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Topic Review
Ordovician–Silurian Extinction Events
The Ordovician–Silurian extinction events, when combined, are the second-largest of the five major extinction events in Earth's history in terms of percentage of genera that became extinct. This event greatly affected marine communities, which caused the disappearance of one third of all brachiopod and bryozoan families, and further numerous groups of conodonts, trilobites, and graptolites. The Ordovician–Silurian extinction occurred during the Hirnantian stage of the Ordovician Period and the subsequent Rhuddanian stage of the Silurian Period. The last event, the Late Ordovician mass extinction (LOME), is dated in the interval of 455 to 430 million years ago, lasting from the Middle Ordovician to Early Silurian, thus including the extinction period. This event was the first of the big five Phanerozoic events and was the first to significantly affect animal-based communities. In May 2020, geologists reported that this mass extinction, the Late Ordovician mass extinction, 445 million years ago, may have been the result of global warming. Almost all major taxonomic groups were affected during this extinction event. Extinction was global during this period, eliminating 49–60% of marine genera and nearly 85% of marine species. Brachiopods, bivalves, echinoderms, bryozoans and corals were particularly affected. Before the late Ordovician cooling, temperatures were relatively warm and it is the suddenness of the climate changes and the elimination of habitats due to sea-level fall that are believed to have precipitated the extinctions. The falling sea level disrupted or eliminated habitats along the continental shelves. Evidence for the glaciation was found through deposits in the Sahara Desert. A combination of lowering of sea level and glacially driven cooling were likely driving agents for the Ordovician mass extinction.
  • 2.9K
  • 23 Oct 2022
Topic Review
Ordnance Survey
Ordnance Survey (OS) is the national mapping agency for Great Britain. The agency's name indicates its original military purpose (see ordnance and surveying), which was to map Scotland in the wake of the Jacobite rising of 1745. There was also a more general and nationwide need in light of the potential threat of invasion during the Napoleonic Wars. Since 1 April 2015 Ordnance Survey has operated as Ordnance Survey Ltd, a government-owned company, 100% in public ownership. The Ordnance Survey Board remains accountable to the Secretary of State for Business, Energy and Industrial Strategy. It was also a member of the Public Data Group. Paper maps for walkers represent only 5% of OS' annual revenue. They produce digital map data, online route planning and sharing services and mobile apps, plus many other location-based products for business, government and consumers. Ordnance Survey mapping is usually classified as either "large-scale" (in other words, more detailed) or "small-scale". The Survey's large-scale mapping comprises 1:2,500 maps for urban areas and 1:10,000 more generally. (The latter superseded the 1:10,560 "six inches to the mile" scale in the 1950s.) These large scale maps are typically used in professional land-use contexts and were available as sheets until the 1980s, when they were digitised. Small-scale mapping for leisure use includes the 1:25,000 "Explorer" series, the 1:50,000 "Landranger" series and the 1:250,000 road maps. These are still available in traditional sheet form. Ordnance Survey maps remain in copyright for fifty years after their publication. Some of the Copyright Libraries hold complete or near-complete collections of pre-digital OS mapping.
  • 857
  • 14 Oct 2022
Topic Review
Orbital Effects on Climate
There are various solar/celestial effects that exist which have an effect on Earth's climate. These effects usually occur in cycles, and primarily include how Earth's obliquity, the eccentricity of Earth's orbit, and the precession of the equinoxes and solstices affect Earth's climate. In addition to these effects, there are also other factors that have an effect on Earth's climate. These other factors include how sun activity affects climate and how celestial phenomena, such as meteors, affect Earth's climate. Some of these factors aren't yet well understood, for instance the ice ages occur on 100,000 year cycles, and it's not completely understood why the various effects with this periodicity have such a strong effect on glaciation (see the 100,000-year problem).
  • 766
  • 24 Nov 2022
Topic Review
Optimizing Sustainability Opportunities for Biochar
Biochar is most commonly considered for its use as a soil amendment, where it has gained attention for its potential to improve agricultural production and soil health. Twenty years of near exponential growth in investigation has demonstrated that biochar does not consistently deliver these benefits, due to variables in biochar, soil, climate, and cropping systems. While biochar can provide agronomic improvements in marginal soils, it is less likely to do so in temperate climates and fertile soils. Here, biochar and its coproducts may be better utilized for contaminant remediation or the substitution of nonrenewable or mining-intensive materials. 
  • 694
  • 18 Oct 2021
Topic Review
Optimized Deep Learning Model for Flood Detection
The increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection models, deep learning techniques are extensively used in flood control.
  • 301
  • 27 Oct 2023
Topic Review Peer Reviewed
Optimization Examples for Water Allocation, Energy, Carbon Emissions, and Costs
The field of Water Resources Management (WRM) is becoming increasingly interdisciplinary, realizing its direct connections with energy, food, and social and economic sciences, among others. Computationally, this leads to more complex models, wherein the achievement of multiple goals is sought. Optimization processes have found various applications in such complex WRM problems. This entry considers the main factors involved in modern WRM, and puts them in a single optimization problem, including water allocation from different sources to different uses and non-renewable and renewable energy supplies, with their associated carbon emissions and costs. The entry explores the problem mathematically by presenting different optimization approaches, such as linear, fuzzy, dynamic, goal, and non-linear programming models. Furthermore, codes for each model are provided in Python, an open-source language. This entry has an educational character, and the examples presented are easily reproducible, so this is expected to be a useful resource for students, modelers, researchers, and water managers.
  • 131
  • 08 Feb 2024
Topic Review
Optimal Interpolation for infrared satellite data
Thermal infrared remote sensing measurements are blinded to surface emissions under cloudiness because infrared sensors cannot penetrate thick cloud layers. Therefore, surface and atmospheric parameters can be retrieved only in clear sky conditions giving origin to spatial fields flagged with missing pieces of information. Motivated by this we present a methodology to retrieve missing values of some interesting geophysical variables retrieved from spatially scattered infrared satellite observations in order to yield level 3 (L3), regularly gridded, data. The technique is based on a 2-Dimensional (2D) Optimal Interpolation (OI) scheme. The goodness of the approach has been tested on 15-min temporal resolution Spinning Enhanced Visible and Infrared Imager (SEVIRI) emissivity and surface temperature (ST) products over South Italy (land and sea), on Infrared Atmospheric Sounding Interferometer (IASI) atmospheric ammonia (NH3) concentration over North Italy and carbon monoxide (CO), sulfur dioxide (SO2) and NH3 concentrations over China. Sea surface temperature (SST) retrievals have been compared with gridded data from MODIS (Moderate-resolution Imaging Spectroradiometer) observations. For gases concentration, we have considered data from 3 different emission inventories, that is, Emissions Database for Global Atmospheric Research v3.4.2 (EDGARv3.4.2), the Regional Emission inventory in ASiav3.1 (REASv3.1) and MarcoPolov0.1, plus an independent study.
  • 745
  • 30 Oct 2020
Topic Review
Optical Sensors
Detection systems using optical principles for ion sensing have become widely used. Optical detection typically relies on the color change resulting from the interaction or reaction between the focal object and the detection reagent. Optical sensors offer the advantages of simplicity and low cost. At the same time, there is no direct contact between the sensor and the sample during analysis, thereby minimizing the effects of contamination of the sensing probe. The portable optical sensors highlighted in this section include fluorescent, colorimetric, Raman scattering, surface plasmon resonance (SPR), and localized surface plasmon resonance (LSPR) sensors.
  • 552
  • 05 May 2023
Topic Review
Opportunities of Concentrated Solar Power
Concentrated solar power (CSP) has been considered an emerging technology that could disrupt the energy production sector. The possibility to store the electricity generated during the sunny operating hours in the form of heat enhances energy dispatchability and gives CSP a unique value proposition that conventional renewable energies cannot provide cost-efficiently since it requires the integration of costly large-scale battery systems. 
  • 1.0K
  • 10 May 2021
Topic Review
OpenMI Standard
The OpenMI (Open Modeling Interface) Standard defines an interface that allows models to exchange data in memory at run-time. When the standard is implemented, existing models can be run simultaneously and share information, for instance at each time step, making model integration feasible at the operational level. The OpenMI standard was created with the intent to facilitate model integration, which is helpful in understanding and predicting process interactions and achieving an integrated approach to environmental management. The OpenMI standard is owned and maintained by the OpenMI Association, an open, not for profit group of international organizations and people. On the 1st of July 2014 the Open Geospatial Consortium (OGC®) membership has approved the Open Modelling Interface Standard Version 2 (OpenMI) as an OGC standard.
  • 361
  • 15 Nov 2022
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