Improved space-time mapping of PM2.5 distribution using a domain transformation method.

The present work uses a new space-time projection (STP) technique to study the distribution of PM 2.5 concentrations in one of the most populous, highly developed and highly polluted regions in China, the Shandong Province, during the period Jan 1–31, 2014. The theoretical and interpretational features of the STP technique are pointed out. A key feature of the technique is that it transfers the study of pollutant distribution from the original space-time domain R 2 × T onto a traveling domain of lower-dimensionality R 2 that moves in the pollutant spread direction; analysis and computations are much easier in the R 2 domain, avoiding the complexities of the R 2 × T domain; and the results are back-transformed to the original R 2 × T to generate space-time PM 2.5 concentration maps over the entire region of interest. The Shandong study shows that the proposed STP technique has certain noteworthy analytical and computational advantages over mainstream mapping techniques of higher dimensionality (like space-time ordinary kriging, STOK): it avoids serious difficulties associated with space-time metric determination and variogram estimation in the original space-time domain, it allows the selection of more appropriate variogram models representing the PM 2.5 variation, it generates more accurate PM 2.5 maps, and it is also a computationally more efficient technique than the STOK technique. [ABSTRACT FROM AUTHOR]