Microplastics in freshwater ecosystems have gained attention for their potential impact on biodiversity. Rivers are complex and dynamic ecosystems that transport particles and organic matter from the ...headwaters through watersheds to the ocean. Changes in land use and the presence of wastewater treatment plants (WWTPs) increase the risk of plastic contamination. Simultaneously, hydromorphological features of the watershed can influence the dispersion and retention of microplastics. This study assesses the impact of urban land uses and river hydromorphology on microplastic abundance and spatial distribution in two watersheds with contrasting land uses. Unexpectedly, our findings show that microplastics were widespread throughout watersheds both in water (3.5 ± 3.3 particles/L) and sediments (56.9 ± 39.9 particles/g). The concentration of microplastics in sediments significantly increased in granulometry ranging from 0.5 to 1 mm. Microplastics in running waters are significantly correlated with increasing urban land use coverage. However, the presence and distance of WWTPs did not affect microplastic distribution. In conclusion, contrasting patterns were observed for suspended and sedimented microplastic particles: suspended microplastics were associated with an anthropogenic effect, whereas the concentration of microplastics in sediments was determined by riverbed granulometry. Our results suggest that the interaction of anthropogenic and environmental factors shapes microplastic distribution along the rivers and their subsequent transport toward the coastal ocean. Finally, a review of the current literature reveals the absence of standardization in field and laboratory assessment techniques and measurement units, representing a challenge for intercomparisons of river microplastic studies.
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•River microplastic dynamics in relation to land uses were studied in two contrasting basins in Catalonia, Spain.•Urban land use and hydromorphological features explain changes in the microplastic transport and accumulation dynamics.•Differential selection of microplastics in riverbed sediments and in running waters is based on microplastic particle sizes.•Sediment retains small microplastic particles whereas larger fractions are transported in running water.•Land use impinges on microplastic abundance only in running waters, and has a positive relationship with Urban land use.
Land use/cover change (LUCC) in the context of rapid urbanization process has exerted profound influences on carbon storage and ecosystem functions. Exploring the relationships between various ...urbanization patterns and carbon storage is conductive to developing scientific carbon storage polices. This study incorporated climate change and socioeconomic development into the urbanization process, and designed six future urbanization scenarios based on the combination of the Representative Concentration Pathways (RCPs) and the Shared Socio-economic Pathways (SSPs). A hierarchical framework that integrates system dynamic, land-use simulation and carbon storage evaluation models was proposed to predict urban land use change under six concurrent scenarios of climate and socioeconomic conditions, and examine their synergic effects on carbon storage. Hubei Province, a rapidly urbanized area in central China, was selected as a case study. The results show that the decline of carbon storage from 2015 to 2030 ranges from 16.40 Tg to 24.22 Tg under different scenarios, and the scenario featuring steady climate conditions, low population growth, moderate economic growth and high-quality urbanization (e.g., technology innovation) will better maintain carbon storage. Our findings also demonstrate the spatially heterogeneous patterns of carbon storage change at regional scale, and more severe carbon storage loss in the medium-sized cities than the metropolis. This study suggests that targeted ecological conservation strategies should be developed for different cities.
•Carbon storage in Hubei will decline depending on different combination of RCPs and SSPs (−16.4~-24.22 Tg).•The carbon storage change and its three main causes present spatially heterogeneous patterns.•Medium-sized cities deserve more attention to mitigate carbon storage loss than Metropolis.•Technological innovation and moderate socioeconomic growth better maintain carbon storage.
Cellular automaton (CA) is a widely-used tool for modeling land-use changes that can enhance our understanding of past and future urban development. Previous studies have demonstrated that ...patch-based CA models are superior to cell-based CA because the spatial homogeneity of urban growth at local scales can be considered. However, there still exists a major limitation that traditional patch-based CA did not incorporate any information about landscape pattern into land-use change modeling. To alleviate this issue, we present a novel landscape-driven patch-based CA (LP-CA) model that can simultaneously consider landscape similarity and cell-by-cell agreement. We have examined this new model by simulating and predicting the urban expansion in a fast-growing city. Results indicate that our method performs better than stand-alone traditional patch-based CA and landscape-driven cell-based CA in terms of the combined error. The capability to characterize and replicate landscape pattern is greatly important for urban planners to explore the potential influences of urban expansion under different land-use planning scenarios. Therefore, this proposed model has the potential to provide valuable support for urban land-use planning and policy-making processes.
•A landscape-driven patch-based CA (LP-CA) is proposed for urban growth modeling.•Landscape similarity and cell-based agreement are considered during CA calibration.•LP-CA outperforms traditional patch-based CA and landscape-driven cell-based CA.•LP-CA has the capability to characterize and replicate landscape pattern.•This capability is useful for analyzing potential impact of future urban expansion.
Expansion of urban areas accompanied by decreasing population density results in inefficient urban growth from a spatial-ecological perspective. This study examines variations in the urban expansion ...patterns across 466 world cities with million + inhabitants in terms of the contribution of three growth modes (infilling, edge expansion, and outlying) and its relationship with urban land use efficiency, measured in terms of urban density. Focusing on two different time periods (1985–2000 and 2000–2015), it has been found that cities that experience inward expansion are largely located in the Global North, while cities in the Global South experience comparatively more outward than inward expansion. We also find a positive relation between inward expansion and the annual change rate of urban density. However, we hypothesize that this is largely attributed to pronounced variations in the initial per capita land consumption, particularly between cities located in the Global North and Global South. Indeed, when we examine the effect of NDEI on the end-point urban density, and control for the initial urban density, a different conclusion is achieved. We find that in the Global North, more inward expansion of cities decreases urban density compare to the subgroup of cities located in the Global South in which inward expansion amplifies urban density. Understanding such differential effects of urban expansion patterns on urban density is important for our advancement towards sustainable development goal indicator 11.3.1.
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•World-wide analysis of urban expansion patterns in sample of 466 cities with million + inhabitants.•Global North cities grow more inward compared to Global South cities.•Initial per capita land consumption moderates urban land use efficiency.•More inward growth doesn't mean low per capita land consumption in the Global North.•Contextualization of infill oriented development is recommended for global urban sustainability.
In contemporary cities, justice stands as a paramount concern, integral to their fabric and functionality. Just urban land use planning (JULUP) is one of the main topics in urban land use planning ...and tries to promote justice in cities through land use planning principles. Despite the abundance of JULUP studies, there is still a lack of comprehensive research that can review JULUP principles in an integrated manner. This article aims to explore and describe the principles of JULUP and seeks to answer the question of what principles JULUP is defined by using a systematic review and qualitative content analysis method. Based on the review of 191 sources, the results show that principles of JULUP can be categorized into four major principles: Land rights management, social cohesion, accessibility and spatial health. This array of principles underscores that attaining justice in urban land use planning necessitates a comprehensive and integrated perspective.
•Just urban land use planning (JULUP) tries to promote justice in cities through land use planning principles.•It seeks to answer the question of what principles JULUP is.•Principles of JULUP can be categorized into land rights management, social cohesion, accessibility and spatial health.•Attaining justice in urban land use planning necessitates a comprehensive and integrated perspective.
Urban land use information is essential for a variety of urban-related applications such as urban planning and regional administration. The extraction of urban land use from very fine spatial ...resolution (VFSR) remotely sensed imagery has, therefore, drawn much attention in the remote sensing community. Nevertheless, classifying urban land use from VFSR images remains a challenging task, due to the extreme difficulties in differentiating complex spatial patterns to derive high-level semantic labels. Deep convolutional neural networks (CNNs) offer great potential to extract high-level spatial features, thanks to its hierarchical nature with multiple levels of abstraction. However, blurred object boundaries and geometric distortion, as well as huge computational redundancy, severely restrict the potential application of CNN for the classification of urban land use. In this paper, a novel object-based convolutional neural network (OCNN) is proposed for urban land use classification using VFSR images. Rather than Pixel-wise convolutional processes, the OCNN relies on segmented objects as its functional units, and CNN networks are used to analyse and label objects such as to partition within-object and between-object variation. Two CNN networks with different model structures and window sizes are developed to predict linearly shaped objects (e.g. Highway, Canal) and general (other non-linearly shaped) objects. Then a rule-based decision fusion is performed to integrate the class-specific classification results. The effectiveness of the proposed OCNN method was tested on aerial photography of two large urban scenes in Southampton and Manchester in Great Britain. The OCNN combined with large and small window sizes achieved excellent classification accuracy and computational efficiency, consistently outperforming its sub-modules, as well as other benchmark comparators, including the Pixel-wise CNN, contextual-based MRF and object-based OBIA-SVM methods. The proposed method provides the first object-based CNN framework to effectively and efficiently address the complicated problem of urban land use classification from VFSR images.
•Object-based CNN (OCNN) were proposed for complex urban land use classification.•The within-object and between-object information were used jointly.•The convolutional position of OCNN were derived by geometry and spatial anisotropy.•High classification accuracy and computational efficiency were achieved.•The OCNN demonstrates great generalisation capability for different applications.
Stormwater runoff is considered a major pathway for land-based microplastic transportation to aquatic environments. By applying time-weighted stormwater sampling at stormwater outlets from industrial ...and residential catchments, we investigated the emission characteristics and loads (number- and mass-based) of microplastics to aquatic environments through urban stormwater runoff during rainfall events. Microplastics were detected in stormwater runoff from industrial and residential areas in the concentration range of 68–568 n/L and 54–639 n/L, respectively. Polypropylene and polyethylene were found as major polymers accounting for around 60 % of total microplastics. The fragment was the dominant shape of microplastics, and the most common size class was 20–100 μm or 100–200 μm. The microplastic load emitted from industrial and residential areas were estimated to be 1.54–46.1 × 108 and 0.63–28.5 × 108 particles, respectively. The discharge characteristics of microplastics inter– and intra–event were affected by the land-use pattern and rainfall characteristics. The concentration of microplastics did not significantly differ between industrial and residential catchments, but the composition of polymer types reflected the land-use pattern. The microplastics in stormwater were more concentrated when the number of antecedent dry days (ADDs) was higher; the concentration of microplastics was generally peaked in the early stage of runoff and varied according to rainfall intensity during a rainfall event. The contamination level and load of microplastics were heavily affected by the total rainfall depth. Most microplastics were transported in the early stage of runoff (19–37 % of total runoff time), but the proportion of larger and heavier particles increased in the later period of runoff. The microplastic emission via stormwater runoff was significantly higher than that through the discharge of wastewater treatment plant effluent in the same area, implying that stormwater runoff is the dominant pathway for transporting microplastics to aquatic environments.
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•Stormwater runoff is a key transporter of microplastics (MPs) to aquatic systems.•Most MPs were transported in the early stage of runoff (within 40 %).•Total rainfall depth heavily influenced the load of MPs.•The coarser and heavier MPs washed out in the later runoff period.•Polymer compositions of MPs reflect the land-use pattern of the drainage area.
•Eco-efficiency of China’s 12 urban agglomerations are evaluated.•Economic radiation capabilities of the UAs’ core cities are investigated.•Some highly developed UAs in China did not achieved high ...eco-efficiency.•Some suggestions for sustainable development of China’s UAs are proposed
The rapid urbanization in China has a huge impact on land use. The scarcity of land resources has become a constraint for sustainable urban development. Recently, urban agglomeration (UA) has become a new type of complex urban system. The aim of this paper is to investigate the relationship of land use and UAs’ socio-economic development, and figure out effective land strategies. There are 12 evaluated UAs in our paper, which includes 184 cities. We analyze the land use performance of China’s UAs from different perspectives. We first analyze the decoupling relationship between economic growth and urban land use, and then evaluate land use efficiency of China’s 12 typical UAs. The k-means clustering is used to clarify evaluated UAs into different groups according to their characteristics. Furthermore, the efficiency decomposition, changing trend and comparison of core cities are also described. At last, the tobit regression model is built to verify the main driving factors of land use efficiency from three aspects, including economic level, economic structure and government regulation. The results show that most UAs showed weak decoupling relationship. Average urban land use efficiency of UAs in China was not very high. Furthermore, the average efficiency showed an evident fluctuation in 2008 and 2015. Yangtze River Delta and Pearl River Delta have been on the effective frontier. Based on group analysis, the UAs in central China have more room for efficiency improvement. The significant factors influencing UAs’ land use efficiency included per capita GDP, population density and the degree of market openness. Finally, several targeted strategies are proposed to improve urban land use performance of China’s UAs.
Clarifying the interactive relationship between urban land-use efficiency (ULUE), industrial transformation, and carbon emissions is of great realistic significance for promoting the coordination of ...‘resources-economy-environment’ and achieving green development. This study used the stochastic frontier analysis (SFA), index method (IM), and remote sensing inversion to calculate the ULUE, the industrial transformation degree (ITD), and the carbon emission intensity (CEI) for 108 cities in the Yangtze River Economic Belt (YREB) from 2005 to 2017, and analyzed their spatiotemporal evolution characteristics. The generalized method of moments (GMM) and impulse response function (IRF) in the panel vector autoregressive (PVAR) model are used to empirically test the dynamic interactive effects of ULUE, ITD, and CEI. The empirical results show that: (i) During the study period, the ULUE and ITD of the YREB increased year-by-year, showing the pattern characteristics of high in the east and low in the west. The CEI decreased by 50.20% cumulatively, and the low-value areas spread from the center of the urban agglomeration towards the periphery. (ⅱ) The GMM shows that there is a significant dynamic dependence between the ULUE, ITD, and CEI. The ULUE has a positive driving effect on the industrial transformation and a negative effects on the CEI in the short term. (ⅲ) The IRF shows that the ULUE and industrial transformation show a synergistic effect of interactive growth. The improvement of the ULUE and industrial restructuring will force the reduction of CEI. The article proposes that the city should take the new urbanization path of resource-conserving, cost-effective, and environment-friendly.
•The paper depicted the spatiotemporal patterns for ULUE, ITD, and CEI in the YREB.•The dynamic interactive effects of the ULUE, ITD, and CEI are revealed.•The ULUE has negative influence on CEI.•The ULUE and ITD show a synergistic effect of interactive growth.•The improvement of the ULUE and ITD jointly form a carbon reduction mechanism.