Abstract

Long-term control measures for reducing the harmful airborne material, the fine particulate matter (PM2.5), has been vigorously implemented by the Hong Kong government over decades. Comprehensive speciation analysis with trend analysis of the higher time resolution (monthly averaged) time series of the PM2.5 components and source tracers from 2008 to 2017 were thus conducted in this work for the evaluation of the control policies. The time series of pollutants were firstly decomposed using the seasonal and trend decomposition with the locally estimated scatter plot smoothing (LOESS) method1, and the slope of the deseasonalized time series were then quantified by the generalized least squares with the autoregressive moving average model. The PM2.5 was successfully decreased by 40% at a mass reducing rate of -1.5 µgm-3yr-1. Such a reduction was predominantly dominated by the local vehicular emissions, where the nitrate dropped by 66% and elemental carbon by 60%. Notable decline was also observed in sulfate with reduction by 40%, in organic carbon by 23%. Those significant decreasing trends confirmed the effectiveness of controls among local vehicular emissions and sulfur-containing compounds from anthropogenic emissions. The two tracers for biomass burning, levoglucosan and K+, interestingly showed different reduction rate (levoglucosan at -47% vs K+ at -60%), implying that they are likely sourced from different biomass burning types. This data-driven long-term trend analysis is rarely performed due to the hardness of maintaining continuous sampling and speciation analysis for long as a decade, and therefore this work serves as a valuable and thorough assessment of existing measures and insights into the control policy formulation.

Acknowledgements

We thank the Hong Kong Environmental Protection Department (HKEPD) for making part of PM2.5 compositional data available for this work. This work is supported by the Environment and Conservation Fund (ECF99/2017).

Reference

1. Cleveland, R.B.; Cleveland, W.S.; Terpenning, I. J. Off. Stat., 1990, 6, 3.