Stations In Proximity Research Articles

Westerlies-driven transboundary transport of atmospheric mercury to the north-central Tibetan Plateau

The transboundary mercury (Hg) pollution has caused adverse effects on fragile ecosystems of the Tibetan Plateau (TP). Yet, knowledge of transport paths and source regions of atmospheric Hg on the inland TP remains poor. Continuous measurements of atmospheric total gaseous mercury (TGM) were conducted in the central TP (Tanggula station, 5100 m a.s.l., June–October). Atmospheric TGM level at Tanggula station (1.90 ± 0.30 ng m−3) was higher than the background level in the Northern Hemisphere. The identified high-potential source regions of atmospheric TGM were primarily located in the northern South Asia region. TGM concentrations were lower during the Indian summer monsoon (ISM)-dominant period (1.81 ± 0.25 ng m−3) than those of the westerly-receding period (2.18 ± 0.40 ng m−3) and westerly-intensifying period (1.91 ± 0.26 ng m−3), contrary to the seasonal pattern in southern TP. The distinct TGM minima during the ISM-dominant period indicated lesser importance of ISM-transported Hg to Tanggula station located in the northern boundary of ISM intrusion, compared to stations in proximity to South and Southeast Asia source regions. Instead, from the ISM-dominant period to the westerly-intensifying period, TGM concentrations showed an increasing trend as westerlies intensified, indicating the key role of westerlies in transboundary transport of atmospheric Hg to the inland TP.

Metro-line expansions and local air quality in Shenzhen: Focusing on network effects

We examine the air-quality effects of urban-rail development in Shenzhen, taking a difference-in-differences approach. This study is motivated by existing mixed evidence on the rail-pollution relationship, which we associate with the dynamic nature of the relationship itself. Our results demonstrate that the relationship varies by time, depending on network density and scale. New station openings had no significant impacts on local air quality or even worsened it until the 2010 metro-line extension, when Shenzhen’s metro network density was still low, with limited spatial service coverage. However, the 2016 extension significantly abated air pollution as the network grew denser and more comprehensive. The rail-driven anti-pollution effects tended to be further strengthened with externalities arising from improved network connectivity, spilling over the effects beyond newly opened stations to preexisting ones. Also, metro stations in proximity to neighborhoods that share key characteristics in transit-oriented development tended to generate a greater anti-pollution effect.

Quantifying N2 fixation and its contribution to export production near the Tonga-Kermadec Arc using nitrogen isotope budgets

The spatial distribution of marine di-nitrogen (N2) fixation informs our understanding of the sensitivities of this process as well as the potential for this new nitrogen (N) source to drive export production, influencing the global carbon (C) cycle and climate. Using geochemically-derived δ15N budgets, we quantified rates of N2 fixation and its importance for supporting export production at stations sampled near the southwest Pacific Tonga-Kermadec Arc. Recent observations indicate that shallow (<300 m) hydrothermal vents located along the arc provide significant dissolved iron to the euphotic zone, stimulating N2 fixation. Here we compare measurements of water column δ15NNO3+NO2 with sinking particulate δ15N collected by short-term sediment traps deployed at 170 m and 270 m at stations in close proximity to subsurface hydrothermal activity, and the δ15N of N2 fixation. Results from the δ15N budgets yield high geochemically-based N2 fixation rates (282 to 638 µmol N m-2 d-1) at stations impacted by hydrothermal activity, supporting 64 to 92% of export production in late spring. These results are consistent with contemporaneous 15N2 uptake rate estimates and molecular work describing high Trichodesmium spp. and other diazotroph abundances associated with elevated N2 fixation rates. Further, the δ15N of sinking particulate N collected at 1000 m over an annual cycle revealed sinking fluxes peaked in the summer and coincided with the lowest δ15N, while lower winter sinking fluxes had the highest δ15N, indicating isotopically distinct N sources supporting export seasonally, and aligning with observations from most other δ15N budgets in oligotrophic regions. Consequently, the significant regional N2 fixation input to the late spring/summer Western Tropical South Pacific results in the accumulation of low-δ15NNO3+NO2 in the upper thermocline that works to lower the elevated δ15NNO3+NO2 generated in the oxygen deficient zones in the Eastern Tropical South Pacific.

Long-Term Assessment of Bioclimatic Conditions at Micro and Local Scales in the Cities of the Western Part of the Balkan Peninsula during the 21st Century

Thermal comfort assessments at local or micro-scales within urban areas can provide crucial insights for the urban adaptation strategies pertaining to climate-conscious urban planning and public health. However, the availability of long-term or mid-term daily or hourly meteorological data sets from urban environments remains a significant challenge even in the 21st century. Consequently, this study aimed to assess the thermal conditions in cities across the western part of the Balkan Peninsula, encompassing five countries (Slovenia, Croatia, Serbia, Bosnia and Herzegovina, and Montenegro), by utilizing the Physiological Equivalent Temperature (PET) index. Meteorological data sets, comprising air temperature, relative humidity, wind speed, and cloudiness, were collected from 32 national meteorological stations/measurement locations spanning the period from 2001 to 2020. The PET calculations were conducted based on meteorological data measured three times per day (7 a.m., 2 p.m., and 9 p.m.). Upon conducting a spatial analysis of the meteorological stations, it was observed that most of them (25 stations) were situated within built-up areas or urban suburbs, rendering them highly relevant for local or micro-scale climate and bioclimate assessments. The findings revealed that urban locations exhibited slightly higher PET heat stress levels, particularly during the summer season and at 2 p.m. Moreover, higher average PET values were observed in both urban and non-urban stations situated within a continental climate during warmer periods, such as summer. In contrast, during the colder seasons, namely winter and spring, higher PET values were prevalent in the Mediterranean region. Furthermore, the PET frequency analysis revealed a greater prevalence of extreme and severe heat stress levels in stations within continental climates, particularly those located in urban areas, as compared to stations in Mediterranean climates. In contrast, during the winter and spring seasons, monitoring stations in close proximity to the Adriatic Sea, characterized by a Mediterranean climate, exhibited significantly lower levels of cold stress compared to inland stations. Evidently, in addition to the climatic characteristics and surrounding terrain, the urban morphology significantly impacts the thermal conditions within cities.

Towards a high-resolution modelling scheme for local-scale urban flood risk assessment based on digital aerial photogrammetry

With the rapid development of cities and the impact of climate change, cities located near rivers are facing an increasingly serious flood threat. Urban flood risk prediction management is pressing. The peak discharge and duration are important factors in urban flood management as well as the important characteristics of flood hygrograph. Mostly, hydrological model is used to obtain the upstream flood hygrograph to drive inundation model. However, lack of information on reservoirs, barrage structures and land use make it difficult to construct high-precision hydrological models, especially in upstream cities where data is lacking. In this study, therefore, we propose an approach to urban flood management based on measured flood data from urban hydrological stations in close proximity to derive flood hydrography for different return periods, and establish a high-precision urban-scale river flood risk management method by combining with Unmanned Aerial Vehicle (UAV) survey data. This method can allow information on river construction and underlying surface change to be introduced into the flood hygrograph implicitly, thus avoiding the difficulty of establishing hydrological and hydrodynamic coupling of the whole basin. The applicability and accuracy of the methodology are explored in this article with reference to Chenxi City in the upper reaches of Yuanshui River. Comparison the flood process of the 10-year with the actual flood in 2016 indicates that the extent of inundation is strongly dependent on the instantaneous discharge, with the peak flow largely determining the maximum inundation extent and risk level. This illustrates the feasibility of risk assessment of urban flooding based on flood hygrograph with different period levels derived from measured flood processes at adjacent sites. Subsequently, the different return periods scenario is simulated and analyzed. This approach provides technical guidance for flood risk assessment in areas where data is lacking (e.g., upstream mountainous cities).

Community structure of abyssal macrobenthos of the South and equatorial Atlantic Ocean - Identifying patterns and environmental controls

The DIVA (Latitudinal Gradients of Deep-sea BiodDIVersity in the Atlantic) expeditions studied benthic biodiversity of the abyssal Equatorial and South Atlantic as part of the Census of the Diversity of Abyssal Marine Life (CeDAMar), the abyssal component of the ten-year programme Census of Marine Life (2000–2010). Three expeditions were carried out from RV Meteor between 2000 and 2009. Samples were taken along a latitudinal gradient spanning the Cape, Angola, and Guinea basins in the SE Atlantic and the Argentine and Brazilian basins in the SW Atlantic. The objectives of this study were to analyse patterns of epi- and suprabenthic macrofaunal density and composition at higher taxon level from epibenthic sledge (EBS) taken during the DIVA sampling campaigns and how they relate to differences in environmental conditions. In particular, the different oceanic basins are characterized by variation in surface primary productivity, sedimentary properties, and depth. We expected this difference to be reflected in the structure of the abyssal benthic communities. Consistent with this hypothesis, we found significant differences in macrofauna density between different deep-sea basins, mainly related to food availability. However, only subtle differences in community composition were observed. We found that stations in close proximity to one another showed great variability in both macrofaunal density and composition. We conclude that smaller spatial scale sampling should be paired with higher taxonomic resolution analyses of macrofaunal samples to better understand the factors contributing to variations of macrobenthic communities in the deep sea.

Marine aerosols in coastal areas and their impact on cave drip water – A monitoring study from Northern Spain

Marine aerosols affect coastal environments and human infrastructure, hence assessing the marine aerosol deposition in coastal areas is important. Field observations of marine aerosol deposition in coastal regions is commonly limited to a single station at high temporal resolution, which does not provide strong constraints on the spatial changes in the rate of aerosol delivery over the first 10 km distance from the coast, a gradient with the potential to constrain scavenging terms in aerosol models. Here, we provide data of monthly marine aerosol deposition (wet and dry) within the first 10 km from the coast during a 15-month monitoring study. Along a transect, a strong decrease of marine aerosols (Na, Mg, S and K) in the first 3 km from the coast but little decrease between 3 and 10 km is found. Based on fluxes of Na, the most conservative component measured and most completely attributed to marine aerosol sources, overall dry aerosol deposition decreases by nearly 20 to 30-fold from the coast to the station 10 km inland. Wet and dry marine aerosol deposition is significantly increased during the windy season (October until March), which is also the season of higher precipitation. The wind effect on aerosol deposition was greatest at the coast and diminished inland: between October and November 2019, the 3-fold increase in cumulative wind speed above the whitecap threshold caused a nearly 10-fold increase in the most proximal site, a 4-fold increase in 3.2 km sites, but only a 2-fold increase in dry aerosol deposition in the most distal sites. Independent of the season, the aerosol deposition rate >3 km from the coast drops to less than 20% of the most coast proximal station. Comparison of elemental ratios with seawater composition confirms the marine origin of Na and Mg in aerosols, but indicates additional sources and sinks for other elements (S and K) which do not correspond with expected marine sources. Furthermore, we test the time-integrated aerosol deposition in shallow groundwaters intercepted as cave drip waters from 13 caves, which confirm the decreasing contribution with distance from the coast but also reveal additional effects on the natural capture of wet and dry aerosols such as wind shielding effects and vegetation cover. The Na/Mg ratio of drip waters can be used to assess the significance of marine aerosols vs. bedrock to cave waters in the present day.

Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity.

The next generation 6G wireless systems are envisioned to have higher reliability and capacity than the existing cellular systems. The reconfigurable intelligent surfaces (RISs)-assisted wireless networks are one of the promising solutions to control the wireless channel by altering the electromagnetic properties of the signal. The dual connectivity (DC) increases the per-user throughput by utilizing radio resources from two different base stations. In this work, we propose the RIS-assisted DC system to improve the per-user throughput of the users by utilizing resources from two base stations (BSs) in proximity via different RISs. Given an -fair utility function, the joint resource allocation and the user scheduling of a RIS-assisted DC system is formulated as an optimization problem and the optimal user scheduling time fraction is derived. A heuristic is proposed to solve the formulated optimization problem with the derived optimal user scheduling time fractions. Exhaustive simulation results for coverage and throughput of the RIS-assisted DC system are presented with varying user, BS, blockage, and RIS densities for different fairness values. Further, we show that the proposed RIS-assisted DC system provides significant throughput gain of 52% and 48% in certain scenarios when compared to the existing benchmark and DC systems.

A record of microplastic in the marine nearshore waters of South Georgia

The polar plastics research community have recommended the spatial coverage of microplastic investigations in Antarctica and the Southern Ocean be increased. Presented here is a baseline estimate of microplastics in the nearshore waters of South Georgia, the first in situ study of the north-east coast of the island. Our results show that the microplastic concentration in seawater at twelve stations in proximity to King Edward Point Research Station ranged from 1.75 ± 5.17 MP/L (mean ± SD), approximately one order of magnitude higher than similar studies of sea surface waters south of the Polar Front. Levels of microplastics in freshwater (sampled from Gull Lake) and precipitation (collected adjacent to the research station) were 2.67 ± 3.05 MP/L, and 4.67 ± 3.21 MP/L respectively. There was no significant difference in the microplastic concentration between seawater sites, and no significant bilateral relationship between concentration and distance from the research station outlets. We report an average concentration of 1.66 ± 3.00 MP/L in wastewater collected from the research station but overall, the counts of microplastics were too low to attach any statistical significance to the similarity in the microplastic assemblages of seawater and wastewater, or assemblages retrieved from penguin species in the region in other studies. Using a calculation described in contemporary literature we estimate the number of microfibres potentially being released from ships and stations annually in the region but acknowledge that further samples are needed to support the figures generated. More extensive research into microplastic distribution, characteristics, and transport in the region is recommended to fully compute the level of risk which this pollutant represents to the ecosystem health of this remote region.

130: PATTERN OF LYMPH NODE METASTASES IN GASTRIC CANCER—A SIDE-STUDY OF THE MULTICENTER LOGICA-TRIAL

Abstract Background and aim The relation between tumor characteristics and the pattern of lymph node (LN) metastases in gastric cancer is unclear, especially following neoadjuvant chemotherapy (NAC). Therefore, the aim of this study is to analyze the pattern of LN metastases of gastric cancer. Methods Individual LN stations were separately collected (no. 7–9, 11 and 12a) or clearly marked at the resection specimen (no. 1–6), and were analyzed for all patients included in the LOGICA-trial. The LOGICA-trial was a multicenter randomized trial comparing laparoscopic versus open gastrectomy in ten hospitals. Total and distal D2-gastrectomy were performed for resectable gastric cancer (cT1–4aN0–3bM0). The pattern of metastases per LN station was related to tumor location, cT-stage, Lauren classification and NAC-treatment. In addition, the distribution of LN metastases over the individual LN stations was assessed for four subgroups based on tumor location, cT-stage, Lauren classification and NAC-treatment, and several combinations of these characteristics. Results Between 2015–2018, 212 patients underwent D2-gastrectomy, of whom 158 (75%) received NAC. LN metastases were present in 121 patients (57%). Proximal tumors metastasized predominantly to proximal LN stations (no. 1, 2, 7 and 9; OR > 1, P < 0,05), and distal tumors to distal LN stations (no. 5, 6 and 8; OR > 1, P > 0,05). However, distal tumors still metastasized to proximal LN stations, and vice versa. Each individual LN station (no. 1–9, 11 and 12a) showed metastases, regardless of the tumor location, cT-stage, histological subtype and NAC-treatment, including station 12a for cT1N0-tumors. Although LN metastases were present more frequently in cT3–4- versus cT1–2-stage (59% versus 51%; P = 0,259) and in diffuse versus intestinal tumors (66% versus 52%; P = 0,048), the pattern of LN metastases was similar for these subgroups. A sensitivity analysis was performed with only the NAC-treated patients to test the robustness of these results, which showed a similar pattern of LN metastases after NAC. Conclusion Although the pattern of LN metastases is related to tumor location in gastric cancer, metastatic spread occurred in all LN stations (no. 1–9, 11 and 12a), regardless of the tumor location, cT-stage (including cT1N0-tumors), histological subtype and NAC-treatment. Therefore, all LN stations (including 12a; D2-lymphadenectomy) should be routinely dissected during gastrectomy.

A Graph Neural Network with Spatio-Temporal Attention for Multi-Sources Time Series Data: An Application to Frost Forecast.

Frost forecast is an important issue in climate research because of its economic impact on several industries. In this study, we propose GRAST-Frost, a graph neural network (GNN) with spatio-temporal architecture, which is used to predict minimum temperatures and the incidence of frost. We developed an IoT platform capable of acquiring weather data from an experimental site, and in addition, data were collected from 10 weather stations in close proximity to the aforementioned site. The model considers spatial and temporal relations while processing multiple time series simultaneously. Performing predictions of 6, 12, 24, and 48 h in advance, this model outperforms classical time series forecasting methods, including linear and nonlinear machine learning methods, simple deep learning architectures, and nongraph deep learning models. In addition, we show that our model significantly improves on the current state of the art of frost forecasting methods.

Machine learning regression models for prediction of multiple ionospheric parameters

• Machine learning regression models to predict multiple ionospheric parameters. • Forecasting of f0F2, hmF2 and TEC parameters up to 1 h in the mid-latitude region. • Performance comparison of DT, RF and SVM regression models. • A novel approach as a dataset of digisonde and GNSS stations in close proximity. The variation of the ionospheric parameters has a crucial role in space weather, communication, and navigation applications. In this research, we analyze the prediction performance of three machine learning (ML) regression models, decision trees, random forest and support vector machine algorithms for the F2-layer critical frequency (f0F2), F2-layer height of the peak electron density (hmF2), and total electron content (TEC). The hourly f0F2 and hmF2 values of ROME (RO041) digisonde and hourly TEC values of a close by International GNSS Service (IGS) station (site code M0SE00ITA) were obtained for the period between January 1, 2012 and 31 December 2013. The inputs to be trained in the proposed methods are the observation periods of the data (sine and cosine of the day of year and hour of the day), hourly values of solar index F10.7 and geomagnetic index Ap, the present values of f0F2(t), hmF2(t), TEC(t), and their values at t − 23 h. The outputs are the predicted values of f0F2, hmF2, TEC at t + 1. The 2012 values of these parameters were used to train the models and they were predicted 1 h in advance during 2013. The root mean square error (RMSE) values between observed and predicted data were compared for the whole year, summer, winter, and equinox periods. The results showed that proposed ML regression models were successful in the prediction of multiple ionospheric parameters, but random forest regression provides more accurate prediction results than support vector machine and decision trees.

Intra-Day Solar Power Forecasting Strategy for Managing Virtual Power Plants

Solar energy penetration has been on the rise worldwide during the past decade, attracting a growing interest in solar power forecasting over short time horizons. The increasing integration of these resources without accurate power forecasts hinders the grid operation and discourages the use of this renewable resource. To overcome this problem, Virtual Power Plants (VPPs) provide a solution to centralize the management of several installations to minimize the forecasting error. This paper introduces a method to efficiently produce intra-day accurate Photovoltaic (PV) power forecasts at different locations, by using free and available information. Prediction intervals, which are based on the Mean Absolute Error (MAE), account for the forecast uncertainty which provides additional information about the VPP node power generation. The performance of the forecasting strategy has been verified against the power generated by a real PV installation, and a set of ground-based meteorological stations in geographical proximity have been used to emulate a VPP. The forecasting approach is based on a Long Short-Term Memory (LSTM) network and shows similar errors to those obtained with other deep learning methods published in the literature, offering a MAE performance of 44.19 W/m2 under different lead times and launch times. By applying this technique to 8 VPP nodes, the global error is reduced by 12.37% in terms of the MAE, showing huge potential in this environment.

Transit-oriented development and historic preservation across the United States: A geospatial analysis

The article examines the spatial relationship between the location of fixed-transit stations in proximity to historic districts and buildings across the United States. This study cross-linked data from the federal National Register of Historic Places database (and parallel sources at state and local historic registers) with a national data source on transit-oriented development (TOD). Findings revealed that half of all transit station areas (area within a half-mile around fixed-route transit stations) intersect with a federally designated national historic district. Moreover, 15.6% of all transit stations in the United States are located within a historic district, and 9.5% of nationally registered historic buildings are within half-mile of a fixed station. The study also found that more than half of all individually listed historic buildings in station areas were located in stations categorized as TODs. There was also a closer spatial cross-linkage between historic resources in higher density and more transit-oriented New Jersey than in Florida. Thus, there is some spatial relationship between the location of fixed-route transit stations and the location of historic resources, albeit the closeness of this interconnection varies by place. That spatial interconnections evokes consideration of how TOD and historic preservation can be complimentary “good neighbors.”

Dynamic User Allocation in Stochastic Mobile Edge Computing Systems

Mobile edge computing (MEC) is a new distributed computing paradigm where edge servers are deployed at, or near cellular base stations in close proximity to end-users. This offers computing resources at the edge of the network, facilitating a highly accessible platform for real-time, latency-sensitive services. A typical MEC environment is highly stochastic with random user arrivals and departures over time. Here, we address the user allocation problem from a service provider's perspective, who needs to allocate its users to the cloud or edge servers in a specific area. A user, who has a multi-dimensional resource requirement, can be allocated to either the remote cloud, which incurs a high latency, or an edge server, which results in a low latency but might require the user to wait in a queue. This article aims to achieve a controllable trade-off between performance (throughput) and several associated costs such as queuing delay and latency costs. We model this problem as a stochastic optimization problem, propose SUAC (Stochastic User AlloCation) – an online Lyapunov optimization-based algorithm, and prove its performance bounds. The experimental results demonstrate that SUAC outperforms existing approaches, effectively allocating users with a desired trade-off while keeping the system strongly stable.

Timetable Optimization for Metro Lines Connecting to Intercity Railway Stations to Minimize Passenger Waiting Time

In major metropolitan cities, metro and intercity rail services usually share stations or have stations in close proximity to facilitate smooth connections for passengers. A large number of passengers may arrive on metro platforms within a short period of time upon the arrivals of intercity trains, while the number may drop significantly afterward. This injected passenger demand is not coped well by the metro timetable with the commonly adopted regular train headway. Focusing on metro lines connecting to intercity railways, this study puts forward a timetable model to optimize train headways at each station, assuming all passengers board the first train available. The objective is to minimize the total waiting time of passengers at platforms throughout the metro line, without changing the number of vehicle trips. To calculate the passenger waiting time accurately, a mathematical model is proposed to obtain the number of transfer passengers arriving at metro platform in each time interval, based on arrivals of intercity trains and transfer facilities at the station. A genetic algorithm, combined with interior-point algorithm, is developed to obtain the solution of the proposed timetable model. Real-life case studies show that the optimized timetable reduces the total passenger waiting time when compared with the current timetable and the solution of another model optimizing train departure times at the first station only. In addition, the peak number of passengers congregating at metro platforms drops significantly, which relieves passenger crowding on the platform.

Determination of the local magnitudes of small earthquakes using a dense seismic array in the Changning−Zhaotong Shale Gas Field, Southern Sichuan Basin

With the development of unconventional shale gas in the southern Sichuan Basin, seismicity in the region has increased significantly in recent years. Though the existing sparse regional seismic stations can capture most earthquakes with <inline-formula><tex-math id="M1">\begin{document}$ {M}_{\mathrm{L}}\ge 2.5 $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M1.jpg"></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M1.png"></graphic></alternatives></inline-formula>, a great number of smaller earthquakes are often omitted due to limited detection capacity. With the advent of portable seismic nodes, many dense arrays for monitoring seismicity in the unconventional oil and gas fields have been deployed, and the magnitudes of those earthquakes are key to understand the local fault reactivation and seismic potentials. However, the current national standard for determining the local magnitudes was not specifically designed for monitoring stations in close proximity, utilizing a calibration function with a minimal resolution of 5 km in the epicentral distance. That is, the current national standard tends to overestimate the local magnitudes for stations within short epicentral distances, and can result in discrepancies for dense arrays. In this study, we propose a new local magnitude formula which corrects the overestimated magnitudes for shorter distances, yielding accurate event magnitudes for small earthquakes in the Changning−Zhaotong shale gas field in the southern Sichuan Basin, monitored by dense seismic arrays in close proximity. The formula is used to determine the local magnitudes of 7,500 events monitored by a two-phased dense array with several hundred 5 Hz 3C nodes deployed from the end of February 2019 to early May 2019 in the Changning−Zhaotong shale gas field. The magnitude of completeness (<inline-formula><tex-math id="M2">\begin{document}$ {M}_{\mathrm{C}} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M2.jpg"></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M2.png"></graphic></alternatives></inline-formula>) using the dense array is −0.1, compared to <inline-formula><tex-math id="M3">\begin{document}$ {M}_{\mathrm{C}} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M3.jpg"></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M3.png"></graphic></alternatives></inline-formula> 1.1 by the sparser Chinese Seismic Network (CSN). In addition, using a machine learning detection and picking procedure, we successfully identify and process some 14,000 earthquakes from the continuous waveforms, a ten-fold increase over the catalog recorded by CSN for the same period, and the <inline-formula><tex-math id="M4">\begin{document}$ {M}_{\mathrm{C}} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M4.jpg"></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M4.png"></graphic></alternatives></inline-formula> is further reduced to −0.3 from −0.1 compared to the catalog obtained via manual processing using the same dense array. The proposed local magnitude formula can be adopted for calculating accurate local magnitudes of future earthquakes using dense arrays in the shale gas fields of the Sichuan Basin. This will help to better characterize the local seismic risks and potentials.

Temporal Modulation of the Local Microseism in the North Sea

AbstractPrimary and secondary microseism originating in the world oceans and peaking at around 14 and 7 s, respectively, characterize the Earth's background noise in that frequency range. Microseism generated in marginal seas with partly shorter periods and higher spatial and temporal variability is less studied and requires stations in immediate proximity to the source to be observed. Such studies can help to elucidate the exact microseism generation areas and mechanisms in a constrained area. We analyze 15 years of broadband data recorded at the seismic station on Helgoland island in the marginal North Sea. In addition to remote primary (RPM) and secondary microseism (RSM) originating in the North Atlantic, we observe strong and dominant local secondary microseism (LSM) with on average higher frequencies above 0.2 Hz, in accordance with shorter wave periods of about 4–8 s in the shallow North Sea. During times with low RSM activity we observe local primary microseism (LPM) at frequencies in agreement with local ocean wave periods. The higher horizontal to vertical (H/V) ratio of LPM with respect to LSM indicates a major non‐Rayleigh wave contribution. LSM and LPM show a strong modulation with local semidiurnal ocean tides and microseism energy maxima preceding the water level maximum by 2.5 and 1.5 hr, respectively. This time shift might be influenced by stronger currents during rising than falling tides. Active sources of tide‐modulated microseism migrate along the North Sea coast in sync with the ocean tidal signal as evidenced by comparison of LSM maxima at stations distributed along the coast.

Towards reconciling seismic and geodetic moment estimations: Case Bárðarbunga

Previous studies have found discrepancies concerning the seismic radiation between planar and curved faults: moment tensor (MT) interpretations, seismic moment estimation and waveforms change dramatically when the rupture is not planar. Therefore, assuming a point source on a planar fault for earthquakes in volcanic environments can be an oversimplification that needs to be addressed if we observe some seismological clues. We study MT inversions for the biggest earthquakes during the 2014–2015 collapse of the Bárðarbunga caldera, which show non-double couple solutions, with vertical compression axis. We calculate synthetic seismograms for partial-ring ruptures using an ideal seismic network, and one emulating the existing monitoring network at Bárðarbunga. Observations using distal stations can return a better-constrained seismic moment, but they fail to characterise the dynamics involved. On the other hand, using proximal stations we obtain a reliable representation of the forces involved. However, the seismic moment is systematically overestimated due to the proximity to the curved source and the corresponding focusing effects. Finally, we correct the area of rupture due to fault shape to estimate the real cumulative seismic moment during the caldera collapse. The result shows a closer relationship between seismic and geodetic moment. In particular, both estimations match when we use a realistic rigidity for a volcanic environment.

Analysis of Methods for Determining Climate Loads at a Specified Territory Point by Meteorological Data

Methods for determining the characteristic values of climate loads at the location of a building have been perfected. Based on comparative analysis, the method of levelling the values of climate loads with an exponential or triangular weight function is recommended. For four climate loads, appropriate equalization intervals are determined, ensuring the maximum amount of weather data taken into account, while maintaining their uniformity. In construction, the determination of the climate load is important for the location of the building. When prescribing building standards, the values of the climate load are determined according to the data of weather stations in relative proximity, which provides values within the limits of reliability. Such an approach can lead to an overestimation of the characteristic values of climate loads and consequently increase the consumption of the construction materials of the building or, in the opposite case, decrease the unnecessarily high-energy consumption to condition the space inside the building.