Document Type : Complete scientific research article
Authors
1
1PhD student of Agrometeorology, Department of Irrigation and Reclamation, Faculty of Agricultural Engineering and Technology, College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran
2
Faculty Member of Wood Technology and Engineering Department, Gorgan Agricultural and Natural Resources University, Gorgan, Iran.
3
Faculty Member of Wood Technology and Engineering Department, Gorgan Agricultural and Natural Resources University, Gorgan, Iran
Abstract
Abstract
Equilibrium moisture content (EMC) of wood is one of the major indicators in wood industries. Determine of EMC in different locations of services, can prevent from wood waste due to meteorological parameters. This study was performed to estimate the relationship between EMC and the geo-statistical parameters (latitude, longitude and altitude). The results showed that the coastal and cool climate and locations have EMC higher than dry and central locations of Iran. The winter months, the early months of spring and fall months leading up to winter season have more EMC. The analysis showed that the spatial variations of the two variables latitude - height equation provide better results than the uni-variable equations. So, multivariable equations showed better results in compare with uni and two variable equations. The good results obtained in the multivariable equations in the warmer months. The best way to assess the EMC by spatial variables is regional scale study of EMC, inclusion of climatic conditions, remoteness and proximity to water sources and finally specific climate modeling for any region.
Abstract
Equilibrium moisture content (EMC) of wood is one of the major indicators in wood industries. Determine of EMC in different locations of services, can prevent from wood waste due to meteorological parameters. This study was performed to estimate the relationship between EMC and the geo-statistical parameters (latitude, longitude and altitude). The results showed that the coastal and cool climate and locations have EMC higher than dry and central locations of Iran. The winter months, the early months of spring and fall months leading up to winter season have more EMC. The analysis showed that the spatial variations of the two variables latitude - height equation provide better results than the uni-variable equations. So, multivariable equations showed better results in compare with uni and two variable equations. The good results obtained in the multivariable equations in the warmer months. The best way to assess the EMC by spatial variables is regional scale study of EMC, inclusion of climatic conditions, remoteness and proximity to water sources and finally specific climate modeling for any region.
The analysis showed that the spatial variations of the two variables latitude - height equation provide better results than the uni-variable equations. So, multivariable equations showed better results in compare with uni and two variable equations. The good results obtained in the multivariable equations in the warmer months. The best way to assess the EMC by spatial variables is regional scale study of EMC, inclusion of climatic conditions, remoteness and proximity to water sources and finally specific climate modeling for any region.
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