•We developed a green accessibility index to study access to urban green space.•The cold and hot spots of green accessibility were identified to offer policy insights.•Shanghai and its urban ...periphery have improved the green accessibility.•The inner and outer suburbs diverged in improvement of green accessibility.•Institutional factors affected urbanization and green accessibility in urban periphery.
We studied the accessibility of public urban green spaces in the context of rapid land transformation within the urban periphery. By using Shanghai, China as a case study, we illustrated how to evaluate the access to public green spaces of an urban periphery and how planning processes can influence the improvement of such access. We constructed a composite index named the “green accessibility index” (GAI), which measures how well residents are treated in terms of access to different types of public urban green spaces. Shanghai and its districts have improved their green accessibility index from 2000 to 2010. However, the GAI in the urban periphery fell behind the city average. Furthermore, while the inner suburbs, especially Pudong and Baoshan, had fared quite well in green accessibility improvement, outer suburbs made moderate progress in comparison to the city average. We identified hot/cold spots and spatial clustering that had a high/low green accessibility index in the urban periphery. The cold spots are in urgent need of substantial improvements to green space accessibility.
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As a consequence of the global increase in economic and societal prosperity, ecosystems and natural resources have been substantially exploited, degraded, or even destroyed in the last century. To ...prevent further deprivation of the quality of ecosystems, the ecosystem services concept has become a central issue in environmental studies. A growing number of environmental agencies and organizations worldwide are now embracing integrated approaches to plan and manage ecosystems, sharing a goal to maintain the long-term provision of ecosystem services for sustainability. A daunting challenge in this process is to move from general pronouncements about the tremendous benefits that ecosystems provide to society to defensible assessments of their services. In other words, we must move beyond the scientific evidences of the ecosystem services concept to its practical applications. In this work, we discuss the theoretical foundations and applications of ecosystem services with a focus on the assessment of ecosystem service trade-offs and synergies at various spatial and temporal scales. Here, we offer examples of the main factors related to land use management that may affect the provision of ecosystem services and provide direction for future research on ecosystem services and related nature-based solutions. We also provide a briefing on the major topics covered in this Special Issue, which focuses on the provision of ecosystem services in the context of global change.
•Theoretical foundations and applications of the ecosystem services concept are discussed.•The main factors that may affect ecosystem services trade-offs and synergies are devised.•A framework to link up “evidence” and “application” in ecosystem service studies is provided.•Nature-based solutions are proposed as way to apply the ecosystem services concept.
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The past five decades have witnessed a rapid growth of computer models for simulating ecosystem functions and dynamics. This has been fueled by the availability of remote sensing data, computation ...capability, and cross-disciplinary knowledge. These models contain many submodules for simulating different processes and forcing mechanisms, albeit it has become challenging to truly understand the details due to their complexity. Most ecosystem models, fortunately, are rooted in a few core biophysical foundations, such as the widely recognized Farquhar model, Ball-Berry-Leuning and Medlyn family models, Penman-Monteith equation, Priestley-Taylor model, and Michaelis-Menten kinetics. After an introduction of biophysical essentials, four chapters present the core algorithms and their behaviors in modeling ecosystem production, respiration, evapotranspiration, and global warming potentials. Each chapter is composed of a brief introduction of the literature, in which model algorithms, their assumptions, and performances are described in detail. Spreadsheet (or Python codes) templates are included in each chapter for modeling exercises with different input parameters as online materials, which include datasets, parameter estimation, and real-world applications (e.g., calculations of global warming potentials). Users can also apply their own datasets. The materials included in this volume serve as effective tools for users to understand model behaviors and uses with specified conditions and in situ applications.
The past five decades have witnessed a rapid growth of computer models for simulating ecosystem functions and dynamics. This has been fuelled by the availability of remote sensing data, computation ...capability, and cross-disciplinary knowledge. These models contain many submodules for simulating different processes and forcing mechanisms, albeit it has become challenging to truly understand the details due to their complexity. Most ecosystem models, fortunately, are rooted in a few core biophysical foundations, such as the widely recognized Farquhar model, Ball-Berry-Leuning and Medlyn family models, Penman-Monteith equation, Priestley-Taylor model, and Michaelis-Menten kinetics.an introduction of biophysical essentials, four chapters present the core algorithms and their behaviors in modeling ecosystem production, respiration, evapotranspiration, and global warming potentials. Each chapter is composed of a brief introduction of the literature, in which model algorithms, their assumptions, and performances are described in detail. Spreadsheet (or Python codes) templates are included in each chapter for modeling exercises with different input parameters as online materials, which include datasets, parameter estimation, and real-world applications (e.g., calculations of global warming potentials). Users can also apply their own datasets. The materials included in this volume serve as effective tools for users to understand model behaviours and uses with specified conditions and in situ applications.
Abstract
Assessments of changes in landscape patterns and functions during urban development need to factor urban fringes (UPs) as part of the overall social-environmental system, especially in ...regions with poor transportation systems where urban functions depend heavily on surrounding suburbs. In this study, we use net primary production (NPP) as an integrative measure to delineate UPs and to measure the expansion in 15 urban areas in the remote Qinghai-Tibet Plateau. Using a logistic curve fitting model based on NPP to delineate differences between the UF and rural landscapes, we explore how NPP-inferred UF expansions may have changed with increase in urban population and the secondary and tertiary industrial production. The UF width (area) was 17.4 km (950.67 km
2
) in 2000 but increased to 27.0 km (2289.06 km
2
) in 2019 for Lhasa. For Xining, this was from 28.0 km (2461.76 km
2
) to 36.0 km (4069.44 km
2
) during 2000–2019. For the prefecture-level cities, the rate increased from 2–16 km (12.56–803.84 km
2
) to 7–17 km (153.86–907.46 km
2
). More importantly, the ratio between UF width and population during the five study periods showed a linear decreasing trend, but an exponential decrease with economic measures. The urban expansion due to population increase changed from 26 m in 2000 to 21 m in 2019 for every increase of 1000 residents, while the expansion due to economic changes was significantly reduced from 732 m per billion RMB (Ren Min Bi) in 2000 to 52 m per billion RMB in 2019. We confirm a hypothesis that the ratio of expansion of UFs was more dependent on economic growth in early stages of urbanization than in later stages, whereas urban population promoted expansions over the entire study period.
Driven by drastic socioeconomic changes in China and Mongolia, urbanization has become one of the most significant driving forces in the transformation of the Mongolian Plateau in the past 30 years. ...Using Hohhot and Ulaanbaatar as case studies, we developed a holistic approach to examine the socioeconomic and natural driving forces for urbanization and to investigate the impact on the urban environment. We used a multidisciplinary approach and relied on a variety of data sources to assess the changes of the landscape and environment of the two cities. We detected a rapid urbanization in Hohhot and Ulaanbaatar, both in terms of urban population growth and urban land expansion, from 1990 to 2010, with a much faster speed in 2000–2010. The local geo-physical conditions have constrained the spatial direction of expansion. Ulaanbaatar lagged behind Hohhot for about a decade when measured by indicators of urban population and urban land. Both cities have a degraded urban environment and a growing air pollution epidemic. While Hohhot had worse air pollution than Ulaanbaatar in the early 2000s, the gap between the two cities became smaller after 2010.
The research presented here highlights the following as key determinants for urbanization and environmental change: (1) the co-evolution of urbanization, economic development, and environmental change; (2) the urbanization of transitional economies driven by the change of the economic structure, i.e., the development by both manufacturing and tertiary sectors and the change in the primary sector; and (3) the recent institutional changes and increased integration with the global economy.
•We compared urbanization and environment change of Hohhot and Ulaanbaatar.•Both had fast growth in population and land but Hohhot was ahead of Ulaanbaatar.•Both did not improve their air quality but the gap between the two gets smaller.•The impact of economic development on urbanization decreases as economy develops.•Globalization and institutional factors are also key determinants of urbanization.
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•Forest area in Shenzhen was restored to 85% of the pre-urbanization level by 2005.•Yet, forest fragmentation in Shenzhen continued from 1979 to 2005.•Forest fragmentation rates were found to be ...nonlinear over the study period.•Socioeconomic drivers explained 75.9% of the changes in the fragmentation rates.•Both positive and negative socioeconomic influences were found to be drivers.
Urban forests are valuable resources in coupled human and natural urban systems where green spaces are essential in maintaining ecological benefits and services of the landscape. In southern coastal China, the Shenzhen Special Economic Zone (SEZ) was established as a new city in 1979 and developed to be a megacity from an agriculture-dominated landscape. To quantify the land-use change during this rapid urbanization process and explore the underline drivers, nine sets of Landsat images from 1973 through 2005 were used to calculate the landscape metrics of forest patches. We found that the forest in Shenzhen SEZ had been restored to 85.85% of pre-urbanization coverage by 2005, but was characterized with smaller, isolated patches across the landscape. The changes in patch density, distribution, and shape during the 30-year study period were nonlinear and defined by episodic periods. The stepwise multiple regression models with socioeconomic drivers provided further explanation for fragmentation rates in patch density, distribution, and shape, with modeled R-squared of 0.837, 0.759, and 0.985 and P-values of 0.011, 0.035, and 0.004, respectively. Among the drivers, urban structure change, industry-related economic booming, and the increase of migrant resident population triggered the urban forest fragmentation while the significantly increased income of city residents drove the de-fragmentation trend. The artificial forestation showed some but a limited role in mitigating forest fragmentation.
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Abstract
The replacement of natural lands with urban structures has multiple environmental consequences, yet little is known about the magnitude and extent of albedo-induced warming contributions ...from urbanization at the global scale in the past and future. Here, we apply an empirical approach to quantify the climate effects of past urbanization and future urbanization projected under different shared socioeconomic pathways (SSPs). We find an albedo-induced warming effect of urbanization for both the past and the projected futures under three illustrative scenarios. The albedo decease from urbanization in 2018 relative to 2001 has yielded a 100-year average annual global warming of 0.00014 0.00008, 0.00021 °C. Without proper mitigation, future urbanization in 2050 relative to 2018 and that in 2100 relative to 2018 under the intermediate emission scenario (SSP2-4.5) would yield a 100-year average warming effect of 0.00107 0.00057,0.00179 °C and 0.00152 0.00078,0.00259 °C, respectively, through altering the Earth’s albedo.
Nature-based solutions (NBS) are increasingly applied to guide the design of resilient landscapes and cities to enable them to reach economic development goals with beneficial outcomes for the ...environment and society. The NBS concept is closely related to other concepts including sustainability, resilience, ecosystem services, coupled human and environment, and green (blue) infrastructure; however, NBS represent a more efficient and cost-effective approach to development than traditional approaches. The European Commission is actively engaged in investing in NBS as a driver in developing ecosystem services-based approaches throughout Europe and the world. The pool of knowledge and expertise presented in this Special Issue of Environmental Research highlights the applications of NBS as ‘living’ and adaptable tools to boost the capacity of landscapes and cities to face today’s critical environmental, economic and societal challenges. Based on the literature and papers of this Special Issue, we propose five specific challenges for the future of NBS.
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Using Barcelona and Shanghai as case studies, we examined the nature-based solutions (NBS) in urban settings-specifically within cities experiencing post-industrialization and globalization. Our ...specific research questions are: (1) What are the spatiotemporal changes in urban built-up land and green space in Barcelona and Shanghai? (2) What are the relationships between economic development, exemplified by post-industrialization, globalization, and urban green space? Urban land use and green space change were evaluated using data derived from a variety of sources, including satellite images, landscape matrix indicators, and a land conversion matrix. The relationships between economic development, globalization, and environmental quality were analyzed through partial least squares structural equation modeling based on secondary statistical data. Both Barcelona and Shanghai have undergone rapid urbanization, with urban expansion in Barcelona beginning in the 1960s-1970s and in Shanghai in the last decade. While Barcelona's urban green space and green space per capita began declining between the 1950s and 1990s, they increased slightly over the past two decades. Shanghai, however, has consistently and significantly improved urban green space and green space per capita over the past six decades, especially since the economic reform in 1978. Economic development has a direct and significant influence on urban green space for both cities and post-industrialization had served as the main driving force for urban landscape change in Barcelona and Shanghai. Based on secondary statistical and qualitative data from on-site observations and interviews with local experts, we highlighted the institution's role in NBS planning. Furthermore, aspiration to become a global or globalizing city motivated both cities to use NBS planning as a place-making tool to attract global investment, which is reflected in various governing policies and regulations. The cities' effort to achieve a higher status in the global city hierarchy may have contributed to the increase in total green space and urban green per capita. In addition, various institutional shifts, such as land property rights in a market economy vs. a transitional economy, may also have contributed to the differences in efficiency when expanding urban green space in Barcelona and Shanghai.
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