The potential risks and exposure of Qinling giant pandas to polycyclic aromatic hydrocarbon (PAH) pollution

Rapid industrialization and urbanization have created a substantial urban-rural gradient for various pollutants. The Qinling Mountains are highly important in terms of biodiversity, providing habitat for giant pandas, which are endemic to China and are a widely recognized symbol for conservation. Whether polycyclic aromatic hydrocarbon (PAH) exposure risks regarding in situ animal conservation zones are affected by environmental pollution or even enhanced by the mountain-trapping effect requires further research. Our group carried out a large-scale investigation on the area ranging from Xi'an to Hanzhong across the giant panda habitat in the Qinling Mountains by collecting atmosphere, soil, bamboo, and fecal samples from different sites over a two-year period. The total toxicity of atmospheric PAHs and the frequencies of soil PAHs above effect range low (ERL) values showed a decreasing trend from urban areas to the central mountains, suggesting a distance effect from the city. The proportions of total 5- and 6-ring PAHs in the atmosphere were higher in the central mountainous areas than in the urban areas, while this difference was reversed in the soil. Health risk assessments showed that the incremental lifetime carcinogenic risks (ILCR) of PAH exposure by bamboo ingestion ranged from 2.16 × 10−4 to 3.11 × 10−4, above the critical level of 10−4. Bamboo ingestion was the main driver of the PAH exposure risks. The concentration difference between bamboo and fecal samples provided a reference for the level of PAHs absorbed by the panda digestive system. Since the Qinling Mountains possess the highest density of giant pandas and provide habitats to many other endangered animal and plant species, we should not ignore the probability of health risks posed by PAHs. Monitoring the pollution level and reducing the atmospheric emissions of toxic pollutants are recommended actions. Further detailed research should also be implemented on pandas' health effects of contaminant exposure.