Pyrolysis of mixed engineering plastics: Economic challenges for automotive plastic waste.

Chemical recycling of complex plastic waste via pyrolysis can reduce fossil resource dependence of the plastics value chain and greenhouse gas emissions. However, economic viability is crucial for its implementation, especially considering challenging waste streams with high shares of engineering plastics that have lower pyrolysis product quality than standard thermoplastics waste. Thus, this study conducts a techno-economic assessment determining the profitability factors of pyrolysis plants for automotive plastic waste in Germany including different plant capacities and calculating cost-covering minimum sales prices for the resulting pyrolysis oil. Main findings are that due to economies of scale, the cost-covering minimum sales prices vary between 1182 €/Mg pyrolysis oil (3750 Mg input/year) and 418 €/Mg pyrolysis oil (100,000 Mg input/year). The pyrolysis technology employed must be robust and scalable to realize these economies of scale. Large plant capacities face challenges such as feedstock availability at reasonable costs, constant feedstock quality, and pyrolysis oil quality, affecting pyrolysis oil pricing. Due to the limited yield and quality of pyrolysis oil produced from these technically demanding feedstocks, policy implications are that additional revenue streams such as gate fees or subsidies that are essential to ensure a positive business case are necessary. Depending on the assessed plant capacity, additional revenues between 720 and 59 €/Mg pyrolysis oil should be realized to be competitive with the price of the reference product heavy fuel oil. Otherwise, the environmental potential of this technology cannot be exploited.

Instance dataset for resource-constrained project scheduling with diverging material flows.

This data article describes an instance dataset motivated by the problem of scheduling a project with diverging material flows. Such material flows are released during the execution of the project and are subject to limited processing and storage capacities. Typical examples are nuclear dismantling or other deconstruction/demolition projects, where large amounts of material must be classified, scanned for hazardousness, and processed accordingly. The problem setting is mathematically described as a resource-constrained project scheduling problem with cumulative resources (RCPSP/c). The RCPSP/c deals with finding a project schedule with minimal makespan that satisfies temporal, renewable resource, and cumulative resource constraints. In total, the dataset comprises 192 artificially generated instances that are suitable for testing models and solution methods. In addition, we provide our best found solution for each instance and different modeling variants (e.g., for two types of objective functions). These solutions were computed by heuristic solution methods. The dataset serves as a benchmark for researchers evaluating the performance of solution methods for the RCPSP/c or the more general problem class with resources that can be produced and consumed.

Thermal Bridges on Building Rooftops.

Thermal Bridges on Building Rooftops (TBBR) is a multi-channel remote sensing dataset. It was recorded during six separate UAV fly-overs of the city center of Karlsruhe, Germany, and comprises a total of 926 high-resolution images with 6927 manually-provided thermal bridge annotations. Each image provides five channels: three color, one thermographic, and one computationally derived height map channel. The data is pre-split into training and test data subsets suitable for object detection and instance segmentation tasks. All data is organized and structured to comply with FAIR principles, i.e. being findable, accessible, interoperable, and reusable. It is publicly available and can be downloaded from the Zenodo data repository. This work provides a comprehensive data descriptor for the TBBR dataset to facilitate broad community uptake.