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At least 865 records · Page 48Linked to original sources

A calorimetric determination of the standard enthalpies of formation of huntite, CaMg3 (CO3)4 , and artinite, Mg2(OH)2 CO3 * 3H2O, and their standard Gibbs free energies of formation

The enthalpies of formation, ΔH° f, of huntite, CaMg 3 (CO 3 ) 4 , and artinite, Mg 2 (OH) 2 CO 3 * 3H 2 O, have been determined by HCl solution calorimetry using a constant-volume isoperibol reaction calorimeter. For the reaction CaO(c) + 3MgO(c) + 4CO 2 (g) = CaMg 3 (CO 3 ) 4 (c), the enthalpy change at 298.15 K, ΔH° 298 , is -123,203±145 cal mol -1 . For the reaction 2MgO(c) + 4H 2 O(l) + CO 2 (g)=Mg 2 (OH) 2 CO 3 * 3H 2 O(c), we obtained -45,132±100 cal mol -1 . These results combined with the standard enthalpies of formation of CaO, MgO, H 2 O, and CO 2 lead to ΔH° 298 (huntite) = -1,082,600±375 cal mol -1 and ΔH° 298 (artinite) = -698,043±170 cal mol -1 . Using recently determined values for the standard entropies of huntite, CaMg 3 (CO 3 ) 4 , and artinite, Mg 2 (OH) 2 CO 3 * 3H 2 O, and of Mg, Ca, C, O 2 , and H 2 , we calculate ΔG° f,298 (huntite) = -1,004,707±390 cal mol -1 and ΔG° f,298 (artinite) = -613,924±180 cal mol -1 .

Journal of Research of the U.S. Geological Survey↗

Adaptive harvest management for the Svalbard population of pink‐footed geese: 2016 progress summary: Technical Report from DCE – Danish Centre for Environment and Energy, No. 86

This document describes progress to date on the development of an adaptive harvest management strategy for maintaining the Svalbard population of pink‐footed geese (Anser brachyrhynchus) near their agreed target level (60,000) by providing for sustainable harvests in Norway and Denmark. This report provides an assessment of the most recent monitoring information (1991-2015) and its implications for the harvest management strategy. By combining varying hypotheses about survival and reproduction, a suite of nine models have been developed that represent a wide range of possibilities concerning the extent to which demographic rates are density dependent or independent. These results suggest that the pink‐footed goose population may have recently experienced a release from density‐dependent mechanisms, corresponding to the period of most rapid growth in population size. Beginning with the 2016 hunting season, harvest quotas will be prescribed on an annual basis rather than every three years because of the potential to better meet population management objectives. Based on updated model weights, the recent observations of population size (74,800), the proportion of the population comprised of one-year-old birds (0.138), and temperature days in Svalbard (20), the optimal harvest quota for the 2016 hunting season is 25,000. The large increase in quota compared to that during first three years of AHM reflects stakeholders’ desire to reduce population size to the goal of 60,000, recognizing that population size remains relatively high and above-average production is expected in 2016 due to a warm spring.

Report↗

Modeling at-sea density of marine birds to support renewable energy planning on the Pacific outer continental shelf of the contiguous United States

This report describes the at-sea spatial distributions of marine birds in Pacific OCS waters off the contiguous U.S. (Figure 1.1) to inform marine spatial planning in the region. The goal was to estimate long-term average spatial distributions for marine bird species using all available science-quality transect survey data and numerous bathymetric, oceanographic, and atmospheric predictor variables. We developed seasonal habitat-based spatial models of the at-sea distribution for 33 individual species and 13 taxonomic groups of marine birds throughout the study region. A statistical modeling framework was used to estimate numerical relationships between bird sighting data (i.e., standardized counts) and a range of temporal (e.g., Pacific Decadal Oscillation [PDO] index), spatially static (e.g., depth), and spatially dynamic (e.g., sea surface chlorophyll-a concentration) environmental variables. The estimated relationships were then used to predict spatially explicit long-term average density (individuals per km 2 ) throughout the study area for each species/group in each of four seasons. Bird sighting data came from multiple scientific survey programs and consisted of at-sea counts of birds collected between 1980 and 2017 using boat-based and fixed-wing aerial transect survey methods. Spatial environmental variables were derived from remote sensing satellite data and an ocean dynamics model.

California, Oregon, Washington↗