bluuebunny/crossref_metadata_2025 huggingface dataset:
Adaptive Blending Method of Radar-Based and Numerical Weather Prediction QPFs for Urban Flood Forecasting
Authors: Yoon Seong-Sim
Published: March 2019

Preparing proper disaster prevention measures is important for decreasing the casualties and property losses resulting from floods. One of the most efficient measures in this regard is real-time flood forecasting using quantitative precipitation forecasts (QPFs) based on either short-term radar-based extrapolation or longer-term numerical weather prediction. As both methods have individual advantages and limitations, in this study we developed a new real-time blending technique to improve the accuracy of rainfall forecasts for hydrological applications. We tested the hydrological applicability of six QPFs used for urban flood forecasting in Seoul, South Korea: the McGill Algorithm for Prediction Nowcasting by Lagrangian Extrapolation (MAPLE), KOrea NOwcasting System (KONOS), Spatial-scale Decomposition method (SCDM), Unified Model Local Data Assimilation and Prediction System (UM LDAPS), and Advanced Storm-scale Analysis and Prediction System (ASAPS), as well as our proposed blended approach based on the assumption that the error of the previously predicted rainfall is similar to that of current predicted rainfall. We used the harmony search algorithm to optimize real-time weights that would minimize the root mean square error between predicted and observed rainfall for a 1 h lead time at 10 min intervals. We tested these models using the Storm Water Management Model (SWMM) and Grid-based Inundation Analysis Model (GIAM) to estimate urban flood discharge and inundation using rainfall from the QPFs as input. Although the blended QPF did not always have the highest correlation coefficient, its accuracy varied less than that of the other QPFs. In addition, its simulated water depth in pipe and spatial extent were most similar to observed inundated areas, demonstrating the value of this new approach for short-term flood forecasting.
Estimation of PMx Concentrations from Landsat 8 OLI Images Based on a Multilayer Perceptron Neural Network
Authors: Zhang Bo , Zhang Meng , Kang Jian , Hong Danfeng , Xu Jian , Zhu Xiaoxiang
Published: March 2019

The estimation of PMx (incl. PM10 and PM2.5) concentrations using satellite observations is of great significance for detecting environmental issues in many urban areas of north China. Recently, aerosol optical depth (AOD) data have been being used to estimate the PMx concentrations by implementing linear and/or nonlinear regression analysis methods. However, a lot of relevant research based on AOD published so far have demonstrated some limitations in estimating the spatial distribution of PMx concentrations with respect to estimation accuracy and spatial resolution. In this research, the Google Earth Engine (GEE) platform is employed to obtain the band reflectance (BR) data of a large number of Landsat 8 Operational Land Imager (OLI) remote sensing images. Combined with the meteorological, time parameter and the latitude and longitude zone (LLZ) method proposed in this article, a new BR (band reflectance)-PMx (incl. PM10 and PM2.5) model based on a multilayer perceptron neural network is constructed for the estimation of PMx concentrations directly from Landsat 8 OLI remote sensing images. This research used Beijing, China as the test area and the conducted experiments demonstrated that the BR-PMx model achieved satisfactory performances for the PMx-concentration estimations. The coefficient of determination (R2) of the BR-PM2.5 and BR-PM10 models reached 0.795 and 0.773, respectively, and the root mean square error (RMSE) reached 20.09 μg/m3 and 31.27 μg/m3. Meanwhile, the estimation results have been compared with the results calculated by Kriging interpolation at the same time point, and the spatial distribution is consistent. Therefore, it can be concluded that the proposed BR-PMx model provides a new promising method for acquiring accurate PMx concentrations for various cities of China.
An Accurate TLS and UAV Image Point Clouds Registration Method for Deformation Detection of Chaotic Hillside Areas
Authors: Zang Yufu , Yang Bisheng , Li Jianping , Guan Haiyan
Published: March 2019

Deformation detection determines the quantified change of a scene’s geometric state, which is of great importance for the mitigation of hazards and property loss from earth observation. Terrestrial laser scanning (TLS) provides an efficient and flexible solution to rapidly capture high precision three-dimensional (3D) point clouds of hillside areas. Most existing methods apply multi-temporal TLS surveys to detect deformations depending on a variety of ground control points (GCPs). However, on the one hand, the deployment of various GCPs is time-consuming and labor-intensive, particularly for difficult terrain areas. On the other hand, in most cases, TLS stations do not form a closed loop, such that cumulative errors cannot be corrected effectively by the existing methods. To overcome these drawbacks, this paper proposes a deformation detection method with limited GCPs based on a novel registration algorithm that accurately registers TLS stations to the UAV (Unmanned Aerial Vehicle) dense image points. First, the proposed method extracts patch primitives from smoothed hillside points, and adjacent TLS scans are pairwise registered by comparing the geometric and topological information of or between patches. Second, a new multi-station adjustment algorithm is proposed, which makes full use of locally closed loops to reach the global optimal registration. Finally, digital elevation models (DEMs, a DEM is a numerical representation of the terrain surface, formed by height points to represent the topography), slope and aspect maps, and vertical sections are generated from multi-temporal TLS surveys to detect and analyze the deformations. Comprehensive experiments demonstrate that the proposed deformation detection method obtains good performance for the hillside areas with limited (few) GCPs.
Estimation of Carbon Fluxes from Eddy Covariance Data and Satellite-Derived Vegetation Indices in a Karst Grassland (Podgorski Kras, Slovenia)
Authors: Noumonvi Koffi Dodji , Ferlan Mitja , Eler Klemen , Alberti Giorgio , Peressotti Alessandro , Cerasoli Sofia
Published: March 2019

The Eddy Covariance method (EC) is widely used for measuring carbon (C) and energy fluxes at high frequency between the atmosphere and the ecosystem, but has some methodological limitations and a spatial restriction to an area, called a footprint. Remotely sensed information is usually used in combination with eddy covariance data in order to estimate C fluxes over larger areas. In fact, spectral vegetation indices derived from available satellite data can be combined with EC measurements to estimate C fluxes outside of the tower footprint. Following this approach, the present study aimed to model C fluxes for a karst grassland in Slovenia. Three types of model were considered: (1) a linear relationship between Net Ecosystem Exchange (NEE) or Gross Primary Production (GPP) and each vegetation index; (2) a linear relationship between GPP and the product of a vegetation index with PAR (Photosynthetically Active Radiation); and (3) a simplified LUE (Light Use-Efficiency) model assuming a constant LUE. We compared the performance of several vegetation indices derived from two remote platforms (Landsat and Proba-V) as predictors of NEE and GPP, based on three accuracy metrics, the coefficient of determination (R2), the Root Mean Square Error (RMSE) and the Akaike Information Criterion (AIC). Two types of aggregation of flux data were explored: midday average and daily average fluxes. The vapor pressure deficit (VPD) was used to separate the growing season into two phases, a wet and a dry phase, which were considered separately in the modelling process, in addition to the growing season as a whole. The results showed that NDVI is the best predictor of GPP and NEE during the wet phase, whereas water-related vegetation indices, namely LSWI and MNDWI, were the best predictors during the dry phase, both for midday and daily aggregates. Model 1 (linear relationship) was found to be the best in many cases. The best regression equations obtained were used to map GPP and NEE for the whole study area. Digital maps obtained can practically contribute, in a cost-effective way to the management of karst grasslands.
Improving Wi-Fi Fingerprint Positioning with a Pose Recognition-Assisted SVM Algorithm
Authors: Zhang Shuai , Guo Jiming , Luo Nianxue , Wang Lei , Wang Wei , Wen Kai
Published: March 2019

The fingerprint method has been widely adopted for Wi-Fi indoor positioning. In the fingerprint matching process, user poses and user body shadowing have serious impact on the received signal strength (RSS) data and degrade matching accuracy; however, this impact has not attracted large attention. In this study, we systematically investigate the impact of user poses and user body shadowing on the collected RSS data and propose a new method called the pose recognition-assisted support vector machine algorithm (PRASVM). It fully exploits the characteristics of different user poses and improves the support vector machine (SVM) positioning performance by introducing a pose recognition procedure. This proposed method firstly establishes a fingerprint database with RSS and sensor data corresponding to different poses in the offline phase, and fingerprints of different poses in the database are extracted to train reference point (RP) classifiers of different poses and a pose classifier using an SVM algorithm. Secondly, in the online phase, the poses of RSS data measured online are recognised by a pose classifier, and RSS data measured online are grouped with different poses. Then online RSS data from each group at an unknown user location are reclassified as corresponding RPs by the RP classifiers of the corresponding poses. Finally, user location is determined by grouped RSS data corresponding to coordinates of the RPs. By considering the user pose and user body shadowing, the observed RSS data matches the fingerprint database better, and the classification accuracy of grouped online RSS data is remarkably improved. To verify performances of the proposed method, experiments are carried out: one in an office setting, and the other in a lecture hall. The experimental results show that the positioning accuracies of the proposed PRASVM algorithm outperform the conventional weighted k-nearest neighbour (WKNN) algorithm by 52.29% and 40.89%, outperform the SVM algorithm by 73.74% and 60.45%, and outperform the pose recognition-assisted WKNN algorithm by 34.76% and 21.86%, respectively. As a result, the PRASVM algorithm noticeably improves positioning accuracy.
A Joint Inversion Estimate of Antarctic Ice Sheet Mass Balance Using Multi-Geodetic Data Sets
Authors: Gao Chunchun , Lu Yang , Zhang Zizhan , Shi Hongling
Published: March 2019

Many recent mass balance estimates using the Gravity Recovery and Climate Experiment (GRACE) and satellite altimetry (including two kinds of sensors of radar and laser) show that the ice mass of the Antarctic ice sheet (AIS) is in overall decline. However, there are still large differences among previously published estimates of the total mass change, even in the same observed periods. The considerable error sources mainly arise from the forward models (e.g., glacial isostatic adjustment [GIA] and firn compaction) that may be uncertain but indispensable to simulate some processes not directly measured or obtained by these observations. To minimize the use of these forward models, we estimate the mass change of ice sheet and present-day GIA using multi-geodetic observations, including GRACE and Ice, Cloud and land Elevation Satellite (ICESat), as well as Global Positioning System (GPS), by an improved method of joint inversion estimate (JIE), which enables us to solve simultaneously for the Antarctic GIA and ice mass trends. The GIA uplift rates generated from our JIE method show a good agreement with the elastic-corrected GPS uplift rates, and the total GIA-induced mass change estimate for the AIS is 54 ± 27 Gt/yr, which is in line with many recent GPS calibrated GIA estimates. Our GIA result displays the presence of significant uplift rates in the Amundsen Sea Embayment of West Antarctica, where strong uplift has been observed by GPS. Over the period February 2003 to October 2009, the entire AIS changed in mass by −84 ± 31 Gt/yr (West Antarctica: −69 ± 24, East Antarctica: 12 ± 16 and the Antarctic Peninsula: −27 ± 8), greater than the GRACE-only estimates obtained from three Mascon solutions (CSR: −50 ± 30, JPL: −71 ± 30, and GSFC: −51 ± 33 Gt/yr) for the same period. This may imply that single GRACE data tend to underestimate ice mass loss due to the signal leakage and attenuation errors of ice discharge are often worse than that of surface mass balance over the AIS.
Mapping Soil Moisture at a High Resolution over Mountainous Regions by Integrating In Situ Measurements, Topography Data, and MODIS Land Surface Temperatures
Authors: Fan Lei , Al-Yaari A. , Frappart Frédéric , Swenson Jennifer J. , Xiao Qing , Wen Jianguang , Jin Rui , Kang Jian , Li Xiaojun , Fernandez-Moran R. , Wigneron J.-P.
Published: March 2019

Hydro-agricultural applications often require surface soil moisture (SM) information at high spatial resolutions. In this study, daily spatial patterns of SM at a spatial resolution of 1 km over the Babao River Basin in northwestern China were mapped using a Bayesian-based upscaling algorithm, which upscaled point-scale measurements to the grid-scale (1 km) by retrieving SM information using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived land surface temperature (LST) and topography data (including aspect and elevation data) and in situ measurements from a wireless sensor network (WSN). First, the time series of pixel-scale (1 km) representative SM information was retrieved from in situ measurements of SM, topography data, and LST. Second, Bayesian linear regression was used to calibrate the relationship between the representative SM and the WSN measurements. Last, the calibrated relationship was used to upscale a network of in situ measured SM to map spatially continuous SM at a high resolution. The upscaled SM data were evaluated against ground-based SM measurements with satisfactory accuracy—the overall correlation coefficient (r), slope, and unbiased root mean square difference (ubRMSD) values were 0.82, 0.61, and 0.025 m3/m3, respectively. Moreover, when accounting for topography, the proposed upscaling algorithm outperformed the algorithm based only on SM derived from LST (r = 0.80, slope = 0.31, and ubRMSD = 0.033 m3/m3). Notably, the proposed upscaling algorithm was able to capture the dynamics of SM under extreme dry and wet conditions. In conclusion, the proposed upscaled method can provide accurate high-resolution SM estimates for hydro-agricultural applications.
Application of Neural Networks for Retrieval of the CO2 Concentration at Aerospace Sensing by IPDA-DIAL lidar
Authors: Matvienko Gennadii G , Sukhanov Alexander Ya
Published: March 2019

Greenhouse gas concentrations are increasing over the past few decades, creating the need to measure their concentration with high accuracy, including for determining their trends, sources, and sinks. In this regard, various methods of regional and global control are being developed. One of the measuring methods is passive satellite method, but they allow for you to get data mainly during the day and outside the poles of the Earth. Another method is active lidar; they require the consideration of various aspects that are related to the technical characteristics of the lidar and methods for solving inverse problems. This article discusses the possibility of using lidars for sensing carbon dioxide from space (orbit 450 km) and from a height of 10 km and 23 km, which presumably corresponds to the aircrafts and balloons. As a method of solving the inverse problem, the method of fully connected neural networks with three layers and pre-training of first layer is considered, allowing for the application of additional data, including the IPDA (Integrated Path Differential Absorption) signal, the scattered DIAL (Differential Absorption Lidar) signal, temperature, and pressure profiles. These estimates show the possibility of measuring the average concentration from an orbit height of 450 km with an error of 0.16%, a resolution of 60 km, with a 50 mJ laser pulse energy, and 1 m diameter telescope. It is also shown that it is possible to obtain the concentration profile, including the near-surface concentration with an error of 2 ppm.
Multi-Objective Particle Swarm Optimization of Sensor Distribution Scheme with Consideration of the Accuracy and the Robustness for Deformation Reconstruction
Authors: Zhao Feifei , Bao Hong , Xue Song , Xu Qian
Published: March 2019

For the inverse finite element method (iFEM), an inappropriate scheme of strain senor distribution would cause severe degradation of the deformation reconstruction accuracy. The robustness of the strain–displacement transfer relationship and the accuracy of reconstruction displacement are the two key factors of reconstruction accuracy. Previous research studies have been focused on single-objective optimization for the robustness of the strain–displacement transfer relationship. However, researchers found that it was difficult to reach a mutual balance between robustness and accuracy using single-objective optimization. In order to solve this problem, a bi-objective optimal model for the scheme of sensor distribution was proposed for this paper, where multi-objective particle swarm optimization (MOPSO) was employed to optimize the robustness and the accuracy. Initially, a hollow circular beam subjected to various loads was used as a case to perform the static analysis. Next, the optimization model was established and two different schemes of strain sensor were obtained correspondingly. Finally, the proposed schemes were successfully implemented in both the simulation calculation and the experiment test. It was found that the results from the proposed optimization model in this paper proved to be a promising tool for the selection of the scheme of strain sensor distribution.
Perspectives on Agricultural Land Use Conversion and Food Security in Rural Ghana
Authors: Appiah Divine Odame , Asante Felix , Nketiah Bernice
Published: March 2019

Rapid peri-urbanization has resulted in increasing demand for and pressure on peri-urban lands at the expense of agricultural lands. Households’ decision to convert from agricultural land uses to residential and commercial land uses is driven by a myriad of factors, ranging from social to economic, in the Asante-Akim South district of the Asante region, Ghana. The paper examined the effects of agricultural land use trade-off on food production in the district. Using a triangulation of qualitative and quantitative methods, 115 household respondents were proportionately sampled from three selected communities in the district, for the collection of data through the administration of questionnaires. The data were subjected to the Pearson’s chi-square, embedded in the SPSS V.16, to test for association among the variables. We report that the increasing rate of agricultural land uses conversions was as a result of increasing demand for residential and commercial land usage at the expense of agricultural land uses. Converting prime agricultural lands into other land uses was seen as profitable to agricultural expansion. A re-examination of the district land use plans by the Ghanaian Physical (Town and Country) Planning Department in tandem with the Lands Commission is therefore recommended.
Influence of Family Variables on Cyberbullying Perpetration and Victimization: A Systematic Literature Review
Authors: López-Castro Leticia , Priegue Diana
Published: March 2019

In recent years, the number of studies conducted on the influence of family variables on cyberbullying perpetration and victimization has increased, especially in terms of relational family processes. The present review investigates the role played by family variables on cyberbullying perpetration and victimization. A systematic literature review was conducted in five databases (ScienceDirect, Scopus, PubMed, ERIC, and Web of Science) from October 2016 to October 2018. During this brief period of time, the number of publications on family variables and cyberbullying, both perpetration and victimization, has significantly increased. We eventually reviewed 34 studies which rigorously met the selection criteria of our research. For the analysis of the results, we distinguish between two types of variables according to the following possibilities of pedagogical intervention: Structural (contextual family variables and individual parental processes), and dynamic (relational family processes). Our review found evidence that there is more controversy around structural variables than around dynamic variables. The most consistent variables are family communication and the quality of the family relationship. However, there is a perceived need for clarifying the influence that different structural variables, parental educational styles, and parental mediation exert on the prevention and consolidation of cyberbullying perpetration and cybervictimization.
Transportation or Narrative Completion? Attentiveness during Binge-Watching Moderates Regret
Authors: Pittman Matthew , Steiner Emil
Published: March 2019

Extant results on the binge-watching outcomes have been mixed. This study sought to examine the crucial factor of attentiveness that might help to enhance viewer experience and mitigate post-binge regret, as well as differentiate the motivation of narrative transportation from narrative completion. While narrative transportation involves a viewer getting unconsciously swept away by the story, the motivation of narrative completion is a more self-aware, cognizant effort to progress through the story. A survey (N = 800) determined that the degree to which an individual pays attention to a show may either increase or decrease subsequent regret, depending on the motivation for binge-watching.
Heart Rate Kinetics Response of Pre-Pubertal Children during the Yo-Yo Intermittent Endurance Test—Level 1
Authors: Brito João , Fernandes Luís , Rebelo António , Krustrup Peter , Silva Gustavo , Oliveira José
Published: March 2019

This study analyzed heart rate (HR) kinetics during the Yo-Yo Intermittent Endurance Test—level 1 (Yo-Yo IE1) in children. At the middle of the school year, 107 boys (7–10 years old) performed the Yo-Yo IE1. Individual HR curves during the Yo-Yo IE1 were analyzed to detect an inflection point between an initial phase of fast rise in HR, and a second phase in which the rise of HR is slower. The 7th shuttle of the test was established as the inflection point. Engagement with extra-school sports practice was identified. Percentile groups (P1, P2 and P3) were created for body weight and physical fitness data composite (PFcomposite). Differences were found between the slopes of P1 and P3 on phase 1 for body weight (12.5 ± 2.7 vs. 13.7 ± 2.0 bpm/shuttle; p = 0.033; d = 0.50) and PFcomposite (14.2 ± 2.5 vs. 12.5 ± 2.0 bpm/shuttle; p = 0.015; d = 0.75). Time spent >95% of peak HR was longer for the children engaged with extra-school sports practice (335 ± 158 vs. 234 ± 124 s; p < 0.001; d = 0.71); differences were also detected for PFcomposite (P1, P2 and P3: 172 ± 92, 270 ± 109, and 360 ± 157 s, respectively; p < 0.05; d = 0.66–1.46). This study indicates that physical fitness and body weight influence HR kinetics during the Yo-Yo IE1 in pre-pubertal boys.
The Effects of Microclimate Parameters on Outdoor Thermal Sensation in Severe Cold Cities
Authors: Lu Ming , Hou Tuoyu , Fu Jingwan , Wei Yuan
Published: March 2019

This study investigated the outdoor thermal sensation characteristics in severe cold cities, and the effects of four microclimate parameters on outdoor thermal sensation. A one-year investigation of public spaces in Harbin, China, as an example of a severe cold city, was carried out. Volunteers were randomly invited to fill out a microclimate perception questionnaire, and the real-time microclimate data were measured and recorded at the same time on site. The relationship between the outdoor actual thermal sensation and the perception of microclimate parameters was analyzed quantitatively. The results showed that the effect of microclimate parameters on the actual thermal sensation was very significant. The actual thermal sensation varies greatly from the seasons. People feel the most comfortable in the transition season. Among the four parameters, temperature has the greatest effect on ATSV in cold season and severe cold season, solar radiation has the greatest effect on ATSV in transition season and hot season. In the severe cold season and hot season, the wind speed also has a significant effect on ATSV.
Drivers and Outcomes of Green IS Adoption in Small and Medium-Sized Enterprises
Authors: Baggia Alenka , Maletič Matjaž , Žnidaršič Anja , Brezavšček Alenka
Published: March 2019

Using the Belief Action Outcome (BAO) framework as a theoretical basis, this study investigates the mechanisms that link organizational beliefs about environmental sustainability with Green information system (IS) actions that are undertaken and, hence, the organizational benefits accruing from these actions. Survey data were collected from 156 small and medium-sized enterprises (SMEs) and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results support the notion that Green IS endeavors lead to increased organizational benefits. External pressures from stakeholders and employees’ attitudes to environmental sustainability affect the organizational attitude to Green IS. The attitude to Green IS is further translated into the organization’s strategy and corresponding Green IS actions, resulting in organizational benefits. This study’s main contribution lies in establishing a link between personal attitudes, institutional mechanisms, internal environmental/sustainability initiatives, and performance implications. Green IS adoption was empirically validated considering the SME context.
The Stakeholders’ Perspective within the B Corp Certification for a Circular Approach
Authors: Poponi Stefano , Colantoni Andrea , Cividino Sirio R.S. , Mosconi Enrico Maria
Published: March 2019

A circular economy has been gaining momentum as the most innovative approach in business. Its proposed model, based on sustainability and new product-driven differentiated strategies of production and organizational exchange, has brought to light the need to better understand the relevance of stakeholders as a critical factor in the creation of new added value in business management. The primary purpose of this paper is to investigate how the B-Corp Certification System could contribute to a process of awareness raising in business organizations. It also focuses on the stakeholders’ commitment, within the framework of circular economy principles, and demonstrates that those companies who are adopting the certification concerning “recycling service and waste management” strongly contribute to the development in the direction of the circular economy. The analysis of the case studies shows two possible scenarios describing the circular approach in business and the different roles of stakeholders in the activation of such a virtuous path. “Social recycling” considers the key role of social participation and contribution in circular-economy related activities of primary and secondary stakeholders, and “highly regenerative recycling” aims to involve qualified stakeholders to start inter-organizational symbioses within the circular process of waste recycling. Key factors, such as industrial symbiosis, tax benefits, financial incentives, legislative harmonization, and the consumers’ behavior, represent the tenets of the circular economy model An awareness-raising perspective and the capacity on the part of companies to understand the relevance of stakeholders and the way to transform their role into the most effective lever to reinforce competitiveness is therefore necessary. Accordingly, the whole system of Benefit Corporation certification could boost business towards new business models involving stakeholders in several directions.
Assessment of Soil Suitability for Improvement of Soil Factors and Agricultural Management
Authors: Abd-Elmabod Sameh , Bakr Noura , Muñoz-Rojas Miriam , Pereira Paulo , Zhang Zhenhua , Cerdà Artemi , Jordán Antonio , Mansour Hani , De la Rosa Diego , Jones Laurence
Published: March 2019

The dramatic growth of the world’s population is increasing the pressure on natural resources, particularly on soil systems. At the same time, inappropriate agricultural practices are causing widespread soil degradation. Improved management of soil resources and identification of the potential agricultural capability of soils is therefore needed to prevent further land degradation, particularly in dryland areas such as Egypt. Here, we present a case study in the El-Fayoum depression (Northern Egypt) to model and map soil suitability for 12 typical Mediterranean crops. Two management scenarios were analyzed: the current situation (CS) and an optimal scenario (OS) of soil variables. The Almagra model was applied to estimate soil suitability under CS and OS. Management options based on the CS assessment were proposed to reduce some limiting factors: a fixed value of 2 dSm−1 for soil salinity and 5% for sodium saturation; these defined the OS. Under optimal management, the OS scenario showed potential, where a notable increase of the area covered by a high suitability class (around 80%) for annual and semi-annual crops was observed. There was also a marked increase (about 70% for CS and 50% for OS) for perennial crops shifting from the marginal to moderate soil suitability class. The results reveal the importance of proper management to massively alter soil suitability into better states in order to achieve sustainable land use in this fertile agro-ecosystem.
A Comprehensive Construction and Demolition Waste Management Model using PESTEL and 3R for Construction Companies Operating in Central Asia
Authors: Turkyilmaz Ali , Guney Mert , Karaca Ferhat , Bagdatkyzy Zhanar , Sandybayeva Aiganym , Sirenova Gulzat
Published: March 2019

The construction industry in Central Asia has shown rapid growth in the last decade due to an economic boom, leading to high construction & demolition waste (C&DW) generation accompanied by waste management operations falling behind worldwide best practices. The present study first employs a comprehensive environmental screening approach, PESTEL analysis, to identify and assess critical external and internal factors that can affect C&DW management in a leading Central Asian construction company (headquarters in Kazakhstan, the country with the largest economy in the region). Then, a case study is performed using 3R (reduce-reuse-recycle) principles and subjecting this company. Current international practices tailored to the given context are provided, existing company practices and applied improvements are discussed and prioritized improvements with implied sustainability benefits are proposed. The findings and recommendations are applicable especially to other construction companies operating in Central Asia that would ensure more sustainable C&DW management operations in the future.
Can Video Surveillance Systems Promote the Perception of Safety? Evidence from Surveys on Residents in Beijing, China
Authors: Zhang Hanqi , Guo Jianfeng , Deng Chao , Fan Ying , Gu Fu
Published: March 2019

Ubiquitous utilization of video surveillance systems is supposed to promote safety, yet whether these systems improve the residents’ perception of safety is unknown. Moreover, the factors that affect the perception of safety are also unclear. We seek to fill these knowledge gaps via a survey-based study, which aims at evaluating the impact of video surveillance systems on perceived safety from crimes and accidents and on behavioral preferences, as well as the attitudes towards such systems. A total of 1080 residents in Beijing, China are validly surveyed, and the surveys returned are exploited for univariate analysis and regression analysis. The analysis results indicate that female respondents are more accustomed to adopt video surveillance systems, as they feel safer and more comfortable with the existence of surveillance systems. Higher levels of education, greater length of residency, and richer knowledge of surveillance systems tend to increase the perception of safety, while age and monthly income act negatively. The effects of these factors should be considered during the implementation of video surveillance systems and recommendations are given to facilitate the adoption of such systems.
A Novel Hyper-Heuristic for the Biobjective Regional Low-Carbon Location-Routing Problem with Multiple Constraints
Authors: Leng Longlong , Zhao Yanwei , Wang Zheng , Zhang Jingling , Wang Wanliang , Zhang Chunmiao
Published: March 2019

With the aim of reducing cost, carbon emissions, and service periods and improving clients’ satisfaction with the logistics network, this paper investigates the optimization of a variant of the location-routing problem (LRP), namely the regional low-carbon LRP (RLCLRP), considering simultaneous pickup and delivery, hard time windows, and a heterogeneous fleet. In order to solve this problem, we construct a biobjective model for the RLCLRP with minimum total cost consisting of depot, vehicle rental, fuel consumption, carbon emission costs, and vehicle waiting time. This paper further proposes a novel hyper-heuristic (HH) method to tackle the biobjective model. The presented method applies a quantum-based approach as a high-level selection strategy and the great deluge, late acceptance, and environmental selection as the acceptance criteria. We examine the superior efficiency of the proposed approach and model by conducting numerical experiments using different instances. Additionally, several managerial insights are provided for logistics enterprises to plan and design a distribution network by extensively analyzing the effects of various domain parameters such as depot cost and location, client distribution, and fleet composition on key performance indicators including fuel consumption, carbon emissions, logistics costs, and travel distance and time.
Competitive Intelligence and Sustainable Competitive Advantage in the Hotel Industry
Authors: Casado Salguero Gisela , Fernández Gámez Manuel Ángel , Aldeanueva Fernández Ignacio , Ruíz Palomo Daniel
Published: March 2019

Competitive intelligence (CI) is a business tool within strategic management, and it is gaining significance as a process that enables companies to achieve sustainable competitive advantage. This study explores the current state of CI in the Spanish hotel industry. For this purpose, a path model has been developed which empirically investigates the relationship between CI use and its backgrounds. The results obtained suggest that environmental and organizational characteristics affect CI effort, and in turn, CI effort affects CI use. This study provides theoretical and practical implications to help managers develop sustainable competitive advantages through the potential that CI offers within the hotel industry.
Teaching Sustainability in European Higher Education Institutions: Assessing the Connections between Competences and Pedagogical Approaches
Authors: Lozano Rodrigo , Barreiro-Gen Maria , Lozano Francisco J. , Sammalisto Kaisu
Published: March 2019

There has been considerable progress in the incorporation of sustainable development (SD) into higher education institutions’ curricula. This has included research on competences for SD and pedagogical approaches used; however, there has been limited research on the connection between how pedagogical approaches are used and how they may develop sustainability competences. A survey was developed, based on the ‘connecting sustainable development pedagogical approaches to competences’ framework, to investigate sustainability being taught, sustainability competences developed, and pedagogical approaches used in European higher education institutions. The survey was sent to a database of more than 4000 contacts from which 390 complete responses (9.80%) were obtained. The results show that the social dimension was the least addressed at 18% of responses, while the economic, environmental, and cross-cutting dimensions were addressed almost equally. The correlation analyses showed a relation between the contribution to sustainability and the strength of competences, and between the strength of competences and the strength of pedagogical approaches. The results from the survey helped to update the theoretical framework, which provides a more precise perspective on how sustainability competences can be better developed in class, and how to better develop all the sustainability competences.
Local Energy Use of Biomass from Apple Orchards—An LCA Study
Authors: Dyjakon Arkadiusz , den Boer Jan , Szumny Antoni , den Boer Emilia
Published: March 2019

Generation of heat in small and medium-size energy systems using local sources of energy is one of the best solutions for sustainable regional development, from an economic, environmental, and social point of view. Depending on the local circumstances and preferences of the agricultural activity, different types and potentials of biomass are available for energy recovery. Poland is the third-largest producer of apples in the world. The large cumulative area of apple orchards in Poland and necessity of regular tree pruning creates a significant potential for agricultural biomass residues. In this paper, the LCA analysis of a new and integrated process chain focused on the conversion of cut branches coming from apple orchards into heat is conducted. Furthermore, the obtained results of the environmental indices have been compared to traditional mulching of pruned biomass in the orchard. It was shown that in terms of the LCA analysis, the biomass harvesting, baling, and transportation to the local heat producer leads to an overall environmental gain. The cumulative Climate Change Potential for pruning to energy scenario was 92.0 kg CO2 equivalent·ha−1. At the same time, the mulching and leaving of the pruned biomass in the orchard (pruning to soil scenario) was associated with a CO2 equivalent of 1690 kg·ha−1, although the soil effect itself amounted to −5.9 kg CO2 eq.·ha−1. Moreover, the sensitivity analysis of the LCA showed that in the case of the PtE chain, the transportation distance of the pruned bales should be limited to a local range to maintain the positive environmental and energy effects.
Accurate Modeling of the Microwave Treatment of Works of Art
Authors: Pierdicca Roberto , Paolanti Marina , Bacchiani Roberto , de Leo Roberto , Bisceglia Bruno , Frontoni Emanuele
Published: March 2019

The microwave heating treatment is a useful methodology and the disinfestation of works of art can also benefit from this approach. However, even if the microwave treatment is able to eliminate the pests that could damage the works of arts, it may nevertheless present some unexpected effects such as the presence of highly heated areas (hot spots) or areas with poor radiation due to particular shapes. To overcome this issue, we developed a mathematical model allowing predicting and monitoring tasks about the heating process. The prediction model has been developed into a software solution able to predict the distribution of heating power in objects to be treated, even of complex shapes, in order to define the exposure conditions, the time necessary to the processing, the power to be transmitted in the chamber and any repair or protection to cover the most sensitive areas. It can also predict the behaviour of irradiation in the presence of other entities such as nails or pests. The data to be provided for performing a simulation are: the geometry of the object, the shape of the infesting agent and their dielectric characteristics. As a result, we obtain the distribution of heating power and a software tool able to model and predict activities for cultural heritage treatments.
Decisions of Supply Chain Considering Chain-to-Chain Competition and Service Negative Spillover Effect
Authors: Wu Yucai , Wang Jiguang , Li Changhong
Published: March 2019

In today’s complex market competition environment, a high quality and high level of service plays a critical role in obtaining and maintaining long-term sustainable competitive advantage for enterprises and supply chains. Considering the service negative spillover effect, this paper investigates the horizontal Stackelberg competition and optimal service decision in two competing manufacturer-led supply chains. Four competitive structure models are constructed and the corresponding equilibrium solutions are obtained. By comparing the equilibrium results of four different structures, it is found that the service negative spillover effect and competition between supply chains have negative incentive effect on service providers and their supply chains. However, the chain-to-chain competition will benefit the supply chain that does not provide services from free-riding effect, which will be intensified with the intensification of competition. In addition, from the perspective of supply chain network and externality, we find that when the structure of one supply chain remains fixed and the other changes from centralized to decentralized, there will be a “double marginalization” effect. At the same time, the structural change from centralized to decentralized has certain “altruism”, that is, positive network externality, so as to improve the rival’s performance significantly.
Exploring Participatory Microregeneration as Sustainable Renewal of Built Heritage Community: Two Case Studies in Shanghai
Authors: Zhong Xiaohua , Leung Ho Hon
Published: March 2019

Since the 1990s, Shanghai has experienced massive urban development and renewal as ways to respond to its demographic, economic, and living space needs. Previous policies have led to the demolishment of many historical communities and valuable heritage housing. The existing ones continue to face extreme threats, such as bad physical conditions and the marginalization of communities. Yet there is a recent trend that emphasizes sustainable urban renewal named microregeneration (微更新), launched by municipal and local states since 2016. One of the main approaches of the initiative was to form new urban coalitions to focus on collaborative governance that helps integrate different agents’ expertise and values for more sustainable urban developments and renewals. This paper explores two cases on how this concept has emerged. The first case is An Shan Si Cun (鞍山四村). This housing block was built in the 1950s for employees of some state-owned enterprises. The second case is Jing Lao Cun (敬老邨). This alley house neighborhood was built in 1930s for migrants who came to Shanghai. Furthermore, this paper is to explore and compare their approaches to sustainable urban renewal, which attempts to preserve these communities that represent cultural and built heritage in Shanghai. Specifically, this paper examines the challenges and accomplishments of these experiments, and discusses policy implications for future tactics of sustainable urban renewal.
What Framework Promotes Saliency of Climate Change Issues on Online Public Agenda: A Quantitative Study of Online Knowledge Community Quora
Authors: Shi Wen , Chen Changfeng , Xiong Jie , Fu Haohuan
Published: March 2019

Though scientists have achieved consensus on the severity and urgency of climate change years ago, the public still considers this issue not that important, as the influence of climate change is widely thought to be geographically and temporally bounded. The discrepancy between scientific consensus and public’s misperception calls for more dedicated public communication strategies to get climate change issues back on the front line of the public agenda. Based on the large-scale data acquired from the online knowledge community Quora, we conduct a computational linguistic analysis followed by the regression model to address the climate change communication from the agenda setting perspective. To be specific, our results find that certain narrative strategies may make climate change issues more salient by engaging public into discussion or evoking their long-term interest. Though scientific communicators have long been blaming lack of scientific literacy for low saliency of climate change issues, cognitive framework is proved to be least effective in raising public concern. Affective framework is relatively more influential in motivating people to participate in climate change discussion: the stronger the affective intensity is, the more prominent the issue is, but the affective polarity is not important. Perceptual framework is most powerful in promoting public discussion and the only variable that can significantly motivate the public’s long-term desire to track issues, among which feeling plays the most critical role compared with seeing and hearing. This study extends existing science communication literature by shedding light on the role of previously ignored affective and perceptual frameworks in making issues salient and the conclusions may provide theoretical and practical implications for future climate change communication.
Contribution and Driving Mechanism of N2O Emission Bursts in a Chinese Vegetable Greenhouse after Manure Application and Irrigation
Authors: Cao Wenchao , Liu Su , Qu Zhi , Song He , Qin Wei , Guo Jingheng , Chen Qing , Lin Shan , Wang Jingguo
Published: March 2019

Solar greenhouse vegetable fields have been found to be hotspots of nitrous oxide (N2O) emissions in China, mainly due to excessive manure application and irrigation. Pulses of N2O emissions have been commonly reported by field monitoring works conducted in greenhouse fields, though their significance regarding total N2O emissions and the driving mechanism behind them remain poorly understood. N2O fluxes were monitored in situ using a static opaque chamber method in a typical greenhouse vegetable field. Then, laboratory incubations were conducted under different soil moisture and manure application gradients to monitor nitrous oxide emissions and related soil properties, using a robotized incubation system. Field monitoring showed that the occurrence of clear N2O emission bursts closely followed fertilization and irrigation events, accounting for 76.7% of the annual N2O efflux. The soil N2O flux increased exponentially with the water-filled pore space (WFPS), causing extremely high N2O emissions when the WFPS was higher than 60%. During the lab incubation, emission bursts led to N2O peaks within 40 h, synchronously changing with the transit soil NO2−. An integrated analysis of the variations in the gas emission and soil properties indicated that the denitrification of transit NO2− accumulation was the major explanation for N2O emission bursts in the greenhouse filed. Nitrous oxide emission bursts constituted the major portion of the N2O emissions in the Chinese greenhouse soils. Nitrite (NO2−) denitrification triggered by fertilization and irrigation was responsible for these N2O emission pulses. Our results clarified the significance and biogeochemical mechanisms of N2O burst emissions; this knowledge could help us to devise and enact sounder N2O mitigation measures, which would be conducive to sustainable development in vegetable greenhouse fields.