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Quantifying Litter Emissions into the Swiss Environment - A bottom-up approach focusing on roads
Summary
Researchers quantified litter emissions from roads into the Swiss environment using a bottom-up measurement approach. They found that road-side littering is one of the largest pathways for plastic entry into Swiss ecosystems, contributing substantially to microplastic loads in soil and water. The study provides quantitative data to support litter reduction campaigns and policy interventions.
The global plastic production is steadily growing and with it the public and scientific concern about micro-and macroplastic emissions into the environment.According to a recent study by EMPA, the largest input of plastics into the Swiss environment is littering 1 .However, this is based on uncertain assumptions as, even though littering is a well-known issue, no quantitative data exist.In this project, littering along roadsides and its input into the environment were experimentally quantified.A mathematical model calculates the sweeping efficiency considering the accuracy of the road workers, the cleaning intervals and the probability of a certain object to be carried away by wind, depending on the object type and its underlying vegetation.Corresponding experiments were designed and carried out.The collected data of roadside litter were extrapolated to Switzerland based on the daily traffic volume and road lengths.A GIS analysis was performed to determine what environments border Swiss roads.The following figure shows the resulting material flows.Every year 252100 tons of plastic are released into the environment.This value is 13 times lower than the one calculated in the above-mentioned study, which is not based on measurements but uses literature values and assumptions.One reason for this difference is the higher sweeping efficiency of roadworkers and farmers calculated in this project.For example, 90% of the littered PET bottles, cigarette boxes and aluminum cans are collected and do not end up in the environment.Sensitivity analysis and testing of the underlying assumptions show that the presented model provides reliable results and can generate important insights for science and politics.