Heavy Goods Vehicles Research Articles

A street-level assessment of greenhouse gas emissions associated with traffic congestion in the city of Nairobi, Kenya

Traffic congestion significantly contributes to climate change due to the emissions of Greenhouse Gases (GHGs) such as Carbon Dioxide (CO2), Nitrous Oxide (N2O), and Ozone (O3). Rapid urbanization and poor planning coupled with increased motorization and fragmented public transport system in cities such as Nairobi have led to increased vehicular emissions especially during heavy traffic along the various roads and within the Central Business District (CBD). To reduce GHG emissions in the urban transport sector, institutional coordination and relevant policy tools must be considered. This study aimed at estimating CO2 emissions from different vehicles during traffic congestion, using Uhuru Highway as a case study. The relationship between traffic congestion and CO2 emissions was analyzed using qualitative and quantitative methods, through a bottom-up approach. Questionnaires were administered to get individual vehicle characteristics and opinions on the best actions for the reduction of CO2 emissions along Uhuru Highway in Nairobi. The Average Annual Daily Traffic (AADT) for different vehicles from 2014 to 2019 was used to estimate the CO2 emissions. Results showed that private cars predominate over other vehicle types, contributing to 73% of the total CO2 emissions in Nairobi (CBD). Private cars are the highest contributor of CO2 emissions with a total of 25.3 million Carbo dioxide equivalent (gCO2e), between 2014 and 2019. In comparison, Public Service Vehicles, commonly referred to as Matatus emitted 6.89 million gCO2e, Light Commercial Vehicles (1.82 million gCO2e), Heavy Goods Vehicles (251,683 gCO2e), and motorcycles (181,054 gCO2e). To minimize CO2 emissions, the study recommended the enforcement of strong mobility policies to control the high motorization rate. One of these policies is the prioritization of the development of the mass public transport systems to achieve the potential health, economic and environmental gains within the CBD.

Work-Related Driving of Heavy Goods Vehicles: Factors That Influence Road Safety and the Development of a Framework for Safety Training

Road traffic accidents are a major health concern all over the world. Each year, 1.3 million people die in fatal road traffic accidents. Fatal and serious heavy goods vehicle (HGV) crashes are over-represented in many countries. This paper is a contribution to the road safety literature and has two aims. First, the study seeks to identify important factors in managing road safety for work-related driving of HGVs. Second, the study proposes an overall framework for how safety training could be executed and its overall content. Methods used were a literature review and a case study. The results show that important factors for management of road safety could be arranged at different levels: governmental level, third-party level, organizational level and driver level. Most important is that a systematic approach to road traffic safety for HGVs is essential. Every party is jointly responsible for road traffic safety, and parties must communicate and work together to increase road traffic safety for work-related driving of HGVs. By developing a safety training program for all parties in the system, the study proposes a method for increased communication, collaboration and cooperation between parties.

Method for Setting Weight Tolerance Limits in High-Speed Weigh-in-Motion Systems: A Case Study in Brazil

High-speed weighing systems are considered a potential tool to restrain overloaded vehicles traffic, since this practice promotes threats to the infrastructure’s durability and to citizens’ safety. In view of the discussion on the certification of such systems, a method to define the weight tolerance limits of heavy goods vehicles was proposed in this work, using statistical experimentation methods. The method was applied to a case study in Brazil, which considered a high-speed weighing system and three known vehicles (3C, 2S3, and 3S3). The vehicles were loaded with gravel and the bending plate scale was used to set the weight. The test was conducted by checking the weight of the vehicles in the HS-WIM system and composed by the observance of three mandatory speeds (60, 70, and 80 km/h), in three different lateral positions in relation to the lane (center, left, and right), and at various times during the collection days. As result, maximum weights accuracy limits were obtained for gross vehicle weight (GVW) and for axes groups (G1, G2, and G3) as 13% (GVW), 20% (G1), 20% (G2), and 17% (G3).

The effectiveness of the Structured Health Intervention For Truckers (SHIFT): a cluster randomised controlled trial (RCT)

BackgroundLong distance heavy goods vehicle (HGV) drivers exhibit higher than nationally representative rates of obesity, and obesity-related co-morbidities, and are underserved in terms of health promotion initiatives. The purpose of this study was to evaluate the effectiveness of the multicomponent ‘Structured Health Intervention For Truckers’ (SHIFT), compared to usual care, at 6- and 16–18-month follow-up.MethodsWe conducted a two-arm cluster RCT in transport sites throughout the Midlands, UK. Outcome measures were assessed at baseline, at 6- and 16–18-month follow-up. Clusters were randomised (1:1) following baseline measurements to either the SHIFT arm or usual practice control arm. The 6-month SHIFT programme included a group-based interactive 6-h education and behaviour change session, health coach support and equipment provision (Fitbit® and resistance bands/balls to facilitate a ‘cab workout’). The primary outcome was device-assessed physical activity (mean steps/day) at 6 months. Secondary outcomes included the following: device-assessed sitting, physical activity intensity and sleep; cardiometabolic health, diet, mental wellbeing and work-related psychosocial variables. Data were analysed using mixed-effect linear regression models using a complete-case population.ResultsThree hundred eighty-two HGV drivers (mean ± SD age: 48.4 ± 9.4 years, BMI: 30.4 ± 5.1 kg/m2, 99% male) were recruited across 25 clusters (sites) and randomised into either the SHIFT (12 clusters, n = 183) or control (13 clusters, n = 199) arms. At 6 months, 209 (55%) participants provided primary outcome data. Significant differences in mean daily steps were found between groups, in favour of the SHIFT arm (adjusted mean difference: 1008 steps/day, 95% CI: 145–1871, p = 0.022). Favourable differences were also seen in the SHIFT group, relative to the control group, in time spent sitting (− 24 mins/day, 95% CI: − 43 to − 6), and moderate-to-vigorous physical activity (6 mins/day, 95% CI: 0.3–11). Differences were not maintained at 16–18 months. No differences were observed between groups in the other secondary outcomes at either follow-up.ConclusionsThe SHIFT programme led to a potentially clinically meaningful difference in daily steps, between trial arms, at 6 months. Whilst the longer-term impact is unclear, the programme offers potential to be incorporated into driver training courses to promote activity in this at-risk, underserved and hard-to-reach essential occupational group.Trial registrationISRCTN10483894 (date registered: 01/03/2017)

Effects on accidents of police checks of drivers of heavy goods vehicles in Norway

During the period from 2007 to 2019, the number of drivers of heavy goods vehicles checked by the traffic police in Norway varied substantially. It declined during the first years of the period, then increased. This paper studies where there is an association between these variations and annual changes in the number of accidents involving heavy goods vehicles. A negative relationship is found: the more drivers checked, the fewer accidents. The relationship can be described by means of a dose–response function. The function indicates that when the number of drivers checked by the police is reduced by 50%, one may expect the number of accidents involving heavy goods vehicles to increase by 7.5%. A 50% increase in the number of drivers checked will be associated with a 3.5% reduction in the number of accidents, and a 150% increase in the number of drivers checked will be associated with an 8.6% reduction in the number of accidents.

Review and Analysis of Technical Designs of Rear Underrun Protective Devices (RUPDs) in Terms of Regulatory Compliance.

The Rear Underrun Protective Device (RUPD) is a basic means to prevent a passenger car from running under the rear of a motor truck (also referred to as heavy goods vehicle or HGV) or a trailer in the case of a rear-end collision and thus to reduce deformations of the car’s passenger compartment (“survival space”). In many publications dealing with such devices, the increasing of RUPD stiffness by applying innovative design solutions or using high-strength materials has been considered; in some designs, additional RUPD components are introduced to absorb the impact energy. In this paper, a review of the RUPD designs is presented and some of them are analyzed, where their characteristics that are essential for the compliance with normative market requirements are indicated. Results of the authors’ research on the selection of an energy absorber incorporated in the rear impact guard bar of an HGV are presented as well.

A Simultaneous Analysis of the User Safety and Resilience of a Twin-Tube Road Tunnel

This study complements our previous work with a simultaneous analysis of user safety and road tunnel resilience. We developed a computational fluid dynamics (CFD) model and simulated the corresponding egress process to evaluate the risk level of users exposed to different types of fire, such those which might occur on the undisrupted lane of a partially closed tube tunnel due to a traffic accident, or in the adjacent tube when used for two-way traffic in the case of the complete closure of the tube involved in the accident. The CFD results showed that: (i) better environmental conditions were found with the partial closure of the tube rather than the complete one; (ii) additional benefits can be achieved by activating variable message signs (VMSs) that suggest an alternative itinerary for heavy good vehicles (HGVs) only; (iii) safety issues for human health may arise only in the case of a 100 MW fire, occurring during the complete closure of the tube and the use of the parallel one for two-way traffic. The findings of the CFD simulations were subsequently used to perform a quantitative risk analysis (QRA) based on a probabilistic approach. The findings of the QRA were found to be consistent with those obtained by the tunnel resilience analysis. In particular, the lowest risk level for user safety was found with the partial closure of the tube instead of the complete one, and by activating the VMSs to redirect HGVs only towards an alternative itinerary. This finding was found to correspond to a higher resilience index of the tunnel (i.e., a lower resilience loss due to a traffic accident occurring in a tube). This study increases our knowledge on certain relevant aspects of the operating conditions of tunnels and can serve as a possible reference for tunnel management agencies (TMAs) in their choice of the most appropriate arrangement to recover the functionality of a tunnel taking into account both user safety and resilience at the same time.

Vulnerable Road User Protection from Heavy Goods Vehicles Using Direct and Indirect Vision Aids

In Europe, heavy goods vehicles (HGVs) are disproportionately involved in serious and fatal collisions with vulnerable road users (VRUs). An interrogation of 2019 national crash data for Great Britain (Stats19) suggested that detection of cyclists and pedestrians in the nearside and front blind spots of HGVs is still a significant problem during forward or left-turn manoeuvres of the HGV. To improve detection, Transport for London introduced Direct Vision and Safe System Standards in 2021 for HGVs entering the Greater London area. This research assessed the efficacy of one of the Safe System requirements—the fitment of sensors to detect vulnerable road users on the nearside of the vehicle. A physical testing procedure was developed to determine the performance of a sensor system meeting the Transport for London Safe System requirements. Overall, the Safe System compliant sensor system missed 52% of expected detection nodes on the nearside of the vehicle. A total of 56% of the “stop vehicle” nodes, 45% of the “slow down” and 48% of the “proceed with caution” nodes were not recognised. The most forward sensor did not fully cover the front-left corner blind spot, missing 70% of the desired detection nodes. Nearside sensor systems fitted to Safe System requirements may cover a reasonable area but could still leave many undetected zones to the left and front of the vehicle. Standardising sensor range and location could help to eliminate sensor blind spots. Mandating additional front sensors would help cover the blind spot at the front-left corner of the HGV.

Interactions Between Heavy Trucks and Vulnerable Road Users-A Systematic Review to Inform the Interactive Capabilities of Highly Automated Trucks.

This study investigates interactive behaviors and communication cues of heavy goods vehicles (HGVs) and vulnerable road users (VRUs) such as pedestrians and cyclists as a means of informing the interactive capabilities of highly automated HGVs. Following a general framing of road traffic interaction, we conducted a systematic literature review of empirical HGV-VRU studies found through the databases Scopus, ScienceDirect and TRID. We extracted reports of interactive road user behaviors and communication cues from 19 eligible studies and categorized these into two groups: 1) the associated communication channel/mechanism (e.g., nonverbal behavior), and 2) the type of communication cue (implicit/explicit). We found the following interactive behaviors and communication cues: 1) vehicle-centric (e.g., HGV as a larger vehicle, adapting trajectory, position relative to the VRU, timing of acceleration to pass the VRU, displaying information via human-machine interface), 2) driver-centric (e.g., professional driver, present inside/outside the cabin, eye-gaze behavior), and 3) VRU-centric (e.g., racer cyclist, adapting trajectory, position relative to the HGV, proximity to other VRUs, eye-gaze behavior). These cues are predominantly based on road user trajectories and movements (i.e., kinesics/proxemics nonverbal behavior) forming implicit communication, which indicates that this is the primary mechanism for HGV-VRU interactions. However, there are also reports of more explicit cues such as cyclists waving to say thanks, the use of turning indicators, or new types of external human-machine interfaces (eHMI). Compared to corresponding scenarios with light vehicles, HGV-VRU interaction patterns are to a high extent formed by the HGV’s size, shape and weight. For example, this can cause VRUs to feel less safe, drivers to seek to avoid unnecessary decelerations and accelerations, or lead to strategic behaviors due to larger blind-spots. Based on these findings, it is likely that road user trajectories and kinematic behaviors will form the basis for communication also for highly automated HGV-VRU interaction. However, it might also be beneficial to use additional eHMI to compensate for the loss of more social driver-centric cues or to signal other types of information. While controlled experiments can be used to gather such initial insights, deeper understanding of highly automated HGV-VRU interactions will also require naturalistic studies.

A numerical method for studying the effect of calcium silicate lining on road tunnel fires

Road tunnel fires can jeopardize the life safety of occupants and the structural integrity of the tunnel. Such fires are usually characterized by the heat release rate (HRR) parameter. Most tunnel fire safety systems are designed based on this parameter. The tunnel structure (walls and ceilings) are usually protected with a passive protections such as magnesium oxide boards, cementitious sprays, polypropylene fiber mix or calcium silicate boards. Amongst these materials, calcium silicate boards are the most popular choice due to their easy installation and capability to protect the tunnel at very high temperatures for several hours. The HRR in a tunnel fire depends on various parameters such as type of vehicle involved in the fire, amount of fuel, location of fuel and ignition source, tunnel geometry, presence of fixed firefighting systems/ventilation, and several other factors. However, no evidence of structural linings (passive protection) affecting the heat release rate is found in the literature. To investigate the role of structural linings (calcium silicate) on the HRR, a numerical study using Fire Dynamic Simulator (FDS) is conducted for a road tunnel involving fire in a heavy goods vehicle. Two scenarios are investigated; one considering concrete tunnel linings without any passive protection while in the second scenario the tunnel is protected with calcium silicate linings. Comparison of the results from the two abovementioned scenarios reveal different patterns of HRR and tunnel temperatures and suggests that in large fires, structural linings such as calcium silicate lining can alter the overall HRR by enhancing the heat feedback and fuel burning rates inside the tunnel.

Physical Activity, Sedentary Time, and Cardiometabolic Health in Heavy Goods Vehicle Drivers.

Physical inactivity, prolonged sitting, and unhealthy dietary habits are common in Heavy Goods Vehicle (HGV) drivers. These factors increase risk of long-term health conditions. 329 HGV drivers across 25 UK depots completed a health assessment, including questionnaire completion, and objectively measured anthropometrics, blood biomarkers, physical activity (PA), and sedentary behavior. The sample demonstrated a high-risk cardiometabolic health profile. 88.1% were overweight or had obesity, and 11.9% had pre-diabetes or diabetes. 28.3% had hypertension, 83.6% had clinically elevated circulating low-density lipoprotein-cholesterol concentrations (>2mmol/l), and 66.6% had high total cholesterol levels (>4mmol/l). On workdays drivers accumulated 12 hours/day of sitting, 1.7 hours/day of light PA, and 9.8 mins/day of moderate-to-vigorous PA. Associations between light PA and cardiometabolic markers were observed. This sample presents high levels of inactivity, overweight, and obesity, and unhealthy cardiometabolic health profiles.

Exploring European Heavy Goods Vehicle Crashes Using a Three-Level Analysis of Crash Data.

Heavy goods vehicles (HGVs) are involved in 4.5% of police-reported road crashes in Europe and 14.2% of fatal road crashes. Active and passive safety systems can help to prevent crashes or mitigate the consequences but need detailed scenarios based on analysis of region-specific data to be designed effectively; however, a sufficiently detailed overview focusing on long-haul trucks is not available for Europe. The aim of this paper is to give a comprehensive and up-to-date analysis of crashes in the European Union that involve HGVs weighing 16 tons or more (16 t+). The identification of the most critical scenarios and their characteristics is based on a three-level analysis, as follows. Crash statistics based on data from the Community Database on Accidents on the Roads in Europe (CARE) provide a general overview of crashes involving HGVs. These results are complemented by a more detailed characterization of crashes involving 16 t+ trucks based on national road crash data from Italy, Spain, and Sweden. This analysis is further refined by a detailed study of crashes involving 16 t+ trucks in the German In-Depth Accident Study (GIDAS), including a crash causation analysis. The results show that most European HGV crashes occur in clear weather, during daylight, on dry roads, outside city limits, and on nonhighway roads. Three main scenarios for 16 t+ trucks are characterized in-depth: rear-end crashes in which the truck is the striking partner, conflicts during right turn maneuvers of the truck with a cyclist riding alongside, and pedestrians crossing the road in front of the truck. Among truck-related crash causes, information admission failures (e.g., distraction) were the main crash causation factor in 72% of cases in the rear-end striking scenario while information access problems (e.g., blind spots) were present for 72% of cases in the cyclist scenario and 75% of cases in the pedestrian scenario. The three levels of data analysis used in this paper give a deeper understanding of European HGV crashes, in terms of the most common crash characteristics on EU level and very detailed descriptions of both kinematic parameters and crash causation factors for the above scenarios. The results thereby provide both a global overview and sufficient depth of analysis of the most relevant cases and aid safety system development.

Resilience Assessment of a Twin-Tube Motorway Tunnel in the Event of a Traffic Accident or Fire in a Tube

We have developed a traffic simulation model to quantitatively assess the resilience of a twin-tube motorway tunnel in the event of traffic accident or fire occurring within a tube. The motorway section containing the tunnel was investigated for different possible scenarios including its partial or complete closure. The functionality of the road infrastructure, in the case of an accident in one of the two tubes (each tube presents two lanes with unidirectional traffic under ordinary conditions), was assumed to be recovered both by using the remaining undisrupted lane of the tube interested by the disruptive event (only one lane is closed) and reorganizing the traffic flow by utilizing the adjacent tube for bi-directional traffic (both lanes are closed). The effects of an alternative itinerary individualized in the corresponding open road network were also examined. The level of functionality of the system during the period in which the tube is partially or completely closed was computed as the ratio between the average travel time required to reach a given destination from a specific origin before and after the occurrence of the disruptive event. The resilience metrics were assumed to be resilience loss, recovery speed, and resilience index. The best scenario was found to be the partial closure of the tube in contrast to the complete one. However, in order to contain the negative effects on the functionality of the motorway section due to the complete closure of the tube, it is worth highlighting how the traffic by-pass before the entrance portal of the closed tube should be open in a very short time by the tunnel management team to allow for the quick use of the adjacent tube for bi-directional traffic. An additional improvement, with reference exclusively to passenger cars traveling through the adjacent unblocked tube, might be obtained by activating the variable message signs, located at a sufficient distance from the motorway junction before the entrance portal of the closed tube, in order to suggest an alternative route to heavy good vehicles (HGVs) only. Whereas, when the alternative itinerary is used by all vehicles traveling towards the blocked tube (i.e., both passenger cars and HGVs), this redirectioning of the motorway traffic flow was found to be characterized by an excessive travel time, with it therefore not being advisable. The results obtained might be useful as a decision-making support tool aimed at improving the resilience of twin-tube tunnels.

Investigating spatio-temporal characteristics and evaluation of heavy goods vehicle risky driving behaviours based on vehicle networking dataset during naturalistic driving

This study analysed the factors that affect vehicle warnings driving incidents caused by risky distracted driving behaviours of Heavy Goods Vehicles (HGV) drivers. The analysis was based on the natural driving networking dataset collected over a 6-month period and comprising 81 fleets made by 5396 HGV drivers in Guangdong, China. First, the spatio-temporal coupling characteristics of warning incidents on HGV risky driving behavior and various levels of roads were established. Then, a global Moran index was built to measure the comprehensive score of risky driving behaviour, based on which the safety level of driving behaviour of HGV drivers was assessed. Results showed that 50% of the HGV drivers tended to drive in a substantially dangerous driving way, and HGV drivers received the highest total number of driving warning events in September, with the dangerous warning types being mainly deviation or blocking cameras and smoking.

Investigating spatio-temporal characteristics and evaluation of heavy goods vehicle risky driving behaviours based on vehicle networking dataset during naturalistic driving

Investigating spatio-temporal characteristics and evaluation of heavy goods vehicle risky driving behaviours based on vehicle networking dataset during naturalistic driving

Quantifying Fuel-Saving Benefit of Low-Rolling-Resistance Tyres from Heavy Goods Vehicle In-Service Operations

Quantifying Fuel-Saving Benefit of Low-Rolling-Resistance Tyres from Heavy Goods Vehicle In-Service Operations

A new framework for assessing the environmental impacts of circular economy friendly soil waste-based geopolymer cements

Portland cement is one of the principal constituents used as a building material and is responsible for high energy consumption and greenhouse gas (GHG) emissions. Any attempt to reduce cement usage would make savings in energy usage and GHG emissions. A case study of Portland cement (CEM-I) replacement using alkali activated soil filter cake as a geopolymer mortar is presented to demonstrate application of a three-stage GHG emission estimation and comparison methodology using a process-based life cycle assessment (LCA) study, with a focus on benchmarking environmental sustainability. Results indicate that the alkali activated soil filter cake reduced total GHG emissions by 31% compared with CEM-I, which equates to 110 kgCO2-eq/m3. Transportation by rail was found to be more sustainable compared with by road, with an overall higher GHG emission reduction of between 5 and 10%. For road transport, heavy goods vehicles (HGV) of between 3.5t and 5.7t recorded the highest GHG emissions whilst articulated lorries recorded the lowest GHG emissions. Furthermore, the results also demonstrated that a bulk carrier is the most environmentally sustainable option for overseas raw material transportation. Monte-Carlo simulations signified the likelihood of achieving lowered GHG emissions when considering commercial production and inventory changes across different countries varies from 18% to 71%. These results highlight the importance of critical analysis of several factors which contribute towards overall environmental sustainability, prior to decision making on sustainable materials. Further research is encouraged on developing processes and methodologies to prioritize selection of sustainable materials to optimize sustainable benefits.

Numerical Simulation of the Evacuation Process in a Tunnel during Contraflow Traffic Operations

The purpose of this numerical research is to assess the evacuation process in a tunnel under the contraflow condition. Numerical simulations utilizing FDS+Evac codes associated with a fire dynamic simulator (FDS) model simulating a fire scenario are used to simulate evacuation and to predict the impact of a 100 MW fire scenario on the occupants inside the tunnel. Traffic and passenger conditions are based on real data from a tunnel in the UK. Two fire loads, 100 MW and 5 MW, are studied to represent an HGV and a passenger car fire. The 100 MW fire source, caused by an unexpected heavy good vehicle (HGV) catching fire, is located in the middle of the tunnel and at 20% of tunnel length to study the effect of fire source location on the usage of emergency exits and tenability thresholds. The dimensions and the inclination angle of the existing roadway tunnel are 1836 m (L) × 7.3 m (W) × 5 m (H) and 4%, respectively. It should be noted that the 4% inclination of the tunnel causes asymmetry propagation of smokes thus the visibility of the downstream and upstream from the fire behave differently. The maximum needed time to evacuate using all egress, the amount of fractional effective dose and visibility at the human’s height are analyzed. Simulation results indicate that when a realistic worst-case fire scenario is modeled, all evacuees can survive before the combustion gases and heat influence their survivability.

Modelling fire occurrences in heavy goods vehicles in road tunnels

The project reported in this paper has been organized to scrutinize current incident data on near fires and fully developed fires in Norwegian road tunnels longer than 500 m. This length is chosen because it is assumed that shorter tunnels are less critical in case of fires. The project included collecting data and transferring it into formats enabling mathematical modelling. The major issue of this work has been to resolve: What are the major contributing tunnel infrastructure factors leading to heavy goods vehicle (HGV) fires in Norwegian tunnels? By using Poisson regression modelling, several models are developed showing good fit with the observations. All models reveal that slope, length, annual average daily traffic of heavy goods vehicles, and whether a tunnel is subsea are significant factors. The most important is the subsea factor, and the effect of other risk factors is also more severe for subsea tunnels. The work also discusses weaknesses in the data material and the fact that there are several other interesting factors, for example related to the state of HGVs and driver behavior that are currently missing. The research potential for better modelling and understanding of HGV fires in tunnels is huge.

What is the energy balance of electrofuels produced through power-to-fuel integration with biogas facilities?

The need to reduce the climate impact of the transport sector has led to an increasing interest in the utilisation of alternative fuels. Producing advanced fuels through the integration of anaerobic digestion and power-to-fuel technologies may offer a solution to reduce greenhouse gas emissions from difficult to decarbonise modes of transport, such as heavy goods vehicles, shipping, and commercial aviation, while also offering wider system benefits. This paper investigates the energy balance of power-to-fuel (power-to-methane, power-to-methanol, power-to-Fischer-Tropsch fuels) production integrated with a biogas facility co-digesting grass silage and dairy slurry. Through the integration of power-to-methane with anaerobic digestion, an increase in system gross energy of 62.6% was found. Power-to-methanol integration with the biogas system increased the gross energy by 50% while power-to-Fischer-Tropsch fuels increased the gross energy yield by 32%. The parasitic energy demand for hydrogen production was highlighted as the most significant factor for integrated biogas and power-to-fuel facilities. Consuming electricity that would otherwise have been curtailed and optimising the anaerobic digestion process were identified as key to improving the energetic efficiency of all system configurations. However, the broad cross-sectoral benefits of the overarching cascading circular economy system, such as providing electrical grid stability and utilising waste resources, must also be considered for a comprehensive perspective on the integration of anaerobic digestion and power-to-fuel.