Tools for Oil Spill Response Waste Management and Logistic Support – Field Exercises Testing the RFID Technology and QR Codes

The aim of this paper is to study the usability of the radio-frequency identification (RFID) tracking system in managing the oil spill response waste logistics. This paper describes the waste management model developed for coastal oil spill response operations in Finland, Northern Europe. The model is part of the Finnish oil spill response management guidelines called SÖKÖ-guidelines (Halonen 2007), which are a collaboration between the Finnish oil spill response authorities and a university of applied sciences. The waste management model, originally established in 2007, was developed further in 2018 by introducing the Quick Response (QR) codes in order to facilitate waste segregation management (Halonen 2018). Most recent development of the model is related to the use of RFID technology. This paper analyses the usability of RFID tracking in oil spill response waste management. This study is based on the outcomes of two oil spill response waste management exercises conducted in September and October 2019 in Finland. The exercises focused on testing QR codes and RFID technology for managing the oil waste logistics in a case of a shoreline clean-up operation. On-water response operations and marine transportation of collected wastes fell outside of the scope of the exercises.

This paper is divided into introduction and five main chapters. In the first chapter after the introduction, the target scenario upon which the Finnish national and regional contingency plans are built, is presented in general terms. The aim of the chapter is to illustrate the scale of the spill response operations and the logistic arrangements needed. The second chapter demonstrates the logistic model developed to respond to that particular target scenario. The third chapter reviews the main features of the radio-frequency identification (RFID) system. The fourth chapter describes the lessons learnt from the exercises, in which the RFID system was tested to track waste units. The last chapter summarizes the outcomes and discusses the future steps.

The Gulf of Finland in the Baltic Sea is an important oil transportation corridor for Russian oil exports as well as for Finnish refined petroleum products. Over twenty oil carriers sail daily in the Gulf of Finland (Jolma et al. 2018, 19) and the annual volume of transported liquid cargoes is about 165 million tonnes (Kajatkari 2019, 115). Typical oil carriers operating in the region have about 100 000 tonnes cargo capacity. However, the trend of tonnage levels of the vessels is increasing and nowadays tankers with 200 000 tonnes cargo capacity sail in the region intermittently. These traffic volumes are very high compared to the relatively small size of the sea area (30 000 km²).

Risk assessment by the Finnish oil spill response authorities has indicated that an oil spill in the Gulf of Finland could rise up to 30 000 tonnes (Hietala & Lampela 2007, 20; Asikainen 2009, 15). Resulting volume of oiled waste is likely to multiply compared with the original volume of spilt oil. This may be due to emulsification of oil as incorporation of water increases the total volume. In addition, contaminated sand, gravel, reeds and entrained debris increases the amount of the wastes to be recovered. (Fingas 2013.) It should also be noted, that the chosen oil spill response method will have an impact on the total volume of recovered waste. In Finland, mechanical recovery is selected as the main oil spill response strategy. In-situ burning or use of dispersants are deemed non-preferred due to the sensitiveness of the marine environment, small water volume, low water temperatures and slow exchange of water of the basin. In-situ burning is also restricted due to the close proximity of densely populated areas. Therefore, Finland's oil spill response preparedness is built upon large response vessel fleet equipped with mechanical recovery systems – there are approximately 20 state owned recovery vessels and over 150 rescue vessels capable of independent oil recovery (Jolma et al. 2018, 49). Mechanical recovery approach inherently produces call for waste logistics. Moreover, the Finnish coast of the Gulf of Finland is characterized by deep and fragmented archipelago, and therefore the risk of shoreline contamination is very high. These characteristics urge high preparedness for shoreline clean-up operation and the related waste management.

Considering the abovementioned aspects, the Finnish authorities have estimated that a stranded oil spill of 30 000 tonnes is likely to generate 200 000–500 000 tonnes of oily wastes (Asikainen 2009, 37). It is recognized that such an exceptional amount of wastes has the potential to overcharge treatment capacities of waste disposal facilities. This emphasizes the necessity of careful pre-planning and led to the development of a logistic model for oil spill response waste management.

Oil spill waste management model consists of three main elements: 1) shoreline segmenting, 2) pre-planned logistic chain with pre-defined waste transportation nodes and 3) waste segregation scheme.

Clean-up of contaminated shorelines requires a careful and pre-planned strategy. For systematic approach, the shoreline of the Gulf of Finland (within the Finnish territorial waters) is divided into one-kilometre wide segments. Each segment is further divided into five 200 metres-wide sectors A–E.

The segments and sectors are named with identification codes based on the municipal name, running number and sector-specific alphabet (Fig. 1). For example, segment code “KOT_15A” refers to the first sector (“A”) in the 15^th segment (“15”) situating 15 kilometres from the city border in the municipality of Kotka City (“KOT”). Segmentation is used to name and identify oiled areas precisely. The identification codes facilitate also documentation and bookkeeping as worksheets, invoices, payment receipts and other documents can be linked to the work site in question. (Halonen & Pascale 2008.)

General principle is, that the oily material is transferred from the clean-up site to a final treatment, recycling or disposal facility, either with or without a series of temporary storage sites with transportation between them (IPIECA-IOGP 2014, 6). In Finland, where the coastline is ragged and, in some places, very difficult to access, the logistic chain may consist of several stages and transportation modes. Ways to transfer the wastes depend on the characteristics of the incident site, in particular whether there is built infrastructure available or not. To facilitate putting the waste logistics into operation at the time of an oil incident, areas suitable for waste transportation and intermediate storing are mapped out in advance. Waste logistic chain consists of primary collection areas, transportation points, intermediate storage areas and final disposal facilities (Fig. 1).

Primary collection areas are located within the cleaning sectors or in their close vicinity. Generally, collected wastes need to be carried by hand or by light means of transport from the collection area to the transportation point. Designated transportation points are areas suitable for either truck or sea transportation. (Halonen 2007, Mänttäri 2010; Kauppinen 2017.) Each logistical point is surveyed on-site and information on accessibility and other features are recorded into the point's Target Card. The Target Cards can be used as an Excel-database (Vuoksio 2010) or via the national Situational Awareness system BORIS 2.0 (Fig. 2). BORIS (Baltic Oil spill Response Information System) is a map-based situation awareness system, which is used in conducting oil spill response operation to achieve a common operating picture among multi-agency response actors in Finland (Hietala et al. 2015).

High waste volume requires segregation in order to maximise the capacities of waste treatment facilities: Segregation allows the distribution of wastes into several various facilities as it increases the number of available treatment options (Hupponen 2007). Segregation also minimizes the related costs – disposal of unsegregated oily wastes is highly expensive (Hupponen 2007; Partila 2010).

Spill response wastes are expected to comprise of recovered oil, oil-water mixtures, oiled soil and sediments and mixed oily wastes. Oiled soil and sediments are estimated to form the majority of the total waste volume (Fig. 3). The second largest waste segment will be generated from the on-water oil recovery measures. The share of the mixed oily wastes is the smallest of the total waste volume. Mixed wastes will result from the recovery operation itself, and the contents is subjected to the response and recovery method used. Mixed wastes may consists of damaged booms, used sorbent materials and personal protective equipment (PPE) as well as oiled geotextiles and tarpaulins.

The calculation of the waste types is based on a research, in which the environmental authorities estimated the Finnish preparedness for waste treatment in exceptional situations (see Asikainen 2009).

Based on the expected waste types generated, added with the possibilities of the existing disposal facilities to handle the wastes, five waste segregation categories were determined (Lempinen 2006, Hupponen 2007, Partila 2010). These categories are: 1) oiled soil and sediments, 2) oil-water mixtures, 3) mixed oily waste, 4) hazardous waste and 5) uncontaminated debris.

Two of these categories (4. and 5.) are supplementary to the previous studies (e.g. Asikainen 2009). The fourth category, hazardous wastes, is defined for wastes with high risk for pathogens, such as oil contaminated birds and animals, and the equipment used for their decontamination. In addition, non-oiled debris (5.) needs to be considered as a separate waste stream, as considerable amounts of packaging materials and plastic covers might be generated.

Segregation sets certain requirements for the logistic arrangements both in primary collection, temporary storing and different transportation phases. Working sites need to be equipped with separate waste containers for each waste category. Containers are marked with specific colours and/or text labels (Fig. 4). In addition, the waste units used in transportation and in temporary/intermediate storage sites are marked similarly. The number of waste units needed will rise as the segregation should be maintained systematically through the logistics chain. The complexity of the segregation combined with the scattered coastline of the Gulf of Finland will challenge the spill response logistics. Nevertheless, the value of segregation is considered high and data management systems are seen as solutions to tackle the complexity.

Segregation is facilitated by the means of easy-to-use segregation guidelines. Guidelines are produced by using colour codes for different waste categories together with the inserted QR (Quick Response) codes to provide segregation instructions (Fig. 4).

Collection and storage containers are labelled with QR codes prior to the clean-up process. The QR code indicates the contents of the container and acts as a hazard label. By reading the QR code by smartphone, segregation guidelines are opened to a browser view containing the description of the particular waste type accompanied by instructive examples of included material types. (Halonen 2018.)

Finnish waste management regulation sets requirements for documentation, record keeping and data management for wastes – also to be complied with in exceptional situations such as oil spill response operations (Finnish Waste Act 2011/646). Regulations prescribe, that the holder of the waste is responsible of knowing where the waste is located. In addition, accurate records are required to support financial claims and compensations (IPIECA & IOGP 2014, 27). Documentation also facilitates the Incident Command to keep up the situational picture of how much waste is recovered, stored or transferred to the final disposal. As the amount of waste with numerous waste units and storage sites may rise high, and the geographical scope of the operation can be wide, there is a need for an operative data management system. The system needs to record the spatial distribution of the waste units, transfer of waste from one location to another and, in particular, to record when the responsibility for managing the waste changes from the generator to the transporter (IPIECA & IOGP 2014, 27; Finnish Waste Act 2011/646). The system also needs to support the transport consignment notes, to be robust and not vulnerable for oil contamination or harsh weather.

Radio Frequency Identification (RFID) technology contains small, easily attachable tracking tags and readers. RFID technology uses electromagnetic fields to automatically identify and track tags, and the objects where the tags are attached to. The tags contain electronically stored information, for example information found necessary to control a logistic system. The tags can be active or passive. Active tags have a local power source, which allows information reading over hundreds of meters apart. A passive RFID tag receives its energy from the reader's signal. The system generally contains a database, in which the readings are stored and a user interface through which the information is managed. (Staljon 2019.)

The use of the RFID systems as an oil spill waste inventory system in Finland was introduced by Peräkylä in 2009. Several data management systems were studied, and the RFID technology showed potential by being generally used and therefore readily available (Peräkylä 2009). Preliminary requirements for the system were set in 2017 by identifying what information should be recorded and the node points in logistics chain, where the information should be recorded (Malk & Halonen 2017).

To test whether the QR codes and RFID system are feasible in oil spill waste management or not, two field exercises were arranged. The aim of the exercises was also to determine the quality and quantity of the data that needs to be stored on the tags in different transportation scenarios. It was also seen important to test whether the previously planned reading nodes along the logistical chain were the correct ones. The exercises were executed in Kotka (September 3^rd 2019), and in Porvoo (October 30^th 2019) in Finland.

The RFID tracking system used in the exercises was “eOil Waste Management System” developed by Finfio Ltd. The system used a tag-model “Confidex Carrier Pro”, which includes a “Impinj Monza” chip (Fig. 5). This tag is water and oil resistant, washable and usable in temperature scale of –35 °C...+85 °C. The tag is designed especially for plastic surfaces but it can be used also on other types of surfaces. The maximum reading distance of the tag on a plastic surface is 12,5 metres and on a cardboard surface 11 metres. (Staljon 2019.)

The surface of the tag itself allows various imprints like barcodes. The tag possesses an extended memory for 64 marks. It contains 16 mark-long Electronic Product Code (EPC code) and a unique Transponder ID code (TID code) for 12 marks. The EPC code identifies a specific item in the supply chain and it can be replaced by a special code in accordance with a desired labelling logic, but changes in the TID codes are not allowed. (Staljon 2019.) In the field tests, the tags were coded and labelled by waste types as follows: “soil”, “mix”, “water”, “risk” and “pure” for uncontaminated waste (Halonen 2019; Halonen 2020).

Two passive EPC Slim UHF readers (fixed, automatic, mounted on a tripod, supplied by Idesco) were used. Their effective reading distances were about 4 metres. These readers were quite small – their sizing can be compared to a cell phone (141 × 43 × 19 mm). The tripod EPC reader and the manual EXA51e reader are presented in Figure 6. The readers included a display board and LED lights, which were programmed separately to show the information of the tag in question (see Fig. 6 and 9). The coordination of the system (running the software and compiling the statistics) was carried out by a computer hardware (Windows 10 laptop) with a user interface and a small server with automatic fixed readers and displays. (Staljon 2019.)

The exercise scenario was a simulated onshore oil spill response waste management situation. The logistic chain was demonstrated with smaller and larger “waste units” or containers (cardboard boxes and envelopes, see Figures 7 and 9). The units were equipped with the RFID tags and labelled with the QR code of the related waste type. The number of waste units was 85 in total, and they were distributed on two one-kilometre long “shoreline segments” as demonstrated in Figure 8. When the “oily wastes” were collected from the shoreline segments, they were transferred to the segments' primary storage points, i.e. transportation points. In the transportation points, the waste quantity inside each container was added to the information content of the attached tag. Information was added simultaneously while reading the tag. Recorded waste units were then loaded into the transportation vehicle. In the second testing session in Porvoo, the demonstrated logistics chain covered also the transportation from the transportation point to the intermediate storage site (Fig. 8), where one of the standing readers was situated at the “gate” of the storing site. (Halonen 2019; Halonen 2020.)

All 85 units were recorded, and some returned and circulated several times so that adequate amount of data could be gathered. The total number of readings in the first testing session was 148 and in the second session 36 readings. The data collected by the system was stored on a laptop, from which it was uploaded to the cloud service. After this, the data was downloadable by the “Incident Command” over a secure mobile connection. (Halonen 2019; Halonen 2020.)

Reading of the tags progressed as expected. At first, the tags were unintentionally recorded several times as the readers were situated too close to each other (within a couple of meters). This problem was fixed by setting the distance between the readers to more than their effective reading distance. It is likely, that this problem was due to the simulated exercise set-up, and in the realistic deployment of the system in the field, the distances will naturally fall far enough. (Halonen 2019; Halonen 2020.)

As a result of the tests, naming the RFID tags according to the waste type was deemed the right solution. The waste type information was considered most permanent by nature among the related data. With this naming logic, the tags can be coded in advance – on the request of the Incident Command – without prior knowledge of the exact oiled segments. Colour-coded QR labels seemed to facilitate the recognition of the waste units, which accelerated the logistics process. It was also discovered, that QR labels could be affixed over the RFID tag to provide additional protection (Halonen 2019; Halonen 2020).

Saving information to the extended memory of the tag was also studied. It turned out that additional information is better to be stored in the system's database rather than in the tag's memory, because extra information slows down the readability of the tag, and moreover, the allowed 64 marks are not enough for detailed information. It was also noted that passive tags, i.e. tags without their own power cells, seem more usable in spill response operations as there is no risk of batteries or other power sources to lose their capacity. (Halonen 2019; Halonen 2020.)

In addition, it was concluded that the RFID tags need to be read in four nodes along the logistic chain (Fig. 10). It seems feasible to start the tracking from the point, in which the size of the waste units is comparable to the transport units. Tracking small collection units; buckets or bags, which are operated manually, were considered not to offer added value, albeit it would increase the accuracy of the documentation. (Halonen 2019; Halonen 2020.)

Afterwards, the system's statistics of the exercise activities were analysed. It turned out that the system's log files were quite versatile. The saved tag-readings could be reviewed as a list of events as well as in graphical format (Fig.11). The data could be filtered e.g. by the waste type, shoreline segment, logistical point or recorded time stamp. Also, a single waste unit could be tracked, or all events during a particular time frame could be reviewed. The system also provided a situational status of a chosen segment telling the volume of transported wastes and the number of occupied or free waste units in the area. These features of the system were considered valuable as they enable the achievement of an overall picture of the operation and maintaining optimal rotation of the waste units. And importantly, it provides up-to-date information on the location and amount of wastes for the holder of the waste, as required by the Finnish Waste Act (2011/646). The stored information could be exploited to prepare situation reports on how the operation progresses. Log files and event history were also considered great aids to compile documentation to support compensation claims. (Halonen 2019; Halonen 2020.)

The exercises also demonstrated some development needs. The usability of the tracking system would be greatly improved if the system was interoperable with the BORIS system. This would allow the demonstration of the prevailing waste situation on a same map view as other response activities. Visualisation of contaminated and cleaned areas, as well as the amounts of wastes per segments or storing sites, could also then be elaborated.

Based on the field test, however, even the tracking system in its present state showed potential for up-to-date monitoring and managing of the waste logistics in a centralized manner. It should also be noted, that the tracking logic demonstrated above, is not product-specific but can be applied to RFID systems in general.

This paper aimed to examine the usability of the RFID tracking in the spill response waste management. In addition, the objective was to introduce the QR segregation guideline and its interoperability with the identification and tracking technology tested. The feasibility of the systems was tested by the means of two field exercises. Managing the oil spill response operation requires robust system of documentation, record keeping and data management. The results supported the presumption that the RFID technology could be a potential option. The tested system proved to provide information on the current status of the wastes, i.e. whether the waste is stored, transported or disposed. It also demonstrated the current situation of each logistical point and the statistics of the oil spill recovery process. The project group estimated that the recorded information would significantly facilitate the operation management in large scale oil incidents and in presenting claims. With the help of a data management system it will also be easier to meet the regulatory requirements of constantly being aware of the situation and ownership of hazardous wastes. Data recordings can be also used as materials for internal communication as well as for press releases. Later, the documentation will give a proper outlook for researchers to study the total quantity of oil recovered (compared to spilled oil) and the overall effectivity of the waste management system.

The field exercises were conducted under SÖKÖSuomenlahti project funded by the Finnish National Oil Spill Compensation Fund of the Finnish Ministry of the Environment and the participating Fire and Rescue Services of Kymenlaakso, Eastern Uusimaa, City of Helsinki and Western Uusimaa. The project advisory committee comprises of designated oil spill response specialists representing the abovementioned Fire and Rescue Services as well as The Finnish Border Guard, Finnish Environment Institute and the Centres for Economic Development, Transport and the Environment of Uusimaa and Southeast Finland. Special acknowledgment is made to the contribution of the project partners and to technical specialists at Finfio Ltd and Vidamin Ltd for collaboration in developing the operations model for tracking oil spill response wastes.