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The Pannonian-Carpathian-Alpine Seismic Experiment (PACASE) is a collaborative project based on a large, passive seismic network comprising 214 temporary stations. Among the primary aims are the imaging of the Earth's crustal, lithospheric and upper mantle structure, including joint inversions; monitoring and mapping of seismic activity; and interpretation of the data from seismotectonic and geodynamic perspectives. The base of the cooperation is a high-quality, broadband seismic network covering the very centre of Europe: the Eastern Alpine and Western Carpathian Mountain ranges, the Bohemian Massif, and the sedimentary Molasse and Pannonian Basins. In this overview, we focus on the implementation and achieved field goals of PACASE, such as seismic station configuration, general network organization, data availability and access to the dataset. With selected seismological examples, we demonstrate the good usability of the records of earthquake detection, and a first publication attests to the structural imaging capability of the PACASE data. We assess the background noise level at various stations and its variations in time and space. Our aim is to collect all practical information relevant to serve as a long-term reference for the PACASE. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: This research aims to critically assess the suitability of current ISO life cycle assessment standards and practices for the challenges of decarbonisation through the use of carbon capture and the circular economy. Currently, the handling of wastes, including carbon dioxide, in life cycle assessment varies from sector to sector. We propose several methodological innovations to improve transparency and comparability of life cycle assessments to aid in the decarbonisation transition. Methods: Three approaches have been used to analyse the shortcomings of life cycle assessment for carbon capture and circular practices: Recent standards and practices have been assessed to determine their suitability for decarbonisation; Life cycle assessment and industry experts were consulted through a workshop held at the University of Bath in September of 2022; Case studies of industrial decarbonisation projects funded by IDRIC have been conducted to apply solutions to the shortcomings identified through the former methods. The issues identified have been categorised into three key areas: (i) guidelines and standards; (i) temporal and regional issues and (iii) data quality analysis. Results and discussion: The methods of handling carbon capture, waste valorisation and circular practices were found to vary significantly from sector to sector. Temporal aspects are frequently aggregated in a specific point of time, leading to low resolution by neglecting emissions over the duration of the process that creates them. Regionalisation was found to be hampered by regional characterisation factors being representative of larger regions but unsuitable at county or state scale. Uncertainty and sensitivity analyses, which are key to assessing the validity of the impacts of new and emerging technologies, were found to be neglected or only partially conducted. Conclusions and recommendations: The ISO life cycle assessment standards require updating to provide consistency in methodologies to make them suitable for use with carbon capture and circular systems and to avoid ambiguity. We recommend that the life cycle assessment community focuses on developing more consistent standards and practices between sectors to address carbon capture and circularity; improving the implementation of temporal aspects of impacts; increasing the number of studies including uncertainty and sensitivity analyses and moving towards global uncertainty in favour of local sensitivity. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This manuscript presents a data quality analysis and holistic ‘machine learning-readiness’ evaluation of a representative set of large-scale, real-world phasor measurement unit (PMU) datasets provided under the United States Department of Energy-funded FOA 1861 research program. A major focus of this study is to understand the present-day suitability of large-scale, real-world synchrophasor datasets for application of commercially-available, off-the-shelf big data and supervised or semi-supervised machine learning (ML) tools and catalogue any major obstacles to their application. To this end, dataset quality is methodically examined through an interconnect-wide quantifications of basic bad data occurrences, a summary of several harder-to-detect data quality issues that can jeopardize successful application of machine learning, and an evaluation of the adequacy of event log labeling for supervised training of models used for online event classification. A global ‘six-point’ statistical analyses of several key dataset variables is demonstrated as a means by which to identify additional hard-to-detect data quality issues, also providing an example successful application of big data technology to extract insights regarding reasonable operational bounds of the US power system. Obstacles for application of commercial ML technologies are summarized, with a particular focus on supervised and semi-supervised ML. Lessons-learned are provided regarding challenges associated with present-day event labeling practices, large spatial scope of the dataset, and dataset anonymization. Finally, insight into efficacy of employed mitigation strategies are discussed, and recommendations for future work are made.

Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Providing high-quality measurement data in analytical system of air pollution monitoring and their key importance for smart cities residents. The article presents selected, main elements of an air pollution automatic monitoring system with analytical subsystems concept in smart cities based on examples from Poland, implemented system in Pomerania, the concept of new system in Warsaw city and pilot research in Nowy Sącz city. All systems are the result of teamwork, ranging from design, development of new methodology and software to implementation in real-time air pollutants smart cities monitoring systems. Focused on the most neuralgic elements: data quality subsystems, new ideas of smart mobility measurement stations and their ability to use in future research and models. Special attention was paid to stochastic models and statistic methodology proposed and used in data diagnostics as analytical system engineering. [ABSTRACT FROM AUTHOR]

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: We present a review of our work on data acquired by GEOSTAR-class (GEophysical and Oceanographic STation for Abyssal Research) observatories deployed at three EMSO (European Multidisciplinary Seafloor and water-column Observatory; http://www.emso-eu.org) sites in southern European waters where strong geo-hazards are present: the Western Iberian Margin, the Western Ionian Sea, the Marmara Sea, and the Marsili basin in the Tyrrhenian Sea. A procedure for multiparameter data quality control is described. Then we explain why the seafloor is an interesting observation point for geophysical parameters and how it differs from land sites. We consider four interesting geophysical phenomena found at the EMSO sites that are related to geo-hazard. In the first case, we show how unknown seismicity and landslides in the Western Ionian Sea were identified and roughly localised through a single-sensor analysis based on the seismometer. In the second case, we concentrate on the problem of near-coast tsunami generation and describe a Tsunami Early Warning Detection (TEWD) system, tested in the Western Iberian Margin and currently operating in real time at the Western Ionian site. In the third case, we consider two large volcanoes in the central Mediterranean area, Mt. Etna and the Marsili seamount. Signals from the seismometer and gravimeter recorded at the seafloor at 2100m b.s.l. show various phases of Mt. Etna's 2002–2003 eruption. For the less-known Marsili we illustrate how several indicators coming from different sensors point to hydrothermal activity. A vector magnetometer at the two volcanic sites helps identify the magnetic lithospheric depth. In the fourth and final case, we present a multiparameter analysis which was focused on finding possible correlations between methane seepage and seismic energy release in the Gulf of Izmit (Marmara Sea). [Copyright &y& Elsevier]

The use of quantitative methods, including stochastic and exploratory techniques in environmental studies does not seem to be sufficient in practical aspects. There is no comprehensive analytical system dedicated to this issue, as well as research regarding this subject. The aim of this study is to present the Eco Data Miner system, its idea, construction and implementation possibility to the existing environmental information systems. The methodological emphasis was placed on the one-dimensional data quality assessment issue in terms of using the proposed QAAH1 method - using harmonic model and robust estimators beside the classical tests of outlier values with their iterative expansions. The results received demonstrate both the complementarity of proposed classical methods solution as well as the fact that they allow for extending the range of applications significantly. The practical usefulness is also highly significant due to the high effectiveness and numerical efficiency as well as simplicity of using this new tool. [ABSTRACT FROM AUTHOR]

Purpose: For compliance with the ISO standard 14044, comparative life cycle assessments are required to address data quality for time-related coverage, geographic coverage, technology coverage, precision, completeness, representativeness, consistency, reproducibility, sources of the data and uncertainty of the information. As the community of practitioners and data developers grows, the purpose of this commentary is to initiate discussion of current issues and opportunities for improvement in data quality analysis. Methods: Commonly applied data quality analysis methods are described as ranging from the collection of only qualitative information to the assignment of numeric scores. Common interpretations of data quality information are described as ranging from comparison in raw form to contribution and sensitivity analysis results, combination into an aggregate/multiaspect score, or use to infer data uncertainty. Method strengths and issues are described. Results: The strengths of current data quality analysis methods lie in the consideration of the data quality aspects specified by the ISO standards and in the differentiation of low and high data quality. Weaknesses, however, lie in unrepeatable scoring criteria, aggregation of data quality information in a way that is difficult to interpret or misinterpreted and the use of data quality information in the estimation of uncertainty with no basis for accuracy. Conclusion: It is found that among commonly applied methods there exists a need for improved repeatability and interpretability. When combined with emerging efforts to provide reliable uncertainty data to support the use of data quality information with contribution and sensitivity analysis results and efforts that have improved consideration of completeness, the future of data quality analysis promises substantial contribution to the field. [ABSTRACT FROM AUTHOR]

Abstract: This study is a review of rain chemistry measurements reported in India. Data from nearly 100 stations were reviewed with regard to sampling location, sampling method and chemical analyses. Some characteristic differences were found between the concentrations in different environments in line with known distributions of emissions. This was most clearly seen for SO4 2− with median concentration increasing from rural and suburban to urban and industrial environments, with concentrations of HCO3 − and H+ varying the opposite way. Ca2+ concentration was higher in suburban and industrial environments compared to rural and urban. Concentration of NH4 + was lower in rural than in the other locations. Sea salt concentration (Na+ and Cl− in approximately constant proportion) was higher in urban than in rural locations at the same distance from the sea. The reported data from rural and suburban locations were used to derive large-scale concentration fields over India. With knowledge of emission fields and with the aid of output from a regional transport model it was possible to see some limited spatial resemblance between modelled and observed concentrations in cases of NH4 +, NO3 - and SO4 2−. For soil dust, current models are very crude but here some resemblance could be seen: primarily limited spatial resemblance with Ca2+, pH and HCO3 − with generally increasing values towards NW. Four sites, at least two of them located in forested environments, had a mean rainwater pH close to neutral (concentration of H+ and HCO3 − about equal). Other sites had on average an excess of HCO3 −, becoming very substantial in the direction of the Thar Desert in NW India. With this review we conclude that there is a need to better assure the quality of the data with regard to sampling methods, chemical analyses and spatial representativeness. [Copyright &y& Elsevier]

In the context of monitoring water quality in natural ecosystems in real time, on-line data quality control is a very important issue for effective system surveillance and for optimizing maintenance of the monitoring network. This paper presents some applications of recursive state-parameter estimation algorithms to real-time detection of signal drift in high-frequency observations. Two continuous-discrete recursive estimation schemes, namely the Extended Kalman Filter and the Recursive Prediction Error algorithm, were applied to assuring the quality of the dissolved oxygen (DO) time series, as obtained from the Lagoon of Venice (Italy) during August 2002, through the real-time monitoring network of the Magistrato alle Acque (the Venice Water Authority). Results demonstrate the effectiveness of the methodology in early detection of a probable drift in the DO signal. Comparison of these results with those obtained from the application of a related recursive scheme (a Dynamic Linear Regression procedure) suggests the strong benefits of approaching the problem of on-line data quality control with several (not merely a single) independent such estimation methods. [ABSTRACT FROM AUTHOR]

In the context of monitoring water quality in natural ecosystems in real time, on-line data quality control is a very important issue for effective system surveillance and for optimizing maintenance of the monitoring network. This paper presents some applications of recursive state-parameter estimation algorithms to real-time detection of signal drift in high-frequency observations. Two continuous-discrete recursive estimation schemes, namely the Extended Kalman Filter and the Recursive Prediction Error algorithm, were applied to assuring the quality of the dissolved oxygen (DO) time series, as obtained from the Lagoon of Venice (Italy) during August 2002, through the real-time monitoring network of the Magistrato alle Acque (the Venice Water Authority). Results demonstrate the effectiveness of the methodology in early detection of a probable drift in the DO signal. Comparison of these results with those obtained from the application of a related recursive scheme (a Dynamic Linear Regression procedure) suggests the strong benefits of approaching the problem of on-line data quality control with several (not merely a single) independent such estimation methods. [ABSTRACT FROM AUTHOR]