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AbstractFossil benthic foraminifera are used to trace past methane release linked to climate change. However, it is still debated whether isotopic signatures of living foraminifera from methane-charged sediments reflect incorporation of methane-derived carbon. A deeper understanding of isotopic signatures of living benthic foraminifera from methane-rich environments will help to improve reconstructions of methane release in the past and better predict the impact of future climate warming on methane seepage. Here, we present isotopic signatures (δ13C and δ18O) of foraminiferal calcite together with biogeochemical data from Arctic seep environments from c. 1200 m water depth, Vestnesa Ridge, 79° N, Fram Strait. Lowest δ13C values were recorded in shells of Melonis barleeanus, − 5.2‰ in live specimens and − 6.5‰ in empty shells, from sediments dominated by aerobic (MOx) and anaerobic oxidation of methane (AOM), respectively. Our data indicate that foraminifera actively incorporate methane-derived carbon when living in sediments with moderate seepage activity, while in sediments with high seepage activity the poisonous sulfidic environment leads to death of the foraminifera and an overgrowth of their empty shells by methane-derived authigenic carbonates. We propose that the incorporation of methane-derived carbon in living foraminifera occurs via feeding on methanotrophic bacteria and/or incorporation of ambient dissolved inorganic carbon.

A comprehensive quality assessment of the ozone products from 18 limb-viewing satellite instruments is provided by means of a detailed intercomparison. The ozone climatologies in form of monthly zonal mean time series covering the upper troposphere to lower mesosphere are obtained from LIMS, SAGE I/II/III, UARS-MLS, HALOE, POAM II/III, SMR, OSIRIS, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, and SMILES within 1978–2010. The intercomparisons focus on mean biases of annual zonal mean fields, interannual variability, and seasonal cycles. Additionally, the physical consistency of the data is tested through diagnostics of the quasi-biennial oscillation and Antarctic ozone hole. The comprehensive evaluations reveal that the uncertainty in our knowledge of the atmospheric ozone mean state is smallest in the tropical and midlatitude middle stratosphere with a 1σ multi-instrument spread of less than ±5%. While the overall agreement among the climatological data sets is very good for large parts of the stratosphere, individual discrepancies have been identified, including unrealistic month-to-month fluctuations, large biases in particular atmospheric regions, or inconsistencies in the seasonal cycle. Notable differences between the data sets exist in the tropical lower stratosphere (with a spread of ±30%) and at high latitudes (±15%). In particular, large relative differences are identified in the Antarctic during the time of the ozone hole, with a spread between the monthly zonal mean fields of ±50%. The evaluations provide guidance on what data sets are the most reliable for applications such as studies of ozone variability, model-measurement comparisons, detection of long-term trends, and data-merging activities.

Abstract The corrosion influence on hydraulic pipelines safety mounted on product and chemical tankers has been presented in this paper. The issue of axial forces in pipelines mounted along ship open decks, resulting from ship hull deformations in waves, is highlighted. Corrosion degradation phenomena of hydraulic pipelines on open deck is described. The analysis of degradation effect on thickness of carbon steel material of pipes is given and influence of the effect on stress level increase in hydraulic pipelines during exploitation at sea is focused. The discussion about fighting against corrosion in hydraulic pipelines on open decks is performed. All the problems analyzed in the paper are based on examples of events observed on product and chemical tankers built in Szczecinska Shipyard, Szczecin, Poland.

A prominent question in transportation planning is how cities should regulate emerging modes, such as shared bikes and e-scooters. This pertains to a range of attributes, including pricing, use of the public right of way, number of vehicles in a fleet, and vehicle speeds. However, less attention has been paid to the way private operators spatially constrain access to their fleets, such as via the use of virtual geographic boundaries (hereafter “geofences”), or how municipalities have regulated these features. San Francisco, given it is home to a number of these schemes, presents a compelling case for studying geofences, and how regulators have sought to influence them to further public policy goals, including spatial equity. This study analyzes each bike and e-scooter geofence in San Francisco longitudinally from 2017 to 2019 via manual digitization of all geofences. This reveals high levels of overlap in the city’s dense northeast quadrant, with limited to no coverage in western neighborhoods. Each operator’s geofence expanded over this period, filling in gaps in the northeast quadrant and expanding outward in each direction. Review of permit guidelines and applications submitted by operators indicate that San Francisco’s regulations for geofences have been limited and inconsistent, which may have contributed to the concentration of services in one section of the city, as well as disconnected geofence “islands.” Together, these observations demonstrate that if broad geofence coverage (i.e., spatial equity) is an explicit municipal goal, such an aim must prominently feature into the regulatory process. This is particularly important given that operators, if left with freedom over geofence design, are likely to emphasize only a city’s densest areas, especially if tight caps are set on the allowed number of vehicles. Finally, this case also exemplifies that geofences are not drawn in a vacuum but instead relate to other permit conditions as well as pressure from community organizations.

Traction inverter has been the subject of many studies due to its essential role in the proper performance of the drive system. With the recent trend in increasing the input voltage in battery-powered electric vehicles, multilevel inverters have been proposed in the literature as a promising substitute for conventional two-level traction inverters. A critical aspect of utilizing multilevel structures is employing proper control and modulation techniques. The control system structure must be capable of handling a number of key issues, like capacitor voltage balancing and equal power loss sharing, which arise in multilevel topologies. This paper presents a review of the present-day traction drive systems in the industry, control and modulation techniques for multilevel structures in the inverters, as well as the principal challenges that need to be addressed in the control stage of the multilevel traction inverter. A comparison has been made between different methods based on the most important criteria and requirements of the traction drive system. Finally, future trends in this application are presented and some suggestions have been made for the next generation of traction drives.

City events are being organized more frequently, and with larger crowds, in urban areas. There is an increased need for novel methods and tools that can provide information on the sentiments of crowds as an input for crowd management. Previous work has explored sentiment analysis and a large number of methods have been proposed relating to various contexts. None of them, however, aimed at deriving the sentiments of crowds using social media in city events, and no existing event-based dataset is available for such studies. This paper investigates how social media can be used to estimate the sentiments of crowds in city events. First, some lexicon-based and machine learning-based methods were selected to perform sentiment analyses, then an event-based sentiment annotated dataset was constructed. The performance of the selected methods was trained and tested in an experiment using common and event-based datasets. Results show that the machine learning method LinearSVC achieves the lowest estimation error for sentiment analysis on social media in city events. The proposed event-based dataset is essential for training methods to reduce estimation error in such contexts.

The COVID-19 pandemic has led to the complete lockdown of many cities worldwide. Lockdowns have significantly changed human behaviour, such as fewer or no industrial activities and limited road and air transport, affecting the environment. In this study, we aimed to assess the variability and trends of PM2.5 (mass concentration of airborne particulate matter < 2.5µm) and carbon monoxide (CO) before and during the COVID-19 lockdown period in Sri Lanka. Data were collected in “Urban Background”, “Public & Mixed Residential”, and “Primary Residential” areas using small sensor technology, "KOALA" air quality sensor units, from five locations, three in Kandy, and two in Colombo city. Daily averages (24h) and daytime averages (08:00 AM to 8:00 PM) were calculated for the period before (before March 20th) and during (March 20th to May 10th) the lockdown. Air pollutions level before & during COVID-19 lockdown were compared, then Mann-Kendall and Sen's slope tests were performed to determine trends of PM2.5 and CO, and the magnitude of the trend. Meteorological parameters were fairly similar before and during both cities' lockdown periods, while both PM2.5 and CO concentrations declined. The highest average reductions of PM2.5 and CO were observed in Colombo's “Urban Background” area (52.4% and 46.7%, respectively). In Kandy, “Urban Background” site had a higher reduction of PM2.5 and CO (30.2% and 41.2%, respectively), compared to “Primary Residential” (10% and 9%, respectively). The daily averages of the pollutants' concentrations were higher before the lockdown period compared to during. Overall, a significant downward trend was observed of air pollutants over the entire study period. In Sri Lanka, the COVID-19 lockdown improved air quality significantly in urban areas.

Purpose. Improvement of existing methods for evaluation of condition and functioning quality of railway stations and development of the new ones in order to improve operation of railway stations. Methodology. During research the local, prognostic, aggregated and interactive analyses of condition and functioning quality of station infrastructure elements and train processing at the stations were applied. Local evaluations are obtained as the result of scheduled and off-schedule surveys. On the basis of local evaluations, aggregated evaluations of different generalization level are applied. Method for interactive evaluation is based on the analysis of compliance with train tables. Method of prognostic analysis applies the prehistory of evaluations obtained during previous surveys. Findings . Resulting from researches held, the complex determinative approach was proposed for evaluation of station sector of Ukrainian Railways. This approach allows determining comprehensive and objective notion about station, functioning quality and interaction between objects of station sector. Originality . Existing method for station infrastructure elements evaluation was improved. Proposed method for interactive evaluation allows performing continuous observation of station functioning quality between scheduled surveys. Practical value. Proposed methodology for complex evaluation may be applied to structural units of station sector of different hierarchy levels. Software developed allows navigating promptly over evaluation results and localizing drawbacks discovered.

Arctic Ocean primary productivity is limited by light and inorganic nutrients. With sea ice cover declining in recent decades, nitrate limitation has been speculated to become more prominent. Although much has been learned about nitrate supply from general patterns of ocean circulation and water column stability, a quantitative analysis requires dedicated turbulence measurements that have only started to accumulate in the last dozen years. Here we present new observations of the turbulent vertical nitrate flux in the Laptev Sea, Baffin Bay, and Young Sound (North-East Greenland), supplementing a compilation of 13 published estimates throughout the Arctic Ocean. Combining all flux estimates with a Pan-Arctic database of in situ measurements of nitrate concentration and density, we found the annual nitrate inventory to be largely determined by the strength of stratification and by bathymetry. Nitrate fluxes explained the observed regional patterns and magnitudes of both new primary production and particle export on annual scales. We argue that with few regional exceptions, vertical turbulent nitrate fluxes can be a reliable proxy of Arctic primary production accessible through autonomous and large-scale measurements. They may also provide a framework to assess nutrient limitation scenarios based on clear energetic and mass budget constraints resulting from turbulent mixing and freshwater flows.