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.

Effect of vegetation treatment and water stress on evapotranspiration in bioretention systems

Evapotranspiration is a key hydrological process for reducing stormwater runoff in bioretention systems, regardless of their physical configuration. Understanding the volumes of stormwater that can be returned to the atmosphere via evapotranspiration is, therefore, a key consideration in the design of any bioretention system. This study establishes the evapotranspiration dynamics of three common, structurally different, bioretention vegetation treatments (an Amenity Grass mix, and mono-cultures of Deschampsia cespitosa and Iris sibirica) compared with an un-vegetated control using lab-scale column experiments. Via continuous mass and moisture loss data, observed evapotranspiration rates were compared with those predicted by the FAO-56 Penman-Monteith model for five 14-day dry periods during Spring 2021, Summer 2021, and Spring 2022. Soil moisture reductions over the 14-day trials led to reduced rates of evapotranspiration. This necessitated the use of a soil moisture extraction function alongside a crop coefficient to represent actual evapotranspiration from FAO-56 Penman-Monteith reference evapotranspiration estimates. Crop coefficients (Kc) varied between 0.65 and 2.91, with a value of 1.0 identified as a recommended default value in the absence of treatment-specific empirical data. A continuous hydrological model with Kc=1.0 and a loading ratio of 10:1 showed that evapotranspiration could account for between 1 and 12% of the annual water budget for a bioretention system located in the UK and Ireland, increasing to a maximum of 35% when using the highest Kc observed (2.91).

Modelling Green Volume Using Sentinel-1, -2, PALSAR-2 Satellite Data and Machine Learning for Urban and Semi-Urban Areas in Germany

Urban Green Infrastructure (UGI) provides ecosystem services such as cooling of temperatures and is majorly important for climate change adaptation. Green Volume (GV) describes the 3-D space occupied by vegetation and is highly useful for the assessment of UGI. This research uses Sentinel-2 (S-2) optical data, vegetation indices (VIs), Sentinel-1 (S-1) and PALSAR-2 (P-2) radar data to build machine learning models for yearly GV estimation on large scales. Our study compares random and stratified sampling of reference data, assesses the performance of different machine learning algorithms and tests model transferability by independent validation. The results indicate that stratified sampling of training data leads to improved accuracies when compared to random sampling. While the Gradient Tree Boost (GTB) and Random Forest (RF) algorithms show generally similar performance, Support Vector Machine (SVM) exhibits considerably greater model error. The results suggest RF to be the most robust classifier overall, achieving highest accuracies for independent and inter-annual validation. Furthermore, modelling GV based on S-2 features considerably outperforms using only S-1 or P-2 based features. Moreover, the study finds that underestimation of large GV magnitudes in urban forests constitutes the biggest source of model error. Overall, modelled GV explains around 79% of the variability in reference GV at 10 m resolution and over 90% when aggregated to 100 m resolution. The research shows that accurately modelling GV is possible using openly available satellite data. Resulting GV predictions can be useful for environmental management by providing valuable information for climate change adaptation, environmental monitoring and change detection.

Quantitative estimation of the PM2.5 removal capacity and influencing factors of urban green infrastructure

Long-term exposure to PM_2.5 (fine particulate matter with an aerodynamic diameter <2.5 μm) could cause great harm to human health and sustainable development. It remains a challenge to estimate the long-term PM_2.5 removal capacity of nature-based green infrastructure in urban areas. In this paper, the annual PM_2.5 removal capacity of urban green infrastructure (UGI) from 2000 to 2019 in Shenyang was estimated based on the PM2.5 dry deposition model. The spatial heterogeneity of annual PM_2.5 removal capacity were detected Sen-MK test and local spatial autocorrelations analysis. Then the effects of landscape patterns and socioeconomic variables on PM_2.5 removal capacity were explored based on linear regression model. The results illustrated that the PM_2.5 removal capacity of UGI increased significantly from 2000 to 2019 in Shenyang, with the amount of PM_2.5 removal, PM_2.5 removal flux and removal rate increasing by 20.64 Mg/a, 0.0258 g/m²/a, and 0.377 %/a, respectively. The PM_2.5 removal capacity of UGI exhibited spatial heterogeneity in the study area. Specifically, the regions experiencing the increase in PM_2.5 removal capacity of UGI accounted for majority of the old urban area of Shenyang City during the study period; the lower PM_2.5 removal capacity clustered in the center urban area, in which high density impervious surfaces distributed, while the higher PM_2.5 removal capacity mainly gathered in the area with large scale green space; PM_2.5 removal capacity were significantly higher in urban functional zones with a high proportion of green spaces. The landscape metrics representing fragmentation and shape complexity positively affected the annual PM_2.5 removal flux and removal rate, while the aggregation metrics had significantly negative correlations with the PM_2.5 removal flux and removal rate. Moreover, it was also found that population density and GDP negatively affected the PM_2.5 removal capacity of UGI. This study provides a methodological reference and some new insights for future urban landscape planning and air pollution purification.

Spatial effects of urban green infrastructure on instream water quality assessed by chemical and sensory indicators

Urban green infrastructure has been simulated effectively and economically to reduce volume and pollutants of stormwater runoffs but its spatial effects remain unclear. A snap sampling campaign was carried out for surface water quality in the downtown waterway network of a pilot sponge city (Suzhou) in China, dividing into 7 subwatersheds according to the digital elevation map. In total, 144 sampling points were investigated and measured for chemical quality of surface water while 68 out of the sampling points had a sensory evaluation questionnaire interview for water quality with 321 respondents, in whom the native residents scored a significant spatiality of water quality. The downtown waterway network had phosphorus-limited eutrophic surface water with total nitrogen worse than Class V of the national guidelines. Chemical and sensory evaluation indexes of surface water quality had significant spatial consistency (p < 0.001). All types of green spaces (%) in subwatershed, especially along the urban waterway network (waterfront) and roadside, and in the 100 m riparian buffer zone, significantly influenced nutrient loads in surface water. Findings of the present study suggest that the 100 m riparian buffer zone would be priority areas and the waterfront and roadside should be the highly efficient spots for planning strategy on urban green infrastructure implementation to reduce nutrient loads in surface water and to improve urban landscape aesthetics.

Integrating knowledge on green infrastructure, health and well-being in ageing populations: Principles for research and practice

Ageing and urbanisation pose significant challenges for public health and urban planning. Ageing populations are at particular risk from hazards arising from urbanisation processes, some of which are in turn exacerbated by climate change. One approach for mitigating the negative effects of urbanisation on ageing populations is the leveraging of the beneficial effects of urban green infrastructure as a public health intervention in the planning process. We assessed the potential of available theoretical frameworks to provide the context for such leverage. This involved active engagement with academics and practitioners specialising in ageing, green infrastructure and health and well-being through a knowledge-brokering approach. We concluded that an integrated and comprehensive framework on the socio-cultural-ecological determinants of health is lacking. To address this, we present a set of principles for overcoming challenges to knowledge integration when working at the intersection of green infrastructure, ageing, health and well-being. Our findings-and the co-production process used to generate them-have wider significance for trans-disciplinary research into the benefits of the natural environment to human health and well-being as well as other complex and interconnected topics associated with global grand challenges.

Assessment and potential of ecosystem services of ornamental dendroflora in public green areas

The green infrastructure of the city of Novi Sad is characterized by a significant presence of ornamental invasive alien species, which might lead to their uncontrolled spread and suppression of autochthonous dendroflora. This study aimed to determine the ecosystem services and disservices of ornamental dendroflora in Novi Sad, as well as how they can affect urban green areas. Of the total ornamental dendroflora in Novi Sad, 88.33% of species with a good adaptation were determined, while 10% had a medium and 1.67% had a very good adaptation. Thirty-four allochthonous species showed very high (38.24%), moderate (47.06%), and low (14.71%) invasive potential according to the conducted invasiveness risk assessment. These species are also characterized by high (2.94%), moderate (67.65%), and low (29.41%) allergenic potential. On the contrary, 26 ornamental autochthonous species are characterized by moderate (38.46%) and low (61.54%) rates of spread on public green areas, while also characterized by high (26.92%), moderate (50%), and weak (23.08%) allergenic potential. Ornamental dendroflora provides many more positive ecosystem services, such as urban afforestation, climate regulation, decorative-aesthetic value, air and water purification, ecotourism and recreation, and other services that are of great benefit to the residents of that city. The highest calculated values of ecosystem services in allochthonous and autochthonous species were 27 and 26.5 (out of possible maximal value 40), while ecosystem disservices accounted down to the value of - 13.5 (out of possible minimal value - 22). Therefore, intrinsic disservices such as the production of large amounts of green waste of ornamental dendroflora can be shifted into a novel ecosystem service-green solutions based on nature, to avoid unsuitable deposition of seeds in the soil and creation of suitable vegetation on public green areas.

Proposing a sustainable urban 3D model to minimize the potential risk associated with green infrastructure by applying engineering tools

The goal of this study is to estimate the potential risk of exposure to urban green infrastructure by calculating and improving of AIROT index, adding meteorological factors as wind direction and updating the index to be more accurate for smaller urban green areas. To achieve this objective, BIM methodology has been applied by creating a 3D BIM model from the reality capture of a street with LiDAR. The BIM model contains the parametric data needed to apply AIROT index and it allows to map results in a graphic environmental sustainability study. The importance of location of green infrastructure is one of main conclusions obtained in order to minimize aerobiological risks in future new buildings or even in maintenance tasks of urban green infrastructure. A valuable result obtained from the developed methodology are walk simulations in the 3D model with the aim to identify high risk of potential exposure of urban green infrastructure with allergenic interest for allergic patients in order to supply health itineraries of pedestrians in a proposal of Smart City.

A dataset of the flowering plants (Angiospermae) in urban green areas in five European cities

This article summarizes the data of a survey of flowering plants in 80 sites in five European cities and urban agglomerations (Antwerp, Belgium; greater Paris, France; Poznan, Poland; Tartu, Estonia; and Zurich, Switzerland). Sampling sites were selected based on a double orthogonal gradient of size and connectivity and were urban green areas (e.g. parks, cemeteries). To characterize the flowering plants, two sampling methodologies were applied between April and July 2018. First, a floristic inventory of the occurrence of all flowering plants in the five cities. Second, flower counts in sampling plots of standardized size (1 m²) only in Zurich. We sampled 2146 plant species (contained in 824 genera and 137 families) and across the five cities. For each plant species, we provide its origin status (i.e. whether the plants are native from Europe or not) and 11 functional traits potentially important for plant-pollinator interactions. For each study site, we provide the number of species, genera, and families recorded, the Shannon diversity as well as the proportion of exotic species, herbs, shrubs and trees. In addition, we provide information on the patch size, connectivity, and urban intensity, using four remote sensing-based proxies measured at 100- and 800-m radii.

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.

Impact of a green roof system on indoor fungal aerosol in a primary school in Greece

A primary school was investigated for airborne fungi by a culture-based method, in classrooms underneath a green roof in comparison to conventional concrete roofs. A portable Burkard sampler was used for the collection of air samples onto petri dishes with 2% Malt Extract Agar. The fungal aerosol mean concentration was 71 CFU m^-3 (range 17-176 CFU m^-3, median 51) in the classroom directly under the green roof, significantly lower than 192-228 CFU m^-3 (range 0-1090 CFU m^-3, median 69) under the concrete roofs and 188-412 CFU m^-3 (range 0-2183 CFU m^-3, median 771) in ground floor classrooms. The Indoor/Outdoor ratio was 0.4 for total fungi and 0.2-1.1 for predominant genera underneath the green roof, whereas 1-2.1 and 0.3-3.2 respectively for the rest of classrooms. The Potential Exposure Dose (PED) for fungal particles was calculated to 4.6 CFU kg^-1 and 9.3-35.3 CFU kg^-1 respectively. The genera Penicillium, Cladosporium and Aspergillus prevailed indoors and in ambient air. Aspergillus concentrations indoors correlated significantly with the concentration of the coarse fraction (PM10) of particulate matter. The genus Penicillium increased indoors during late spring and summer, in temperature 20-23 °C and relative humidity 42-53% and also predominated in ambient air, both indicative of multiple anthropogenic sources of amplification. The evidence about the green roof positive effect on microbial indoor air quality (mIAQ) is a matter of concern for further investigation.

Co-creating urban green infrastructure connecting people and nature: A guiding framework and approach

Urban green infrastructure (UGI) and nature-based solutions are increasingly recognized as instruments to address urban sustainability challenges, yet rely on a good understanding of complex social-ecological system (SES) to function adequately. Adaptive co-management (ACM), engaging a broad variety of stakeholders in collaborative learning, is an effective strategy to improve the resilience of a SES. However, ACM studies have been criticized for neglecting the urban context, while also offering little clarity on process objectives and outcomes. To address these knowledge gaps, while also drawing attention to the important issue of socially inclusive UGI development, we present a guiding framework and approach to encourage the ACM of UGI featuring two main components. Firstly, a Learning Alliance (LA) serves as an instrument for collaborative learning and experimentation across different scales. To facilitate upscaling, we propose to establish a complementary Urban Learning Lab (ULL) to facilitate a regular exchange between the LA and legitimate peripheral networks and stakeholders in the city region. Secondly, a stepwise approach to SES analysis serves to engage a representative group of stakeholders in the LAs and ULLs, and support the processes of setting LA objectives and monitoring of adaptive capacity. We illustrate our approach to the ACM of UGI with a case study of LivadaLAB in Ljubljana, Slovenia. Applying the framework and approach, we demonstrate increased adaptive capacity of the SES around UGI as indicated by: 1) improved overall stakeholder salience, in particular for previously disempowered actor groups, 2) increased number and strength of connections between stakeholders, and 3) the consideration of a broader range of sustainable development objectives by stakeholders in their daily practice.

Urban green space availability in Bathinda City, India

This paper aims to investigate and map the spatial distribution of urban green spaces (UGSs) in Bathinda City, India. Since urban green spaces affect the quality of life and provide various ecological, socio-cultural and economic benefits to a city, the spatial distribution of UGSs and per capita availability deserve greater consideration in urban planning and research. The UGSs are extracted from freely available Sentinel 2 image with spatial resolutions of 10 m (blue, green, red, and near infrared bands). The result indicates that the planned urban setups have higher area under UGSs as compared to the rest of the city. Analysis and intra-city comparison (ward wise) of distribution of green spaces and per capita availability indicate that there is an inequitable distribution of UGSs in Bathinda City. The study also attempts to accentuate the scope of green initiatives in the various wards of the city to ensure the well-being of people.

Innovative urban forestry governance in Melbourne?: Investigating "green placemaking" as a nature-based solution

A nature-based approach to climate resilience aims to challenge and re-frame conventional environmental management methods by refocusing solutions from technological strategies to socio-ecological principles such as human well-being and community-based governance models, thereby improving and legitimizing the delivery of ecosystem services (ES). There are, however, many challenges to applying a socio-ecological agenda to urban climate resilience and thereby re-framing ES delivery as community and people focused, a knowledge gap extensively outlined in the environmental governance literature. In this paper, we aim to contribute to this re-assesment of urban environmental governance by examining the City of Melbourne's approach to urban re-naturing governance from a place-based perspective. Here we focus on the city's internationally-acclaimed urban forest strategy (UFS), investigating how and to which extent the governance arrangements embedded within the UFS draw strength from diverse perspectives and allow for institutional arrangements that support "situated" reflexive decision making and co-creation. We find that Melbourne's UFS governance process fosters green placemaking by re-focusing climate adaptation solutions from technological strategies to situated socio-ecological principles such as human well-being and community-based decision making. In this sense, this case provides valuable insight for the broader UGI governance field regarding the opportunities and challenges associated with a socio-cultural approach to urban re-naturing and ES delivery.

Disentangling urban habitat and matrix effects on wild bee species

In face of a dramatic decline of wild bee species in many rural landscapes, potential conservation functions of urban areas gain importance. Yet effects of urbanization on pollinators, and in particular on wild bees, remain ambiguous and not comprehensively understood. This is especially true for amenity grassland and extensively managed wastelands within large-scale residential housing areas. Using Berlin as a study region, we aimed to investigate (a) if these greenspaces are accepted by wild bee assemblages as foraging habitats; (b) how assemblage structure of bees and individual bee species are affected by different habitat (e.g., management, flower density) and urban matrix variables (e.g., isolation, urbanization); and (c) to what extent grassland restoration can promote bees in urban environments. In summer 2012, we collected 62 bee species belonging to more than 20% of the taxa known for Berlin. Urbanization significantly affected species composition of bees; 18 species were affiliated to different levels of urbanization. Most bee species were not affected by any of the environmental variables tested, and urbanization had a negative effect only for one bee species. Further, we determined that restoration of diverse grasslands positively affected bee species richnesss in urban environments. We conclude that differently structured and managed greenspaces in large-scale housing areas can provide additional foraging habitats and refuges for pollinators. This supports approaches towards a biodiversity friendly management within urban regions and may be of particular importance given that anthropogenic pressure is increasing in many rural landscapes.