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<p>This study investigates the influence of climate variables, specifically temperature and relative humidity, on the equilibrium moisture content (EMC) of wood—a critical quality parameter. Using data from 100 synoptic stations across Iran (1987–2019), we analyzed trends in temperature, humidity, and EMC through the Mann-Kendall and Sen’s slope methods. Future projections (2020–2049) employed CMIP6 models—CanESM5, CanESM5-CanOE, CNRM-CM6-1, CNRM-ESM2-1, and IPSL-CM6A-LR—under SSP scenarios, with model selection based on RMSE, Scatter Index, and R². Scenarios SSP1-2.6, SSP2-4.5, and SSP5-8.5 were used to project future climatic conditions and corresponding EMC values. The CanESM5-CanOE model exhibits the lowest monthly relative humidity estimation errors in Iran, with errors ranging from 10.1% to 15.0% across different climate zones. Increasing EMC is most frequent under SSP1-2.6 (20%-92% of stations) and SSP5-8.5 (34%-100%). Decreasing trends are significant under SSP2-6.5 (66%-100%) and SSP5-8.5 (45%-88%). Monthly variations: -4.74% to + 3.71%; seasonal: -2.87% to + 2.45%; annual: -1.17% to + 1.00%. Significantly decreasing EMC trends are under SSP2-6.5, increasing trends under SSP5-8.5. Over a 30-year span, EMC varied from 0.06 to 0.62% in winter, from − 1.14 to -1.23% in spring, from − 0.84 to -0.89% in summer, and from − 0.80 to -1.34% in autumn, with most changes being statistically significant. These findings suggest climate change will substantially impact on wood EMC, underscoring the importance of revising future EMC standards accordingly.</p>

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Analyzing climate change trends and projection of their effects on wood equilibrium moisture content using CMIP6 models under SSP scenarios in Iran

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月23日

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  • Jalil Helali,
  • Mehdi Mohammadi Ghaleni,
  • Zahra Kalantari,
  • Christian Brischke,
  • Ebrahim Asadi Oskouei

摘要

This study investigates the influence of climate variables, specifically temperature and relative humidity, on the equilibrium moisture content (EMC) of wood—a critical quality parameter. Using data from 100 synoptic stations across Iran (1987–2019), we analyzed trends in temperature, humidity, and EMC through the Mann-Kendall and Sen’s slope methods. Future projections (2020–2049) employed CMIP6 models—CanESM5, CanESM5-CanOE, CNRM-CM6-1, CNRM-ESM2-1, and IPSL-CM6A-LR—under SSP scenarios, with model selection based on RMSE, Scatter Index, and R². Scenarios SSP1-2.6, SSP2-4.5, and SSP5-8.5 were used to project future climatic conditions and corresponding EMC values. The CanESM5-CanOE model exhibits the lowest monthly relative humidity estimation errors in Iran, with errors ranging from 10.1% to 15.0% across different climate zones. Increasing EMC is most frequent under SSP1-2.6 (20%-92% of stations) and SSP5-8.5 (34%-100%). Decreasing trends are significant under SSP2-6.5 (66%-100%) and SSP5-8.5 (45%-88%). Monthly variations: -4.74% to + 3.71%; seasonal: -2.87% to + 2.45%; annual: -1.17% to + 1.00%. Significantly decreasing EMC trends are under SSP2-6.5, increasing trends under SSP5-8.5. Over a 30-year span, EMC varied from 0.06 to 0.62% in winter, from − 1.14 to -1.23% in spring, from − 0.84 to -0.89% in summer, and from − 0.80 to -1.34% in autumn, with most changes being statistically significant. These findings suggest climate change will substantially impact on wood EMC, underscoring the importance of revising future EMC standards accordingly.