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Data and code for: Explainable machine learning revealed the conditional response of biogenic isoprene to the changes in environmental factors at an urban site in the Yangtze River Delta, China

Citation

Qin, Yiming (2022), Data and code for: Explainable machine learning revealed the conditional response of biogenic isoprene to the changes in environmental factors at an urban site in the Yangtze River Delta, China, Dryad, Dataset, https://doi.org/10.7280/D1PM5M

Abstract

Biogenic isoprene is highly sensitive to environmental conditions while the confounding factors makes it challenging to identify the causal response. We report here an enhanced isoprene concentration from biogenic source during May to October at an urban site in the Yangtze River Delta, China. Random forest coupled with Shapley additive explanations dependence algorithm was used to determine the conditional response of biogenic isoprene to the changes in environmental factors. The conditional response of isoprene concentration exponentially increased as temperature increased, in line with previous laboratory control experiment. Sharp increase in isoprene concentration was observed with the onset of solar radiation but remained unchanged at higher solar radiation. A near-linear decrease in isoprene was evident as O3 increased. These results show how the biogenic isoprene concentration responds to a changing environmental condition without confounding factors, provide parameterization of isoprene in local air quality and vegetation-climate feedback.