Abstract
The increasing importance of lignocellulosic biomass based energy production has led to an urgent need to conduct a reliable resource supply assessment. This study analyses and estimates the availability of agricultural residue biomass in Beijing, where biomass energy resources are relatively rich and is mainly distributed in the suburbs. The major types of crops considered across Beijing include food crops (e.g., maize, winter wheat, soybean, tubers and rice), cotton crops and oil-bearing crops (e.g., peanuts). The estimates of crop yields are based on historical data between 1996 and 2017 collected from the Beijing Municipal Bureau of Statistics. The theoretical and collectable amount of agricultural residues was calculated on the basis of the agricultural production for each crop, multiplied by specific parameters collected from the literature. The assessment of current and near future agricultural residues from crop harvesting and processing resources in Beijing was performed by employing three advanced modeling methods: the Time Series Analysis Autoregressive moving average (ARMA) model, Least Squares Linear Regression and Gray System Gray Model (GM) (1,1). The results show that the time series model prediction is suitable for short-term prediction evaluation; the least squares fitting result is more accurate but the factors affecting agricultural waste production need to be considered; the gray system prediction is suitable for trend prediction but the prediction accuracy is low.
Highlights
Biomass, as an important alternative energy source to conventional fossil fuels, has received major interest in recent years due to the progressive exhaustion of fossil fuels and the continually increasing demand for energy on a global level [1]
The estimate of biomass for the various categories of matrices used in Beijing was made by determining the potentially available quantity according to the type of biomass considered, which are agricultural residues from crop harvesting and processing for the present study
The raw crops’ yield data cannot be used directly in Time Series Analysis and a pre-processing of the data is necessary to fit it to different forecast forms
Summary
As an important alternative energy source to conventional fossil fuels, has received major interest in recent years due to the progressive exhaustion of fossil fuels and the continually increasing demand for energy on a global level [1]. In order to evaluate the feasibility of introducing biomass-derived energy applications, it is necessary to conduct an assessment of the resources and their availability [3]. As one type of renewable energy, agricultural residue has been widely seen as an effective substitute for conventional fuels such as petroleum, gas and coal [4,5]. Collection of agricultural waste for bioenergy use and promotion is one of the most important state affairs [6,7]. Various methods have been proposed on the availability of different biomass resources in the literature.
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