Trends in the impact of socioeconomic developments on polycyclic aromatic hydrocarbon concentrations in Dianchi Lake

An analysis of the correlation between polycyclic aromatic hydrocarbons (PAHs) and economic parameters demonstrates that the total population, gross domestic product, coal consumption, petroleum, temperature, and day consumption significantly affect PAH concentrations in Dianchi Lake, Yunnan province, China. An artificial neural network (ANN) model was developed to predict the trend in PAH concentrations in the sediments of Dianchi Lake over the next 10 years based on current indicators of economic development. The ANN model estimated the concentration of PAHs from 1980 to 2014. The model was evaluated using available observations for the historical trends; concentrations of PAHs in the sediments of Dianchi Lake are calculated to be at 2128.1 ng/g in 2025 and are expected to decline up to 1044.3 ng/g by 2030. These concentrations are considered relatively high because of their impacts on the health of people and aquatic organisms and the development of surrounding industries. We show the importance of the socioeconomic and climate factors in increasing the pollution levels. Our results could support the local government to formulate effective measures to reduce the pollution levels in the lake.

Automated summary

The correlation between polycyclic aromatic hydrocarbons (PAHs) and economic parameters in Dianchi Lake, Yunnan province, China, was analyzed, showing significant impact of total population, GDP, energy consumption, etc. An artificial neural network (ANN) model was developed to predict the trend in PAH concentrations in the sediments over the next 10 years. Results indicate the importance of economic and climate factors in increasing pollution levels.