Plastic particles and fluorescent brightener co-modify Chlorella pyrenoidosa photosynthesis and a machine learning approach predict algae growth.

Global release of plastics exerts various impacts on the ecological cycle, particularly on primary photosynthesis, while the impacts of plastic additives are unknown. As a carrier of fluorescent brightener, plastic particles co-modify Chlorella pyrenoidosa (C. pyrenoidosa) growth and its photosynthetic parameters. In general, adding to the oxidative damage induced by polystyrene, fluorescent brightener-doped polystyrene produces stronger visible light and the amount of negative charge is more likely to cause photodamage in C. pyrenoidosa leading to higher energy dissipation through conditioning than in the control group with a date of ETR (II) inhibition rate of 33 %, Fv/Fm inhibition rate of 8.3 % and Pm inhibition rate of 48.8 %. To elucidate the ecological effect of fluorescent brightener doping in plastic particles, a machine learning method is performed to establish a Gradient Boosting Machine model for predicting the impact of environmental factors on algal growth. Upon validation, the model achieved an average fitting degree of 88 %. Relative concentration of plastic particles and algae claimed the most significant factor by interpretability analysis of the machine learning. Additionally, both Gradient Boosting Machine prediction and experimental results indicate a matching result that plastic additives have an inhibitive effect on algal growth.