13 Recent Developments in Industrial Minerals Research: Issues and Processes (Posters)

A REGIONAL PREDICTIVE MODEL OF CRUSHED STONE AGGREGATE PRODUCTION SITES IN NEW ENGLAND

Program: THEME SESSIONS
Time: 8:00 AM – 12:00 PM

Authors

Abstract

Production sites for aggregate occur where suitable source materials exist and where transportation and market conditions are favorable. Weights of evidence is used to model crushed stone aggregate (CS) production sites using geologic map, transportation network, and population data in New England. This analysis shows that 72% of 89 CS producers are sited within 1 mile of either a principle highway or rail line in the region (34% of area). 78% of CS producers are sited in census tracts with population densities exceeding 100 people/square mile (27% of area). These relations illustrate the importance of proximity to transportation corridors and developing areas where aggregate is predominately used. No CS producers are located in census tracts with population densities less than 15 people/square mile, reflecting the lack of sufficient market demand in many rural areas. CS is predominately produced from three hard rock types that are widely distributed in New England; 20% of sites use carbonate rock, 27% use granite, and 37% use mafic rocks. Carbonate rocks and Jurassic basalt are the most important source rocks on an area-weighted basis.

The increasing demand for aggregate and the difficulty of developing and permitting new sites of aggregate production means that aggregate will be supplied from sources yet to be developed or delineated in many areas. Site development and permitting for aggregate production is difficult because many land management plans and zoning actions fail to anticipate future demand patterns that integrate the aggregate quality, transportation, and socioeconomic factors that define the economic viability of the industry. Spatial analysis quickly ranks tracts by their relative suitability for production of CS based on geology, transportation, and population. The results of this regional analysis can identify areas for more detailed evaluation. As transportation or population features change, the model can be revised easily to reflect these changes.