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Mesoscale eddies (MEs) affect the transport and redistribution of oceanic matter and energy. The long-lived and long-distance propagation of individual eddies has garnered extensive attention; however, short-lived MEs (< 7 days) have been widely overlooked. In this study, the basic features of short-lived MEs and their spatial-temporal variations in a tropical eddy-rich region were extracted and analyzed for the first time. Short-lived cyclonic and anticyclonic eddies (CEs/AEs) were found to be widespread in two eddy belts in the tropical region of the western Pacific warm pool (WPWP). The CEs and AEs were formed by the shear instability between large-scale circulations and were distributed on both sides of the North Equatorial Countercurrent, with significant differences in spatial distribution. The variations in sea surface temperature, mixed layer depth, and surface chlorophyll-a concentration in the core of the WPWP were spatially and temporally related to the development of the two eddy belts. This new insight into short-lived MEs in the tropical region contributes to our current understanding of ocean eddies. The potential impacts of short-lived MEs on climate change, global air–sea interactions, and tropical cyclone formation should receive adequate attention and further assessment in future research.

Ecological vulnerability assessment of wetlands is a very important early-stage task for wetland protection, pollution treatment, ecological restoration and water resources utilization. On the basis of the study of vulnerability evolution mechanism of wetland ecosystem in the Yellow River Delta, this paper proposes a Pressure-Support-State-Response Model (PSSR) for ecosystem vulnerability assessment and employs a single-factor evaluation method. The proposed model is applied to assessing ecosystem vulnerability of wetland in Yellow River Delta (a case study of Dongying City). Research results show that: from 2005 to 2009, the ecosystem vulnerability of wetlands in Yellow River Delta was 0.62, and 0.68 from 2010 to 2014; the ecosystem vulnerability grade is moderately vulnerable during the two periods. Generally speaking, regional ecosystem vulnerability slightly decreases. More efforts should be made to protect and restore the ecosystem and prevent it from deterioration and wetlands degradation. This study may provide a theoretical support for wetland protection, management, exploitation and policy making in the Yellow River Delta.

By means of analyzing formation mechanism and impact factors of ecological vulner-ability of estuarine wetland of the Yellow River Delta, an ecological vulnerability assessment index system based on relevant criteria is constructed. Criteria include resource and environment, human factors and ecological balance. There are 14 indexes which are Annual mean temperature difference, population density, saline-alkali soil area, average annual frost-free period and so on. An assessment model based on entropy weight is further constructed by using entropy method and is applied in the ecological vulnerability assessment. Research results show that mildly vulnerable area occupies 25.87% of total estuarine wetland of the Yellow River Delta. Mildly vulnerable area is where there are abundant natural resources, ecosystem functions well and human activities have weak influence. General vulnerable area takes 15.93% where fresh water supplement is adequate and ecosystem functions averagely. Moderately and severel...

Air pollution has been increasingly highlighted in China with the fast-paced development of industrialization, which has drawn a great deal of attention from the general public. In order to provide guidance on the reduction of air pollution, an accurate forecasting of air quality index (AQI) plays a vitally important role. To ensure an accurate forecasting of AQI while improving the accuracy of forecasting, three single forecasting models, radial basis function neural network (RBFNN), ensemble empirical mode decomposition and RBFNN (EEMD-RBFNN), EEMD-RBFNN and autoregressive integrated moving average model (EEMD-RBFNN-ARIMA) are incorporated into the combination forecasting model (CFM) through weight assignment. Despite the study of AQI forecasting performed in Zhengzhou and Shanghai China, the results demonstrate that: the forecasting effect of the sub-component of the influencing factors as the input of the network is more desirable than that of the influencing factors taken as the input of the network, the CFM is superior to the remaining three single models, and the forecasting effect of inverse variance method is better compared to the mean square error method and the simple weighted average method. Therefore, the CFM constructed using different weight methods provides a new approach to AQI forecasting.