Modeling the provision of air-quality regulation ecosystem service provided by urban green spaces using lichens as ecological indicators

Urban green spaces and resident health: an empirical analysis from data across 30 provinces in China

Background

This study aims to explore the correlation between urban green space coverage and resident health, and to analyze its underlying mechanisms.

Methods

Using panel data from 30 provinces in China from 2006 to 2022, which mainly includes urban green space coverage, general health of the population, air quality, and social connectivity. This research constructed a fixed effects model to perform baseline regression analysis. A series of robustness tests, including variable substitution, controlling for geographical differences, regional robustness tests, and shortening the time span of the study, further verified the robustness of the results. Additionally, mechanism tests were conducted to examine the positive impacts of urban green spaces on resident health by improving air quality and enhancing social connectivity.

Results

The findings indicate a significant positive correlation between urban green space coverage and resident health levels. That is, the greater the area covered with urban green space, the healthier the residents of the area will be. Robustness tests support the reliability of this finding, while mechanism analysis reveals that urban green spaces have a positive impact on the health of the population by improving air quality and increasing social connectivity.

Discussion

This study underscores the importance of urban green space planning in improving resident health and quality of life, providing urban planners with scientific evidence to optimize urban green systems for broader health objectives.

Using fs/QCA to explore the influencing factors of urban green infrastructure development and its combinational drivers: the case of the Yangtze River Delta region of China

High levels of urban green infrastructure (UGI) development can help mitigate the climate, biodiversity, and habitat crises faced by cities and support the achievement of sustainable urban development. Based on the relevant data of 41 cities in the Yangtze River Delta region obtained from 2011 to 2020, this study measured the development level of natural and geographic conditions, economic development, urban construction, social and cultural development, and eco-environment quality and urban green infrastructure (UGI); evaluated the development trend of UGI in the region during the 12th Five-Year Plan and 13th Five-Year Plan by using entropy TOPSIS; and used fs/QCA to explain the high-level development path of each city toward the achievement of a green infrastructure. The results showed that (1) the development level of UGI in the Yangtze River Delta region decreases from southeast to northwest, and gradually decreases from Shanghai, Hangzhou, and other central cities. (2) There were several different configurations of high levels and non-high levels of UGI development drivers across regions, confirming the existence of multiple causality and asymmetry indices in the drivers of UGI. (3) During the "12th Five-Year Plan" and the "13th Five-Year Plan" period, the conditions needed to achieve a high level of UGI gradually became stricter, expanding from nature-social culture and urban construction-eco-environmental drivers to nature-urban construction, nature-social culture-eco-environmental, urban construction-economy-social culture-eco-environmental drivers. Research findings can provide greater guidance and implications for future sustainable urban development.

Bioinspired robots can foster nature conservation

We live in a time of unprecedented scientific and human progress while being increasingly aware of its negative impacts on our planet's health. Aerial, terrestrial, and aquatic ecosystems have significantly declined putting us on course to a sixth mass extinction event. Nonetheless, the advances made in science, engineering, and technology have given us the opportunity to reverse some of our ecosystem damage and preserve them through conservation efforts around the world. However, current conservation efforts are primarily human led with assistance from conventional robotic systems which limit their scope and effectiveness, along with negatively impacting the surroundings. In this perspective, we present the field of bioinspired robotics to develop versatile agents for future conservation efforts that can operate in the natural environment while minimizing the disturbance/impact to its inhabitants and the environment's natural state. We provide an operational and environmental framework that should be considered while developing bioinspired robots for conservation. These considerations go beyond addressing the challenges of human-led conservation efforts and leverage the advancements in the field of materials, intelligence, and energy harvesting, to make bioinspired robots move and sense like animals. In doing so, it makes bioinspired robots an attractive, non-invasive, sustainable, and effective conservation tool for exploration, data collection, intervention, and maintenance tasks. Finally, we discuss the development of bioinspired robots in the context of collaboration, practicality, and applicability that would ensure their further development and widespread use to protect and preserve our natural world.

The role of park size on ecosystem services in urban environment: a review

Urban parks play an important role in urban ecosystems with multifunctional services. Park size is one of the important attributes to explain the potential capacity of urban parks. In recent years, the number of studies that focus on the relationship between park size and ecosystem services in the context of ecosystem services has been increasing. This study aims to focus on investigating the relationship between ecosystem services and urban park size. The Web of Science online databases were searched using the keywords "green space", "size" and "urban" as well as related terms. A total of 129 papers meeting the inclusion criteria were examined within the scope of the research aims. The results obtained from the systematic search were summarized and presented in the three categories with sub-categories: (i) cultural services with sub-categories of physical activity (n = 42) and housing prices (n = 10), (ii) supporting services with sub-categories of fauna (n = 44), and flora (n = 3) and (iii) regulating services with sub-categories of microclimate (n = 25) and air quality (n = 5). The results indicated that park size influences a wide range of services by providing more spaces for physical activities, increasing housing prices, creating habitats for birds, insects, and bats, and effects on their richness, diversity and density, increasing the cooling effect capacity and reducing air pollution of urban parks. In conclusion, a comprehensive approach is needed, recognizing the potential of both large and small green spaces to optimize ecosystem services delivery, promote resilience, and enhance urban well-being. This includes considering supply and demand aspects and improving measurement methods. Furthermore, exploring optimal improvements across diverse park sizes remains a promising avenue for research, contributing to the development of more efficient urban green spaces.

Exploring the effect of ecological land structure on PM2.5: A panel data study based on 277 prefecture-level cities in China

In the context of serious urban air pollution and limited land resources, it is important to understand the environmental value of ecological land. Previous studies focused mostly on the effectiveness of a particular type of green space or the total amount of ecological land on PM_2.5 and have rarely analyzed the association between ecological land structure and PM_2.5 systematically and quantitatively. Therefore, we took 277 cities in China as an example, comprehensively compared the results of different models, and selected a spatial Durbin model using time-fixed effects to dissect the degree of influence of ecological land and different land types within it on PM_2.5. The urban ecological land use structure was closely related to PM_2.5, and the higher the proportion of ecological land use was, the lower the PM_2.5. The degree and direction of influence of different types of land functions within ecological land on PM_2.5 differed, with forests, shrubs, and grasslands causing a weakening impact on PM_2.5, while wetlands and waters did not have a weakening role. The degree of reduction of PM_2.5 by a single type of ecological land was significantly smaller than that by a composite type of ecological land. Green space should be comprehensively considered, designed and adjusted in urban planning to continuously optimize the ecological spatial structure, increase landscape diversity and maximize ecological benefits. The findings of this study help with exploring the effects of land use structure under the goal-oriented control of air pollution and provide theoretical reference and decision-making support for formulating precise air pollution control policies and optimizing the spatial development of national land.

Causality and dynamic spillover effects of megacities on regional industrial pollution reduction

Regional economic power and local environmental policies have a substantial impact on pollution reduction in urban agglomerations (UAs); however, whether megacities in UAs exert spillover effects of pollution reduction on surrounding cities remains unknown. This study presents a causal analytic framework to evaluate the spillover effects of megacities on regional industrial pollution reduction in three major UAs in China between 2005 and 2016. The interaction between industrial pollution reduction and infrastructure investment indicators was also examined. Results indicated a good fit for spatial spillover of sulfur dioxide reduction (SR) in the Pearl River Delta (PRD) and Yangtze River Delta (YRD) but not in the Beijing-Hebei-Tianjin cluster (JJJ). Spatial spillover of dust reduction (DR) was evident in the PRD and JJJ but not the YRD. Spatial analysis showed that infrastructure investment indicators, at megacity and UA levels, had short-term spillover effects on surrounding cities for DR but not SR. However, spatial spillover effects, at both the city and UA levels, were substantial over the long term. In addition, the results of the spatial-time lag analysis suggest a linear relationship between pollution control-related infrastructure investment indicators and long-term pollution reduction. This study provides new information regarding the spatial spillover effects of megacities on regional industrial pollution reduction in UAs.

Can Potted Plants Catch Mosquitoes? Applying Rare-Earth Luminescent Materials and Plant Energy to the Development of Innovative Mosquito-Trapping Potted Plants

Due to the global warming crisis, the spread of various infectious diseases is worsening, with mosquito-borne contagious diseases posing a significant threat. While many residential and public spaces contain plants, often for greening the environment and improving mental and physical well-being, the carbon dioxide released by these plants produces ideal habitats for mosquitoes. Considering the quality of life of urban residents and the development of health-related products simultaneously is an important topic. This study used diverse complementary techniques, such as energy-storing rare-earth luminescent materials, sustainable power generation using plant energy, blue light-emitting diodes, and environmentally friendly fermentation formula, to develop planting products with potential mosquito control functionality. The prototype design for this mosquito-trapping potted plant has been patented. The aim of this paper is to discuss the design principles adopted to improve the defects of existing mosquito-trapping designs, the green energy materials and techniques employed, the architecture configuration of the product prototype, and the test results. By integrating green materials and technology, the prototype can be self-powered without being plugged in to yield conspicuous energy savings. The results showed that the developed multi-function products, combined with the concept of energy sustainability, can improve global public health as well as individuals' physical and mental health.

Quantitative analysis of lake-cooling effect in Hefei City, China, based on multispectral remote sensing and its response to urban expansion

Urban expansion has intensified the heat-island effect, and the negative impact on the natural environment has gradually become considerable. However, urban lakes can significantly alleviate the heat-island effect caused by urbanization. Based on four-phase multispectral remote-sensing images during 2005-2020, 17 lakes in the main and surrounding urban areas of Hefei, China, were selected as the objects of our research. Each lake's cooling intensity and distance were calculated; cooling-efficiency data for different lakes were compared and analyzed considering lake areas and regional differences. The following conclusions were drawn: (1) The mean temperature of the lake had a strong positive correlation with the cooling-intensity efficiency and the cooling-distance efficiency, and it was the leading influencing factor of the cooling-intensity efficiency and the cooling-distance efficiency. The mean explanation degree was as high as 63.33% and 51.70%, respectively. (2) The lake area and the distance from the lake to the city center had a negative correlation with the cooling-intensity efficiency and cooling-distance efficiency and were the secondary factors that affect the cooling-intensity efficiency and cooling-distance efficiency. (3) The lakes around the urban area were far away from the main urban area where the heat-island effect was most concentrated, the ability of absorbing the high surface temperature caused by the heat-island effect was limited, and the cooling-intensity efficiency and cooling-distance efficiency were reduced by ~ 6.6 °C/km² and ~ 607.47 m/km², respectively, compared with the lakes in the main urban area. (4) With urban expansion and the intensified urban heat-island effect, the cooling-intensity efficiency of lakes in the main urban area gradually increased, whereas the cooling-distance efficiency of lakes decreased.

Do We Need More Urban Green Space to Alleviate PM2.5 Pollution? A Case Study in Wuhan, China

Urban green space can help to reduce PM2.5 concentration by absorption and deposition processes. However, few studies have focused on the historical influence of green space on PM2.5 at a fine grid scale. Taking the central city of Wuhan as an example, this study has analyzed the spatiotemporal trend and the relationship between green space and PM2.5 in the last two decades. The results have shown that: (1) PM2.5 concentration reached a maximum value (139 μg/m3) in 2010 and decreased thereafter. Moran’s I index values of PM2.5 were in a downward trend, which indicates a sparser distribution; (2) from 2000 to 2019, the total area of green space decreased by 25.83%. The reduction in larger patches, increment in land cover diversity, and less connectivity led to fragmented spatial patterns of green space; and (3) the regression results showed that large patches of green space significantly correlated with PM2.5 concentration. The land use/cover diversity negatively correlated with the PM2.5 concentration in the ordinary linear regression. In conclusion, preserving large native natural habitats can be a supplemental measure to enlarge the air purification function of the green space. For cities in the process of PM2.5 reduction, enhancing the landscape patterns of green space provides a win-win solution to handle air pollution and raise human well-being.

Research on the Spatial Heterogeneity and Influencing Factors of Air Pollution: A Case Study in Shijiazhuang, China

Rapid urbanization causes serious air pollution and constrains the sustainable development of society. The influencing factors of urban air pollution are complex and diverse. Multiple factors act together to interact in influencing air pollution. However, most of the existing studies on the influencing factors of air pollution lack consideration of the interaction mechanisms between the factors. Using multisource data and geographical detectors, this study analyzed the spatial heterogeneity characteristics of air pollution in Shijiazhuang City, identified its main influencing factors, and analyzed the interaction effects among these factors. The results of spatial heterogeneity analysis indicate that the distribution of aerosol optical depth (AOD) has obvious agglomeration characteristics. High agglomeration areas are concentrated in the eastern plain areas, and low agglomeration areas are concentrated in the western mountainous areas. Forests (q = 0.620), slopes (q = 0.616), elevation (q = 0.579), grasslands (q = 0.534), and artificial surfaces (q = 0.506) are the main individual factors affecting AOD distribution. Among them, natural factors such as topography, ecological space, and wind speed are negatively correlated with AOD values, whereas the opposite is true for human factors such as roads, artificial surfaces, and population. Each factor can barely affect the air pollution status significantly alone, and the explanatory power of all influencing factors showed an improvement through the two-factor enhanced interaction. The associations of elevation ∩ artificial surface (q = 0.625), elevation ∩ NDVI (q = 0.622), and elevation ∩ grassland (q = 0.620) exhibited a high explanatory power on AOD value distribution, suggesting that the combination of multiple factors such as low altitude, high building density, and sparse vegetation can lead to higher AOD values. These results are conducive to the understanding of the air pollution status and its influencing factors, and in future, decision makers should adopt different strategies, as follows: (1) high-density built-up areas should be considered as the key areas of pollution control, and (2) a single-factor pollution control strategy should be avoided, and a multi-factor synergistic optimization strategy should be adopted to take full advantage of the interaction among the factors to address the air pollution problem more effectively.

Is Active Moss Biomonitoring Comparable to Air Filter Standard Sampling?

Recently, significant attention has been paid to air quality awareness and its impact on human health, especially in urban agglomerations. Many types of dust samplers for air quality monitoring are used by governmental environmental monitoring agencies. However, these techniques are associated with high costs; as a consequence, biological methods such as active moss biomonitoring are being developed. The main disadvantages of such techniques are the lack of standardization of the preparation procedures and the lack of reliable comparisons of results with data from instrumental analyses. Our study aimed to compare the results obtained from active biomonitoring with the use of three moss species: Pleurozium schreberi, Sphagnum fallax and Dicranum polysetum. Samples were exposed via the moss-bag technique to measure the concentrations of analytes (Mn, Fe, Cu, Zn, Cd, Hg and Pb) which had accumulated among the total suspended particulates (TSP) collected from the filters of a dust collector in the city of Opole (Opole voivodeship, Poland). With regard to the physicochemical and biological traits of the mosses, their assessed lifetime and actual photochemical efficiency (yield) following exposure were meagre, which may have been related to the change of environment and their exposure to pollutants. When comparing the results obtained by the two methods used to monitor air pollution, the biomonitoring method was found to be incompletely consistent with the reference method. Biological monitoring using mosses must be carefully considered depending on the monitoring objectives, the required level of sensitivity and quality of measurement and the type of pollutant.

Do Value Orientations and Beliefs Play a Positive Role in Shaping Personal Norms for Urban Green Space Conservation?

Urban Green Spaces (UGS) have a huge contribution to the health of urban ecosystems. However, they are threatened by numerous factors such as rapid urbanization, resource depletion, and climate change. These factors are inextricably linked to human behaviors, guided by the values and beliefs of people. According to value-belief-norm theory and norm activation model, personal norms are defined as self-expectations of pro-environmental behavior influenced by the ascription of responsibility and awareness of consequences in values and beliefs. When the conditions of responsibility and consequence awareness are met, individuals are more likely to experience a sense of moral obligation to exhibit environmentally responsible behavior. To address conservation and better enable UGS to have a positive function, we must explore how to promote the development of personal norms that are beneficial to UGS conservation. This study explored the influence that UGS values and beliefs have on personal norms. A questionnaire was administered to 1641 urban residents in Beijing, China, and Partial Least Square Structural Modeling was used to assess the causal relationship in the formation of personal norms on UGS conservation. The results showed that intrinsic, instrumental, and relational UGS value orientations contribute directly or indirectly to the formation of personal norms for the conservation of UGS through environmental beliefs as mediators, with the most significant effect being the relational value orientations. The results of the study can provide scientific guidance for future public participation in UGS conservation.

Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review

Scientific interest in the potential of urban green spaces, particularly urban parks, to improve health and well-being is increasing. Traditional research methods such as observations and surveys have recently been complemented by the use of social media data to understand park visitation patterns. We aimed to provide a systematic overview of how social media data have been applied to identify patterns of urban park use, as well as the advantages and limitations of using social media data in the context of urban park studies. We used the PRISMA method to conduct a systematic literature analysis. Our main findings show that the 22 eligible papers reviewed mainly used social media data to analyse urban park visitors’ needs and demands, and to identify essential park attributes, popular activities, and the spatial, social, and ecological coherence between visitors and parks. The review allowed us to identify the advantages and limitations of using social media data in such research. These advantages include a large database, real-time data, and cost and time savings in data generation of social media data. The identified limitations of using social media data include potentially biased information, a lack of socio-demographic data, and privacy settings on social media platforms. Given the identified advantages and limitations of using social media data in researching urban park visitation patterns, we conclude that the use of social media data as supplementary data constitutes a significant advantage. However, we should critically evaluate the possible risk of bias when using social media data.

Mapping Urban Green Spaces at the Metropolitan Level Using Very High Resolution Satellite Imagery and Deep Learning Techniques for Semantic Segmentation

Urban green spaces (UGSs) provide essential environmental services for the well-being of ecosystems and society. Due to the constant environmental, social, and economic transformations of cities, UGSs pose new challenges for management, particularly in fast-growing metropolitan areas. With technological advancement and the evolution of deep learning, it is possible to optimize the acquisition of UGS inventories through the detection of geometric patterns present in satellite imagery. This research evaluates two deep learning model techniques for semantic segmentation of UGS polygons with the use of different convolutional neural network encoders on the U-Net architecture and very high resolution (VHR) imagery to obtain updated information on UGS polygons at the metropolitan area level. The best model yielded a Dice coefficient of 0.57, IoU of 0.75, recall of 0.80, and kappa coefficient of 0.94 with an overall accuracy of 0.97, which reflects a reliable performance of the network in detecting patterns that make up the varied geometry of UGSs. A complete database of UGS polygons was quantified and categorized by types with location and delimited by municipality, allowing for the standardization of the information at the metropolitan level, which will be useful for comparative analysis with a homogenized and updated database. This is of particular interest to urban planners and UGS decision-makers.

Functional Traits in Lichen Ecology: A Review of Challenge and Opportunity

Community ecology has experienced a major transition, from a focus on patterns in taxonomic composition, to revealing the processes underlying community assembly through the analysis of species functional traits. The power of the functional trait approach is its generality, predictive capacity such as with respect to environmental change, and, through linkage of response and effect traits, the synthesis of community assembly with ecosystem function and services. Lichens are a potentially rich source of information about how traits govern community structure and function, thereby creating opportunity to better integrate lichens into 'mainstream' ecological studies, while lichen ecology and conservation can also benefit from using the trait approach as an investigative tool. This paper brings together a range of author perspectives to review the use of traits in lichenology, particularly with respect to European ecosystems from the Mediterranean to the Arctic-Alpine. It emphasizes the types of traits that lichenologists have used in their studies, both response and effect, the bundling of traits towards the evolution of life-history strategies, and the critical importance of scale (both spatial and temporal) in functional trait ecology.

The Potential of Tram Networks in the Revitalization of the Warsaw Landscape

The current crisis of worldwide agglomeration and economic, spatial, and ownership factors, among others, mean that there is usually a shortage of new green areas, which are socially very beneficial. Therefore, various brownfields or degraded lands along public transport routes, e.g., tram lanes, are effectively transformed for this purpose. The significant potential of tram systems is that they can became a backbone of green corridors across the city. This case study of the Warsaw tram system (total length over 300 km of single tracks in service in 2019) enables us to simulate the potential growth of a biologically active area connected with an increasing share of greenery around tram lanes in Warsaw. Experience allows the authors to present the types of greenery systems based on existing and future tram corridors best suited for this city. The suggested usage of tram lanes as green corridors is in line with the generally-accepted concept of urban green infrastructure. Therefore, the aim of the authors is to present in a condensed fashion their views on a very important issue within the program of the revitalization of the Warsaw landscape by converting where possible the existing tram lines, as well as planning new ones according to the “green point of view”.

Does socioeconomic development lead to more equal distribution of green space? Evidence from Chinese cities

Despite the wide implementation of green spaces to mitigate the negative effects of urbanization, there is little evidence of how cities' socioeconomic development impacts the equality of urban green space (UGS) distribution. This paper addresses this knowledge gap. Employing longitudinal data analysis and the Gini index with various socioeconomic factors, we investigated potential driving factors for UGS equality at the prefectural city level (221 out of 341 cities in total) in China during the rapid urbanization from 2000 to 2015. Results indicated that 72% of Chinese cities (160 of 221) in our sample improved their UGS equality level from 2000 to 2015, whereas 14% of cities studied (31 out of 221) declined in both quantity and equality of green space. Nationwide, economic development levels reflected by gross domestic product per capita exerted a positive and significant impact on the equality of green space distributions. Urban afforestation-related policies in China were successful in promoting the equal distribution of green space. Regional analysis indicated divergent impacts of socioeconomic development and government policies on green space equality. Other institutional development factors, such as adopting a freer land market, might harm efforts toward equal green space distribution without appropriate safeguarding regulations and enforcement powers to ensure the implementation of an equal distribution of green spaces. These findings inform decision-makers about spatial variances in the equality of green space distribution in urban areas, which demand location-oriented interventions to promote inclusive urban afforestation in Chinese cities.

Influence of Environment on Microbial Colonization of Historic Stone Buildings with Emphasis on Cyanobacteria

Microbial cells that produce biofilms, or patinas, on historic buildings are affected by climatic changes, mainly temperature, rainfall and air pollution, all of which will alter over future decades. This review considers the colonization of stone buildings by microorganisms and the effects that the resultant biofilms have on the degradation of the structure. Conservation scientists require a knowledge of the potential effects of microorganisms, and the subsequent growth of higher organisms such as vascular plants, in order to formulate effective control strategies. The vulnerability of various structural materials (“bioreceptivity”) and the ways in which the environmental factors of temperature, precipitation, wind-driven rain and air pollution influence microbial colonization are discussed. The photosynthetic microorganisms, algae and cyanobacteria, are acknowledged to be the primary colonizers of stone surfaces and many cyanobacterial species are able to survive climate extremes; hence special attention is paid to this group of organisms. Since cyanobacteria require only light and water to grow, can live endolithically and are able to survive most types of stress, they may become even more important as agents of stone cultural property degradation in the future.

Towards a Standard Framework to Identify Green Infrastructure Key Elements in Dense Mediterranean Cities

Present-day dense cities are increasingly affected by the impacts associated with climate change. The recurrence of extreme climate events is projected to be intensified in cities in the next decades, especially in the most vulnerable areas of the world, such as the Mediterranean region. In this context, the urban green infrastructure (UGI) is presented as a nature-based solution that directly contributes to climate change mitigation in Mediterranean compact cities and improves health, social, welfare, and environmental conditions for inhabitants. This research sets out a manageable framework to define, locate, and categorize more functional green urban and peri-urban areas in a dense Mediterranean city. It takes spatial distribution, extension, and the capacity to improve inhabitants’ wellbeing through the provision of ecosystem services as classification criteria. Results show a scenario with a greater functional green surface available for the citizens to be managed. Identified areas have been categorized as cores, nodes, links, and green spaces defined as “other” areas. In particular, the latter play a significant role at social, structural, and ecological levels. The study showcases that rethinking urban design and strategic decision-making around these areas can enhance green equity in Mediterranean dense cities, their capacity to better deal with environmental extremes, and the inhabitants’ engagement with a culture of sustainability and wellbeing.

Reduction of Atmospheric Suspended Particulate Matter Concentration and Influencing Factors of Green Space in Urban Forest Park

In the process of urbanization in China, the problem of atmospheric suspended particulate matter pollution is becoming increasingly serious. It has been impossible to completely rely on pollution source control measures to solve this problem for a long time due to the diversity and complexity of pollution sources. Therefore, there is an urgent need to explore alternate solutions to significantly improve air quality through increasing the capacity of green space in cities as these locations can provide multiple ecosystem services. In this study, a three-dimensional classification system was created by utilizing Beijing’s urban forest as a study area. Considering the meteorological factors, change of month and time and the characteristics of the forest itself, the significance and difference of reducing the concentration of atmospheric suspended particulate matter by the forest with different vegetation structures were tested. The results showed that meteorological factors such as wind velocity, temperature, and relative humidity all had a very significant effect on the concentration of atmospheric suspended particulate matter in the conditions of this study. The concentration was highest in winter, followed by spring and autumn, and lowest in summer. The concentration in the morning was the lowest of the day, increasing in the noon and afternoon with time. It was the lowest in the closed single-layered mixed forest, and the highest in the open lawn green space. By comparing the forest with gradient areas of 0.5 ha and 3.0 ha, it was found that with the increase in the area, the green space did not necessarily show a better dust retention effect, and the vegetation structure type of the green space often had more important influence. There was a very significant correlation between vegetation structure and plant diversity (Shannon–Wiener Diversity Index and Simpson Diversity Index). Biodiversity could significantly support and strengthen urban forest ecological service functions that improve air quality. Increasing the plant species diversity could lead to lower particulate matter concentration. The research conclusions could provide theoretical and practical bases for how to select the combination of vegetation structure in the planning and design of urban forest oriented to improve air quality.

Investigation of the impacts of urban vegetation loss on the ecosystem service of air pollution mitigation in Karaj metropolis, Iran

The present study aims to investigate the relationship between reduced air pollution and ecosystem services in Karaj metropolis, Iran. To the end, the trends in the concentrations of O₃, NO₂, CO, SO₂, PM₁₀, and PM_2.5 as the main atmospheric pollutants of Karaj were studied. Five time series models of autoregressive (AR), moving average (MA), autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA), and seasonal autoregressive integrated moving average (SARIMA) were used to predict changes in air pollutant concentrations. Air pollution zoning is conducted via ArcGIS_10.3 by using spline tension interpolation method. Then, normalized difference vegetation index (NDVI) was obtained from Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) images to analyze vegetation dynamics as an index of ecosystem functioning. NDVI thresholds were selected to present guidelines for qualitative and quantitative changes in green cover and were divided into five different categories. Based on the results, AR (1) and ARIMA (1,2,1) were recognized as appropriate models for predicting the concentration of air pollutants in the study area. A decrease in very dense vegetation coverage and increase in poor vegetation areas, followed by an increase in air pollution, revealed that the loss of urban green coverage and decreased ecosystem services were positively related. Furthermore, the expansion of urban lands toward the north and the west from the baseline to future condition led to great changes in the land cover and losses in vegetation along these axes, which finally resulted in increased air pollution in these areas. Thus, the results of this study can be directly used in decision-making in the area of air pollution.

Using green to cool the grey: Modelling the cooling effect of green spaces with a high spatial resolution

The urban heat island effect creates warmer and drier conditions in urban areas than in their surrounding rural areas. This effect is predicted to be exacerbated in the future, under a climate change scenario. One way to mitigate this effect is to use the urban green infrastructure as a way to promote the cooling island effect. In this study we aimed to model, with a high spatial resolution, how Mediterranean urban parks can be maximized to be used as cooling islands, by answering the following questions: i) which factors influence the cooling effect and when?; ii) what type of green spaces contributes the most to the cooling effect?; iii) what is the cooling distance of influence? To answer these questions we established a sampling design where temperature and relative humidity were measured in different seasons, in locations with contrasting characteristics of green and grey cover. We were able to model the effect of green and grey spaces in the cooling island effect and build high spatial resolution predicting maps for temperature and relative humidity. Our study showed that even green spaces with reduced areas can regulate microclimate, alleviating temperature by 1-3 °C and increasing moisture by 2-8%, on average. Green spaces with a higher density of trees were more efficient in delivering the cooling effect. The morphology, aspect and level of exposure of grey surfaces to the solar radiation were also important features included in the models. Green spaces influenced temperature and relative humidity up to 60 m away from the parks' limits, whereas grey areas influenced in a much lesser range, from 5 m up to 10 m. These models can now be used by citizens and stakeholders for green spaces management and human well-being impact assessment.

Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing

Urban green space (UGS) plays a pivotal role in improving urban ecosystem services and building a livable environment for urban dwellers. However, remotely sensed investigation of UGS at city scale is facing a challenge due to the pixels’ mosaics of buildings, squares, roads and green spaces in cities. Here we developed a new algorithm to unmix the fraction of UGS derived from Landsat TM/ETM/8 OLI using a big-data platform. The spatiotemporal patterns and dynamics of UGSs were examined for 70 major cities in China between 2000 and 2018. The results showed that the total area of UGS in these cities grew from 2780.66 km2 in 2000 to 6764.75 km2 in 2018, which more than doubled its area. As a result, the UGS area per inhabitant rose from 15.01 m2 in 2000 to 18.09 m2 in 2018. However, an uneven layout of UGS occurred among the coastal, western, northeastern and central zones. For example, the UGS percentage in newly expanded urban areas in the coastal zone rose significantly in 2000–2018, with an increase of 2.51%, compared to the decline in UGS in cities in the western zone. Therefore, the effective strategies we have developed should be adopted to show disparities and promote green infrastructure capacity building in those cities with less green space, especially in western China.

Perceptions of ecosystem services, disservices and willingness-to-pay for urban green space conservation

While planning and management of urban green space (UGS) remain primarily driven by policymakers and expert knowledge, increasing attention has been paid to the general public's perception of and demand for UGS. This study was conducted to provide price-related outcomes to support UGS-related decision making and achieve an improved understanding of the causal relationships underpinning the residents' willingness-to-pay (WTP) for UGS conservation. An extensive survey with 3000 urban residents from three provincial capital cities in central China (i.e., Wuhan, Changsha and Nanchang) was conducted. We applied structural equation modelling to examine a range of hypothetical causal relationships among residents' perceptions about ecosystem services/disservices provided by UGS, frequency of UGS visits, socioeconomic status (SES) and WTP for the conservation of five different types of UGS. We found that residents had an average WTP of 202.4 CNY or 30.6 USD per year cross UGS types, with the attached green space having the greatest WTP (223.0 CNY or 33.7 USD per year), followed by park (215.4 CNY or 32.6 USD year), square (201.7 CNY or 30.5 USD year), suburban ecological (190.1 CNY or 28.7 USD year) and protective (182.0 CNY or 27.5 USD year) green spaces. Perceptions of UGS's ecosystem services had a positive causal impact on WTP, while perceptions of ecosystem disservices would have a negative impact. The frequency of UGS visits was found to amplify WTP at a limited level. It could further heighten and diminish the perceptions of ecosystem services and disservices. Participants with higher SES typically had greater perceptions of UGS's ecosystem services and WTP. Finally, we found that the structure of the causal relationships on WTP varied between cities, highlighting the importance of considering the fine-level impacts of biophysical environment jointly. Our results could help urban planners to understand better the ways urban green space was perceived and anticipate the likely effects of changing spatial patterns of UGS on the benefits and nuisances experienced by the general public.

Optimizing Spatial Distribution of Urban Green Spaces by Balancing Supply and Demand for Ecosystem Services

The capacity and ecological flows of ecosystem services as well as the demand for them are key areas of urban and rural ecological planning that have been studied using the spatial-explicit model as a decision support tool. This study develops a framework for mapping the relationships among the capacity of and demand for ecosystem services, ecological flows, and planning management. This is done by estimating the ecosystem services based on the space for recreation and environmental conditions and assessing planning for green spaces using the spatial-explicit model. The results show that the carrying capacity of green recreational space was high in the northwest, southwest, and southeast parts of the city of Hefei in China, where this space was highly sustainable in the northwest and southwest. The data also show that the carrying capacity for air purification was higher in the northwest, southwest, and southeast suburbs of Hefei, while areas with high demand for air purification were mainly located in the northeast. The spatial variation in the flows of supply and demand for ecosystem services remained high and unbalanced in the northeast and southwest of Hefei. The excessive use of ecosystem services was concentrated in the urban center while their use in suburban areas was sustainable. The results show that the gap between the supply and demand of space for recreation increased with distance while that between the supply and demand of air purification decreased with increasing distance. The results of assessment based on spatial visualization show that green space was abundant in areas with low demand for it, while those with high demand for it tended to have limited green space in Hefei. This analysis shows that indices for the demand for green spaces in the context of ecosystem services can be improved via public participation, interactions between different scales of ecosystem services for green space, and use of decision support in urban and rural planning systems. These areas will form important directions for future research.

Urban Vegetation in Air Quality Management: A Review and Policy Framework

Recent episodes of high air pollution concentration levels in many Polish cities indicate the urgent need for policy change and for the integration of various aspects of urban development into a common platform for local air quality management. In this article, the focus was placed on the prospects of improving urban air quality through proper design and protection of vegetation systems within local spatial planning strategies. Recent studies regarding the mitigation of air pollution by urban greenery due to deposition and aerodynamic effects were reviewed, with special attention given to the design guidelines resulting from these studies and their applicability in the process of urban planning. The conclusions drawn from the review were used to conduct three case studies: in Gdańsk, Warsaw, and Poznań, Poland. The existing local urban planning regulations for the management of urban greenery were critically evaluated in relation to the findings of the review. The results indicate that the current knowledge regarding the improvement of urban air quality by vegetation is not applied in the process of urban planning to a sufficient degree. Some recommendations for alternative provisions were discussed.

Effects of land-use patterns on PM2.5 in China's developed coastal region: Exploration and solutions

While land-use models have often been used to determine the spatial distribution of air pollutant concentrations at urban spatial scales, the effects of land use on PM_2.5 concentrations and removal are rarely investigated at regional spatial scales. We studied these effects in Jiangsu Province, which is part of the Yangtze River Delta Urban Agglomeration. Results showed that forest lands and industrial lands had greater effects on the PM_2.5 concentration than did other land-use types. In addition, industrial lands and built-up lands had greater effects on the PM_2.5 concentrations in winter than in summer. The spatiotemporal change in the PM_2.5 concentration was mainly impacted by industrial distribution and development, while the spatiotemporal change in PM_2.5 removal was mainly impacted by forest land distribution and change. Therefore, PM_2.5 removal was generally higher in rural areas than in urban areas. The spatial PM_2.5 concentration slowly increased with net primary productivity (NPP) first and then decreased with NPP, with an inflection point at 19 g C m^-2 a^-1 NPP. However, the spatial PM_2.5 removal per unit area exponentially increased with NPP. The average removal rate of PM_2.5 by forests was about 0.03% in Jiangsu Province, while the absolute removed amount of PM_2.5 was about 3013 tons in 2015. It was concluded that the impact of forests on air quality in terms of PM_2.5 is significant at regional spatial scales. Therefore, scientific trade-offs and decision-making are necessary to maintain forest ecosystem services in order to improve air quality and human health.

Determination of the urbanization and changes in open-green spaces in Nevsehir city through remote sensing

The physical texture of cities is comprised of built-up spaces, open-green spaces, and transportation arteries. Urbanization is a dynamic that compose of each of the factors above in a fair proportion to human beings and nature. On the other hand, due to the rapid increase in urban population, urbanization has become a concept that poses serious problems for cities in the last decades and this leads a pressure on open-green spaces in urban areas. Open-green spaces have a great importance in improving urban life conditions and balancing the destroyed relations between humans and environment. For this reason, the sustainability of urban open-green spaces cannot be ignored in the planning studies. In this study, the change in the urban texture in Nevsehir (Turkey) was evaluated in a 10-year period (2004-2014) through the integration of remote sensing (RS) and geographical information systems (GIS). Through the use of satellite images with high ground sample distance-QuickBird (60 cm) (2004) and Worlview-2 (50 cm) (2014)-the direction of urban expansion and changes which occurred in urban open-green spaces and urban development areas were examined in detail at the whole city and district scales. Analyses consist of satellite image classification, plant index production, and GIS-based analyses methods. According to the results, it was determined that from 2004 to 2014, the 23.28% decrease in urban open-green spaces was detected in Nevsehir city. It was observed that the city expands towards the north-east, south-west, and west. It was indicated that there is a serious increase in built-up areas especially at the north-east part of the city (107.11%). Thus, a significant decrease has happened in the amount of urban open-green spaces in this area.

The Low-Impact Development Demand Index: A New Approach to Identifying Locations for LID

The primary goal of low impact development (LID) is to capture urban stormwater runoff; however, multiple indirect benefits (environmental and socioeconomic benefits) also exist (e.g., improvements to human health and decreased air pollution). Identifying sites with the highest demand or need for LID ensures the maximization of all benefits. This is a spatial decision-making problem that has not been widely addressed in the literature and was the focus of this research. Previous research has focused on finding feasible sites for installing LID, whilst only considering insufficient criteria which represent the benefits of LID (either neglecting the hydrological and hydraulic benefits or indirect benefits). This research considered the hydrological and hydraulic, environmental, and socioeconomic benefits of LID to identify sites with the highest demand for LID. Specifically, a geospatial framework was proposed that uses publicly available data, hydrological-hydraulic principles, and a simple additive weighting (SAW) method within a hierarchical decision-making model. Three indices were developed to determine the LID demand: (1) hydrological-hydraulic index (HHI), (2) socioeconomic index (SEI), and (3) environmental index (ENI). The HHI was developed based on a heuristic model using hydrological-hydraulic principles and validated against the results of a physical model, the Hydrologic Engineering Center-Hydrologic Modeling System model (HEC-HMS). The other two indices were generated using the SAW hierarchical model and then incorporated into the HHI index to generate the LID demand index (LIDDI). The framework was applied to the City of Toronto, yielding results that are validated against historical flooding records.

Testing the Poleotolerance Lichen Response Trait as an Indicator of Anthropic Disturbance in an Urban Environment

Urban environments are densely populated areas buzzing with a wide range of anthropic activities that cause disturbances like air pollution or the heat island effect, threatening both human and environmental health. Mitigating its impacts implies understanding the integrated effects that those disturbances exert on urban environments. Lichen biodiversity is frequently used as an ecological indicator, being able to integrate its effects in a quantifiable way. The poleotolerance response trait classifies lichens according to their tolerance to human disturbance, but it was developed for Italy’s flora and has seldom been applied outside Italy or in urban context studies. The aim of this work was to assess this trait suitability as an indicator of urban anthropic disturbance and test it outside Italy. For that, we sampled lichen diversity in 41 green spaces in Lisbon. Lichens were classified into the respective poleotolerance trait functional groups and their community weighted mean related with three type of environmental variables used as surrogates of urban disturbance. We showed that disturbance-tolerant functional groups could be used as an ecological indicator of the integrated effects of environmental disturbances. Some species were clearly misclassified, so we propose reclassification for those. Natural and seminatural functional groups did not behave as expected. Nevertheless, disturbance-tolerant functional groups have the potential to be used in in other Southern European cities.