کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
301519 512508 2010 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Variations in fuel characteristics of corn (Zea mays) stovers: General spatial patterns and relationships to soil properties
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
Variations in fuel characteristics of corn (Zea mays) stovers: General spatial patterns and relationships to soil properties
چکیده انگلیسی

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 south-western 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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Renewable Energy - Volume 35, Issue 6, June 2010, Pages 1185–1191
نویسندگان
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