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In the high-speed-rail (HSR) construction boom of China, although some cities have upgraded old train stations in inner cities to be compatible with HSR, more cities have built new HSR stations on undeveloped land in the urban periphery. This study investigates the impact of intra-city access to inter-city transport nodes and explores the implications of HSR station locations for the accessibility and residential property values in Chinese cities connected by bullet trains. We find that for the cities with HSR stations in suburbs, the gains in inter-city travel brought by HSR are largely offset by the prolonged intra-city travel time to reach the stations, thus limiting frequent usage of HSR for daily commuting. The inner-city HSR station in Hangzhou shows a positive impact on residential property value in the vicinity, while the suburban HSR station in Guangzhou has not been observed to raise the residential property values noticeably in the short term despite the government’s intention to stimulate development in surrounding areas. The research findings show the need for better connections of HSR stations with the city to magnify the accessibility provided by HSR and careful integrated planning to promote desirable urban development outcomes in station areas.

Sea-Level Rise (SLR) Projections from the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Army Corp of Engineers (USACE) indicate increasing, and imminent, risk to coastal communities from tidal flooding and hurricane storm surge. Building on recent research related to the potential demographic impacts of such changes (Hauer et al. 2016, in Nat Clim Chang 3:802-806, 2017; Neumann et al. 2015; Curtis and Schneider in Popul Environ 33:28-54, 2011), localized flooding projections in the Miami Beach area (Wdowinski et al. in Ocean Coast Manag 126:1-8, 2016) and projected economic losses associated with this rise in projected SLR (Fu et al. Ocean Coast Manag 133:11-17, 2016); this research investigates the accrued current cost, in terms of real-estate dollars lost, due to recurrent tidal flooding and projected increases of flooding in Miami-Dade County. Most directly related to this line of research, Keenan et al. (2018) have recently produced results indicating that Climate Gentrification is taking place in Miami, FL with higher elevations in flood prone areas appreciating at a higher rate. In that vein of thinking, we seek to answer a question posed by such research: What is the actual accrued loss to sea-level rise over the recent past! To answer this question, we replicate well-documented estimation methods by combining publicly available sea-level rise projections, tide gauge trends, and property lot elevation data to identify areas regularly at risk of flooding. Combining recent patterns of flooding inundation with future forecasts, we find that properties projected to be inundated with tidal flooding in 2032 have lost $3.08 each year on each square foot of living area, and properties near roads that will be inundated with tidal flooding in 2032 have lost $3.71 each year on each square foot of living area. These effects total over $465 million in lost real-estate market value between 2005 and 2016 in the Miami-Dade area.

Making our cities more sustainable includes the need to make the transition a just one. This paper focuses on distributive justice with regard to greenspace in cities. Urbanisation and densification will likely result in less greenspace in urban residential areas, especially in deprived neighbourhoods. This is a threat to the aim of healthy and liveable cities, as greenspace has positive effects on human health and well-being. In this study, we show that in The Netherlands, neighbourhoods with a low socioeconomic status already tend to have a lower presence and quality of greenspace than those with a high socioeconomic status. This outcome is independent of the greenness metric that was used. However, depending on the precise greenness metric, socioeconomic differences in greenness between neighbourhoods are smaller in highly urban municipalities than in less urban municipalities, rather than larger. The paper discusses the implications of these outcomes for policy and planning regarding urban greenspace.

Higher consumption of ‘ultra-processed’ (UP) foods has been linked to adverse health outcomes. The present paper aims to characterise percentage energy from UP foods by participant socio-economic status (SES), diet quality, self-reported food expenditure and energy-adjusted diet cost. Participants in the population-based Seattle Obesity Study III (n 755) conducted in WA in 2016–2017 completed socio-demographic and food expenditure surveys and the FFQ. Education and residential property values were measures of SES. Retail prices of FFQ component foods (n 378) were used to estimate individual-level diet cost. Healthy Eating Index (HEI-2015) and Nutrient Rich Food Index 9.3 (NRF9.3) were measures of diet quality. UP foods were identified following NOVA classification. Multivariable linear regressions were used to test associations between UP foods energy, socio-demographics, two estimates of food spending and diet quality measures. Higher percentage energy from UP foods was associated with higher energy density, lower HEI-2015 and NRF9.3 scores. The bottom decile of diet cost ($216·4/month) was associated with 67·5 % energy from UP foods; the top decile ($369·9/month) was associated with only 48·7 % energy from UP foods. Percentage energy from UP foods was inversely linked to lower food expenditures and diet cost. In multivariate analysis, percentage energy from UP foods was predicted by lower food expenditures, diet cost and education, adjusting for covariates. Percentage energy from UP foods was linked to lower food spending and lower SES. Efforts to reduce UP foods consumption, an increasingly common policy measure, need to take affordability, food expenditures and diet costs into account.

Noise exposure has reached an alarming degree over the years because of rapid growth in the industry, transportation, and urbanization. Therefore, it is a dire need to provide awareness of the sources and mitigation strategies of noise, and to highlight the health, and socio-economic impacts of noise. A few research studies have documented this emerging issue; however, there is no comprehensive document describing all types of noise, their impacts on living organisms, and control strategies. This review article summarizes the sources of noise; their effects on industrial workers, citizens, and animals; and the value of property in noisy areas. The plethora of literature is showing an increased level of noise in various cities of the world, which have various health consequences such as high blood pressure, insomnia, nausea, heart attack, exhaustion, dizziness, headache, and triggered hearing loss. Apart from humans, noise also affects animal habitat, preying, and reproduction ability; increases heart rate and hearing loss to even death and loss in property value; and impairs the hospital environment. Finally, we have discussed the possible strategies to mitigate the noise problem, policy statements, and regulations to be followed, with future research directions based on the identified research gaps.

The South Korean government plans to switch from a centralized power generation method to a distributed one. However, due to opposition from local residents, construction of distributed power plants is frequently delayed or suspended. This study attempts to investigate whether proximity to a power plant negatively affects housing property values, using the hedonic pricing technique and quantitatively analyzing the level of impact. To this end, 2291 apartment sales data from a specific city in the South Korean Seoul Metropolitan area with a power plant were used. As a result of the analysis, it was found that proximity to a power plant had a negative effect on apartment prices, which was statistically significant at the significance level of 5%. The difference in apartment prices per 1 km direct distance from the power plant to the apartment was derived as KRW 8 million (USD 7.1 thousand). This value is about 0.7% of the average price of apartments in the area (KRW 1102 million = USD 0.98 thousand). The results of this study can be used as a useful reference when the government determines the size of subsidies for local residents near power plants.

This study assesses the impact of proximity to light rail transit stations on residential property values in Buffalo, New York, where light rail has been in service for 20 years, but population is declining and ridership is decreasing. Hedonic models are constructed of assessed value for residential properties within half a mile of 14 light rail stations and independent variables are included that describe property characteristics, neighbourhood characteristics and locational amenities. The model suggests that, for homes located in the study area, every foot closer to a light rail station increases average property values by $2.31 (using geographical straight-line distance) and $0.99 (using network distance). Consequently, a home located within one-quarter of a mile radius of a light rail station can earn a premium of $1300-3000, or 2-5 per cent of the city's median home value. Model results further suggest that three independent variables—the number of bathrooms, size of the parcel and location on the East side or West side of Buffalo—are more influential than rail proximity in predicting property values. Individual regression models for each of the light rail system's 14 stations suggest that effects are not felt evenly throughout the system. Proximity effects are positive in high-income station areas and negative in low-income station areas. An analysis of the actual walking distance to stations (along the street network) versus the perceived proximity to stations (measured by straight-line distance) reveals that the results are statistically more significant in the network distance than the straight-line distance model, but the effects are greater in the straight-line distance model, which suggests that apparent proximity to rail stations is an added locational advantage compared with physical walking distance to the station.

This study investigates the spatial effects of the service frequency and transport interchange facilities of rail stations on residential property values for the entire metropolitan train network in Melbourne. Residential properties are classified as either detached or attached dwellings. Given that a traditional hedonic price model cannot handle the spatial dependence and spatial non-stationarity of the housing market, several geographically weighted regression (GWR) models are used and multicollinearity is considered; the model with the Euclidean distance metric outperforms others. Results indicate that the service frequency and facilities of the stations influence the residential property values in a spatially variable way. For every 1 km closer to the train stations, an increase in the frequency of the train services per unit results in a change in the residential property values ranging from −4.01% to 2.71%; an improvement in the transport interchange facilities per unit results in a change in the residential property values ranging from −29.93% to 47.04%. Crime and retail activities that indirectly affect the relationship between rail stations and residential property values are also identified. For every 1 km closer to the train stations, the crime density increases significantly from 5.64% to 42.88% and this occurs in one-fifth of the areas in Melbourne. In contrast, the relationship between retail activities and train stations remains spatially stable. This study complements the relatively scarce literature on the link between railway service levels and residential property values while extending the case study to the local level. 本研究调查了墨尔本整个列车网络的车次频率和交通换乘设施对住宅物业价值的空间影响。住宅物业分为独立住宅和多户住宅。鉴于传统的特征价格模型无法处理住房市场的空间依赖性和空间非平稳性，我们采用了几个地理加权回归 (GWR) 模型，并考虑了多重共线性；欧几里德距离度量的模型优于其他模型。结果表明，火车站的车次频率和设施对住宅物业价值的影响随着空间距离而变动。每靠近火车站 1 公里，列车车次频率每增加一个单位，对住宅物业价值的影响从提升 24.01% 到提升 2.71% 不等；每增加一个交通换乘设施，对住宅物业价值的影响从提升 229.93% 至提升 47.04% 不等。研究还确定了间接影响火车站与住宅物业价值之间关系的犯罪活动和零售活动。每靠近火车站 1 公里，犯罪密度显著增加 5.64% 到 42.88%，这一数据覆盖墨尔本五分之一的地区。相比之下，零售活动与火车站之间的关系在空间距离变化情况下保持稳定。关于铁路运行水平与住宅物业价值之间的联系，现有研究文献相对稀缺，本研究填补了一定空白，并将案例研究扩展到局域空间分析的层面

Estimating the effect of rail transit on residential property values has resulted in mixed findings. Some researchers report positive effects on property values while others are negative or insignificant. The current paper argues that the impact of rail transit on property values depends on contextual factors which can influence magnitude and direction of the impact and cause variation in the findings. Tehran’s Metro Rail System is chosen because the neighbourhoods served by the metro to the north side and south side of the city are dramatically different in terms of economic, social and physical circumstances. A comparative analysis of six of Tehran’s metro stations is conducted between the high-income neighbourhoods, which are located primarily on the city’s north side, and lower-income neighbourhoods on the south side to determine the effects of proximity to metro stations on residential property values. The paper uses a mixed-method sequential explanatory design based on a before-and-after estimation strategy, which includes trend analysis, difference-in-differences model and qualitative impact assessment methods. The results show that there are large increases in premiums for residential properties near the lower-income neighbourhoods, the south side parts of the Tehran Metro Rail System, while a negative treatment effect for residential properties lying close to the northern stations in the high-income neighbourhoods. The qualitative survey also suggests that the impact of metro station is affected by a number of contextual factors, including the need for public transportation, land-use planning and management, socio-cultural effect and possible nuisance effects. 估算轨道交通对住宅价值的影响产生了各种不同的发现。一些研究者报告轨道交通对物业价值有积极的影响，而另一些则报告说是负面的或微不足道的。本文认为，轨道交通对物业价值的影响取决于各个背景因素，可能形成不同的影响规模和方向，并导致调查结果的差异。选择德黑兰的地铁系统是因为地铁服务的城市北部和南部居住区在经济、社会和物理环境方面存在巨大差异。我们对德黑兰六个地铁站主要位于北城的高收入居住区与主要位于南城的低收入居住区做了比较分析，以确定邻近地铁站对住宅物业价值的影响。本文采用了基于前后估计策略的混合法序列解释设计，其中包括趋势分析、差异中的差异模型和定性影响评估方法。结果显示，德黑兰地铁系统南部低收入社区附近的住宅大幅溢价，而对于高收入地区靠近北部地铁站的住宅物业，地铁系统产生了负面效果。定性调查还表明，地铁站的影响受到一系列背景因素的影响，包括对公共交通的需求、土地利用规划和管理、社会文化影响以及可能的滋扰效应。

Railway stations function as nodes in transport networks and places in an urban environment. They have accessibility and environmental impacts, which contribute to property value. The literature on the effects of railway stations on property value is mixed in its finding in respect to the impact magnitude and direction, ranging from a negative to an insignificant or a positive impact. This paper attempts to explain the variation in the findings by meta-analytical procedures. Generally the variations are attributed to the nature of data, particular spatial characteristics, temporal effects and methodology. Railway station proximity is addressed from two spatial considerations: a local station effect measuring the effect for properties with in 1/4 mile range and a global station effect measuring the effect of coming 250 m closer to the station. We find that the effect of railway stations on commercial property value mainly takes place at short distances. Commercial properties within 1/4 mile rang are 12.2% more expensive than residential properties. Where the price gap between the railway station zone and the rest is about 4.2% for the average residence, it is about 16.4% for the average commercial property. At longer distances the effect on residential property values dominate. We find that for every 250 m a residence is located closer to a station its price is 2.3% higher than commercial properties. Commuter railway stations have a consistently higher positive impact on the property value compared to light and heavy railway/Metro stations. The inclusion of other accessibility variables (such as highways) in the models reduces the level of reported railway station impact. [PUBLICATION ABSTRACT]