989 resultados para Rockingham County


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As part of the rebuilding efforts following the long civil war, the Liberian government has renegotiated long-term contracts with international investors to exploit natural resources. Substantial areas of land have been handed out in large-scale concessions across Liberia during the last five years. While this may promote economic growth at the national level, such concessions are likely to have major environmental, social and economic impacts on local communities, who may not have been consulted on the proposed developments. This report examines the potential socio-economic and environmental impacts of a proposed large-scale oil palm concession in Bopolu District, Gbarpolu County in Liberia. The research provided an in-depth mapping of current resource use, livelihoods and ecosystems services, in addition to analysis of community consultation and perceptions of the potential impacts of the proposed development. This case study of a palm oil concession in Liberia highlights wider policy considerations regarding large-scale land acquisitions in the global South: • Formal mechanisms may be needed to ensure the process of Free, Prior, Informed Consent takes place effectively with affected communities and community land rights are safeguarded. • Rigorous Environmental and Social Impact Assessments need to be conducted before operations start. Accurate mapping of customary land rights, community resources and cultural sites, livelihoods, land use, biodiversity and ecosystems services is a critical tool in this process. • Greater clarity and awareness-raising of land tenure laws and policies is needed at all levels. Good governance and capacity-building of key institutions would help to ensure effective implementation of relevant laws and policies. • Efforts are needed to improve basic services and infrastructure in rural communities and invest in food crop cultivation in order to enhance food security and poverty alleviation. Increasing access to inputs, equipment, training and advice is especially important if male and female farmers are no longer able to practice shifting cultivation due to the reduction/ loss of customary land and the need to farm more intensively on smaller areas of land.

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At various times during the Quaternary, north-eastern England was a zone of confluence between dynamic ice lobes sourced from the Pennines, northern Scotland, the Cheviots, and Scandinavia. The region thus has some of the most complex exposures of Middle to Late Pleistocene sediments in Britain, with both interglacial and glacial sediments deposited in terrestrial and marine settings. We investigated sedimentary sequences exposed on the coastline of County Durham at Warren House Gill, and present a new model of British and Fennoscandian Ice Sheet interaction in the North Sea Basin during the Middle Pleistocene. The stratigraphy at Warren House Gill consists of a lower diamicton and upper estuarine sediments, both part of the Warren House Formation. They are separated from the overlying Weichselian Blackhall and Horden tills by a substantial unconformity. The lower diamicton of the Warren House Formation is re-interpreted here as an MIS 8 to 12 glaciomarine deposit containing ice-rafted lithics from north-eastern Scotland and the northeast North Sea, and is renamed the ‘Ash Gill Member’. It is dated by lithological comparison to the Easington Raised Beach, Middle Pleistocene Amino Acid Racemisation values, and indirectly by optically stimulated luminescence. The overlying shallow subaqueous sediments were deposited in an estuarine environment by suspension settling and bottom current activity. They are named the ‘Whitesides Member’, and form the uppermost member of the Warren House Formation. During glaciation, ice-rafted material was deposited in a marine embayment. There is no evidence of a grounded, onshore Scandinavian ice sheet in County Durham during MIS 6, which has long been held as the accepted stratigraphy. This has major implications for the currently accepted British Quaternary Stratigraphy. Combined with recent work on the Middle Pleistocene North Sea Drift from Norfolk, which is now suggested to have been deposited by a Scottish ice sheet, the presence of a Scandinavian ice sheet in eastern England at any time during the Quaternary is becoming increasingly doubtful.

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Footemineite, ideally Ca2Mn2+square Mn22+Be4(PO4)(6)(OH)(4)-6H(2)O, triclinic, is a new member of the roscherite group. It occurs on thin fractures crossing quartz-microcline-spodumene pegmatite at the Foote mine, Kings Mountain, Cleveland County, North Carolina, U.S.A. Associated minerals are albite, analcime, eosphorite, siderite/rhodochrosite, fairfieldite, fluorapatite, quartz, milarite, and pyrite. Footemineite forms prismatic to bladed generally rough to barrel-shaped crystals up to about 1.5 mm long and I mm in diameter. Its color is yellow, the streak is white, and the luster is vitreous to slightly pearly. Footemineite is transparent and non-fluorescent. Twinning is simple, by reflection, with twin boundaries across the length of the crystals. Cleavage is good on {0 (1) over bar1}) and {100}. Density (calc.) is 2.873 g/cm(3). Footemineite is biaxial (-), n(alpha) = 1.620(2), n(beta) = 1.627(2), n(gamma) = 1.634(2) (white light). 2V(obs) = 80 degrees, 2V(calc) = 89.6 degrees. Orientation: X boolean AND b similar to 12 degrees, Y boolean AND c similar to 15 degrees, Z boolean AND a similar to 15 degrees. Elongation direction is c, dispersion: r > v or r < v, weak. Pleochroism: beta (brownish yellow) > alpha = gamma (yellow). Mossbauer and IR spectra are given. The chemical composition is (EDS mode electron microprobe, Li and Be by ICP-OES, Fe3+:Fe2+ y Mossbauer, H2O by TG data, wt%): Li2O 0.23, BeO 9.54, CaO 9.43, SrO 0.23, BaO 0.24, MgO 0.18, MnO 26.16, FeO 2.77, Fe2O3 0.62, Al2O3 0.14, P2O5 36.58, SiO2 0.42, H2O 13.1, total 99.64. The empirical formula is (Ca1.89Sr0.03Ba0.02)Sigma(1.94)(Mn-0.90(2+)square(0.10))Sigma(1.00)(square 0.78Li0.17Mg0.05) Sigma(1.00)(Mn3.252+Fe0.432+ Fe0.093+Al0.03)Sigma(3.80) Be-4.30(P5.81Si0.08O24)[(OH)3.64(H2O)0.36]Sigma(4.00)center dot 6.00H(2)O . The strongest reflection peaks of the powder diffraction pattern [d, angstrom (1, %) (hkl)] are 9.575 (53) (010), 5.998 (100) (0 (1) over bar1), 4.848 (26) (021), 3.192 (44) (210), 3.003 (14) (0 (2) over bar2), 2.803 (38) ((1) over bar 03), 2.650 (29) ((2) over bar 02), 2.424 (14) (231). Single-crystal unit-cell parameters are a = 6.788(2), b = 9.972(3), c = 10.014(2) A, (x = 73.84(2), beta = 85.34(2), gamma = 87.44(2)degrees,V = 648.74 angstrom(3), Z = 1. The space group is P (1) over bar. Crystal structure was refined to R = 0.0347 with 1273 independent reflections (F > 2(5). Footemineite is dimorphous with roscherite, and isostructural with atencioite. It is identical with the mineral from Foote mine described as ""triclinic roscherite."" The name is for the Foote mine, type locality for this and several other minerals.

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China Lake is located in Kennebec County, Maine. Since 1983 the lake has suffered from yearly algal blooms as a result of the addition of excess nutrients. The nutrient load was amplified by erosion within the watershed. Erosion varies widely depending on a number of factors, including the slope of the land, the type of soil, and the way the land is being used. Certain land use types have a high potential to add nutrients to the environment, while others may help absorb excess nutrients and prevent erosion and runoff into the lake. A comprehensive examination of the China Lake watershed was completed using GIS to calculate the erosion potential for the entire area, taking into account past and present land use patterns. This information will help the towns around the lake to make informed decisions about future development and land management.

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http://digitalcommons.colby.edu/atlasofmaine2005/1016/thumbnail.jpg

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http://digitalcommons.colby.edu/atlasofmaine2005/1025/thumbnail.jpg

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This document lists keywords for searching the collection of Kennebec County Interviews. Keywords are arranged in classic, hierarchical index style.

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The U.S. Department of Housing and Urban Development defines affordable housing as a household paying no more than 30 percent of its annual income on housing. That is, families who pay more than 30 percent of their income on housing are considered cost burdened and may have difficulty affording necessities such as food, clothing, healthcare, and transportation. This project focused on Kennebec County, Maine. Between 1990 and 2000, market demand for housing increased at a faster rate than did the supply of housing. Despite the addition of 6,719 homes, the average home price increased faster than average household income. This raises the question of just how many households in Kennebec County are facing unaffordable housing. Using shapefiles and data provided by the US Census Bureau, a map was created with ArcGIS to illustrate the percentage of households, down to the Census Block level of detail, that are paying more than 30 percent of their income to housing. By looking at this information I was able to get a better picture of the housing situation and where in the county households are having the hardest time meeting their needs. The results indicate that households in the more urbanized sections of the county are more likely than rurally located households to be facing unaffordable housing. Namely, Waterville and Augusta held the highest percentage of households paying more than 30 percent of their income for housing.

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Fire is a major management issue in the southwestern United States. Three spatial models of fire risk for Coconino County, Northern Arizona. These models were generated using thematic data layers depicting vegetation, elevation, wind speed and direction, and precipitation for January (winter), June (summer), and July (start of monsoon season). ArcGIS 9.0 was used to weight attributes in raster layers to reflect their influence on fire risk and to interpolate raster data layers from point data. Final models were generated using the raster calculator in the Spatial Analyst extension of ArcGIS 9.0. Ultimately, the unique combinations of variables resulted in three different models illustrating the change in fire risk during the year.

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A poster of the front cover for the publication prepared by the RISD Department of Landscape Architecture.