Vol. 2, No. 4 (2014): Regular Issue

Environmental Management Systems (EMS) offer a structured framework for the improvement of the environmental performance of a company. Moreover, organized industrial estates can offer synergies among industrial companies. The aim of the research was to identify some of the factors that affect the EMS implementation by the companies and particularly to examine the relation between synergy creation and EMS adoption, which may be an indicator that the industrial estates can provide an ideal environment for the EMS implementation. The research focused on all the companies that are located in the industrial estates of Greece, apart from the firms that are purely commercial or service oriented. The data were collected during 2013, through a structured questionnaire. Selected variables from the questionnaire were used in order to build a logistic regression model. The results indicate that improved environmental performance and willingness of the companies to improve their corporate image are factors that increase the possibility for the implementation of an Environmental Management System; On the other hand, the main obstacles are the negative effect between the cost perception of the companies towards environmental actions and the costs associated with the EMS implementation.

Environmental Management Systems (EMS) offer a structured framework for the improvement of the environmental performance of a company. Moreover, organized industrial estates can offer synergies among industrial companies. The aim of the research was to identify some of the factors that affect the EMS implementation by the companies and particularly to examine the relation between synergy creation and EMS adoption, which may be an indicator that the industrial estates can provide an ideal environment for the EMS implementation. The research focused on all the companies that are located in the industrial estates of Greece, apart from the firms that are purely commercial or service oriented. The data were collected during 2013, through a structured questionnaire. Selected variables from the questionnaire were used in order to build a logistic regression model. The results indicate that improved environmental performance and willingness of the companies to improve their corporate image are factors that increase the possibility for the implementation of an Environmental Management System; On the other hand, the main obstacles are the negative effect between the cost perception of the companies towards environmental actions and the costs associated with the EMS implementation.

An Emergy Assessment (EMA) of sugarcane cultivation as feedstock for bioethanol production in South Florida was performed to develop a sustainability profile of the farming systems. In this study, a sugarcane farming system on muck soil (organic soil) was compared with a similar cropping system on a sandy soil (mineral soil). The study provides a comparison of these alternative systems from the perspective of their resource use, environmental impact and sustainability. The representative farm for both systems was based on a 5000 acre farm assumed to be already established in South Florida. Emergy analysis was applied to evaluate environmental support required for the sugarcane production in both systems. In line with the methodology a quantitative inventory of free natural resources and purchased input flows into the systems was created. The results showed that aside ground water irrigation which dominates (44%) in both systems, the largest emergy flows for biofuel production on organic soil were associated with soil erosion or subsidence (19%), labor (12%), evapotranspiration (11%), and fuel (8%). However, for sandy soil production, the main contributors were lime (13%), labor (12%), and fuel (8%). The emergy analysis suggests that due to the non-renewability of soil loss in the organic soil farming system, a reduction in the purchased inputs for sandy (mineral) soils based on alternative farming measures potentially makes mineral soil sugarcane ethanol production a rather more sustainable and attractive alternative for a better environmental performance.

An Emergy Assessment (EMA) of sugarcane cultivation as feedstock for bioethanol production in South Florida was performed to develop a sustainability profile of the farming systems. In this study, a sugarcane farming system on muck soil (organic soil) was compared with a similar cropping system on a sandy soil (mineral soil). The study provides a comparison of these alternative systems from the perspective of their resource use, environmental impact and sustainability. The representative farm for both systems was based on a 5000 acre farm assumed to be already established in South Florida. Emergy analysis was applied to evaluate environmental support required for the sugarcane production in both systems. In line with the methodology a quantitative inventory of free natural resources and purchased input flows into the systems was created. The results showed that aside ground water irrigation which dominates (44%) in both systems, the largest emergy flows for biofuel production on organic soil were associated with soil erosion or subsidence (19%), labor (12%), evapotranspiration (11%), and fuel (8%). However, for sandy soil production, the main contributors were lime (13%), labor (12%), and fuel (8%). The emergy analysis suggests that due to the non-renewability of soil loss in the organic soil farming system, a reduction in the purchased inputs for sandy (mineral) soils based on alternative farming measures potentially makes mineral soil sugarcane ethanol production a rather more sustainable and attractive alternative for a better environmental performance.

Soil pollution has become an important environmental issue due to changes in the land use pattern over the last few decades. However, up to now, except Cd and Pb, little attention was paid on more heavy metals in Baiyangdian soil. This article applied multivariate statistical techniques with element concentration analysis and correlation analysis for source identification of heavy metals in the soil of Baiyangdian. The application of multivariate statistical techniques combined with element concentration analysis and correlation analysis has been proved to be an effective tool for source identification of heavy metals in Baiyangdian soil. Firstly, based on the comparison of heavy metals concentrations of soil with background values of Chinese soils, the examined elements were classified into two main groups: natural and anthropogenic sources. Then principal component analysis and cluster analysis, coupled with correlation analysis, were used to gain additional insight into the origins of different elements in soil. Three main sources for these studied elements, as well as some subdivided sources, were therefore identified. Hg, Pb and As are attributed to commercial and domestic sources; Cd and Cu are mainly derived from industrial sources and Cr and Zn associated with traffic sources.

Soil pollution has become an important environmental issue due to changes in the land use pattern over the last few decades. However, up to now, except Cd and Pb, little attention was paid on more heavy metals in Baiyangdian soil. This article applied multivariate statistical techniques with element concentration analysis and correlation analysis for source identification of heavy metals in the soil of Baiyangdian. The application of multivariate statistical techniques combined with element concentration analysis and correlation analysis has been proved to be an effective tool for source identification of heavy metals in Baiyangdian soil. Firstly, based on the comparison of heavy metals concentrations of soil with background values of Chinese soils, the examined elements were classified into two main groups: natural and anthropogenic sources. Then principal component analysis and cluster analysis, coupled with correlation analysis, were used to gain additional insight into the origins of different elements in soil. Three main sources for these studied elements, as well as some subdivided sources, were therefore identified. Hg, Pb and As are attributed to commercial and domestic sources; Cd and Cu are mainly derived from industrial sources and Cr and Zn associated with traffic sources.

The Pampas region contributes 80% of the total national production of Coal resource is an important material basis for China’s economic and social development. Coal consumption in China has been increasing rapidly especially in recent years. According to the data of IEA, China is the top country in coal production and consumption. Thereupon, CO2 emissions from coal consumption have also been increasing. China is facing more and more pressure from CO2 emissions. Under the background of economic globalization and the pressure of ecological environment deterioration, China's CO2 emissions have become a hot issue in the world. Previous studies mainly focus on the main driving factors of CO2 emissions in economic development or in total energy consumption. Only several studies focus on the driving factors of CO2 emissions from single kind of energy that is coal consumption, which provides much space for this study. This paper aims to inspect the main factors driving CO2 emissions from coal consumption and their driving degree using the STIRPAT model. The ridge regression is borrowed to test the multicollinearity among population, GDP per capita, technology level and urbanization level. The results show that the sequence of the driving factors in CO2 emissions from coal consumption is GDP per capita (A)>urbanization level (UL)>the total population (P)> economic structure (ES) >Technology level (T). The research results provide a scientific basis for Chinese government and relevant departments in making policy decisions to limit CO2 emissions.

The Pampas region contributes 80% of the total national production of Coal resource is an important material basis for China’s economic and social development. Coal consumption in China has been increasing rapidly especially in recent years. According to the data of IEA, China is the top country in coal production and consumption. Thereupon, CO2 emissions from coal consumption have also been increasing. China is facing more and more pressure from CO2 emissions. Under the background of economic globalization and the pressure of ecological environment deterioration, China's CO2 emissions have become a hot issue in the world. Previous studies mainly focus on the main driving factors of CO2 emissions in economic development or in total energy consumption. Only several studies focus on the driving factors of CO2 emissions from single kind of energy that is coal consumption, which provides much space for this study. This paper aims to inspect the main factors driving CO2 emissions from coal consumption and their driving degree using the STIRPAT model. The ridge regression is borrowed to test the multicollinearity among population, GDP per capita, technology level and urbanization level. The results show that the sequence of the driving factors in CO2 emissions from coal consumption is GDP per capita (A)>urbanization level (UL)>the total population (P)> economic structure (ES) >Technology level (T). The research results provide a scientific basis for Chinese government and relevant departments in making policy decisions to limit CO2 emissions.

In this study, ecological network structure analysis is applied into water ecological carrying capacity assessment. Based on theory of ecological network analysis in sustainability quantification and the relationship of WECC and sustainable water use, with the application of presumed water use network model and a new index, WECC is measured from integrated perspective with Baiyang Lake Basin as a case study. The result suggests that with a distance of 28.33×108 m3 network throughflow from that of sustainable network, the network structure is unbalanced. It means that for Baiyang Lake Basin in 2007, the water use network cannot carry throughputs in a sustainable way and its overload quantity is 28.33×108 m3. Through adjusting throughflow on each pathway toward network structure balancing, this method could provide a scientific basis for the coordinated development of social economy and the water eco-environment improvement in the Baiyang Lake Basin.

In this study, ecological network structure analysis is applied into water ecological carrying capacity assessment. Based on theory of ecological network analysis in sustainability quantification and the relationship of WECC and sustainable water use, with the application of presumed water use network model and a new index, WECC is measured from integrated perspective with Baiyang Lake Basin as a case study. The result suggests that with a distance of 28.33×108 m3 network throughflow from that of sustainable network, the network structure is unbalanced. It means that for Baiyang Lake Basin in 2007, the water use network cannot carry throughputs in a sustainable way and its overload quantity is 28.33×108 m3. Through adjusting throughflow on each pathway toward network structure balancing, this method could provide a scientific basis for the coordinated development of social economy and the water eco-environment improvement in the Baiyang Lake Basin.

In a context of increasing use of renewable sources, it is of importance to correctly evaluate the actual sustainability of their implementation. Emergy analysis is one of the possible methods useful for such an assessment. This work aims to demonstrate how the emergy approach can be used to assess the sustainability of wind energy resource in Europe. The Emergy Index of Sustainability (EIS) and the Emergy Yield Ratio (EYR) are used to analyze 90 stations of European regions for three types of wind turbines. To do so, the simplified Chou wind turbine model is used for different set of parameters as: nominal power and size of the wind turbines, and cut-in and cut-out wind speeds. Based on the calculation of the emergy indices, a mapping is proposed to identify the most appropriate locations for an implementation of wind turbines in European regions.The influence of the wind turbine type on the sustainability is also analyzed, in link with the local wind resource. Thus, it is concluded that the emergy sustainability indices are sensitive to the wind turbine design parameters (size, cut-in and cut-outwind speed).

In a context of increasing use of renewable sources, it is of importance to correctly evaluate the actual sustainability of their implementation. Emergy analysis is one of the possible methods useful for such an assessment. This work aims to demonstrate how the emergy approach can be used to assess the sustainability of wind energy resource in Europe. The Emergy Index of Sustainability (EIS) and the Emergy Yield Ratio (EYR) are used to analyze 90 stations of European regions for three types of wind turbines. To do so, the simplified Chou wind turbine model is used for different set of parameters as: nominal power and size of the wind turbines, and cut-in and cut-out wind speeds. Based on the calculation of the emergy indices, a mapping is proposed to identify the most appropriate locations for an implementation of wind turbines in European regions.The influence of the wind turbine type on the sustainability is also analyzed, in link with the local wind resource. Thus, it is concluded that the emergy sustainability indices are sensitive to the wind turbine design parameters (size, cut-in and cut-outwind speed).

The livestock sector is required by the European Union policies to strengthen its multifunctional role by diversifying its production patterns. In Italy many dairy farms have already installed energy plants such as biogas digestors, mainly to increase their economic sustainability. We evaluate in this study the environmental performance of raw milk production to be used for world-renowned ParmigianoReggiano cheese production in a dairy farm located in northern Italy.Other products (crops, meat, biogas, electricity) are also included in the assessment. The study was carried out by means of Material Flow Accounting, Cumulative Energy Demand, Emergy Accounting and Life Cycle Assessment methods. The final purpose was to analyze the effects induced by different mixes of inputs (feedstock, electricity, fertilizers) and outputs (crops, milk, meat, electricity) on the process performance. The evaluation was implemented beforeand afterthe installation of a photovoltaic power plant and a biogas digester coupled to a biogas-fueled electric generator. This study explores five alternative scenarios: Scenario 1. An intensive livestock farm, in which feedstock and electricity are purchased from outside and manure is sold or disposed of; Scenario 2. The real farm before the implementation of PV and biogas, using a fraction of self-produced feedstock and manure as fertilizer; Scenario 3. The same farm, after photovoltaic electricity implementation, to cover 100% of local demand; Scenario 4. The same farm, after installing a manure digester and an electric generator, to produce electricity from biogas (sold as additional product, while digestate is used as fertilizer); 5. A Polish dairy farm, producing crops, meat and milk for the market, using manure as fertilizer and no renewable energy appliances. Results show local and large-scale improvements in the transition from Scenario 1 to Scenario 2 (due to increased optimization driven by fodder self-reliance) as well as in the transition from Scenario 3 to Scenario 3 (due to electricity self-reliance). The transition from Scenario 3 to Scenario 4 shows the added value of additional biogasdriven electric generation, while Scenario 5 shows the advantage of optimized milk production due to pedigree breeding, pasture availability and sale of crops in addition to dairy products. Results suggest that several kinds of improvements are possible by acting on farm structure, renewable energy supply, and different mix of products. Results also confirm the effectiveness of a multicriteriamultiscale biophysical assessment method towards a better understanding of costs and benefits of production alternatives.

The livestock sector is required by the European Union policies to strengthen its multifunctional role by diversifying its production patterns. In Italy many dairy farms have already installed energy plants such as biogas digestors, mainly to increase their economic sustainability. We evaluate in this study the environmental performance of raw milk production to be used for world-renowned ParmigianoReggiano cheese production in a dairy farm located in northern Italy.Other products (crops, meat, biogas, electricity) are also included in the assessment. The study was carried out by means of Material Flow Accounting, Cumulative Energy Demand, Emergy Accounting and Life Cycle Assessment methods. The final purpose was to analyze the effects induced by different mixes of inputs (feedstock, electricity, fertilizers) and outputs (crops, milk, meat, electricity) on the process performance. The evaluation was implemented beforeand afterthe installation of a photovoltaic power plant and a biogas digester coupled to a biogas-fueled electric generator. This study explores five alternative scenarios: Scenario 1. An intensive livestock farm, in which feedstock and electricity are purchased from outside and manure is sold or disposed of; Scenario 2. The real farm before the implementation of PV and biogas, using a fraction of self-produced feedstock and manure as fertilizer; Scenario 3. The same farm, after photovoltaic electricity implementation, to cover 100% of local demand; Scenario 4. The same farm, after installing a manure digester and an electric generator, to produce electricity from biogas (sold as additional product, while digestate is used as fertilizer); 5. A Polish dairy farm, producing crops, meat and milk for the market, using manure as fertilizer and no renewable energy appliances. Results show local and large-scale improvements in the transition from Scenario 1 to Scenario 2 (due to increased optimization driven by fodder self-reliance) as well as in the transition from Scenario 3 to Scenario 3 (due to electricity self-reliance). The transition from Scenario 3 to Scenario 4 shows the added value of additional biogasdriven electric generation, while Scenario 5 shows the advantage of optimized milk production due to pedigree breeding, pasture availability and sale of crops in addition to dairy products. Results suggest that several kinds of improvements are possible by acting on farm structure, renewable energy supply, and different mix of products. Results also confirm the effectiveness of a multicriteriamultiscale biophysical assessment method towards a better understanding of costs and benefits of production alternatives.