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Article

Analysis of Resource and Emission Impacts: An Emergy-Based Multiple Spatial Scale Framework for Urban Ecological and Economic Evaluation

State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
*
Author to whom correspondence should be addressed.
Entropy 2011, 13(3), 720-743; https://doi.org/10.3390/e13030720
Submission received: 3 December 2010 / Revised: 17 January 2011 / Accepted: 1 March 2011 / Published: 23 March 2011
(This article belongs to the Special Issue Advances in Information Theory)

Abstract

:
The development of the complex and multi-dimensional urban socio-economic system creates impacts on natural capital and human capital, which range from a local to a global scale. An emergy-based multiple spatial scale analysis framework and a rigorous accounting method that can quantify the values of human-made and natural capital losses were proposed in this study. With the intent of comparing the trajectory of Beijing over time, the characteristics of the interface between different scales are considered to explain the resource trade and the impacts of emissions. In addition, our improved determination of emergy analysis and acceptable management options that are in agreement with Beijing’s overall sustainability strategy were examined. The results showed that Beijing’s economy was closely correlated with the consumption of nonrenewable resources and exerted rising pressure on the environment. Of the total emergy use by the economic system, the imported nonrenewable resources from other provinces contribute the most, and the multi-scale environmental impacts of waterborne and airborne pollution continued to increase from 1999 to 2006. Given the inputs structure, Beijing was chiefly making greater profits by shifting resources from other provinces in China and transferring the emissions outside. The results of our study should enable urban policy planners to better understand the multi-scale policy planning and development design of an urban ecological economic system.

1. Introduction

Due to the complex and multi-dimensional urban socio-economic system, the knowledge of the organizational structure, urban energy and material inward-outward flows [1], capturing the trade-offs between natural, economic and social capital [2] is a major step towards the design of sustainable development schemes. Meanwhile, as governments are increasingly concerned about international negotiations, cooperation, and conflicts on climate change issues, the traditional environmental problems in cities such as waste water removal, sanitation, water supply, indoor and exterior air pollution, etc. have been proven to have a cross-regional impact [3]. Analysis of individual urban processes is not enough for understanding the inherent functional principles and evaluating their environmental performance since such a narrow view may indistinguishably consider international and regional trading [4] or simply shift the environmental impacts to the other parts of local economic activities life cycle [5]. Challenges for urban development from a sustainable perspective have been divided into two categories: (1) modes of resource supply; (2) the activity boundary that outlines the emissions emitting operations for which a city is responsible and that must be accounted for in the city’s mass/energy balance. As a consequence, urban socio-economic performance metrics must be capable of linking local scales and extend further to the economy and ecosystems scales [6]. With the international trading network taken into account, fruitful studies focusing on specific countries have been presented [7,8,9,10,11,12,13]. There is an urgent need to develop a quantitative methodology that can evaluate both the resource supply and the adverse environmental effects of urban socio-economic systems at different scales and take into account how they affect the urban system’s dynamics and sustainability.
Methods relying on input-side information have also been developed, usually based on mass [14], energy [15], exergy [16], emergy [17,18,19,20] and ecological cumulative exergy consumption [21]. Emergy synthesis is a method of environmental accounting derived from energy system theory that uses the energy (in units of the same kind) required to produce a good or service as a nonmonetary measure of the value or worth of components or processes within ecosystems and the economy [22]. The Emergy synthesis method transcends systems’ analysis boundaries, considers resource inputs and environmental contributions, and constructs the basic emergy-based index system [23]. Until now, a large number of systems have been evaluated by means of the emergy method on regional and national scales [19,20,24,25,26,27,28,29,30,31]. Most of these studies, however, did not focus on the multiscale analysis of resource supply and emissions impact, although important steps ahead have been taken in that direction. Chen and Shonnard [32] presented a hierarchical approach for environmentally conscious chemical process design based on the Analytic Hierarchy method. Brown and Ulgiati [33] applied the emergy method to suggest a system view of ecosystem integrity and also to assess the emergy investment needed to restore ecosystem health. Bakshi and his colleagues proposed a multiscale statistical framework for life cycle inventory analysis in some case studies of the U.S. economy and the CGAM cogeneration system [5,34,35,36]. Four kinds of spatial hierarchy structures were defined, including economy, life cycle, equipment and hybrid scale, yet the majority of these works have just developed a conceptual framework rather than specify a detailed list of the different emission categories, especially the emission impacts on different scales. As a smaller control unit, the city nests in a nation’s economic system, which is different from the doubly-nested world economic system. A city’s expanding resources consumption requires its neighbors to expend (considering the factor of state socioeconomic regulation) and purchase from abroad; meanwhile, a city should be held accountable for its “external” emissions. Here, emergy algebra was used to quantify the values of human-made and natural capital losses which were considered as indirect inputs of ecological services for airborne and waterborne pollutants dilution and damage repair or replacement to “internalize” the “externalities” with emphasis on a joint application of the emergy synthesis and LCA methods. The results obtained are potentially useful in understanding the supply networks of a city belonging to different hierarchical levels of the economy and would enable decision-makers to target emission policy measures by purchasing third-party offsets.
This paper proposes an emergy-based multiple spatial scale analysis framework and a rigorous accounting method that can quantify the values of human-made and natural capital losses. With the intent of comparing the trajectory of Beijing, the characteristics of the interface between different scales are considered for explaining the resource trade and the impacts of emissions. In addition, we examine our improved determination of emergy analysis and acceptable management options that are in agreement with Beijing’s overall sustainability strategy.
As a follow-up work of our earlier effort to make an assessment evaluating the environment and economic development in Beijing’s socio-economic system on a common base [29,30,37,38], this work serves as a further attempt to assess both the energy resource consumption and the adverse environmental effects in a unitary manner from a cross-regional perspective based on emergy analysis.

2. Methods

2.1. Emergy-Based Multiple Spatial Scale Analysis Model

Emergy is formally defined as all the available energy of one kind previously used up directly and indirectly to make a product or service [39,40]. As a thermodynamic-based environmental accounting approach, the emergy synthesis converts all materials, energy sources, human labor and services required directly and indirectly into emergy unit that are summed up to yield the total emergy [22]. Emergy analyses are carried out using transformities, specific emergies and other factors that are determined according to a particular planetary baseline [22,41], which is decided by the solar equivalences of the three primary energy inputs to the biogeosphere, i.e., solar radiation, residual and deep heat of the Earth, and the gravitational attraction of the sun and moon. In this study, transformities were converted from global emergy baseline of 9.44 × 1024 to 15.83 × 1024 seJ/yr recommended by Brown and Ulgiati [41].
A typical diagram describing an urban system is shown in Figure 1, where the standard energy system symbols are used [22]. At the planetary level of organization, there are no substantial exchanges with the larger system, except for solar and gravitational energy entering the system from external sources. Within the large box, they indicate the spatial boundaries of the urban system, renewable emergy (R), i.e., the rain, wind, tides, waves, etc., Nature also does work that indirectly supports the activities of the world socioeconomic system (e.g., the photosynthesis of natural ecosystems that fixes carbon and replenishes oxygen in the atmosphere, which is necessary for all life, the movement of clean air that replaces contaminated air over cities and water flows that supply the capacity to dilute municipal wastes). The emergy provided by fuels and electricity is modeled on a separate pathway that acts on the material products arranging and ordering them. Humans extract and process the slowly renewed material products of natural work in the environmental system, i.e., fossil fuels and minerals. These inflows are considered to be nonrenewable because they are being used by socioeconomic system at a rate that is much greater than their natural renewal rate. Human work is also used to carry out economic production using these raw materials and to carry out the other processes and functions of society.
Figure 1. The urban socio-economic system position and role in the national and world system, described in terms of net emergy flows and trade (without considering transport of pollutants).
Figure 1. The urban socio-economic system position and role in the national and world system, described in terms of net emergy flows and trade (without considering transport of pollutants).
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The multiple spatial scales between the environment and human socioeconomic systems can most easily be understood by modeling the world system as a whole (see Figure 1 and Figure 2). Emergy and associated systems language also provides a tool for illustrating energy and material flows between regions, as well as controlling (feedback) mechanisms. In other words, it becomes possible to visualize the flows and interactions referred to above, and simplify them through aggregation, thereby enabling the human mind to conceptualize small and large parts simultaneously, and hence see the bigger picture more clearly. By drawing on the results in this thesis, and the example above, Figure 1 therefore illustrates the urban system’s position and role in both the national and world system, depicted in emergy systems language.
Figure 2. The urban socio-economic system position and role in the national and world system, described in terms of net emergy flows and trade (considering transport of pollutants).
Figure 2. The urban socio-economic system position and role in the national and world system, described in terms of net emergy flows and trade (considering transport of pollutants).
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However, even if resources or pollutions embodied in trade are fully understood and international responsibilities are reallocated on a consumption basis, it is far from enough to promote global cooperation to combat economic loss and ecological impacts. It would be great progress, though, not to mention that net pollution importers may not accept consumption-based methods. Figure 2 represents the waste released and its interaction with the urban system itself. Air and water emissions and solid waste are controlled based on additional input of fuels, goods and labor force. Thus, simply trying to seek a single global solution that is implemented by national governmental units because of global impacts is far from satisfactory. The essential role of smaller-scale effects must be recognized. In this sense, a polycentric approach might be an alternative for the problem, which means actions at various levels with active oversight of urban, regional, and national boundaries.
As we live in a highly globalized world, economies of scale and comparative advantages exist in certain areas, rendering trade and commerce highly valuable and emissions “ownership” more complex. The processes described in Figures 2 are similar in many ways, but have one major difference; on a more aggregate scale, not only is control fed back, but waste is also generated by the world system. Put together, this means that the city draws on local environmental and human resources, together with non-renewable energies from other peripheries, hence facilitating the process of accumulation in the core, only to risk exhausting the local, national and global resource base, and building up stored waste. With this current voluntary set-up and focus solely on emissions produced in each country, and in the globalized world in which we live, a perverse incentive exists for industrialized countries to transfer high emitting activities to the developing world.

2.2. Emergy Algebra

Emergy algebra comprises two parts: (1) resources and energy inputs and (2) emission impacts. The emergy embodied into an imported product is made up of two parts, one is from geobiosphere work and the other one is from services needed for its production during previous manufacturing steps [23]. Here, a monetary measure is used to account the indirect labor embodied in the production and delivery of imported goods.
In the waste side, Ulgiati et al. [42] focused on the emergy resources required in order to prevent or fix reversible damages. Moreover, they pointed out that: (1) additional emergy resources are needed to replace the lost assets or units, when irreversible damages occur, and that (2) when replacement is not possible, at least a conservative estimate of the natural or human capital loss should be attempted, based on the resources previously invested for its generation, in order to ascertain the true cost of a process product. Following Ulgiati et al. [42] and Ulgiati and Brown [43], additional emergy cost terms should be included in order to account for: (a) dilution and abatement of emissions by natural processes, (b) abatement, uptake and recycle of emissions by means of technological devices, (c) repair of damages to human-made assets by means of maintenance activities, (d) reversible and irreversible damages to natural capital (e.g., loss of biodiversity), and finally (e) reversible and irreversible damages to human health. As a consequence, the total emergy cost U (here, U = used) can be calculated as:
U = R + N + F + F1 + … + Fn
where R and N are respectively the locally renewable and nonrenewable emergy resources, F is the emergy of imported goods and commodities (including their associated services) and where the Fi terms include the environmental or human-driven emergy investments (here, F = feedback) needed to prevent or fix the damages occurred and charged to the process:
  • F1 = Σj F1,j = the sum of all j-th input flows to prevent or fix damage 1;
  • Fn = Σk Fn,k = the sum of all k-th input flows to prevent or fix damage n.
In this study, a preliminary damage assessment of losses is performed according to the framework of the Eco-Indicator 99 assessment method [44] as well as the authors’ own preliminary work [30,31]. Such a method, like all end-point life cycle impact assessment methods, suffers from very large uncertainties intrinsically embodied in its procedure for assessment of final impacts. Damages to natural capital are expressed as the Potentially Disappeared Fraction (PDF) of species in the affected ecosystem, while damages to human health are expressed as Disability Adjusted Life Years (DALY), according to references [44,45,46]. The impact of emissions on human health can be viewed as an additional indirect demand for resource investments. Human resources (considering all their complexity: life quality, education, know-how, culture, social values and structures, hierarchical roles, etc.) can be considered as a local slowly renewable storage that is irreversibly lost due to the polluting production and use processes. The emergy loss can be calculated as:
L w , 1 * = m i * × DALY i × τ H
where, Lw,1* is the emergy loss in support of the human resource affected, i refers to the i-th pollutant, m* is the mass of chemicals released, DALY is its E.I. 99 impact factor and τH is the unit emergy allocated to the human resource per year, calculated as τH = total annual emergy/population.
The effect of Potentially Disappeared Fraction of Species (PDF) can be quantified as the emergy of the loss of local ecological resources, under the same rationale discussed above for the human resource:
L w , 2 * = m i * × PDF ( % ) i × E B i o
where, Lw,2* is the emergy equivalent of the impact of a given emission on urban natural resource, PDF(%) is the fraction potentially affected, measured as PDF × m2 × yr × kg−1.
Finally, damage associated with solid waste generation can be measured by land occupation for landfill and disposal. This may be converted to emergy via the emergy/area ratio (upper bound, average emergy density of economic activities) or even via the emergy intensity of soil formation (lower bound, average environmental intensity). Thus the related emergy loss (Lw,3) can be obtained using the total occupied land area multiplied by the economic or environmental emergy intensity of such an area (choice depends on the area of the investigated system).

2.3. Case Study

Beijing (N115°25–117°30´, E39°26´–41°03´) lies at the eastern edge of the Eurasian continent and belongs to the Bohai sea rim economic circle, with small plains in the south and mountains in the west and north, covering an area of 16,807.8 km2. Characterized by its long history and central political and cultural position, Beijing is amongst the most developed cities in China with a fully integrated industrial structure, including electronics, machinery, chemicals, light industry, textile and automobile manufacturing. Like other metropolis in developing countries, Beijing faces the dilemma of urban economic development versus social and ecological problems comprising the large floating population, high-yield agricultural land loss, resource shortages, high levels of pollution, ecological deterioration, and increasing risks of disaster. The evolution of the Beijing urban system can be treated as a history of resource consumption and accumulation, which has, in turn, brought about the changes in the urban structure and organization. As mentioned above, most of these intensive resources consumed in Beijing are purchased from outside with the exception of a small proportion of the fuels and minerals. Also, all the flows of resources are accompanied with human services and money flows.
The reason for choosing Beijing as the primary study site for this research is that Beijing is a major node linking China and the world and the nation and its provinces. The strong nationwide support for the 2008 Olympic Games in Beijing—hosted at the expense of investments elsewhere in the country—offers a typical example of the Chinese desire for global recognition. The successful hosting of this globally significant event is seen as firmly demonstrating China’s winning a central position on the world stage. This interpretation is possible because Beijing as the capital city represents China to the outside world. This paper focuses on how Beijing—in terms of both its physical reality and how it is imagined—mediates the interesting dynamics among various local, national, and global processes.

3. Results

3.1. Main Emergy Flows in Beijing

Figure 3 shows the inputs and internal structures of Beijing that were quantified in this study. We evaluated the emergy inputs supporting economic activities of urban system and compared the emergy inflows to measures of economic activity in Beijing. The following major classes of emergy inputs supporting Beijing from 1999 to 2006 were documented: (1) renewable energy sources, (2) soil erosion, (3) energy consumption, (4) minerals consumed, (5) imported goods other than fuels and minerals, (6) imported services in goods, fuels and minerals, (7) imported services, and (8) immigrants.
Figure 3. Summary flow diagram for the main emergy flows in Beijing.
Figure 3. Summary flow diagram for the main emergy flows in Beijing.
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3.2. The Determination of Pollutants

Our study deals with the emissions harmful to human health and the ecosystem listed in Table 1. Air emission discharges from both urban production and use include SO2, dust, NOx and CH4 (respiratory disorders), CO2, N2O and CH4 (climate change). Eight waterborne pollutants (mercury, cadmium, hexavalent chromium, lead, arsenic, volatile phenol, cyanide, oil) were selected as indicated. The loss fractions of human health and ecosystem quality (DALY/kg of emission, PDF × m2 × yr) are collected in the reference [44]. The emission data related to SO2, dust, and NOx were collected from governmental publications, such as the Beijing Statistical Yearbook and the Chinese Environmental Statistical Yearbook [47,48]. Data about CO2, N2O and CH4 are calculated as greenhouse gases released at local and global scales, based on direct and indirect energy consumption, that in turn are evaluated according to the Embodied Energy Analysis method [49,50]. The embodied energy of materials and energy flows is calculated by multiplying local inputs by appropriate Oil Equivalent Factors.
Table 1. Lists of emissions and environmental impacts.
Table 1. Lists of emissions and environmental impacts.
Type of PollutionPollutantDamage Category Human HealthDALY/kg of EmissionDamage Category Ecosystem QualityPDF × m2 × yr
Airborne pollutionCO2Climate change2.10 × 10−7
NOxRespiratory disorders8.87 × 10−5Acidification5.71
SO2Respiratory disorders5.46 × 10−5Acidification1.04
DustRespiratory disorders3.75 × 10−4
N2OClimate change6.90 × 10−5
CH4Respiratory disorders1.28 × 10−8
CH4Climate change4.40 × 10−6
Waterborne pollutionMercury Ecotoxic emissions1.97 × 102
CadmiumCarcinogenic effects7.12 × 10−2Ecotoxic emissions4.80 × 102
Hexavalent ChromiumCarcinogenic effects3.43 × 10−1
Lead Ecotoxic emissions7.39
ArsenicCarcinogenic effects6.57 × 10−2Ecotoxic emissions11.4
Volatile phenolCarcinogenic effects1.05 × 10−5
CyanideCarcinogenic effects4.16 × 10−5
OilCarcinogenic effects4.16 × 10−5

3.3. Emergy Accounting of Beijing Socio-Economic System

Examination of various aspects of the Beijing economy includes a discussion of Beijing’s emergy resources, emergy consumption patterns, emergy conservation, and emergy yields. The results in 2006 are shown in the Appendix. In accordance with the system picture of Beijing (see Figure 3) and the consequent calculations shown in the Appendix, main flows introduced to the Beijing urban socio-economic system for the studied years are summarized in Table 2.

3.3.1. Emergy Inflows in Beijing Socio-Economic System

Since 1999, Beijing as the capital of China has adhered to the policy of reform and opening-up, and focused on economic construction. Gradually, it has stepped onto the road of establishing a market-oriented economy system. As a result, the consumption of energy, material and labors increased correspondingly. Total emergy actually used (U), as potential investment in emergy yield of the city, increases with an annual average of 19.88% with a peak in 2004 (25.11%).
As the primary impetus for the economy, environmental free renewable resources (R) involving sunlight, rain, wind, and geothermal heat remains approximately unchanged at this temporal scale (Figure 4). For the Beijing economy, the specific flow of the geothermal heat with emergy is much more than that from the sunlight, wind and rain. It is worth noticing that, of all the renewable inputs, only the largest item, rain, is taken into account though all the emergy inputs are estimated to avoid double-accounting, see Appendix. Participation of non-renewable emergy flows from urban local sources (N) fluctuated in this period so that the obvious fluctuation in constructed local input includes limestone, sand and gravel and iron ore. Construction materials are the largest individual N flows, which is much more than the natural topsoil losses for plant growing and from the degraded soil erosion.
Table 2. Comparison of main emergy indexes and flows for time series emergy synthesis of Beijing.
Table 2. Comparison of main emergy indexes and flows for time series emergy synthesis of Beijing.
VariableItemUnit2000200220042006
POPPeople supportedUnit1.36 × 1071.42 × 1071.49 × 1071.58 × 107
GDPGross domestic product$/yr3.00 × 10103.88 × 10105.17 × 10101.01 × 1011
RRenewable sourcesseJ/yr1.05 × 10211.05 × 10211.03 × 10211.03 × 1021
N0 + N1F + N1MLocally nonrenewable resourcesseJ/yr5.65 × 10226.48 × 10228.34 × 10228.04 × 1022
N2F + N2MImported fuels and minerals (from other provinces)seJ/yr1.04 × 10231.07 × 10231.25 × 10231.45 × 1023
N3F + N3MImported fuels and minerals (from other countries)seJ/yr1.26 × 10202.28 × 10205.95 × 10217.19 × 1021
G1Imported goods (from other provinces)seJ/yr4.69 × 10226.71 × 10229.54 × 10221.19 × 1023
G2Imported goods (from other countries)seJ/yr2.76 × 10223.39 × 10225.56 × 10226.95 × 1022
I11 + I12 + I13Dollars paid for imports goods (from other provinces)$/yr1.28 × 10101.50 × 10102.44 × 10103.61 × 1010
I21 + I22 + I23Dollars paid for imports goods (from other countries)$/yr7.55 × 1097.60 × 1091.42 × 10102.10 × 1010
I3Dollars for tourism$/yr1.10 × 10101.43 × 10101.70 × 10102.30 × 1010
I4Dollars paid for imported labor$/yr1.89 × 1082.88 × 1084.67 × 1087.30 × 108
P3 (I11 + I12 + I13)Emergy value of imported services (from other provinces)seJ/yr4.59 × 10225.56 × 10228.72 × 10221.29 × 1023
P2 (I21 + I22 + I23)Emergy value of imported services (from other countries)seJ/yr2.69 × 10222.81 × 10225.08 × 10227.51 × 1022
P3I2Emergy value for tourismseJ/yr5.52 × 10227.17 × 10228.50 × 10221.15 × 1022
P3I3Emergy paid for imported laborseJ/yr9.43 × 10201.44 × 10212.33 × 10213.65 × 1021
The Appendix also lists main imported inputs in terms of emergy flows for 2006 in Beijing. The total imports increased from 1.51 × 1023 to 3.49 × 1023 seJ/yr. Of the total imported resources, fuels grew by 1.52-fold, with emergy rising from 8.84 × 1022 to 1.35 × 1023 seJ/yr, while the total imported building materials (including iron ores, sand and gravel, iron and steel) increased by 3.92-fold from 4.32 × 1022 to 1.70 × 1023 seJ/yr. This indicates that Beijing’s economic development is increasingly dependent on the infrastructure construction, which has even replaced the fuel-consuming industry for nearly a decade. In emergy to money terms, imported goods have become the most important item in this category. The export emergy flows could be highlighted petroleum derived products, minerals and mechanical and transport equipment. As shown in Figure 4, the service associated with imports in Beijing was a total of 2.04 × 1023 seJ/yr in 2006, 4.04 times more than that in 1999. This increase in import results in decreased self-sufficiency, so the purchased component of the total economy was more important, supporting the growth of the economy. The services imported from other provinces were 7.6 times more than that from abroad, indicating that the imports of Beijing were still increasingly dependent upon the transmission of domestic market. And it’s worth mentioning that, in emergy to money terms, the tourism and emergy paid for imported labor are increasing strongly, more than 2.58 and 5.52 times respectively.
Figure 4. Temporal variations of emergy inflows in Beijing socio-economic system during concerned period of 1999–2006.
Figure 4. Temporal variations of emergy inflows in Beijing socio-economic system during concerned period of 1999–2006.
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3.3.2. The Components of the Energy Consumed in Beijing

The Appendix and Table 2 give detailed information on the consumption of energy by source for Beijing from 1999 to 2006. During this period, coal was still the most primary energy source for the region, as measured by both heat content and emergy. The coal input decrease from 2000 is evident in the figure, but this was followed by a rapid rebound over the next three years when Beijing won the bid to stage the 2008 Olympiad. Meanwhile, the consumption of petroleum from other provinces steadily decreased; however, the imported oil increases along with coal consumption in these ten years. Imported electricity is a large fraction of the total emergy use (11% to 13%) that grew fast from 1999 to 2006. During the decade, exported electricity in these years remained low. Natural gas also became the fourth largest energy source. The consumption of natural gas showed a similar trend to that of imported electricity, but with a damped response to fluctuations.

3.3.3. Mineral Use in Beijing

The emergy of iron and steel made the largest contribution to the emergy of minerals consumed followed by the emergy of lead up to 1999, when it was overtaken by the emergy of sand and gravel for construction. Compared with sand and gravel, hi-tech products, machinery and electrical equipment increased greatly from 1999 to 2006 and it consistently occupied the position of the 3rd largest emergy input after labor and services.

3.4. The Human Capital and Natural Capital Losses

From 1999 to 2006, the total human capital losses caused by the six air pollutants increased dramatically from 4.17 × 1020 to 1.15 × 1021 seJ/yr and reached a maximum peak of 1.31 × 1021 seJ/yr in 2005 (Table 3), while losses due to the urban production sectors fluctuated with a maximum at 1.70 × 1021 seJ/yr in 2005, as shown in Table 3. The natural capital losses showed that such losses, different from human capital losses, were assessed on the basis of acidification and ecotoxicologic emissions. The loss due to NOx shows a very large increase in the investigated period, especially after 2004. Results seem to suggest that NO2 has overtaken SO2 as the ever-bigger issue in Beijing’s environmental pollution treatment during 1999–2006. The growth rate of damage that is caused by the emissions from urban consumption processes climbs up faster. Nitrogen dioxide and sulfur dioxide provided the largest contribution to natural capital loss while the greenhouse gases (CO2) and dust play the larger role in human capital loss.
Table 3. Indirect emergy input associated to emissions (Unit: seJ/yr).
Table 3. Indirect emergy input associated to emissions (Unit: seJ/yr).
Emissions2000200220042006
Human Capital LossesNatural Capital LossesHuman Capital LossesNatural Capital LossesHuman Capital LossesNatural Capital LossesHuman Capital LossesNatural Capital Losses
CO23.98 × 1020 4.40 × 1020 7.36 × 1020 7.82 × 1020
CO0 0 0 0
NOx2.03 × 10201.79 × 10212.98 × 10202.04 × 10213.03 × 10201.39 × 10216.16 × 10202.65 × 1021
SO23.96 × 10201.03 × 10213.46 × 10207.02 × 10203.13 × 10204.23 × 10202.85 × 10203.62 × 1020
TSP7.04 × 1020 6.92 × 1020 1.19 × 1021 8.90 × 1020
N2O2.27 × 1018 2.57 × 1018 4.45 × 1018 4.97 × 1018
CH41.26 × 1018 1.51 × 1018 2.43 × 1018 2.72 × 1018
Mercury00000000
Cadmium0000004.23 × 10151.90 × 1015
Hexavalent chromium2.03 × 1018 7.53 × 1017 1.22 × 1018 9.27 × 1017
Lead08.00 × 101503.46 × 101501.12 × 101503.07 × 1014
Arsenic6.50 × 10161.54 × 1015000000
Volatile phenol1.66 × 1015 3.46 × 1014 1.34 × 1014 2.42 × 1014
Cyanide3.29 × 1015 9.14 × 1014 3.74 × 1014 1.24 × 1014
Oil3.70 × 1017 2.28 × 1017 1.54 × 1017 8.99 × 1016
Lw,1*1.71 × 10211.78 × 10212.55 × 10212.58 × 1021
Lw,2*2.82 × 10212.74 × 10211.81 × 10213.01 × 1021
Lw,31.54 × 10191.87 × 10193.96 × 10194.98 × 1019
Note: Lw,1* is emergy of the human life losses caused by the emissions; Lw,2* is emergy of the ecological losses due to the emissions; Lw,3 is emergy of the land occupation caused by the emissions.

3.5. Analysis of the Emergy Indicators for Beijing

In this section, a series of emergy indicators based on the emergy accounting for Beijing economy are analyzed, discussed and compared with those of other Chinese cities. These indicators lend insight to the emergy support basis, the economic structure and the characters of the Beijing economy.

3.5.1. Emergy Intensity

Empower density or the emergy flow per unit area is a related measure that indicates the spatial concentration of economic activity or the intensity of development in a city. As shown in Table 4, the empower density of the Beijing economy developed from 1.85 × 1013 seJ/m2 in 1999 to 4.59 × 1013 seJ/m2 in 2006, revealing that Beijing maintained a rapid economic growth and scored a new high in economic aggregates during the past years. Accounting results shows that this growth was mainly caused by the input from goods and services which hold relatively high emergy transformity. Combined with the emergy use structure and the value of emergy use per person in Beijing, we find that of the total resource consumed in Beijing, most is correlated with goods and services purchased from outside, with little from free natural inputs. It also means that the development both in the living standard of local residents and in urban economy depends completely on the purchase of resources from outside.
Table 4. The integrated emergy indicator of Beijing.
Table 4. The integrated emergy indicator of Beijing.
VariableItemUnit2000200220042006
UTotal emergy usedseJ/yr3.68 × 10234.30 × 10235.96 × 10237.53 × 1023
EDEmpower densityseJ/m22.19 × 10132.56 × 10133.63 × 10134.59 × 1013
U/POPUse per personseJ/ pop2.71 × 10163.02 × 10164.00 × 10164.76 × 1016
ELREnvironmental loading ratio 3.48 × 1024.07 × 1025.78 × 1027.31 × 102
EYRNet emergy yield ratio 1.191.181.161.12
ESIEnvironmental sustainability index 3.40 × 1032.90 × 1032.01 × 1031.53 × 103
Note: U = R + N2F + N2M + N3F + N3M + G1 + G2 + P3 (I11 + I12 + I13) + P2 (I21 + I22 + I23) + P3I2 + P3I3 + N0 + N1F + N1M; ED = U/area; ELR = (N2F + N2M + N3F + N3M + G1 + G2 + P3 (I11 + I12 + I13) + P2 (I21 + I22 + I23) + P3I2 + P3I3 + N0 + N1F + N1M + Lw,1* + Lw,2* + Lw,3)/(R + P3 (I11 + I12 + I13) + P2 (I21 + I22 + I23)); EYR = (U + Lw,1* + Lw,2* + Lw,3)/(N2F + N2M + N3F + N3M + G1 + G2 + P3 (I11 + I12 + I13) + P2 (I21 + I22 + I23) + P3I2 + P3I3 + Lw,1* + Lw,2* + Lw,3); ESI = EYR/ELR.

3.5.2. Import/Export Structure

For an urban ecosystem, the emergy welfare enjoyed by its residents also can be revealed by comparing the resource imports and exports, which are accounted through two ratios here, one is the difference between exports and imports; the other is exports to imports. From 1999 to 2006, the exports/imports ratio of Beijing is less than 1. During this period, the rapid development of Beijing industry brought about a quick need for energy, which made the fuel consumption increase from 1.01 × 1023 seJ in 1999 to 1.90 × 1023 seJ in 2006. Most of these fuels are used by industry, construction and transportation. In this period, the imported emergy was much more than the exported emergy with the largest difference appearing in 2005 and 2006.

3.5.3. Environmental Sustainability Index

This index is an aggregate measure of the economic benefit (EYR) per unit of environmental loading (ELR). It shows that the long-term capacity of the renewable emergy sources to support life is being degraded. A quick estimate of the renewable carrying capacity of a state at the current standard of living is obtained by multiplying the fraction of use that is renewable by the present population of the state [22]. As a consequence of EYR and ELR trends, the sustainability index ESI dropped significantly, thus suggesting that emissions greatly reduced the sustainability of the urban socio-economic system by pulling resources for damage repair and for replacement of lost natural and human-made capital.

3.6. Emergy-Based Multiple Spatial Scale Analysis of Beijing Socio-Economic System

We modeled the interaction of economic activities with environmental resources as a production function situated at the interface between the environment and society in cross-hierarchy perspective. Minerals, fuels, natural products as timber, water and human labor, are all required emergy inputs from different regions that support economic activities. Meanwhile, the conceptual model also showed that the environment provides emergy to support society as a whole and the emissions have the direct and indirect impacts on the economic production function on all urban, country and global scales. The multiple spatial scale analysis separates inflow and outflow, which are ordered into societal assets and structures. Indeed, when materials and emergy were placed on an equal basis using emergy, we found that materials (steel and iron, et al.) from local and other provinces in China were the dominant input to Beijing’s economy during the period considered. Thus, it is plausible that the total emergy used by a prosperous city, which takes into account the materials as well as the energy used, might explain more of the variance of economic activity than energy alone. If mass alone was used as the measure of relative importance, the construction materials, sand and gravel and crushed stone would dominate the signature of inputs to the Beijing’s economy by an order of magnitude. However, when specific emergies are used to transform the mass inputs to emergy, the picture of the relative importance of materials is very different. Construction materials are still the largest input at times, but other unexpected materials show their strategic importance when converted to emergy. Except for iron ore and steel, from the 1999 to the 2006, purchased/traded commodities including hi-tech products, machinery and electrical equipments from other provinces in China was the third largest contributor of emergy to the urban system. But the growth of traded rate from other countries is much slower than that from other provinces. As Figure 5 shows, emergy flows from the national system are 52.7 times higher than those from the world system in 2006. Also the emergy values are much more than that returned via monetary transactions. This way of illustrating net emergy flows is also possible to be applied to regional relations in general. From another point of view, the multi-scale environmental impacts of waterborne and airborne pollutions continue increasing from 1999 to 2006 and the values cannot be neglected.
Figure 5. Diagrams of emergy cross-hierarchy inflows in different years. Note: R is renewables; NS is local natural system; NRL is local Non-renewables; NRC is Non-renewables from other provinces; NRW is Non-renewables from other countries; W is waste emissions.
Figure 5. Diagrams of emergy cross-hierarchy inflows in different years. Note: R is renewables; NS is local natural system; NRL is local Non-renewables; NRC is Non-renewables from other provinces; NRW is Non-renewables from other countries; W is waste emissions.
Entropy 13 00720 g005
As illustrated in Figure 5, denser flows of emergy move from left to right than what is fed back via monetary transactions, hence resulting in a net accumulation in the global system. In addition, this unfair exchange is self-reinforcing due to neo-colonial controls. Therefore, the distribution of resources and wealth can never be fully understood without explicit emphasis on power relations and fairness. In this figure, control resulting from such power relations is represented by the pathway line moving from right to left. So as long as there is trade, a part of the regions will specialize in resource-intensive production. In that case, in a prosperous city, such as Beijing, the urban consumption demand will shift to other regions and increase their production, which includes the shift of environmental impacts. If resources intensity of these regions is lower than others, then global emissions will decrease. On the contrary, other regions' resource use reduction will even increase global emissions. In this sense, a more systematic consumption-based approach, which can eliminate pollution leakage and encourage reductions to occur where the costs are the lowest, will be more favorable. Thus, given the structure of input, Beijing was chiefly making greater profits by shifting resources from other provinces in China and transferring the emissions outside.

4. Conclusions

Increasing interest among the general public in reducing environmental impacts has fueled the aspiration of eco-cities to achieve healthy status. This study contributes to the current body of relevant literature by exploring Beijing’s organizational structure of the socio-economic system. Our research focused on the characteristics of the interface in Beijing between different scales based on an emergy synthesis approach, in order to highlight the resource trade and environmental impact and separate the inwards/outwards flow, economic and ecological losses between different scales. Clarifications regarding the emissions scope and system boundaries are essential in order to develop a strategy for monitoring the intimate relationship between the resource base and economic structure. Detailed trends of the resource base and performance indicators are examined from a historical perspective for the contemporary Beijing urban system after China’s Economic Reform and Opening Policies in the latest decade.
The results demonstrated that the development of economy in Beijing was closely correlated with the consumption of the nonrenewable resources and exerts rising pressure on the environment. Of the total emergy use by the economic system, the imported nonrenewable resources from other provinces contribute the most, with increasing use of imported nonrenewable resources. The multi-scale environmental impacts of waterborne and airborne pollutions continue to increase from 1999 to 2006.
Considering the structure of inputs, Beijing was chiefly making greater profits by shifting resources from other provinces in China and transferring the emissions outside. Our findings suggested several policy implications, assuming the goal is to achieve urban ecosystem health. In this regard, a regional emission trade scheme (ETS) should be enacted in the Chinese market system, via which the eastern developed regions (such as Beijing) could buy emissions directly from the west area via local governmental transactions. Via such an ETS, emissions in the eastern area can be reduced; furthermore the less developed area also benefit from such an emissions trading system. These policies may seem harsh. Curtailing development, trade or limiting access to resources may end up neo-colonial controls. Our message is not to abandon all development, stop all trade and limit resource access, but rather to highlight the limitations and consequences that might result from not taking such actions.
It is in this sense that we see this article as a step along a research path rather than its final statement. Going beyond a conceptual framework, this study specified a detailed list of emissions categories and regarded them as indirect inputs of ecological services for airborne and waterborne pollutants dilution and damage repair or replacement to “internalize” the “externalities” of different scales with emphasis on a joint application of the emergy synthesis. It is expected that such a detailed listing will evolve over time as formal standards are proposed and revised, and as the technical capacity to increase the pollution types and local impacts continues to improve.

Acknowledgements

This work is supported by the National Ministry of Science and Technology (Grant No. 2007BAC28B03), the National Natural Science Foundation of China (Grant No. 40871056), and the National Science Foundation for Distinguished Young Scholars (Grant No. 50625926).

References

  1. Sachs, W. The Development Dictionary: A Guide to Knowledge as Power; Zed Books: London, UK, 1992. [Google Scholar]
  2. Graedel, T.E.; Allenby, B.R. Hierarchical metrics for sustainability. Environ. Qual. Manage. 2002, 12, 21–30. [Google Scholar] [CrossRef]
  3. Brandon, C.; Ramankutty, R. Toward an Environmental Strategy for Asia; World Bank: New York, NY, USA, 1993. [Google Scholar]
  4. Ahmad, N.; Wyckoff, A.W. Carbon Dioxide Emissions Embodied in International Trade of Goods; Organization for Economic Co-operation and Development: Paris, France, 2003. [Google Scholar]
  5. Hau, J.L. Toward environmentally conscious process systems engineering via joint thermodynamic accounting of industrial and ecological systems. PhD thesis, The Ohio State University, Columbus, OH, USA, 2005. [Google Scholar]
  6. Bakshi, B.R.; Fiksel, J. The quest for sustainability: Challenges for process systems engineering. AIChE J. 2003, 49, 1350–1358. [Google Scholar] [CrossRef]
  7. Schwarz, J.; Beloff, B.; Beaver, E. Use sustainability metrics to guide decision making. Chem. Eng. Progr. 2002, 7, 58–63. [Google Scholar]
  8. Wikle, C.K. Hierarchical models in environmental science. Int. Stat. Rev. 2003, 71, 181–199. [Google Scholar] [CrossRef]
  9. Bakshi, B.R.; Ukidwe, N.U. A multiscale bayesian framework for environmentally conscious process design. In Proceedings of Foundations of Computer Aided Process Design (FOCAPD); Princeton University: Princeton, NJ, USA, 2004. [Google Scholar]
  10. McGregor, P.G.; Swales, J.K.; Turner, K. The CO2 ‘trade balance’ between Scotland and the rest of the UK: Performing a multi-region environmental input-output analysis with limited data. Ecol. Econ. 2008, 66, 662–673. [Google Scholar] [CrossRef]
  11. Nakano, S.; Okamura, A.; Sakurai, N.; Suzuki, M.; Tojo, Y.; Yamano, N. The Measurement of CO2 Embodiments in International Trade: Evidence from the Harmonised Input-output and Bilateral Trade Database; Organization for Economic Co-operation and Development: Paris, France, 2009. [Google Scholar]
  12. Liu, X.B.; Ishikawa, M.; Wang, C.; Dong, Y.L.; Liu, W.L. Analyses of CO2 emissions embodied in Japan-China trade. Energy Pol. 2010, 38, 1510–1518. [Google Scholar] [CrossRef]
  13. Chen, G.Q.; Chen, H.; Chen, Z.M.; Zhang, B.; Shao, L.; Guo, S.; Zhou, S.Y.; Jiang, M.M. Low-carbon building assessment and multi-scale input-output analysis. Commun. Nonlin. Sci. Num. Sim. 2011, 16, 583–595. [Google Scholar] [CrossRef]
  14. Adriaanse, A.; Bringezu, S.; Hammond, A.; Moriguchi, Y.; Rodenburg, E.; Rogich, D.; Schütz, H. Resource Flows: The Material Basis of Industrial Economie; World Resources Institute: Washington D.C., DC, USA, 1997. [Google Scholar]
  15. Spreng, D.T. Net-energy Analysis and the Energy Requirements of Energy Systems; Praeger Publishers: New York, NY, USA, 1988. [Google Scholar]
  16. Szargut, J.; Morris, D.R.; Steward, F.R. Exergy Analysis of Thermal, Chemical and Metallurgical Processe; Hemisphere Publishers: New York, NY, USA, 1988. [Google Scholar]
  17. Odum, H.T. Systems Ecology; John Wiley and Sons: New York, NY, USA, 1983. [Google Scholar]
  18. Odum, H.T. Self-organization and maximum power. In Maximum Power, the Ideas and Applications of H.T. Odum; Hall, C., Ed.; Colorado University Press: Niwot, CO, USA, 1995. [Google Scholar]
  19. Brown, M.; Ulgiati, S. Emergy measures of carrying capacity to evaluate economic investment. Popul. Environ. 2001, 22, 471–501. [Google Scholar] [CrossRef]
  20. Campbell, D.E.; Brandt-Williams, S.L.; Meisch, M.E.A. Environmental Accounting Using Emergy: Evaluation of the State of West Virginia; USEPA: Narragansett, RI, USA, 2005. [Google Scholar]
  21. Ukidwe, N.U.; Bakshi, B.R. Thermodynamic accounting of ecosystem contribution to economic sectors with application to 1992 U.S. Economy. Environ. Sci. Technol. 2004, 38, 4810–4827. [Google Scholar] [CrossRef] [PubMed]
  22. Odum, H.T. Environmental Accounting: EMERGY and Environmental Decision Making; John Wiley & Sons: New York, NY, USA, 1996. [Google Scholar]
  23. Zhang, X.H.; Deng, S.H.; Jiang, W.J.; Zhang, Y.Z.; Peng, H.; Li, L.; Yang, G.; Li, Y.W. Emergy evaluation of the sustainability of two industrial systems based on wastes exchanges. Res. Cons. Recycl. 2010, 55, 182–195. [Google Scholar] [CrossRef]
  24. Brown, M.T.; Odum, H.T. Emergy synthesis perspectives, sustainable development and public policy options for Papua New Guinea. In A Research Report to the Cousteau Society; Center for Wetlands, University of Florida: Gainsville, FL, USA, 1992. [Google Scholar]
  25. Yan, M.C.; Odum, H.T. A study on emergy evaluation and sustainable development of Tibet eco-economic system. J. Nat. Res. 1998, 13, 116–125, In Chinese. [Google Scholar]
  26. Lan, S.F.; Odum, H.T. Emergy evaluation of the environment and economy of Hong Kong. J. Environ. Sci. 2004, 6, 432–439. [Google Scholar]
  27. Huang, S.L.; Chen, C.W. Theory of urban energetics and mechanisms of urban development. Ecol. Model. 2005, 189, 49–71. [Google Scholar] [CrossRef]
  28. Ulgiati, S.; Bargigli, S.; Raugei, M. An emergy evaluation of complexity, information and technology, towards maximum power and zero emissions. J. Clean. Prod. 2007, 15, 1354–1372. [Google Scholar] [CrossRef]
  29. Jiang, M.M.; Zhou, J.B.; Chen, B.; Yang, Z.F.; Ji, X.; Zhang, L.X.; Chen, G.Q. Ecological evaluation of Beijing economy based on emergy indices. Commun. Nonlin. Sci. Num. Sim. 2009, 14, 2482–2494. [Google Scholar] [CrossRef]
  30. Liu, G.Y.; Yang, Z.F.; Chen, B.; Ulgiati, S. Emergy-based urban health evaluation and development pattern analysis. Ecol. Model. 2009, 220, 2291–2301. [Google Scholar] [CrossRef]
  31. Zhang, Y.; Yang, Z.F.; Liu, G.Y.; Yu, X.Y. Emergy analysis of the urban metabolism of Beijing. Ecol. Model. 2010. [Google Scholar] [CrossRef]
  32. Chen, H.; Shonnard, D.R. Systematic framework for environmentally conscious chemical process design: Early and detailed design stages. Ind. Eng. Chem. Res. 2004, 43, 535–552. [Google Scholar] [CrossRef]
  33. Brown, M.T.; Ulgiati, S. Emergy, transformity and ecosystem health. In Handbook of Ecological Indicators for Assessment of Ecosystem Health; Jørgensen, S.E., Costanza, R., Xu, F.L., Eds.; CRC Press: Boca Raton, FL, USA, 2005; pp. 333–352. [Google Scholar]
  34. Ukidwe, N.U. Thermodynamic Input-output Analysis of Economic and Ecological Systems for Sustainable Engineering. Ph.D. thesis, The Ohio State University, Columbus, OH, USA, 2005. [Google Scholar]
  35. Choi, J.K.; Bakshi, B.R.; Haab, T. Effects of a carbon price in the U.S. on economic sectors, resource use, and emissions: An input-output approach. Energy Pol. 2010, 38, 3527–3536. [Google Scholar]
  36. Urban, R.A.; Bakshi, B.R.; Grubb, G.F.; Baral, A.; Mitsch, W.J. Towards sustainability of engineered processes: Designing self-reliant networks of technological-ecological systems. Comput. Chem. Eng. 2010, 34, 1413–1420. [Google Scholar] [CrossRef]
  37. Zhang, L.X.; Chen, B.; Yang, Z.F.; Chen, G.Q.; Jiang, M.M.; Liu, G.Y. Comparison of typical mega cities in China using emergy synthesis. Commun. Nonlin. Sci. Num. Sim. 2009, 14, 2827–2836. [Google Scholar] [CrossRef]
  38. Zhang, Y.; Yang, Z.F.; Yu, X.Y. Evaluation of urban metabolism based on emergy synthesis: A case study for Beijing (China). Ecol. Model. 2009, 220, 1690–1696. [Google Scholar] [CrossRef]
  39. Odum, H.T. Ecological engineering and self-organization. In Ecological Engineering—An Introduction to Ecotechnology; Mitsch, W.J., Jørgensen, S.E., Eds.; John Wiley & Sons: New York, NY, USA, 1989. [Google Scholar]
  40. Scienceman, D.M. Energy and emergy. In Environmental Economics: The Analysis of a Major Interface; Pillet, G., Murota, T., Eds.; R. Leimgruber: Geneva, Switzerland, 1987; pp. 257–276. [Google Scholar]
  41. Brown, M.T.; Ulgiati, S. Updated evaluation of exergy and emergy driving the geobiosphere: A review and refinement of the emergy baseline. Ecol. Model. 2010, 221, 2501–2508. [Google Scholar] [CrossRef]
  42. Ulgiati, S.; Brown, M.T.; Bastianoni, S.; Marchettini, N. Emergy-based indices and ratios to evaluate the sustainable use of resources. Ecol. Eng. 1995, 5, 519–531. [Google Scholar] [CrossRef]
  43. Ulgiati, S.; Brown, M.T. Quantifying the environmental support for dilution and abatement of process emissions: The case of electricity production. J. Clean. Prod. 2002, 10, 335–348. [Google Scholar] [CrossRef]
  44. Goedkoop, M.; Spriensma, R. The Eco–Indicator 99: A Damage Oriented Method for Life Cycle Impact Assessment: Methodology report; Pre. Consultans: Amersfoort, The Netherlands, 2000. [Google Scholar]
  45. Murray, C.J.L.; Lopez, A.D.; Jamison, D.T. The global burden of disease in 1990: Summary results, sensitivity analysis and future directions. Bull. World Health Org. 1994, 72, 495–509. [Google Scholar] [PubMed]
  46. Ukidwe, N.U.; Bakshi, B.R. Industrial and ecological cumulative exergy consumption of the United States via the 1997 input–output benchmark model. Energy. 2007, 32, 1560–1592. [Google Scholar] [CrossRef]
  47. BSY. Beijing Statistical Yearbook 2000–2007; China Statistical Publishing House: Beijing, China, 2001-2008; In Chinese. [Google Scholar]
  48. CESY. China Energy Statistical Yearbook 2000–2007; Statistical Publishing House: Beijing, China, 2001-2008; In Chinese. [Google Scholar]
  49. Slesser, M. Energy Analysis Workshop on Methodology and Conventions; IFIAS: Stockholm, Sweden, 1974; p. 89. [Google Scholar]
  50. Herendeen, R.A. Energy analysis and emergy analysis—A comparison. Ecol. Model. 2004, 178, 227–237. [Google Scholar] [CrossRef]
  51. Odum, H.T.; Brown, M.T.; Brandt-Williams, S.B. Handbook of Emergy Evaluation: A Compendium of Data for Emergy Computation in a Series of Folios, Folio. #1; Center for Environmental Policy, University of Florida: Gainesville, FL, USA, 2000. [Google Scholar]
  52. Brandt-Williams. Handbook of Emergy Evaluation: Folio #4; Center for Environmental Policy, Environmental Engineering Sciences, University of Florida: Gainesville, FL, USA, 2001. [Google Scholar]
  53. Bastianoni, S.; Campbell, D.E.; Ridolfi, R.; Pulselli, F.M. The solar transformity of petroleum fuels. Ecol. Model. 2009, 220, 40–50. [Google Scholar] [CrossRef]
  54. Romitelli, M.S. Emergy analysis of the New Bolivia—Brazil Aas pipeline. In Emergy Synthesis: Theory and Applications of the Emergy Methodology; Brown, M.T., Ed.; Center for Environmental Policy, University of Florida: Gainesville, FL, USA, 2000; pp. 53–69. [Google Scholar]
  55. Yan, M.C.; Odum, H.T. A study on emergy evaluation and sustainable development of Tibetan eco–economic system. J. Nat. Res 1998, 13, 116–125. [Google Scholar]
  56. Odum, H.T.; Diamond, C.; Brown, M.T. Emergy analysis and public policy in texas, policy research project report. Ecol. Econ. 1987, 12, 54–65. [Google Scholar]
  57. Ulgiati, S.; Odum, H.T.; Bastianoni, S. Emergy use, environmental loading and sustainability: An emergy analysis of Italy. Ecol. Model. 1994, 73, 215–268. [Google Scholar] [CrossRef]
  58. Lan, S.F.; Odum, H.T. Emergy evaluation of the environment and economy of Hong Kong. J. Environ. Sci. 2004, 6, 432–439. [Google Scholar]
  59. Brown, M.T.; Ulgiati, S. Emergy analysis and environmental accounting. Encyclopedia of Energy 2004, 2, 329–354. [Google Scholar]
  60. Bargigli, S.; Ulgiati, S. Emergy and life-cycle assessment of steel production. In Proceedings of the Second Biennial Emergy Evaluation and Research Conference, Gainesville, FL, USA, 20–22 September 2003.
  61. Liu, G.Y. Study of urban metabolism process based on ecological thermodynamics. Ph.D. thesis, Beijing Normal University, Beijing, China, 2010. [Google Scholar]

Appendix

Table A-1. Emergy flows supporting urban socio-economic system in 2006.
Table A-1. Emergy flows supporting urban socio-economic system in 2006.
ItemsUnitsRaw AmountTransformity (seJ/unit)Ref. trans.Emergy (seJ/yr)
Free renewable environmental resources
1   SunJ/yr7.02 × 10191by definition7.02 × 1019
2   Kinetic energy of windJ/yr4.87 × 10162.51 × 103[51]1.22 × 1020
3   Rainfall (Geopotential Energy)J/yr1.25 × 10151.74 × 104[51]2.19 × 1019
4   Rainfall (Chemical Potential)J/yr1.12 × 10163.05 × 104[51]3.43 × 1020
5   Geothermal HeatJ/yr1.79 × 10165.76 × 104[51]1.03 × 1021
Exploited local nonrenewable resources
6   Top soil lossJ/yr3.17 × 10141.23 × 105[51]3.90 × 1019
7   CoalJ/yr2.04 × 10176.69 × 104[51]1.37 × 1022
8   Minerals
   Limestoneg/yr1.52 × 10131.68 × 109[52]2.55 × 1022
   Sand and gravelg/yr1.02 × 10131.68 × 109[52]1.70 × 1022
   Iron oreg/yr1.68 × 10131.44 × 109[51]2.41 × 1022
Calculations:
  • Sun: average insolation = 5.36 × 109 J/m2/yr, total area of Beijing region = 1.64 × 104 km2, continental albedo = 0.201. Solar energy received = (total area of Beijing region) (average insolation) (1 − albedo) = (1.64 × 104 km2 × 106) (5.36 × 109 J/m2/yr) (1 – 0.201) = 7.02 × 1019 J/yr.
  • Kinetic energy of wind: air density = 1.3 kg/m3, wind velocity (annual average) = 2.5 m/s, observed winds are about 0.6 of geostrophic wind, drag coefficient = 1.00 × 10−3, Time frame = 365 × 24 × 60 × 60 = 3.15 × 107 s/yr. Wind energy = (air density) (drag coeff.) (geostrophic wind velocity)3 (total area) (time frame) = (1.3 kg/m3) (1.00 × 10−3) (2.5 m/s/0.6)3 (1.64 × 104 km2 × 106) (3.15 × 107 s/yr) = 4.87 × 1016 J/yr.
  • Rainfall (geopotential Energy): total agricultural area of Beijing = 1.64 × 1010 m2, rain (annual average) = 0.318 m/yr, average elevation = 43.5 m, runoff rate = 56.40%. Energy = (total area) (rainfall) (% runoff) (avg elevation) (gravity) = (1.64 × 104 km2 × 106) (0.318 m/yr) (56.40%) (43.5 m) (9.8 kg/m2) = 1.25 × 1015 J/yr.
  • Rainfall (chemical potential energy): water density = 1.00 × 106 g/m3, mass of rainfall water = (rainfall) (total area) (water density) = (0.318 m/yr) (1.64 × 104 km2 × 106) (1.00 × 106 g/m3) = 5.22 × 1015 g/yr, fraction of water that is evapotranspired = 44%, Gibbs free energy of water = 4.94 J/g. Energy = (evapotranspired water) (Gibbs free energy per gram water) = (5.22 × 1015 g/yr) (44%) (4.94 J/g) = 1.12 × 1016 J/yr.
  • Geothermal heat: average heat flow per area = 3.50 × 10−2 J/m2/s. Energy = (land area) (heat flow per area) = 1.79 × 1016 J/yr.
  • Net loss of organic matter in topsoil: soil erosion rate = 8.15 × 102 g/m2/yr, average % organic in soil = 0.02, assuming water content in organic matter = 0.7, energy content of dry organic matter = 5.00 kcal/g. Energy = (total agricultural area) (erosion rate) (% organic) (1 − water content in organic matter) (energy content of dry organic matter) (4186 J/kcal) = (1.64 × 1010 m2) (8.15 × 102 g/m2/yr) (0.02) (1 – 0.7) (5.00 kcal/g) (4186 J/kcal) = 3.17 × 1014 J/yr.
  • Fuels input from local region: coal = 6.42 × 106 t/yr, coal energy = (6.42 × 106 t/yr) (3.18 × 1010 J/t) = 2.04 × 1017 J/yr; Oil = 0 t/yr, oil energy = (0 t/yr) (4.30 × 1010 J/t) = 0 J/yr; Natural gas= 0 m3, natural gas energy = (0 m3) (0.7174 kg/m3) = 0 J/yr.
  • Constructed local input: cement quantity of production = 1.27 × 107 t/yr, assuming 1.2 t limestone and 1.6 t sand and gravel are needed to produce 1t cement and 50% of sand and gravel is from local regain, limestone = 1.52 × 1013 g/yr, sand and gravel = 1.02 × 1013 g/yr, iron ore = 1.68 × 107 t = 1.68 × 1013 g/yr.
Table A-2. Emergy imports for urban socio-economic system in 2006.
Table A-2. Emergy imports for urban socio-economic system in 2006.
ItemsUnitsRaw amountTransformity (seJ/unit)Ref. trans.Emergy (seJ/yr)
9HydroelectricityJ/yr2.30 × 10143.36 × 105[51]7.74 × 1019
10Stream flowJ/yr8.81 × 10153.05 × 104[52]2.69 × 1020
11Fuels import
    CoalJ/yr7.04 × 10176.69 × 104[51]4.83 × 1022
    CokeJ/yr4.72 × 10161.10 × 105[53]5.18 × 1021
    Crude oilJ/yr3.45 × 10179.08 × 104[53]3.13 × 1022
    GasolineJ/yr9.20 × 10161.05 × 105[53]9.64 × 1021
    KeroseneJ/yr1.23 × 10171.10 × 105[53]1.36 × 1022
    Diesel oilJ/yr8.61 × 10161.10 × 105[53]9.48 × 1021
    Fuel oilJ/yr4.42 × 10151.10 × 105[53]4.87 × 1020
    Liquefied petroleum gas (LPG)J/yr6.66 × 10151.11 × 105[53]7.37 × 1020
    Natural gasJ/yr1.58 × 10179.85 × 104[54]1.56 × 1022
12ElectricityJ/yr1.47 × 10171.74 × 105[51]2.57 × 1022
13Imported goods
13.1Imported food, livestock and products
    GrainJ/yr1.91 × 10161.14 × 105[55]2.18 × 1021
    RapeseedJ/yr8.23 × 10168.88 × 104[56]7.31 × 1021
    VegetableJ/yr1.42 × 10147.37 × 104[56]1.05 × 1019
    FruitJ/yr2.30 × 10138.88 × 104[57]2.04 × 1018
    MeatJ/yr2.75 × 1095.31 × 106[55]1.46 × 1016
    MilkJ/yr2.36 × 10113.35 × 106[55]7.90 × 1017
13.2Imported raw and processed materials
    WoodJ/yr1.51 × 10155.36 × 104[51]8.11 × 1019
    Iron oresg/yr4.68 × 10131.44 × 109[51]6.72 × 1022
    Sand and gravelg/yr1.02 × 10131.68 × 109[52]1.70 × 1022
    Paper and paperboardJ/yr1.20 × 10157.37 × 104[58]8.85 × 1019
    SilkJ/yr6.39 × 10111.12 × 107[51]7.18 × 1018
    Wool, animal hairJ/yr1.32 × 10147.37 × 106[51]9.70 × 1020
13.3Imported goods
    Polythene (PE)g/yr7.30 × 10104.69 × 109[59]3.43 × 1020
    Polypropylene(PP)g/yr1.60 × 10104.69 × 109[59]7.51 × 1019
    Polystyrene (PS)g/yr1.10 × 10104.69 × 109[59]5.16 × 1019
    Other coke chemicalsg/yr2.54 × 10104.89 × 109[59]1.24 × 1020
    Other petroleum productsg/yr1.16 × 10124.89 × 109[59]5.69 × 1021
    Iron and steelg/yr2.70 × 10133.16 × 109[60]8.53 × 1022
    Aluminum and articlesg/yr1.20 × 10127.74 × 108[51]9.29 × 1020
13.4Other metals and articlesg/yr2.16 × 10114.74 × 109[51]1.02 × 1021
13.5Hi-tech products, machinery and electrical equipment
    Steelg/yr3.65 × 1093.16 × 109[60]1.15 × 1019
    Aluminumg/yr1.65 × 1097.74 × 108[51]1.28 × 1018
    Copperg/yr1.20 × 1093.36 × 109[59]4.05 × 1018
    Other metalsg/yr4.20 × 1094.74 × 109[51]1.89 × 1019
    Ceramics/Glassesg/yr1.69 × 10103.18 × 109[59]5.37 × 1019
    Plasticsg/yr6.09 × 1097.21 × 109[51]4.39 × 1019
13.6Transport equipment
    Steelg/yr1.88 × 10103.16 × 109[60]5.94 × 1019
    Aluminumg/yr3.21 × 1097.74 × 108[51]2.48 × 1018
    Rubber and plastic materialg/yr2.29 × 1087.21 × 109[51]1.65 × 1018
    Copperg/yr6.87 × 1083.36 × 109[59]2.31 × 1018
13.7Electronic goods (estimated from component materials)
    Ferrous metalg/yr1.25 × 1093.16 × 109[60]3.94 × 1018
    Silica/glassg/yr1.62 × 1093.18 × 109[51]5.16 × 1018
    Copperg/yr4.36 × 1083.36 × 109[59]1.47 × 1018
    Plasticsg/yr1.43 × 1097.21 × 109[51]1.03 × 1019
    Aluminumg/yr8.72 × 1087.74 × 108[51]6.75 × 1017
    Other metalg/yr4.98 × 1084.74 × 109[51]2.36 × 1018
14Imported human labor (commuters)$/yr7.30 × 1085.00 × 1012This study, country emergy/$ ratio3.65 × 1021
15Services associated to imports
    From other provinces$/yr1.80 × 10105.00 × 1012This study, country emergy/$ ratio9.02 × 1022
    Import$/yr1.05 × 10101.13 × 1012This study, world emergy/$ ratio1.19 × 1022
   Size of specific sectors
16Tourism$/yr2.30 × 10105.00 × 1012This study, country emergy/$ ratio1.15 × 1023
Calculations:
9.
Hydroelectricity: Hydroelectricity = 6.40 × 107 kwh/yr. Energy = (6.40 × 107 kwh/yr) (3.60 × 106 J/kwh) = 2.30 × 1014 J/yr.
10.
Stream flow: upstream inflow = 1.78 × 109 m3/yr, coefficient = 4.94 × 106 J/m3. Energy = (upstream inflow) (coefficient) = (1.78 × 109 m3/yr) (4.94 × 106 J/m3) = 8.81 × 1015 J/yr.
11.
Fuel imports: coal = 2.68 × 107 t/yr, coal energy = (2.68 × 107 t/yr) (3.18 × 1010 J/t) = 7.04 × 1017 J/yr; coke = 1.66 × 106 t/yr, coke energy = (1.66 × 106 t/yr) (2.85 × 1010 J/t) = 4.72 × 1016 J/yr; crude oil = 8.09 × 106 t/yr, oil energy = (8.09 × 106 t/yr) (4.30 × 1010 J/t) = 3.45 × 1017 J/yr; gasoline = 1.97 × 106 t/yr, gasoline energy = (1.97 × 106 t/yr) (4.67 × 1010 J/t) = 9.20 × 1016 J/yr; kerosene = 1.23 × 1017 t/yr, kerosene energy = (1.23 × 1017 t/yr) (4.30 × 1010 J/t) = 1.23 × 1017 J/yr; diesel oil = 2.00 × 106 t/yr, diesel oil energy = (2.00 × 106 t/yr) (4.30 × 1010 J/t) = 8.61 × 1016 J/yr; fuel oil = 1.04 × 105 t/yr, fuel oil energy = (1.04 × 105 t/yr) (4.26 × 1010 J/t) = 4.42 × 1015 J/t; LPG = 1.56 × 105 t/yr, LPG energy = (1.56 × 105 t/yr) (4.26 × 1010 J/t) = 6.66 × 1015 J/t; natural gas = 4.06 × 109 m3, natural gas energy = (4.06 × 109 m3) (3.89 × 107 J/m3) = 1.58 × 1017 J/yr.
12.
Electricity: electricity = 4.10 × 1010 kwh/yr. Energy = (4.10 × 1010 kwh/yr) (3.60 × 106 J/kwh) = 1.47 × 1017 J/yr.
13.1.
Imported food, livestock and products: grain = 1.32 × 106 t/yr, grain energy = (1.32 × 106 t/yr × 1000) (1.45 × 107 J/kg) = 1.91 × 1016 J/yr; rapeseed = 3.29 × 106 t/yr, rapeseed energy = (3.29 × 106 t/yr × 1000) (2.50 × 107 J/kg) = 8.23 × 1016 J/yr; vegetable = 1.01 × 104 t/yr, vegetable energy = (1.01 × 104 t/yr × 1000) (1.41 × 107 J/kg) = 1.42 × 1014 J/yr; fruit = 1.00 × 104 t/yr, fruit energy = (1.00 × 104 t/yr × 1000) (2.30 × 106 J/kg) = 2.30 × 1013 J/yr; meat = 3.94 × 102 t/yr, meat energy = (3.94 × 102 t/yr × 1000) (6.99 × 106 J/kg) = 2.75 × 109 J/yr; milk = 8.04 × 104 t/yr, milk energy = (8.04 × 104 t/yr × 1000) (2.93 × 106 J/kg) = 2.36 × 1011 J/yr.
13.2.
Imported raw and processed materials: wood = 1.89 × 105 m3/yr, wood energy = (1.89 × 105 m3/yr) (8.00 × 109 J/m3) = 1.51 × 1015 J/yr; Iron ores, sand and gravel are from; paper and paperboard = 6.00 × 107 t/yr, paper and paperboard energy = (6.00 × 107 t/yr) (2.00 × 107 J/t) = 1.20 × 1015 J/yr; silk = 3.40 × 107 kg/yr, silk energy = (3.40 × 107 kg/yr/1000) (1.88 × 107 J/t) = 6.39 × 1011 J/yr; wool, animal hair = (7.00 × 106 t/yr) (1.88 × 107 J/t) = 1.32 × 1014 J/yr.
13.3.
The weight data of imported goods including polythene (PE), polypropylene (PP), polystyrene (PS), other coke chemicals, other petroleum products, iron and steel, aluminum and articles are collected from [47].
13.4.
The weight data of other metals and articles are collected from [47].
13.5.–13.7.
The weight data of hi-tech products, machinery and electrical equipment including steel, aluminum, copper, other metals, ceramics/glasses, plastics, transport equipment including steel, aluminum, rubber and plastic material, copper, computer technology including ferrous metal, silica/glass, copper, plastics, aluminum and other metals are collected from [61].
14.–16.
The currency data of import human labor, services and tourism are from [47].

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Liu, G.; Yang, Z.; Chen, B.; Zhang, L. Analysis of Resource and Emission Impacts: An Emergy-Based Multiple Spatial Scale Framework for Urban Ecological and Economic Evaluation. Entropy 2011, 13, 720-743. https://doi.org/10.3390/e13030720

AMA Style

Liu G, Yang Z, Chen B, Zhang L. Analysis of Resource and Emission Impacts: An Emergy-Based Multiple Spatial Scale Framework for Urban Ecological and Economic Evaluation. Entropy. 2011; 13(3):720-743. https://doi.org/10.3390/e13030720

Chicago/Turabian Style

Liu, Gengyuan, Zhifeng Yang, Bin Chen, and Lixiao Zhang. 2011. "Analysis of Resource and Emission Impacts: An Emergy-Based Multiple Spatial Scale Framework for Urban Ecological and Economic Evaluation" Entropy 13, no. 3: 720-743. https://doi.org/10.3390/e13030720

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