English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The purpose of this paper is to calculate the external noise cost of China’s high-speed railway and forecast its future trend. Firstly, the unit value transfer method after correction is selected as a method of calculation. Secondly, the noise cost calculation model of China’s high-speed railway is established by introducing the correction factors such as GDP-PPP, population density ratio and CPI ratio. At last, the external noise cost since the opening of high-speed railway is calculated. The model validation results show that although the average external noise cost of high-speed railway increases year by year, it does not increase significantly. This is not only related to economic growth and improvement of noise reduction technology, but also related to the increase of investment in noise reduction facilities in the early stage. Compared with it, the total external cost of high-speed railway noise increases obviously, which is positively related to the rapid development of high-speed railway. With the increase of high-speed railway mileage and passenger turnover, the total noise cost increases significantly. It can be predicted that with the implementation of high-speed railway planning in the future, the negative external cost of noise will continue to increase.

Negative External Cost Computing Model for Noise of China’s High-speed Railway and its Verification and Trend Analysis