2 resultados para Huanglong World Natural Heritage Site

em Instituto Politécnico do Porto, Portugal


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Air pollution represents a serious risk not only to environment and human health, but also to historical heritage. In this study, air pollution of the Oporto Metropolitan Area and its main impacts were characterized. The results showed that levels of CO, PM10 and SO2 have been continuously decreasing in the respective metropolitan area while levels of NOx and NO2 have not changed significantly. Traffic emissions were the main source of the determined polycyclic aromatic hydrocarbons (PAHs; 16 PAHs considered by U.S. EPA as priority pollutants, dibenzo[a,l]pyrene and benzo[j]fluoranthene) in air of the respective metropolitan area. The mean concentration of 18 PAHs in air was 69.9±39.7 ng m−3 with 3–4 rings PAHs accounting for 75% of the total ΣPAHs. The health risk analysis of PAHs in air showed that the estimated values of lifetime lung cancer risks considerably exceeded the health-based guideline level. Analytical results also confirm that historical monuments in urban areas act as passive repositories for air pollutants present in the surrounding atmosphere. FTIR and EDX analyses showed that gypsum was the most important constituent of black crusts of the characterized historical monument Monastery of Serra do Pilar classified as “UNESCO World Cultural Heritage”. In black crusts, 4–6 rings compounds accounted approximately for 85% of ΣPAHs. The diagnostic ratios confirmed that traffic emissions were the major source of PAHs in black crusts; PAH composition profiles were very similar for crusts and PM10 and PM2.5.

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In this paper we study the optimal natural gas commitment for a known demand scenario. This study implies the best location of GSUs to supply all demands and the optimal allocation from sources to gas loads, through an appropriate transportation mode, in order to minimize total system costs. Our emphasis is on the formulation and use of a suitable optimization model, reflecting real-world operations and the constraints of natural gas systems. The mathematical model is based on a Lagrangean heuristic, using the Lagrangean relaxation, an efficient approach to solve the problem. Computational results are presented for Iberian and American natural gas systems, geographically organized in 65 and 88 load nodes, respectively. The location model results, supported by the computational application GasView, show the optimal location and allocation solution, system total costs and suggest a suitable gas transportation mode, presented in both numerical and graphic supports.