A spatiotemporal assessment of field residues of rice, maize, and wheat at provincial and county levels in China

Abstract

China has a huge resource potential for biomass‐based renewable energy development, but the resources of field residues are still not effectively used. Rice, maize, and wheat made up 89% of staple crop production in China in 2009. A comprehensive assessment of field residues of these three crops is necessary for the development of biomass‐based industries. This research was based on multiyear county‐level data of crop production, area and yield, as well as the crop phenology information from agrometeorological stations. Spatial and temporal analyses were conducted to quantify the spatial patterns, seasonal variations, and temporal trends of the three major field residues. The mean amount of field residue of rice, maize, and wheat was 470.8 Mt/year from 2002 to 2009. Rice residue topped the field residues at 188.5 Mt/year, followed by maize (152.6 Mt/year) and wheat (129.8 Mt/year). The resource supply of field residues varied temporally throughout the season, where peak months are May, June, September, and October. The resources of all three field residues increased from 2002 to 2009, topped by maize residues at a rate of 10.0 Mt/year. Spatially, high production counties had the fast growth rate and a strong positive spatial autocorrelation. The results showed that the intersection area of East and South Central regions has a spatially concentrated residue density and a stable supply for 5 months. The region can be considered as a suitable region for bioenergy development. A better understanding of spatial and temporal distribution of crop residues could facilitate strategic and tactical bioenergy planning.

Corn Residue Covered Area Mapping with a Deep Learning Method Using Chinese GF-1 B/D High Resolution Remote Sensing Images

“…The CRCA mapping is important for monitoring conservation tillage and agricultural subsidy policy application. Many studies have revealed the potential of crop residue covered area mapping using medium spatial resolution remote sensing images [58][59][60][61]. Considering the inhomogeneity and randomness resulting from human management difference, the Chinese high spatial resolution GF-1 B/D image and developed MSCU-net+C deep learning method is used to mapping CRCA in this study.…”

Mapping the environmental and techno‐economic potential of biojet fuel production from biomass residues in Brazil

“…At country level, other studies have also assessed the environmental potential of biomass residues. 22,27,28 Of all these studies, a more limited number 19,21,29,30 have used a bottom-up approach to model the environmental constraints spatially to estimate the biomass residue removal rate at field level. All of these studies contributed, to differing extents, to an understanding of how the spatial heterogeneity in agroecological conditions affect the environmental potential of biomass residues for bioenergy.…”

Spatially explicit analyses of sustainable agricultural residue potential for bioenergy in China under various soil and land management scenarios

“…China has a huge potential of agricultural residue resources to offer, but the residues are not effectively used, especially in terms of bioenergy production [1]. Apart from using residues as livestock feed, rural household fuel, paper pulp, and substrate for mushroom cultivation, agricultural residue-based bioenergy production is now a popular practice in many countries, such as Denmark, Sweden, the UK, Spain, and China [2].…”

“…Therefore, it is necessary to answer the questions arising about the extent of the potential of available agricultural residues and their spatial distribution. In recent decades, an increasing number of studies estimating the potential of biomass feedstocks were carried out at global, national, or regional scales by using different research methods, i.e., either statistical [2,[7][8][9][10][11][12][13][14][15] or geographic information system (GIS)-based methods [1,6,[16][17][18][19][20]. However, evaluated quantities of biomass residues available for bioenergy production vary greatly among different studies due to differences in the types of crop residues analysed, residue to product ratios, and constraining factors taken into account.…”