Ecological footprint accounting based on emergy—A case study of the Chinese society

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

available at www.sciencedirect.com

journal homepage: www.elsevier.com/locate/ecolmodel

Ecological footprint accounting based on emergy—A case study of the Chinese society B. Chen, G.Q. Chen∗ National Laboratory for Turbulence and Complex Systems, Department of Mechanics and Engineering Science, Peking University, Beijing 100871, China

a r t i c l e

i n f o

a b s t r a c t

Article history:

The resource consumption of the Chinese society from 1981 to 2001 is investigated using

Received 17 August 2005

ecological footprint (EF) and emergetic ecological footprint (EEF). The latter is a newly devel-

Received in revised form

opment modification of ecological footprint based on ecological thermodynamics. Individ-

13 April 2006

ual sectors in society are described in detail corresponding to the EF and EEF components

Accepted 19 April 2006

based on different views of ecological production. The EF and EEF intensities are also pre-

Published on line 23 June 2006

sented to depict the resource consumption level corresponding to unit economic output. Finally, EEF is suggested to serve as a modified indicator of EF to illustrate the resource,

Keywords:

environment, and population activity, and thereby reflecting the ecological overshoot of the

China

general ecological system. © 2006 Elsevier B.V. All rights reserved.

Ecological Footprint Emergy Resource consumption

1.

Introduction

Natural capital accounts focused on biophysical limits are increasingly prominent. Meanwhile, there is a felt need for the scarce productive land to support complex social–economic– ecological systems. This paper intends to present a case study of ecological footprint for the “emerging economy" of China, a country with one-fifth of the world’s population, and at present the second largest economic and energy consumption. Currently, resources, such as fossil fuels, agricultural products and forest products, have been squeezed along with the constantly increasing GDP. It is necessary to make an overall analysis of the society from the biophysical perspective.

∗

Corresponding author. Tel.: +86 1062767167; fax: +86 1062750416. E-mail address: [email protected] (G.Q. Chen).

0304-3800/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.ecolmodel.2006.04.022

1.1.

Chinese society from 1981 to 2001

Chinese population increased steadily during 1981–2001 (Fig. 1). Announced in 1979, the one-child family policy was enforced as the basic principle of China in order to control population growth. Nevertheless, the one-child policy is a difficult target to achieve, with the population increasing steadily from 1.01 × 109 in 1981 to 1.28 × 109 in 2001. The large increasing population in China leads to a low per capita availability of essential natural resources. Also, the energy efficiency of China is relative low compared with other countries. Economic development always has priority over sustainable economic-environment development. This has resulted in an overloaded and depleted resource base in China.

102

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

As shown in Figs. 2 and 3 the rapid development of GDP or GDP per capita, which has been considered as the hallmark of the Chinese economy, experiences three major periods. During the first period (from 1981 to 1986), industrialization and reform of agriculture contributed most to the GDP growth. The rapidly growing industries and services drove the GDP during the second period (from 1987 to 1991). During the last period (from 1992 to 2001), GDP increased linearly at the average growth rate of 10%. Since the early 1990s, the Chinese economy has achieved a soft-landing after the central government took measures to adjust the economic polices and restrain overexpanded infrastructures (Teather and Yee, 1999). In addition, there is growing concerns regarding agricultural production in China. Soil and water loss is one of the most serious problems agriculture confronts, for large amount of nutrients in nearly 5 billions tonnes of eroded soil are carried each year to the sea from the local areas, weakening the foundation of the agriculture. Lastly, different provinces and counties are often directed by the government to promote special crop production according to the local cropping conditions and economic status thus regional inequalities in grain production.

1.2.

Ecological footprint

Vitousek et al. (1986) attempted to determine the human economy’s draw on terrestrial net primary productivity and estimate the magnitude of human appropriation of the products of photosynthesis, which can be regarded as a conceptual predecessor of the EF which assesses the relationship between humans and resources (Wackernagel and Monfreda, 2004). Wackernagel and Rees (1996, 1997) proposed the ecological footprint (EF hereafter) as an indicator of the carrying capacity of regions, nations and the globe, and sometimes extended it as an indicator of sustainability. EF is defined as the aggregate area of land and water in various ecological categories that is claimed by participants in that economy to produce all the resources they consume, and to absorb all their wastes they generate on a continuous basis, using prevailing technology , and later, modified to measure the biocapacity a population, organization, or process requires to produce its resources and absorb its waste using prevailing technology (Wackernagel and Monfreda, 2004). There are some potential improvements in the current EF method. First, as van den Bergh and Verbruggen (1999) pointed out, the physical consumption-land conversion factors function as implicit weights in the conversion as well as the aggregation, which impede the application of EF as an objective indicator in ecological evaluation without any arbitrary components. Second, an ecological evaluation indicator should reflect both the quantity and quality of the resource, not just a hypothetical land area derived from the quantity of biomass produced from different types of bioproductive areas, wherein the resource quality is the intrinsic value of the ecological products and the core of sustainable or unsustainable development mode of the ecological system, e.g., land system. Third, to avoid the debate on the land required to absorb carbon (Ayres, 2000), an alternative method should be presented to determine the ecological footprint caused by energy, especially fossil fuels. Although the energy produced from nuclear and

renewable resources, such as wind power, water power, photovoltaic, tide power, etc. are roughly investigated by Wackernagel (2004), the related estimation is based on some local case studies, which is still uncertain for other regions or nations. Lastly, as Wackernagel and Monfreda (2004) indicated, embodied energy should be considered, especially the free energy source dominated by the energy embodied in most renewable resources infrastructure. In view of the time and space scales, depending on the researcher’s objectives and knowledge, the sense of the EF can be interpreted in different ways. With the fundamental time scale of the ecospherical evolution and space scale of the global earth, the EF serves as an indicator of sustainability , for each global hectare is formed and sustained by the others. Meanwhile, on smaller time and space scales, e.g., national or regional, EF can be regarded as an indicator of ecological competitive power, for the limited commodities appropriated by humans and the “actual land area” humans demand are out of consideration for the anthropogenic, temporary and local economic views, not the earth-centered ecocentrism (Chen, 2005, 2006). As Wackernagel et al. (2004a) indicated, the EF can be measured by either consumption or production. Associated with the EF based on consumption, the concept “ecological deficit” is proposed, whereas the concept “ecological overshoot” is presented based on production. Considering a country with much less net import compared to the domestic production, which can be termed as “production-based” country, the concept “ecological overshoot” is more appropriate to reflect the ecological resource depletion of the country. Meanwhile, regarding a country with much more net import compared to the domestic production, which is termed as “service-based” country, the concept “ecological deficit” describes the seized resources of the country from the “global ecological hectare share”, which should be understood as ecological competitive power.

1.3.

Emergy

Defined as the availability of energy (exergy) of one kind that is used-up in transformations directly or indirectly to make a product or service with the unit emjoule (Odum, 1983, 1988, 1994, 1996), emergy reflects the “energy memory” of the work previously done to make a product or service. Thus, emergy represents a donor value different from the general use value of certain good or service (Brown and Ulgiati, 1997, 2004a,b; Sciubba and Ulgiati, 2005). Accounting the donated exergy in the development of the system embedded in the surrounding environment, emergy measures how much resources are obtained from the context of environment on which the system relies. With a kind of path-dependent integration, emergy and transformity calculations are determined by the process generating the product or service. Natural selection and evolution patterns are therefore implicated in the concept, for the path is presumed along with a generative trial and error process based on the maximum power-output principle stem from Darwin’s theory of natural selection and Lotka’s hypothesis of natura selection as an energy-maximum process (Odum and Pinkerton, 1955; Sciubba and Ulgiati, 2005). Therefore, emergy method as a kind of energy equivalent assessment performs

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

well when dealing with large scale steady-state ecological systems. To distinguish emergy units from available energy units and assess the energy quality (Brown and Ulgiati, 2004a), all energy transformations are simplified from a complex interconnected energy web to a linear energy hierarchy in the holistic view, considering the components of similar transformity can be combined and interconnections as close loop transfer function with feedback circuit can be further transformed into open loop system with one-source forward successive chain. The rate of entropy production or available energy (exergy) consumption is implicated in the transformity, for each segment of the chain is regarded as a black-box identified only with input–output flows when the transformity per se as a kind of input–output process efficiency is calculated. Unlike human-dominated production that is optimized to meet the control objective, natural processes of the ecological system tend to maximize the exergy storage or dissipation during different stages (Jørgensen et al., 1995, 2000; Fath, 2004; Fath et al., 2004), thus self-adapting to the changing environment with more structures emerged and higher hierarchy obtained. Economic value, argued by Odum, is thus reduced to solar emergy, considering the fact that money and energy flow in the opposite direction in the economy. Resource flows that are not exchanged in the market, including the renewable energy resources of solar radiation, precipitation, wind, wave, topsoil, etc., are internalized in the economic production and evaluated by emergy. Moreover, labor, culture and information, can also be evaluated by emergy in terms of donations required to generate them. Recently, emergy used to build and maintain genetic information of the biological organisms is estimated and the preliminary relationship between the emergy costs of gene maintenance and the solar transformity of biomass is revealed (Jørgensen et al., 2004). Emergy analysis has been conducted on regional scales (e.g., Odum et al., 1987b; Odum, 1996; Campbell, 1997; Higgins, 2003), national scales (e.g., Odum, 1983; Pillet and Odum, 1984; Pillet et al., 2001; Odum, 1996; Brown and Ulgiati, 1997; Ulgiati et al., 1993, 1994, 1995; Ulgiati and Brown, 1998, 1999) and global scales (e.g., Odum, 1996; Brown and Ulgiati, 2004b). A Handbook of Emergy Evaluation standardizes the procedure from illustrating overview system diagrams, organizing analysis tables to calculating different indices (Odum, 2000a,b; Odum et al., 2000; Brown and Bardi, 2001; BrandtWilliams, 2002; Kangas, 2002). Emergy analysis to various ecosystems are also provided (e.g., Ulgiati et al., 1993; Brown and McClanahan, 1996; Odum, 2000a,b; Nelson et al., 2001; Kang and Park, 2002; Martin, 2002; Brown and Buranakarn, 2003).

1.4.

Emergy and ecological footprint

Time series research on EF has been done in order to “track” the amount of natural resource a population used in related to the carrying capacity of the ecological system of a region, nation or the globe (e.g., Wackernagel et al., 2004a,b; Erb, 2004). Meanwhile, through the environmental window of the ecological system, the amount of the previously used-up, (directly or indirectly) available energy in the transformation process (Odum et al., 1987a; Odum, 1988, 1996) is analyzed in a sys-

103

tems ecology view to “track” both the quality and quantity of the resource used and embody the degraded available energy in an organized hierarchy. Corresponding to the potential improvements of the EF method mentioned above, this paper compares the modified EF based on emergy with the conventional EF, which stems from energy theory of value (Odum, 1971, 1983; Odum and Brown, 1975; Costanza, 1980, 2000; Costanza and Herendeen, 1984; Costanza et al., 1997; Cleveland et al., 1984)).

1.4.1.

Numeraire

The unit of emergy is emjoule, which refers to the available energy of one kind consumed in transformations. Renewable resources, including surface wind, physical energy of rain on land, chemical energy of rain on land, physical stream energy, waves absorbed on shores, earth sedimentary cycle, agricultural,forest, pasture and fishery products, as well as nonrenewable resources, mainly fossil fuels, are all measured on a common basis expressed in solar energy required to produce them. The unit of EF is gha, measuring the areas required to harvest crops and woods, infrastructure, and fossil fuels consumption under certain conditions. To distinguish the unit of emergetic ecological footprint (EEF) from that of EF, the unit of EEF is denoted as ha, although the units of emergy, EF and EEF are all based on the global ecological average sense. Since the EF originated from the terrestrial net primary production to calculate the human appropriation of the photosynthetic production, the fossil fuels and the space for infrastructure have to be estimated on some prior assumptions. Thus, emergy, EF and EEF can provide different common units as numeraires for the aggregated accounting and analysis.

1.4.2.

Cost

Emergy cost is totally embodied by the transformity, which reflects the hierarchy of the biosphere at the thermodynamic level. Criticisms of emergy focus on the transformity values that are difficult to be determined precisely on the basis of global emergy balances (Hau and Bakshi, 2004; Sciubba and Ulgiati, 2005). However, it is necessary to distinguish the ‘strictness’ and the ‘exactness’ of every field of science. Regarding emergy analysis of ecological complex system, strictly performing a system partition and boundary determination, normalizing the evaluation procedure and establishing a clear interpretive framework are more important than concerning exact calculation of transformities, for the uncertainty and emergence are the essence of the development of the general ecological system that cannot be represented by exact mathematics at large scales. Also, accounting from the sun as a starting point, emergy represents the cost of the ‘virtual environment’ that is defined at biophysical time and spatial scales and supposed to follow the ‘trial and error’ paradigm when a certain product or service is generated. Therefore, emergy is the path-dependent cost of available energy, and not available energy itself. In addition, the emergy cost is oriented to the total biosphere, including both the studied system and its environment. On the contrary, EF representing human demands versus biological supply emphasizes the appropriation of bioproduction closely related with human activities. The EF cost

104

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

focuses on six types of human demand, i.e., cropland, forest, pasture, built-up areas and fossil energy. Thus, the EF cost is anthropogenic and oriented to the global bioproductive areas usable for human, regarding the rest areas marginally productive or unproductive for human use (Wackernagel and Monfreda, 2004).

1.4.3.

Scarcity

The annual emergy contributions to the global process system is estimated as 9.44 × 1024 sej/yr (Odum, 1996). Although the global emergy input comprising solar energy, tidal energy and the deep earth heat has been analyzed and the anthropogenic emergy use evaluated, emergy itself is apparently not scarce due to the constant solar radiation intercepted by the earth when neglecting the lost exergy content as the driving force to revitalize the meteorological system, feed the hydrological cycle, renovate the biosphere and make all the other natural and anthropogenic phenomena possible (Chen, 2005; Chen and Chen, 2006). There are 9.1 billion ha of land and 2.3 billion ha of water providing humans with usable biomass (Wackernagel and Monfreda, 2004). The usable area is therefore limited. Moreover, the total area is decreasing by soil erosion and desertification, and the related bioproductivity is also declining. In fact, land, whether in the biophysical sense or the economic sense, has always been the fundamental scarce resource for human production.

1.4.4.

Ideology

The emergy concept stems from general systems theory and systems ecology and can be regarded as holistic instead of reductionistic. As a top-down approach with the biosphere selected as the control volume (Sciubba and Ulgiati, 2005), emergy analyzes the general ecological systems in a ecocentric perspective. Thus, research can be simplified and concentrated on the specified ‘environmental window’ based on the systems overview that everything in the universe is connected to the others directly or indirectly. Emergy synthesis seeks to quantify the environmental support provided by nature to a certain ecological process. It can be imagined that if the system develops in the paradigm implicated in the emergy theory, the system will yield a maximum empower output and both the system and the environment will develop in a sustainable way. However, EF is calculated in an ecocentric view. The standardized hectares, termed as global hectares, represent hectares with the potential to produce usable biomass equal to the world’s potential average of that year (Monfreda et al., 2004). Hectares for each type of bioproductive are thereafter converted into global hectares by weighting their productivity against the world average productivity using equivalence factors and yield factors. Particularly, the fossil fuel EF is assessed with the waste assimilation method, where the primarily limitation of fossil fuels depends on the biosphere’s ability to absorb CO2 emissions.

2.

Methodology

Studies of national EF have been done for Austria, Philippines, South Korea, Benin, Bhutan, Costa Rica, the Netherlands, etc.,

wherein applications of EF and assessments of sustainability are presented and discussed (e.g., Wackernagel and Rees, 1996, 1997; Wackernagel et al., 1999, 2004a,b; Monfreda et ¨ al., 2004; Haberl et al., 2001; Kratena, 2004; Stoglehner, 2003; Senbel et al., 2003; McDonald and Patterson, 2004; van Vuuren and Bouwman, 2005; Fricker, 1998). Chen et al. (2004) estimated the per caput EF between 1981 and 2000 in China based on the conventional EF method. Moreover, Faucheux and O’Connor (1998) briefly suggested that measures of trade balances in exergy or embodied energy terms could easily be constructed concerning the National eMergy Surplus (NES). This paper follows two distinct strategies to study the EF of the Chinese society from 1981 to 2001. First, we follow the conventional EF approach based on global hectares implementing recent suggestions by Wackernagel (2004) and Wackernagel et al. (2004a). Second, Zhao et al. (2005) intended to construct a modified method of EF based on emergy, in which the human consumption corresponding to six types of basic bioproductive areas are translated into a common emergy unit and the emergy-based EF and carrying capacity are defined and calculated through a case study of the Gansu province of China in 2000. In this paper, we compare and analyze EF method to emergy synthesis from the numeraire, cost, scarcity and philosophical perspectives, investigate the EEF accounting procedure, and finally make a time series (1981–2001) study of the Chinese society with further promoted EEF method as well as sectoral analysis. The results of ecological footprint, biocapacity and ecological overshoot of conventional EF and EEF are also illustrated, compared and discussed in detail. Empower density defined as ratio of empower to area directly relates the emergy synthesis with the EF method when the spatial distribution of empower is projected onto the surface of the studied ecological system. Thus, together with the global average empower density corresponding to the global average EF, the local EF hierarchy can be conceived and represented based on the local empower density hierarchy, which is important for both operational methods to be aggregated, thus probing into the spatial distribution and organization of different kinds of energy and material flows at the landscape scale. Moreover, Kangas (2002) evaluated eight natural landforms comprising floodplain, coral reef, salt marsh, glacier, palsa mound, arroyo, oyster reef, marine mud mound, as well as one human-made landform, i.e., spoil mound. The emergy storages are given on a unit area basis, which makes the applications of emergy in geomorphology more feasible. Hence, the local empower density can be determined according to the weighted sum of different landforms. The whole country, except Hong Kong, Macao and Taiwan, is chosen as the political boundary of the conversion process analysis. For avoidance of repetitive and cross-calculations, the entrance boundary points are set at the same level of the resource inflow and outflow. The components of biophysical resources come from cropping, forestry, pasture and fossil fuels. Major agricultural products include rice, wheat, corn, beans, tubers, peanuts, rapeseed, sugarcane, beet, cotton and vegetables. Fruits and wood are calculated as forest products. Coal, petroleum and natural gas consist the major fossil fuels. Fish, crustacean, and mollusc are counted as

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

the fishery products. Husbandry production, including meats, milks, eggs and wool, is regarded as secondary from pasture and not accounted in the EF and EEF. Hence, the double accounting of secondary products such as meats, milks, eggs and wool, which can be found in Zhao et al. (2005), is removed from both the conventional EF and EEF in this paper. Most of the data available for the present EF analysis of China are from standard yearbooks compiled by the central government and subordinate ministries (e.g., CAY, 1982– 2003, CCIY, 1982–2002, CESY, CEY, CFY, CIESY, RSYC, 1985– 2003 and SYC). Unlike other countries, statistical data of China , are often available after a 1–3 years delay. State Statistical Bureau published the annual statistical yearbook and energy statistics yearbook, including the main energy carrier flows broken down to the end-use sectors. The other yearbooks are compiled by the subordinated ministries with more detailed data and sometimes different statistical coverage.

2.1.

Conventional national EF accounting

The calculation of conventional EF in this paper follows the detailed process of national EF accounting underlying recent advances of EF research (Monfreda et al., 2004). Equivalence factor represents the world average potential ‘usable’ productivity contained in a given bioproductive area relative to the world average potential ‘usable’ bioproductive areas, which is aggregated on the anthropogenic mode of the utilization of biomass, thereby excluding some of the biomass beyond the human utilization scope. For this study, the time series of equivalence factors from 1981 to 2001 are cited from the work presented by Wackernagel et al. (2004a). Yield factors are determined by the variable ratio between the given bioproductive area and the global average bioproductive area of the same land use during long periods of time (Haberl et al., 2001). The variable local yields method, i.e., both global and local yields refer to the year of consumption, is used to calculate EF. Renewable resources footprints, e.g., cropland, pasture, forest and fisheries, are revised according to the classification of primary products and secondary products. Only the primary products are included in the EF accounts, whereas the imported or exported secondary products are added to the total traded EF. Built environment footprint is set equal to the same amount of cropland it replaces with the yield factor of cropland. The productivity of land inundated by hydropower reservoir, which is formed by the dam, is uncertain. Due to the high variety, the hydropower area is calculated with the equivalence factor of 1.0 and yield factor of 1.0 (Monfreda et al., 2004). At an average output of 8200 GJ/ha/yr, the built-up footprint of a wind power plant on averagequality pasture is 1.8 gha/MW. Considering the energy embodied in construction of wind farm, as pointed by Wackernagel and Monfreda (2004), the carbon sequestration footprint is 16.9 gha/MW. Photovoltaic (PV) accounts for part of the solar power. Pacca and Horvath (2002) estimated the carbon emission footprint embodied in a PV system amounted to be 211 gha/MW. The nuclear power is regarded as the fossil fuel in the conventional EF accounts. In China, the EFs of

105

the wind power and photovoltaic are relatively small compared to the other resources and can be neglected in this analysis.

2.2.

Emergetic ecological footprint accounting

Emergy accounting starts with an evaluation of the earth energy process. As emergy due to earth’s heat and the gravitational effect associated with sun and moon is negligible, the global emergy sustaining the global earth is approx. 9.44 × 1024 sej/yr (Odum, 1996). The total surface area of the earth is 5.1 × 1014 m2 . Therefore, the global empower density (hereafter GED) is the ratio of the annual global emergy consumption to the surface area of the earth, i.e., 1.85 × 1010 sej/m2 yr. Renewable resources, including surface wind, physical energy of rain on land, chemical energy of rain on land, physical stream energy, waves absorbed on shores, earth sedimentary cycle and chemical stream energy, are calculated as the ecological capacity. It should be noted that the global emergy flows are not additive and cannot be summed up, for the flows in the geobiosphere are coupled with each other. To avoid double accounting, only the largest renewable emergy flow is chosen to determine the biocapacity. The emergy transformities of the renewable resources in this paper are given as listed in Odum (1996). The EF of the ith product based on emergy is calculated as follows: EEFi = (Productiond,i + Importi − Exporti ) ×Transformityem,i /GED

(1)

where EEFi is the ecological footprint based on emergy of the ith product, Productiond,i is the yield of the ith domestic product calculated by emergy contents, Importi and Exporti are the emergy contents of the imported and exported ith products, respectively. Transformityem,i is the dimensionless quotient of the ith product’s emergy divided by its emergy, standing for the quantity of the emergy required to make 1 J of the ith product. GED is the global empower density. As a first approximation, the transformities of the products in this paper are calculated according to previous studies (Odum, 1988, 1996; Brown and Ulgiati, 1997; Ulgiati et al., 1994, 1995; Ulgiati and Brown, 1998, 1999).

3.

Results

3.1.

Conventional EF method

3.1.1.

EF

The EF per capita of China has increased during the period 1981–1996, reached the maximum (1.55 gha) in 1996 and then declined after 1997 (Fig. 4). Fossil fuels and cropland contributed most to the EF amongst the six components of the EF per capita of China. The EFs of the coal, oil and natural gas increased from 0.34, 0.07 and 0.007 gha in 1981, reached the peak 0.68, 0.10 and 0.009 gha, then fell to 0.57, 0.13 and 0.01 gha in 2001, respectively(Fig. 5). The long-run decline of the EF of the cropland has been slow, being 0.4 gha on the average during the past 21 years. The EFs of pasture kept con-

106

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

Fig. 1 – Population from 1981 to 2001 of China.

Fig. 5 – Time series of per capita EF of fossil fuels in China 1981–2001.

Fig. 2 – GDP from 1981 to 2001 of China.

stantly at 0.05 gha, whereas the built-up land 0.02 gha between 1981 and 2001. The EF of the forest stagnated around 0.11 gha throughout the study period. The EF of the sea has increased from 0.05 gha in 1981 to 0.13 gha in 2001. The total EF is given by the product of the EF per capita and the population. The total EF has risen from 1.13 × 109 gha in 1981 to 1.95 × 109 gha in 1996, and then declined little to 1.84 × 109 gha in 2001 (Fig. 6).

3.1.2.

Fig. 6 – Time series of total EF components in China 1981–2001.

Biocapacity

The biocapacity per capita changed little during the period 1981–2001, with the average being 0.67 gha (Fig. 7). It was the counteraction of the population growth and the declining crop yields that made the biocapacity per capita remained stagnant, compared to the trends of the EF per capita. The total biocapacity increased from 6.55 × 108 gha in 1981 to 7.37 × 108 gha in 1984, followed by a fluctuation around 7.53 × 108 gha between 1985 and 1995, and then recovered to the peak 8.62 × 108 gha in 1996, falling to 7.86 × 108 gha in 2001(Fig. 8). The varying scope of the biocapacity amounted to 2.07 × 108 gha.

Fig. 7 – Time series of per capita biocapacity components in China 1981–2001.

Fig. 3 – GDP per capita from 1981 to 2001 of China.

Fig. 8 – Time series of total biocapacity components in China 1981–2001.

3.1.3.

Fig. 4 – Time series of per capita EF in China 1981–2001.

Ecological overshoot

The ecological overshoot per capita and the total ecological overshoot of China have varied in a similar way during 1981–2001 (Figs. 9 and 10). The ecological overshoot per capita(Fig. 9) and the total ecological overshoot (Fig. 10) ex-

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

Fig. 9 – Time series of per capita ecological overshoot in China 1981–2001.

107

Fig. 13 – Time series of EEF of fossil fuels components in China 1981–2001.

Fig. 10 – Time series of total ecological overshoot in China 1981–2001. Fig. 14 – Time series of total EEF components in China 1981–2001.

3.1.4.

Fig. 11 – Time series of ratio of GDP to EF in China 1981–2001.

panded from 0.51 gha and 5.06 × 108 gha in 1981 to 0.65 gha and 8.36 × 108 gha in 2001, respectively. The ecological overshoot per capita and the total ecological overshoot reached the peak in 1997, amounting to 0.87 gha and 1.08 × 109 gha, respectively.

Fig. 12 – Time series of per capita EEF components in China 1981–2001.

Ratio of GDP to EF per capita

EF intensity, defined as the ratio of the EF and the real status of the economic output, which is often represented in GDP, is used to depict the resource consumption intensity corresponding to a unit of economic output. The ratio of GDP to EF per capita can be regarded as an attempt to show the close relationship between the “land demand” and economic output, as discussed by Farber et al. concerning the relationship between available energy and economic output (Farber et al., 2002). However, different from what is stated in Chen et al. (2004) that the ratio of GDP to EF per captita can be considered as a direct measure of resource use efficiency, it is much better to understand this indicator as a numeraire between the land area and the currency. The hypothesis implied by Chen et al. (2004) is that the “bioproductive land consumption” growth rate should keep in pace with the GDP growth rate, which is not always the case, especially in China. First, the bioproductive land consumption growth rate varies in different sectors. Second, the developing imbalance amongst different sectors due to the unbalanced central planning investments affects the total bioproductive land consumption growth rate of the national economy. Finally, the “bioproductive land” does not aggregate all the available resources, especially the so-called renewable resources in China. The ratio of GDP to EF per capita in China increased steadily over the period 1981–2001, from 429 RMB/gha in 1981 to 5139 RMB/gha in 2001 (Fig. 11).

108

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

3.2.

Emergetic EF method

3.2.1.

Emergetic EF

The emergetic EF (hereafter EEF) per capita of China has constantly increased during the period 1981–1996, reached a maximum (4.08 ha) in 1996, declined before 2000, and then resurged a little (3.56 ha)in 2001 (Fig. 12). Fossil fuels contributed most to the EEF amongst the six components of the EEF per capita of China, whereas cropland, pasture and sea water contribute approximately the same to the total EEF. The EEFs per capita of the coal, oil and natural gas increased from 1.05, 0.41 and 0.04 ha in 1981, reaching a peak of 1.93, 0.53 and 0.06 ha, then fell to 1.28, 0.53 and 0.08 ha in 2001, respectively (Fig. 13). The long-run fluctuation of the EEF per capita of the cropland has been slow, being 0.83 ha on the average during the past 21 years. The EEF of the built-up area has risen from 0.03 ha in 1981 to 0.11 ha in 2001. The EEF of pasture moves around 0.08 ha during the study period. The EEF of forest stagnated throughout the study period between 0.04 and 0.06 ha. The EEF of the sea has increased from 0.09 ha in 1981 to 0.56 ha in 2001. The total EEF is the product of the EF per capita and the population. The total EEF has risen from 1981 to 1996, and then declined little from 1996 to 2001 (see Fig. 14).

3.2.2.

Emergetic biocapacity

The emergetic biocapacity per capita changed from 4.25 ha in 1981 to 3.33 ha in 2001, with the average being 3.72 ha (see Table 1). The varying scope of the emergetic biocapacity per capita amounted to 0.92 ha.

3.2.3.

Emergetic ecological overshoot

Fig. 15 – Time series of per capita emergetic ecological overshoot in China 1981–2001.

overshoot per capita (Fig. 15) and the total ecological overshoot (Fig. 16) expanded from −1.80 ha and 2.45 × 109 ha in 1981, and reached the peak 0.63 ha and 5.03 × 109 ha in 1997, respectively, and thereafter followed a reduction, amounting to 0.23 ha and 4.55 × 109 ha in 2001, respectively.

3.2.4.

Ratio of GDP to EEF per capita

Based on the the concept of emergy, EEF intensity, defined as the ratio of the EEF and the real status of the economic output is used to depict the resource consumption intensity corresponding to a unit of economic output. The ratio of GDP to EEF per capita is an attempt to show the close relationship between the land demand from emergy and economic output. The ratio of GDP to EEF per capita in China increased steadily over the period 1981–2001, from 198 RMB/ha in 1981 to 2074 RMB/ha in 2001 (Fig. 17).

The emergetic ecological overshoot increased continuously during the period 1981–2001 (Figs. 15 and 16). The ecological

Table 1 – Emergetic biocapacity per capita in China 1981–2001 (unit: ha) Year 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Emergetic biocapacity per capita 4.25 4.19 4.13 4.08 4.02 3.96 3.89 3.83 3.78 3.67 3.67 3.63 3.59 3.55 3.51 3.48 3.44 3.41 3.38 3.36 3.33

Fig. 16 – Time series of total emergetic ecological overshoot in China 1981–2001.

Fig. 17 – Time series of per capita GDP to EEF in China 1981–2001.

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

4. Discussion of results of Chinese sectoral analysis 1981–2001 As Wackernagel et al. (2004a) stated, the EF documents present ecological demand and supply and describes the quality of impacts and resource management brought about yield changes. For the varying components of the EF, sectoral analysis of time series will depict clearer cause-effect relationship concerning with more specific management practices in each sector. In China, the transitional stages of the constitution during the period 1981–2001 profoundly affected the corresponding EF time series.

4.1.

Cropland

Relative political infrastructure and organization of the agricultural production in the rural areas will be discussed below, for frequent and rapid transformation of the rural policies have direct impact on the crop yields and in turn the EF or EEF. Collectivization was the main structure of Chinese agriculture from 1957 to 1979, with three levels, production team, brigade and commune. The major decisions about the crop farming and investments on the agricultural production were made and circumscribed not by the peasant or the production team, but by the brigade and commune that are at the higher levels. As the communes based on the collectivization were proved to be unworkable, production responsibility systems spontaneously emerged in the early 1980s and over time were forced to be performed in the countryside by the state. Thus, the EF (EEF) increased from 0.42 gha (0.71 ha) in 1981 to 0.45 gha (0.84 ha) in 1983. From 1983, the household production contracting responsibility system was regarded as the basic agricultural production system and the state grain procurement was partly abolished, decreasing from 113 types of procurement grains to 38, while the contracts between the state and the peasants are allowed the rest of the procured grains to be circulated in the market. As a result, a large harvest occurred in 1984, with the EF (EEF) being 0.45 gha (0.89 ha). Also, the 30-year state monopoly purchase and marketing policy was replaced by contract purchase in 1985, keeping the EF (EEF) at 0.43 gha (0.81 ha). The central conference on rural policy in 1993 prescribed that the land contract could be extended for 30 years and the management right could be transferred freely during the contract period which laid a solid foundation for the large-scale crop farming and management. The marketing of the grain was also decentralized by the government in 1993, with the EF (EEF) rebounding to 0.40 gha (0.80 ha). To release the pressure of the demand for scarce cultivated land, the management right of the “four barrens” was auctioned with more than 50 years operating time. The auctioned barrens, summing up to 4.67 × 106 ha by 1995, stimulated enthusiasm of the farmers to reclaim and exploit large amount of non-cultivated land resources in China, thereby stimulating the increase of the EF and EEF. The decentralization measures by the government to abolish the grain coupon since 1993 has totally changed the circulation channel and system of the grain. From 1991 to 1995, the provincial governors were required to assume the respon-

109

sibility of the grain supply, taking advantage of the market to regulate the shortage and surplus grain amongst different provinces and guaranteeing the self-sufficiency of grain. Also, the grain reserve of the central and local government was established in order to regulate the supply of the grain market. For example, the central government undersold up to 1.5 × 107 tonnes grain to depress the inflation of the grain prices owing to the poor harvest in 1994, with the EF (EEF) being 0.41 gha (0.82 ha).

4.2.

Fossil energy

4.2.1.

Coal

Coal production can be divided into three major parts according to the administrative institutions, i.e., state-controlled unified central planning, local state-controlled and rural coal mines. In 1990, the unified central planning, local statecontrolled and rural production amounted to 44.5, 19.0 and 36.0% of the total production, respectively (Jin et al., 1997). In 1981, the coal production associated with 0.34 gha/cap EF or 1.05 ha/cap EEF was adjusted because of the mismatch which included irregular cutting and tunneling and chaotic management of the whole coal industry. With 87 coal mines adjusted and the production capacity of the newly established mines expanded to 1.2 × 108 tonnes (0.36 gha/cap or 1.11 ha/cap), the production of 1982 started to increase slightly. The coal production met the target 7 × 108 tonnes (0.39 gha/cap or 1.17 ha/cap)in 1983 which was scheduled to be met in 1985. Also, the policy was specified to develop the rural coal mines, which increased to 40,000 associated with 16% production increment to provide more jobs in coal industries. In 1984, the coal production continued the upward trend, summing up to 7.9 × 108 tonnes (0.40 gha/cap or 1.28 ha/cap), of which the production of the rural coal mines amounted to 2.1 × 108 tonnes. Considering the rich coal resources, which are distributed in more than 1100 cities and towns and were suitable for the farmers to exploit, the government encouraged the peasants to contract and operate the medium and small-sized coal mines so as to meet the rising demand for the coal under poor transportation facilities. Further, with the coal market transactions permitted, coal was transported freely throughout the whole country. Marginal and scrappy coal fields were distributed to the peasants and number of the rural coal mines skyrocketed to 50,000 and the corresponding yields amounted for 62% of the total coal production increment. The central government put the “General Contract Programme” into practice in 1985 with the coal production increased drastically to 8.7 × 108 tonnes (0.43 gha/cap or 1.39 ha/cap). The coal production mounted to 1.08 × 109 tonnes (0.52 gha/cap or 1.57 ha/cap) in 1990, accompanied by improved mechanization and efficiency (1.217 tonnes daily per capita). Despite the growth, the state-fixed price of the coal was still extremely low and the state of the operation of the state-owned coal mines was terrible. From 1991 to 1993, the Chinese economy experienced serious inflation. Macroeconomic polices were implemented to cool down the overheated investments in a wide range of industries, therein the coal investment and production gradually contracted because the demand for the coal which is less than the supply suppressed

110

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

the coal production. Thereafter, the coal production revived and the deficit was 1.97 billion Yuan which is less than the “scheduled” deficit 2.00 billion Yuan in 1994 and the deficit 3.26 billion Yuan in 1993. In addition, the rural coal mines were initially reformed and consolidated, 13,000 small-sized coal mines without certification being closed. The deficit of the key state-owned coal mines decreased to 1.03 billion Yuan, for the whole coal industry began to be transferred from the conventional policy based on the state-fixed yields to the market forces in 1995. Coal production in 1996 mounted to a maximum of 1.37 × 109 tonnes (0.68 gha/cap or 1.93 ha/cap), of which the central controlled unified planning production was 5.4 × 108 tonnes , the local state-controlled 52.2 × 108 tonnes and the rural ones 6.1 × 108 tonnes. The deficit of the key state-owned coal mines reduced to 0.6 billion Yuan, with the production, diversified management and logistics departments being separated and independently accounted. In 1997, rectification and readjustment were performed to balance the wide gap between supply and demand, with coal production being 1.33 × 109 tonnes (0.65 gha/cap or 1.88 ha/cap). Drastic measures were implemented in 1998, resulting in 94 key state-controlled coal mines associated with 237.9 billion asset and 4.35 million employees were handed over to the local government with no production plans and breakeven indices prescribed by the State Coal Industry Bureau were needed to be finished thereafter. The decision to close various small-sized coal mines and decrease 2.5 × 108 tonnes production was also made by the State Council. “14.40” Project was also scheduled to make 14 deficit coal enterprises bankrupted and 40 resource-depleted and lowquality coal mines closed in 1999 to adjust the fundamental structure of the coal industry. After the fading production with 1.23 × 109 tonnes (0.60 gha/cap or 1.69 ha/cap)in 1998, the total production was further reduced to 1.04 × 109 tonnes (0.58 gha/cap or 5.12 ha/cap) in 1999 due to 31.2 thousands closed small-sized coal mines. Coal production reached 9.99 × 108 tonnes (0.57 gha/cap or 1.40 ha/cap) in 2000. Until the end of 2000, 4.6 × 104 smallsized coal mines were closed with only 2.5 × 104 left. Moreover, to alleviate the pressure of the civil coal market, the government supported the coal export by providing the refund of the export tax rates and decreasing the freight base and commodity inspection expense, with the result that the coal export amounted to 5.5 × 107 tonnes. From 2001 onwards, the coal production has rebounded, for the production structure was adjusted, the supply and demand tended to balance and the coal stocks continued to be disposed. Also, the government reinstated regulation and control of the whole coal market restoring more than 80% of the total state-controlled coal production (only 57% in 1997).

imu Basin oil field was explored. Meanwhile, the production of Daqing, Liaohe, Shengli, Dagang and Zhongyuan fields continued to increase with adjustment to stabilize the declining ratio and water content. The explored reserves accumulated 0.89 billion tonnes, the total production kept rising gradually during 1991–1995 with four new million-tonnages oil fields, Tazhong, Shixi, Qiuling and Ansai. In addition, crude oil import exceeded export for the first time in 1993, which indicated the increasing demand for crude oil. It can be concluded that the increasing crude oil production mainly depended on the production of the new discovered oil fields over the past 20 years.

4.2.2.

4.3.

Oil

Crude oil production amounted to 5.49 × 108 tonnes (0.35 gha/cap or 5.43 ha/cap) during 1981–1985, which in turn constrained the development of the civil transportation and heavy industries though about 26 billion dollars were gained from the foreign exchange. From 1986 to 1990, the production of the former major oil industries located in the eastern China was stabilized. The exploitation transferred to the western areas, where the Tal-

4.2.3.

Natural gas

In 1980, the first natural gas reservoir was put into operation in Daqing. In the following years (1980–1995), the natural gas production developed slowly compared with the crude oil production. Investments in the natural gas industries are only onetenth of the amount invested in petroleum industries and the heavy resource tax (2–15 Yuan/m3 ), added value tax (13%) and income tax (33%) further impede the exploitation of natural gas. Also, the materials input to the natural gas industries are regulated by the market whereas the production is decided and fixed by the parent administrative department, at costs which keep the natural gas industries in deficit without the capability to operate at a profit to explore. Despite the disadvantages mentioned above, new gas fields discovered in the eighth 5-year period, encompassing ShaanxiGansu-Ningxia with 2.28 × 1011 m3 reserves, Eastern Sichuan with 2.0 × 1011 m3 reserves and Xinjiang with 1.87×1011 m3 reserves, provided sufficient resources to increase the production. The exploitation scale of the gas blanket expanded in Sichuan, Qinghai, Tuha and Xinjiang in 1996 in order to compensate the decreasing natural gas production accompanied by the declining crude oil production of the eastern oil fields. Seven gas fields were discovered and two were put into operation with production capacity 6.27 × 1011 m3 and associated gas 2.28 × 1011 m3 . The supervisor mode transferred in 1997, from the focus on the safe and stable production to the multichannel marketing, which in turn stimulated the further production increment. Natural gas production skyrocketed with 0.007 gha/cap or 0.04 ha/cap in 1981 and 0.013 gha/cap or 0.08 ha/cap in 2001 , for the large scale explored gas fields, distributed in Zhungeer, Talimu, Shanxi-Gansu-Ningxia and Sichuan were discovered with the generation of new technologies, e.g., high resolution imaging well logging method. Investments in abroad natural gas resources and obtained natural gas quotas also added to the civil increasing production.

Forest

Forest resources are scarce in China, especially in the Yellow River Basin where percent coverage of forest is extremely low, leading to serious soil and water loss associated with declining fertility of the cultivated land. Thereby, forestry is directly related to agriculture as the basic guarantee. However, due to the increasing demand for woods in paper-making industries and large amount of woods treated as fuels in rural areas,

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

excessive cutting and low conservation are quite common. Forests regulate the hydrologic cycle and microclimate, conserve the soil and water resource, break the wind and maintain the healthy ecological system. Special forests are planted for the purpose of military, experiment, landscape and natural protection. Firewood forest, providing rapid growth wood as biomass fuels for the rural areas, are explained afore in the biomass part. The EF or EEF of the forest sector fluctuated around 0.11 gha/cap or 0.05 ha/cap during 1981 and 2001. Forest use kept increasing during the past two decades, mirroring the rational economic utilization based on market demand. The firewood forest area increased in the 1980s, caused by the policy stipulated by the Forestry Ministry, and decreased in the 1990s, when fossil fuels were introduced and firewood were not preferred. Meanwhile, protected forest area have been rising since the 1990s, due to increased awareness of deteriorating soil and water resources and reserve of the scarce forest resources.

4.4.

Fishery

From 1966 to 1976, sideline production including fishery was prohibited in China, whereas the egalitarianism was strictly carried out and state unified procurement of aquatic products made the fishery develop slowly. Meanwhile, fishermen dislike fish breeding and prefer direct fishing. In the offshore areas, the catching capacity far overtook the reproducibility of the fish concerning the growing fishing boats and nets, with the result that belt fish and yellow-fin tuna could not format fishing season in the Yellow Sea and drastically decreased in the East China Sea. The EF or EEF of the fishery sector has increased from 0.05 gha/cap or 0.09 ha/cap in 1981 to 0.13 gha/cap or 0.56 ha/cap in 2001. The bump years have been from 1976 to 1984, when the fishery production restored according to the policy of the national economy, namely, “Adjustment, Reform, Rectification and Improvement”. The whole fishery started to be adjusted, contracting the fishing production, developing the breeding and undertaking transoceanic fishery. In addition, from 2000 onwards, introduction, cultivation, trial cultivation and breeding system, which is generalized and promoted, have helped to set up new fishery bases integrating tourism, sightseeing, recreation, famous species cultivation and popularization in one and improve the quality and economic benefit of the fishery.

4.5.

Pasture

The EF or EEF of the pasture sector fluctuated around 0.11 gha/cap or 0.08 ha/cap during 1981 and 2001. From 1981 to 1995, the average annually cultivated and improved pasture amounted to 1.1 × 106 , 2.2 × 106 and 2.6 × 106 ha, respectively. Moreover, the nationwide pasture production contract responsibility akin to the agriculture production was generalized which stimulated the incentives of the herdsmen to protect, construct and utilize the pasture resources in a rational way. Strategic adjustment was made in 1996 to meet the increasing demand for rangeland resources and the comprehensive development of the southern rangeland resources

111

was implemented with improved seed and livestock. Considering the vertical distribution of the grassland in the southern areas, the integrated ecological mode of “grain–grass–forest– drug” was proposed and developed to reconstruct the mountain ecological systems. To promote the natural rangeland protection, the government set down the National Ecological Construction Programme in 2000, which includes rotational grazing by fence, conservation, tending and control of rodent and insect pests, propagation of the pasture improvements embracing afterculture, shallow-plowing, fertilization and irrigation and construction methods to raise the relatively low level of the rangeland construction areas accounting for only 3–30% of the total pasture areas. Despite the efforts made by the government, the degradation of the rangeland is still serious compared with the ecological construction concerning the degenerated rangeland areas totaled 9 × 107 ha and 1% yield decline (Wang et al., 2002). In addition, over grazing intensity leads to desertification, resulting in yield decline on rangeland and 2.5 × 105 ha desertification areas each year, especially in agropastoral transitional zones.

4.6.

Built-up land

Along with the increasing population and urbanization, the built-up area kept growing during the period 1981–2001. On one hand, since the boundary of the urban areas and the rural areas that was fixed in the 1950s has changed and the domain of the city keeps expanding, the hinterlands of the city have to be enlarged to effectively support the city itself, with more and more cropland and other types of lands being appropriated for built-up land to accommodate the additional people from the surrounding countriside. On the other hand, the farmers encountering inequality in the rural areas seek for migration to urban areas in search of employment.

5.

Comparison and discussion

In view of the different results based on conventional EF and EEF, comparison and related discussion on EF, biocapacity and ecological overshoot are presented as below.

5.1.

EF

The conventional EF is calculated in the bioproduction aspect, whereas the EEF is founded on aggregation of population, economic production and environment. Although the emergy contents (sej)of the products differ greatly from the weight (kg) of the yields from the bioproductive areas, the EF per capita varied similarly as the EEF per capita from 1981 to 2001, indicating a reasonable accordance between the results of these two methods. There are also some differences on more detailed levels. The EEF expanded by larger growth rate than the conventional EF. Also, considering the components, fossil energy and cropland contributed most to the total EF in conventional EF method, whereas fossil energy, cropland and fisheries are the major contents of the EEF. The difference of the contribution can be explained by the fact that the products from the marine areas, although as intensely explored as the

112

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

land, is assumed as a small fraction of human consumption and less manipulated by the policy and management, are simplified and sometimes underestimated by the conventional EF based on the fundamental assumptions (Wackernagel and Rees, 1996).

5.2.

Biocapacity

Due to the different definitions of the biocapacity, its trends of the conventional EF and EEF are obviously distinguished. Along with the population growth, the emergetic biocapacity per capita has been steadily declining, from 4.25 ha in 1981 to 3.33 ha in 2001, as is shown in Fig. 6. The conventional biocapacity per capita fluctuates around the mean line (0.67 gha). However, the point is not how to define the biocapacity, but to describe to what extent human use of natural capital, which is represented in the next subsection.

5.3.

Ecological overshoot

The EF per capita of the conventional EF method always exceed the biocapacity in the studied period. In contrast, the EEF per capita started to exceed the biocapacity after 1990 due to the different definitions of biocapacity. However, the varying trends of the ecological overshoot based on conventional EF and EEF are similar, although some principles of conventional EF and EEF are quite different. To illustrate and demonstrate the possibility and actual emergence of the ecological overshoot, which is the forgotten core concept of sustainability (Wackernagel and Silverstein, 2000), EEF, as a modification and complementary concept of the conventional EF, can help determine the overall depletion status of the natural capital based on the second law of thermodynamics. The consistent results of the ecological overshoot founded on conventional EF and EEF show that the basic assumption of the conventional EF is reasonable and the extent to which human use of nature capital is not overestimated, but underestimated.

6.

Conclusions

Based on the second law of thermodynamics, the concept of emergy is applied to ecological evaluation, resource accounting and environmental impact assessment. Emergy, as a kind of embodied energy, further internalizes the impact external to the existing process of the earth, part of which is intercepted by the earth and consumed in driving and sustaining the earth system. Emergy can be regarded as a necessary indicator for ecological evaluation as it raises a unified thermodynamic metric for objectively evaluating resource depletion, environment degradation and ecological overshoot and provides an essential measure of “use scarcity” (Cleveland and Stern, 1999) of the real power driving the earth system. This paper compares EF with EEF and makes a time series case study of China 1981–2001. Compared with the conventional EF, EEF analysis avoids the disputable assumptions presumed by the conventional EF method, provides a consistent physical value to assess the resource, environment and buffering capacity in three production perspectives, including population, economic and environmental. The land area is reconstructed

on the limiting factor of the ecological production, i.e., emergy, offering an improved and reliable measure of the development of the ecological system in the ecologically average sense over different time and space scales. Moreover, associated with the concept of emergy, EEF intensity, defined as the ratio of the EEF and the real status of the economic output, which is often represented in GDP, is used to depict the resource consumption intensity, also in the ecologically average sense, corresponding to unit economic output. Finally, the EEF investigated in this paper can be further improved if the detailed proportions of landforms are available, for the global empower density can be modified with the local power density based on geomorphologic settings, thereafter revealing the real geological structures of landforms with quite different bioproductivities compared with the present EF and EEF accounting based on the average bioproducts.

Acknowledgements This work was funded by the State Key Basic Research and Development Plan (973 Plan, Grant No. 2005CB724204), National Natural Science Foundation of China (Grant No. 1037226) and China Postdoctoral Science Foundation (Grant No. 2005038036). We would also like to thank Brian D. Fath, Associate Editor of this Journal, for his significant assistance in promoting the quality of this paper.

references

Ayres, R.U., 2000. Commentary on the utility of the ecological footprint concept. Ecol. Econ. 32, 347–349. Brandt-Williams, S.L., 2002. Emergy of Florida Agriculture. Folio No. 4 of Handbook of Emergy Evaluation. The Center for Environmental Policy, University of Florida, Gainesville. Brown, M.T., McClanahan, T.R., 1996. EMergy analysis perspectives of Thailand and Mekong River dam proposals. Ecol. Model. 91, 105–130. Brown, M.T., Ulgiati, S., 1997. Emergy-based indices and ratios to evaluate sustanability: monitoring economies and technology toward environmentally sound innovation. Ecol. Eng. 9, 51–69. Brown, M.T., Bardi, E., 2001. Emergy of Ecosystems. Folio No. 3 of Handbook of Emergy Evaluation. The Center for Environmental Policy, University of Florida, Gainesville. Brown, M.T., Buranakarn, V., 2003. Emergy indices and ratios for sustainable material cycles and recycle options. Res. Conserv. Recycl. 38, 1–22. Brown, M.T., Ulgiati, S., 2004a. Energy quality, emergy, and trasformity: H.T. Odum’s contributions to quantifying and understanding systems. Ecol. Model. 178, 201–213. Brown, M.T., Ulgiati, S., 2004b. Emergy analysis and environmental accounting. In: Cleveland, C.J. (Ed.), Encyclopedia of Energy, vol. 2. Elsevier, pp. 329–354. Campbell, D.E., 1997. Emergy analysis of human carrying capacity and regional sustainability: an example using the State of Maine. Eviron. Monit. Assess. 51, 531–569. CAY, China Agriculture Yearbook, 1982–2003. China Statistical Publishing House, Beijing. CCIY, China Coal Industry Yearbook, 1982–2002. China Coal Industry Publishing House, Beijing. CESY, China Energy Statistical Yearbook, 1986, 1991, 1991/1996, 1997/1999, 2000/2002. China Statistical Publishing House, Beijing.

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

CEY, China Environmental Yearbook, 1990–2003. China Environmental Yearbook Press, Beijing. CFY, China Forestry Yearbook, 1949/1986, 1987–2003. China Forestry Press, Beijing. Chen, G.Q., 2005. Exergy consumpution of the earth. Ecol. Model. 184, 363–380. Chen, G.Q., 2006. Scarcity of exergy and ecological evaluation based on embodied exergy. Commun. Nonlinear Sci. Numer. Simul. 11, 531–552. Chen, B., Chen, G.Q., 2006. Exergy analysis for resource conversion of the Chinese society 1993 under the material product system. Energy 31, 1115–1150. Chen, D.J., Cheng, G.D., Xu, Z.M., Zhang, Z.Q., 2004. Ecological footprint of the Chinese population, environment and development. Environ. Conserv. 31 (1), 63–68. CIESY, China Industrial Economic Statistical Yearbook, 1988–1990, 1992–1995, 1998, 2001–2003. China Statistical Publishing House, Beijing. Cleveland, C.J., Costanza, R., Hall, C.A.S., Kaufmann, R., 1984. Energy and the US economy: a biophysical perspective. Science 225, 890–897. Cleveland, C.J., Stern, D.I., 1999. Indicators of natural resource scarcity: a review and synthesis. In: van den Bergh, Jeroen C.J.M. (Eds.), Handbook of Environemtnal and Resource Economics. Edward Elgar, pp. 89–108. Costanza, R., 1980. Embodied energy and economic valuation. Science 210, 1219–1224. Costanza, R., 2000. The dynamics of the ecological footprint concept. Ecol. Econ. 32, 341–345. Costanza, R., Herendeen, R.A., 1984. Embodied energy and economic value in the United States economy: 1963, 1967 and 1972. Resour. Energy 6, 129–163. Costanza, R., Perrings, C., Cleveland, C.J., 1997. The Development of Ecol. Econ. An Elgar Referece Collection, UK. Erb, K.-H., 1926. Actual land demand of Austria 1926–2000: a variation on ecological footprint assessments. Land Use Policy 21, 247–259. Farber, S.C., Costanza, R., Wilson, M.A., 2002. Economic and ecological concepts for valuing ecosystem services. Ecol. Econ. 41, 375–392. Fath, B.D., 2004. Distributed control in ecological networks. Ecol. Model. 179, 235–245. Fath, B.D., Jørgensen, S.E., Patten, B.C., Stra˘skraba, M., 2004. Ecosystem growth and development. Biosystems 77, 213–228. Faucheux, S., O’Connor, M., 1998. Energy measures and their uses. In: Faucheux, S., O’Connor, M. (Eds.), Valuation for Sustainable Development. Edward Elgar, pp. 121–166. Fricker, A., 1998. The ecological footprint of New Zealand as a step towards sustainability. Futures 30 (9), 559–567. Haberl, H., Erb, K.-H., Krausmann, F., 2001. How to calculate and interpret ecological footprints for long periods of time: the case of Austri 1926–1995. Ecol. Econ. 38, 25–45. Hau, J.L., Bakshi, B.R., 2004. Promise and problems of emergy analysis. Ecol. Model. 178, 215–225. Higgins, J.B., 2003. Emergy analysis of the oak openings region. Ecol. Eng. 21 (1), 75–109. Jin, S.X., Jiang, Y., et al., 1997. Present Situation and Rational Exploitation and Utilization of Coal Resources of China. Geological Publishing House, Beijing (in Chinese). Jørgensen, S.E., Nielsen, S., Mejer, H., 1995. Emergy, environ, exergy and ecological modelling. Ecol. Model. 77, 99–109. Jørgensen, S.E., Patten, B.C., Milan, S., 2000. Ecosystems emerging. 4. Growth. Ecol. Model. 126, 249–284. Jørgensen, S.E., Odum, H.T., Brown, M.T., 2004. Emergy and exergy stored in genetic information. Ecol. Model. 178, 11–16. Kang, D., Park, S.S., 2002. Emergy evaluation perspectives of a multipurpose dam proposal in Korea. J. Environ. Manage. 66, 293–306.

113

Kangas, P.C., 2002. Handbook of Emergy Evaluation: A Compendium of Data for Emergy Computation Issued in a Series of Folios. Folio No. 5—Emergy of Landforms. The Center for Environmental Policy, University of Florida, Gainesville. Kratena, K., 2004. ‘Ecological value added’ in an integrated ecosystem-economy model—an indicator for sustainability. Ecol. Econ. 48, 189–200. Martin, J.F., 2002. Emergy valuation of diversions of river water to marshes in the Mississippi River Delta. Ecol. Eng. 18, 265–286. McDonald, G.W., Patterson, M.G., 2004. Ecological footprints and interdependencies of New Zealand regions. Ecol. Econ. 50, 49–67. Monfreda, C., Wackernagel, M., Deumling, D., 2004. Establishing national natural capital accounts based on detailed ecological footprint and biological capacity assessment. Land Use Policy 21, 231–246. Nelson, M., Odum, H.T., Brown, M.T., Alling, A., 2001. Living off the land: resource efficiency of wetland wastewater treatment. Adv. Space Res. 27 (9), 1547–1556. Odum, H.T., Pinkerton, R.C., 1955. Time’s speed regulator: the optimum efficiency for maximum power output in physical and biological systems. Am. Scientist 43 (2), 331–343. Odum, H.T., 1971. Environment, Power and Society. John Wiley, NY, p. 336. Odum, H.T., Brown, M.T., 1975. Carrying Capacity for Man and Nature in South Florida. Final Report to the National Park Service, US Dept. Interior and State of Florida, Division of State Planning. Odum, H.T., 1983. Systems Ecology: An Introduction. John Wiley, NY, p. 644 (revised in 1994. Ecological and General Systems: An Introduction to Systems Ecology. Univ. Press of Colo., P.O. Box 849, Niwot 80544). Odum, H.T., Odum, E.C., Blisset, M., 1987a. Ecology and Economy: Emergy Analysis and Public Policy in Texas. L.B. Johnson School of Public Affairs and Texas Dept. of Agriculture, University of Texas, Austin. Odum, H.T., Wang, F.C., Alexander, J.F., Gilliland, M., Miller, M.A., Sendzimir, J., 1987b. Energy Analysis of Environmental Value. Center for Wetlands, University of Florida, Gainesville, FL. Odum, H.T., 1988. Self-organization, transformity and information. Science 242, 1132–1139. Odum, H.T., 1994. Ecological and General Systems—An Introduction to Systems Ecology. University Press of Colorado, U.S. Odum, H.T., 1996. Environmental Accounting: Emergy and Environmental Decision Making. John Wiley, New York, US. Odum, H.T., 2000a. Handbook of Emergy Evaluation: A compendium of Data for Emergy Computation Issued in a Series of Folios. Folio No. 2—Emergy of Global Processes. The Center for Environmental Policy, University of Florida, Gainesville. Odum, H.T., 2000b. Emergy Evaluation of an OTEC electrical power system. Energy 25, 389–393. Odum, H.T., Brown, M.T., Brandt-Williams, S.L., 2000. Handbook of Emergy Evaluation: A compendium of Data for Emergy Computation Issued in a Series of Folios. Folio No. 1—Introduction and Global Budget. The Center for Environmental Policy, University of Florida, Gainesville. Pacca, S., Horvath, A., 2002. Greehouse gas emissions from building and operating electric power plants in the Upper Colorado River Basin. Environ. Sci. Technol. 36 (14), 3194– 3200. Pillet, G., Odum, H.T., 1984. Energy Externality and the Economy of Switzerland. Swiss. J. Pol. Econ. Stat. 120, 409–35. Pillet, G., Maradan, D., Zingg, N., Brandt-Williams, S., 2001. Emternalities: theory and assessment. In: Brown (Ed.), Emergy Synthesis: Theory Applications of the Emergy Methodology.

114

e c o l o g i c a l m o d e l l i n g 1 9 8 (2006) 101–114

Proceedings of the First Biennial Emergy Analysis Research Conference, Gainesville, FL, USA, pp. 39–51. RSYC, Rural Statistical Yearbook of China, 1985–2003. China Statistical Publishing House, Beijing. Sciubba, E., Ulgiati, S., 2005. Energy and exergy analyses: complementary methods or irreducible ideological options? Energy 30, 1953–1988. Senbel, M., McDaniels, T., Dowlatabadi, H., 2003. The ecological footprint: a non-monetary metric of human consumption applied to North America. Global Environ. Changes 13, 83–100. ¨ Stoglehner, G., 2003. Ecological footprint—a tool for assessing sustainable energy supplies. J. Cleaner Prod. 11, 267–277. SYC, Statistical Yearbook of China, 1980–2002. China Statistical Publishing House, Beijing. Teather, D.C.B., Yee, H.S., 1999. China in Transition—Issues and Polices. Macmillan Press Ltd., London, pp. xvi–xxvii, 171–193. Ulgiati, S., Odum, H.T., Bastianoni, S., 1993. Emergy analysis of Italian agricultural system: the role of energy quality and environmental inputs. In: Bonati, L., Cosentino, U., Lasagni, M., Moro, G., Pitea, D., Schiraldi, A. (Eds.), Trends in Ecological Physical Chemistry. Elsevier Science Publishers, Amsterdam, pp. 187–215. Ulgiati, S., Odum, H.T., Bastianoni, S., 1994. Emergy analysis, environmental loading and sustainability: an emergy analysis of Italy. Ecol. Model. 73, 215–268. Ulgiati, S., Brown, M.T., Bastianoni, S., Marchettini, N., 1995. Emergy based indices and ratios to evaluate the sustainable use of resources. Ecol. Eng. 5, 519–531. Ulgiati, S., Brown, M.T., 1998. Monitoring patterns of sustainability in natural and man-made ecosystems. Ecol. Model. 108, 23–36. Ulgiati, S., Brown, M.T., 1999. Emergy accounting of human-dominated, large scale ecosystems. In: Jørgensen, K. (Ed.), Thermodynamics and Ecology. CRC Press LLC. van den Bergh, Jeroen C.J.M., Verbruggen, H., 1999. Spatial sustainability, trade and indicators: an evaluation of the ‘ecological footprint’. Ecol. Econ. 29, 61–72.

van Vuuren, D.P., Bouwman, L.F., 2005. Exploring past and future changes in the ecological footprint for world regions. Ecol. Econ. 52, 43–62. Vitousek, P.M., Ehrlich, P.R., Ehrlich, A.H., Matson, P.A., 1986. Human appropriation of the products of photosynthesis. Bioscience 36 (6), 368–373. Wackernagel, M., Rees, W.E., 1996. Our Ecological Footprint: Reducing Human Impact on the Earth. New Society, Gabrioala, BC, Canada. Wackernagel, M., Rees, W.E., 1997. Perceptual and structural barriers to investing in natural capital: economics from an ecological footprint perspective. Ecol. Econ. 20, 3–24. Wackernagel, M., Onisto, L., Bello, P., Linares, A.C., Falfn, I.S.L., Garca, J.M., Guerrero, A.I.S., Guerrero, M.G.S., 1999. National natural capital accounting with the ecological footprint concept. Ecol. Econ. 29, 375–390. Wackernagel, M., Silverstein, J., 2000. Big things first: focusing on the scale imperative with the ecological footprint. Ecol. Econ. 32, 391–394. Wackernagel, M., Monfreda, C., Schulz, N.B., Erb, K.H., Haberl, H., Schulz, N.B., 2004a. Ecological footprint time series of Austria, the Philippines, and South Korea for 1961–1999: comparing the conventional approach to an ‘actual land area’ approach. Land Use Policy 21, 261–269. Wackernagel, M., Monfreda, C., Schulz, N.B., Erb, K.H., Haberl, H., Krausmanh, F., 2004b. Calculating national and global ecological footprint time series: resolving conceptual challenges. Land Use Policy 21, 271–278. Wackernagel, M., Monfreda, C., 2004. Ecological footprints and energy. In: Cleveland, C.J. (Ed.), Encyclopedia of Energy, vol. 2. Elsevier, pp. 1–11. Wang, K., Han, J.G., Zhou, H., 2002. The current situation and developing strategy of Chinese grassland industry. Acta Agresia Sinca 10 (4), 293–297 (in Chinese). Zhao, S., Li, Z.Z., Li, W.L., 2005. A modified method of ecological footprint calculation and its application. Ecol. Model. 185, 65–75.