Diffendorfer Jay E, Compton Roger W
U.S. Geological Survey, Geosciences and Environmental Change Science Center, Denver Federal Center, Denver, Colorado, United States of America.
PLoS One. 2014 Feb 18;9(2):e88914. doi: 10.1371/journal.pone.0088914. eCollection 2014.
Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here.
与风力设施相关的土地转化(每兆瓦表面扰动面积,单位为公顷)在报告值上存在很大差异。此外,尚无研究试图解释不同设施之间的这种差异。我们利用高分辨率航空影像对39个风力设施的土地转化情况进行了数字化处理。然后,我们在三个空间尺度上模拟了涡轮机尺寸、布局、土地覆盖和地形对土地转化水平的影响。这些尺度包括机组列(仅含中间有道路的涡轮机)、场地(有机组列且有连接道路、地下电缆和其他基础设施)以及整个设施(场地以及将其与现有基础设施相连的道路或输电线路)。一种信息论建模方法表明,土地覆盖和地形是影响土地转化的有力支持变量,但涡轮机尺寸和布局并非如此。耕地景观尽管涡轮机之间距离较大,但平均土地转化较低,而森林景观中的设施通常土地转化最高。在场地和机组列尺度上,平坦地形的土地转化最低,而台地的设施土地转化最大。结果表明,风力设施所处的景观会影响与风能相关的土地转化水平。这为优化风能生产同时最小化土地覆盖变化创造了机会。此外,结果表明,预测风能对土地转化的影响应包括此处报告的影响土地转化的地理变量。