Search Results (65)

As urbanization accelerates and climate change intensifies, the ecological integrity of urban riparian forests faces growing threats, underscoring the need for a systematic framework to guide their sustainable management. To address this gap, we developed a causal framework by applying text mining and sentence classification to 1001 abstracts from previous studies, structured within the DPSIR (Driver–Pressure–State–Impact–Response) model. The analysis identified six dominant thematic clusters—water quality, ecosystem services, basin and land use management, climate-related stressors, anthropogenic impacts, and greenhouse gas emissions—which reflect the multifaceted concerns surrounding urban riparian forest research. These themes were synthesized into a structured causal model that illustrates how urbanization, land use, and pollution contribute to ecological degradation, while also suggesting potential restoration pathways. To validate its applicability, the framework was applied to four major urban streams in Seoul, where indicator-based analysis and correlation mapping revealed meaningful linkages among urban drivers, biodiversity, air quality, and civic engagement. Ultimately, by integrating large-scale text mining with causal inference modeling, this study offers a transferable approach to support adaptive planning and evidence-based decision-making under the uncertainties posed by climate change. Full article

In the face of increasingly complex urban challenges, a critical question arises: can urban ecosystems maintain resilience, vitality, and sustainability when confronted with external threats and pressures? Taking Kunming—a plateau-mountainous city in China—as a case study, this research constructs an urban ecosystem resilience (UER) assessment model based on the DPSIR (Driving forces, Pressures, States, Impacts, and Responses) framework. A total of 25 indicators were selected via questionnaire surveys, covering five dimensions: driving forces such as natural population growth, annual GDP growth, urbanization level, urban population density, and resident consumption price growth; pressures including per capita farmland, per capita urban construction land, land reclamation and cultivation rate, proportion of natural disaster-stricken areas, and unit GDP energy consumption; states measured by Evenness Index (EI), Shannon Diversity Index (SHDI), Aggregation Index (AI), Interspersion and Juxtaposition Index (IJI), Landscape Shape Index (LSI), and Normalized Vegetation Index (NDVI); impacts involving per capita GDP, economic density, per capita disposable income growth, per capita green space area, and per capita water resources; and responses including proportion of natural reserve areas, proportion of environmental protection investment to GDP, overall utilization of industrial solid waste, and afforestation area. Based on remote sensing and other data, indicator values were calculated for 2006, 2011, and 2016. The entire-array polygon indicator method was used to visualize indicator interactions and derive composite resilience index values, all of which remained below 0.25—indicating a persistent low-resilience state, marked by sustained economic growth, frequent natural disasters, and declining ecological self-recovery capacity. Forecasting results suggest that, under current development trajectories, Kunming’s UER will remain low over the next decade. This study is the first to integrate the DPSIR framework, entire-array polygon indicator method, and Grey System Forecasting Model into the evaluation and prediction of urban ecosystem resilience in plateau-mountainous cities. The findings highlight the ecosystem’s inherent capacities for self-organization, adaptation, learning, and innovation and reveal its nested, multi-scalar resilience structure. The DPSIR-based framework not only reflects the complex human–nature interactions in urban systems but also identifies key drivers and enables the prediction of future resilience patterns—providing valuable insights for sustainable urban development. Full article

Iraq has faced escalating water scarcity over the past two decades, driven by climate change, upstream water withdrawals, and prolonged economic instability. These factors have caused deterioration in irrigation systems, inefficient water distribution, and growing social unrest. As per capita water availability falls below critical levels, Iraq is entering a period of acute water stress. This escalating water scarcity directly impacts water and food security, public health, and economic stability. This study aims to develop a general framework combining decision support systems (DSSs) with Integrated Comprehensive Water Management Strategies (ICWMSs) to support water planning, allocation, and response to ongoing water scarcity and reductions in Iraq. Implementing such a system is essential for Iraq to alleviate its continuing severe situation and adequately tackle its worsening water scarcity that has intensified over the years. This integrated approach is fundamental for enhancing planning efficiency, improving operational performance and monitoring, optimizing water allocation, and guiding informed policy decisions under scarcity and uncertainty. The current study highlights various international case studies that show that DSSs integrate real-time data, artificial intelligence, and advanced modeling to provide actionable policies for water management. Implementing such a framework is crucial for Iraq to mitigate this critical situation and effectively address the escalating water scarcity. Furthermore, Iraq’s water management system requires modifications considering present and expected future challenges. This study analyzes the inflows of the Tigris and Euphrates rivers from 1933 to 2022, revealing significant reductions in water flow: a 31% decrease in the Tigris and a 49.5% decline in the Euphrates by 2021. This study highlights the future 7–20% water deficit between 2020 and 2035. Furthermore, this study introduces a flexible, tool-based framework supported by a DSS with the DPSIR model (Driving Forces, Pressures, State, Impacts, and Responses) designed to address and reduce the gap between water availability and increasing demand. This approach proposes a multi-hazard risk matrix to identify and prioritize strategic risks facing Iraq’s water sector. This matrix links each hazard with appropriate DSS-based response measures and supports scenario planning under the ICWMS framework. The proposed framework integrates hydro-meteorological data analysis with hydrological simulation models and long-term investment strategies. It also emphasizes the development of institutional frameworks, the promotion of water diplomacy, and the establishment of transboundary water allocation and operational policy agreements. Efforts to enhance national security and regional stability among riparian countries complement these actions to tackle water scarcity effectively. Simultaneously, this framework offers a practical guideline for water managers to adopt the best management policies without bias or discrimination between stakeholders. By addressing the combined impacts of anthropogenic and climate change, the proposed framework aims to ensure rational water allocation, enhance resilience, and secure Iraq’s water strategies, ensuring sustainability for future generations. Full article

Water resources are a key constraint on sustainable development in arid regions, especially for agricultural production where water use is intensive. To assess the sustainability of agricultural water use in such environments, this study utilizes 2010–2020 agricultural data from the Turpan–Hami Basin and is among the first to integrate the water footprint (WF) theory with the DPSIR (driver–pressure–state–impact–response) model into a comprehensive framework for evaluating water resource sustainability in arid agricultural systems. The agricultural blue, green, and grey WF in the Turpan–Hami Basin were quantified for 2010–2020, followed by a sustainability assessment under the DPSIR framework using a comprehensive weighting method. The results showed a continuous increase in the WF, dominated by the blue WF (>60%), largely due to crops like cotton and grapes, intensifying regional water stress. Turpan experienced prolonged resource overload, while Hami exhibited slightly higher sustainability. DPSIR analysis revealed stronger policy responses in Turpan and significant ecological investments in Hami. Key influencing factors included the crop yield, WF modulus, per capita WF, and water quality shortage index. Overall, sustainability in the basin fluctuated between “Basically Sustainable (Level III)” and “Insufficiently Sustainable (Level IV)”, with slight improvement in 2020. The findings highlight the need for region-specific agricultural optimization, strengthened ecological governance, and improved water-saving strategies to enhance water use efficiency and sustainability in arid regions. Full article

The Yangtze River Delta (YRD) region, located inside the Yangtze River Basin, functions as a vital ecological and economic area in China, with its natural environment directly impacting human existence. This study seeks to elucidate the spatial and temporal evolution of rural resilience in the Yangtze River Delta region and its underlying mechanisms by establishing a comprehensive assessment framework for rural resilience, thereby offering a scientific foundation and policy guidance for the region’s sustainable development. The research first established the DPSIR (driving force–pressure–state–impact–response) assessment index system. Subsequently, the entropy weighting method and TOPSIS were utilized to assess and rank the rural resilience levels in the Yangtze River Delta region (Shanghai, Jiangsu, Zhejiang, and Anhui) from 2012 to 2022. Ultimately, partial least squares structural equation modeling (PLS-SEM) was employed to examine the intrinsic logical relationships among the five dimensions of the DPSIR framework and to extract conclusions. The study effectively met the goals of SDG 7 (clean water and sanitation), SDG 8 (decent work and economic growth), and SDG 11 (sustainable cities and communities). The research indicated that (1) the resilience level in the Yangtze River Delta region initially declined, then increased, and eventually attained a condition of stabilization. Changes in the “driving force”, influenced by the “response level” and environmental “pressure”, have affected the resilience level of rural areas. There is heterogeneity in the assessment values and ranges of change among provinces, with the “impact” component exhibiting the most substantial evaluation value. The findings yield policy recommendations for the implementation of diverse regional governance, the establishment of connectivity mechanisms, the customization of strategies to address the specific deficiencies of each province, and the systematic enhancement of rural resilience. Full article

Coal mining in the eastern Huaihe Plain has led to land degradation and hydrological disturbances, transforming terrestrial ecosystems into a complex of terrestrial and aquatic systems. These changes significantly impact regional ecological processes, structure, and functions. Hence, assessing the health condition and restoring the degraded subsidence wetlands efficiently have become urgent issues in coal resource-based cities. This research developed an ecosystem health assessment model for mining subsidence wetlands using the Driving Force–Pressure–State–Impact–Response (DPSIR) framework, with a focus on the subsidence wetlands of Yingshang County, Anhui Province. The assessment findings indicated that the wetland ecosystem was in a sub-healthy condition, with a health score of 0.51. Specific scores for the subsystems “Driving Force”, “Pressure”, and “State” were 0.584, 0.690, and 0.537, respectively, indicating that these subsystems were categorized as healthy, very healthy, and sub-healthy. In contrast, the scores for the “Impact” and “Response” subsystems were 0.076 and 0.093, both falling within the very poor (V) status. Weight analysis of the indicators revealed that the regional development index (Cp1), mining subsidence disturbance intensity (Cp2), aggregation index (Cs3), diversity index (Cs4), and wetland conservation rate (Cr1) significantly affected wetland ecosystem health. Taking into account both the health assessment results and the specific environmental conditions of the study area, this research recommends restoration strategies and the preservation of wetland ecosystems. The findings from this study can provide a basis for governmental bodies to create specific strategies and policies aimed at the conservation and management of subsidence wetlands. Full article

In recent years, the disruption of the prefabricated building supply chain has led to increased construction period delays and cost overruns, limiting the development and popularization of prefabricated buildings in China. Therefore, this study established a vulnerability evaluation index system for the prefabricated building supply chain using the driving force–pressure–state–impact–response (DPSIR) framework. We employed the intuitionistic fuzzy analytic hierarchy process (IFAHP), the projection pursuit (PP) model, and variable weight theory to determine the indicator weights. The IFAHP was utilized to reduce the subjectivity in weight assignment and to obtain the degree of membership, non-membership, and hesitation of experts in evaluating the importance of indicators. The PP model was used to determine objective weights based on the structure of the evaluation data, and variable weight theory was applied to integrate subjective and objective weights according to management needs. We utilized Set Pair Analysis (SPA) to establish a vulnerability evaluation model for the building supply chain, treating evaluation data and evaluation levels as a set pair. By analyzing the degree of identity, difference, and opposition of the set pair, we assessed and predicted the vulnerability of the building supply chain. Taking the Taohua Shantytown project in Nanchang as a case study, the results showed that the primary index with the greatest influence on the vulnerability of the prefabricated building supply chain was the driving force, with a weight of 0.2692, followed by the secondary indices of market demand and policy support, with weights of 0.0753 and 0.0719, respectively. The project’s average vulnerability rating was moderate (Level III), and it showed an improvement trend. During the project’s implementation, the total cost overrun of the prefabricated building supply chain was controlled within 5% of the budget, the construction period delay did not exceed 7% of the plan, and the rate of production safety accidents was below the industry average. The results demonstrated that the vulnerability assessment method for the prefabricated building supply chain based on SPA comprehensively and objectively reflected the vulnerability of the supply chain. It is suggested to improve the transparency and flexibility of the supply chain, strengthen daily management within the supply chain, and enhance collaboration with supply chain partners to reduce vulnerability. Full article

China has a vast land area, with mountains accounting for 1/3 of the country’s land area. Flooding in these areas can cause significant damage to human life and property. Therefore, rainstorms and flood hazards in Huangshan City should be accurately assessed and effectively managed to improve urban resilience, promote green and low-carbon development, and ensure socio-economic stability. Through the Random Forest (RF) algorithm and the Soil Conservation Service (SCS) model, this study aimed to assess and demarcate rainstorm and flood hazard risks in Huangshan City. Specifically, Driving forces-Pressure-State-Impact-Response (DPSIR)’s framework was applied to examine the main influencing factors. Subsequently, the RF algorithm was employed to select 11 major indicators and establish a comprehensive risk assessment model integrating four factors: hazard, exposure, vulnerability, and adaptive capacity. Additionally, a flood hazard risk zoning map of Huangshan City was generated by combining the SCS model with a Geographic Information System (GIS)-based spatial analysis. The assessment results reveal significant spatial heterogeneity in rainstorm and flood risks, with higher risks concentrated in low-lying areas and urban fringes. In addition, precipitation during the flood season and economic losses were identified as key contributors to flood risk. Furthermore, flood risks in certain areas have intensified with ongoing urbanization. The evaluation model was validated by the 7 July 2020 flood event, suggesting that Huangshan District, Huizhou District, and northern Shexian County suffered the most severe economic losses. This confirms the reliability of the model. Finally, targeted flood disaster prevention and mitigation strategies were proposed for Huangshan City, particularly in the context of carbon neutrality and green urbanization, providing decision-making support for disaster prevention and emergency management. These recommendations will contribute to enhancing the city’s disaster resilience and promoting sustainable urban development. Full article

A systematic literature review was conducted on papers studying coastal socio-ecological systems (SESs) in adapting to climate change to support sustainable coastal management and contribute to achieving the UN SDGs. We selected, analyzed, and synthesized 173 peer-reviewed, English-language scientific publications using the PRISMA method. Firstly, we summarized and compared the selected literature; then, we explored its geographical distribution and respective coastal landscapes, and we identified and classified the adaptation strategies focused on different coastal landscapes. Furthermore, we processed the results obtained to develop a unique conceptual model based upon the DPSIR framework for coastal SESs adapting to climate change. This review shows a gradual increase in the number of published papers, particularly after the Paris Agreement, with an uneven distribution across the world. The number of papers and case studies was lower in highly vulnerable coastal areas, with the exception of Bangladesh. Most of the literature presented a local perspective rather than a national or transnational one, focusing more on vulnerability assessment than adaptation strategies. Recent studies have shown an increasing focus on ecosystem-based adaptation. Institutional and financial support are reported as the main constraints on ensuring long-term monitoring and beneficial impacts. Full article

The development of healthy building technology has become a major trend in the global construction industry, especially in China, owing to accelerating urbanization and increasing health awareness among residents. However, an effective evaluation framework to quantify and evaluate the maturity of healthy building technology is lacking. This paper proposes a novel maturity evaluation model for healthy building technology. After analyzing the Driver–Pressure–State–Impact–Response (DPSIR) framework for asserting the maturity of healthy building in China, it constructs an evaluation indicator system, comprising five and twenty-seven first- and second-class indicators, respectively. Subsequently, this paper constructs an improved projection pursuit model based on border collie optimization. The model obtains evaluation results by mining evaluation data, thus overcoming the limitations of traditional evaluation models in dealing with complex data. The empirical research results demonstrate that China is in the optimization stage in terms of the level of maturity of healthy building technology. The weight of impact is as high as 0.2743, which is the most important first-level indicator. Strict green energy utilization policy requirements are the most important secondary indicator, with a weight of 0.0513. Notably, the model is more advanced than other algorithms. In addition, this paper offers some countermeasures and suggestions to promote healthy building in China. Developing and applying this model can promote and popularize healthy building technology in China and even the globe and contribute to a healthier and more sustainable living environment. Full article

Sustainability in cities, and its accurate and exhaustive assessment, represent a major keystone of environmental sciences and policy making in urban planning. This study aims to provide methods for a reproducible, descriptive, predictive and prescriptive analysis of urban residential choices and mobility, which are key components of an urban system’s sustainability. Using the DPSIR framework for building agent evolution rules, we design an agent-based model of the canton of Geneva, Switzerland. The model leverages real geographical data for the canton of Geneva and its public transportation network. The resulting simulations show the dynamics of the relocation choices of commuters, in terms of the function of their travel time by public transportation to their workplace. Results show that areas around the city centre are generally preferred, but high rent prices and housing availability may prevent most residents from relocating to these areas. Other preferred housing locations are distributed around major tram and train lines and where rent prices are generally lower. The model and its associated tools are capable of spatialising aggregated statistical datasets, inferring spatial correlations, and providing qualitative and quantitative analysis of relocation dynamics. Such achievements are made possible thanks to the efficient visualisation of our results. The agent-based modelling methodology represents an adequate solution for understanding complex phenomena related to sustainability in urban systems, which can be used as guidance for policy making. Full article

Amidst the mounting global challenges associated with climate change and resource depletion, achieving sustainable development is paramount. Focusing on cities as vital scenarios for pursuing sustainability, this research measured urban sustainability and identified its obstacles. Employing the DPSIR (Driver–Pressure–State–Impact–Response) framework, we establish a metric system with 25 indicators to assess the urban sustainability of six innovation zones in China and identify their developmental impediments to sustainability with an obstacle model. The core findings of the study are as follows: First, over the five-year period, all six cities demonstrated a consistent increase in their urban sustainability levels except for Shenzhen, which experienced a decline from its top position among these cities due to a decrease in its score from 0.44296 to 0.36942 in 2017. Second, there was consistent urban sustainability progress in five cities, with the exception of Shenzhen, from 2016 to 2020. Third, inadequate government response emerges as a primary obstacle across all six cities, marked by shortcomings in public expenditure, R&D investment, and healthcare. Every year, all six cities experienced more than 60% obstacle degrees in terms of response, with the exception of Shenzhen in 2016. The urban sustainability pursuit model we developed bridges urban sustainability theory with practical interventions, promoting adaptive governance. In addition, this study provides scholars and policymakers with a comprehensive approach to gauging urban sustainability, recognizing obstacles, and designing strategies for a sustainable urban future. Full article

Unveiling the spatial and temporal distribution of urban ecological resilience and analyzing the configuration paths for enhancing its levels are crucial for promoting sustainable development in China. Our study integrates the DPSIR and EES models, considering the causal relationships between systems affecting urban ecological resilience while also examining their internal structures. Based on this, we construct an evaluation system for urban ecological resilience indicators. Utilizing the entropy-TOPSIS method, we assess the ecological resilience index (ERI) across 280 Chinese cities from 2011 to 2021, and the kernel density estimation and Markov chain are used to study the evolution process while the magnitude and source of spatial–regional differences are examined by the Dagum Gini coefficient decomposition method. Additionally, we empirically investigate the driving mechanisms toward high ERI with the focused stepwise quantitative case analysis (fsQCA) method based on the technology–organization–environment (TOE) framework. The results find that the ERI in China shows a tendency of moderate growth in variability, with an obvious gradient distribution: higher levels in the eastern and southern and lower levels in the western and northern regions. Also, ERI exhibits evolutionary features of increasing polarization and inter-regional differentiation. Spatial disparities gradually increase with fluctuations, driven primarily by transvariation density and intra-regional differences, contributing to a dual non-equilibrium state of east–west and north–south directions. Achieving a high ERI is influenced by various antecedent variables interacting with each other, and there are three predominant driving paths among these variables, with the level of informatization playing a central role in each pathway. Full article

This study quantified uncertainties involved in assessing the future flood vulnerability in 33 urban areas with population exceeding designated thresholds in South Korea. The driver-pressure-state-impact-response (DPSIR) framework was utilized as the study procedure, integrating social, economic, and environmental factors. In addition, a total of 220 cases of combinations were examined, encompassing twenty general circulation models combined with shared socioeconomic pathway scenarios, five weight determination methods, and three multi-criteria decision-making (MCDM) techniques, as sources of inherent uncertainties in the process. The rankings of urban flood vulnerability (UFV) for the selected cities were comprehensively assessed considering all combinations, followed by an analysis of variance test to investigate contributing sources of uncertainties. As a result, Incheon and Busan were found to be vulnerable to flooding, while Yeongcheon and Andong appeared to be safe cities. Some cities exhibited wide ranges in their rankings, such as Daegu, Yangpyeon, and Jeongeup. The identified contributing sources were weighting (58%), MCDM (27%), and the combination of weighting and MCDM methods together (15%). This study revealed that weight determination methods and MCDM techniques are the primary sources of uncertainties in the assessment of future UFV instead of multiple GCMs and SSPs. This finding underscores the importance for decision-makers and stakeholders to carefully consider these uncertainties for sustainable flood risk management and prevention. Full article

The green transition of China’s cities is crucial for ecology civilization realization. Based on the driver–pressure–state–impact–response (DPSIR) framework, an integrated technique for order preference by similarity to ideal solution (TOPSIS) model with entropy weight, this study achieved the comprehensive assessment of the green transition of 288 province-level municipalities and prefecture-level cities in China over 18 years from 2002 to 2019, in addition to the spatial correlations and obstacles analysis. The results indicate that major cities in China have a more significant green transition value, and the eastern region is developing fast, while the northeast region is relatively slow. There was heterogeneous spatial distribution for green transition, because of the disequilibrium sustainable development of 288 cities. Green transition has a significantly positive spatial autocorrelation in the cities of China, the high–high significant clusters greatly increased, and the main locations changed from the northeast to southeast of China. Frequent obstacles were also found, including road infrastructure construction, water resources, and the green coverage of urban built-up areas. Based on these results, several policy implications were put forward, including the optimization of environmental laws and regulations, the development of green transportation infrastructure, resource conservation and the circular economy, the establishment of a green financial system, and increasing the linkage for the green transition of different cities. Full article