Subjective perception of noise exposure in relation to urban green space availability

Noise pollution has been recognized as one of major threats to the health of urban residents. Increasing green space availability can create a natural buffer to the adverse effects of living in an urban environment. These positive effects of urban green space can be directly related to an objective reduction of noise levels and – indirectly – to the subjective perception of noise exposure. In our study carried out in Lodz, Poland, we explored the relationship between objective noise levels and the subjective perception of noise exposure by urban residents in relation to urban green space availability. We refer to objective noise exposure expressed as GIS modelled L_den derived from noise maps (compliant with the Environmental Noise Directive, 2002/49/EC), and subjective (self-reported) perception of noise exposure as declared in a questionnaire-based survey. We compared the percentage of green space in a buffer, the objectively measured noise level, and the perceived exposure to noise to find the most appropriate radius of the green space buffer. We decided to choose the green space coverage which is not correlated with an objective noise level to avoid potential multicollinearity in regression models. This contrasts with most studies, in which the radius of the buffer is set a priori. We thus compared the selected buffer of green space coverage – 300 m (representing green space availability) – with perceived noise exposure. We used the spatial error probit model to differentiate the impacts of objective and subjective noise indicators, at the same time including also the factor of green space availability. We found out that the direct effect of objectively measured noise levels, education, the presence of noisy neighbours, and building characteristics were the most important variables influencing the self-reported perception of noise by urban residents. The indirect effect of green space availability on noise perception was not strong, yet statistically significant. Although our study does not provide clear-cut evidence, it indicates that the indirect, psychological effects of urban green spaces can positively affect the life satisfaction of urban residents.     

Green and calm: Modeling the relationships between noise pollution propagation and spatial patterns of urban structures and green covers

The mechanism of noise pollution propagation is considerably affected by 1) the type and configuration of its receiving environment and 2) the distance that sound waves pass to reach that environment. This study adopts a spatio-statistical approach to quantify and model associations between noise pollution levels and landscape metrics of land categories (built-up structures and urban green covers). Accordingly, noise levels were measured employing a sound pressure meter to quantify equivalent levels (Leq in dB A), in addition to their corresponding percentiles (L₁₀ and L₉₀). A collection of 30 sampling points were selected to measure noise data within the fall season and between 4 p.m. and 8 p.m. hours of the day. A hierarchical distance-sampling framework based on buffer areas with different radius (300 m, 600 m and 1 km) around each sampling point was compiled to measure composition and configuration metrics of land categories within each buffer area. The results derived from Pearson correlation analysis and multiple-linear regression models indicated that there is a distance-dependent relationship between the metrics of green areas and noise levels. We didn’t find remarkable distance-dependency between built-up structures and noise levels. Based on our new spatio-statistical approach, we conclude that more connected and compacted pattern of green areas closer to pollution centers can significantly alleviate the effects of noise propagation mechanism and appropriate pattern of built-up areas follows a low density distribution with coming green areas in between. Findings of this study highlight the potential of landscape ecology approach as an effective planning paradigm for designing greener and calmer cities.     

Rethinking the distribution of urban green spaces in Mexico City: Lessons from the COVID-19 outbreak

The COVID-19 pandemic has exposed inequalities that are expected to widen if no action is taken to support the most marginalized populations. One such inequality is the distribution of urban green spaces (UGS), which are essential to pandemic recovery. Cities that aim to be inclusive and resilient should assess whether access to their UGS is equitably distributed among the population and identify the areas where these spaces are most needed. This study therefore examines the equity of access to UGS in Mexico City at the neighborhood level using network analysis. First, access to UGS was identified at a threshold of 300 m, regardless of UGS size. Second, access was differentiated by the functional level of the UGS, which primarily depends on their size, with larger UGS having more extensive catchment areas. The results of this study suggest a deficit of access to small green spaces in most of the neighborhoods of Mexico City, with the neighborhoods with higher rates of poverty showing an even lower average of UGS access. The results further highlight which neighborhoods in Mexico City should receive priority attention and funding for UGS to mitigate the disproportionate effects of public health crises. This is critical for future city planning and may be used as a roadmap for identifying priority neighborhoods in other cities with similar segregation patterns.     

Assessment of green space benefits and burdens for urban health with spatial modeling

We present a new spatial model to quantify and map health-related impacts of urban green space (UGS), with the aim to address major shortcomings of existing models and to meet the needs of urban spatial planners for quantitative, spatially-explicit assessment of both the health benefits and burdens of UGS. This GIS-based model uses publicly available high-resolution geospatial data to estimate street-level values of five major determinants of urban health that are significantly influenced by urban spatial design (including UGS): unattractive views, heat stress, air pollution, perceived unsafety and tick-bite risk. We also describe a potential major application of the model for urban spatial planners, a so-called hotspot analysis for a set of five urban design-related health problems, which can assist in setting spatial priorities in urban greening strategies as well as in designing effective greenspace interventions. Hotspots are areas within a city where urban design-related health problems are the largest. An analysis for Maastricht (The Netherlands) showed that in hotspots UGS was mostly a net burden, but also that redesign of UGS could make its role more beneficial for human health.     

Nature orientation and opportunity: Who values and who has opportunity for satisfactory green spaces in proximity to their place of residence

Urban green spaces (UGS) provide important contributions to people. Yet, UGS planning requires better understanding of by whom and where such contributions are being valued or missed. Based on a mixed-methods online survey and choice experiment with residents of Wellington in Aotearoa New Zealand, we analyse how much and why residents value UGS and their benefits when deciding where to live and how socio-economic and spatial factors might impact nature orientation and opportunity for satisfactory local UGS. We find that local UGS are an important residential choice criteria for the majority of respondents, especially in the context of Wellington’s intensification plans. However, we show that socio-economic and spatial factors significantly impact whether someone values and is satisfied with UGS in proximity to their place of residence. Our findings call for careful scoping of a city’s population and spatial structure when planning for equitable UGS provision. More holistic approaches to green space planning are needed to address contextualities and the complex interdependencies between nature orientation and opportunity and to plan for green space distributions that provide opportunities now and help shaping nature orientation for future generations.     

Detection of unfavourable urban areas with higher temperatures and lack of green spaces using satellite imagery in sixteen Spanish cities

This paper seeks to identify the most unfavourable areas of a city in terms of high temperatures and the absence of green infrastructure. An automatic methodology based on remote sensing and data analysis has been developed and applied in sixteen Spanish cities with different characteristics. Landsat-8 satellite images were selected for each city from the July-August period of 2019 and 2020 to calculate the spatial variation of land surface temperature (LST). The Normalized Difference Vegetation Index (NDVI) was used to determine the abundance of vegetation across the city. Based on the NDVI and LST maps created, a k-means unsupervised classification clustering was performed to automatically identify the different clusters according to how favourable these areas were in terms of temperature and presence of vegetation. A Disadvantaged Area Index (DAI), combining both variables, was developed to produce a map showing the most unfavourable areas for each city. Overall, the percentage of the area susceptible to improvement with more vegetation in the cities studied ranged from 13 % in Huesca to 64–65 % in Bilbao and Valencia. The influence of several factors, such as the presence of water bodies or large buildings, is discussed. Detecting unfavourable areas is a very interesting tool for defining future planning strategy for green spaces.     

不同基因型茄子果实发育过程中色素与可溶性糖的关系

以茄子果实颜色不同的4个品种为试材,测定了茄子果实发育过程中花青素苷、叶绿素和可溶性糖含量,并分析了色素和可溶性糖的相关性。结果表明:茄子果色由花青素苷和叶绿素共同作用,各色素含量因基因型而异,紫色茄子花青素苷在果实形成后期迅速增加,叶绿素递减,绿色茄子则相反。茄子果实中蔗糖和葡萄糖等还原糖是主要的可溶性糖。在果实形成后期蔗糖、葡萄糖和总还原糖都是紫色茄子大于绿色茄子。紫色茄子果实的花青素苷与蔗糖、还原糖及低聚糖的含量呈显著或极显著正相关;绿色茄子果实叶绿素和总可溶性糖含量呈显著正相关,表明茄子果实花青素苷和叶绿素的积累是两个独立过程,两者的积累都与可溶性糖含量变化密切相关,而且相关性存在基因型差异。