While promoting green and low-carbon transition, clean energy facilities also have externalities, which may lead to opposition and economic losses. There is evidence that the impact of facilities decreases with distance, but existing research make strict assumption on its functional form. In this research work we explore the non-linear relationship between housing transaction prices and distances to the nearest facility without predefined functions combined with spatial smoothing in the hedonic pricing model by taking China as a case-study. We use the housing transaction data from 2015 to 2018 to estimate the distance decay of HRS (Hydrogen Refueling Station) in different regions in the rental and sale markets. The results show that the HRS has a significant negative impact on sale prices, while it has no significant impact on rental prices. In the sale market, for every 1% decrease in the distance, the house prices decrease by 6.62%, and the main impact distance is 3.5 km. In the eastern region, HRS has a significant impact on both rents and prices; in the central and western regions, there may be a positive impact on the rental market, but there is no significant impact in the northeastern region. Based on the empirical results, policy recommendations are given.