ALBERT

Description / Table of Contents: Frederiks, E.; Stenner, K.; Hobman, E. The Socio-Demographic and Psychological Predictors of Residential Energy Consumption: A Comprehensive Review. Energies 2015, 8(1), 573-609; doi:10.3390/en8010573 --- Sun, W.; He, Y.; Chang, H. Forecasting Fossil Fuel Energy Consumption for Power Generation Using QHSA-Based LSSVM Model. Energies 2015, 8(2), 939-959; doi:10.3390/en8020939 --- Gutierrez-Escolar, A.; Castillo-Martinez, A.; Gomez-Pulido, J.; Gutierrez-Martinez, J.; Stapic, Z.; Medina-Merodio, J. A Study to Improve the Quality of Street Lighting in Spain. Energies 2015, 8(2), 976-994; doi:10.3390/en8020976 --- Chew, K.; Klemeš, J.; Alwi, S.; Manan, Z.; Reverberi, A. Total Site Heat Integration Considering Pressure Drops. Energies 2015, 8(2), 1114-1137; doi:10.3390/en8021114 --- Kim, S.; Shin, K.; Choi, B.; Jo, J.; Cho, S.; Cho, Y. A Study on the Variation of Heating and Cooling Load According to the Use of Horizontal Shading and Venetian Blinds in Office Buildings in Korea. Energies 2015, 8(2), 1487-1504; doi:10.3390/en8021487 --- Sheng, P.; Yang, J.; Shackman, J. Energy’s Shadow Price and Energy Efficiency in China: A Non-Parametric Input Distance Function Analysis. Energies 2015, 8(3), 1975-1989; doi:10.3390/en8031975 --- Benavides, C.; Gonzales, L.; Diaz, M.; Fuentes, R.; García, G.; Palma-Behnke, R.; Ravizza, C. The Impact of a Carbon Tax on the Chilean Electricity Generation Sector. Energies 2015, 8(4), 2674-2700; doi:10.3390/en8042674 --- Li, W.; Li, H.; Sun, S. China’s Low-Carbon Scenario Analysis of CO2 Mitigation Measures towards 2050 Using a Hybrid AIM/CGE Model. Energies 2015, 8(5), 3529-3555; doi:10.3390/en8053529 --- Nasirov, S.; Silva, C.; Agostini, C. Investors’ Perspectives on Barriers to the Deployment of Renewable Energy Sources in Chile. Energies 2015, 8(5), 3794-3814; doi:10.3390/en8053794 --- Deng, X.; Yu, Y.; Liu, Y. Temporal and Spatial Variations in Provincial CO2 Emissions in China from 2005 to 2015 and Assessment of a Reduction Plan. Energies 2015, 8(5), 4549-4571; doi:10.3390/en8054549 --- Klimscheffskij, M.; Van Craenenbroeck, T.; Lehtovaara, M.; Lescot, D.; Tschernutter, A.; Raimundo, C.; Seebach, D.; Timpe, C. Residual Mix Calculation at the Heart of Reliable Electricity Disclosure in Europe—A Case Study on the Effect of the RE-DISS Project. Energies 2015, 8(6), 4667-4696; doi:10.3390/en8064667 --- Ferrara, R. The Smart City and the Green Economy in Europe: A Critical Approach. Energies 2015, 8(6), 4724-4734; doi:10.3390/en8064724 --- Stenner, K.; Nwokora, Z. Current and Future Friends of the Earth: Assessing Cross-National Theories of Environmental Attitudes. Energies 2015, 8(6), 4899-4919; doi:10.3390/en8064899 --- Atlason, R.; Oddsson, G.; Unnthorsson, R. Theorizing for Maintenance Management Improvements: Using Case Studies from the Icelandic Geothermal Sector. Energies 2015, 8(6), 4943-4962; doi:10.3390/en8064943 --- Ellenbeck, S.; Beneking, A.; Ceglarz, A.; Schmidt, P.; Battaglini, A. Security of Supply in European Electricity Markets—Determinants of Investment Decisions and the European Energy Union. Energies 2015, 8(6), 5198-5216; doi:10.3390/en8065198 --- Hasager, C.; Vincent, P.; Badger, J.; Badger, M.; Di Bella, A.; Peña, A.; Husson, R.; Volker, P. Using Satellite SAR to Characterize the Wind Flow around Offshore Wind Farms. Energies 2015, 8(6), 5413-5439; doi:10.3390/en8065413 --- Puigjaner, L.; Pérez-Fortes, M.; Laínez-Aguirre, J. Towards a Carbon-Neutral Energy Sector: Opportunities and Challenges of Coordinated Bioenergy Supply Chains-A PSE Approach. Energies 2015, 8(6), 5613-5660; doi:10.3390/en8065613 --- Thollander, P.; Palm, J. Industrial Energy Management Decision Making for Improved Energy Efficiency—Strategic System Perspectives and Situated Action in Combination. Energies 2015, 8(6), 5694-5703; doi:10.3390/en8065694 --- Jänicke, M. Horizontal and Vertical Reinforcement in Global Climate Governance. Energies 2015, 8(6), 5782-5799; doi:10.3390/en8065782 --- Benavides, C.; Gonzales, L.; Diaz, M.; Fuentes, R.; García, G.; Palma-Behnke, R.; Ravizza, C. Correction: The Impact of a Carbon Tax on the Chilean Electricity Generation Sector. Energies 2015, 8(6), 6247-6248; doi:10.3390/en8066247 --- Wang, W.; Ouyang, W.; Hao, F. A Supply-Chain Analysis Framework for Assessing Densified Biomass Solid Fuel Utilization Policies in China. Energies 2015, 8(7), 7122-7139; doi:10.3390/en8077122 --- Punys, P.; Dumbrauskas, A.; Kasiulis, E.; Vyčienė, G.; Šilinis, L. Flow Regime Changes: From Impounding a Temperate Lowland River to Small Hydropower Operations. Energies 2015, 8(7), 7478-7501; doi:10.3390/en8077478 --- Reid, G.; Wynn, G. The Future of Solar Power in the United Kingdom. Energies 2015, 8(8), 7818-7832; doi:10.3390/en8087818 --- Scott, C.; Sugg, Z. Global Energy Development and Climate-Induced Water Scarcity—Physical Limits, Sectoral Constraints, and Policy Imperatives. Energies 2015, 8(8), 8211-8225; doi:10.3390/en8088211 --- Lilliestam, J.; Patt, A. Barriers, Risks and Policies for Renewables in the Gulf States. Energies 2015, 8(8), 8263-8285; doi:10.3390/en8088263 --- Van Ackere, S.; Van Eetvelde, G.; Schillebeeckx, D.; Papa, E.; Van Wyngene, K.; Vandevelde, L. Wind Resource Mapping Using Landscape Roughness and Spatial Interpolation Methods. Energies 2015, 8(8), 8682-8703; doi:10.3390/en8088682 --- Komendantova, N.; Vocciante, M.; Battaglini, A. Can the BestGrid Process Improve Stakeholder Involvement in Electricity Transmission Projects?. Energies 2015, 8(9), 9407-9433; doi:10.3390/en8099407 --- Kiyar, D.; Wittneben, B. Carbon as Investment Risk—The Influence of Fossil Fuel Divestment on Decision Making at Germany’s Main Power Providers. Energies 2015, 8(9), 9620-9639; doi:10.3390/en8099620 --- Bernardes, L.; Carneiro, J.; Madureira, P.; Brandão, F.; Roque, C. Determination of Priority Study Areas for Coupling CO2 Storage and CH4 Gas Hydrates Recovery in the Portuguese Offshore Area. Energies 2015, 8(9), 10276-10292; doi:10.3390/en80910276 --- Dovì, V.; Battaglini, A. Energy Policy and Climate Change: A Multidisciplinary Approach to a Global Problem. Energies 2015, 8(12), 13473-13480; doi:10.3390/en81212379

Description / Table of Contents: Water covers approximately 71% of the planet’s surface and human activities have been relying on it since remote times. Many traces of these exist under the “zero level” and will continue to exist in the future. Measuring, positioning, and mapping objects under water have experienced very significant modifications, brought about by advances in technology and also by changed requirements, demands for new products, introduction of new tools, and the modification of existing equipment. The exploration, documentation, and recording of underwater environments remains a difficult task, and is sometimes still unsolved. The research, design, and development of techniques and procedures for correctly validating underwater environments are more than ever important. This Special Issue originates from the ISPRS/CIPA Workshop "UNDERWATER 3D RECORDING & MODELING—Experiences in Data Acquisition, Calibration, Orientation, Modelling & Accuracy Assessment” (http://3dom.fbk.eu/files/underwater/index.html).

Description / Table of Contents: The reversible elimination of hydrogen from metal hydrides serves as the basis for unique methods of energy transformation. This technology has found widespread practical utilization in applications such as hydrogen compressors, storage, and sensors, as well as batteries. Moreover, it is plausible that metal hydride technology could be utilized to provide practically viable solutions to the challenges of energy storage. For nearly two decades, an extensive, worldwide research effort has been devoted to complex metal hydrides possessing high volumetric and/or gravimetric hydrogen densities with the goal of their practical utilization as onboard hydrogen storage materials. Additionally, a significant and growing number of efforts have been devoted to developing metal hydrides as advanced sensors and ionic conductors, and for electrochemical and stationary energy storage. This Special Issue will provide a sampling of on-going, state-of-art research on metal hydrides, ranging from fundamental investigations to practical applications with a concentration on topics which are currently of high interest.

Description / Table of Contents: As the fields of organometallic and coordination chemistry of the transition metals has grown more mature, the under-explored chemistry of the rare-earths and actinides has drawn the attention of research groups from across the globe looking for new fundamental discoveries and access to compounds with unique properties. The rare earths – the group 3 metals and the 4f lanthanide series – have long shown many interesting properties in the solid state which exploit their unique electronic configurations. However, it is the molecular chemistry of these metals that has expanded dramatically in recent years as researchers identify the differences between – and unique features of – their molecular compounds. Recent highlights include the identification of new oxidation states and patterns of reactivity as well as applications in medical imaging and health care which represent new and exciting areas of research. The actinides show a wide range of different properties as a consequence of their radioactivity and radiochemistry, but this has not stopped recent rapid progress into the exploration of their unique chemistry. Uranium, in particular, shows huge potential with its transition metal like range of oxidation states (+2 to +6), and in specialised laboratories, the heavier actinides are also beginning to show their unique chemistry as well. This Special Issue aims to bring together these strands of research in an openly-accessible way to allow better communication of these advances to a wider audience. This is necessary as despite these exciting advances, the rare earths and actinides are still much neglected topics in both school and undergraduate curriculums.

Description / Table of Contents: Wang, X.; Wang, R.; Wei, Q.; Wang, P.; Wei, J. Mineralogical and Geochemical Characteristics of Late Permian Coals from the Mahe Mine, Zhaotong Coalfield, Northeastern Yunnan, China. Minerals 2015, 5(3), 380-396; doi:10.3390/min5030380. http://www.mdpi.com/2075-163X/5/3/380 --- Hower, J.; Eble, C.; O'Keefe, J.; Dai, S.; Wang, P.; Xie, P.; Liu, J.; Ward, C.; French, D. Petrology, Palynology, and Geochemistry of Gray Hawk Coal (Early Pennsylvanian, Langsettian) in Eastern Kentucky, USA. Minerals 2015, 5(3), 592-622; doi:10.3390/min5030511. http://www.mdpi.com/2075-163X/5/3/0511 --- Devasahayam, S.; Ameen, M.; Verheyen, T.; Bandyopadhyay, S. Brown Coal Dewatering Using Poly (Acrylamide-Co-Potassium Acrylic) Based Super Absorbent Polymers. Minerals 2015, 5(4), 623-636; doi:10.3390/min5040512. http://www.mdpi.com/2075-163X/5/4/0512 --- Wang, X.; Feng, Q.; Sun, R.; Liu, G. Radioactivity of Natural Nuclides (40K, 238U, 232Th, 226Ra) in Coals from Eastern Yunnan, China. Minerals 2015, 5(4), 637-646; doi:10.3390/min5040513. http://www.mdpi.com/2075-163X/5/4/0513 --- Yang, N.; Tang, S.; Zhang, S.; Chen, Y. Mineralogical and Geochemical Compositions of the No. 5 Coal in Chuancaogedan Mine, Junger Coalfield, China. Minerals 2015, 5(4), 788-800; doi:10.3390/min5040525. http://www.mdpi.com/2075-163X/5/4/0525 --- Jia, J.; Li, X.; Wu, P.; Liu, Y.; Han, C.; Zhou, L.; Yang, L. Human Health Risk Assessment and Safety Threshold of Harmful Trace Elements in the Soil Environment of the Wulantuga Open-Cast Coal Mine. Minerals 2015, 5(4), 837-848; doi:10.3390/min5040528. http://www.mdpi.com/2075-163X/5/4/0528 --- Wang, G.; Luo, Z.; Zhang, J.; Zhao, Y. Modes of Occurrence of Fluorine by Extraction and SEM Method in a Coal-Fired Power Plant from Inner Mongolia, China. Minerals 2015, 5(4), 863-869; doi:10.3390/min5040530. http://www.mdpi.com/2075-163X/5/4/0530 --- Zhao, L.; Ward, C.; French, D.; Graham, I. Major and Trace Element Geochemistry of Coals and Intra-Seam Claystones from the Songzao Coalfield, SW China. Minerals 2015, 5(4), 870-893; doi:10.3390/min5040531. http://www.mdpi.com/2075-163X/5/4/0531 --- Johnston, M.; Hower, J.; Dai, S.; Wang, P.; Xie, P.; Liu, J. Petrology and Geochemistry of the Harlan, Kellioka, and Darby Coals from the Louellen 7.5-Minute Quadrangle, Harlan County, Kentucky. Minerals 2015, 5(4), 894-918; doi:10.3390/min5040532. http://www.mdpi.com/2075-163X/5/4/0532 --- Liu, S.; Qi, C.; Zhang, S.; Deng, Y. Minerals in the Ash and Slag from Oxygen-Enriched Underground Coal Gasification. Minerals 2016, 6(2), 27; doi:10.3390/min6020027. http://www.mdpi.com/2075-163X/6/2/27 --- Xiao, L.; Zhao, B.; Duan, P.; Shi, Z.; Ma, J.; Lin, M. Geochemical Characteristics of Trace Elements in the No. 6 Coal Seam from the Chuancaogedan Mine, Jungar Coalfield, Inner Mongolia, China. Minerals 2016, 6(2), 28; doi:10.3390/min6020028. http://www.mdpi.com/2075-163X/6/2/28 --- Xie, P.; Song, H.; Wei, J.; Li, Q. Mineralogical Characteristics of Late Permian Coals from the Yueliangtian Coal Mine, Guizhou, Southwestern China. Minerals 2016, 6(2), 29; doi:10.3390/min6020029. http://www.mdpi.com/2075-163X/6/2/29 --- Hower, J.; Granite, E.; Mayfield, D.; Lewis, A.; Finkelman, R. Notes on Contributions to the Science of Rare Earth Element Enrichment in Coal and Coal Combustion Byproducts. Minerals 2016, 6(2), 32; doi:10.3390/min6020032. http://www.mdpi.com/2075-163X/6/2/32 --- Liu, H.; Sun, Q.; Wang, B.; Wang, P.; Zou, J. Morphology and Composition of Microspheres in Fly Ash from the Luohuang Power Plant, Chongqing, Southwestern China. Minerals 2016, 6(2), 30; doi:10.3390/min6020030. http://www.mdpi.com/2075-163X/6/2/30 --- Dang, J.; Xie, Q.; Liang, D.; Wang, X.; Dong, H.; Cao, J. The Fate of Trace Elements in Yanshan Coal during Fast Pyrolysis. Minerals 2016, 6(2), 35; doi:10.3390/min6020035. http://www.mdpi.com/2075-163X/6/2/35 --- Yang, N.; Tang, S.; Zhang, S.; Chen, Y. Modes of Occurrence and Abundance of Trace Elements in Pennsylvanian Coals from the Pingshuo Mine, Ningwu Coalfield, Shanxi Province, China. Minerals 2016, 6(2), 40; doi:10.3390/min6020040. http://www.mdpi.com/2075-163X/6/2/40 --- Zhao, L.; Dai, S.; Graham, I.; Wang, P. Clay Mineralogy of Coal-Hosted Nb-Zr-REE-Ga Mineralized Beds from Late Permian Strata, Eastern Yunnan, SW China: Implications for Paleotemperature and Origin of the Micro-Quartz. Minerals 2016, 6(2), 45; doi:10.3390/min6020045. http://www.mdpi.com/2075-163X/6/2/45 --- Zou, J.; Tian, H.; Li, T. Geochemistry and Mineralogy of Tuff in Zhongliangshan Mine, Chongqing, Southwestern China. Minerals 2016, 6(2), 47; doi:10.3390/min6020047. http://www.mdpi.com/2075-163X/6/2/47 --- Yang, L.; Song, J.; Bai, X.; Song, B.; Wang, R.; Zhou, T.; Jia, J.; Pu, H. Leaching Behavior and Potential Environmental Effects of Trace Elements in Coal Gangue of an Open-Cast Coal Mine Area, Inner Mongolia, China. Minerals 2016, 6(2), 50; doi:10.3390/min6020050. http://www.mdpi.com/2075-163X/6/2/50 --- Wang, X.; Zhang, L.; Jiang, Y.; Wei, J.; Chen, Z. Mineralogical and Geochemical Characteristics of the Early Permian Upper No. 3 Coal from Southwestern Shandong, China. Minerals 2016, 6(3), 58; doi:10.3390/min6030058. http://www.mdpi.com/2075-163X/6/3/58 --- Giménez-García, R.; Vigil de la Villa Mencía, R.; Rubio, V.; Frías, M. The Transformation of Coal-Mining Waste Minerals in the Pozzolanic Reactions of Cements. Minerals 2016, 6(3), 64; doi:10.3390/min6030064. http://www.mdpi.com/2075-163X/6/3/64 --- Wang, R. Geological Controls on Mineralogy and Geochemistry of an Early Permian Coal from the Songshao Mine, Yunnan Province, Southwestern China. Minerals 2016, 6(3), 66; doi:10.3390/min6030066. http://www.mdpi.com/2075-163X/6/3/66 --- Luo, Y.; Zheng, M. Origin of Minerals and Elements in the Late Permian Coal Seams of the Shiping Mine, Sichuan, Southwestern China. Minerals 2016, 6(3), 74; doi:10.3390/min6030074. http://www.mdpi.com/2075-163X/6/3/74

Description / Table of Contents: Reliable access to water, managing the spatial and temporal variability of water availability, ensuring the quality of freshwater and responding to climatological changes in the hydrological cycle are prerequisites for the development of countries in Africa. Water being an essential input for biomass growth and for renewable energy production (e.g. biofuels and hydropower schemes) plays an integral part in ensuring food and energy security for any nation. Water, as a source of safe drinking water, is furthermore the basis for ensuring the health of citizens and plays an important role in urban sanitation. The concept of Integrated Water Resource Management (IWRM) is seen as an opportunity to help manage water variability and the wide spread water scarcity in Africa. One key component missing from IWRM in Africa is the limited knowledge of the available extent and quality of water resources at basin level. Earth Observation (EO) technology can help fill this information gap by assessing and monitoring water resources at adequate temporal and spatial scales. The goal of this Special Issue is to understand and demonstrate the contribution which satellite observations, consistent over space and time, can bring to improve water resource management in Africa. Possible EO products and applications range from catchment characterization, water quality monitoring, soil moisture assessment, water extent and level monitoring, irrigation services, urban and agricultural water demand modeling, evapotranspiration estimation, ground water management, to hydrological modeling and flood mapping/forecasting. Some of these EO applications have already been developed by African scientists within the 10 year lifetime of the TIGER initiative: Looking after Water in Africa (http://www.tiger.esa.int), whose contributions are intended to be the starting point of this Special Issue and is only one example of the wide range of activities in the field. Contributions from the entire African and international scientific community dealing with the challenges of water resource management in Africa are the target of the special issue. In the years to come, an ever increasing number of international EO missions, such as the Landsat, ALOS, CBERS and RESOURCESAT mission suites, the family of Sentinel missions and the SMAP mission, will provide an unprecedented capacity to observe and monitor the different components of the water cycle. This Special Issue aims also at reviewing the latest developments in terms of new missions as well as related EO products and techniques that will be available in the near future to face some of the major challenges for IWRM in Africa.

Description / Table of Contents: Water is not only an interesting object to be studied on its own, it also is an important component driving almost all ecological processes occurring in our landscapes. Plant growth depends on soil water content, as well is nutrient turnover by microbes. Water shapes the environment by erosion and sedimentation. Species occur or are lost depending on hydrological conditions, and many infectious diseases are water-borne. Modeling the complex interactions of water and ecosystem processes requires the prediction of hydrological fluxes and stages on the one side and the coupling of the ecosystem process model on the other. While much effort has been given to the development of the hydrological model theory in recent decades, we have just begun to explore the difficulties that occur when coupled model applications are being set up.

Description / Table of Contents: The pulse width of an electromagnetic wave is determined by the frequency band width of the wave used. Therefore, one femtosecond is the ultimate in pulse width for an “optical” wave. For this reason, several methods have been proposed for the generation of an ultrashort optical pulse. For example, resonance/non-resonance four-wave mixing would be one of the candidates for generating multi-color laser emission in an extremely wide spectral region, thus breaking the 1-fs barrier. To date, numerous emission lines have been generated from the deep-ultraviolet to the near-infrared region (〈45,000 cm−1). Such generations use a variety of techniques, such as four-wave Raman mixing in molecular hydrogen. This type of technique is promising for the generation of 1-fs optical pulses via phase locking and the Fourier synthesis of the emission lines. For verification, it would be necessary to develop a new method for measuring the pulse width, since the spectral band width approaches or is beyond one octave. Ultrashort optical pulses can be utilized in a variety of applications in science and technology. For example, an ultrashort optical pulse can be used in the studies of ultrafast phenomena. More practically, a laser pulse shorter than 100 fs is reported to be useful in mass spectrometry for observing a molecular ion of triacetone triperoxide, an explosive used in terrorist attacks. A train of ultrashort optical pulses in the terahertz region, which has been generated in the optical cavity to enhance the nonlinear optical effect, would be employed as a clock pulse in optical computation/communication in future advanced industries.

Description / Table of Contents: The success of the Suomi National Polar-orbiting Partnership (NPP) brings us into a new era of global daily Earth observations, ranging from the faintest light of human settlements and air glows to the dramatic events of hurricanes and forest fires, as well as the subtle changes in the planet Earth which we call home. At the heart of all satellite applications, calibration/validation of the measurements and derived products is the key. Satellite product calibration and validation have become increasingly more important and challenging in order to meet the stringent requirements for accurate quantitative data for climate change detection, numerical weather prediction, and environmental intelligence. Validation is required not only for the satellite measurements, but also for all geophysical retrievals, including aerosols, cloud properties, radiation budget, sea surface temperature, ocean color, active fire, albedo, snow and ice, vegetation, as well as nightlights from human settlements. Active validation research includes but not limited to, comparisons with similar products from other satellites, with in situ, aircraft measurements, or observations from other platforms. Validation results not only help users and decision makers but also serve as feedback to calibration, which in turn improves the products. This Special Issue of Remote Sensing aims at exploring recent results in the calibration and validation of the Suomi National Polar-orbiting Partnership satellite (Suomi NPP)/JPSS radiometers.

Description / Table of Contents: The present Special Issue intends to explore new directions in the field of acoustics and ultrasonics. The interest includes, but is not limited to, the use of acoustic technology for condition monitoring of materials and structures. (The basis of this issue comes from selected papers of the 6th International Conference on Emerging Technologies in Non-destructive Testing, ETNDT6 held in Brussels May 27-29th, 2015).

Description / Table of Contents: Polar microbiology is a promising field of research that can tell us much about the fundamental features of life. The microorganisms that inhabit Arctic and Antarctic environments are important not only because of the unique species they represent, but also because of their diverse and unusual physiological and biochemical properties. Furthermore, microorganisms living in Polar Regions provide useful models for general questions in ecology and evolutionary biology given the reduced complexity of their ecosystems, the relative absence of confounding effects associated with higher plants or animals, and the severe biological constraints imposed by the polar environment. In terms of applied science, the unique cold-adapted enzymes and other molecules of polar microorganisms provide numerous opportunities for biotechnological development. Another compelling reason to study polar microbial ecosystems is the fact that they are likely to be among the ecosystems most strongly affected by global change. For these reasons, polar microbiology is a thriving branch of science with the potential to provide new insights into a wide range of basic and applied issues in biological science. In this context, it is timely to review and highlight the progress so far and discuss exciting future perspectives. In this special issue, some of the leaders in the field describe their work, ideas and findings.

Description / Table of Contents: All living organisms are composed of major, minor, and trace elements, given by nature and supplied by geology. Medical geology is a rapidly growing discipline dealing with the influence of natural geological and environmental risk factors on the distribution of health problems in humans and animals. As a multi-disciplinary scientific field, medical geology has the potential of helping medical and public health communities all over the world in the pursuit of solutions to a wide range of environmental and naturally induced health issues. The natural environment can impact health in a variety of ways. The composition of rocks and minerals are imprinted on the air that we breathe, the water that we drink, and the food that we eat. For many people this transference of minerals and the trace elements they contain is beneficial as it is the primary source of nutrients (such as calcium, iron, magnesium, potassium, and about a dozen other elements) that are essential for a healthy life. However, sometimes the local geology can cause significant health problems because there is an insufficient amount of an essential element or an excess of a potentially toxic element (such as arsenic, mercury, lead, fluorine, etc.), or a harmful substance such as methane gas, dust-sized particles of asbestos, quartz or pyrite, or certain naturally occurring organic compounds. Current and future medical geology concerns include: dangerous levels of arsenic in drinking water in dozens of countries including the USA; mercury emissions from coal combustion and its bioaccumulation in the environment; the impacts of mercury and lead mobilizations in regions were artisanal gold mining is conducted; the residual health impacts of geologic processes such as volcanic emissions, earthquakes, tsunamis, hurricanes, and geogenic dust; exposure to fibrous minerals such as asbestos and erionite; and the health impacts of global climate change. Billions of people, most in developing countries, are afflicted by these and other environmental health issues that can be avoided, prevented, mitigated or minimized through research and educational outreach. This Special Issue of Geosciences discusses recent advances in medical geology, providing examples from research conducted all over the world. Among the topics to be discussed are: - Health effects from trace elements, metals and metalloids - Regional and global impacts of natural dust (including the study of nanoparticles) - Chemical and environmental pathology of diseases associated with natural environment - Novel analytical approaches to the study of natural geochemical and environmental agents - Research on beneficial health aspects of natural geological materials - Risk management, risk communication and risk mitigation on medical geology - Remote sensing and GIS applications on medical geology - Epidemiology and public health studies on medical geology - Climate change and medical geology - Clinical and toxicological research on biomarkers of exposure - Veterinary medical geology - Biosurveillance and biomonitoring studies on medical geology

Description / Table of Contents: This special issue contains selected papers from the 13th International Conference on Estuarine and Coastal Modeling (ECM13), held Nov 4-6, 2013. The conference brings modelers from academic institutions, government and private industry together to present and discuss the latest developments in the field of marine environmental modeling. Begun in 1989 by Dr. Malcolm Spaulding, the conference is held every other year in a retreat-like setting with a maximum of about 125 people to encourage interaction and help strengthen ties between modeling communities. A wide range of modeling issues are encouraged, including advances in physical understanding, numerical algorithm development, model applications, and better tools. A wide range of modeling topics are encouraged as well, including storm surge, eutrophication, larval transport, search and rescue, oil spills, fisheries issues, coastal erosion and contaminated sediment transport. Many conferences also have special themes. The special theme of ECM13 was modeling related to Hurricane Sandy which in late October 2012 devastated the Caribbean and the US East Coast, including record flooding in New York City. The 22 papers presented here cover a broad spectrum of topics, including simulations of cohesive sediment, inundation, effluent mixing, shoaling waves, and water quality and with modeling applications from Alaska to New Zealand.

Description / Table of Contents: Over the last decades, the study of extremophiles has providing ground breaking discoveries that challenge the paradigms of modern biology and make us rethink intriguing questions such as “what is life?”, “what are the limits of life?”, and “what are the fundamental features of life?”. The mechanisms by which different microorganisms adapt to extreme environments provide a unique perspective on the fundamental characteristics of biological processes present in most species. Extremophiles are also critical for evolutionary studies related to the origins of life, since they form a cluster on the base of the tree of life. Furthermore, the application of extremophiles in industrial processes has opened a new era in biotechnology. The study of extreme environments has become a key area of research for astrobiology. Extremophiles may help us understand what form life takes on other planetary bodies in our own solar system and beyond. These findings and possibilities have made the study of life in extreme environments one of the most exciting areas of research in recent decades. However, despite the latest advances we are just in the beginning of exploring and characterizing the world of extremophiles. This special issue covers all aspects of life in extreme environments.

Description / Table of Contents: In 1692, Newton wrote: "That gravity should be innate inherent and essential to matter so that one body may act upon another at a distance through a vacuum without the mediation of anything else by and through which their action or force may be conveyed from one to another is to me so great an absurdity that I believe no man who has in philosophical matters any competent faculty of thinking can ever fall into it. Gravity must be caused by an agent acting constantly according to certain laws, but whether this agent be material or immaterial is a question I have left to the consideration of my readers". One of them who, just over 200 years later, picked up the baton of Newton was Albert Einstein. His General Theory of Relativity, which marks the centenary this year, opened up new windows on our comprehension of Nature, disclosed new, previously unpredictable, phenomena occurring when relative velocities dramatically change in intense gravitational fields reaching values close to the speed of light and, for the first time after millennia of speculations, put Cosmology on the firm grounds of empirically testable science. This Special Issue is dedicated to such a grandest achievement of the human thought.

Description / Table of Contents: In the face of climate change and resource scarcity, energy supply systems are on the verge of a major transformation, which mainly includes the introduction of new components and their integration into the existing infrastructures, new network configurations and reliable topologies, optimal design and novel operation schemes, and new incentives and business models. This revolution is affecting the current paradigm and demanding that energy systems be integrated into multi-carrier energy hubs. It is greatly increasing the interactions between today’s energy systems at various scales (ranging from the multinational, national, community scales down to the building level) and future intelligent energy systems, which are able to incorporate an increasing amount of often fluctuating, renewable energy sources (RESs). It is also increases the need for the integration of energy storage options into the energy mix, not only to reduce the need for increased peak generation capacity, but also to enhance grid reliability and support higher penetration of RESs. Moreover, this transformation is accommodating active participation of end-users as responsive prosumers at different scales, which in turn help to reduce energy costs to all consumers, increase reliability of service and mitigate carbon footprints. However, this plan of action necessitates regulatory frameworks, strategic incentives and business models for efficient deployment. This Special Issue will cover these promising and dynamic areas of research and development, and will allow gathering of contributions in design, control and optimization of integrated energy systems. This Special Issue also seeks papers to report advances in any aspect of these developments. The manuscripts should be unpublished and report significant advancement.

Description / Table of Contents: The “landscape Approach” is widely promoted as a way to reconcile biodiversity conservation with both commercial agriculture and local peoples’ demands for land. Landscape approaches imply a strong role for local communities in decision making and, therefore, local citizen science plays a role in determining landscape outcomes (Sayer et al., under review). Many claims and counter claims are made about the success and failure of local management in achieving good forest outcomes. There is significant uncertainty about the incentives for local people to manage forests for their global carbon storage and biodiversity values. Local people may be more concerned about immediate economic returns and less about the long term global environmental values of their forests. This Special Issue seeks to assemble papers that provide empirical evidence for the success of landscape and community managed initiatives to conserve biodiversity. We are seeking papers that report upon successful biodiversity conservation projects that have operated at a landscape scale and those that have been led by local communities. We are also interested in cases where these approaches were attempted but were less successful. Our ultimate goals is to identify the conditions under which these approaches have succeeded and those where they have been less successful.

Description / Table of Contents: Nishimura, T. Rust Formation Mechanism on Low Alloy Steels after Exposure Test in High Cl− and High SOx Environmen. Materials 2017, 10(2), 199; doi:10.3390/ma10020199. http://www.mdpi.com/1996-1944/10/2/199 --- Chang, T.; Odnevall Wallinder, I.; de la Fuente, D.; Chico, B.; Morcillo, M.; Welter, J.; Leygraf, C. Analysis of Historic Copper Patinas. Influence of Inclusions on Patina Uniformity. Materials 2017, 10(3), 298; doi:10.3390/ma10030298. http://www.mdpi.com/1996-1944/10/3/298 --- Na, O.; Cai, X.; Xi, Y. Corrosion Prediction with Parallel Finite Element Modeling for Coupled Hygro-Chemo Transport into Concrete under Chloride-Rich Environment. Materials 2017, 10(4), 350; doi:10.3390/ma10040350. http://www.mdpi.com/1996-1944/10/4/350 --- Kreislova, K.; Knotkova, D. The Results of 45 Years of Atmospheric Corrosion Study in the Czech Republic. Materials 2017, 10(4), 394; doi:10.3390/ma10040394. http://www.mdpi.com/1996-1944/10/4/394 --- Alcántara, J.; Fuente, D.; Chico, B.; Simancas, J.; Díaz, I.; Morcillo, M. Marine Atmospheric Corrosion of Carbon Steel: A Review. Materials 2017, 10(4), 406; doi:10.3390/ma10040406. http://www.mdpi.com/1996-1944/10/4/406 --- Hosseinpour, S.; Johnson, M. Vibrational Spectroscopy in Studies of Atmospheric Corrosion. Materials 2017, 10(4), 413; doi:10.3390/ma10040413. http://www.mdpi.com/1996-1944/10/4/413 --- Panchenko, Y.; Marshakov, A. Prediction of First-Year Corrosion Losses of Carbon Steel and Zinc in Continental Regions. Materials 2017, 10(4), 422; doi:10.3390/ma10040422. http://www.mdpi.com/1996-1944/10/4/422 --- Chico, B.; de la Fuente, D.; Díaz, I.; Simancas, J.; Morcillo, M. Annual Atmospheric Corrosion of Carbon Steel Worldwide. An Integration of ISOCORRAG, ICP/UNECE and MICAT Databases. Materials 2017, 10(6), 601; doi:10.3390/ma10060601. http://www.mdpi.com/1996-1944/10/6/601 --- Bouchar, M.; Dillmann, P.; Neff, D. New Insights in the Long-Term Atmospheric Corrosion Mechanisms of Low Alloy Steel Reinforcements of Cultural Heritage Buildings. Materials 2017, 10(6), 670; doi:10.3390/ma10060670. http://www.mdpi.com/1996-1944/10/6/670 --- Tidblad, J.; Kreislová, K.; Faller, M.; de la Fuente, D.; Yates, T.; Verney-Carron, A.; Grøntoft, T.; Gordon, A.; Hans, U. ICP Materials Trends in Corrosion, Soiling and Air Pollution (1987–2014). Materials 2017, 10(8), 969; doi:10.3390/ma10080969. http://www.mdpi.com/1996-1944/10/8/969 --- Cole, I. Recent Progress and Required Developments in Atmospheric Corrosion of Galvanised Steel and Zinc. Materials 2017, 10(11), 1288; doi:10.3390/ma10111288. http://www.mdpi.com/1996-1944/10/11/1288

Description / Table of Contents: Climate change affects global and regional water cycling, as well as surficial and subsurface water availability. These changes have increased the vulnerabilities of ecosystems and of human society. Understanding how climate change has affected water resource variability in the past and how climate change is leading to rapid changes in contemporary systems is of critical importance for sustainable development in different parts of the world. This Special Issue focuses on “Water Resource Variability and Climate Change” and aims to present a collection of articles addressing various aspects of water resource variability as well as how such variabilities are affected by changing climates. Topics include the reconstruction of historic moisture fluctuations, based on various proxies (such as tree rings, sediment cores, and landform features), the empirical monitoring of water variability based on field survey and remote sensing techniques, and the projection of future water cycling using numerical model simulations. Articles are about recent discoveries related to water resource variability in paleoenvironmental reconstruction, hydrology, and geomorphology, as well as articles concerning new emerging technologies and their applications in monitoring water resource variability.

Description / Table of Contents: Today, sustainability of a healthy freshwater ecosystem and its associated ecosystem services are hot issues with ever-growing attention placed upon them. We are increasingly recognizing that they are crucial for the survival of the aquatic biota and human beings on our planet. The efficient monitoring of water resources is fundamental for effective management of water quality and aquatic ecosystems. The first stage in sustainable ecosystem management is the evaluation of the current status of target ecosystems. Traditionally, and even today, physico-chemical parameters have mainly been used to evaluate the quality of water resources. However, they have a large limit to grab the wholeness of water system, particularly in the sense of ecosystem health and integrity, for which ecological monitoring should be based on biological factors. Various approaches are applicable to ecosystem health assessment at different levels of the biological hierarchy, from genes to ecosystems. This Special Issue is designed to improve scientific understanding and strategies for sound aquatic ecosystem management and services for researchers, decision makers, and stakeholders.

Description / Table of Contents: The use of agent-based models (ABMs) and modelling for understanding landscape change and dynamics continues to grow. One reason for the popularity of ABMs is that they provide a framework to represent multiple, discrete, multi-faceted, heterogeneous actors (human or otherwise) and their relationships and interactions between one another and their environment, through time and across space. This special issue seeks to showcase innovative uses of ABMs for investigating and explaining landscape change and dynamics and to explore and identify how researchers in different disciplines can learn from one another to further innovate. Thus, this special issue will emphasise multidisciplinary dialogue between researchers using ABM in physical geography, hydrology, ecology, land change science, economics, alternative histories, archaeology, sociology, psychology and others. Innovation may come in the form of computational, conceptual, analytical, participatory or epistemological advances in the use of ABM for a range of aims and motivations associated with landscape change and dynamics. Modelling advances may include new ways of representing agent decisions and/or interactions, establishing and evaluating model structures and rules, presenting and visualising change, multi-scale analysis, comparative techniques, narrative methods, and more. The presentation of innovative agent-based modelling from diverse research backgrounds and perspectives will demonstrate opportunities for learning and enable dialogue to enhance future use of ABMs for understanding landscape change.

Description / Table of Contents: According to the 2014 revision of the World Urbanization Prospects by UN DESA, urbanization could add another 2.5 billion people to the urban population by 2050, with close to 90 percent of the increase concentrated in Asia and Africa. The largest urban growth will take place in India, China and Nigeria. This unprecedented increase in urban population not only poses challenges to providing urban jobs, housing, and infrastructure, but also exerts an increased pressure on urban land and sustainability. As land is a vital yet limited resource, sustainable management of urban land to cater to the needs of this growing urban population is seen as one of the key challenges for achieving an economically efficient, socially equitable, and environmentally safe society. A key tenet for sustainable economic development and smart growth is promoting sustainable urban land development and mitigating land use conflicts. While a large body of literature has dealt with both land use and sustainable development, the study of the interactive effects of these two remains limited. We also need more sophisticated empirical studies examining processes, mechanisms, institutions, equity, and sustainability of urban land use. We also encourage efforts to develop new theories, new concepts and new methods to understand the myriad ways in which urban land and sustainable development correlate each other. This special issue examines patterns, structure, and dynamics of urban land development and sustainability from multiple perspectives, in various contexts and at multiple dimensions (economic, social, political, developmental, environmental, etc.).

Description / Table of Contents: Atmospheric particulate matter (PM) is known to have far-ranging impacts, from human health to climate forcing. The characterization of emission sources and the quantification of specific source impacts to PM concentrations significantly enhance our understanding of and our ability to eventually predict the fate and transport of atmospheric PM and its associated impacts on humans and the environment. The source apportionment of PM has been realized through combinations of chemical analysis (of elemental tracers, particle size, isotopic composition, and organic composition via unique tracers and molecular fingerprints) and numerical modeling (e.g., diagnostic source ratios, chemical mass balance modeling, positive matrix factorization, and Monte Carlo simulations). Recent advances in source apportionment applications have contributed unique combinations of chemical and numerical techniques for determining the contributions of specific sources, including diesel exhaust and biomass burning. These advances also identify and help characterize the contributions of previously uncharacterized sources. Numerical modeling has also enabled estimations of contributions of emission sources to atmospherically processed PM in urban and rural regions.

Description / Table of Contents: Fu, R.; Wu, Y.; Wang, H.; Xie, J. A Distributed Control Strategy for Frequency Regulation in Smart Grids Based on the Consensus Protocol. Energies 2015, 8(8), 7930-7944; doi:10.3390/en8087930. http://www.mdpi.com/1996-1073/8/8/7930 --- Chae, W.; Lee, H.; Won, J.; Park, J.; Kim, J. Design and Field Tests of an Inverted Based Remote MicroGrid on a Korean Island. Energies 2015, 8(8), 8193-8210; doi:10.3390/en8088193. http://www.mdpi.com/1996-1073/8/8/8193 --- Nguyen, T.; Yoo, H.; Kim, H. Application of Model Predictive Control to BESS for Microgrid Control. Energies 2015, 8(8), 8798-8813; doi:10.3390/en8088798. http://www.mdpi.com/1996-1073/8/8/8798 --- Jung, S.; Jang, G. Development of an Optimal Power Control Scheme for Wave-Offshore Hybrid Generation Systems. Energies 2015, 8(9), 9009-9028; doi:10.3390/en8099009. http://www.mdpi.com/1996-1073/8/9/9009 --- Yang, Y.; Zhang, W.; Jiang, J.; Huang, M.; Niu, L. Optimal Scheduling of a Battery Energy Storage System with Electric Vehicles’ Auxiliary for a Distribution Network with Renewable Energy Integration. Energies 2015, 8(10), 10718-10735; doi:10.3390/en81010718. http://www.mdpi.com/1996-1073/8/10/10718 --- Xia, H.; Chen, H.; Yang, Z.; Lin, F.; Wang, B. Optimal Energy Management, Location and Size for Stationary Energy Storage System in a Metro Line Based on Genetic Algorithm. Energies 2015, 8(10), 11618-11640; doi:10.3390/en81011618. http://www.mdpi.com/1996-1073/8/10/11618 --- Telaretti, E.; Ippolito, M.; Dusonchet, L. A Simple Operating Strategy of Small-Scale Battery Energy Storages for Energy Arbitrage under Dynamic Pricing Tariffs. Energies 2016, 9(1), 12; doi:10.3390/en9010012. http://www.mdpi.com/1996-1073/9/1/12 --- Gelažanskas, L.; Gamage, K. Distributed Energy Storage Using Residential Hot Water Heaters. Energies 2016, 9(3), 127; doi:10.3390/en9030127. http://www.mdpi.com/1996-1073/9/3/127 --- Pietrosanti, S.; Holderbaum, W.; Becerra, V. Optimal Power Management Strategy for Energy Storage with Stochastic Loads. Energies 2016, 9(3), 175; doi:10.3390/en9030175. http://www.mdpi.com/1996-1073/9/3/175 --- Lin, F.; Li, X.; Zhao, Y.; Yang, Z. Control Strategies with Dynamic Threshold Adjustment for Supercapacitor Energy Storage System Considering the Train and Substation Characteristics in Urban Rail Transit. Energies 2016, 9(4), 257; doi:10.3390/en9040257. http://www.mdpi.com/1996-1073/9/4/257 --- Bruen, T.; Hooper, J.; Marco, J.; Gama, M.; Chouchelamane, G. Analysis of a Battery Management System (BMS) Control Strategy for Vibration Aged Nickel Manganese Cobalt Oxide (NMC) Lithium-Ion 18650 Battery Cells. Energies 2016, 9(4), 255; doi:10.3390/en9040255. http://www.mdpi.com/1996-1073/9/4/255 --- Chung, Y. A Novel Power-Saving Transmission Scheme for Multiple-Component-Carrier Cellular Systems. Energies 2016, 9(4), 265; doi:10.3390/en9040265. http://www.mdpi.com/1996-1073/9/4/265 --- Zangs, M.; Adams, P.; Yunusov, T.; Holderbaum, W.; Potter, B. Distributed Energy Storage Control for Dynamic Load Impact Mitigation. Energies 2016, 9(8), 647; doi:10.3390/en9080647. http://www.mdpi.com/1996-1073/9/8/647 --- Zhao, Z.; Sun, Y.; Hu, A.; Dai, X.; Tang, C. Energy Link Optimization in a Wireless Power Transfer Grid under Energy Autonomy Based on the Improved Genetic Algorithm. Energies 2016, 9(9), 682; doi:10.3390/en9090682. http://www.mdpi.com/1996-1073/9/9/682 --- Gatta, F.; Geri, A.; Lamedica, R.; Lauria, S.; Maccioni, M.; Palone, F.; Rebolini, M.; Ruvio, A. Application of a LiFePO4 Battery Energy Storage System to Primary Frequency Control: Simulations and Experimental Results. Energies 2016, 9(11), 887; doi:10.3390/en9110887. http://www.mdpi.com/1996-1073/9/11/887 --- Kies, A.; Schyska, B.; von Bremen, L. The Demand Side Management Potential to Balance a Highly Renewable European Power System. Energies 2016, 9(11), 955; doi:10.3390/en9110955. http://www.mdpi.com/1996-1073/9/11/955 --- Yang, J.; Choi, J.; An, G.; Choi, Y.; Kim, M.; Won, D. Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation. Energies 2016, 9(12), 1010; doi:10.3390/en9121010. http://www.mdpi.com/1996-1073/9/12/1010 --- Gao, Z.; Chin, C.; Woo, W.; Jia, J. Integrated Equivalent Circuit and Thermal Model for Simulation of Temperature-Dependent LiFePO4 Battery in Actual Embedded Application. Energies 2017, 10(1), 85; doi:10.3390/en10010085. http://www.mdpi.com/1996-1073/10/1/85 --- Yunusov, T.; Zangs, M.; Holderbaum, W. Control of Energy Storage. Energies 2017, 10(7), 1010; doi:10.3390/en10071010. http://www.mdpi.com/1996-1073/10/7/1010

Description / Table of Contents: Chen, K.; Zamora, N.; Babeyko, A.; Li, X.; Ge, M. Precise Positioning of BDS, BDS/GPS: Implications for Tsunami Early Warning in South China Sea. Remote Sensing 2015, 7(12), 15955-15968; doi:10.3390/rs71215814 --- Cianflone, G.; Tolomei, C.; Brunori, C.; Dominici, R. InSAR Time Series Analysis of Natural and Anthropogenic Coastal Plain Subsidence: The Case of Sibari (Southern Italy). Remote Sensing 2015, 7(12), 16004-16023; doi:10.3390/rs71215812 --- Kropáček, J.; Vařilová, Z.; Baroň, I.; Bhattacharya, A.; Eberle, J.; Hochschild, V. Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment. Remote Sensing 2015, 7(12), 16183-16203; doi:10.3390/rs71215821 --- Pacheco-Martínez, J.; Cabral-Cano, E.; Wdowinski, S.; Hernández-Marín, M.; Ortiz-Lozano, J.; Zermeño-de-León, M. Application of InSAR and Gravimetry for Land Subsidence Hazard Zoning in Aguascalientes, Mexico. Remote Sensing 2015, 7(12), 17035-17050; doi:10.3390/rs71215868 --- Al-Rawabdeh, A.; He, F.; Moussa, A.; El-Sheimy, N.; Habib, A. Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition. Remote Sensing 2016, 8(2), 95; doi:10.3390/rs8020095 --- Zhai, W.; Shen, H.; Huang, C.; Pei, W. Building Earthquake Damage Information Extraction from a Single Post-Earthquake PolSAR Image. Remote Sensing 2016, 8(3), 171; doi:10.3390/rs8030171 --- Jiang, Y.; Liao, M.; Zhou, Z.; Shi, X.; Zhang, L.; Balz, T. Landslide Deformation Analysis by Coupling Deformation Time Series from SAR Data with Hydrological Factors through Data Assimilation. Remote Sensing 2016, 8(3), 179; doi:10.3390/rs8030179 --- He, M.; Zhu, Q.; Du, Z.; Hu, H.; Ding, Y.; Chen, M. A 3D Shape Descriptor Based on Contour Clusters for Damaged Roof Detection Using Airborne LiDAR Point Clouds. Remote Sensing 2016, 8(3), 189; doi:10.3390/rs8030189 --- Hu, J.; Wang, Q.; Li, Z.; Zhao, R.; Sun, Q. Investigating the Ground Deformation and Source Model of the Yangbajing Geothermal Field in Tibet, China with the WLS InSAR Technique. Remote Sensing 2016, 8(3), 191; doi:10.3390/rs8030191 --- Hsieh, Y.; Chan, Y.; Hu, J. Digital Elevation Model Differencing and Error Estimation from Multiple Sources: A Case Study from the Meiyuan Shan Landslide in Taiwan. Remote Sensing 2016, 8(3), 199; doi:10.3390/rs8030199 --- Zhu, S.; Xu, C.; Wen, Y.; Liu, Y. Interseismic Deformation of the Altyn Tagh Fault Determined by Interferometric Synthetic Aperture Radar (InSAR) Measurements. Remote Sensing 2016, 8(3), 233; doi:10.3390/rs8030233 --- Vetrivel, A.; Gerke, M.; Kerle, N.; Vosselman, G. Identification of Structurally Damaged Areas in Airborne Oblique Images Using a Visual-Bag-of-Words Approach. Remote Sensing 2016, 8(3), 231; doi:10.3390/rs8030231 --- Bardi, F.; Raspini, F.; Ciampalini, A.; Kristensen, L.; Rouyet, L.; Lauknes, T.; Frauenfelder, R.; Casagli, N. Space-Borne and Ground-Based InSAR Data Integration: The Åknes Test Site. Remote Sensing 2016, 8(3), 237; doi:10.3390/rs8030237 --- Liu, P.; Li, Q.; Li, Z.; Hoey, T.; Liu, G.; Wang, C.; Hu, Z.; Zhou, Z.; Singleton, A. Anatomy of Subsidence in Tianjin from Time Series InSAR. Remote Sensing 2016, 8(3), 266; doi:10.3390/rs8030266 --- Ma, Y.; Chen, F.; Liu, J.; He, Y.; Duan, J.; Li, X. An Automatic Procedure for Early Disaster Change Mapping Based on Optical Remote Sensing. Remote Sensing 2016, 8(4), 272; doi:10.3390/rs8040272 --- Yang, C.; Zhang, Q.; Xu, Q.; Zhao, C.; Peng, J.; Ji, L. Complex Deformation Monitoring over the Linfen–Yuncheng Basin (China) with Time Series InSAR Technology. Remote Sensing 2016, 8(4), 284; doi:10.3390/rs8040284 --- Watanabe, M.; Thapa, R.; Shimada, M. Pi-SAR-L2 Observation of the Landslide Caused by Typhoon Wipha on Izu Oshima Island. Remote Sensing 2016, 8(4), 282; doi:10.3390/rs8040282 --- Plank, S.; Twele, A.; Martinis, S. Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data. Remote Sensing 2016, 8(4), 307; doi:10.3390/rs8040307 --- Solaro, G.; De Novellis, V.; Castaldo, R.; De Luca, C.; Lanari, R.; Manunta, M.; Casu, F. Coseismic Fault Model of Mw 8.3 2015 Illapel Earthquake (Chile) Retrieved from Multi-Orbit Sentinel1-A DInSAR Measurements. Remote Sensing 2016, 8(4), 323; doi:10.3390/rs8040323 --- Bai, L.; Jiang, L.; Wang, H.; Sun, Q. Spatiotemporal Characterization of Land Subsidence and Uplift (2009–2010) over Wuhan in Central China Revealed by TerraSAR-X InSAR Analysis. Remote Sensing 2016, 8(4), 350; doi:10.3390/rs8040350 --- Xu, B.; Li, Z.; Feng, G.; Zhang, Z.; Wang, Q.; Hu, J.; Chen, X. Continent-Wide 2-D Co-Seismic Deformation of the 2015 Mw 8.3 Illapel, Chile Earthquake Derived from Sentinel-1A Data: Correction of Azimuth Co-Registration Error. Remote Sensing 2016, 8(5), 376; doi:10.3390/rs8050376 --- Chen, M.; Tomás, R.; Li, Z.; Motagh, M.; Li, T.; Hu, L.; Gong, H.; Li, X.; Yu, J.; Gong, X. Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry. Remote Sensing 2016, 8(6), 468; doi:10.3390/rs8060468 --- Ji, L.; Xu, J.; Zhao, Q.; Yang, C. Source Parameters of the 2003–2004 Bange Earthquake Sequence, Central Tibet, China, Estimated from InSAR Data. Remote Sensing 2016, 8(6), 516; doi:10.3390/rs8060516 --- Li, Y.; Jiang, W.; Zhang, J.; Luo, Y. Space Geodetic Observations and Modeling of 2016 Mw 5.9 Menyuan Earthquake: Implications on Seismogenic Tectonic Motion. Remote Sensing 2016, 8(6), 519; doi:10.3390/rs8060519 --- Trasatti, E.; Tolomei, C.; Pezzo, G.; Atzori, S.; Salvi, S. Deformation and Related Slip Due to the 2011 Van Earthquake (Turkey) Sequence Imaged by SAR Data and Numerical Modeling. Remote Sensing 2016, 8(6), 532; doi:10.3390/rs8060532 --- Wang, C.; Mao, X.; Wang, Q. Landslide Displacement Monitoring by a Fully Polarimetric SAR Offset Tracking Method. Remote Sensing 2016, 8(8), 624; doi:10.3390/rs8080624 --- Liu, Y.; Xu, C.; Li, Z.; Wen, Y.; Chen, J.; Li, Z. Time-Dependent Afterslip of the 2009 Mw 6.3 Dachaidan Earthquake (China) and Viscosity beneath the Qaidam Basin Inferred from Postseismic Deformation Observations. Remote Sensing 2016, 8(8), 649; doi:10.3390/rs8080649 --- Xu, B.; Feng, G.; Li, Z.; Wang, Q.; Wang, C.; Xie, R. Coastal Subsidence Monitoring Associated with Land Reclamation Using the Point Target Based SBAS-InSAR Method: A Case Study of Shenzhen, China. Remote Sensing 2016, 8(8), 652; doi:10.3390/rs8080652 --- Sun, L.; Muller, J. Evaluation of the Use of Sub-Pixel Offset Tracking Techniques to Monitor Landslides in Densely Vegetated Steeply Sloped Areas. Remote Sensing 2016, 8(8), 659; doi:10.3390/rs8080659 --- De Novellis, V.; Castaldo, R.; Lollino, P.; Manunta, M.; Tizzani, P. Advanced Three-Dimensional Finite Element Modeling of a Slow Landslide through the Exploitation of DInSAR Measurements and in Situ Surveys. Remote Sensing 2016, 8(8), 670; doi:10.3390/rs8080670 --- Zhang, Y.; Wu, H.; Kang, Y.; Zhu, C. Ground Subsidence in the Beijing-Tianjin-Hebei Region from 1992 to 2014 Revealed by Multiple SAR Stacks. Remote Sensing 2016, 8(8), 675; doi:10.3390/rs8080675 --- Zhou, G.; Yue, T.; Shi, Y.; Zhang, R.; Huang, J. Second-Order Polynomial Equation-Based Block Adjustment for Orthorectification of DISP Imagery. Remote Sensing 2016, 8(8), 680; doi:10.3390/rs8080680 --- Bonì, R.; Pilla, G.; Meisina, C. Methodology for Detection and Interpretation of Ground Motion Areas with the A-DInSAR Time Series Analysis. Remote Sensing 2016, 8(8), 686; doi:10.3390/rs8080686 --- Xie, S.; Duan, J.; Liu, S.; Dai, Q.; Liu, W.; Ma, Y.; Guo, R.; Ma, C. Crowdsourcing Rapid Assessment of Collapsed Buildings Early after the Earthquake Based on Aerial Remote Sensing Image: A Case Study of Yushu Earthquake. Remote Sensing 2016, 8(9), 759; doi:10.3390/rs8090759 --- Fernández, T.; Pérez, J.; Cardenal, J.; Gómez, J.; Colomo, C.; Delgado, J. Analysis of Landslide Evolution Affecting Olive Groves Using UAV and Photogrammetric Techniques. Remote Sensing 2016, 8(10), 837; doi:10.3390/rs8100837 --- Cignetti, M.; Manconi, A.; Manunta, M.; Giordan, D.; De Luca, C.; Allasia, P.; Ardizzone, F. Taking Advantage of the ESA G-POD Service to Study Ground Deformation Processes in High Mountain Areas: A Valle d’Aosta Case Study, Northern Italy. Remote Sensing 2016, 8(10), 852; doi:10.3390/rs8100852 --- Cooner, A.; Shao, Y.; Campbell, J. Detection of Urban Damage Using Remote Sensing and Machine Learning Algorithms: Revisiting the 2010 Haiti Earthquake. Remote Sensing 2016, 8(10), 868; doi:10.3390/rs8100868 --- Zhou, W.; Li, S.; Zhou, Z.; Chang, X. InSAR Observation and Numerical Modeling of the Earth-Dam Displacement of Shuibuya Dam (China). Remote Sensing 2016, 8(10), 877; doi:10.3390/rs8100877 --- Qu, T.; Lu, P.; Liu, C.; Wu, H.; Shao, X.; Wan, H.; Li, N.; Li, R. Hybrid-SAR Technique: Joint Analysis Using Phase-Based and Amplitude-Based Methods for the Xishancun Giant Landslide Monitoring. Remote Sensing 2016, 8(10), 874; doi:10.3390/rs8100874 --- Gong, L.; Wang, C.; Wu, F.; Zhang, J.; Zhang, H.; Li, Q. Earthquake-Induced Building Damage Detection with Post-Event Sub-Meter VHR TerraSAR-X Staring Spotlight Imagery. Remote Sensing 2016, 8(11), 887; doi:10.3390/rs8110887 --- Ding, C.; Feng, G.; Li, Z.; Shan, X.; Du, Y.; Wang, H. Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements. Remote Sensing 2016, 8(11), 937; doi:10.3390/rs8110937 --- Ma, C.; Cheng, X.; Yang, Y.; Zhang, X.; Guo, Z.; Zou, Y. Investigation on Mining Subsidence Based on Multi-Temporal InSAR and Time-Series Analysis of the Small Baseline Subset—Case Study of Working Faces 22201-1/2 in Bu’ertai Mine, Shendong Coalfield, China. Remote Sensing 2016, 8(11), 951; doi:10.3390/rs8110951 --- Caló, F.; Notti, D.; Galve, J.; Abdikan, S.; Görüm, T.; Pepe, A.; Balik Şanli, F. DInSAR-Based Detection of Land Subsidence and Correlation with Groundwater Depletion in Konya Plain, Turkey. Remote Sensing 2017, 9(1), 83; doi:10.3390/rs9010083 --- Tomás, R.; Li, Z. Earth Observations for Geohazards: Present and Future Challenges. Remote Sensing 2017, 9(3), 194; doi:10.3390/rs9030194

Description / Table of Contents: Chen, K.; Zamora, N.; Babeyko, A.; Li, X.; Ge, M. Precise Positioning of BDS, BDS/GPS: Implications for Tsunami Early Warning in South China Sea. Remote Sensing 2015, 7(12), 15955-15968; doi:10.3390/rs71215814 --- Cianflone, G.; Tolomei, C.; Brunori, C.; Dominici, R. InSAR Time Series Analysis of Natural and Anthropogenic Coastal Plain Subsidence: The Case of Sibari (Southern Italy). Remote Sensing 2015, 7(12), 16004-16023; doi:10.3390/rs71215812 --- Kropáček, J.; Vařilová, Z.; Baroň, I.; Bhattacharya, A.; Eberle, J.; Hochschild, V. Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment. Remote Sensing 2015, 7(12), 16183-16203; doi:10.3390/rs71215821 --- Pacheco-Martínez, J.; Cabral-Cano, E.; Wdowinski, S.; Hernández-Marín, M.; Ortiz-Lozano, J.; Zermeño-de-León, M. Application of InSAR and Gravimetry for Land Subsidence Hazard Zoning in Aguascalientes, Mexico. Remote Sensing 2015, 7(12), 17035-17050; doi:10.3390/rs71215868 --- Al-Rawabdeh, A.; He, F.; Moussa, A.; El-Sheimy, N.; Habib, A. Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition. Remote Sensing 2016, 8(2), 95; doi:10.3390/rs8020095 --- Zhai, W.; Shen, H.; Huang, C.; Pei, W. Building Earthquake Damage Information Extraction from a Single Post-Earthquake PolSAR Image. Remote Sensing 2016, 8(3), 171; doi:10.3390/rs8030171 --- Jiang, Y.; Liao, M.; Zhou, Z.; Shi, X.; Zhang, L.; Balz, T. Landslide Deformation Analysis by Coupling Deformation Time Series from SAR Data with Hydrological Factors through Data Assimilation. Remote Sensing 2016, 8(3), 179; doi:10.3390/rs8030179 --- He, M.; Zhu, Q.; Du, Z.; Hu, H.; Ding, Y.; Chen, M. A 3D Shape Descriptor Based on Contour Clusters for Damaged Roof Detection Using Airborne LiDAR Point Clouds. Remote Sensing 2016, 8(3), 189; doi:10.3390/rs8030189 --- Hu, J.; Wang, Q.; Li, Z.; Zhao, R.; Sun, Q. Investigating the Ground Deformation and Source Model of the Yangbajing Geothermal Field in Tibet, China with the WLS InSAR Technique. Remote Sensing 2016, 8(3), 191; doi:10.3390/rs8030191 --- Hsieh, Y.; Chan, Y.; Hu, J. Digital Elevation Model Differencing and Error Estimation from Multiple Sources: A Case Study from the Meiyuan Shan Landslide in Taiwan. Remote Sensing 2016, 8(3), 199; doi:10.3390/rs8030199 --- Zhu, S.; Xu, C.; Wen, Y.; Liu, Y. Interseismic Deformation of the Altyn Tagh Fault Determined by Interferometric Synthetic Aperture Radar (InSAR) Measurements. Remote Sensing 2016, 8(3), 233; doi:10.3390/rs8030233 --- Vetrivel, A.; Gerke, M.; Kerle, N.; Vosselman, G. Identification of Structurally Damaged Areas in Airborne Oblique Images Using a Visual-Bag-of-Words Approach. Remote Sensing 2016, 8(3), 231; doi:10.3390/rs8030231 --- Bardi, F.; Raspini, F.; Ciampalini, A.; Kristensen, L.; Rouyet, L.; Lauknes, T.; Frauenfelder, R.; Casagli, N. Space-Borne and Ground-Based InSAR Data Integration: The Åknes Test Site. Remote Sensing 2016, 8(3), 237; doi:10.3390/rs8030237 --- Liu, P.; Li, Q.; Li, Z.; Hoey, T.; Liu, G.; Wang, C.; Hu, Z.; Zhou, Z.; Singleton, A. Anatomy of Subsidence in Tianjin from Time Series InSAR. Remote Sensing 2016, 8(3), 266; doi:10.3390/rs8030266 --- Ma, Y.; Chen, F.; Liu, J.; He, Y.; Duan, J.; Li, X. An Automatic Procedure for Early Disaster Change Mapping Based on Optical Remote Sensing. Remote Sensing 2016, 8(4), 272; doi:10.3390/rs8040272 --- Yang, C.; Zhang, Q.; Xu, Q.; Zhao, C.; Peng, J.; Ji, L. Complex Deformation Monitoring over the Linfen–Yuncheng Basin (China) with Time Series InSAR Technology. Remote Sensing 2016, 8(4), 284; doi:10.3390/rs8040284 --- Watanabe, M.; Thapa, R.; Shimada, M. Pi-SAR-L2 Observation of the Landslide Caused by Typhoon Wipha on Izu Oshima Island. Remote Sensing 2016, 8(4), 282; doi:10.3390/rs8040282 --- Plank, S.; Twele, A.; Martinis, S. Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data. Remote Sensing 2016, 8(4), 307; doi:10.3390/rs8040307 --- Solaro, G.; De Novellis, V.; Castaldo, R.; De Luca, C.; Lanari, R.; Manunta, M.; Casu, F. Coseismic Fault Model of Mw 8.3 2015 Illapel Earthquake (Chile) Retrieved from Multi-Orbit Sentinel1-A DInSAR Measurements. Remote Sensing 2016, 8(4), 323; doi:10.3390/rs8040323 --- Bai, L.; Jiang, L.; Wang, H.; Sun, Q. Spatiotemporal Characterization of Land Subsidence and Uplift (2009–2010) over Wuhan in Central China Revealed by TerraSAR-X InSAR Analysis. Remote Sensing 2016, 8(4), 350; doi:10.3390/rs8040350 --- Xu, B.; Li, Z.; Feng, G.; Zhang, Z.; Wang, Q.; Hu, J.; Chen, X. Continent-Wide 2-D Co-Seismic Deformation of the 2015 Mw 8.3 Illapel, Chile Earthquake Derived from Sentinel-1A Data: Correction of Azimuth Co-Registration Error. Remote Sensing 2016, 8(5), 376; doi:10.3390/rs8050376 --- Chen, M.; Tomás, R.; Li, Z.; Motagh, M.; Li, T.; Hu, L.; Gong, H.; Li, X.; Yu, J.; Gong, X. Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry. Remote Sensing 2016, 8(6), 468; doi:10.3390/rs8060468 --- Ji, L.; Xu, J.; Zhao, Q.; Yang, C. Source Parameters of the 2003–2004 Bange Earthquake Sequence, Central Tibet, China, Estimated from InSAR Data. Remote Sensing 2016, 8(6), 516; doi:10.3390/rs8060516 --- Li, Y.; Jiang, W.; Zhang, J.; Luo, Y. Space Geodetic Observations and Modeling of 2016 Mw 5.9 Menyuan Earthquake: Implications on Seismogenic Tectonic Motion. Remote Sensing 2016, 8(6), 519; doi:10.3390/rs8060519 --- Trasatti, E.; Tolomei, C.; Pezzo, G.; Atzori, S.; Salvi, S. Deformation and Related Slip Due to the 2011 Van Earthquake (Turkey) Sequence Imaged by SAR Data and Numerical Modeling. Remote Sensing 2016, 8(6), 532; doi:10.3390/rs8060532 --- Wang, C.; Mao, X.; Wang, Q. Landslide Displacement Monitoring by a Fully Polarimetric SAR Offset Tracking Method. Remote Sensing 2016, 8(8), 624; doi:10.3390/rs8080624 --- Liu, Y.; Xu, C.; Li, Z.; Wen, Y.; Chen, J.; Li, Z. Time-Dependent Afterslip of the 2009 Mw 6.3 Dachaidan Earthquake (China) and Viscosity beneath the Qaidam Basin Inferred from Postseismic Deformation Observations. Remote Sensing 2016, 8(8), 649; doi:10.3390/rs8080649 --- Xu, B.; Feng, G.; Li, Z.; Wang, Q.; Wang, C.; Xie, R. Coastal Subsidence Monitoring Associated with Land Reclamation Using the Point Target Based SBAS-InSAR Method: A Case Study of Shenzhen, China. Remote Sensing 2016, 8(8), 652; doi:10.3390/rs8080652 --- Sun, L.; Muller, J. Evaluation of the Use of Sub-Pixel Offset Tracking Techniques to Monitor Landslides in Densely Vegetated Steeply Sloped Areas. Remote Sensing 2016, 8(8), 659; doi:10.3390/rs8080659 --- De Novellis, V.; Castaldo, R.; Lollino, P.; Manunta, M.; Tizzani, P. Advanced Three-Dimensional Finite Element Modeling of a Slow Landslide through the Exploitation of DInSAR Measurements and in Situ Surveys. Remote Sensing 2016, 8(8), 670; doi:10.3390/rs8080670 --- Zhang, Y.; Wu, H.; Kang, Y.; Zhu, C. Ground Subsidence in the Beijing-Tianjin-Hebei Region from 1992 to 2014 Revealed by Multiple SAR Stacks. Remote Sensing 2016, 8(8), 675; doi:10.3390/rs8080675 --- Zhou, G.; Yue, T.; Shi, Y.; Zhang, R.; Huang, J. Second-Order Polynomial Equation-Based Block Adjustment for Orthorectification of DISP Imagery. Remote Sensing 2016, 8(8), 680; doi:10.3390/rs8080680 --- Bonì, R.; Pilla, G.; Meisina, C. Methodology for Detection and Interpretation of Ground Motion Areas with the A-DInSAR Time Series Analysis. Remote Sensing 2016, 8(8), 686; doi:10.3390/rs8080686 --- Xie, S.; Duan, J.; Liu, S.; Dai, Q.; Liu, W.; Ma, Y.; Guo, R.; Ma, C. Crowdsourcing Rapid Assessment of Collapsed Buildings Early after the Earthquake Based on Aerial Remote Sensing Image: A Case Study of Yushu Earthquake. Remote Sensing 2016, 8(9), 759; doi:10.3390/rs8090759 --- Fernández, T.; Pérez, J.; Cardenal, J.; Gómez, J.; Colomo, C.; Delgado, J. Analysis of Landslide Evolution Affecting Olive Groves Using UAV and Photogrammetric Techniques. Remote Sensing 2016, 8(10), 837; doi:10.3390/rs8100837 --- Cignetti, M.; Manconi, A.; Manunta, M.; Giordan, D.; De Luca, C.; Allasia, P.; Ardizzone, F. Taking Advantage of the ESA G-POD Service to Study Ground Deformation Processes in High Mountain Areas: A Valle d’Aosta Case Study, Northern Italy. Remote Sensing 2016, 8(10), 852; doi:10.3390/rs8100852 --- Cooner, A.; Shao, Y.; Campbell, J. Detection of Urban Damage Using Remote Sensing and Machine Learning Algorithms: Revisiting the 2010 Haiti Earthquake. Remote Sensing 2016, 8(10), 868; doi:10.3390/rs8100868 --- Zhou, W.; Li, S.; Zhou, Z.; Chang, X. InSAR Observation and Numerical Modeling of the Earth-Dam Displacement of Shuibuya Dam (China). Remote Sensing 2016, 8(10), 877; doi:10.3390/rs8100877 --- Qu, T.; Lu, P.; Liu, C.; Wu, H.; Shao, X.; Wan, H.; Li, N.; Li, R. Hybrid-SAR Technique: Joint Analysis Using Phase-Based and Amplitude-Based Methods for the Xishancun Giant Landslide Monitoring. Remote Sensing 2016, 8(10), 874; doi:10.3390/rs8100874 --- Gong, L.; Wang, C.; Wu, F.; Zhang, J.; Zhang, H.; Li, Q. Earthquake-Induced Building Damage Detection with Post-Event Sub-Meter VHR TerraSAR-X Staring Spotlight Imagery. Remote Sensing 2016, 8(11), 887; doi:10.3390/rs8110887 --- Ding, C.; Feng, G.; Li, Z.; Shan, X.; Du, Y.; Wang, H. Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements. Remote Sensing 2016, 8(11), 937; doi:10.3390/rs8110937 --- Ma, C.; Cheng, X.; Yang, Y.; Zhang, X.; Guo, Z.; Zou, Y. Investigation on Mining Subsidence Based on Multi-Temporal InSAR and Time-Series Analysis of the Small Baseline Subset—Case Study of Working Faces 22201-1/2 in Bu’ertai Mine, Shendong Coalfield, China. Remote Sensing 2016, 8(11), 951; doi:10.3390/rs8110951 --- Caló, F.; Notti, D.; Galve, J.; Abdikan, S.; Görüm, T.; Pepe, A.; Balik Şanli, F. DInSAR-Based Detection of Land Subsidence and Correlation with Groundwater Depletion in Konya Plain, Turkey. Remote Sensing 2017, 9(1), 83; doi:10.3390/rs9010083 --- Tomás, R.; Li, Z. Earth Observations for Geohazards: Present and Future Challenges. Remote Sensing 2017, 9(3), 194; doi:10.3390/rs9030194

Description / Table of Contents: Coordinate measuring machines (CMMs) have been conventionally used in industry for 3D-dimensional and form-error measurements of macro parts for many years. Ever since the first CMM, developed by Ferranti Co. in late 1950s, they have been regarded as versatile measuring equipment, yet many CMMs on the market still have inherent systematic errors due to the violation of the Abbe Principle in the design aspect. Current CMMs are suitable only for part tolerance above 10 μm. With the rapid advent of ultraprecision technology, multi-axis machining, and micro/nanotechnology in the past twenty years, new types of ultraprecision and micro/nao-CMMs are urgently needed in all aspects of society.

Description / Table of Contents: Falcinelli, S.; Pirani, F.; Vecchiocattivi, F. The Possible Role of Penning Ionization Processes in Planetary Atmospheres. Atmosphere 2015, 6(3), 299-317; doi:10.3390/atmos6030299 --- Park, S.; Seo, B.; Lee, G.; Kahng, S.; Jang, Y. Chemical Composition of Water Soluble Inorganic Species in Precipitation at Shihwa Basin, Korea. Atmosphere 2015, 6(6), 732-750; doi:10.3390/atmos6060732 --- Kassianov, E.; Berg, L.; Pekour, M.; Barnard, J.; Chand, D.; Flynn, C.; Ovchinnikov, M.; Sedlacek, A.; Schmid, B.; Shilling, J.; Tomlinson, J.; Fast, J. Airborne Aerosol in Situ Measurements during TCAP: A Closure Study of Total Scattering. Atmosphere 2015, 6(8), 1069-1101; doi:10.3390/atmos6081069 --- Majewski, G.; Rogula-Kozłowska, W.; Czechowski, P.; Badyda, A.; Brandyk, A. The Impact of Selected Parameters on Visibility: First Results from a Long-Term Campaign in Warsaw, Poland. Atmosphere 2015, 6(8), 1154-1174; doi:10.3390/atmos6081154 --- Khwaja, H.; Aburizaiza, O.; Hershey, D.; Siddique, A.; E., D.; Zeb, J.; Abbass, M.; Blake, D.; Hussain, M.; Aburiziza, A.; Kramer, M.; Simpson, I. Study of Black Sand Particles from Sand Dunes in Badr, Saudi Arabia Using Electron Microscopy. Atmosphere 2015, 6(8), 1175-1194; doi:10.3390/atmos6081175 --- Wu, Z.; Liu, F.; Fan, W. Characteristics of PM10 and PM2.5 at Mount Wutai Buddhism Scenic Spot, Shanxi, China. Atmosphere 2015, 6(8), 1195-1210; doi:10.3390/atmos6081195 --- Saldarriaga-Noreña, H.; López-Márquez, R.; Murillo-Tovar, M.; Hernández-Mena, L.; Ospina-Noreña, E.; Sánchez-Salinas, E.; Waliszewski, S.; Montiel-Palma, S. Analysis of PAHs Associated with Particulate Matter PM2.5 in Two Places at the City of Cuernavaca, Morelos, México. Atmosphere 2015, 6(9), 1259-1270; doi:10.3390/atmos6091259 --- Faxon, C.; Bean, J.; Ruiz, L. Inland Concentrations of Cl2 and ClNO2 in Southeast Texas Suggest Chlorine Chemistry Significantly Contributes to Atmospheric Reactivity. Atmosphere 2015, 6(10), 1487-1506; doi:10.3390/atmos6101487 --- Asa-Awuku, A.; Sorooshian, A.; Flagan, R.; Seinfeld, J.; Nenes, A. CCN Properties of Organic Aerosol Collected Below and within Marine Stratocumulus Clouds near Monterey, California. Atmosphere 2015, 6(11), 1590-1607; doi:10.3390/atmos6111590 --- Yang, M.; Wang, Y.; Liu, Q.; Ding, A.; Li, Y. The Influence of Sandstorms and Long-Range Transport on Polycyclic Aromatic Hydrocarbons (PAHs) in PM2.5 in the High-Altitude Atmosphere of Southern China. Atmosphere 2015, 6(11), 1633-1651; doi:10.3390/atmos6111633 --- Rubio, M.; Lissi, E.; Gramsch, E.; Garreaud, R. Effect of Nearby Forest Fires on Ground Level Ozone Concentrations in Santiago, Chile. Atmosphere 2015, 6(12), 1926-1938; doi:10.3390/atmos6121838 --- Lopez, D.; Rabbani, M.; Crosbie, E.; Raman, A.; Arellano, A.; Sorooshian, A. Frequency and Character of Extreme Aerosol Events in the Southwestern United States: A Case Study Analysis in Arizona. Atmosphere 2016, 7(1), 1; doi:10.3390/atmos7010001 --- Stovern, M.; Guzmán, H.; Rine, K.; Felix, O.; King, M.; Ela, W.; Betterton, E.; Sáez, A. Windblown Dust Deposition Forecasting and Spread of Contamination around Mine Tailings. Atmosphere 2016, 7(2), 16; doi:10.3390/atmos7020016 --- Raman, A.; Arellano, A.; Sorooshian, A. Decreasing Aerosol Loading in the North American Monsoon Region. Atmosphere 2016, 7(2), 24; doi:10.3390/atmos7020024 --- Hetem, I.; Andrade, M. Characterization of Fine Particulate Matter Emitted from the Resuspension of Road and Pavement Dust in the Metropolitan Area of São Paulo, Brazil. Atmosphere 2016, 7(3), 31; doi:10.3390/atmos7030031

Description / Table of Contents: Mercury is a serious environmental toxin that is distributed globally by large-scale atmospheric circulations. Atmospheric chemists have only been studying mercury in earnest for approximately the past 10 years. In the troposphere elemental mercury (Hgo) is observed ubiquitously with contemporary mixing ratios at the parts per quadrillion by volume (ppqv; 1 ng m−3 = 112 ppqv) level. The distributions of gaseous oxidized mercury (GOM) and particulate mercury (HgP) are not well documented at this time. In fact, the chemical composition of GOM is presently highly uncertain. At most mid-latitude locations, Hgo exhibits seasonality with the lowest mixing ratios in the fall and the greatest in late winter/early spring. It is highly desirable to conduct measurements of a variety of trace gases along with atmospheric mercury to facilitate source identification, but few studies have done so to date. A serious drawback in modeling atmospheric mercury is a lack of reliable rigorous emission inventories. Consequently, much work is needed to identify mercury sources and to quantify emission strengths. There are few published papers on measurements of atmospheric mercury from aircraft. Initial work has shown that there is little to no Hgo above the tropopause and that HgP is elevated there. The chemical cycling and transformations in the tropopause region are essentially unstudied. Both measurements and modeling are required to ascertain the important processes affecting atmospheric mercury in the tropopause region.

Description / Table of Contents: Belle, J.; Liu, Y. Evaluation of Aqua MODIS Collection 6 AOD Parameters for Air Quality Research over the Continental United States. Remote Sens. 2016, 8(10), 815; doi:10.3390/rs8100815. http://www.mdpi.com/2072-4292/8/10/815 --- Sun, K.; Chen, X.; Zhu, Z.; Zhang, T. High Resolution Aerosol Optical Depth Retrieval Using Gaofen-1 WFV Camera Data. Remote Sens. 2017, 9(1), 89; doi:10.3390/rs9010089. http://www.mdpi.com/2072-4292/9/1/89 --- Chen, X.; Yang, D.; Cai, Z.; Liu, Y.; Spurr, R. Aerosol Retrieval Sensitivity and Error Analysis for the Cloud and Aerosol Polarimetric Imager on Board TanSat: The Effect of Multi-Angle Measurement. Remote Sens. 2017, 9(2), 183; doi:10.3390/rs9020183. http://www.mdpi.com/2072-4292/9/2/183 --- Jiang, M.; Sun, W.; Yang, G.; Zhang, D. Modelling Seasonal GWR of Daily PM2.5 with Proper Auxiliary Variables for the Yangtze River Delta. Remote Sens. 2017, 9(4), 346; doi:10.3390/rs9040346. http://www.mdpi.com/2072-4292/9/4/346 --- Wang, Y.; Chen, L.; Li, S.; Wang, X.; Yu, C.; Si, Y.; Zhang, Z. Interference of Heavy Aerosol Loading on the VIIRS Aerosol Optical Depth (AOD) Retrieval Algorithm. Remote Sens. 2017, 9(4), 397; doi:10.3390/rs9040397. http://www.mdpi.com/2072-4292/9/4/397 --- Wang, W.; Mao, F.; Pan, Z.; Du, L.; Gong, W. Validation of VIIRS AOD through a Comparison with a Sun Photometer and MODIS AODs over Wuhan. Remote Sens. 2017, 9(5), 403; doi:10.3390/rs9050403. http://www.mdpi.com/2072-4292/9/5/403 --- Zhu, J.; Xia, X.; Wang, J.; Che, H.; Chen, H.; Zhang, J.; Xu, X.; Levy, R.; Oo, M.; Holz, R.; Ayoub, M. Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain. Remote Sens. 2017, 9(5), 432; doi:10.3390/rs9050432. http://www.mdpi.com/2072-4292/9/5/432 --- Dolgii, S.; Nevzorov, A.; Nevzorov, A.; Romanovskii, O.; Kharchenko, O. Intercomparison of Ozone Vertical Profile Measurements by Differential Absorption Lidar and IASI/MetOp Satellite in the Upper Troposphere–Lower Stratosphere. Remote Sens. 2017, 9(5), 447; doi:10.3390/rs9050447. http://www.mdpi.com/2072-4292/9/5/447 --- Liu, L.; Zhang, X.; Xu, W.; Liu, X.; Lu, X.; Wang, S.; Zhang, W.; Zhao, L. Ground Ammonia Concentrations over China Derived from Satellite and Atmospheric Transport Modeling. Remote Sens. 2017, 9(5), 467; doi:10.3390/rs9050467. http://www.mdpi.com/2072-4292/9/5/467 --- Chen, W.; Fan, A.; Yan, L. Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing. Remote Sens. 2017, 9(5), 496; doi:10.3390/rs9050496. http://www.mdpi.com/2072-4292/9/5/496 --- Osorio, M.; Casaballe, N.; Belsterli, G.; Barreto, M.; Gómez, Á.; Ferrari, J.; Frins, E. Plume Segmentation from UV Camera Images for SO2 Emission Rate Quantification on Cloud Days. Remote Sens. 2017, 9(6), 517; doi:10.3390/rs9060517. http://www.mdpi.com/2072-4292/9/6/517 --- Gu, J.; Chen, L.; Yu, C.; Li, S.; Tao, J.; Fan, M.; Xiong, X.; Wang, Z.; Shang, H.; Su, L. Ground-Level NO2 Concentrations over China Inferred from the Satellite OMI and CMAQ Model Simulations. Remote Sens. 2017, 9(6), 519; doi:10.3390/rs9060519. http://www.mdpi.com/2072-4292/9/6/519 --- Wang, Y.; Wang, J.; Levy, R.; Xu, X.; Reid, J. MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water. Remote Sens. 2017, 9(6), 595; doi:10.3390/rs9060595. http://www.mdpi.com/2072-4292/9/6/595 --- Kim, D.; Lee, H.; Hong, H.; Choi, W.; Lee, Y.; Park, J. Estimation of Surface NO2 Volume Mixing Ratio in Four Metropolitan Cities in Korea Using Multiple Regression Models with OMI and AIRS Data. Remote Sens. 2017, 9(6), 627; doi:10.3390/rs9060627. http://www.mdpi.com/2072-4292/9/6/627 --- Qu, Y.; Han, Y.; Wu, Y.; Gao, P.; Wang, T. Study of PBLH and Its Correlation with Particulate Matter from One-Year Observation over Nanjing, Southeast China. Remote Sens. 2017, 9(7), 668; doi:10.3390/rs9070668. http://www.mdpi.com/2072-4292/9/7/668 --- Tosca, M.; Campbell, J.; Garay, M.; Lolli, S.; Seidel, F.; Marquis, J.; Kalashnikova, O. Attributing Accelerated Summertime Warming in the Southeast United States to Recent Reductions in Aerosol Burden: Indications from Vertically-Resolved Observations. Remote Sens. 2017, 9(7), 674; doi:10.3390/rs9070674. http://www.mdpi.com/2072-4292/9/7/674 --- Tao, M.; Wang, Z.; Tao, J.; Chen, L.; Wang, J.; Hou, C.; Wang, L.; Xu, X.; Zhu, H. How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China?. Remote Sens. 2017, 9(8), 800; doi:10.3390/rs9080800. http://www.mdpi.com/2072-4292/9/8/800 --- Wang, W.; Mao, F.; Du, L.; Pan, Z.; Gong, W.; Fang, S. Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China. Remote Sens. 2017, 9(8), 858; doi:10.3390/rs9080858. http://www.mdpi.com/2072-4292/9/8/858 --- Yuchechen, A.; Lakkis, S.; Canziani, P. Linear and Non-Linear Trends for Seasonal NO2 and SO2 Concentrations in the Southern Hemisphere (2004−2016). Remote Sens. 2017, 9(9), 891; doi:10.3390/rs9090891. http://www.mdpi.com/2072-4292/9/9/891 --- Qin, K.; Rao, L.; Xu, J.; Bai, Y.; Zou, J.; Hao, N.; Li, S.; Yu, C. Estimating Ground Level NO2 Concentrations over Central-Eastern China Using a Satellite-Based Geographically and Temporally Weighted Regression Model. Remote Sens. 2017, 9(9), 950; doi:10.3390/rs9090950. http://www.mdpi.com/2072-4292/9/9/950