PEF-CaS: Product Environmental Footprint Calculation system
Client.
AFarCloud
Problem.
The main goal of the PEF-DST is to support the end-user in monitoring the PEF of two Diary Supply Chain (DSC) stages: milk production and milk transportation. The DSC data is analyzed in order to assess the quality of the supply chain operation in terms of sustainability.
Solution.
- aggregated PEF of the factory the number is the indicator for the user on the overall PEF performance along the supply chain,
- a graphical presentation of aggregated PEF of the factory and its components (in this case: Aggregated Transport PEF, Farm PEF and Average PEF per route)
- the graphical presentation of Aggregated Factory PEFliter should allow for simplified overview and extended view with detailed data and components of analyzed Factory PEF,
- historical data – the user needs to be allowed to review historical data to improve future inference and business decisions. PEF reductions will be the goal.
- transport PEF for each hauler and Farm PEF for each milk supplier – environmental issues should be one of the components of decision making when choosing business partners. Each party in the supply chain should aim to minimize PEF of its own activities.
- input data edit option for each transport provider – possibility to edit input data to show what changes in Aggregated PEF occur when CO2 emission norm changes or the provider modifies routes and limits the number of kilometers daily.
- input form – some of the data needs to be entered manually for the players that do not have own PEF monitoring tools. PEF of each farm may be calculated from the chosen parameters provided once by each supplier. Data sets may be updated.
- archiving of data sets – modification of data sets (manual or real) influence the performance on PEF. It is useful to have a possibility to leave a comment if a data set modification results from a known event or external factors (e.g. weather conditions, new investments, road failures, etc.)
- emission norms – the following versions of PEF Mode may be connected to databases that will update automatically the standardized data as they are modified by the authorities. Now, however, those values should be updated manually.
The goal is to give the user a bigger picture – PEF is not just a number. The possibility to modify the data manually and see the prediction of expected PEF values is essential from the perspective of the sense of agency. First attempts of PEF implementation into business routine require to relate to users’ sentiments and the image of a cycle where each party along the supply chain plays a significant role. The user should feel the change is possible.
Process.
PEF is based on Life Cycle Assessment methodology, defined by the European Commission’s Joint Research Center. Its purpose is to provide a standard for entities within the EU to measure environmental performance. Every product category can be defined by a distinctive set of rules that are to be applied.
PEF-DST monitors the footprint as a multi-factor measure of the impact of dairy farms or transportation on the environment. It is calculated using a set of factors that impact the milk production and transport ecosystem. Monitoring PEF in PEF-DST allows us to identify trade-offs and make better strategic decisions.
The EU commission has provided Product Environmental Footprint Category Rules (PEFCRs) as specific guidance for PEF studies, at the level of a specific product category, for calculating and reporting products’ life cycle environmental impacts. PEFCRs shift the focus of the PEF study towards these aspects and parameters that matter the most and hence contribute to increased relevance, reproducibility, and consistency of the results by reducing costs.
Delivered value.
The aim of the PEF-DST is to present the PEF results for farmers and milk transportation. The PEF-DST provides an end-user interface with clean, consistent and personalized dashboards. The tool also provides customized enterprise reporting capabilities for the DSC participants.
Used Technologies.
System Prototype Demonstrated in Operational Environment.
PEF-CaS is a business intelligence tool for industry sectors where the collection of raw materials is involved in milk production. It is a solution based on the methodology of assessing Product Environmental Footprint (PEF), a metric developed by the European Council to measure the environmental impact of different production industries.
Apart from the PEF calculation, a system enabling real-time data collection was implemented and consisted of a cloud-based application. The system has been tested and deployed for milk haulers to show how to calculate it for the milk production industry and how particular parts of this process contribute to PEF (milk transport, milking, cow feeding, etc.).
PEF-CaS is mature and has diverse capabilities. It is implementable to other software solutions. PEF is a highly complex indicator, and each enterprise has specific, controllable factors influencing its aggregated PEF. The DAC’s goal was to design an interface flexible enough to be suitable for the presentation of various data sets. PEF-CaS was designed as an additional component of the MilkMap system. MilkMap is a tailored solution for managing the milk supply chain that was developed by DAC.Digital in cooperation with their clients (both milk and dairy producers).
The system has the potential to be adapted for other industries and sectors for the calculation of PEF based on European Commission guidelines.
State of the art.
The environmental effect of the Dairy Supply Chain (DSC) has been and is a major factor in the direction of sustainable growth. However, this is not the only one, other factors that align with the sustainable development approach also exist.
For example, improving food waste recycling, strengthening facility sharing, and sustainable logistics, which are understood as a balance between logistics, the environment, and the economy. There is a need to define sustainability measures that indicate/estimate the impact of human activities within the dairy industry on the environment to achieve sustainable development goals, such as ensuring sustainable consumption and production patterns and taking urgent action to combat climate change and its impacts.
In order to give explicit guidelines at the level of a single product category for calculating and reporting goods’ life cycle environmental impacts, the European Commission created Product Environmental Footprint Category Rules (PEFCRs). By lowering expenditures compared to research based on the exhaustive criteria of the PEF guide, PEFCRs aid in shifting the emphasis of the PEF study toward those features and characteristics that matter the most, increasing the relevance, repeatability, and consistency of the results. These PEFCRs are industry specific.
The whole life cycle of dairy products supplied in the European and EFTA markets is covered by PEFCR for Dairy Products (PEFCR-DP). Liquid milk, dry whey products, cheeses, fermented milk products, and butterfat products are considered subcategories. This PEFCR-DP makes it possible to evaluate several dairy products in the same subcategory side by side. In order to get comparable results, it uses a structured and systematic methodology to assess the environmental effects of dairy products supplied in Europe.
This raises the need for ensuring all stages of DSC are visible to facilitate its sustainability orientation. Visibility of all DSC phases would also guarantee the DSC’s long-term growth, which produces dairy products of the highest quality. DSC visibility is shown in Figure 1 and is defined as the ability of the supply chain to view the life cycle of a dairy product, including the production of feed and milk, transportation of milk, processing of milk, distribution of dairy products to end users, and end-of-life activities and processes.
Figure 1. Dairy Supply Chain with corresponding data sources.
Currently, visibility is enabled across much of the DSC, from milk production to dairy product consumption, making the DSC manageable. Traceability is another desirable feature in modern DSC, which is defined in the food industry as the ability to trace and follow a food, feed, food-producing animal, or substance intended to be, or expected to be, incorporated into a food or feed through all stages of production, processing, and distribution as per the Regulation (EC) No 178/2002 of the European Parliament and of the Council of 28 January 2002. The Internet of Things (IoT) is the core notion that offers visibility and interoperability amongst dispersed systems in complicated DSCs depicted in Figure 1. As a result, today’s administration of integrated DSC is shifting toward IoT-based cloud-distributed solutions, blockchain-based transactions, and big data analysis of tracked data.
The visibility and traceability afforded by IoT, among other things, help in monitoring the two most important environmental variables impacting DSC, water consumption and GHG emissions. When milk production and transportation are included, the impact of DSC on world GHG emissions is estimated to be 2.7%. As a result, the dairy industry is an important actor/suspect in the EU’s climate change policy, with the European Union Emission Trading System (EU ETS) functioning as a critical tool for cost-effectively cutting greenhouse gas emissions. Here a Product Environmental Footprint Decision Support Tool would come in very handy.
The Solution: How does it work?
PEF-CaS is based on the European Commission’s Joint Research Center’s Life Cycle Assessment approach. Its goal is to offer a standard for measuring environmental performance among EU institutions. Every product category can be defined by a unique set of criteria that must be followed.
PEF-CaS measures the footprint as a multi-factor assessment of the environmental effect of dairy farms or transportation. It is estimated by taking into account a number of elements that influence the milk production and transportation environment. We may detect trade-offs and make better strategic decisions by monitoring PEF in PEF-CaS.
Required Inputs to PEF-CaS.
The AFarCloud Semantic Middleware has a data streaming component (see Figure 2) that can quickly ingest and analyze high-velocity data from remote data sources. The data in question comes from various phases of milk production and transportation and is required to calculate the PEF factor.
Figure 2 Streaming Engine architecture
Input data depends on the PEF factory accuracy and the product category. Some of the global normalization factors which have been recommended by European Commission are:
Acidification, Climate change, Eutrophication – freshwater, Eutrophication – marine, Eutrophication – terrestrial, Ionizing radiation – human health, Land use, Ozone depletion, Particulate matter, Photochemical ozone formation – human health, Resource use – fossils, Resource use – minerals and metals, and Water use.
OnPuts from PEF-CaS.
The output received from the PEF-CaS are the PEF results for farmers and milk transportation. It offers an end-user experience that is clean, consistent, and customized. The technology also gives DSC members customizable corporate reporting options.
To summarize PEF-CaS can carry out the following functions:
estimation of the environmental footprint of milk production (results calculated per cow)
graphical presentation of farm-scale environmental footprint (results calculated for the entire herd)
PEF-calculation implements the EU recommended Environmental Impact Assessment methodology
Example Applications.
Use Case.
Calculating the Product Environmental Footprint
Scenario.
Product Environmental Footprint (PEF) can be calculated for the farm or a specific type of farm production (e.g. cows breeding or milk transportation).
Solution.
| SPE saves data from sensors that monitor the whole production (plants or animals), such as corrals, stables, greenhouses, vehicles, agricultural gadgets, and types of machinery. As a result, SPE collects all of the information required to compute PEF through a specific application of third-party software, DSS algorithm, or Stream Processor. |
Use Case.
Monitoring of global PEF production
Scenario.
Required analysis of PEF by concerned agencies / associations
Solution.
The aggregated data includes the amount of milk collected from each farm and information on how the milk was delivered (e.g. average speed, the distance between collection points). Every day, data for each milk transportation route is pooled.
Use Case.
PEF Administration
Scenario.
PEF profile management
Solution.
The PEF indications and levels can be customized by the user. It will be able to update the reference indicators in the event of a change (by European or national guidelines).
The so-called PEF component is generated by every milk producer and every vehicle providing transportation services. PEF production from the dairy production and transport phases is totaled up at the conclusion of the trip for a certain vehicle. With such information available in monitoring mode, the analyst can investigate what PEF production looked like throughout the supply chain, such as PEF in dairy production or PEF in transportation.
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