An ensemble multi-scale framework for long-term forecasting of air quality.

The significance of accurate long-term forecasting of air quality for a long-term policy decision for controlling air pollution and for evaluating its impacts on human health has attracted greater attention recently. This paper proposes an ensemble multi-scale framework to refine the previous version with ensemble empirical mode decomposition (EMD) and nonstationary oscillation resampling (NSOR) for long-term forecasting. Within the proposed ensemble multi-scale framework, we on one hand apply modified EMD to produce more regular and stable EMD components, allowing the long-range oscillation characteristics of the original time series to be better captured. On the other hand, we provide an ensemble mechanism to alleviate the error propagation problem in forecasts caused by iterative implementation of NSOR at all lead times and name it improved NSOR. Application of the proposed multi-scale framework to long-term forecasting of the daily PM2.5 at 14 monitoring stations in Hong Kong demonstrates that it can effectively capture the long-term variation in air pollution processes and significantly increase the forecasting performance. Specifically, the framework can, respectively, reduce the average root-mean-square error and the mean absolute error over all 14 stations by 8.4% and 9.2% for a lead time of 100 days, compared to previous studies. Additionally, better robustness can be obtained by the proposed ensemble framework for 180-day and 365-day long-term forecasting scenarios. It should be emphasized that the proposed ensemble multi-scale framework is a feasible framework, which is applicable for long-term time series forecasting in general.

Latent negative precipitation for the delineation of a zero-precipitation area in spatial interpolations.

The spatial interpolation of precipitation has been employed in a number of fields, including by spatially downscaling the Global Circulation Model (GCM) to a finer scale. Most precipitation events become more sporadic when the coverage area increases (i.e., a portion of the points experience zero precipitation). However, spatial interpolations of precipitation generally ignore these dry areas, and the interpolated grids are filled with certain precipitation amounts. Subsequently, no delineation of dry and wet regions can be made. Therefore, the current study suggested a novel approach to determine dry areas in spatial interpolations of precipitation events by assigning latent negative precipitation (LNP) to points with observed precipitation values of zero. The LNP-assigned points are then employed in a spatial interpolation. After that, the dry region can be determined using the negative region (i.e., points with zero precipitation). The magnitude of LNP can be defined by multiplying the precipitation values of neighboring stations by a tuning parameter. The LNP method and the tuning parameter are tested on weather stations covering South Korea. The results indicate that the proposed LNP method can be suitable for the spatial interpolation of precipitation events by delineating dry and wet regions. Additionally, the tuning parameter plays a special role in that it increases in value with longer precipitation durations and denser networks. A value of 0.5-1.5 can be suggested for the tuning parameter as a rule of thumb when high accuracy for final products of interpolated precipitation is not critical. For future studies, the LNP model derived herein can be tested over much larger areas, such as the United States, and the model can also be easily adopted for other variables with spatially sporadic values.

Serial Multiple Mediation Analyses: How to Enhance Individual Public Health Emergency Preparedness and Response to Environmental Disasters.

Recent environmental disasters have revealed the government's limitations in real-time response and mobilization to help the public, especially when disasters occur in large areas at the same time. Therefore, enhancing the ability to prepare for public health emergencies at the grassroots level and extend public health emergency response mechanisms to communities, and even to individual families, is a research question that is of practical significance. This study aimed to investigate mechanisms to determine how media exposure affects individual public health emergency preparedness (PHEP) to environmental disasters; specifically, we examined the mediating role of knowledge and trust in government. The results were as follows: (1) knowledge had a significant mediating effect on the relationship between media exposure and PHEP; (2) trust in government had a significant mediating effect on the relationship between media exposure and PHEP; (3) knowledge and trust in government had significant multiple mediating effects on the relationship between media exposure and PHEP.

Integrating nonstationary behaviors of typhoon and non-typhoon extreme rainfall events in East Asia.

Extreme rainfall events in East Asia can be derived from the two subcomponents of tropical cyclones (TC) and non-TC based rainfall (mostly summer monsoons). Critical natural hazards including floods and landslides occur repeatedly due to the heavy rainfall associated with the two subcomponents, and disaster losses are increasing because global warming has caused changes in the extreme rainfall characteristics of two subcomponents. Subsequently, the frequency and intensity of extreme rainfall have reportedly become nonstationary. The majority of literature on nonstationary frequency analyses do not account for the different behaviors (stationarity or nonstationarity) of annual maximum rainfall (AMR) from the two subcomponents (PM TC and PM NTC ). To carry out a nonstationary frequency analysis considering the different behaviors of the PM TC and PM NTC series, this study proposes a novel approach of integrating the fitted PM TC and PM NTC series after modeling the nonstationarity of the PM TC and PM NTC series individually. The presented results conclude that the proposed approach provides more reliable estimates than existing nonstationary approaches by reflecting the different features of the PM TC and PM NTC series. We suggest that the proposed approach provides a reasonable design rainfall in constructing hydraulics to mitigate the different nonstationary effects of two TC and non-TC rainfall extremes.