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Variations in fuel characteristics of corn (Zea mays) stovers: General spatial patterns and relationships to soil properties

机译:玉米(Zea mays)秸秆燃料特性的变化:总体空间格局及其与土壤特性的关系

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摘要

The geographic variations in corn stover fuel and soil characteristics from 22 sites in the Kerchin region (43.8-45.0°N, 122.7-125.1°E), north-east China, were examined in both 2006 and 2007. The correlations between fuel characteristics and soil parameters were analysed using principal component analysis (PCA) and partial least squares regression (PLS). The main emphasis was on the feasibility of using corn stovers as feedstock in direct combustion for heat and power generation. The examined corn stovers from Kerchin generally have similar characteristics to energy grasses grown in Europe and may be used as biofuels. However, large variations, up to several orders of magnitude, in the fuel characteristics existed among the samples. With PCA, the studied soils showed a clear distinction between soluble and less soluble elements, with a trend for higher insoluble element (such as Si) concentrations in southwestern soils and a higher pH in the more northern soils. The component for fuel characteristics showed a distinct trend with latitude that can be explained by the above-mentioned soil component pattern. PLS regression models suggested some important relationships that may be used to predict corn stover fuel characteristics using soil and environment properties; for example, latitude, soil pH and Si are the most important predictors for Ca content in corn stovers, but not for K that is best predicted by soil K. Although limited by numbers of samples and sites, this study indicated that this approach can be used to predict biofuel quality.
机译:在2006年和2007年,研究了中国东北克孜钦地区(43.8-45.0°N,122.7-125.1°E)的22个站点的玉米秸秆燃料和土壤特征的地理变化。使用主成分分析(PCA)和偏最小二乘回归(PLS)分析土壤参数。主要重点是使用玉米秸秆作为直接燃烧产生热量和发电的原料的可行性。经过检查的科钦玉米秸秆通常具有与欧洲种植的能源草相似的特性,可以用作生物燃料。然而,样品之间在燃料特性方面存在大的变化,直至几个数量级。使用PCA,所研究的土壤在可溶性元素和难溶性元素之间表现出明显的区别,在西南土壤中存在较高的不溶元素(例如Si)浓度,在较北部土壤中具有较高的pH值趋势。用于燃料特性的成分表现出明显的纬度趋势,可以通过上述土壤成分模式来解释。 PLS回归模型提出了一些重要的关系,可以利用土壤和环境特性来预测玉米秸秆的燃料特性。例如,纬度,土壤pH值和Si是玉米秸秆中Ca含量的最重要预测指标,但不是土壤K能够最佳预测的K指标。尽管受样品和地点数量的限制,但这项研究表明该方法可以用于预测生物燃料质量。

著录项

  • 来源
    《Renewable energy》 |2010年第6期|1185-1191|共7页
  • 作者单位

    Unit of Biomass Technology and Chemistry, Swedish University of Agricultural Sciences, SE-901 83 Umea, Sweden College of Life Science, Beijing Normal University, Beijing, China;

    College of Life Science, Beijing Normal University, Beijing, China;

    Biomass Engineering Centre, China Agricultural University, Beijing, China;

    Unit of Biomass Technology and Chemistry, Swedish University of Agricultural Sciences, SE-901 83 Umea, Sweden;

    Unit of Biomass Technology and Chemistry, Swedish University of Agricultural Sciences, SE-901 83 Umea, Sweden;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    corn stover; fuel characteristics; geographic pattern; soil property; PCA;

    机译:玉米秸秆;燃油特性地理格局土壤性质PCA;
  • 入库时间 2022-08-18 00:26:48

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