The link between operational efficiency and environmental impacts. A joint application of Life Cycle Assessment and Data Envelopment Analysis

A conceptual model for evaluating eco-efficiency of thermal spraying processes

Thermal spraying (TS) is one of the main processes for obtaining surfaces with the desired protective properties in various industrial applications. TS is an energy-intensive treatment required to heat the application material and consumes different resources. To assess the environmental impact of TS, it becomes necessary to integrate an approach that jointly analyses and evaluates the economic and environmental variables influencing the system. The concept of eco-efficiency (EE) added to the TS process allows for assessing the environmental and economic condition through the survey and application of eco-indicators. The lack of an EE evaluation model for TS processes was identified based on literature searches. Thus, the overall objective of this work is to propose a conceptual model to evaluate the EE of TS treatment, selecting environmental and economic indicators considered more impactful in the process. The model developed consists of three main steps: (i) the input and output indicators (environmental and economic) are identified by applying the Analytic Hierarchy Process (AHP) method; (ii) the structure to be employed in the model is defined; and (iii) the Data Envelopment Analysis (DEA) model is applied to define the EE evaluation form. The proposed model consists of clear and easy-to-follow steps for evaluating the EE of spraying processes, filling the gap found in the literature. The use of DEA allowed the integration of the environmental and economic indicators obtained from the TS processes to generate important insights for evaluating EE. The results prove the model's effectiveness in identifying the EE results for each analysed unit of the TS process. The model has provided an evaluation consistent with the existing studies, and the EE scores were assessed according to twenty-one decision-making units (DMUs) allowing the identification of the most eco-efficient DMUs concerning TS processes.

Decline or Rejuvenation? Efficiency Development of China’s National Scenic Areas

The decline is one of the essential issues for developing tourism destinations. The rapid adoption of appropriate policies will enable them to reverse the decline and enter the rejuvenation stage in time. This study advocated establishing an operational evaluation model of tourism efficiency with DEA and the super-SBM model to estimate when China’s mass tourism destinations are in decline and rejuvenation based on the tourism area life cycle (TALC) theory regarding China’s national scenic areas (NSAs) samples. The results show that the development of China’s mass tourism destinations can be divided into three phases, in which there is a clear process of persistent decline and rejuvenation. Different types of NSAs vary in terms of efficiency level and change trends. Human landscape, caves, and wetland and lakes all have distinct phases of persistent decline, but humanistic landscapes show a significant rejuvenation trend. These findings provide an innovative re-interpretation of the TALC model.

The Cradle-to-Cradle Life Cycle Assessment of Polyethylene terephthalate: Environmental Perspective

Over the last several years, the number of concepts and technologies enabling the production of environmentally friendly products (including materials, consumables, and services) has expanded. One of these ways is cradle-to-cradle (C2C) certified^TM. Life cycle assessment (LCA) technique is used to highlight the advantages of C2C and recycling as a method for reducing plastic pollution and fossil depletion by indicating the research limitations and gaps from an environmental perspective. Also, it estimates the resources requirements and focuses on sound products and processes. The C2C life cycle measurements for petroleum-based poly (ethylene terephthalate) (PET) bottles, with an emphasis on different end-of-life options for recycling, were taken for mainland China, in brief. It is considered that the product is manufactured through the extraction of crude oil into ethylene glycol and terephthalic acid. The CML analysis method was used in the LCIA for the selected midpoint impact categories. LCA of the product has shown a drastic aftermath in terms of environmental impacts and energy use. But the estimation of these consequences is always dependent on the system and boundary conditions that were evaluated throughout the study. The impacts that burden the environment are with the extraction of raw material, resin, and final product production. Minor influences occurred due to the waste recycling process. This suggests that waste degradation is the key process to reduce the environmental impacts of the production systems. Lowering a product’s environmental impact can be accomplished in a number of ways, including reducing the amount of materials used or choosing materials with a minimal environmental impact during manufacture processes.

Economic and Environmental Aspects of Agriculture in the EU Countries

The analysis of the economic efficiency of agriculture has been the subject of numerous studies. An economically efficient agricultural sector is not always environmentally efficient. Agriculture is a large emitter of greenhouse gases. The Intergovernmental Panel on Climate Change states that food production and agriculture are responsible for 21–37% of total global CO2 emissions. Due to the comprehensive assessment of the agricultural efficiency, it is worthwhile to apply to its measurement an integrated approach based on economic, energy and environmental aspects. These aspects were the main reasons for undertaking this research. The purpose of the study was to determine the economic, energy and environmental efficiency of agriculture in the EU Member States in 2019. The environmental analyses relate to the period 1990–2019. A total of 26 member states of the European Union (excluding Malta and Luxembourg) were selected for research. The sources of materials were Eurostat and the European Environmental Agency. This study was based on the Data Envelopment Analysis method, and used the DEA model focused on minimizing inputs. The research also adopts energy productivity and greenhouse gas emission efficiency indicators. The DEA model features the following variables: one effect (value of agricultural production) and four inputs (land, labour, use of fertilizers and use of energy). It was found that seven out of the 26 studied EU countries have efficient agriculture. The efficient agriculture group included The Netherlands, Denmark, Greece, Cyprus, the United Kingdom, Italy and Ireland. Based on the DEA method, benchmarks have been defined for countries with inefficient agriculture. On the basis of these benchmarks for inefficient agricultural sectors, it was possible to determine how they could improve efficiency to achieve the same results with fewer inputs. This issue is particularly important in the context of sustainable agricultural development. In the next stage of the research, the analysis of economic and energy efficiency was combined with the analysis of GHG emission efficiency in agriculture. Four groups of countries have been distinguished: eco-efficiency leaders, eco-efficiency followers, environmental slackers, eco-efficiency laggards. The leaders of the classification were The Netherlands, Italy, Greece, Cyprus and Portugal.

Eco-efficiency convergence and technology spillovers of European industries

European policies regarding global warming have been outspread the last few decades with many initiatives focusing on industrial production process. In this paper we model eco-efficiency (ECOE) performance under a metafrontier (MF) framework for 14 industries of the manufacturing sector from 27 European countries over the 1995-2011 period. The utilization of NO_x, SO_x, CO₂, CH₄, N₂O, CO, NMVOC and NH₃ as undesirable outputs represent the impact of industrial activities on the environment. In a first stage, we estimate eco-efficiency using a conventional Directional Distance Function (DDF) as well as a non-radial slack-based DDF (DDFS) approach. In the second stage of our analysis, we investigate the existence of conditional and unconditional convergence by employing several methodologies. Our results point out that heavy industries perform eco-inefficiently. In addition, our results support the non-convergence hypothesis and the creation of discrete clubs with uneven characteristics when the distributional dynamics approach and the recent approach of Phillips and Sul (PS) come into play. Finally, the establishment of a catch-up index indicate that technological spillovers do exist but with a small effect.

Impact of energy flow optimization on the mitigation of environmental consequences and costs in greenhouse cucumber production

Cucumber, as a major cultivated plant in Iran, takes up more than 80% of greenhouse production. So, improving the production efficiency can save energy, reduce the environmental consequences and production costs, and also create a lot of job opportunities. The present study aimed to investigate the impact of energy flow optimization on the environmental impacts and costs in greenhouse cucumber production by data envelopment analysis (DEA) and life cycle assessment (LCA) methods. For environmental assessment, human health damage, ecosystem damage, and resource scarcity were considered and analyzed in the form of 8, 12, and 2 impact categories, respectively, using the ReCiPe2016 (H) method on endpoint level. Required data were collected through questionnaire from 30 cucumber growers. The results of the current status of environmental impacts showed the major contribution of fuels (natural gas and diesel) in all three main impact categories. Based on DEA analysis, 19 greenhouses (63%) were identified as inefficient units with a mean efficiency score of 0.70 (TE = 0.7). The highest inefficiency was related to the manure (72%), electricity (71.7%), and fuel (59%), respectively. Electricity and manure showed the highest saving potential, while the highest contribution to total energy saving was related to fuel (87%). Environmental analysis of optimized greenhouses showed that efficient use of inputs can reduce all environmental impacts between 7 and 80%, which highlights the importance of efficient resource management in this study. Also, production costs were decreased by about 67 $ tonne^-1 (196 to 129 $) after the optimization of the units.

An integrated data envelopment analysis and life cycle assessment method for performance measurement in green construction management

The construction industry routinely extracts vast quantities of materials and releases deleterious pollutant emissions to the biosphere. In this study, we propose an integrated data envelopment analysis (DEA) and life cycle assessment (LCA) method to measure the performance of eco-friendly building materials in green construction management. Initially, we use the LCA method and environmental impact analysis to identify alternative green flooring systems and relevant sustainability criteria. We then use factor analysis to further evaluate these criteria and choose the most significant sustainability factors. Finally, a DEA model and a new enhanced Russell model (ERM) is proposed to measure the performance of the green flooring systems with factor analysis.

The joint use of life cycle assessment and data envelopment analysis methodologies for eco-efficiency assessment: A critical review, taxonomy and future research

Eco-efficiency has become a cornerstone for any company that seeks to improve their environmental and economic aspects. In this context, the joint use of Life Cycle Assessment and Data Envelopment Analysis, known as LCA + DEA methodology, is an emerging and growing line of research. LCA estimates the environmental impacts of the products or services, while DEA evaluates their efficiency, providing targets and benchmarks for the inefficient ones. In this way, both the environmental and economic aspects are considered in the eco-efficiency assessment. Since LCA + DEA methodology is a novel research line, a literature review is necessary to depict its full scope and to support researchers and practitioners. This manuscript presents the first comprehensive and structured literature review of the joint use of LCA and DEA for eco-efficiency assessment. We propose a taxonomy for the reviewed articles based on the theoretical and practical issues of LCA + DEA methodology and classify them accordingly. This classification allows recognizing and discussing the main findings, which offer some managerial implications for professionals who want to start employing this methodology. In addition, a procedure for selecting a suitable method is proposed and the main limitations and research opportunities are identified. Finally, this review could be a starting point and a guide for systematically building knowledge about the in the joint use of LCA and DEA for eco-efficiency assessment.

Identification of leading hazardous waste generating industries with high improvement potential in Spain

This paper employs Economic Input-Output Life Cycle Assessment and Data Envelopment Analysis to attribute total (direct and indirect) hazardous waste generation to the different industries and to connect total hazardous waste generation to the value added generated by each industry in Spain. In difference with previous studies we include all the industries of the economy and we focus on one specific type of environmental burden: the generation of hazardous waste. The results show that there is a very high concentration in total hazardous waste generation: only three industries accounted for almost 80% of total hazardous waste generation. This concentration also affects the type of hazardous waste generated. Thus, we find two main types of waste that account for 93% of total hazardous waste. Overall, the greatest hazardous waste generating industries are also the least efficient ones and exhibit a high improvement potential. Prevention measures directed to these industries should be implemented.

Sensitivity of operational and environmental benchmarks of retail stores to decision-makers' preferences through Data Envelopment Analysis

Within the framework of multi-criteria decision analysis (MCDA), weighting methods are typically used to capture decision-makers' preferences. In this regard, the increasing use of the combined LCA (Life Cycle Assessment) + DEA (Data Envelopment Analysis) methodology as an MCDA tool requires an in-depth analysis of how the preferences of decision-makers could affect the outcomes of LCA + DEA studies. This work revisits a case study of 30 retail stores/supply chains located in Spain by applying alternative weighted DEA approaches to evaluate the influence of decision-makers' preferences (weights) on the final outcomes, with a focus on efficiency scores and operational and environmental benchmarks. The ultimate goal is to effectively capture the view of stakeholders when applying LCA + DEA for the sound, sustainability-oriented management of multiple similar entities. Different weight vectors are separately applied to three types of DEA elements: operational inputs, time terms, and divisions. Besides, preferences from three alternative standpoints are considered: company manager through direct rating, and environmental policy-maker and local community through AHP (analytic hierarchy process). A significant influence on efficiency scores and sustainability benchmarks was found when weighting decision-makers' preferences on operational inputs. Additionally, a moderate influence was observed when weighting divisions according to a policy-maker or local community perspective. Although the results are case-specific, they lead to the general recommendation to enrich LCA + DEA studies by following not only an equal-weight approach but also approaches that include the preferences of the stakeholders effectively involved in the study.

Efficiency under different methods for incorporating undesirable outputs in an LCA+DEA framework: A case study of winter wheat production in Poland

Incorporating undesirable outputs in the operational assessments through the integration of Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) has received great attention recently. There are many studies throughout literature that apply various methods to integrate LCA and DEA. In this case study, the six most common approaches were employed to assess the winter wheat cropping system in Poland. These six methods were: a) ignoring undesirable outputs, b) treating undesirables as inputs to the DEA model, c) data transformation, d) impact rate, e) ratio model, and f) slack based measurement DEA with undesirable outputs. The environmental impact of wheat production was assessed by determining its carbon footprint (CF). The mean CF equalled 0.45 kg CO_2eq per kg wheat grain (ranging from 0.25 to 0.67). According to the model comparison results, a slack based measurement DEA with undesirable outputs could better reflect the performance of undesirable outputs, and was selected as the most appropriate method to maximize the efficiency of winter wheat production while minimizing undesirable outputs. The advantage of applying the slack based model with undesirable outputs was that the targets presented by this model were based on existing efficient farms, as opposed to theoretical results; thus achieving these targets are feasible. The average efficiency score equalled 0.43, whereby few farms were classified as efficient farms. The results of the proposed integrated model showed a high reduction potential for mineral fertilizers (up to 595 kg ha^-1 y^-1), seed (up to 37 kg ha^-1 y^-1), and fuel (up to 75 L ha^-1 y^-1) in winter wheat farms. These results help farmers to obtain a realistic and reliable usage pattern for inputs in a winter wheat production system, whereby the greatest production can be achieved in conjunction with the lowest possible environmental impact.

Eco-Efficiency in Measuring the Sustainable Production of Agricultural Crops

Agriculture is one of the main factors with a direct impact on the natural environment (soil, water and air). An increased interest in the environmental impact of agricultural production results is due to—among other factors—significant human interference in the natural circulation of nutrients, posing a potential threat to the balance of ecosystems. Under current conditions, it is necessary to develop comprehensive diagnostic methods to control production processes in a way that would reduce costs and environmental burden throughout the product’s life cycle. Only a holistic approach that integrates environmental and economic analysis meets the criteria of analysis complexity, which is one of the main goals of methodical analysis of sustainable development. The article presents the results of the integrated environmental and economic assessment of selected crops. Maize and rapeseed production were assessed using the life cycle assessment (LCA) and life cycle costing (LCC) methodologies. The analysis was carried out on farms representing plant- and animal-based farming types. The conclusion presented in the study was based on the data from a study group consisting of 69 private commercial farms located in two regions of Poland. The calculated carbon footprint of both of winter rape and grain maize production was found to be higher in animal farming types. Pig farming type presented the highest overall costs of these crops, based on the approach of the LCC. Inclusion of carbon sequestration to the assessment of greenhouse warming potential allowed for the reduction of the net global warming potential (GWP) impact associated with the production of the analyzed crops. In both crops, mineral fertilization was the main factor influencing both the total carbon footprint and the LCC.

Efficiency of materials management in the European Union

Purpose

The purpose of this paper is to measure and evaluate the efficiency of materials management in the European Union countries (EU-28) during the period of 2008–2017.

Design/methodology/approach

The study was conducted using the method of data envelopment analysis (DEA) and variables applied to determine the resource productivity indicator. Therefore, the components of domestic material consumption constituted inputs in the DEA method, while gross domestic product (GDP) was applied as an output.

Findings

The results of the analysis showed that the Netherlands, Luxembourg, Latvia and the UK are the efficiency leaders among all the member states of the European Union. One of the least efficient countries is Poland, which uses too much natural resources in the process of generating goods and services. However, this consumption is growing at a slower rate than the value of GDP, which is beneficial from the point of view of sustainable development. Poland, like other inefficient countries, should reduce its consumption of natural resources in line with the best international practices.

Practical implications

The obtained research results can be a valuable source of information for decision-makers, and contribute to the adoption of more effective policies in order to improve the relationship between materials consumption and economic growth.

Originality/value

The application of the DEA method for calculating the efficiency of materials management represents a new approach, and it is the first attempt of its kind in the European Union countries.

Eco-Efficiency Assessment of Intensive Rice Production in Japan: Joint Application of Life Cycle Assessment and Data Envelopment Analysis

To promote sustainable agriculture worldwide, it is important to understand what constitutes eco-efficiency for rice, a staple food in many countries. This study examined whether expanding the scale of rice farming contributed to the improved eco-efficiency of intensive rice production in Japan. Both life cycle assessment (LCA) and data envelopment analysis (DEA) were used to measure comprehensively the eco-efficiency of rice production. A DEA window analysis technique with two DEA inputs (global warming and eutrophication from the LCA results) and one DEA output (weight-based rice yield) was applied to the statistical data for 2005–2011 categorized by the size of rice farms. The results indicate that expanding the size of rice farms is an effective way of improving the eco-efficiency of intensive rice production in Japan. The important factors for improving eco-efficiency are the implementation of economies of scale, reduced outsourcing of farm work, and savings in chemical fertilizers and pesticides. Expansion of the size of rice farms through the recent abolition of the rice production adjustment program will also contribute to improving the eco-efficiency of Japanese rice production.

Sustainability-oriented management of retail stores through the combination of life cycle assessment and dynamic data envelopment analysis

A sound management of retail stores is a crucial aspect in the path towards a sustainable commercial sector, with a lack of research studies in the field of joint efficiency and sustainability assessment within this sector. In this sense, this work delves into the role of operational efficiency in the sustainability-oriented management of retail stores through the case study of 30 groceries in Spain over the period 2015-2017. With this purpose, and given the current knowledge gap in period-oriented sustainability benchmarking for management plans, for the first time a five-step methodological framework based on the combination of Life Cycle Assessment (LCA) and dynamic Data Envelopment Analysis (DEA) was proposed and applied to a case study within the service sector. The overall- and term-efficiency scores calculated through this method led to the general conclusion of a relatively good performance of the set of grocery stores over the evaluated period, which is associated with the centralised management strategy followed by the retail company. Furthermore, operational, socio-economic and environmental benchmarks were calculated as target values that could assist decision-makers at the retail company level in setting the path for a sustainable operation of the company's stores. Overall, the proposed period-oriented LCA + DEA method proved to be a feasible and valuable tool for sustainability management of retail stores, being preferred over the static (i.e., single term) alternative provided that time-series data are available at the company level.

Comparing two CF+DEA methods for assessing eco-efficiency from theoretical and practical points of view

Nowadays, sustainability has become of increasing concern in policy and the decision making of stakeholders. Companies have been increasing their attention to their environmental performance. In order to measure sustainability performance, different approaches have been proposed. The joint application of Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA), called LCA+DEA, is used to assess eco-efficiency, which is to produce more with less environmental impact and with fewer resources. In this manuscript, we compare two methods that implement the LCA+DEA approach, the five-step and four-step methods, focused on Carbon Footprint (CF), called CF+DEA. These methods have not been compared previously. This comparison will encompass the theoretical and practical points of view according to efficiency indices, best practices, and targets for the CF emissions. To perform this comparison, we use a case study of raspberry producers in Chile. From a practical point of view, we have observed that both methods have achieved the main objective of reducing CF. Moreover, results show similar eco-efficiency scores; the targets given by the five-step method are less demanding than those given by the four-step method. In this sense, the four-step method provides a higher average CF reduction. This is due to the inclusion of CF as an undesirable output in the DEA assessment and the use of an output-oriented DEA model. Additionally, in including the CF within the DEA assessment, the four-step method reflects better the definition of eco-efficiency. Following these results, it is advisable to implement the targets provided by the five-step method for a short term and then the targets provided by the four-step method for a mid-term or long term.

Eco-Efficiency Evaluation of Agricultural Production in the EU-28

This paper evaluates the eco-efficiency performance of agriculture at the sector level using the joint application of life cycle assessment (LCA) and data envelopment analysis (DEA) techniques. The research has been performed for the agricultural production of the 28 member states of the European Union (the EU-28). The foundation for the calculation of the eco-efficiency performance was a statistically selected set of impact categories derived from the life cycle impact assessment (LCIA) phase as input values and economic indicators, with the gross domestic product (GDP) of their agriculture as the output value. The results of the analysis showed that the agricultural sectors of 10 member states of the European Union (i.e., Belgium, Bulgaria, Estonia, Finland, Greece, Italy, Malta, the Netherlands, Romania, and Sweden) are relatively eco-efficient. The remaining 18 member states of the EU-28 have eco-inefficient agricultural sectors, though to a varying extent. This means that their agricultural sectors consume too many natural resources (in particular, energy), use too much fertilizer, and produce considerable amounts of airborne emissions in relation to the current level of GDP per hectare. These insights into the eco-efficiency performance of agriculture in the EU-28 may contribute to the adoption of better management techniques and more effective agricultural policies.

Expansion of environmental impact assessment for eco-efficiency evaluation of China's economic sectors: An economic input-output based frontier approach

Due to the increasing environmental burdens caused by dramatic economic expansion, eco-efficiency indicating how efficient the economic activity is with respect to its environmental impacts has become a topic of considerable interest in China. In this context, Economic Input-output Life Cycle Assessment (EIO-LCA) and Data Envelopment Analysis (DEA) are combined to assess the environmental impacts and eco-efficiency of China's 26 economic sectors. The EIO-LCA results indicate that Electricity Production and Supply sector is the largest net exporter in energy usage, CO₂ emission and exhaust emission categories, while Construction sector is the largest net importer for five impact categories except for water withdrawal. Moreover, Construction sector is found to be the destination of the largest sector-to-sector environmental impact flows for the five impact categories and make the most contributions to the total environmental impacts. Another key finding is that Agriculture sector is both the largest net exporter and the greatest contributor for water withdrawal category. DEA results indicate that seven sectors are eco-efficient while over 70% of China's economic sectors are inefficient and require significant improvements. The average target improvements range between 23.30% and 35.06% depending on the impact category. Further sensitivity analysis reveals that the average sensitivity ratios vary from 7.7% to 15.7% among the six impact categories, which are found to be negatively correlated with their improvement potentials. Finally, several policy recommendations are made to mitigate environmental impacts of China's economic sectors and improve their eco-efficiency levels.

Environmental impact efficiency of natural gas combined cycle power plants: A combined life cycle assessment and dynamic data envelopment analysis approach

The energy sector is still dominated by the use of fossil resources. In particular, natural gas represents the third most consumed resource, being a significant source of electricity in many countries. Since electricity production in natural gas combined cycle (NGCC) plants provides some benefits with respect to other non-renewable technologies, it is often seen as a transitional solution towards a future low‑carbon power generation system. However, given the environmental profile and operational variability of NGCC power plants, their eco-efficiency assessment is required. In this respect, this article uses a novel combined Life Cycle Assessment (LCA) and dynamic Data Envelopment Analysis (DEA) approach in order to estimate -over the period 2010-2015- the environmental impact efficiencies of 20 NGCC power plants located in Spain. A three-step LCA+DEA method is applied, which involves data acquisition, calculation of environmental impacts through LCA, and the novel estimation of environmental impact efficiency (overall- and term-efficiency scores) through dynamic DEA. Although only 1 out of 20 NGCC power plants is found to be environmentally efficient, all plants show a relatively good environmental performance with overall eco-efficiency scores above 60%. Regarding individual periods, 2011 was -on average- the year with the highest environmental impact efficiency (95%), accounting for 5 efficient NGCC plants. In this respect, a link between high number of operating hours and high environmental impact efficiency is observed. Finally, preliminary environmental benchmarks are presented as an additional outcome in order to further support decision-makers in the path towards eco-efficiency in NGCC power plants.

Joint carbon footprint assessment and data envelopment analysis for the reduction of greenhouse gas emissions in agriculture production

Operations management tools are critical in the process of evaluating and implementing action towards a low carbon production. Currently, a sustainable production implies both an efficient resource use and the obligation to meet targets for reducing greenhouse gas (GHG) emissions. The carbon footprint (CF) tool allows estimating the overall amount of GHG emissions associated with a product or activity throughout its life cycle. In this paper, we propose a four-step method for a joint use of CF assessment and Data Envelopment Analysis (DEA). Following the eco-efficiency definition, which is the delivery of goods using fewer resources and with decreasing environmental impact, we use an output oriented DEA model to maximize production and reduce CF, taking into account simultaneously the economic and ecological perspectives. In another step, we stablish targets for the contributing CF factors in order to achieve CF reduction. The proposed method was applied to assess the eco-efficiency of five organic blueberry orchards throughout three growing seasons. The results show that this method is a practical tool for determining eco-efficiency and reducing GHG emissions.

Eco-efficiency assessment of farm-scaled biogas plants

The aim of this study was to analyse the eco-efficiency of 15 agricultural biogas plants located in Northern Italy. For this, the combination of life cycle assessment (LCA) and data envelopment analysis (DEA) methodologies was considered with the purpose of identifying efficient operational plants and proposing improvement measures for the inefficient ones. The environmental profile of both the original and the virtual plants (obtained after the improvement measures) were compared in order to identify the net environmental gains linked with the inputs reduction. As a result of improvement measures, the production of electricity from biogas in all plants would imply environmental benefits compared with the average electricity production in the Italian grid. In light of the results obtained, special attention should be paid to the feedstock selection since it has a key role in the overall eco-efficiency of the plant, due to their different origin and composition.

Environmental challenges of the chlor-alkali production: Seeking answers from a life cycle approach

Life Cycle Assessment (LCA) has been used to assess the environmental sustainability of the chlor-alkali production in Europe. The three current technologies applied nowadays are mercury, diaphragm, and membrane cell technology. Despite, having achieved higher energy efficiencies since the introduction of membrane technology, energy consumption is still one of the most important issues in this sector. An emerging technology namely oxygen-depolarised cathodes (ODC) is suggested as a promising approach for reducing the electrolysis energy demand. However, its requirement of pure oxygen and the lack of production of hydrogen, which could otherwise be valorised, are controversial features for greener chlorine production. The aim of this work is to evaluate and compare the environmental profiles of the current and emerging technologies for chlorine production and to identify the main hot spots of the process. Salt mining, brine preparation, electrolysis technology and products treatment are included inside the system boundaries. Twelve environmental impact categories grouped into natural resources usage and environmental burdens are assessed from cradle to gate and further normalised and weighted. Furthermore, hydrogen valorisation, current density and allocation procedure are subjected to sensitivity analysis. Results show that the electrolysis stage is the main contributor to the environmental impacts due to energy consumption, causing 99.5-72% of these impacts. Mercury is the less environmentally sustainable technology, closely followed by diaphragm. This difference becomes bigger after normalisation, owing to hazardous waste generated by mercury technique. Conversely, best results are obtained for ODC instead of membrane scenario, although the reduction in energy requirements is lesser than expected (7%).

Review of life-cycle approaches coupled with data envelopment analysis: launching the CFP + DEA method for energy policy making

Life-cycle (LC) approaches play a significant role in energy policy making to determine the environmental impacts associated with the choice of energy source. Data envelopment analysis (DEA) can be combined with LC approaches to provide quantitative benchmarks that orientate the performance of energy systems towards environmental sustainability, with different implications depending on the selected LC + DEA method. The present paper examines currently available LC + DEA methods and develops a novel method combining carbon footprinting (CFP) and DEA. Thus, the CFP + DEA method is proposed, a five-step structure including data collection for multiple homogenous entities, calculation of target operating points, evaluation of current and target carbon footprints, and result interpretation. As the current context for energy policy implies an anthropocentric perspective with focus on the global warming impact of energy systems, the CFP + DEA method is foreseen to be the most consistent LC + DEA approach to provide benchmarks for energy policy making. The fact that this method relies on the definition of operating points with optimised resource intensity helps to moderate the concerns about the omission of other environmental impacts. Moreover, the CFP + DEA method benefits from CFP specifications in terms of flexibility, understanding, and reporting.

Benchmarking environmental and operational parameters through eco-efficiency criteria for dairy farms

Life Cycle Assessment (LCA) is often used for the environmental evaluation of agri-food systems due to its holistic perspective. In particular, the assessment of milk production at farm level requires the evaluation of multiple dairy farms to guarantee the representativeness of the study when a regional perspective is adopted. This article shows the joint implementation of LCA and Data Envelopment Analysis (DEA) in order to avoid the formulation of an average farm, therefore preventing standard deviations associated with the use of average inventory data while attaining the characterization and benchmarking of the operational and environmental performance of dairy farms. Within this framework, 72 farms located in Galicia (NW Spain) were subject to an LCA+DEA study which led to identify those farms with an efficient operation. Furthermore, target input consumption levels were benchmarked for each inefficient farm, and the corresponding target environmental impacts were calculated so that eco-efficiency criteria were verified. Thus, average reductions of up to 38% were found for input consumption levels, leading to impact reductions above 20% for every environmental impact category. Finally, the economic savings arising from efficient farming practices were also estimated. Economic savings of up to 0.13€ per liter of raw milk were calculated, which means extra profits of up to 40% of the final raw milk price.

Assessing farming eco-efficiency: a Data Envelopment Analysis approach

This paper assesses farming eco-efficiency using Data Envelopment Analysis (DEA) techniques. Eco-efficiency scores at both farm and environmental pressure-specific levels are computed for a sample of Spanish farmers operating in the rain-fed agricultural system of Campos County. The determinants of eco-efficiency are then studied using truncated regression and bootstrapping techniques. We contribute to previous literature in this field of research by including information on slacks in the assessment of the potential environmental pressure reductions in a DEA framework. Our results reveal that farmers are quite eco-inefficient, with very few differences emerging among specific environmental pressures. Moreover, eco-inefficiency is closely related to technical inefficiencies in the management of inputs. Regarding the determinants of eco-efficiency, farmers benefiting from agri-environmental programs as well as those with university education are found to be more eco-efficient. Concerning the policy implications of these results, public expenditure in agricultural extension and farmer training could be of some help to promote integration between farming and the environment. Furthermore, Common Agricultural Policy agri-environmental programs are an effective policy to improve eco-efficiency, although some doubts arise regarding their cost-benefit balance.

Further potentials in the joint implementation of life cycle assessment and data envelopment analysis

The combined application of Life Cycle Assessment and Data Envelopment Analysis has been recently proposed to provide a tool for the comprehensive assessment of the environmental and operational performance of multiple similar entities. Among the acknowledged advantages of LCA+DEA methodology, eco-efficiency verification and avoidance of average inventories are usually highlighted. However, given the novelty of LCA+DEA methods, a high number of additional potentials remain unexplored. In this sense, there are some features that are worth detailing given their wide interest to enhance LCA performance. Emphasis is laid on the improved interpretation of LCA results through the complementary use of DEA with respect to: (i) super-efficiency analysis to facilitate the selection of reference performers, (ii) inter- and intra-assessments of multiple data sets within any specific sector with benchmarking and trend analysis purposes, (iii) integration of an economic dimension in order to enrich sustainability assessments, and (iv) window analysis to evaluate environmental impact efficiency over a certain period of time. Furthermore, the capability of LCA+DEA methodology to be generally implemented in a wide range of scenarios is discussed. These further potentials are explained and demonstrated via the presentation of brief case studies based on real data sets.

Mitigating secondary aerosol generation potentials from biofuel use in the energy sector

This paper demonstrates secondary aerosol generation potential of biofuel use in the energy sector from the photochemical interactions of precursor gases on a life cycle basis. The paper is divided into two parts-first, employing life cycle analysis (LCA) to evaluate the extent of the problem for a typical biofuel based electricity production system using five baseline scenarios; second, proposing adequate mitigation options to minimise the secondary aerosol generation potential on a life cycle basis. The baseline scenarios cover representative technologies for 2010 utilising energy crop (miscanthus), short rotation coppiced chips and residual/waste wood in different proportions. The proposed mitigation options include three approaches-biomass gasification prior to combustion, delaying the harvest of biomass, and increasing the geographical distance between the biomass plant and the harvest site (by importing the biofuels). Preliminary results indicate that the baseline scenarios (assuming all the biomass is sourced locally) bear significant secondary aerosol formation potential on a life cycle basis from photochemical neutralisation of acidic emissions (hydrogen chloride and sulphur dioxide) with ammonia. Our results suggest that gasification of miscanthus biomass would provide the best option by minimising the acidic emissions from the combustion plant whereas the other two options of delaying the harvest or importing biofuels from elsewhere would only lead to marginal reduction in the life cycle aerosol loadings of the systems.

A quantitative integrated assessment of pollution prevention achieved by integrated pollution prevention control licensing

This paper presents an innovative, quantitative assessment of pollution avoidance attributable to environmental regulation enforced through integrated licensing, using Ireland's pharmaceutical-manufacturing sector as a case study. Emissions data reported by pharmaceutical installations were aggregated into a pollution trend using an Environmental Emissions Index (EEI) based on Lifecycle Assessment methodologies. Complete sectoral emissions data from 2001 to 2007 were extrapolated back to 1995, based on available data. Production volume data were used to derive a sectoral production index, and determine 'no-improvement' emission trends, whilst questionnaire responses from 20 industry representatives were used to quantify the contribution of integrated licensing to emission avoidance relative to these trends. Between 2001 and 2007, there was a 40% absolute reduction in direct pollution from 27 core installations, and 45% pollution avoidance relative to hypothetical 'no-improvement' pollution. It was estimated that environmental regulation avoided 20% of 'no-improvement' pollution, in addition to 25% avoidance under business-as-usual. For specific emissions, avoidance ranged from 14% and 30 kt a(-1) for CO(2) to 88% and 598 t a(-1) for SO(x). Between 1995 and 2007, there was a 59% absolute reduction in direct pollution, and 76% pollution avoidance. Pollution avoidance was dominated by reductions in emissions of VOCs, SO(x) and NO(x) to air, and emissions of heavy metals to water. Pollution avoidance of 35% was attributed to integrated licensing, ranging from between 8% and 2.9 t a(-1) for phosphorus emissions to water to 49% and 3143 t a(-1) for SO(x) emissions to air. Environmental regulation enforced through integrated licensing has been the major driver of substantial pollution avoidance achieved by Ireland's pharmaceutical sector - through emission limit values associated with Best Available Techniques, emissions monitoring and reporting requirements, and performance targets specified in environmental management plans. This compliant sector offers a positive, but not necessarily typical, case study of IPPC effectiveness.