Use of AIS data for the environmental characterization of world cruise ship traffic

2019 ◽  
Vol 14 (6) ◽  
pp. 465-474
Author(s):  
Isaías Vicente-Cera ◽  
Asunción Acevedo-Merino ◽  
Juan Antonio López-Ramírez ◽  
Enrique Nebot
Keyword(s):  
Cruise Ship ◽  
Ship Traffic ◽  
Environmental Characterization

scholarly journals Living Benthic Foraminifera from the Surface and Subsurface Sediment Layers Applied to the Environmental Characterization of the Brazilian Continental Slope (SW Atlantic)

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1863
Author(s):  
Luciana Cristina de Carvalho Santa-Rosa ◽  
Sibelle Trevisan Disaró ◽  
Violeta Totah ◽  
Silvia Watanabe ◽  
Ana Tereza Bittencourt Guimarães
Keyword(s):  
Continental Slope ◽  
Benthic Foraminifera ◽  
Subsurface Layer ◽  
Environmental Characterization ◽  
Potiguar Basin ◽  
Middle Slope ◽  
Sw Atlantic ◽  
Sediment Layers ◽  
Lower Slope

Living benthic foraminifera (>63 µm) were studied to characterize the continental slope of the Potiguar Basin (SW Atlantic). Foraminifers from the surface (0–2 cm), subsurface (2–5 cm), and integrated (0–5 cm) sediment layers were analyzed to verify their contribution to environmental characterization. It was also estimated if and which changes occur when the subsurface is added. Sampling stations were distributed in five transects in four isobaths (150, 400, 1000, and 2000 m). Sediment samples were fixed with 4% buffered formaldehyde and stained with Bengal rose. Were recorded 396 species in the surface layer, 228 in the subsurface, and 449 in integrating both layers. This study did not include tubular agglutinated species. The assemblages from 150 m isobath indicated the upper slope, from 400 m indicated the middle slope and the ones from the 2000 m indicated the lower slope. The surface layer’s assemblage at 1000 m isobath was more similar to the middle slope; in contrast, its subsurface layer´s assemblage had more similarity with the lower slope. Rarefaction curves, Permanova, and NMDS routines indicated a high resemblance between surface and integrated layers. Therefore, the first two centimeters were sufficient to characterize this region based on living benthic foraminifera.

scholarly journals STATISTICAL MULTIVARIATE ANALYSIS APPLIED TO ENVIRONMENTAL CHARACTERIZATION OF SOIL IN SEMIARID REGION1

2019 ◽  
Vol 32 (1) ◽  
pp. 200-210
Author(s):  
Antônio Italcy de Oliveira Júnior ◽  
Luiz Alberto Ribeiro Mendonça ◽  
Sávio de Brito Fontenele ◽  
Adriana Oliveira Araújo ◽  
Maria Gorethe de Sousa Lima Brito
Keyword(s):  
Organic Matter Content ◽  
Principal Component ◽  
Matter Content ◽  
Multivariate Statistical ◽  
Statistical Tool ◽  
Environmental Characterization ◽  
Hierarchical Grouping ◽  
Two Factors ◽  
Total Data

ABSTRACT Soil is a dynamic and complex system that requires a considerable number of samples for analysis and research purposes. Using multivariate statistical methods, favorable conditions can be created by analyzing the samples, i.e., structural reduction and simplification of the data. The objective of this study was to use multivariate statistical analysis, including factorial analysis (FA) and hierarchical groupings, for the environmental characterization of soils in semiarid regions, considering anthropic (land use and occupation) and topographic aspects (altitude, moisture, granulometry, PR, and organic-matter content). As a case study, the São José Hydrographic Microbasin, which is located in the Cariri region of Ceará, was considered. An FA was performed using the principal component method, with normalized varimax rotation. In hierarchical grouping analysis, the “farthest neighbor” method was used as the hierarchical criterion for grouping, with the measure of dissimilarity given by the “square Euclidean distance.” The FA indicated that two factors explain 75.76% of the total data variance. In the analysis of hierarchical groupings, the samples were agglomerated in three groups with similar characteristics: one with samples collected in an area of the preserved forest and two with samples collected in areas with more anthropized soils. This indicates that the statistical tool used showed sensitivity to distinguish the most conserved soils and soils with different levels of anthropization.

Geographical Characterization of Ship Traffic and Emissions

2005 ◽  
Vol 1909 (1) ◽  
pp. 90-99 ◽  
Author(s):  
Chenfeng Wang ◽  
James J. Corbett
Keyword(s):  
Coastal Waters ◽  
East Coast ◽  
Air Emissions ◽  
Traffic Network ◽  
Traffic Patterns ◽  
Data Set ◽  
Ship Traffic ◽  
Traffic Pattern ◽  
Adequate Data

The Commercial Marine Vessel Traffic and Air Emissions Model (CMV-TAEM) estimates and geographically represents offshore vessel traffic and emissions based on actual shipping activities. The CMV-TAEM has three modules: ship traffic, ship emissions, and policy analysis. The model establishes empirical ship traffic network on the basis of ship observations derived from the International Comprehensive Ocean-Atmosphere Data Set and shipping activity records. Geographical representations of ship traffic intensities and emissions can be produced through the math-ematic manipulation of matrices of ship traffic network, shipping activity, and ship characteristic data. Overall, although seasonal changes are apparent, the global ship traffic pattern does not change much annually. The ship traffic pattern changes regionally, with a net increase in some areas and net decrease in others. Multiple-year observations are combined to make traffic patterns for major shipping lanes smoother and clearer. Results indicate that 84.5% of global ship traffic occurs north of the equator and two-thirds of global ship traffic within 200 nautical miles of the shore. About 10% of global ship traffic occurs in U.S. coastal waters; shipping along the East Coast accounts for more than one-fifth of the U.S. coastal traffic. Adequate data are available to determine ship activities and ship attributes and to implement the model.

Waste to energy ash monofill mining: An environmental characterization of recovered material

2017 ◽  
Vol 328 ◽  
pp. 63-69 ◽  
Author(s):  
Justin G. Roessler ◽  
Timothy G. Townsend ◽  
Abhimanyu Kanneganti
Keyword(s):  
Waste To Energy ◽  
Environmental Characterization ◽  
Recovered Material
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