Vulnerability assessment of coastal tourist attractions to oil spill stress based on a pressure-state-response framework: A case study of the Bohai Sea, China

Abstract

The protection of coastal tourist attractions under oil spill stress requires a more detailed vulnerability assessment approach. In this study, an assessment model for estimating the vulnerability of coastal tourist attractions to oil spills along the Bohai Sea’s coastlines was developed, natural environmental and socioeconomic data were collected, and a geographic information system (GIS) was used. As many as 26 factors were selected for the vulnerability analysis of typical tourist destinations in the littoral area. All of the factors were grouped into different categories according to a pressure-state-response (PSR) framework (pressure parameters, state parameters, and response parameters), and a different rank of importance was assigned to each factor via the analytical hierarchy process. The comprehensive analysis results were calculated and visualized using GIS. The results show that the state and response together strongly affected the vulnerability of the various coastal tourist attractions, while the pressure had less effect on the vulnerability. There were obvious spatial variations among the different coastal tourist destinations. Overall, the coastal tourist attractions surrounding the Bohai Sea were characterized by a high oil spill pressure, high sensitivity, low emergency response capabilities, and high vulnerability. This study provides a reference for vulnerability assessment of tourist destinations under oil spill stress, provides a scientific decision-making basis for the protection of coastal tourist destinations, and is conducive to promoting the healthy development of the coastal tourism industry.

Characteristics and Influencing Factors of the Spatial and Temporal Variability of the Coupled Water–Energy–Food Nexus in the Yellow River Basin in Henan Province

“…The subjective weights obtained via the entropy method are denoted as w j [24][25][26], and the objective weights obtained by the hierarchical analysis method are denoted as c j [27,28]. The weights w j and c j were combined linearly to obtain the final weight, denoted as Q, where Q = ac j + bw j ; a and b denote the relative importance of the objective and subjective weights, and satisfy 0 ≤ a ≤ 1, 0 ≤ b ≤ 1 and a + b = 1.…”