# Evaluating the Marginal Land Resources Suitable for Developing Bioenergy in Asia

Authors: Jingying Fu; Dong Jiang; Yaohuan Huang; Dafang Zhuang; Wei Ji
Journal: Advances in Meteorology
 (2014)

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## Abstract

Bioenergy from energy plants is an alternative fuel that is expected to play an increasing role in fulfilling future world energy demands. Because cultivated land resources are fairly limited, bioenergy development may rely on the exploitation of marginal land. This study focused on the assessment of marginal land resources and biofuel potential in Asia. A multiple factor analysis method was used to identify marginal land for bioenergy development in Asia using multiple datasets including remote sensing-derived land cover, meteorological data, soil data, and characteristics of energy plants and Geographic Information System (GIS) techniques. A combined planting zonation strategy was proposed, which targeted three species of energy plants, includingPistacia chinensis (P. chinensis), Jatropha curcas L. (JCL), and Cassava. The marginal land with potential for planting these types of energy plants was identified for each 1 km2 pixel across Asia. The results indicated that the areas with marginal land suitable for Cassava, P. chinensis, and JCL were established to be 1.12 million, 2.41 million, and 0.237 million km2, respectively. Shrub land, sparse forest, and grassland are the major classifications of exploitable land. The spatial distribution of the analysis and suggestions for regional planning of bioenergy are also discussed.


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## Body

## 1. Introduction

The world is facing problems related to finite availability of fossil fuels, the high price of petroleum, and the environmental impacts caused by the use of traditional fuels. The energy consumption of the world increased from 77,245 thousand barrels per day in 2001 to 88,034 thousand barrels per day in 2011. Asia Pacific accounted for 32% of the total world energy consumption [1]. This increase in energy demand is depleting fossil energy reserves at a high rate. In addition, the use of fossil fuels has caused many environmental problems, such as greenhouse gas (GHG) emissions. Therefore, energy security and climate change mitigation are two main drivers that have pushed renewable energy production to the top of the global agenda [2].Bioenergy, the most abundant and versatile type of renewable energy, has recently attracted worldwide attention [3]. Biofuels are environmentally friendly and carbon neutral and can play a prominent role in the energy portfolio [4]. The production of liquid biofuels can reduce GHG emissions by 12%–115% compared to traditional fossil fuels. GHG emissions are reduced 12% by the production and combustion of ethanol and 41% by biodiesel according to Hill et al. [5]. Adler et al. found that ethanol and biodiesel reduced GHG emissions by approximately 40% when derived from corn, by approximately 85% when from reed canary grass, and by approximately 115% when from hybrid switch grass and poplar [6]. The global warming potential (GWP, in kg CO2-equivalent) of the production of biodiesel in the UK was calculated Stephenson et al. The results showed that large-scale production of biodiesel saved 26% of the GWP and small-scale production saved 32% of the GWP when compared to ultralow sulphur diesel [7].The present global biomass demand for energy purposes is estimated to be 53 Quintillion joules [8]. Overall, global energy demand will grow 35%, even with significant efficiency gains. Energy demand in developing nations will rise 65 percent by 2040 (compared to 2010) as a result of expanding economies and growing populations. According to the new public energy outlook, 75 percent of the world’s population will reside in Asia Pacific and Africa by 2040. India will have the largest population after 2030 [9]. A wide range of indicators suggest that dramatic developments are taking place in Asian energy markets [10], and large-scale bioenergy development is extremely urgent.Recently, a number of studies have assessed the potential of biofuel. Kumar et al. assessed ethanol and biodiesel development in Thailand in terms of feedstock, production, planned targets, policies, and sustainability (environmental, socioeconomic, and food security aspects) [11]. An assessment of bioenergy potential was also carried out in England, the Midwest United States, China, and other countries [12–15]. The environmental life cycle assessment of lignocellulosic conversion to ethanol was reviewed by Borrion et al. Numerous studies of lignocellulosic ethanol fuel generated significantly different results due to differences in data, methodologies, and local geographic conditions [16]. In addition to feedstock, energy benefits, and GHG reductions, issues related to land resources and food security are an important consideration for Asia-scaled applications.Schröder et al. considered bioenergy development as an effective way to save the world from an energy crisis. They illustrated the ability to produce novel energy plants for growth on abandoned land [17]. Liu et al. analyzed the bioenergy production potential on marginal land in Canada. The results showed that approximately 9.48 million hectares could be identified as available marginal land in Canada. If this land was fully utilized for growing energy crops, the production of biofuel would be 33 million tons (using switch grass) or 380 million tons (using hybrid poplar). Batidzirai et al. reviewed the current, state-of-the-art approaches and methodologies used in bioenergy assessments and identified key elements that are critical determinants of bioenergy potentials. Bioenergy potential assessments in the US, China, India, Indonesia, and Mozambique were also presented in the paper [18]. Hattori and Morita [19] studied which energy crops can be used for sustainable bioethanol production and where they can be grown. They found that, in Japan and other Asian countries, rice can be grown as an energy crop in unused low-land paddy fields. Bioenergy development in China has also been studied, especially the potential energy production on marginal land in the context of food security [3, 20–22]. The biomass plantJatropha curcas L. (JCL) was shown to be a better economic, environmental, and land preservation alternative to corn or millet planted in the poor, gravel soil. and drought land in Taitung, Taiwan [23].However, the bioenergy development in the above-mentioned studies and most other current research is studied on a regional scale. A potential bioenergy view of the entirety of Asia is not available. The main objective of this study is to present a comprehensive assessment on the marginal land resources which are suitable for developing bioenergy in Asia, without affecting food and ecoenvironmental security. Asia is the world’s largest and most populous continent. It is facing significant pressure for food production. To avoid using the limited amount of arable land, adaptable energy plants that can be grown on marginal land and at scale must be used.Cassava, P. chinensis, andJCLhave been widely proven in existing literature and are further studied in this paper [14, 24–34].P. chinensis andJCLare nonfood plants.Cassava is used as a food plant in some places. However, we only analyzed its development potential in uncultivated areas (marginal land).Cassava andJCLare classified as second-generation biofuel feedstock, which are derived from crop residues, energy plants, and construction waste [35]. They can reduce GHG emissions and energy dependency during the life cycle when compared to the fossil fuel. The most important advantage of second-generation biofuels is that they will ensure the security of food supply compared with first-generation biofuels which are produced from food-based crops. They are sustainable and environmentally friendly [36]. Bioethanol is produced by hydrolysis and fermentation of carbohydrate feedstock. This type of energy plant usually has high saccharide, starch, and fiber content.Cassava which has been widely studied is this kind of plant. Biodiesel is produced from oil plants such asJCL. The oil extracted is blended with diesel to produce fuel [34, 37–47].To achieve our goal, we used Geographic Information System (GIS) technology to identify the spatial distribution of marginal lands which are suitable for bioenergy development. The datasets of growth habits of energy plants, remote sensing-derived land cover, terrain, meteorological data, and soil data were processed to 1 km2 grid across Asia.


## 2. Methodology

Four steps were implemented for this study. First, we identified the marginal land resources suitable for developing bioenergy in Asia. Second, we chose the three aforementioned energy plants that have been proven as biofuels. Third, we reviewed the environmental requirements of each energy plant including preferred meteorological conditions, soil, and terrain. Finally, a multiple factor analysis method was used to evaluate the bioenergy development potential based on the availability of marginal land resources and the growing conditions of the energy plants within the data grid. This analysis was performed using ArcMap software. The specific procedures are presented in Figure1.Figure 1
Evaluation of spatial distribution and suitability of marginal land resources for energy plants.


### 2.1. Data Acquisition

In this study, the land cover, terrain (including elevation and slope), meteorological conditions (including precipitation and temperature), and soil data (including soil organic matter content, soil depth, and soil texture) were used. The data sources and spatial resolutions are listed in Table1. All the data in this study was resampled to cover the entirety of Asia at a 1 km2 resolution.Table 1
Input data for identification of marginal land resources.
Input data
Data sources
Original spatial resolution
Land cover
ESA 2010 and UCLouvain [48]
1 km
Terrain
Elevation
SRTM [49]
90 m
Slope
90 m
Meteorological data
Precipitation
WorldClim [50]
30 arc-seconds (~1 km)
Temperature
30 arc-seconds (~1 km)
Soil data
Organic matter content
FAO/IIASA/ISRIC/ISS-CAS/JRC [51]
30 arc-seconds (~1 km)
Soil depth
30 arc-seconds (~1 km)
Soil texture
30 arc-seconds (~1 km)


#### 2.1.1. Land Cover

Land resources defined as marginal must also include land that is considered economically marginal. Therefore, we spatially define marginal land resources based on the land cover classification of unused land. The land cover dataset can be obtained from the GlobCover project. There are 23 land cover types in the dataset. This is the fundamental dataset for identification of marginal land that is suitable for bioenergy development.


#### 2.1.2. Terrain

The CGIAR-CSI GeoPortal provides SRTM 90 m digital elevation data for the entire world [49]. The digital elevation models (DEMs) of Asia were extracted from the dataset above, and the slope was calculated using the spatial analysis tool in ArcMap. Thresholds for DEMs and slope, based on the growth habits of each energy plant, were determined (see Section 2.2).


#### 2.1.3. Meteorological Data

WorldClim is a set of global climate layers (climate grids) with a spatial resolution of 30 arc-seconds (often referred to as 1 km resolution). The precipitation and temperature data used in this study were interpolated from observed data from 1950 to 2000 [50]. These two elements are very important for identifying suitable land. The requirement of each energy plant was identified (see Section 2.3).


#### 2.1.4. Soil Data

The Harmonized World Soil Database (HWSD) contributes sound scientific knowledge for planning sustainable expansion of agricultural production and for guiding policies to address emerging land competition issues concerning food production, bioenergy demand, and threats to biodiversity. A resolution of approximately 1 km was selected to analyze agroecological zoning, food security, and climate change impacts. Soil attribute data were linked with GIS so that specific parameters could be displayed, characterized, and analyzed. These parameters include soil units, organic carbon, pH, water storage capacity, soil depth, cation exchange, clay fraction, total exchangeable nutrients, lime and gypsum contents, sodium exchange percentage, salinity, textural class, and granulometry [51]. Soil texture, organic carbon content, and depth are key factors for growing energy plants.


### 2.2. Identification of Marginal Land

Marginal land has various meanings in different disciplines and, therefore, the spatial coverage of marginal land differs. Generally, marginal land is evaluated in terms of a cost-benefit analysis and is determined to be economically marginal [3]. Zhuang et al. established a marginal land evaluation system based on the definition of the Ministry of Agriculture (MoA) of China, a qualitative analysis of energy plants in different parts of China, expert suggestions on local planting of energy plants, land resources, and ecology, and other factors [22]. According to the definition of marginal land by MoA of China, marginal land is winter-fallowed paddy land and wasteland that may be used to cultivate energy crops. We only considered the wasteland in this study. Wasteland includes natural grassland, sparse forestland, scrubland, and unused land that may be used to grow energy crops [3]. We selected six land cover types as the available marginal land for growing the energy plants in compliance with the principle that bioenergy development should not compete with cropland and ecologically protected land. These six types were “mosaic vegetation (grassland/shrub land/forest) (50–70%)/cropland (20–50%),” “sparse (<15%) vegetation,” “mosaic grassland (50–70%)/forest or shrub land (20–50%),” “closed to open (>15%) (broad-leaved or needle-leaved and evergreen or deciduous) shrub land (<5 m),” “closed to open (>15%) grassland or woody vegetation on regularly flooded or waterlogged soil,” and “bare areas.” The selection of land cover types for each country can be flexible based on the law, policy, environmental conditions, and special regulations. For example, nature reserves should be excluded in further studies.


### 2.3. Characteristics of Selected Energy Plants

Cassava, as feedstock for fuel ethanol, has three advantages over others. First,Cassava is a shrubby tropical plant, widely grown for its large, tuberous, starchy roots, especially on marginal land. Second,Cassava is not a staple food for most people in Asia. Third, it is easy to comminute, has short cooking times, and has a low gelatinization temperature. Therefore,Cassava is a suitable feedstock for fuel ethanol [33, 57].P. chinensisis an ideal species for producing biodiesel. The tree has several outstanding characteristics: drought resistance, tolerance to cold climate, and tolerance to poor, acid, or alkaline soils. It also has some advantages that cannot be replaced by other trees, such as oil yield and its conversion rate, biodiesel quality, geographical distribution, adaptability, and economic benefits cycle. Therefore,P. chinensis is considered an important source of biodiesel [34, 47, 52].JCL is a famous biofuel plant and has been studied globally [31, 58]. It is a tropical species, native to Mexico and Central America, but is widely distributed in wild or semicultivated stands in Latin America, Africa, India, and South-East Asia [59]. TheJatropha curcas plant is a nonedible, drought-resistant, perennial plant that has the capability to grow on marginal lands because it requires very few nutrients to survive [34, 44].Jatropha has several other advantages, such as a short gestation period, resistance to common pests, lack of consumption by cattle, and production of biofertilizer and glycerine as useful by-products of biodiesel. In addition, the seed collection period ofJatropha does not coincide with the rainy season in June and July, which is when most agricultural activities take place. This makes it possible for people to generate additional income during the slack agricultural season [60, 61].All the specific requirements of the energy plants were chosen according to the literature and advice from experts. The growing conditions of the energy plants are listed in Table2. The marginal land presented in the previous section was used as the basic condition in the multiple factor analysis.Table 2
Growing conditions of energy plants.
Growing conditions
Cassava
[24]
P.  chinensis [52, 53]
JCL [54–56]
Suitable
Moderately suitable
Suitable
Moderately suitable
Suitable
Moderately suitable
Meteorological data
Annual average temperature/°C
21~29
18~21
10~15.3
5.8~10 or 15.3~28.4
20~25
17~20
Average annual extreme lowest temperature/°C
—
—
≥−15
−26.5~−15
≥2
0~2
Accumulated temperature of 10/°C·d
—
—
≥3800
1180~3800
—
—
Precipitation/mm
1000~2000
600~1000 or 2000~6000
400~1300
1300~1900
600~1000
300~600 or 1000~1300
Soil data [51]
Soil depth/cm
≥75
30~75
≥60
30~60
≥75
30~75
Soil organic matter content/%
≥3.5
1.5~3.5
—
—
≥3.5
1.5~3.5
Soil texture/classes
1
2
—
—
1
2
Terrain
Elevation/m
≤1500
1500~2000
—
—
≤500
500~1600
Slope/°
≤15
15~25
≤15
15~25
≤15
15~25We used strict criteria during the identification of suitable and moderately suitable areas for energy plants. Marginal land resource areas were only characterized as suitable if all of the suitable conditions were met. If one of the growing conditions was moderately suitable, the land resources were identified as moderately suitable.The soil texture data used in this paper was classified into two classes. Class 1 was defined as fine textured with more than 35% clay. Class 2 was defined as medium textured with a clay percentage between 18% and 35%. The soil texture requirement of energy plants is that the volumetric ratio of clay should be more than 30% for suitable land and 18%~35% for moderately suitable land. Therefore, there may be more potential land resource areas available for growing energy plants if more accurate soil data can be obtained.


## 2.1. Data Acquisition

In this study, the land cover, terrain (including elevation and slope), meteorological conditions (including precipitation and temperature), and soil data (including soil organic matter content, soil depth, and soil texture) were used. The data sources and spatial resolutions are listed in Table1. All the data in this study was resampled to cover the entirety of Asia at a 1 km2 resolution.Table 1
Input data for identification of marginal land resources.
Input data
Data sources
Original spatial resolution
Land cover
ESA 2010 and UCLouvain [48]
1 km
Terrain
Elevation
SRTM [49]
90 m
Slope
90 m
Meteorological data
Precipitation
WorldClim [50]
30 arc-seconds (~1 km)
Temperature
30 arc-seconds (~1 km)
Soil data
Organic matter content
FAO/IIASA/ISRIC/ISS-CAS/JRC [51]
30 arc-seconds (~1 km)
Soil depth
30 arc-seconds (~1 km)
Soil texture
30 arc-seconds (~1 km)


### 2.1.1. Land Cover

Land resources defined as marginal must also include land that is considered economically marginal. Therefore, we spatially define marginal land resources based on the land cover classification of unused land. The land cover dataset can be obtained from the GlobCover project. There are 23 land cover types in the dataset. This is the fundamental dataset for identification of marginal land that is suitable for bioenergy development.


### 2.1.2. Terrain

The CGIAR-CSI GeoPortal provides SRTM 90 m digital elevation data for the entire world [49]. The digital elevation models (DEMs) of Asia were extracted from the dataset above, and the slope was calculated using the spatial analysis tool in ArcMap. Thresholds for DEMs and slope, based on the growth habits of each energy plant, were determined (see Section 2.2).


### 2.1.3. Meteorological Data

WorldClim is a set of global climate layers (climate grids) with a spatial resolution of 30 arc-seconds (often referred to as 1 km resolution). The precipitation and temperature data used in this study were interpolated from observed data from 1950 to 2000 [50]. These two elements are very important for identifying suitable land. The requirement of each energy plant was identified (see Section 2.3).


### 2.1.4. Soil Data

The Harmonized World Soil Database (HWSD) contributes sound scientific knowledge for planning sustainable expansion of agricultural production and for guiding policies to address emerging land competition issues concerning food production, bioenergy demand, and threats to biodiversity. A resolution of approximately 1 km was selected to analyze agroecological zoning, food security, and climate change impacts. Soil attribute data were linked with GIS so that specific parameters could be displayed, characterized, and analyzed. These parameters include soil units, organic carbon, pH, water storage capacity, soil depth, cation exchange, clay fraction, total exchangeable nutrients, lime and gypsum contents, sodium exchange percentage, salinity, textural class, and granulometry [51]. Soil texture, organic carbon content, and depth are key factors for growing energy plants.


## 2.1.1. Land Cover

Land resources defined as marginal must also include land that is considered economically marginal. Therefore, we spatially define marginal land resources based on the land cover classification of unused land. The land cover dataset can be obtained from the GlobCover project. There are 23 land cover types in the dataset. This is the fundamental dataset for identification of marginal land that is suitable for bioenergy development.


## 2.1.2. Terrain

The CGIAR-CSI GeoPortal provides SRTM 90 m digital elevation data for the entire world [49]. The digital elevation models (DEMs) of Asia were extracted from the dataset above, and the slope was calculated using the spatial analysis tool in ArcMap. Thresholds for DEMs and slope, based on the growth habits of each energy plant, were determined (see Section 2.2).


## 2.1.3. Meteorological Data

WorldClim is a set of global climate layers (climate grids) with a spatial resolution of 30 arc-seconds (often referred to as 1 km resolution). The precipitation and temperature data used in this study were interpolated from observed data from 1950 to 2000 [50]. These two elements are very important for identifying suitable land. The requirement of each energy plant was identified (see Section 2.3).


## 2.1.4. Soil Data

The Harmonized World Soil Database (HWSD) contributes sound scientific knowledge for planning sustainable expansion of agricultural production and for guiding policies to address emerging land competition issues concerning food production, bioenergy demand, and threats to biodiversity. A resolution of approximately 1 km was selected to analyze agroecological zoning, food security, and climate change impacts. Soil attribute data were linked with GIS so that specific parameters could be displayed, characterized, and analyzed. These parameters include soil units, organic carbon, pH, water storage capacity, soil depth, cation exchange, clay fraction, total exchangeable nutrients, lime and gypsum contents, sodium exchange percentage, salinity, textural class, and granulometry [51]. Soil texture, organic carbon content, and depth are key factors for growing energy plants.


## 2.2. Identification of Marginal Land

Marginal land has various meanings in different disciplines and, therefore, the spatial coverage of marginal land differs. Generally, marginal land is evaluated in terms of a cost-benefit analysis and is determined to be economically marginal [3]. Zhuang et al. established a marginal land evaluation system based on the definition of the Ministry of Agriculture (MoA) of China, a qualitative analysis of energy plants in different parts of China, expert suggestions on local planting of energy plants, land resources, and ecology, and other factors [22]. According to the definition of marginal land by MoA of China, marginal land is winter-fallowed paddy land and wasteland that may be used to cultivate energy crops. We only considered the wasteland in this study. Wasteland includes natural grassland, sparse forestland, scrubland, and unused land that may be used to grow energy crops [3]. We selected six land cover types as the available marginal land for growing the energy plants in compliance with the principle that bioenergy development should not compete with cropland and ecologically protected land. These six types were “mosaic vegetation (grassland/shrub land/forest) (50–70%)/cropland (20–50%),” “sparse (<15%) vegetation,” “mosaic grassland (50–70%)/forest or shrub land (20–50%),” “closed to open (>15%) (broad-leaved or needle-leaved and evergreen or deciduous) shrub land (<5 m),” “closed to open (>15%) grassland or woody vegetation on regularly flooded or waterlogged soil,” and “bare areas.” The selection of land cover types for each country can be flexible based on the law, policy, environmental conditions, and special regulations. For example, nature reserves should be excluded in further studies.


## 2.3. Characteristics of Selected Energy Plants

Cassava, as feedstock for fuel ethanol, has three advantages over others. First,Cassava is a shrubby tropical plant, widely grown for its large, tuberous, starchy roots, especially on marginal land. Second,Cassava is not a staple food for most people in Asia. Third, it is easy to comminute, has short cooking times, and has a low gelatinization temperature. Therefore,Cassava is a suitable feedstock for fuel ethanol [33, 57].P. chinensisis an ideal species for producing biodiesel. The tree has several outstanding characteristics: drought resistance, tolerance to cold climate, and tolerance to poor, acid, or alkaline soils. It also has some advantages that cannot be replaced by other trees, such as oil yield and its conversion rate, biodiesel quality, geographical distribution, adaptability, and economic benefits cycle. Therefore,P. chinensis is considered an important source of biodiesel [34, 47, 52].JCL is a famous biofuel plant and has been studied globally [31, 58]. It is a tropical species, native to Mexico and Central America, but is widely distributed in wild or semicultivated stands in Latin America, Africa, India, and South-East Asia [59]. TheJatropha curcas plant is a nonedible, drought-resistant, perennial plant that has the capability to grow on marginal lands because it requires very few nutrients to survive [34, 44].Jatropha has several other advantages, such as a short gestation period, resistance to common pests, lack of consumption by cattle, and production of biofertilizer and glycerine as useful by-products of biodiesel. In addition, the seed collection period ofJatropha does not coincide with the rainy season in June and July, which is when most agricultural activities take place. This makes it possible for people to generate additional income during the slack agricultural season [60, 61].All the specific requirements of the energy plants were chosen according to the literature and advice from experts. The growing conditions of the energy plants are listed in Table2. The marginal land presented in the previous section was used as the basic condition in the multiple factor analysis.Table 2
Growing conditions of energy plants.
Growing conditions
Cassava
[24]
P.  chinensis [52, 53]
JCL [54–56]
Suitable
Moderately suitable
Suitable
Moderately suitable
Suitable
Moderately suitable
Meteorological data
Annual average temperature/°C
21~29
18~21
10~15.3
5.8~10 or 15.3~28.4
20~25
17~20
Average annual extreme lowest temperature/°C
—
—
≥−15
−26.5~−15
≥2
0~2
Accumulated temperature of 10/°C·d
—
—
≥3800
1180~3800
—
—
Precipitation/mm
1000~2000
600~1000 or 2000~6000
400~1300
1300~1900
600~1000
300~600 or 1000~1300
Soil data [51]
Soil depth/cm
≥75
30~75
≥60
30~60
≥75
30~75
Soil organic matter content/%
≥3.5
1.5~3.5
—
—
≥3.5
1.5~3.5
Soil texture/classes
1
2
—
—
1
2
Terrain
Elevation/m
≤1500
1500~2000
—
—
≤500
500~1600
Slope/°
≤15
15~25
≤15
15~25
≤15
15~25We used strict criteria during the identification of suitable and moderately suitable areas for energy plants. Marginal land resource areas were only characterized as suitable if all of the suitable conditions were met. If one of the growing conditions was moderately suitable, the land resources were identified as moderately suitable.The soil texture data used in this paper was classified into two classes. Class 1 was defined as fine textured with more than 35% clay. Class 2 was defined as medium textured with a clay percentage between 18% and 35%. The soil texture requirement of energy plants is that the volumetric ratio of clay should be more than 30% for suitable land and 18%~35% for moderately suitable land. Therefore, there may be more potential land resource areas available for growing energy plants if more accurate soil data can be obtained.


## 3. Results and Discussion

The planting zones of each energy plant were identified based on marginal land areas and the plant’s growth habits. The multiple factor analysis method was adopted to evaluate the suitable marginal land resources based on the evaluation criteria for suitable and moderately suitable growing conditions of each single factor and the type of available land cover. The distributions of marginal land resources suitable for the three energy plants are presented in Figures2, 3, and 4.Distribution of marginal land resources forCassava.
(a)
Spatial distribution
(b)
Distribution in different countriesDistribution of marginal land resources forP. chinensis.
(a)
Spatial distribution
(b)
Distribution in different countriesDistribution of marginal land resources forJCL.
(a)
Spatial distribution
(b)
Distribution in different countriesFrom the figures above, we can see that the area suitable for the growth ofP. chinensisis much larger than those for the other two plants. Approximately 70% of Asian countries have more than one thousand square kilometers of marginal land resources suitable forP. chinensis.CassavaandJCLresources are limited because they require warmer temperatures thanP. chinensis, andCassavahas a higher precipitation requirement. The results in Table 3 show that the areas of marginal land resources ofCassava, P. chinensis,andJCLare nearly 1.12 million, 2.41 million, and 237 thousand square kilometers, respectively. China has the most marginal land area available for all of the energy plants. Myanmar possesses 21% of the land resources suitable forCassava. Turkey and Thailand have the second largest marginal land resources suitable forP. chinensis andJCL. Shrub land is the dominant land cover type for growing energy plants, which accounts for 51.14% of the total suitable area. Mosaic vegetation is next, accounting for 34.49%.Table 3
Marginal land resources suitable and moderately suitable forCassava, P.   chinensis, and JCL planting based on multiple factor analysis in Asia (km2).
Land cover
Cassava
P.  chinensis
JCL
Total
S
M
S
M
S
M
S
M
Mosaic vegetation
1422
307537
130443
769321
1
92458
131866
1169316
Mosaic grassland
4
3697
17223
73886
0
2461
17227
80044
Shrub land
2089
788006
73008
942428
2
123672
75099
1854106
Herbaceous vegetation
6
16928
9221
89459
0
8794
9227
115181
Sparse vegetation
0
684
28002
180892
0
5732
28002
187308
Bare areas
0
3572
7529
88703
0
4530
7529
96805
Total
3521
1120424
265426
2144689
3
237647
268950
3502760
S: suitable land; M: moderately suitable land.


## 4. Conclusion

In this paper, a multiple factor analysis method was adopted to identify marginal land resources for three types of energy plants (Cassava, P. chinensis, andJCL) in Asia based on land cover, meteorological data, soil characteristics, terrain data, and the growth habits of energy plants. GIS was used to identify potential land resource areas at the resolution of 1 square kilometer. The conclusions of this study are as follows.(1)
The areas of marginal land suitable forCassava, P. chinensis, andJCL were established to be 1.12 million, 2.41 million, and 0.237 million km2, respectively. The policy and environmental constraints of each specific county were not considered in this study.
(2)
China has great prospects for bioenergy development. It has the most marginal land resources available for all three energy plants. Myanmar, Turkey, and Thailand have the second largest areas of marginal land resources available forCassava, P. chinensis, andJCL, respectively.
(3)
With regard to land cover, shrub land is the dominant land cover type for growing energy plants, accounting for 51.14% of the total suitable area. Mosaic vegetation is second, accounting for 34.49%.Bioenergy development is important and full of challenges. Further research needs to be performed to choose the best feedstock, improve marginal land resource calculations using more accurate input data, estimate the energy production potential, and analyze the environmental effects coupled with social and economic benefits.



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*Source: 238945-2014-03-13.xml*