• Energy Research
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We use extreme regional pollution emergencies to provide new evidence regarding the motivations for corporate social responsibility (CSR). We document that local firms strategically improve CSR to build trust following pollution emergencies, and this is specifically true for highly polluting firms. Firms face different intensities of external pressure from their stakeholders. In particular, following pollution emergencies, political dependency, institutional investors and public monitoring are the main sources of stakeholder pressure and drivers of the increased CSR. We further find that firms that gain trust through CSR activities after pollution emergencies are rewarded. CSR serves as a buffer against financial constraints, financing distress and the negative profitability effect following emergencies. This study contributes to the CSR literature on trust-building-motivated CSR strategies.

Pyrolysis of plastic waste is a key technology for closing the anthropogenic carbon cycle. The energy demand (ED) of this endothermic process is a crucial factor to evaluate its benefits compared to established recycling pathways. The pyrolysis ED can be determined experimentally. However, this is elaborate and limited in transferability. Existing models cover virgin plastics or hydrocarbon thermoplastic mixtures on a laboratory scale. Here, a model for calculating the ED of thermoplastic mixtures based on the superposition of virgin polymer data is developed. The material data, such as heat capacity, phase transition enthalpy, and reaction enthalpy, are determined using differential scanning calorimetry. Pilot-scale experiments are performed in a 1 kg/h screw reactor. These experimental data are compared to model calculations. The feedstock-specific ED for pyrolysis is plastic-type independent. It amounts to approximately 4−6% of the feedstocks’ net calorific value. The validation shows excellent accordance for virgin plastics and hydrocarbon plastics mixtures. The modeled ED of mixtures including heteroatoms is systematically underestimated, which indicates changes in the degradation mechanism. The model allows for resolving several phenomena contributing to the pyrolysis ED. The simple calculation of the ED with in-depth information on occurring phenomena enables more reliable process design, optimization, and evaluation.