Environmental Key Performance Indicators Research Articles

A solution approach for decision-making on vessel fleet sustainability focusing on alternative fuels in a life-cycle basis

International Maritime Organization has launched a set of different regulatory frameworks focusing on maritime pollution prevention mechanisms and practicing different solution approaches. A multi-dimensional life-cycle analysis on vessels and maritime fuels (fossil & alternative low carbon fuels) can make an important contribution to the IMO's long-term carbon neutrality target for 2050. A typical vessel's operational profile contributes on approx. 80% of greenhouse gas emissions and 50% of total costs respectively during its lifetime. Therefore, the investigation of ships operational benchmarks following a lifecycle analysis approach could create suitable decision-making support tools for different optimization problems regarding alternative green fuels. This paper proposes a solution approach to evaluate current vessel fleet operational benchmarks for different ship categories and provide a decision-making support mechanism to tackle important operational problems during ship's lifetime. The proposed approach contains an evaluation mechanism to determine the suitable economic and environmental key performance indicators necessary to properly evaluate the multi-dimensional sustainability of the examined case studies with respect to the IMO (MARPOL) environmental regulations.

Key Performance Indicators: their use in the energy efficiency retrofit for historic buildings

Energy efficiency in the built environment is gaining ground due to policies to mitigate climate change impact. This contribution focuses on investigating the role of Key Performance Indicators (KPIs) that can be useful for the energy retrofit of historic buildings. The KPIs were hinged upon PESTEL domains (Political, Economic, Social, Technological, Environmental, and Legislative) in order to define objective and measurable criteria that allow for a comprehensive evaluation of an energy retrofit performance. A literature review carried out through the PRISMA flow chart allowed to select 59 papers, subsequently analyzed to investigate the occurrences of the selected KPIs. The findings showed that the political domain is the less considered, differently from the legislative one, whose KPI highlighted the importance of being compliant with regulations. The domains representing economic, social, technological, and environmental KPIs are mostly present together in the scientific literature, underlining the importance of a holistic and multidisciplinary approach. Future research should be oriented towards delineation of best practices to meet sustainability and conservation needs, and to better integrate current policies and international requirements.

Exploring the potential of scaling up Smart Local Energy Systems to transform clusters of housing: Insights from a case study in Wales, UK

The research investigates the potential of Smart Local Energy Systems (SLES) to transform existing small clusters of housing into aggregates of prosumers capable of sharing locally generated renewable energy in SLES located in the Swansea area, South Wales, UK. The performance of 3 SLES retrofit scenarios is compared and evaluated at a household and cluster scale. The Energy Plus software within the DesignBuilder interface is used to carry out the modelling. Results show that SLES retrofit measures at a cluster scale are advantageous in terms of economic and environmental Key Performance Indicators (KPIs). The modelling also showed that replacing photovoltaic panels with a wind turbine in a small cluster of homes in rural Wales, UK offers no benefit in terms of renewable energy generation, carbon emissions or income. Overall, this research offers insights into the potential of SLES in retrofitting small housing clusters into low-carbon aggregates, emphasising the role of PV panels as a renewable electricity source.

Optimizing mixed-use district designs in hot climates: A two-phase computational workflow for energy balance and environmental performance

While mixed-use developments remain one of the preferable strategies for sustainable urbanism, there is a need for design-integrated methods to determine the performative impacts of mixed-use and mixed-building forms. This paper presents a computational method for optimizing the energy balance of mixed-use districts in hot climates. Its methodology includes an energy parametric analysis and a correlation study that introduces the Solar Cover Factor (SCF), a solar-driven metric for predicting energy balance in mixed-use configurations. Three studies involving multi-objective optimization incorporate the SCF and the context exposure index. In a second phase of analysis, the optimization results are evaluated and compared to a uniform design using a series of environmental key performance indicators. Results indicate that diverse designs have the potential for up to twice the energy balance and that all the best-performing solutions exhibit a high diversity factor. The results demonstrated the high potential of the SCF metric to account for energy tradeoffs in the optimization of mixed-use districts. The two-phase optimization sequence offers a new hierarchy between automated and interactive analytical workflows for zero-energy performance and livable districts, which can be used to address other environmental challenges in future applications for sustainable urban development where multiple performance indicators interact.

Multi-objective economic and environmental assessment for the preliminary design of CO2 transport pipelines

A methodology based on the multi-objective optimisation of economic and environmental aspects is presented to support the preliminary design of CO2 transport pipelines employed as part of Carbon Capture and Storage (CCS) systems. Pareto optimal design solutions are determined for a realistic point-to-point CO2 pipeline using Level Diagrams and choosing the Nominal Pipe Size (NPS) as a decision variable. A quantitative procedure entailing the definition of economic and environmental key performance indicators is defined to allow the identification of an optimum pipeline design. The outcome is compared against the minimisation of single-objective indicators based on the CO2 avoided and carbon pricing concepts. The results of a case-study concerning a 70 km long pipeline transporting 10 Mt yr−1 of supercritical CO2 show that the multi-objective method yields an optimum NPS equal to 30, higher than the NPS 28 deriving from the alternative indexing methods. The proposed multicriteria approach effectively considers case-specific environmental sustainability constraints, which result in determining 46% of the overall performance measure of the identified optimum solution. The results show that conventional single-objective methods underestimate the contribution of environmental factors up to 2.6% of the overall performance index value. A Monte Carlo probabilistic analysis is performed to verify the robustness of the results with respect to the possible uncertainties.

Comprehensive Low Voltage Microgrid Planning Methodology for Rural Electrification

Recently, DC-powered devices such as loads (USB plugs, chargers, LED lighting) and distributed energy resources (solar photovoltaic and battery energy storage) have been increasingly used. Therefore, their connection to the grid requires AC/DC converters, which raises the question of operating part of the grid in DC in order to connect DC loads to DC producers and storage. In Cambodia, the electrification rate is only about 82% of the population in 2021 in rural areas. The objective of this work is to propose a low voltage microgrid comprehensive planning tool for electrification of developing countries. From the data collected on consumption needs, the objective is to find the optimal electrification scheme, i.e., AC or AC/DC distribution, optimal topology and distributed energy resources allocation and operation for both grid-connected and off-grid mode. A set of technical, economic, and environmental key performance indicators allows for comparison of solutions. The interest and efficiency of such a tool are illustrated on a real case study, an island area. Moreover, uncertainties on load consumption are also considered to assess the sensitivity and robustness of the proposed algorithm. The results show that, although the overall cost of the hybrid AC/DC microgrid is slightly higher than that of the AC microgrid, it allows a gradual electrification avoiding large initial investments.

DSF Core: Integrated Decision Support for Optimal Scheduling of Lifetime Extension Strategies for Industrial Equipment.

This paper proposes a generic algorithm for industries with degrading and/or failing equipment with significant consequences. Based on the specifications and the real-time status of the production line, the algorithm provides decision support to machinery operators and manufacturers about the appropriate lifetime extension strategies to apply, the optimal time-frame for the implementation of each and the relevant machine components. The relevant recommendations of the algorithm are selected by comparing smartly chosen alternatives after simulation-based life cycle evaluation of Key Performance Indicators (KPIs), considering the short-term and long-term impact of decisions on these economic and environmental KPIs. This algorithm requires various inputs, some of which may be calculated by third-party algorithms, so it may be viewed as the ultimate algorithm of an overall Decision Support Framework (DSF). Thus, it is called "DSF Core". The algorithm was applied successfully to three heterogeneous industrial pilots. The results indicate that compared to the lightest possible corrective strategy application policy, following the optimal preventive strategy application policy proposed by this algorithm can reduce the KPI penalties due to stops (i.e., failures and strategies) and production inefficiency by 30-40%.

The chip manufacturing industry: Environmental impacts and eco-efficiency analysis

Semiconductor manufacturing has followed the fate of a large part of industrial production: many companies, around the world, have maintained higher functions (design and engineering) and outsourced other production stages to third-party manufacturers, located mostly in Asia. Some chip companies have thus become “fabless” firms, commissioning the “fabrication” of their product to wafer “foundries” or “fabs”. For the first time, in this paper, by calculating and subsequently analyzing various key environmental performance indicators (KEPIs) from the data of the fabs Corporate Social Responsibility (CSR) reports, the environmental impacts and the eco-efficiency of the world's leading semiconductor foundries are analyzed and assessed. The aim is to highlight the relations between company size, technological capacity and environmental impact. A preliminary homogenization was necessary to process the company original data and indicators, often related to different units of production, and to obtain raw data in absolute value. Subsequently, adopting a single common manufacturing index (MI), it was possible to obtain and use new comparable performance indicators and KEPIs. The consequent comparative assessment allowed to give a reliable overall picture of the current resource consumption and pollution of this highly strategic sector, highlighting its next heavy environmental challenges. The result, in fact, is that, differently to what happens in many other sectors, in the semiconductor industry, larger company size (higher revenue), higher value added per wafer produced (higher revenue/MI), and higher technological capacity (higher R&D expenses and smaller technology node) are not always related to lower quantities (per unit of production) of water, energy, waste, wastewater and GHG emissions. It is hoped that, for the future, foundry firms, especially those with the most advanced technologies, will invest much more to optimize their resource use and to further reduce GHGs emissions and waste generation.

Transforming Old Cities into Smart Cities Using Environmental Key Performance Indicators to Solve Environmental Problems

Recently, smart city has become a tool for linking the sustainability dimensions with information and communication technology to enhance the quality of life. The current research problem lies in the increase in migration rates from the countryside and adjacent villages to the urban cities which may lead to an increase in environmental problems. Hence, the transformation of existing cities into smart cities has become an urgent need requiring immediate action or attention for achieving the Sustainable Development Goals (SDG) and effectively dealing with urban and environmental problems, particularly in developing countries. Therefore, the research adopts the environmental key performance indicators KPI of the smart sustainable cities (SSC) which was identified by the International Telecommunication Union (ITU) to examine the performance of the East Mansoura District city as a case study. To achieve the aim of this study, a set of core environmental indicators was adopted to measure and evaluate the current status of the selected case study. Finally, an action plan was proposed to transform East Mansoura District city into a smart sustainable city. This may pave the way for other cities in Egypt and developing countries.

Improving the Sustainability and Profitability of Oat and Garlic Crops in a Mediterranean Agro-Ecosystem under Water-Scarce Conditions

In areas with scarce water resources, population growth and climate change scenarios will mean that there is increasingly less water available for agricultural activity. Thus, optimizing crop irrigation water management is an absolute necessity. To address this situation, the SUPROMED project (sustainable production in water-limited environments of Mediterranean agro-ecosystems), available in an online platform, brings together a series of models and methodologies designed to promote more efficient management of water, energy and fertilizers. A two-year trial (2020–2021) was implemented in the Castilla-La Mancha region (Spain), with the aim of showing the effectiveness of SUPROMED as a farm management support tool. The trial was conducted on two of the region’s most important crops (oats and garlic). A series of productive, economic, and environmental key performance indicators (KPIs) were analyzed to measure the impact of transferring MOPECO (model for the economic optimization of irrigation water use at farm level), the irrigation scheduling model integrated in the SUPROMED platform, to farmers. In 2020, the management plan proposed by SUPROMED achieved a higher yield for oat than that generated by traditional management, using 40% less water. In the case of garlic, the same yield was obtained, using 30% less water. Gross margin and gross economic irrigation water productivity were improved for both crops. In 2021, one of the selected farmers was trained to use the SUPROMED platform to work with garlic crop. This management improved most of the KPIs analyzed compared to previous management without the SUPROMED platform, obtaining similar results to those obtained by SUPROMED in 2020. The results demonstrate that the tools and models included in SUPROMED have been properly adapted and can be easily used by farmers, improving the economic and environmental sustainability of Mediterranean agroecosystems.

Sustainable Production of Barley in a Water-Scarce Mediterranean Agroecosystem

Scarcity of water resources is one of the main constraints on agricultural activity in arid and semi-arid areas. Despite the great technological development over recent decades, farmers are demanding methodologies and tools adapted to their training, management restrictions, and economic capacity. To tackle these challenges, the sustainable production in water-limited environments of Mediterranean agroecosystems (SUPROMED) project combines, in an online platform, a set of models and methodologies for more efficient management of water, energy, and fertilizers. A two-year trial (2020–2021) was conducted in the Castilla-La Mancha region (Spain) to demonstrate, for a barley crop, the effectiveness of SUPROMED as a farm management support tool. The impact of transferring the model for the economic optimization of irrigation water use at farm level (MOPECO model) irrigation scheduling among other methods and tools, integrated in the SUPROMED platform, to farmers was determined by analyzing a set of productive, economic, and environmental key performance indicators (KPIs). The KPIs were selected to show farmers how the efficient use of productive factors could improve the profitability of their farms, thus reducing the impact of agriculture on the environment. In 2020, the management plan proposed by SUPROMED achieved the same yield as traditional management using 32% less water and resulting in a 13% and 66% improvement in gross margin and gross economic irrigation water productivity, respectively. In 2021, the management implemented by a farmer trained in the use of the tools and methodologies in the SUPROMED platform showed improvements in most of the KPIs analyzed, achieving similar results to those obtained by SUPROMED during 2020. The results are promising, indicating that the tools and models proposed in SUPROMED can be easily used by farmers and can improve the economic and environmental sustainability of Mediterranean agroecosystems. The involvement of public administrations, together with local researchers and technicians, is required for the effective promotion and use of these methodologies by the productive sector.

An Assessment of the Key Performance Indicators (KPIs) of Energy Efficient Retrofits to Existing Residential Buildings

Quantifying the wider benefits of energy efficient building retrofits is crucial to incentivise householder retrofit investments. This research recognises the value of key performance indicators (KPIs) for assessing and demonstrating retrofitting benefits and provides an assessment of KPIs for evaluating retrofits. An integrated framework for evaluating retrofits using a set of economic, social, and environmental KPIs is proposed. This KPI framework is then applied in a pre- and post-retrofit assessment of five case study dwellings located in Ireland, revealing its usefulness in demonstrating the wider benefits of retrofitting to householders, with a view to driving retrofit investment. Three of these case study dwellings had state-of-the-art retrofit technologies installed as part of the works, including heat pumps and solar PV systems. In addition to demonstrating the wider benefits of retrofitting, the framework allowed for the identification of potential causes for differences in performance of these technologies across households, as well as patterns of underperformance. Such insights are useful for the future design of these technologies and retrofit packages, as well as policy measures, which support householders in the adoption and use of these measures. The results demonstrate that householders experience various benefits from retrofitting. Showcasing the different benefits that householders receive from retrofitting, and their satisfaction with the retrofit works, can serve to de-risk retrofit investments, and inspire others to seek similar benefits through retrofitting. Applying the developed framework to a larger, comparable sample size, can distinguish the retrofit packages, which perform best across the KPIs and various household profiles. Furthermore, the application of the developed framework can serve as an evidence base for retrofit designers, contractors, and policy makers in the design of retrofit packages and policy measures that will maximise the benefit for householders.

Analysis of Life Cycle Environmental Impacts of Using Enogen Corn in Beef Cattle Rations.

Simple SummaryThis study presents a comparative lifecycle assessment of the environmental performance of Enogen® corn as an ingredient in beef rations. We show that the reductions in environmental impact per unit of live weight gain are approximately 5% across four primary impact categories: climate change, embedded energy, land use, and water use. These conclusions are robust under a series of evaluations considering different phases of the supply chain.Agricultural production systems have been identified as significant sources of anthropogenic impacts across several environmental key performance indicators (KPIs). Livestock husbandry is growing in global importance as the demand for high-quality protein continues to increase. It is therefore imperative to have sustainable intensification technologies, and we describe one such technology. The purpose of this study was to evaluate the performance of Enogen® corn grain compared to conventional feed corn when used as an ingredient in backgrounding and feed yard beef rations using life cycle assessment. The project was conducted in compliance with ISO standards, including a third-party panel review. A series of scenarios were analyzed to evaluate the impacts of boundaries and functional units on the outcomes. The use of Enogen corn as a feed component in beef production showed a quantifiable benefit in terms of the sustainability metrics of primary interest in this study. The gate-to-gate improvements at the feed yard and backgrounding based on full field trial datasets from field trials conducted at Kansas State University and at the University of Nebraska, Lincoln showed 3.4 and 5.8 percent reductions in Global Warming Potential, respectively. It is particularly noteworthy that the improvement in feed conversion ratio at the feed yard results in approximately 6 percent improvement in the four key environmental performance metrics of beef production, which demonstrates potential for the sector to meet its sustainability targets.

Selection of second-generation crop for biodiesel extraction and testing its impact with nano additives on diesel engine performance and emissions

The scope of this study was twofold: to define the most suitable Egypt's biodiesel source, and to assess the impact of this biodiesel source with the addition of carbon nano additives on diesel engine performance and emissions. Environmental Key Performance Indicators were used as metrics to identify the appropriate biodiesel source with respect to several criteria including environmental, economic, ecological, and demographic situation. The most suitable Egypt's biodiesel source was identified from different sources including algae, Jatropha, coffee waste, rice straw, sugarcane, and switchgrass. Then, the production process of biodiesel from this renewable source by transesterification was carried out using chemical catalyst or biocatalyst. Following this, this source's impact with carbon nano additives on the performance and emissions of a 0.825-L single-cylinder diesel engine was further examined at engine loads varying between 0 and 4 kW and 1500 rpm constant engine speed. The carbon nano additives were added at a different mass fractions of 25, 50 and 100 ppm to Jatropha biodiesel and diesel blend (20 % jatropha biodiesel+ 80 % diesel) by volume. The results showed Jatropha as the most efficient biodiesel source among all the tested fuels to be produced in Egypt. Furthermore, the experimental engine test results revealed that Jatropha biodiesel without and with carbon nano additives consistently has a higher brake thermal efficiency and lower brake specific fuel consumption in comparison to that of diesel fuel. Likewise, Jatropha biodiesel without and with carbon nano additives enhanced the engine performance and consequently reduced the exhaust emissions including CO, CO2, HC, NOx, and smoke in comparison to that of diesel fuel.

Environmental key performance indicators: the role of regulations and stakeholder influence

Environmental protection is of vital importance and needs to be considered in the context of business strategies, including companies’ reporting decisions. This paper aims to investigate the importance of stakeholders for environmental key performance indicators (KPIs) and the significance of different types of environmental KPIs to various stakeholders. The study is based on a content analysis of the disclosures provided by large public interest companies operating in Poland. The data were processed to produce descriptive statistics as well as classification and regression trees (C&RTs). According to the study results, the sample companies provide a variety of environmental indicators, with a total of 735 KPIs identified. The research confirms the importance of stakeholders interested in environmental issues for corporate decisions regarding environmental KPI disclosure. The study contributes to the extant literature by providing new insights into the importance of different stakeholder groups for the disclosure of environmental KPIs. It may serve as an incentive for standard setters and practitioners to take a proactive approach in further developing and improving environment-related reporting regulations.

Coupling landscape-scale diagnostics surveys, on-farm experiments, and simulation to identify entry points for sustainably closing rice yield gaps in Nepal

CONTEXTRice is the primary staple food crop in Nepal, contributing 20% of the agricultural gross domestic product and more than 50% of the total calories in the national diet. Nevertheless, the productivity of rice (3.36 t ha−1) is the lowest in South Asia region. OBJECTIVEThe objective of this study was to employ a mixed-methods approach to characterize and decompose yield gaps (YGs) in the context of identifying sustainable intensification pathways for rice production in Nepal. METHODSMethodologies include: a) landscape-scale crop diagnostic survey on crop management, field attributes, and productivity outcomes combined with gridded soil and daily weather data to decompose rice yield gaps into constituent factors with machine learning diagnostics; b) with survey data, computation of key performance indicators to identify factors associated with productivity, profitability, and resource use efficiencies; c) complementary multi-location on-farm experiments (2011–2017) evaluating new agronomic management practices; and d) dynamic simulation (ORYZA3) to derive estimates of rice yield potential. RESULTS AND CONCLUSIONSAnalysis of survey data suggests an exploitable YG of 2.57 t ha−1 (40%) and the total YG of 4.85 t ha−1 (55%) indicating substantial scope for increasing rice yields in Nepal. Frequency of irrigation, amount of late-season rainfall, soil type, amount of early-season rainfall, presence of water stress, soil pH, and nitrogen (N) and phosphorus (P) fertilizer rates are the principal determinants of productivity outcomes in descending ranked order. Efficiency metrics suggest rice farmers in the study region make good use of fertilizer inputs, but since application rates are very low (e.g. most farmers apply <20 kg P ha−1) unsustainable mining of soil nutrients is likely common. Farmers in the top 10% of the yield distribution had lower greenhouse gas emission intensities (−43%), increased water productivity (+66%), and higher use efficiencies of N and P fertilizers (+28% and + 20%, respectively), suggesting that yield intensification can be achieved without tradeoffs with key environmental performance indicators. On-farm experiments conducted over several seasons support insights from surveys by demonstrating that major gains in rice yield (1.86 t ha−1) and profitability (US$ 243 ha−1) are achievable through the adoption of good agronomic practices. SIGNIFICANCEThrough a mixed methods approach, our results suggest that adoption of integrated 'good agronomic practices' can close YGs and improve food security outcomes associated with the rice-based agricultural systems of Nepal while simultaneously preserving or enhancing key sustainability and livelihood objectives.

Process simulation coupled with LCA for the evaluation of liquid - liquid extraction processes of phenol from aqueous streams

The steel industry is currently a major water pollution source, releasing high quantities of chemicals. One of the pollutants is phenol, known for its toxicity even when it is present in low concentrations. Liquid-liquid extraction employing various aromatics and cycloalkanes (i.e., benzene, toluene, cyclohexane, ethylbenzene) and ketones (i.e., methyl isobutyl ketone, cyclohexanone and mesityl oxide) as solvents, is studied in the present paper. A comparison among the seven solvents is performed based on process modelling simulation tools and Life Cycle Assessment (LCA). The simulations of the seven cases under study are conducted at the same wastewater flowrate of 100 tons/h, with a phenol content of 0.2 wt.% and compared using various parameters (i.e., quantity of solvent, steam and power used, quantity of solvent present in the output phenol streams). The simulation results show that the lowest quantity of solvent is registered in the phenol removal which uses cyclohexanone as solvent (e.g., 34,212.40 kg/h), followed by the case which uses mesityl oxide for the liquid-liquid extraction (e.g., 34,759.80 kg/h) and by the case involving cyclohexanone (e.g., 37,490.60 kg/h). The lowest steam consumption is registered also in the case of cyclohexanone usage (e.g., 47.56 GJ/h) while the lowest power consumption corresponds to mesityl oxide usage (e.g., 11.20 MJ/h). The simulation results are then used to perform an environmental analysis, quantified in terms of environmental key performance indicators, embedding several solvents production methods as well as various fuels. Our life cycle assessment leads to the conclusions that the most environmentally friendly design is phenol removal using cyclohexanone as a solvent, whose provision comes from cyclohexane, which in turn is produced from benzene in conjunction with steam production from natural gas. For instance, the lowest global warming potential indicator score is about 342 kg CO2 equivalents per kg of phenol, while the same indicator for the worst solvent, i.e., toluene produced using reforming technology and steam being produced using hard coal as fuel, is almost double (e.g., 341.94 kg CO2 equivalents per kg of phenol vs. 575.30 CO2 equivalents per kg of phenol). Lower values for other impact indicators are also obtained in the phenol removal using cyclohexanone as a solvent with steam being generated form natural gas (e.g., acidification potential indicator is 0.42 kg SO2 equivalents per kg of phenol, eutrophication potential is 4.21 × 10−2 kg PO43- equivalents per kg phenol, ozone depletion potential is 1.13 × 10-9 kg R11 equivalents per kg phenol).

Environmental Key Performance Indicators for Sustainable Evaluation in Automotive Industry: A Focus Group Study

Regarding the significant share of the automotive industry in both producing economic value added and employment, this sector is dominated in the industrial development approach. On the other side, different societies have focussed on the emissions, energy consumption and also waste production of road transportation as important risk threatening environmental health. So, the supply side is highly expected to deal with the expectations of stakeholders relating to sustainability concerns and related risks. To evaluate the implementation of environmental policies in the direction of sustainability and respond to the sustainability and environmental concerns of stakeholders, similar organisations need a uniform framework for performance appraisal. The present study aimed to identify, select and validate the environmental key performance indicators for sustainability assessment of the automotive industry to create a framework for selecting the indicators and using them as a uniform method for better comparison of the performance of car companies in the field of environmental sustainability. In this research, key environmental performance indicators are studied in accordance with sustainability evaluation in the vehicle industry and final indicators introduced using SMARTL criteria. The results showed that 41 indicators included in five categories of waste and waste water, soil contaminators and solid waste, carbon production and energy consumption and management are introduced according to ISO14031 model. Evaluating and monitoring these indicators, defined based on the UN Sustainable Development Goals 2030, can both reflect the quantitative improvement in the environmental performance. Additionally, using SMARTL key environmental performance indicators, the organization is able to comprehensively manage the environmental performance in accordance with environmental and sustainable development goals and policy. Using a uniform method for evaluating and monitoring the environmental performance allows us to compare the environmental performance of similar companies in line with sustainable development policies and creates a competition that allows the organisation to always increase its performance in a positive way.

A Study for the Optimal Exploitation of Solar, Wind and Hydro Resources and Electrical Storage Systems in the Bormida Valley in the North of Italy

The exploitation of distributed renewable energy sources leads to a low-carbon energy transition, mainly based on the optimal integration of hydro, PV and wind power plants with the remaining high-performance fossil-fuel power stations. In the last twenty years, European Union (EU) countries have shown a significant increase of the power installed in new PV and wind power plants, together with the refurbishment of small and medium size hydro stations. In particular, in Italy, PV and wind energy production has strongly increased and nowadays there are regions characterized by a very green energy mix. In this new scenario, energy storage becomes a viable solution to mitigate the variability of renewable energy sources thus optimizing the network operation. The present paper is focused on the Liguria region, in the North of Italy and in particular on the Bormida Valley where nowadays more than the half of the annual electricity consumption is covered by the renewable energy local production. The paper describes the current energy situation and proposes an optimization tool to investigate the possibility of installing new PV and wind power plants, as well as energy intensive storage units based on sodium-sulphur batteries; moreover, different scenarios are analyzed through the definition of economic and environmental key performance indicators.

A novel approach for assessing the ports’ environmental impacts in real time – The IoT based port environmental index

In recent years, exchange of goods around the world has mostly been done by the sea, which increased the pollution coming from the port areas. Activities connected with shipping and handling of goods in ports may harm both human health and the environment. These activities include different (mostly diesel-fueled) machinery used in ports, resulting in air emissions including GHG, NOX, SOX, PM, etc. Besides air pollution, port activities affect noise, light, and odor emission, waste accumulation and water pollution. Existing methodologies for estimating environmental impacts of port activities are mostly qualitative and include self-assessment methods which can often lead to biased results. Because of that, there is a need for a quantitative, industry-validated, and cohesive method that would give more accurate results. In this article, the Port Environmental Index (PEI) which has all the attributes described above will be presented. The PEI mission is to integrate all of the main environmental aspects of port such as air emission, waste production, water pollution, noise, light, and odor pollution into one metric that can then be used to assess the port performance and make comparison between ports. The PEI is made as a quantitative composite index based on aggregations of individual indicators for significant aspects of port operations. It includes different indices according to the source of the emission; the Ship Environmental Index (SEI), the Terminal Environmental Index (TEI), and the Port Authority Environmental Index (PAEI). While designing the PEI, correctly choosing the environmental impacts is paramount to properly identify port activities and associated environmental aspects. After their identification, for each significant aspect, a set of representative environmental key performance indicators (eKPIs) is identified. Afterwards, a series of mathematical operations are to be applied: normalization, weighting and aggregation. In this short communication, those methods are outlined yet not definitively chosen. The main idea behind the PEI is to use quantitative, data-based information collected automatically leveraging Internet of Things (IoT) techniques making it possible to assess the environmental impacts of port operations in real-time. The advantages of having such metric in the environmental management plan of a port are numerous. Amongst the most remarkable, it allows inter-port comparison and it can be used for decision making to estimate the impacts using one single metric rather than having many disperse values. Moreover, it can be used by ports for estimating their environmental performance and progress. Since it is based on information collected using IoT technologies provided in real-time, ports can make immediate corrections in their activities.