado, cerca de 37%. A capacidade de retenção de sólidos pelo tubo geotêxtil foi influenciada pela concentração inicial de SST do resíduo, onde com baixa concentração (

A escassez de água em regiões densamente urbanizadas gera disputa na alocação da água em reservatórios para o abastecimento urbano. Nesse artigo foi utilizada uma metodologia proposta para a definição do custo da escassez da água e posterior utilização em um modelo hidroeconômico de alocação de água. Como exemplo, foi utilizado o Sistema Cantareira em um estudo de caso. O modelo hidroeconômico apresentou a maior disponibilidade de água para as vazões urbanas demandadas e maior volume per capita armazenado nos reservatórios. A metodologia proposta pode promover a sustentabilidade econômica das companhias de saneamento. O benefício econômico regional obtido somente para o abastecimento urbano é de cerca de R$ 3 bilhões (média anual) na região de estudo. Palavras-chave: Sustentabilidade financeira. Sistema de suporte à decisão. Custo da escassez hídrica. Curva de demanda hídrica. Planejamento em recursos hídricos.

O tratamento de lixiviado de aterro sanitário, efluente de cabines sanitárias e lodo de fossa séptica combinado com esgoto sanitário tem sido uma estratégia utilizada para reduzir custos operacionais no tratamento de efluentes externos (EE). Entretanto, ainda não há consenso sobre os impactos na segurança operacional e na eficiência das estações de tratamento de esgotos sanitários (ES). Este trabalho avaliou um sistema de lodos ativados do tipo RSB tratando ES e EE. O percentual total de EE adicionados ao ES foi de 3,6% da vazão de ES tratado, provocando um aumento na carga afluente de DQO, DBO e nutrientes. As cargas de choque decorrentes da entrada dos EE dificultaram a manutenção de características adequadas de sedimentabilidade do lodo aeróbio, verificado pela perda de biomassa no efluente final e aumento do índice volumétrico de lodo de 46 mL.g-1 para 287 mL.g-1. A relação A/M oscilou entre 0,42 d-1 e 0,82 d-1. A entrada dos EE contribuiu para decréscimo na remoção de matéria orgânica e nutrientes. Análise do lodo ativado apresentou 56% de Fe, 16% de Ca, 10% de Si, 8% de S, 4% de Zn, 3% de Cu, 1,5% de Mn e 1,2% de K adsorvidos aos flocos, possivelmente devido à entrada dos EE. Palavras-chave: Efluente de banheiro químico. Esgoto sanitário. Lixiviado de aterro sanitário. Lodo de tanque séptico. Lodo ativado

The Nimbus 7 Limb Infrared Monitor of the Stratosphere (LIMS) instrument operated from 25 October 1978 through 28 May 1979. Its version 6 (V6) profiles were processed and archived in 2002. We present several diagnostic examples of the quality of the V6 stratospheric species distributions based on their level 3 zonal Fourier coefficient products. In particular, we show that there are small differences in the ascending (A) minus descending (D) orbital temperature–pressure or T(p) profiles (their A−D values) that affect (A−D) species values. Systematic A−D biases in T(p) can arise from small radiance biases and/or from viewing anomalies along orbits. There can also be (A−D) differences in T(p) due to not resolving and correcting for all of the atmospheric temperature gradient along LIMS tangent view-paths. An error in T(p) affects species retrievals through (1) the Planck blackbody function in forward calculations of limb radiance that are part of the iterative retrieval algorithm of LIMS, and (2) the registration of the measured LIMS species radiance profiles in pressure altitude, mainly for the lower stratosphere. There are clear A−D differences for ozone, H2O, and HNO3 but not for NO2. Percentage differences are larger in the lower stratosphere for ozone and H2O because those species are optically thick. We evaluate V6 ozone profile biases in the upper stratosphere with the aid of comparisons against a monthly climatology of UV–ozone soundings from rocketsondes. We also provide results of time series analyses of V6 ozone, H2O, and potential vorticity for the middle stratosphere to show that their average (A+D) V6 level 3 products provide a clear picture of the evolution of those tracers during Northern Hemisphere winter. We recommend that researchers use the average V6 level 3 product for their science studies of stratospheric ozone and H2O, while keeping in mind that there are uncorrected nonlocal thermodynamic equilibrium effects in daytime ozone in the lower mesosphere and in daytime H2O in the uppermost stratosphere. We also point out that the present-day Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) experiment provides measurements and retrievals of temperature and ozone that are nearly free of anomalous diurnal variations and of effects from gradients at low and middle latitudes.

Lignocellulosic biomass feedstocks are promising alternatives to fossil fuels for meeting raw material needs of processing industries and helping transit from a linear to a circular economy and thereby meet the global sustainability criteria. The sugar platform route in the biochemical conversion process is one of the promising and extensively studied methods, which consists of four major conversion steps: pretreatment, hydrolysis, fermentation, and product purification. Each of these conversion steps has multiple challenges. Among them, the challenges associated with the pretreatment are the most significant for the overall process because this is the most expensive step in the sugar platform route and it significantly affects the efficiency of all subsequent steps on the sustainable valorization of each biomass component. However, the development of a universal pretreatment method to cater to all types of feedstock is nearly impossible due to the substantial variations in compositions and structures of biopolymers among these feedstocks. In this review, we have discussed some promising pretreatment methods, their processing and chemicals requirements, and the effect of biomass composition on deconstruction efficiencies. In addition, the global biomass resources availability and process intensification ideas for the lignocellulosic-based chemical industry have been discussed from a circularity and sustainability standpoint.

The cloud particle concentration, size, and shape data from optical array probes (OAPs) are routinely used to parameterise cloud properties and constrain remote sensing retrievals. This paper characterises the optical response of OAPs using a combination of modelling, laboratory, and field experiments. Significant uncertainties are found to exist with such probes for ice crystal measurements. We describe and test two independent methods to constrain a probe's sample volume that remove the most severely mis-sized particles: (1) greyscale image analysis and (2) co-location using stereoscopic imaging. These methods are tested using field measurements from three research flights in cirrus. For these cases, the new methodologies significantly improve agreement with a holographic imaging probe compared to conventional data-processing protocols, either removing or significantly reducing the concentration of small ice crystals (< 200 µm) in certain conditions. This work suggests that the observational evidence for a ubiquitous mode of small ice particles in ice clouds is likely due to a systematic instrument bias. Size distribution parameterisations based on OAP measurements need to be revisited using these improved methodologies.

Wind-tracking algorithms produce atmospheric motion vectors (AMVs) by tracking clouds or water vapor across spatial–temporal fields. Thorough error characterization of wind-tracking algorithms is critical in properly assimilating AMVs into weather forecast models and climate reanalysis datasets. Uncertainty modeling should yield estimates of two key quantities of interest: bias, the systematic difference between a measurement and the true value, and standard error, a measure of variability of the measurement. The current process of specification of the errors in inverse modeling is often cursory and commonly consists of a mixture of model fidelity, expert knowledge, and need for expediency. The method presented in this paper supplements existing approaches to error specification by providing an error characterization module that is purely data-driven. Our proposed error characterization method combines the flexibility of machine learning (random forest) with the robust error estimates of unsupervised parametric clustering (using a Gaussian mixture model). Traditional techniques for uncertainty modeling through machine learning have focused on characterizing bias but often struggle when estimating standard error. In contrast, model-based approaches such as k-means or Gaussian mixture modeling can provide reasonable estimates of both bias and standard error, but they are often limited in complexity due to reliance on linear or Gaussian assumptions. In this paper, a methodology is developed and applied to characterize error in tracked wind using a high-resolution global model simulation, and it is shown to provide accurate and useful error features of the tracked wind.

The aerosol fine-mode fraction (FMF) is an important optical parameter of aerosols, and the FMF is difficult to accurately retrieve by traditional satellite remote sensing methods. In this study, FMF retrieval was carried out based on the multiangle polarization data of Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from Lidar (PARASOL), which overcame the shortcomings of the FMF retrieval algorithm in our previous research. In this research, FMF retrieval was carried out in China and compared with the AErosol RObotic NETwork (AERONET) ground-based observation results, Moderate Resolution Imaging Spectroradiometer (MODIS) FMF products, and Generalized Retrieval of Aerosol and Surface Properties (GRASP) FMF results. In addition, the FMF retrieval algorithm was applied, a new FMF dataset was produced, and the annual and quarterly average FMF results from 2006 to 2013 were obtained for all of China. The research results show that the FMF retrieval results of this study are comparable with the AERONET ground-based observation results in China and the correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), and the proportion of results that fall within the expected error (Within EE) are 0.770, 0.143, 0.170, and 65.01 %, respectively. Compared with the MODIS FMF products, the FMF results of this study are closer to the AERONET ground-based observations. Compared with the FMF results of GRASP, the FMF results of this study are closer to the spatial variation in the ratio of PM2.5 to PM10 near the ground.

Precipitation is a crucial driver of hydrological processes. Ironically, a reliable characterization of its spatiotemporal variability is challenging. Ground-based rainfall measurement using rain gauges is more accurate. However, installing a dense gauging network to capture rainfall variability can be impractical. Satellite-based rainfall estimates (SREs) could be good alternatives, especially for data-scarce basins like in Ethiopia. However, SRE rainfall is plagued with uncertainties arising from many sources. The objective of this study was to evaluate the performance of the latest versions of several SRE products (i.e., CHIRPS2, IMERG6, TAMSAT3 and 3B42/3) for the Dhidhessa River Basin (DRB). Both statistical and hydrological modeling approaches were used for the performance evaluation. The Soil and Water Analysis Tool (SWAT) was used for hydrological simulations. The results showed that whereas all four SRE products are promising to estimate and detect rainfall for the DRB, the CHIRPS2 dataset performed the best at annual, seasonal and monthly timescales. The hydrological simulation-based evaluation showed that SWAT's calibration results are sensitive to the rainfall dataset. The hydrological response of the basin is found to be dominated by the subsurface processes, primarily by the groundwater flux. Overall, the study showed that both CHIRPS2 and IMERG6 products could be reliable rainfall data sources for the hydrological analysis of the DRB. Moreover, the climatic season in the DRB influences rainfall and streamflow estimation. Such information is important for rainfall estimation algorithm developers.

Os reatores UASBs são amplamente utilizados no Paraná para tratamento de esgotos domésticos e requerem gerenciamento adequado de lodo e escuma. A disposição da escuma em conjunto com lodo facilitaria a logística na Estação de Tratamento de Esgoto (ETE). A fim de avaliar a semelhança desses dois substratos, compararam-se os teores de óleos e graxas (O&G) de 135 amostras de escumas e lodos de 8 ETEs de Curitiba e Região Metropolitana. Constatou-se que o valor médio de O&G para o lodo de esgoto anaeróbio (0,43%) é ligeiramente superior ao valor médio da escuma (0,36 %), porém essa diferença fica dentro do desvio padrão dos resultados. Ainda, o espaçamento diferenciado do gradeamento de cada ETE não interferiu na composição de O&G das escumas e lodos avaliados, enquanto o fato de operar muito acima da vazão de projeto pode contribuir com uma maior quantidade de O&G no lodo, assim como ETEs que operam em vazões abaixo das vazões de projeto possuem maior teor de O&G na escuma. Palavras-chave: Reator UASB. Lodo. Escuma. Óleos e graxas.

A adição de composto orgânico aos solos de cobertura de aterros sanitários, principalmente em regiões do semiárido, apresenta-se como ótima alternativa para melhoramento das suas propriedades. O principal objetivo é avaliar a influência da adição de composto orgânico no solo em relação às propriedades geotécnicas de misturas estudadas. O campo experimental foi o Aterro Sanitário em Campina Grande-PB. O solo utilizado foi coletado diretamente da camada de cobertura e o composto orgânico, resultante de compostagem, foi concedido pelo laboratório de engenharia agrícola da Universidade Federal de Campina Grande. Os ensaios de caracterização geotécnica e sucção foram realizados segundo normas nacionais e internacionais. Verificou-se uma diminuição no percentual de partículas finas, aumento dos limites de consistência e redução da massa específica seca máxima na compactação, além de aumento da capacidade de retenção de umidade com o aumento do percentual orgânico nas misturas. Conclui-se que a adição de composto orgânico ao solo contribuiu para melhorar suas propriedades geotécnicas e fornecer nutrientes adequados ao processo de oxidação de metano por bactérias metanotróficas. Palavras-chave: Sucção. Matéria orgânica. Compostagem. Misturas. Oxidação de metano. Bactérias metanotróficas.

The LiDAR Statistical Barnes Objective Analysis (LiSBOA), presented in Letizia et al. (2021), is a procedure for the optimal design of lidar scans and calculations over a Cartesian grid of the statistical moments of the velocity field. Lidar data collected during a field campaign conducted at a wind farm in complex terrain are analyzed through LiSBOA for two different tests. For both case studies, LiSBOA is leveraged for the optimization of the azimuthal step of the lidar and the retrieval of the mean equivalent velocity and turbulence intensity fields. In the first case, the wake velocity statistics of four utility-scale turbines are reconstructed on a 3D grid, showing LiSBOA's ability to capture complex flow features, such as high-speed jets around the nacelle and the wake turbulent-shear layers. For the second case, the statistics of the wakes generated by four interacting turbines are calculated over a 2D Cartesian grid and compared to the measurements provided by the nacelle-mounted anemometers. Maximum discrepancies, as low as 3 % for the mean velocity (with respect to the free stream velocity) and turbulence intensity (in absolute terms), endorse the application of LiSBOA for lidar-based wind resource assessment and diagnostic surveys for wind farms.

Low-level clouds play a key role in the energy budget and hydrological cycle of the climate system. The accurate long-term observation of low-level clouds is essential for understanding their climate effect and model constraints. Both ground-based and spaceborne millimeter-wavelength cloud radars can penetrate clouds but the detected low-level clouds are always contaminated by clutter, which needs to be removed. In this study, we develop an algorithm to accurately separate low-level clouds from clutter for ground-based cloud radar using multi-dimensional probability distribution functions along with the Bayesian method. The radar reflectivity, linear depolarization ratio, spectral width, and their dependence on the time of the day, height, and season are used as the discriminants. A low-pass spatial filter is applied to the Bayesian undecided classification mask by considering the spatial correlation difference between clouds and clutter. The final feature mask result has a good agreement with lidar detection, showing a high probability of detection rate (98.45 %) and a low false alarm rate (0.37 %). This algorithm will be used to reliably detect low-level clouds at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) site for the study of their climate effect and the interaction with local abundant dust aerosol in semi-arid regions.

The comparative reactivity method (CRM) was developed more than a decade to measure OH reactivity (i.e., OH loss frequency) in both laboratory and field studies. However, accurate OH reactivity quantification remains challenging under real ambient conditions, especially for OH reactivity measurements in high-NOx (e.g., > 10 ppbv) environments, as ambient NO enhances the regeneration of OH radicals in the CRM reactor. To solve this problem, we design a new and improved CRM reactor (ICRM) and add NO into the system continuously so that the HO2 radical concentration is suppressed. We confirmed the appropriate level of NO by determining the maximum decrease in the pyrrole level caused by regenerated OH radicals from NO + HO2. RO2 radicals induced by volatile organic compounds (VOCs) in the ICRM reactor were also found to react with NO, which led to the regeneration of OH radicals and thus the underestimation of OH reactivity. This effect was quantified by the calibration of representative VOC species at different NO levels, and the correction coefficients obtained were used to correct the measured OH reactivity. All these efforts resulted in reducing the uncertainty of the NO-artifact correction by at least an order of magnitude compared to the original CRM system. Additionally, these technological improvements also considerably reduced the systematic errors from pyrrole photolysis in the original system. A new operation mode was proposed for the ICRM, which is able to avoid the interference resulting from OH radicals produced by photolysis of residual humidity and save time for ambient measurement. The ICRM system was employed in a field campaign to measure OH reactivity and performed well with ambient NO levels ranging from 0 to 50 ppbv, which are typically observed in the urban and suburban atmosphere.

Ozone (O3) plays a significant role in weather and climate on regional to global spatial scales. Most studies on the variability in the total column of O3 (TCO) are typically carried out using daytime data. Based on knowledge of the chemistry and transport of O3, significant deviations between daytime and night-time O3 are only expected either in the planetary boundary layer (PBL) or high in the stratosphere or mesosphere, with little effect on the TCO. Hence, we expect the daytime and night-time TCO to be very similar. However, a detailed evaluation of satellite measurements of daytime and night-time TCO is still lacking, despite the existence of long-term records of both. Thus, comparing daytime and night-time TCOs provides a novel approach to verifying the retrieval algorithms of instruments such as the Atmospheric Infrared Sounder (AIRS) and the Microwave Limb Sounder (MLS). In addition, such a comparison also helps to assess the value of night-time TCO for scientific research. Applying this verification on the AIRS and the MLS data, we identified inconsistencies in observations of O3 from both satellite instruments. For AIRS, daytime–night-time differences were found over oceans resembling cloud cover patterns and over land, mostly over dry land areas, which is likely related to infrared surface emissivity. These differences point to issues with the representation of both processes in the AIRS retrieval algorithm. For MLS, a major issue was identified with the “ascending–descending” orbit flag, used to discriminate night-time and daytime MLS measurements. Disregarding this issue, MLS day–night differences were significantly smaller than AIRS day–night differences, providing additional support for the retrieval method origin of AIRS in stratospheric column ozone (SCO) day–night differences. MLS day–night differences are dominated by the upper-stratospheric and mesospheric diurnal O3 cycle. These results provide useful information for improving infrared O3 products.

形態: カラー図版あり, Physical characteristics: Original contains color illustrations, Accepted: 2021-02-03, 資料番号: PA2110031000

O presente estudo tem por finalidade analisar o tratamento de efluente vinícola em sistema combinado de um reator anaeróbio de manta de lodo e fluxo ascendente (Upflow Anaerobic Sludge Blanket - UASB) seguido de um filtro biológico aeróbio submerso (FBAS) na remoção de matéria carbonácea, nitrogenada, fosforada e de compostos fenólicos totais para enquadramento nos padrões ambientais de lançamento local. O sistema de escala laboratorial foi operado com efluente vinícola em diferentes concentrações de DQO (500- 1000 mg.L-1; Etapa I, II e III e 1000-2000 mg.L-1; Etapa IV e V) e foi variado também seu TDH (16h; Etapas III e IV 18h; Etapas II e V e 24h; Etapa I). Dos 422 dias de operação, o sistema combinado apresentou estado de equilíbrio aparente no dia 134, no qual foram iniciados os perfis de amostragem das características físico-químicas. As etapas I, II e III atenderam às legislações locais (< 200 mgDQOb.L-1) no residual orgânico máximo de 39 mgDQOb.L-1. A remoção dos nutrientes na forma de nitrito e nitrato atende à demanda da legislação nas etapas II, III, IV e V, apenas na primeira que o valor para nitrito ficou 0,4 mgNO2-.L-1 acima do limite. Os compostos fosforados não alcançaram em nenhuma etapa o limite máximo de lançamento (< 0,03 mg.L-1). A remoção dos compostos fenólicos ocorreu predominantemente na fase anaeróbia, tendo residual mínimo de 3,1 mgCFT.L-1. Portanto, é possível identificar que a condição com TDH global de 16 horas e concentração inicial do efluente vinícola de 500 a 1000 mgDQOb.-1 apresentou as melhores eficiências de remoção das características estudadas e para condições experimentais ao serem aplicadas a indústria. O efluente final do sistema UASB-FBAS atende parcialmente às legislações da Resolução Conama 357/2005, 430/2011; e à Portaria 70/2009 da CEMA. Dentre as características analisadas, é possível concluir que os maiores problemas de remoção foram os compostos fenólicos totais e fósforo total. Palavras-chave: Águas Residuárias. UASB. FBAS. Remoção Nutriente. Compostos Fenólicos.

The COVID-19 pandemic resulted in reduced anthropogenic carbon dioxide (CO2) emissions during 2020 in large parts of the world. To investigate whether a regional-scale reduction of anthropogenic CO2 emissions during the COVID-19 pandemic can be detected using space-based observations of atmospheric CO2, we have analysed a small ensemble of OCO-2 and GOSAT satellite retrievals of column-averaged dry-air mole fractions of CO2, i.e. XCO2. We focus on East China and use a simple data-driven analysis method. We present estimates of the relative change of East China monthly emissions in 2020 relative to previous periods, limiting the analysis to October-to-May periods to minimize the impact of biogenic CO2 fluxes. The ensemble mean indicates an emission reduction by approximately 10 % ± 10 % in March and April 2020. However, our results show considerable month-to-month variability and significant differences across the ensemble of satellite data products analysed. For example, OCO-2 suggests a much smaller reduction (∼ 1 %–2 % ± 2 %). This indicates that it is challenging to reliably detect and to accurately quantify the emission reduction with current satellite data sets. There are several reasons for this, including the sparseness of the satellite data but also the weak signal; the expected regional XCO2 reduction is only on the order of 0.1–0.2 ppm. Inferring COVID-19-related information on regional-scale CO2 emissions using current satellite XCO2 retrievals likely requires, if at all possible, a more sophisticated analysis method including detailed transport modelling and considering a priori information on anthropogenic and natural CO2 surface fluxes.

O tratamento de efluentes contendo metais pesados é de extrema relevância, uma vez que tais substâncias apresentam elevada toxicidade, mesmo em baixas concentrações. Neste trabalho, empregou-se com sucesso um reator eletroquímico de leito fluidizado na remoção de cobre. O desempenho do reator foi avaliado pela Eficiência de Corrente (EC) e Consumo Energético Específico (CEE), tendo-se como variáveis a distância entre alimentador de corrente e contra-eletrodo (D), corrente (I) e concentrações de cobre (CCu) e de ácido (Các). O maior valor experimental obtido para EC foi de 82,18%, e o menor valor para CEE foi de 2,46 kW.h.kg-1. Utilizou-se um Planejamento Composto Central para obtenção de modelos empíricos para EC e CEE. Com o uso da Metodologia de Superfícies de Resposta e da técnica da Análise de Cristas, obtiveram-se as condições operacionais que minimizam CEE para dois valores de CCu, sendo os valores mínimos 1,58 e 2,31 kW.h.kg-1. Palavras-chave: Eletrodeposição de cobre. Eletrodo de leito fluidizado. Metodologia de superfície de respostas. Análise de cristas.

The microwave temperature profiler (MTP), an airborne passive microwave radiometer, measures radiances, recorded as counts and calibrated to brightness temperatures, in order to estimate temperature profiles around flight altitude. From these data, quantities such as potential temperature gradients and static stability, indicating the state of the atmosphere, can be derived and used to assess important dynamical processes (e.g., gravity waves or stability assessments). DLR has acquired a copy of the MTP from NASA–JPL, which was designed as a wing-canister instrument and is deployed on the German High Altitude LOng range research aircraft (HALO). For this instrument a thorough analysis of instrument characteristics has been made in order to correctly determine the accuracy and precision of MTP measurements. Using a laboratory setup, the frequency response function and antenna diagram of the instrument were carefully characterized. A cold chamber was used to simulate the changing in-flight conditions and to derive noise characteristics as well as reliable calibration parameters for brightness temperature calculations, which are compared to those calculated from campaign data. The MTP shows quite large changes in the instrument state, imposing considerable changes in calibration parameters over the course of a single measurement flight; using a built-in heated target for calibration may yield large errors in brightness temperatures due to a misinterpretation of the measured absolute temperature. Applying the corrections presented herein to the calibration parameter calculations, the measurement noise becomes the dominant source of uncertainty and it is possible to measure the brightness temperatures around flight level (closely related to the absolute temperature close to the instrument) with a precision of 0.38 K. Furthermore, radiative transfer simulations, using the Py4CAtS package in a pencil-beam approach, indicate that the altitude range of the sensitivity of the MTP instrument can be increased by applying a modified measurement strategy. This is the first time such an extensive characterization of an MTP instrument, including a thorough calibration strategy assessment, has been published. The presented results, relevant for the wing-canister design of the MTP instrument, are important when processing MTP data: knowledge of the relevant uncertainties and instrument characteristics is essential for retrieval setup and is mandatory to correctly identify and interpret significant atmospheric temperature fluctuations.

Open-path measurements of methane (CH4) with the use of GasFinder systems (Boreal Laser Inc, Edmonton Canada) have been frequently used for emission estimation with the inverse dispersion method (IDM), particularly from agricultural sources. It is common to many IDM applications that the concentration enhancement related to CH4 sources is small, typically between 0.05 and 0.5 ppm, and accurate measurements of CH4 concentrations are needed at concentrations close to ambient levels. The GasFinder3-OP (GF3) device for open-path CH4 measurements is the latest version of the commercial GasFinder systems by Boreal Laser Inc. We investigated the uncertainty of six GF3 devices from side-by-side intercomparison measurements and comparisons to a closed-path quantum cascade laser device. The comparisons were made at near-ambient levels of CH4 (85 % of measurements below 2.5 ppm) with occasional phases of elevated concentrations (max. 8.3 ppm). Relative biases as high as 8.3 % were found, and a precision for half-hourly data between 2.1 and 10.6 ppm-m (half width of the 95 % confidence interval) was estimated. These results deviate from the respective manufacturer specifications of 2 % and 0.5 ppm-m. Intercalibration of the GF3 devices by linear regression to remove measurement bias was shown to be of limited value due to drifts and step changes in the recorded GF3 concentrations.

In this paper, we compare column-averaged dry-air mole fractions of water vapor (XH2O) retrievals from the COllaborative Carbon Column Observing Network (COCCON) with retrievals from two co-located high-resolution Fourier transform infrared (FTIR) spectrometers as references at two boreal sites, Kiruna, Sweden, and Sodankylä, Finland, from 6 March 2017 to 20 September 2019. In the framework of the Network for the Detection of Atmospheric Composition Change (NDACC), an FTIR spectrometer is operated at Kiruna. The H2O product derived from these observations has been generated with the MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) processor. In Sodankylä, a Total Carbon Column Observing Network (TCCON) spectrometer is operated, and the official XH2O data as provided by TCCON are used for this study. The datasets are in good overall agreement, with COCCON data showing a wet bias of (49.20±58.61) ppm ((3.33±3.37) %, R2=0.9992) compared with MUSICA NDACC and (56.32±45.63) ppm ((3.44±1.77) %, R2=0.9997) compared with TCCON. Furthermore, the a priori H2O volume mixing ratio (VMR) profiles (MAP) used as a priori information in the TCCON retrievals (also adopted for COCCON retrievals) are evaluated with respect to radiosonde (Vaisala RS41) profiles at Sodankylä. The MAP and radiosonde profiles show similar shapes and a good linear correlation of integrated XH2O, indicating that MAP is a reasonable approximation of the true atmospheric state and an appropriate choice for the scaling retrieval methods as applied by COCCON and TCCON. COCCON shows a reduced dry bias (−14.96 %) in comparison with TCCON (−19.08 %) with respect to radiosonde XH2O. Finally, we investigate the quality of satellite data at high latitudes. For this purpose, the COCCON XH2O is compared with retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) generated with the MUSICA processor (MUSICA IASI) and with retrievals from the TROPOspheric Monitoring Instrument (TROPOMI). Both paired datasets generally show good agreement and similar correlations at the two sites. COCCON measures 4.64 % less XH2O at Kiruna and 3.36 % less at Sodankylä with respect to MUSICA IASI, whereas COCCON measures 9.71 % more XH2O at Kiruna and 7.75 % more at Sodankylä compared with TROPOMI. Our study supports the assumption that COCCON also delivers a well-characterized XH2O data product. This emphasizes that this approach might complement the TCCON network with respect to satellite validation efforts. This is the first published study where COCCON XH2O has been compared with MUSICA NDACC and TCCON retrievals and has been used for MUSICA IASI and TROPOMI validation.

A 2-year measurement campaign of the ZephIR 300 vertical profiling continuous-wave (CW) focusing wind lidar has been carried out by the Royal Netherlands Meteorological Institute (KNMI) at the Cabauw site. We focus on the (height-dependent) data availability of the wind lidar under various meteorological conditions and the data quality through a comparison with in situ wind measurements at several levels in the 213 m tall meteorological mast. We find an overall availability of quality-controlled wind lidar data of 97 % to 98 %, where the missing part is mainly due to precipitation events exceeding 1 mm h−1 or fog or low clouds below 100 m. The mean bias in the horizontal wind speed is within 0.1 m s−1 with a high correlation between the mast and wind lidar measurements, although under some specific conditions (very high wind speed, fog or low clouds) larger deviations are observed. The mean bias in the wind direction is within 2∘, which is of the same order as the combined uncertainty in the alignment of the wind lidars and the mast wind vanes. The well-known 180∘ error in the wind direction output for this type of instrument occurs about 9 % of the time. A correction scheme based on data of an auxiliary wind vane at a height of 10 m is applied, leading to a reduction of the 180∘ error below 2 %. This scheme can be applied in real-time applications in the situation that a nearby freely exposed mast with wind direction measurements at a single height is available.

An evaluation of the performance and relative accuracy of a Cavity Attenuated Phase-Shift Single Scattering Albedo Monitor (CAPS PMSSA; Aerodyne Research, Inc.) was conducted in an optical-closure study with proven technologies: Cavity Attenuated Phase-Shift Particle Extinction Monitor (CAPS PMex; Aerodyne Research, Inc.), three-wavelength integrating nephelometer (TSI Model 3563) and three-wavelength filter-based Particle Soot Absorption Photometer (PSAP; Radiance Research Inc.). The evaluation was conducted by connecting the instruments to a controlled aerosol generation system and comparing the measured scattering, extinction and absorption coefficients measured by the CAPS PMSSA with the independent measurements. Three different particle types were used to generate aerosol samples with single-scattering albedos (SSAs) ranging from 0.4 to 1.0 at 630 nm wavelength. The CAPS PMSSA measurements compared well with the proven technologies. Extinction measurement comparisons exhibited a slope of the linear regression line for the full dataset between 1.05 and 1.01, an intercept below ±1.5×10-6 m−1 (±1.5 Mm−1), and a regression coefficient R2>0.99, whereas scattering measurements had a slope between 0.90 and 1.04, an intercept of less than ±2.0×10-6 m−1 (2.0 Mm−1), and a coefficient R2>0.96. The derived CAPS PMSSA absorption compared well to the PSAP measurements for the small particle sizes and modest (0.4 to 0.6) SSA values tested, with a linear regression slope between 0.90 and 1.07, an intercept of ±3.0×10-6 m−1 (3.0 Mm−1), and a coefficient R2>0.99. For the SSA measurements, agreement was highest (regression slopes within 1 %) for SSA =1.0 particles at extinction levels of per tens of inverse megameters and above; however, as extinctions approach 0, small uncertainties in the baseline can introduce larger errors. SSA measurements for absorbing particles exhibited absolute differences up to 18 %, though it is not clear which measurement had the best relative accuracy. For a given particle type, the CAPS PMSSA instrument exhibited the lowest scatter around the average. This study demonstrates that the CAPS PMSSA is a robust and reliable instrument for the direct measurement of the scattering and extinction coefficients and thus SSA. This conclusion also holds for the indirect measurement of the absorption coefficient with the constraint that the relative accuracy of this particular determination degrades as the SSA and particle size increases.

A bacia hidrográfica do rio São Marcos, inserida nos Estados de Minas Gerais, Goiás e Distrito Federal, tem destaque na produção agrícola e na geração de energia elétrica, levando a conflitos pelo uso da água. O objetivo deste artigo foi trazer propostas para otimização do aproveitamento hídrico superficial, minimizando os conflitos de uso da água entre a geração hidroelétrica (Centrais Hidrelétricas de Batalha e Serra do Facão) e a irrigação por meio de pivôs centrais. Foram analisados novos critérios na estimativa da vazão de referência, com a determinação em bases sazonais, considerando os seis meses mais chuvosos (outubro a março) e os seis meses mais secos (abril a setembro), além da adoção de critérios de outorga diferentes dos adotados atualmente pelos Estados de Minas Gerais (50% da Q7,10), Goiás (70% da Q95) e Distrito Federal (80% da Q7,10), com porcentagens maiores e menores do que a vazão máxima outorgável. Com as alterações das vazões de referência calculadas em bases sazonais, percebeu-se uma piora na disponibilidade hídrica ao utilizar o período de estiagem, com um amento de 8% das áreas críticas. Já no período chuvoso houve uma diminuição de aproximadamente 2% nas áreas críticas. Na substituição dos critérios de outorga, o que trouxe os melhores resultados foi a adoção do critério de 80% da Q7,10, em que somente 2,3% das áreas da bacia hidrográfica estiveram acima dos limites outorgáveis. Nas regiões em que as situações de escassez são mais recorrentes, foram estimados cortes máximos no volume captado de até 89%. No reservatório de Serra do Facão, o potencial existente para captação se mostra favorável, sendo possível o aumento da demanda na região sem prejudicar a geração de energia elétrica. Em 27% da série temporal analisada, o reservatório de Batalha esteve no seu volume de reserva mínimo devido às grandes demandas existentes na região. Contudo, este estudo contribui para o planejamento e gestão dos recursos hídricos superficiais na bacia hidrográfica do rio São Marcos. Palavras-chave: Otimização hídrica. OPTIGES. Uso da água. Vazão de referência. Rio São Marcos.

The new platforms for Earth observation from space are characterized by measurements made at great spatial and temporal resolutions. While this abundance of information makes it possible to detect and study localized phenomena, it may be difficult to manage this large amount of data for the study of global and large-scale phenomena. A particularly significant example is the use by assimilation systems of Level 2 products that represent gas profiles in the atmosphere. The models on which assimilation systems are based are discretized on spatial grids with horizontal dimensions of the order of tens of kilometres in which tens or hundreds of measurements may fall in the future. A simple procedure to overcome this problem is to extract a subset of the original measurements, but this involves a loss of information. Another option is the use of simple averages of the profiles, but this approach also has some limitations that we will discuss in the paper. A more advanced solution is to resort to the so-called fusion algorithms, capable of compressing the size of the dataset while limiting the information loss. A novel data fusion method, the Complete Data Fusion algorithm, was recently developed to merge a set of retrieved products in a single product a posteriori. In the present paper, we apply the Complete Data Fusion method to ozone profile measurements simulated in the thermal infrared and ultraviolet bands in a realistic scenario. Following this, the fused products are compared with the input profiles; comparisons show that the output products of data fusion have smaller total errors and higher information contents in general. The comparisons of the fused products with the fusing products are presented both at single fusion grid box scale and with a statistical analysis of the results obtained on large sets of fusion grid boxes of the same size. We also evaluate the grid box size impact, showing that the Complete Data Fusion method can be used with different grid box sizes even if this possibility is connected to the natural variability of the considered atmospheric molecule.

Accurate knowledge of cloud properties is essential to the measurement of atmospheric composition from space. In this work we assess the quality of the cloud data from three Copernicus Sentinel-5 Precursor (S5P) TROPOMI cloud products: (i) S5P OCRA/ROCINN_CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks;Clouds-As-Layers), (ii) S5P OCRA/ROCINN_CRB (Clouds-as-Reflecting Boundaries), and (iii) S5P FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands – Sentinel). Target properties of this work are cloud-top height and cloud optical thickness (OCRA/ROCINN_CAL), cloud height (OCRA/ROCINN_CRB and FRESCO-S), and radiometric cloud fraction (all three algorithms). The analysis combines (i) the examination of cloud maps for artificial geographical patterns, (ii) the comparison to other satellite cloud data (MODIS, NPP-VIIRS, and OMI O2–O2), and (iii) ground-based validation with respect to correlative observations (30 April 2018 to 27 February 2020) from the Cloudnet network of ceilometers, lidars, and radars. Zonal mean latitudinal variation of S5P cloud properties is similar to that of other satellite data. S5P OCRA/ROCINN_CAL agrees well with NPP VIIRS cloud-top height and cloud optical thickness and with Cloudnet cloud-top height, especially for the low (mostly liquid) clouds. For the high clouds, S5P OCRA/ROCINN_CAL cloud-top height is below the cloud-top height of VIIRS and of Cloudnet, while its cloud optical thickness is higher than that of VIIRS. S5P OCRA/ROCINN_CRB and S5P FRESCO cloud height are well below the Cloudnet cloud mean height for the low clouds but match on average better with the Cloudnet cloud mean height for the higher clouds. As opposed to S5P OCRA/ROCINN_CRB and S5P FRESCO, S5P OCRA/ROCINN_CAL is well able to match the lowest CTH mode of the Cloudnet observations. Peculiar geographical patterns are identified in the cloud products and will be mitigated in future releases of the cloud data products.