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首页> 外文期刊>Atmospheric chemistry and physics >Spatiotemporal distribution of nitrogen dioxide within and around a large-scale wind farm - a numerical case study
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Spatiotemporal distribution of nitrogen dioxide within and around a large-scale wind farm - a numerical case study

机译:大型风电场内外氮素二氧化氮的时空分布 - 一个数值案例研究

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摘要

As a renewable and clean energy source, wind power has become the most rapidly growing energy resource worldwide in the past decades. Wind power has been thought not to exert any negative impacts on the environment. However, since a wind farm can alter the local meteorological conditions and increase the surface roughness lengths, it may affect air pollutants passing through and over the wind farm after released from their sources and delivered to the wind farm. In the present study, we simulated the nitrogen dioxide (NO2) air concentration within and around the world's largest wind farm (Jiuquan wind farm in Gansu Province, China) using a coupled meteorology and atmospheric chemistry model WRF-Chem. The results revealed an "edge effect", which featured higher NO2 levels at the immediate upwind and border region of the wind farm and lower NO2 concentration within the wind farm and the immediate downwind transition area of the wind farm. A surface roughness length scheme and a wind turbine drag force scheme were employed to parameterize the wind farm in this model investigation. Modeling results show that both parameterization schemes yield higher concentration in the immediate upstream of the wind farm and lower concentration within the wind farm compared to the case without the wind farm. We infer this edge effect and the spatial distribution of air pollutants to be the result of the internal boundary layer induced by the changes in wind speed and turbulence intensity driven by the rotation of the wind turbine rotor blades and the enhancement of surface roughness length over the wind farm. The step change in the roughness length from the smooth to rough surfaces (overshooting) in the upstream of the wind farm decelerates the atmospheric transport of air pollutants, leading to their accumulation. The rough to the smooth surface (undershooting) in the downstream of the wind farm accelerates the atmospheric transport of air pollutants, resulting in lower concentration
机译:作为可再生和清洁的能源来源,在过去的几十年里,风电已成为全球最快的能源资源。被认为没有对环境产生任何负面影响的风力。然而,由于风电场可以改变局部气象条件并增加表面粗糙度长度,因此在从它们的来源释放并送到风电场后,它可能会影响通过穿过风电场的空气污染物。在本研究中,我们使用耦合气象和大气化学模型WRF-Chem模拟了世界上最大的风电场内和世界各地的二氧化氮(NO2)空气集中(甘肃省九泉风电场)。结果揭示了“边缘效应”,其在风电场的立即上冲和边界区域的高压和边界地区具有较高的NO2水平,并且在风电场内降低NO2浓度和风电场的立即下风过渡区域。采用表面粗糙度长度方案和风力涡轮机阻力方案参数化这一模型调查中的风电场。建模结果表明,与没有风电场的情况相比,均参数化方案两种参数化方案在风电场的立即上游和风电场的浓度下降。我们推断出这种边缘效应和空气污染物的空间分布,是由风力涡轮机转子叶片的旋转驱动的风速和湍流强度的变化引起的内部边界层的结果,并通过了表面粗糙度长度的增强风电场。在风电场上游的平滑到粗糙表面(过冲)中粗糙度长度的粗糙度长度减速了空气污染物的大气输送,导致其积累。在风电场下游的光滑表面(下汗)加速了空气污染物的大气运输,导致浓度较低

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  • 来源
    《Atmospheric chemistry and physics》 |2017年第23期|共14页
  • 作者单位

    Lanzhou Univ Coll Earth &

    Environm Sci Key Lab Environm Pollut Predict &

    Control Lanzhou Gansu Peoples R China;

    Lanzhou Univ Coll Earth &

    Environm Sci Key Lab Environm Pollut Predict &

    Control Lanzhou Gansu Peoples R China;

    Lanzhou Univ Coll Earth &

    Environm Sci Key Lab Environm Pollut Predict &

    Control Lanzhou Gansu Peoples R China;

    Lanzhou Univ Coll Earth &

    Environm Sci Key Lab Environm Pollut Predict &

    Control Lanzhou Gansu Peoples R China;

    Lanzhou Univ Coll Atmospher Sci Lanzhou Gansu Peoples R China;

    Lanzhou Univ Coll Earth &

    Environm Sci Key Lab Environm Pollut Predict &

    Control Lanzhou Gansu Peoples R China;

    Lanzhou Univ Coll Earth &

    Environm Sci Key Lab Environm Pollut Predict &

    Control Lanzhou Gansu Peoples R China;

    Lanzhou Univ Coll Earth &

    Environm Sci Key Lab Environm Pollut Predict &

    Control Lanzhou Gansu Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 大气科学(气象学);
  • 关键词

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