1) design, develop, and implement systems and databases to access and store geospatial data - 2) analyze data utilizing mapping software - 3) design digital maps using geospatial data and analyze spatial and non-spatial information - 4)Prepares the project's safety plan and is responsible for ensuring safety and executing work in compliance with company's safety procedure, government safety and regulations, standards and procedures as well as clients safety requirements.
Description: Studies about the health effects of long-term average exposure to outdoor air pollution have played an important role in the recent health impact assessments. Exposure assessment for epidemiological studies of long-term exposure to ambient air pollution remains a difﬁcult challenge because of substantial small-scale spatial variation. Current approaches for assessing intra-urban air pollution contrasts include the use of exposure indicator variables, interpolation methods, dispersion models and land-use regression (LUR) models. LUR models have been increasingly used in the past few years. Land-use regression combines monitoring of air pollution at typically 20-100 locations, spread over the study area, and development of stochastic models using predictor variables usually obtained through Geographic Information Systems (GIS). Signiﬁcant predictor variables include various trafﬁc representations, population density, land use, physical geography (e.g. altitude) and climate. Land-use regression methods have generally been applied successfully to model annual mean concentrations of SO2, NO2, PM10, PM2.5, the soot content of PM and VOCs in different environments, including European and North-American cities. The performance of the method in urban areas is typically better or equivalent to geo-statistical methods, such as kriging, and dispersion models. Further developments of the land-use regression method have more focus on developing models. This can be transferred to other areas and include of additional predictor variables such as wind direction or emission data and further exploration of focal sum methods. Models that include a spatial and a temporal component are of interest for (e.g. birth cohort) the studies that require exposure variables on a ﬁner temporal scale. There is a strong need for validation of LUR models with personal exposure monitoring.
Description: There is growing knowledge that the cement industry is a significant contributor to global greenhouse gases emissions. It is expected that this industry will come under increasing regulatory pressures to reduce its emissions and contribute more aggressively to mitigating global warming. It is important that the industry’s stakeholders become more familiar withglobal warming issues, along with emerging policies that may affect the future of the industry. This paper discusses climate change, the current and proposed actions for mitigating its effects, and the implications of such actions for the cement industry. International negotiations on climate change are summarized and mechanisms available under the Kyoto Protocol for reducing greenhouse gas emissions are explained.The paper examines some of the traditional and emerging related regulations for greenhouse gas emissions and analyses their advantages and disadvantages. The applicability, effectiveness and potential impact of these related regulations for the global cement industry in general is discussed with recommendations for possible courses of action.