Construction and optimization of Green Infrastructure Network in mountainous cities: a case study of Fuzhou, China.

Green infrastructure networks enhance the protection and improvement of urban ecological environments, augment the efficiency and quality of ecosystem services, and furnish residents with healthier and more comfortable living conditions. Although previous research has investigated the construction or optimization methods of green infrastructure networks, these studies have been relatively isolated and lacking in case studies for mountainous cities. In the development of green infrastructure, mountainous cities must specifically consider the impact of terrain on network construction. Taking Fuzhou, a mountainous city in China, as an example, this study constructs and optimizes the green infrastructure network by employing morphological spatial pattern analysis, connectivity analysis, the Minimum Cumulative Resistance model, and circuit theory. These methodologies increase the connectivity of the Green Infrastructure within the study area, thereby promoting the health of the local ecosystem and creating conducive circumstances for the city's sustainable development. The findings reveal that: (1) Green infrastructure in Fuzhou takes up 5366.38 ha, constituting 21.76% of the study area, primarily situated in the northwest and south; (2) Fuzhou's Green Infrastructure network comprises 10 hubs and 17 corridors with a hub area of 1306.98 ha, predominantly distributed in the mountains encircling the city, including Meifeng Mountain, Gaogai Mountain, and Qingliang Mountain; (3) Based on optimization, the circuit centrality index categorizes hub importance into three protection levels, pinpointing nine crucial protected areas in the corridors and 680 areas requiring enhancement, including 68 areas for first-level improvement, 149 areas for second-level improvement, and 463 areas for third-level improvement. This research offers a methodological reference for constructing and optimizing green infrastructure networks in mountainous cities, providing both theoretical and practical foundations for optimizing green infrastructure networks in Fuzhou City.

How does 2D and 3D of urban morphology affect the seasonal land surface temperature in Island City? A block-scale perspective.

The global climate warming caused by urbanization has significantly affected the urban environment. Whilst land surface temperature (LST) is an important factor reflecting urban temperature, previous research on LST mostly focused on two-dimensional (2D) factors and rarely mentioned about the role of three-dimensional (3D) factors, particularly the LST variation characteristics of island cities. Therefore, this study examined the seasonal variation characteristics of urban LST by analyzing the impact of 2D and 3D urban morphology factors of different urban block types on LST in Xiamen Island. The main results are as follows. First, compact low layer (CL), a block type with a higher density of low-rise buildings, has a higher LST in any season. Under the same block density (BD), the higher the block average height (BH), the lower the LST. Second, among the 2D urban morphology factors, normalized difference vegetation index (NDVI) was the main factor for cities to reduce urban LST, especially in summer, while normalized difference built-up index (NDBI) was the opposite. Different from land cities, we found a positive correlation between modified normalized difference water body index (MNDWI) and LST in autumn and winter. Third, in the 3D urban morphology factors, sky view factor (SVF) was significantly positively correlated with LST, while building fluctuation (BF) was negatively correlated. The higher the SVF, the worse the radiation shielding effect between buildings. On the contrary, the higher the BF, the higher the building undulation, and the better the building radiation shielding. These findings should provide some quantitative insights for the future construction and planning of island cities, which can be used to improve the thermal environment of island cities and support the sustainable development of cities.

Factors Influencing Users' Perceived Restoration While Using Treetop Trails: The Case of the Fu and Jinjishan Forest Trails, Fuzhou, China.

Studies have indicated that urban greenways promote physical and perceived restoration. However, there is a lack of research on the impact of treetop trails on human perceived restoration. In this study, two representative treetop trails in Fuzhou city were selected to investigate treetop trails' impact on users' perceived restoration. The study adopted a structural equation modelling approach to explore the influence mechanisms and pathways of treetop trails on users' perceived restoration, through 412 questionnaires. The results showed that the perceived environmental quality of treetop trails had a significant positive effect on users' overall psychological wellbeing. Place attachment had a significant positive effect on users' perceived restoration and a significant mediating effect on users' perceived environmental quality of trails. The results of this study revealed that the mechanisms of the impact of treetop trails on users' perceived restoration and the construction of treetop trails can be enhanced in the future by improving trail facilities, enriching trail perception of elevated feeling, improving trail landscape quality, and optimising trail design.

The Relationships between Perceived Design Intensity, Preference, Restorativeness and Eye Movements in Designed Urban Green Space.

Recent research has demonstrated that landscape design intensity impacts individuals' landscape preferences, which may influence their eye movement. Due to the close relationship between restorativeness and landscape preference, we further explore the relationships between design intensity, preference, restorativeness and eye movements. Specifically, using manipulated images as stimuli for 200 students as participants, the effect of urban green space (UGS) design intensity on landscapes' preference, restorativeness, and eye movement was examined. The results demonstrate that landscape design intensity could contribute to preference and restorativeness and that there is a significant positive relationship between design intensity and eye-tracking metrics, including dwell time percent, fixation percent, fixation count, and visited ranking. Additionally, preference was positively related to restorativeness, dwell time percent, fixation percent, and fixation count, and there is a significant positive relationship between restorativeness and fixation percent. We obtained the most feasible regression equations between design intensity and preference, restorativeness, and eye movement. These results provide a set of guidelines for improving UGS design to achieve its greatest restorative potential and shed new light on the use of eye-tracking technology in landscape perception studies.

Spatial and Temporal Variations of Six Criteria Air Pollutants in Fujian Province, China.

Air pollution has become a critical issue in the urban areas of southeastern China in recent years. A complete understanding of the tempo-spatial characteristics of air pollution can help the public and governmental bodies manage their lives and work better. In this study, data for six criteria air pollutants (including particulate matter (PM2.5, PM10), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3)) from 37 sites in nine major cities within Fujian Province, China were collected between January 2015 to December 2016, and analyzed. We analyzed the spatial and temporal variations of these six criteria pollutants, as well as the attainment rates, and identified what were the major pollutants. Our results show that: (1) the two-year mean values of PM2.5 and PM10 exceeded the Chinese National Ambient Air Quality Standard (CAAQS) standard I levels, whereas other air pollutants were below the CAAQS standard I; (2) the six criteria air pollutants show spatial variations (i.e. most air pollutants were higher in the city center areas, followed by suburban areas and exurban areas, except for O3; and the concentrations of PM10, PM2.5, NO2, O3 were higher in coastal cities than in inland cities); (3) seasonal variations and the no attainment rates of air pollutants were found to be higher in cold seasons and lower in warm seasons, except for O3; (4) the most frequently present air pollutant was PM10, with PM2.5 and O3 being the second and third most frequent, respectively; (5) all the air pollutants, except O3, showed positive correlations with each other. These results provide additional information for the effective control of air pollution in the province of Fujian.

Long-Term Atmospheric Visibility Trends and Their Relations to Socioeconomic Factors in Xiamen City, China.

Atmospheric visibility (AV), one of the most concerning environmental issues, has shown a continuous decline in China's urban areas, especially in Southeastern China. Existing studies have shown that AV is affected by air pollutants and climate change, which are always caused by human activities that are linked to socioeconomic factors, such as urban size, residents' activities, industrial activities, and urban greening. However, the contribution of socioeconomic factors to AV is still not well understood, especially from a long-term perspective, which sometimes leads to ineffective policies. In this study, we used the structural equation model (SEM) in order to quantify the contribution of socioeconomic factors on AV change in Xiamen City, China, between 1987⁻2016. The results showed that the annual average AV of Xiamen between 1987⁻2016 was 12.00 km, with a change rate of -0.315 km/year. Urban size, industrial activities, and residents' activities were found to have a negative impact on AV, while the impact of urban greening on the AV was modest. Among all of the indicators, the number of resident's vehicles, total retail sales of consumer goods, and household electricity consumption were found to have the highest negative direct impact on the AV. The resident population, urban built-up area, and secondary industry gross domestic product (GDP) were the most important indirect impact factors. Based on our results, we evaluated the existing environmental regulations and policies of Xiamen City.