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Pseudotsuga sinensis, a vulnerable relict coniferous tree species, faces threats from overexploitation and habitat loss. Despite its status, the forest types, community structure, and population characteristics of this species in China have remained largely unknown. In our study, we conducted analyses of 69 vegetation plots where P. sinensis was the dominant species in southwestern China. We identified five forest types, i.e., Type 1: Pseudotsuga sinensis evergreen coniferous forest; Type 2: Pseudotsuga sinensis - Pinus yunnanensis evergreen coniferous forest; Type 3: Pseudotsuga sinensis - Cyclobalanopsis glaucoides evergreen coniferous and broad-leaved mixed forest; Type 4: Pseudotsuga sinensis - Platycarya strobilacea evergreen coniferous and deciduous broad-leaved mixed forest; Type 5: Pseudotsuga sinensis - Calocedrus macrolepis evergreen coniferous forest. These forests exhibited a multilayered vertical structure. The Simpson diversity index ranged between 0.58-0.86, while the Shannon-Wiener diversity index ranged from 1.24 to 2.3. P. sinensis trees' average growth rate of ring width decreased from 5.86 to 0.33 mm/year as increasing ages. Observed maximum age of P. sinensis was 115 years with 78 cm diameter at the breast height. Age frequency distribution of P. sinensis was multimodal. There was a great lack of individuals at 0-20 years old. Forests with moderate disturbance showed a significantly higher number of P. sinensis individuals younger than 30 years compared to areas with no, slight, or severe disturbance. P. sinensis' regeneration depends on moderate disturbance. We recommended delineating buffer zones in the protected areas at certain sites and in such zones can be allowed to sustainable firewood cutting by selectively marked species other than P. sinensis. [ABSTRACT FROM AUTHOR]

Vegetation and fire archives of the late Holocene are essential for understanding the importance of natural and anthropogenic forcings on past and future vegetation successions as well as climate changes. Here we present a 1640-year record of vegetation and fire history of the Lake Haixihai catchment in northwestern Yunnan, southwest China. Pollen and charcoal analyses as well as XRF (X-ray fluorescence) analysis of lacustrine sediments from Lake Haixihai were employed to reveal its regional vegetation, forest fire, and soil erosion intensity changes over the last 1640 years. The results show their significant changes attributed to both climatic conditions and human activities: The lake catchment witnessed the densest forests (including pine and hemlock forests, and evergreen broadleaved forests) and the weakest soil erosion of the last 1640 years as well as relatively frequent forest fires at 380–880 AD, when vegetation succession, forest fire, and soil erosion were mainly driven by natural forcings, i.e., climatic conditions. A significant and abrupt drop in forest density, minor changes in abundance of forest components, and gradually strengthening soil erosion occurred at the transition from 880 to 1040 AD, when anthropogenic forcings such as the development of agriculture and systematic deforestation gradually became dominant ones driving vegetation succession and soil erosion. After this transition, forest density and soil erosion intensity never returned to the level before 880 AD, implying that the modern landscape in the lake catchment was already established approximately at as early as ca. 1040 AD. No significant changes in forest component and density as well as forest fire and soil erosion occurred until 1940 AD. The most frequent forest fires, the strongest soil erosion, and low forest density after 1940 AD might be attributed partially to climatic conditions and partially to extensive deforestation around 1960 AD. [ABSTRACT FROM AUTHOR]

Sugarcane leaf blight (SLB), a major fungal leaf disease of sugarcane (Saccharum spp.), has been attributed to Stagonospora tainanensis. In December 2020 and May 2021, signs of leaf blight were observed on sugarcane in the fields of Chongzuo City, in the Guangxi Province of China. Lesions on the leaves were characterized by yellow or dark red spots in the center. Fungal species were isolated, purified and subjected to pathogenicity evaluation on the sugarcane plants. An isolate that caused symptoms the same as those observed in the field was initially identified as S. tainanensis (Leptosphaeria taiwanensis, perfect state) based on its morphological characteristics both of asexual and sexual stages. Dark brown and nearly spherical pycnidia with conidia of long ellipsoidal, hyaline, one to four cells and 29.27 to 54.39 μm long and 9.03 to 16.12 μm wide were found on corn meal agar medium. Ascomata with asci of cylindrical to clavate, a short stipe and eight spores slightly constricted at the septum, with the size of the spore ranging from 36 to 44 μm long and 8.5 to 12 μm wide, were formed on the sugarcane-leaf-decoction saccharose agar medium. The identity of the species was further confirmed by rDNA ITS and TEF-1α sequencing. The optimal temperature for mycelial growth was 25 °C and the optimal pH was 6.0. The pathogen grew well in a medium with oats as the carbon source and yeast extract as the nitrogen source, but poorly in a medium with urea as the nitrogen source. This study is the first to identify the sugarcane leaf blight pathogen in Guangxi, and the first publication describing the biological characterization of S. tainanensis. The occurrence of sugarcane leaf blight should alert sugarcane breeders and plant pathologists to consider integrating control of this potentially important disease into the agenda of their breeding and disease control programs. [ABSTRACT FROM AUTHOR]

Urban green space (UGS) is an important component in the urban ecosystem and has great significance to the urban ecological environment. Although the development of remote sensing platforms and deep learning technologies have provided opportunities for UGS mapping from high-resolution images (HRIs), challenges still exist in its large-scale and fine-grained application due to insufficient annotated datasets and specially designed methods for UGS. Moreover, the domain shift between images from different regions is also a problem that must be solved. To address these issues, a general deep learning (DL) framework is proposed for UGS mapping in the large scale, and fine-grained UGS maps of 31 major cities in mainland China are generated (UGS-1m). The DL framework consists of a generator and a discriminator. The generator is a fully convolutional network designed for UGS extraction (UGSNet), which integrates attention mechanisms to improve the discrimination to UGS, and employs a point-rending strategy for edge recovery. The discriminator is a fully connected network aiming to deal with the domain shift between images. To support the model training, an urban green space dataset (UGSet) with a total number of 4544 samples of 512×512 in size is provided. The main steps to obtain UGS-1m can be summarized as follows: (a) first, the UGSNet will be pre-trained on the UGSet in order to obtain a good starting training point for the generator. (b) After pre-training on the UGSet, the discriminator is responsible for adapting the pre-trained UGSNet to different cities through adversarial training. (c) Finally, the UGS results of 31 major cities in China (UGS-1m) are obtained using 2179 Google Earth images with a data frame of 7 ′ 30 ′′ in longitude and 5 ′ 00 ′′ in latitude and a spatial resolution of nearly 1.1 m. An evaluation of the performance of the proposed framework by samples from five different cities shows the validity of the UGS-1m products, with an average overall accuracy (OA) of 87.56 % and an F1 score of 74.86 %. Comparative experiments on UGSet with the existing state-of-the-art (SOTA) DL models proves the effectiveness of UGSNet as the generator, with the highest F1 score of 77.30 %. Furthermore, an ablation study on the discriminator fully reveals the necessity and effectiveness of introducing the discriminator into adversarial learning for domain adaptation. Finally, a comparison with existing products further shows the feasibility of the UGS-1m and the great potential of the proposed DL framework. The UGS-1m can be downloaded from 10.57760/sciencedb.07049. [ABSTRACT FROM AUTHOR]

Ecosystem services can be enhanced through ecological restoration, industrial structure adjustment, land-use optimization, and agricultural and forestry ecosystem transformation. The ecosystem services in hilly and mountainous areas of southern China are crucially needed to be enhanced since these regions are important ecological functional zones in China. However, due to its large area, it is not possible to simultaneously upgrade the ecosystem services for all areas, and therefore, priority areas need to be selected to individually upgrade the ecosystem service function. In this study, via an approach of combining remote sensing, geographic information system, and spatial statistics, we identify the priority areas that need to be upgraded based on the analysis of ecological sensitivity, importance of ecosystem service function, and decreased degree in ecosystem services. For five counties in hilly and mountainous areas of southern China, only less than 2% of the total area was identified as the first priority area; its land-use compositions were analyzed and recommendations on how to enhance ecosystem service were suggested. This approach overcomes the conflict and contradiction issues associated with identifying priority areas in previous studies and solves the problems of high cost or difficult implementation of priority areas. [ABSTRACT FROM AUTHOR]

High spatial resolution precipitation data are important for hydrological modeling and meteorological applications, especially at regional scales. Statistical downscaling methods for satellite precipitation products using the normalized difference vegetation index (NDVI) have been carried out in many regions to provide high spatial resolution precipitation. These methods generally use NDVI and precipitation at the same time, assuming that there is a real-time response of vegetation to precipitation. However, this assumption does not hold in many scenarios. It is known that different vegetation types exhibit different response times to precipitation, i.e., there is a possible lag in the response of vegetation to precipitation depending on the vegetation/landcover type. Therefore, it is not appropriate to estimate precipitation using NDVI collected at the same time. To better represent the relationship between precipitation and vegetation, this article develops a new vegetation index based on adaptive lag phase (VIAL) estimated from a new growth rate that is adaptive to landcover type. Based on VIAL, a new local precipitation downscaling method called LPVIAL is proposed, which essentially considers the nonstationary relationship between precipitation and VIAL. The performance of LPVIAL is assessed by downscaling Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) from 0.1° to 1-km spatial resolution over the Pearl River Basin in Southern China from 2010 to 2017 at 16-day temporal resolution, and the downscaled products are validated against ground observations. Results indicate that the high-resolution precipitation data obtained from the new downscaling approach perform well, and the accuracy is higher than traditional approaches. With the enhancement of spatial resolution, LPVIAL downscaled products show more detailed spatial information of precipitation with smooth distribution, and the downscaled products have slightly higher accuracy compared with IMERG. It is, therefore, suggested that the adaptive lag phase should be considered in the satellite precipitation product downscaling process. [ABSTRACT FROM AUTHOR]

The lack of in situ data has always posed challenges to remote-sensing-data product validation. Herein, the products of sea-ice concentration (SIC) data derived using the arctic radiation and turbulence interaction study (ARTIST) sea ice (ASI) algorithm were evaluated by comparing them with SICs from a high-resolution sea-ice aerial image obtained during the 27th China Antarctic expedition in January 2011. Results suggest that data obtained from the advanced microwave scanning radiometer for the earth-observing system (AMSR-E) underestimate SICs by 19%. We performed step-by-step comparisons among the aerial image, moderate-resolution-imaging spectroradiometer (MODIS), and AMSR-E SIC. These types of comparisons have not been made in previous validation studies. First, SICs acquired from MODIS-Terra imagery were acquired using a tie-point method and corrected by SICs derived from the aerial photography. Second, SICs of MODIS-Aqua images were trained based on the consistency of SIC results between MODIS-Terra and MODIS-Aqua over the selected region on the same day. Finally, the MODIS-Aqua SICs were employed to validate synchronous AMSR-E swath SIC products. The results show that the AMSR-E products underestimate SICs by 8.5% in the marginal ice zone in comparison with MODIS SICs. According to our further analysis between sea-ice types and AMSR-E biases, the higher the proportion of first-year ice, the smaller the AMSR-E SIC bias. In other words, results suggest that the higher the thin ice proportion, the more the AMSR-E underestimates the SIC. [ABSTRACT FROM AUTHOR]

• LCZ mapping is considered as remote sensing scene classification instead of pixel-based classification to fully exploit the urban environment context. • A convolutional neural network integrating residual learning and the Squeeze-and-Excitation block is proposed for LCZ mapping. • Image sizes of 32 × 32 to 64 × 64 corresponding to 320 × 320 to 640 × 640 m 2 areas are found suitable for LCZ mapping depending on the region. • LCZ maps are generated for fifteen cities in China. China, with the world's largest population, has gone through rapid development in the last forty years and now has over 800 million urban citizens. Although urbanization leads to great social and economic progress, they may be confronted with other issues, including extra heat and air pollution. Local climate zone (LCZ), a new concept developed for urban heat island research, provides a standard classification system for the urban environment. LCZs are defined by the context of the urban environment; the minimum diameter of an LCZ is expected to be 400–1,000 m so that it can have a valid effect on the urban climate. However, most existing methods (e.g., the WUDAPT method) regard this task as pixel-based classification, neglecting the spatial information. In this study, we argue that LCZ mapping should be considered as a scene classification task to fully exploit the environmental context. Fifteen cities covering 138 million population in three economic regions of China are selected as the study area. Sentinel-2 multispectral data with a 10 m spatial resolution are used to classify LCZs. A deep convolutional neural network composed of residual learning and the Squeeze-and-Excitation block, namely the LCZNet, is proposed. We obtained an overall accuracy of 88.61% by using a large image (48 × 48 corresponding to 480 × 480 m 2 ) as the representation of an LCZ, 7.5% higher than that using a small image representation (10 × 10) and nearly 20% higher than that obtained by the standard WUDAPT method. Image sizes from 32 × 32 to 64 × 64 were found suitable for LCZ mapping, while a deeper network achieved better classification with larger inputs. Compared with natural classes, urban classes benefited more from a large input size, as it can exploit the environment context of urban areas. The combined use of the training data from all three regions led to the best classification, but the transfer of LCZ models cannot achieve satisfactory results due to the domain shift. More advanced domain adaptation methods should be applied in this application. [ABSTRACT FROM AUTHOR]

Sub-pixel mapping is the prevailing approach for dealing with the mixed pixel effect in urban land use/land cover classification, by reconstructing the sub-pixel-scale distribution inside each mixed-pixel based on spatial autocorrelation. However, 1) traditional spatial autocorrelation is limited to a local window, which cannot model the teleconnection between two locations or objects that are far apart and 2) autocorrelation is based on the idea of "the more proximate, the more similar", which relies on a distance-weight decay parameter and cannot characterize the rich variety of mutual information in spatially heterogenous areas in urban. In this research, we develop and demonstrate a learnable correlation-based sub-pixel mapping (LECOS) method. 1) We use the "mutual retrieval" mechanism of the self-attention operation to model teleconnections that enable more distant locations or objects to be mutually correlated and 2) we design a parameter-free "self-attention in self-attention" operation to learn adaptively the diverse global correlation patterns between pixel and sub-pixel. The learned spatial correlations are then used for reasoning the sub-pixel-scale distribution of each class. We validated our method on the most challenging public datasets of urban scenes, which exhibit considerable spatial heterogeneity with complex structures and broken objects. The learned building-tree, building-road and road-tree correlation patterns contributed most to the sub-pixel reconstruction result of the urban scenes, consistent with in-situ reference data. We further explored the model's explicability in a large-area of several metropolises in China, by mapping land cover in these cities at a 2 m very fine spatial resolution using 10 m Sentinel-2 input images, and found that the derived result not only revealed rich urban spatial heterogeneity, but also that the learned correlation was indicative of urban pattern dynamics, suggesting the potential for greater understanding of issues such as urban fairness, accessibility, human exposure and sustainability. • An explicable deep learning is developed for urban land use/land cover mapping. • The spatial teleconnection of urban components is embedded into neural network. • Sub-pixel mapping network is used to restore 10 m Sentinel image to 2 m urban map. • Our results reveal unprecedented urban patterns with rich spatial heterogeneity. • The learned correlation is explainable for urban fairness and human exposure. [ABSTRACT FROM AUTHOR]

The United Nations' Sustainable Development Goals (SDGs) for 2030 underscore the urgency of "eradicating hunger and ensuring food security" (SDG 2: Zero Hunger) and the critical need to "cease and reverse land degradation and biodiversity decline" (SDG 15: Life on Land). The Dongting Lake area in China, serving as a significant wetland nature reserve and grain production zone, is increasingly confronted with complex, interdependent trade-offs between agricultural cultivation and the ecological and environmental preservation of wetlands (SDG 2 and 15). To analyze the trade-off between conservation and food security, it is crucial to rely on long-term, continuous monitoring of land cover changes in the lake area. However, the absence of reliable optical remote sensing has posed a significant challenge due to the prevalence of cloudy and rainy conditions. Our study begins by integrating long-term Landsat and MODIS data using the GF-SG fusion algorithm to generate 8-day NDVI data with a spatial resolution of 30 m. This analysis focuses on the areas outside the embankment of Dongting Lake (referred to as O-DTL) from 2003 to 2020. We then employ a pixel-connected sample migration method to facilitate automated sampling of land cover types and a random forest classification algorithm to analyze long-term dynamic changes. Finally, by combining meteorological and social data, we examine the temporal patterns of land cover changes in the study area and identify the underlying factors influencing them. The results indicate a trade-off between the fluctuation of cropland and forest area from 2003 to 2020. Water body areas have exhibited a significant decrease, while impervious surface areas have consistently increased annually. Impervious surface areas have experienced a substantial increase of approximately 70%, with almost 90% of this expansion resulting from the conversion of cropland. Under the premise of maintaining a stable area for food cultivation, the land consumed by urban expansion eventually encroached on the wetland water bodies of the reserve. The reduction in wetland water area in the O-DTL can be primarily attributed to agricultural cultivation, while urban expansion and urbanization have indirectly contributed to the decrease. This study provides a case in which prioritizing food security (SDG 2) takes precedence over ecological conservation (SDG 15), highlighting its significant implications for guiding subsequent development in the Dongting Lake area. This finding is crucial for minimizing unintended consequences and maximizing co-benefits between sustainable development goals. • Wetland cover changes in Dongting Lake were monitored from 2003 to 2020. • Integration of Landsat and MODIS data improved data availability in cloudy and rainy areas. • Food security (SDG 2) was prioritized over ecological conservation (SDG 15) in the Dongting Lake area. [ABSTRACT FROM AUTHOR]

Porcine bocavirus (PBoV), which belongs the genus Bocaparvovirus, has been identified throughout the world. However, serological methods for detecting anti-PBoV antibodies are presently limited. In the present study, an indirect enzyme-linked immunosorbent assay (PBoV-rNP1 ELISA) based on a recombinant form of nucleoprotein 1 (NP1) of PBoV was established for investigating the seroprevalence of PBoV in 2025 serum specimens collected in north-central China from 2016 to 2018, and 42.3% of the samples tested positive for anti-PBoV IgG antibodies, indicating that the seroprevalence of PBoV is high in pig populations in China. [ABSTRACT FROM AUTHOR]

As the world's largest carbon emitter, China is confronting a great challenge to mitigate its carbon emissions. The construction industry is one of the major contributors to the carbon emissions in China. This study investigated the driving factors of the changes in the carbon emissions in the Chinese construction industry by using the structural decomposition analysis method and the data from the World Input-Output Database. The results show that the total final demand effect contributed most (131%) to the increase in the construction carbon emissions, while the energy intensity effect offset the largest part (108%) of the increase during the whole period. The production structure effect and final demand ratio effect contributed 49% and 35% to the total increase in the carbon emissions between 1995 and 2009, respectively. The carbonization factor effect had a very small decrease impact (7%) on the carbon emissions between 1995 and 2009. The trends of the effects of driving factors during 1995–2009 and the contributions by industries to the effects of driving factors between 1999 and 2009 have been further explored. This study can help the Chinese policymakers formulate more effective policies for mitigating the construction carbon emissions. [ABSTRACT FROM AUTHOR]

As an important resource of functional food, the seeds of tree peony are rich in phenolic compounds, which are associated with antioxidant activity. However, so far there has not been systematic study on phenolic compositions and antioxidant activity of the seeds from wild tree peony species. The aim of this study was to determine the phenolic content, antioxidant compounds and antioxidant activity of seeds from nine tree peony species native to China. Among the seed samples, Paeonia rockii had the highest total flavonoid content, strongest DPPH and ABTS radical scavenging activities, and strongest cupric reducing capacity; P . decomposita subsp. rotundiloba had the highest total phenolic and flavanol contents, as well as the strongest hydroxyl radical scavenging activity. Sixteen individual phenolic compounds were quantitatively measured, with (+)-catechin being the most abundant component. The content of the phenolic compounds luteolin, paeonol, and the total flavonoid content were significantly correlated with four antioxidant activities. Hierarchical cluster analysis showed that P . rockii and P . decomposita subsp. rotundiloba could be clustered in a group having a high phenolic content and strong antioxidant activity. These results suggest P . rockii and P . decomposita subsp. rotundiloba are the most promising candidates as useful sources of natural antioxidants. [ABSTRACT FROM AUTHOR]

Last decades have witnessed growing public concerns on sustainable development in China arguably due to the social and environmental issues associated with the rapid urbanization. As a result, sustainable neighborhood development has attracted an increasing level of attention from both industry and government. A number of factors exist that may impede the development of sustainable neighborhoods. This study aims to explore the inter-relationship amongst various barriers to sustainable neighborhood development with consideration given to the complex nature of the system. A hierarchical structural model is developed via interpretative structural modeling, which is followed by a classification via Matrice d’Impacts Croisés Multiplication Appliquée á un Classeement (MICMAC) analysis. The complex inter-relationships among various barriers to the sustainable neighborhood developments are examined. The most influential barriers are identified, i.e. unsustainable urbanization mode, lack of supporting policy, lack of national standards and assessment tools, and unsustainable planning. Top priorities can be assigned to deal with these issues properly to facilitate the development of sustainable neighborhoods. This informs the urban policy making process as well as industry practices. [ABSTRACT FROM AUTHOR]

A method based on sample preparation by accelerated solvent extraction and analysis by liquid chromatography–tandem mass spectrometry was validated and used for determination of seven typical lipophilic marine toxins (LMTs) in marine sediment samples collected from three typical coastal bays in China. Satisfactory specificity, reproducibility (RSDs ≤ 14.76%), stability (RSDs ≤ 17.37%), recovery (78.0%–109.0%), and detection limit (3.440 pg/g–61.85 pg/g) of the developed method were achieved. The results obtained from the analysis of samples from Hangzhou Bay revealed okadaic acid as the predominant LMT with concentrations ranging from 186.0 to 280.7 pg/g. Pecenotoxin-2 was quantified in sediment samples from Laizhou Bay at the concentrations from 256.4 to 944.9 pg/g. These results suggested that the proposed method was reliable for determining the typical LMTs in marine sediments and that the sediments obtained from Hangzhou Bay, Laizhou Bay and Jiaozhou Bay were all contaminated by certain amounts of LMTs. [ABSTRACT FROM AUTHOR]

There has been a growing public concern on global warming and associated implications, which is arguably due to greenhouse gas emissions (carbon emission). Building stock is one of biggest emitters. As a result, a number of studies have been undertaken to investigate the effective ways of carbon emission reduction in buildings. However, there is lack of a systematic investigation of the interactive relationship between various factors related to low carbon building. Vast majority of existing studies place focus on one aspect of low carbon building, e.g. policy, technology, awareness, etc. An integrated Interpretative Structural Modeling (ISM) and Matrice d׳Impacts croises-multipication appliqué a classment (MICMAC) approach is adopted in this study to explore the interactions amongst various factors related to low carbon buildings. Outcome of the integrated ISM and MICMAC modeling exercise provides a visualized tool for facilitating the low carbon building developments. This study not only identified the critical success factors for the implementation of low carbon buildings, but also explored how they interacted. Results showed that higher priority should be assigned to international cooperation, macro-level management, the development of low-carbon theories and technologies due to their strong driving power to low carbon buildings. As a result, other factors such as low-carbon facilities, the structure of building energy consumption, and low carbon building project practice will be developed rapidly because of their strong dependent power. This in turn helps to promote the low carbon building developments. Therefore, these factors need to be taken into consideration during policy making process. [ABSTRACT FROM AUTHOR]

Flavonoids are the main active components of natural medicinal plants with many physiological functions. In this study, an HPLC fingerprinting method based on the distribution and relative amount of 11 bioactive flavonoids was established for the quality evaluation of commercially available wild Jujube leaf tea ( JLT) from China. Separation of the crude flavonoid extract was achieved on a column filled with C18 material with a high carbon content. The flavonoids in wild JLT were identified based on UV spectroscopy and accurate mass measurements by TOF- MS. Twenty-one batches of practical samples collected from different habitats were analyzed by using the developed HPLC method to construct the HPLC characteristic fingerprint of wild JLT. Then, combined with clustering and similarity analyses, the HPLC characteristic fingerprint was used for the authentication and quality evaluation of commercial wild JLT. Results indicated that the proposed HPLC characteristic fingerprint reflected the inherent characteristics of wild JLT collected from different regions. Authenticity identification and quality control of commercially available wild Jujube tea were achieved based on the HPLC characteristic fingerprint analysis. This new approach to bioactive component profiling provided a promising reference method for the quality evaluation of commercial wild flower and plant tea. [ABSTRACT FROM AUTHOR]

Abstract: Construction activities have significant impacts on the community and environment. As a result, green construction has been promoted to mitigate these issues. A questionnaire survey was conducted with major stakeholders of the construction industry in Shanghai to investigate issues associated with the adoption of green construction. The results showed that additional cost, incremental time and limited availability of green suppliers and information are critical barriers. Discussions were made to breakdown these barriers to foster green construction practice. This study provides a useful reference to both policy makers and industry practitioners to implement green construction. [Copyright &y& Elsevier]

Sustainable construction is achieved by the implementation of sustainable development principles in the construction industry. The complexity and higher level of inter-project conflicts that occur in large-scale projects mean that the implementation of sustainable construction in those projects is substantially different from that in smaller scale projects. A case study approach has been adopted to analyse the planning and implementation of sustainable construction in the Shanghai World Expo 2010 across the entire programme lifecycle. As one of the largest programmes in China, the Shanghai World Expo 2010 has the potential to serve as a showcase for the application of sustainable development principles in construction. The key factors that need to be considered in order to promote sustainable construction at the programme level are identified. These include the establishment of a dedicated department to coordinate various stakeholders’ efforts and the release of conceptual guidelines and management regulations. In addition, a framework is proposed to implement sustainable construction at the programme management level. [ABSTRACT FROM PUBLISHER]

Last decades have witnessed growing public concerns on sustainable development in China arguably due to the social and environmental issues associated with the rapid urbanization. As a result, sustainable neighborhood development has attracted an increasing level of attention from both industry and government. A number of factors exist that may impede the development of sustainable neighborhoods. This study aims to explore the inter-relationship amongst various barriers to sustainable neighborhood development with consideration given to the complex nature of the system. A hierarchical structural model is developed via interpretative structural modeling, which is followed by a classification via Matrice d’Impacts Croisés Multiplication Appliquée á un Classeement (MICMAC) analysis. The complex inter-relationships among various barriers to the sustainable neighborhood developments are examined. The most influential barriers are identified, i.e. unsustainable urbanization mode, lack of supporting policy, lack of national standards and assessment tools, and unsustainable planning. Top priorities can be assigned to deal with these issues properly to facilitate the development of sustainable neighborhoods. This informs the urban policy making process as well as industry practices. [ABSTRACT FROM AUTHOR]

Abstract: The higher education is experiencing a rapid development in China, with the sharp increase of energy use and the low level of campus facility operation. Meanwhile, with the responsibility for knowledge transformation, sci-tech talents cultivation and technical innovation, universities are of great importance in the development of the sustainable society. The initiative of green campus has attracted great attention from both the society and the universities themselves. Therefore, it is very meaningful to get a full understanding of the current status of green campus development in China, and make the feasibility planning for the next step on this base. In this paper, the progress of green campus development in China is summarized, including all the initiatives to conduct the energy and resource efficient campus, and the current status of upgrading the energy and resource efficient campus to the green campus; the problems occurred during the development are analyzed, and the possible approaches and the action plan are explored accordingly, to promote the green campus development. It is found from the analysis that the development of energy and resource efficient campus has been expanded in a large scale in China, mainly aiming at the energy efficient technology application and campus energy management, and all these initiatives are strongly promoted by the national government with policy support and financial funding. With these great endeavors, an upgrade from the energy and resource efficient campus to the green campus is on progress, which expands its scope to sustainable education and the initiative of low-carbon life on campus. However, many problems also occurred during the progress, such as the lack of a good top-level design among different national ministries and the collaborative innovation among different departments in the university, and the need of a practical propulsion mode and a long-term mechanism to guarantee green campus development. Hence, some suggestions are made in terms of the administrative management, propulsion approach, evaluation standard, and action plan. [Copyright &y& Elsevier]

Background: Adolescent suicide ideation (SI) has received increased attention in recent years, and emotion reactivity (ER) has been found to be a risk factor for SI. However, little is known about the mediating and moderating mechanisms underlying this relationship. The aim of this study is to test a moderated mediation model of SI.Method: A total of 2,716 Chinese adolescents (53.2% males, mean age = 13.19 years, SD = 0.52) completed self-report questionnaires regarding SI, ER, nonsuicidal self-injury (NSSI), and regulatory emotional self-efficacy (RESE).Results: After controlling for gender, ER was significantly associated with SI, and this association was mediated by NSSI. RESE buffered the relation between ER and SI, as well as the relation between ER and NSSI.Limitation: This study was cross-sectional in design and relied upon self-report measures only. Almost all participants were recruited from a single city of China.Conclusion: Findings of this study demonstrate a relationship among ER, NSSI, and SI, and expand our understanding of the development of SI. Further, RESE may be a protective factor against SI and NSSI in adolescence, which suggests a potential role of promoting RESE in the prevention and intervention of SI and NSSI. [ABSTRACT FROM AUTHOR]

Abstract The rapid urbanization process in China has given rise to a number of sustainability issues, including land shortages, concentrated areas of poverty, inefficient land use, and environmental pollution. Urban redevelopment has been identified as an effective method for addressing these issues and establishing new modes of sustainable urban development. In practice, urban redevelopment projects typically involve a range of stakeholders with competing claims. Managing the conflicting interests of these stakeholders presents a significant challenge to the success of urban redevelopment. In this study, we proposed a model for analyzing stakeholder conflicts in urban redevelopment projects based on the stakeholder salience theory and Pawlak's conflict theory. In this model, the attributes, key concerns, and attitudes of different stakeholders are captured by empirical investigation and salience analysis. Stakeholder conflicts are then quantified using Pawlak's conflict theory with consideration of stakeholder specifics. Finally, an action scheme is generated that mitigates stakeholder conflicts and maximizes project benefits. To evaluate its effectiveness, we applied this model to a real redevelopment project in the Wenzhou Ecological Park. The results indicate that this model can be used to balance the interests of stakeholders and reduce stakeholder conflicts in urban redevelopment projects in China. Graphical abstract Image 1 Highlights • A model was established to generate action schemes for mitigating stakeholder conflicts in urban redevelopment projects. • Stakeholder attributes can be captured via stakeholder salience analysis. • This model can be used to quantify stakeholder conflicts with consideration given to stakeholder specifics. • The practical effectiveness of this model was tested in a real urban redevelopment project. [ABSTRACT FROM AUTHOR]

This study reveals that a distinct damming incident occurred during a prehistory period (approximately 30 ka BP) in the upper Minjiang River, at the southeastern margin of the Tibetan Plateau, which formed a giant dammed lake. It can be inferred that paleoseismic induced major landslides were the direct cause of the river damming. The dammed lake breached and caused a large outburst flood at about 27 ka BP. Between the section of the prehistoric ancient dam-body and its downstream areas (5 km), an abundance of diamicts consisting of a poor-sorted wide range of particle sizes, including gravel, sand, and minor silt and clay, have been observed. The outburst deposits in the Diexi area maybe divided into two periods: the thick outburst deposits represented the earlier and largest dammed-break event, and the deposit terrace was due to the subsequent and smaller dammed-break event. The sedimentary structures of the outburst deposits included imbrication, cavitation, matrix, and massive structures, as well as gravel support-stacked structures. Furthermore, a special sedimentary structure became evident, consisting of a rhythmite interbedded structure composed of a coarser gravel layer, and a finer sand and gravel layer, with no sand lens formed within the layers. This special structure can potentially provide an important original criterion for the outburst deposits in this area. The two types of facies associations have been recorded which indicate contrasting sediment transport regimes. The characteristics of boulder facies were most likely associated with hyperconcentrated flood flows. However, the finer-grained Gm/Gfm/GRm facies, which overlaid the Bcm facies, were determined to represent the waning stage of the flooding events. The delicate structures, as well as the absence of coarse components in the Sh facies, indicated an episode of accumulations, which was subsequent to the deposition of the underlying Bcm facies. The results of this study potentially provide important implications for the interpretation of the diamicts in the Diexi area. The grain-size frequency curves of the outburst deposits in the Diexi area were found to all be bimodal (a main peak and an inconspicuous sub-peak). These findings indicated a poorly sorted sedimentary structure. It was found that, from the upstream segment to the downstream segment, the gravel sediment became gradually lessened, while the fine-grained sediment increased. Additionally, the outburst flood hydrodynamic intensity was found to have gradually become weakened. [ABSTRACT FROM AUTHOR]

In assuming its commitments to the reduction of CO 2 emissions, China is contributing great efforts to mitigate CO 2 emissions across its all economic sectors including construction industry. The Chinese construction industry is one of the main contributors to CO 2 emissions in China. This paper presents an empirical study on the CO 2 emissions in the Chinese construction industry across the period of 1995–2011. The input-output analysis method is employed for conducting the study. The data used for analysis are mainly collected from the world input-output database. The analysis results demonstrate that the CO 2 emissions in the Chinese construction industry increased by 388.7% from 1995 to 2011, reached to 3035.9 Mt in 2011. However, the carbon intensity in the construction industry decreased by 46.9% from 1995 to 2011, recorded as 0.00198 Mt/million dollars in 2011. The indirect CO 2 emissions were the majority of the construction CO 2 emissions, accounting for over 95% during 1995–2011. The process-based CO 2 emissions contributed 8.7%–12.6% of the total construction CO 2 emissions during 1995–2011. The electricity, gas and water supply industry, the other non-metallic mineral industry, and the basic metals and fabricated metal industry were the main contributors to the construction CO 2 emissions during 1995–2009. This study presents a comprehensive picture on the CO 2 emissions in the Chinese construction industry, which provides valuable references both to further study and to formulate more effective policies. [ABSTRACT FROM AUTHOR]

Brightness temperature (BT), which is remotely sensed by the space-borne microwave radiometer, is widely used in snow cover monitoring for its long time series imaging capabilities in all-weather conditions. Traditional linear fitting and stand-alone methods are usually uncertain with respect to the spatial distribution and temporal variation of derived snow cover, as they rarely consider local conditions and scene characteristics but fit the model with static empirical coefficients. In this paper, a novel method utilizing daily ground in situ observations is proposed and evaluated, with the purpose for accurate estimation of long-term daily snow cover. To solve the challenge that ground snow-free records are insufficient, a one-class classifier, namely the Presence and Background Learning (PBL) algorithm, is employed to identify daily global snow cover. Benefiting from daily ground in situ observations on a global scale, the proposed method is temporally and spatially dynamic such that estimation errors are globally independent during the entire study period. The proposed method is applied to the estimation of global daily snow cover from 1987 to 2010; the results are validated by ground in situ observations and compared with available optical-based and microwave-based snow cover products. Promising accuracy and model stability are achieved in daily, monthly and yearly validations as compared against ground observations (global omission error < 0.13, overall accuracy > 0.82 in China region, and keep stable in monthly and yearly averages). The comparison against the MODIS daily snow cover product (MOD10C1) shows good agreement under cloud-free conditions (Cohen's kappa = 0.715). The comparison against the NOAA daily Interactive Multisensor Snow and Ice Mapping System (IMS) dataset suggests promising agreement in the Northern Hemisphere. Another comparison against the AMSR-E daily SWE dataset (AE_DySno) demonstrates the efficiency of the proposed method regarding to the overestimation problem in thin snow cover region. [ABSTRACT FROM AUTHOR]