bluuebunny/crossref_metadata_2025 huggingface dataset:
Monitoring Key Wheat Growth Variables by Integrating Phenology and UAV Multispectral Imagery Data into Random Forest Model
Authors: Han Shaoyu , Zhao Yu , Cheng Jinpeng , Zhao Fa , Yang Hao , Feng Haikuan , Li Zhenhai , Ma Xinming , Zhao Chunjiang , Yang Guijun
Published: August 2022

Rapidly developing remote sensing techniques are shedding new light on large-scale crop growth status monitoring, especially in recent applications of unmanned aerial vehicles (UAVs). Many inversion models have been built to estimate crop growth variables. However, the present methods focused on building models for each single crop stage, and the features generally used in the models are vegetation indices (VI) or joint VI with data derived from UAV-based sensors (e.g., texture, RGB color information, or canopy height). It is obvious these models are either limited to a single stage or have an unstable performance across stages. To address these issues, this study selected four key wheat growth parameters for inversion: above-ground biomass (AGB), plant nitrogen accumulation (PNA) and concentration (PNC), and the nitrogen nutrition index (NNI). Crop data and multispectral data were acquired in five wheat growth stages. Then, the band reflectance and VI were obtained from multispectral data, along with the five stages that were recorded as phenology indicators (PIs) according to the stage of Zadok’s scale. These three types of data formed six combinations (C1–C6): C1 used all of the band reflectances, C2 used all VIs, C3 used bands and VIs, C4 used bands and PIs, C5 used VIs and PIs, and C6 used bands, Vis, and PIs. Some of the combinations were integrated with PIs to verify if PIs can improve the model accuracy. Random forest (RF) was used to build models with combinations of different parameters and evaluate the feature importance. The results showed that all models of different combinations have good performance in the modeling of crop parameters, such as R2 from 0.6 to 0.79 and NRMSE from 10.51 to 15.83%. Then, the model was optimized to understand the importance of PIs. The results showed that the combinations that integrated PIs showed better estimations and the potential of using PIs to minimize features while still achieving good predictions. Finally, the varied model results were evaluated to analyze their performances in different stages or fertilizer treatments. The results showed the models have good performances at different stages or treatments (R2 > 0.6). This paper provides a reference for monitoring and estimating wheat growth parameters based on UAV multispectral imagery and phenology information.
Performance Evaluation of Interest Point Detectors for Heterologous Image Matching
Authors: Wang Zhengbin , Yu Anxi , Dong Zhen , Zhang Ben , Chen Xing
Published: August 2022

In point-based heterologous image matching algorithms, high-quality interest point detection directly affects the final image matching quality. In this paper, starting from the detection mechanism of each interest point detector, optical images and SAR images with different resolutions and covering different areas are selected as experimental data. The five state-of-the-art SAR-Harris, UND-Harris, Har-DoG, Harris-Laplace and DoG interest point detectors are analyzed in terms of scale difference adaptability, nonlinear intensity difference adaptability, distribution uniformity, image registration alignment performance and detection efficiency. Then, we performed registration experiments on images from different sensors, at different times, and at different resolutions to further validate our evaluation results. Finally, the applicable image types of each detector are summarized. The experimental results show that SAR-Harris has the best performance in scale difference adaptability, and UND-Harris has the weakest performance. In terms of nonlinear intensity difference adaptability, SAR-Harris and UND-Harris are comparable, and DoG performance is the weakest. The distribution uniformity of UND-Harris is significantly better than other detectors. Although Har-DoG is weaker than Har-Lap and DoG in repeatability, it is better than both in final image alignment performance. DoG is superior in detection efficiency, followed by SAR-Harris. A comprehensive evaluation and a large amount of experimental data are used to evaluate and summarize each detector in detail. This paper provides a useful guide for the selection of interest point detectors during heterologous image matching.
Real-Time Imaging Processing of Squint Spaceborne SAR with High-Resolution Based on Nonuniform PRI Design
Authors: Jin Yanghao , Liang Buge , Chen Jianlai , Xiong Yi , Xiong Mingyao
Published: August 2022

The real-time imaging research of squint spaceborne synthetic aperture radar (SAR) with high resolution has significant value in both military and civil fields, which makes it a hot issue in SAR research. It is necessary to solve the contradictory problems of nonlinear trajectory and efficient imaging at the same time in order to achieve the two goals, high-resolution and real-time imaging. A large number of complex operations are required in the accurate correction algorithms for nonlinear trajectory, which will reduce the imaging efficiency, and this problem becomes more prominent with the improvement of resolution. To solve the above problems, this paper proposes a new real-time imaging processing of squint high-resolution SAR, which eliminates the velocity–azimuth variation caused by nonlinear trajectory in the data acquisition stage through nonuniform pulse repetition interval (PRI) design. The imaging efficiency has been greatly improved because the new method avoids the complex azimuth resampling operation. Simulation experiments verify the effectiveness of the method.
Photovoltaics Plant Fault Detection Using Deep Learning Techniques
Authors: Jumaboev Sherozbek , Jurakuziev Dadajon , Lee Malrey
Published: August 2022

Solar energy is the fastest-growing clean and sustainable energy source, outperforming other forms of energy generation. Usually, solar panels are low maintenance and do not require permanent service. However, plenty of problems can result in a production loss of up to ~20% since a failed panel will impact the generation of a whole array. High-quality and timely maintenance of the power plant will reduce the cost of its repair and, most importantly, increase the life of the power plant and the total generation of electricity. Manual monitoring of panels is costly and time-consuming on large solar plantations; moreover, solar plantations located distantly are more complicated for humans to access. This paper presents deep learning-based photovoltaics fault detection techniques using thermal images obtained from an unmanned aerial vehicle (UAV) equipped with infrared sensors. We implemented the three most accurate segmentation models to detect defective panels on large solar plantations. The models employed in this work are DeepLabV3+, Feature Pyramid Network (FPN) and U-Net with different encoder architectures. The obtained results revealed intersection over union (IoU) of 79%, 85%, 86%, and dice coefficients of 87%, 92%, 94% for DeepLabV3+, FPN, and U-Net, respectively. The implemented models showed efficient performance and proved effective to resolve these challenges.
Effect of Rising Temperature and Carbon Dioxide on the Growth, Photophysiology, and Elemental Ratios of Marine Synechococcus: A Multistressor Approach
Authors: Basu Samarpita , Mackey Katherine R. M.
Published: August 2022

Marine picocyanobacteria belonging to the genus Synechococcus are one of the most abundant photosynthetic organisms on Earth. They are often exposed to large fluctuations in temperature and CO2 concentrations in the ocean, which are expected to further change in the coming decades due to ocean acidification and warming resulting from rising atmospheric CO2 levels. To decipher the effect of changing temperature and CO2 levels on Synechococcus, six Synechococcus strains previously isolated from various coastal and open ocean sites were exposed to a matrix of three different temperatures (22 °C, 24 °C and 26 °C) and CO2 levels (400 ppm, 600 ppm and 800 ppm). Thereafter, the specific growth rates, photophysiological parameters (σPSII and Fv/Fm), C/N (mol/mol) ratios and the nitrogen stable isotopic composition (δ15N (‰)) of the strains were measured. Temperature was found to be a stronger driver of the changes in specific growth rates and photophysiology in the Synechococcus strains. Carbon-concentrating mechanisms (CCM) operational in these strains that shield the photosynthetic machinery from directly sensing ambient changes in CO2 possibly played a major role in causing minimal changes in the specific growth rates under the varying CO2 levels.
The Pricing Mechanism Analysis of China’s Natural Gas Supply Chain under the “Dual Carbon” Target Based on the Perspective of Game Theory
Authors: Che Cheng , Geng Xin , Zheng Huixian , Chen Yi , Zhang Xiaoguang
Published: August 2022

China is currently the world’s largest energy consumer and carbon emitter. In order to reduce the harm of carbon dioxide to the global ecological environment, the use of natural gas instead of coal is a realistic choice for China to achieve the “dual carbon” goal. Opportunities also bring new challenges, and the price of natural gas is an important method of promoting the upstream and downstream industrial chains of natural gas, so it is of great practical significance to study the price of natural gas. This paper builds a three-level supply chain model consisting of suppliers in the natural gas market, city gas companies and consumers in the market and uses the Stackelberg game to study the decision-making models of different subjects under their own dominance and centralized decision-making; it also considers the pricing mechanism and profit situation of stakeholders in the natural gas market under the low-carbon preference of consumers and the level of corporate carbon emission reduction. The research results show that when considering consumers’ low-carbon preferences, the sales prices of various stakeholders in the market have increased, which is beneficial for all entities in the natural gas industry chain. At the same time, with the low-carbon transformation of energy companies, the production method drives the price of raw materials to rise in the process of low-carbon innovation, which, in turn, makes the price of various stakeholders in the natural gas market and the level of carbon emission reduction per unit show a positive relationship; in order to maximize the overall profit of the supply chain, the natural gas market should adopt a centralized decision-making method to further promote the reform of China’s natural gas marketization.
Back Contact Engineering to Improve CZTSSe Solar Cell Performance by Inserting MoO3 Sacrificial Nanolayers
Authors: Chen Cheng-Ying , Kholimatussadiah Septia , Chen Wei-Chao , Lin Yi-Rung , Lin Jia-Wei , Chen Po-Tuan , Chen Ruei-San , Chen Kuei-Hsien , Chen Li-Chyong
Published: August 2022

Earth-abundant Cu2ZnSn(S,Se)4 (CZTSSe) is a promising nontoxic alternative compound for commercially available Cu(In,Ga)(S,Se)2 thin-film solar cells. In this study, a MoO3 nanolayer was applied as a sacrificial layer to optimize the quality of the interface between the CZTSSe and Mo back contact. MoO3 nanolayers can greatly improve CZTSSe grain growth and suppress the formation of some harmful secondary phases, especially the undesirable MoS(e)2. In terms of device performance, the series resistance was reduced from 1.83 to 1.54 Ω·cm2, and the fill factor was significantly enhanced from 42.67% to 52.12%. Additionally, MoO3 nanolayers improved CZTSSe absorber quality by lowering the defect energy levels from 228 to 148 meV. Furthermore, first-principles calculations demonstrate that the partial sulfoselenized MoO3 nanolayers may function as the (p-type) hole-selective contacts at Mo/CZTSSe interfaces, leading to an overall improvement in device performance. Lastly, a CZTSSe solar cell with about 26% improvement (compared with reference cells) in power conversion efficiency was achieved by inserting 5 nm MoO3 sacrificial layers.
Structural Evolution and Sustainability of Agricultural Trade between China and Countries along the “Belt and Road”
Authors: Zhou Lunzheng , Tong Guangji
Published: August 2022

Enhancing trade in agricultural products between China and countries along the “Belt and Road” (B&R) will help strengthen China’s food security and promote global, sustainable economic development. Based on the agricultural trade data between China and B&R countries from 2001 to 2019, we used the TII index, the HHI index, and the social network analysis method to calculate the trade structure of agricultural products between China and B&R countries, in terms of plane structure and spatial network structure, and analyzed the influencing factors of their spatial network structure. The results show that China’s agricultural trade with B&R countries is highly concentrated in terms of regions and types, the import trade is decentralized, while the export trade is concentrated, and the regions with high trade intensity are mainly concentrated in the countries in close proximity. China’s agricultural trade network with B&R countries has become increasingly close, and China has a significant presence in trade networks. The trade network shows four major segments, and the internal and external trade of each segment has become increasingly close. Water resources, geographical location, transportation, trade agreements, and trade structure are the main influencing factors in the trade network between China and B&R countries. Our findings provide useful insights for informed decision-making in the development of international agricultural sustainable cooperation strategies.
Adapting Reverse Mentoring Strategy to SMEs: A New Pilot Model Implemented in Brazil
Authors: Schwartz Dafna , Bar-El Raphael , Bentolila David J.
Published: August 2022

In recent years, the Reverse Mentoring (RM) model has gained popularity in large companies. Although the prevailing RM model—junior employees mentoring senior employees—benefits both groups and promotes innovation, small and medium-sized enterprises (SMEs) do not implement it due to lack of economies of scale, organizational capacities, and skilled junior employees. We devise a new RM model for SMEs that overcomes these disadvantages. First, the intervention of an intermediate, trusted professional entity initiates and supports the program for several companies; second, the mentors are not junior employees, but external graduate students with education in innovation. A pilot experiment was tested in the state of Ceara, Brazil. The preliminary findings support the new model’s feasibility and efficacy for SMEs. The intervention stimulated significant innovative ideas and resulted in out-of-the-box thinking, identification of potentials for innovation opportunities, and adaptation of an open innovation approach, which is important for SMEs with limited financial and non-financial resources. This study contributes to the literature on SMEs and RM by offering a new model that can overcome existing market failures experienced by SMEs. Empirical testing demonstrates its feasibility.
Citizen Science as an Innovative Approach to Analyze Spatial and Temporal Influences on Nitrate Pollution of Water Bodies: Results of a Participatory Research Project in Germany
Authors: Brockhage Frauke , Lüsse Mientje , Klasmeier Jörg , Pietzner Verena , Beeken Marco
Published: August 2022

Anthropogenic influences and the excessive input of reactive nitrogen compounds into the environment have already severely destabilized the natural nitrogen cycle. Especially in northwestern Germany, many water bodies are polluted by nitrate, inducing negative effects on the ecosystem and drinking water as well as possible risks to human health. In cooperation with almost 600 citizens and 200 students, this issue was addressed in a citizen science project carried out by the Universities of Osnabrück and Oldenburg, gathering 8754 nitrate measurements at 545 monitoring sites from September 2019 to March 2021. The data were used to evaluate the potential of citizen science for research on nitrogen pollution of water bodies. In a pre-investigation, we proved that nitrate test strips are suitable as a measurement method for the citizen science approach to provide an overview of nitrate pollution. We then analyzed whether the citizen science approach can be used to establish an area-wide representative measurement network, to what extent the data can be used for spatial and temporal analyses, and whether the data are consistent with the results of other monitoring initiatives. For this purpose, geoprocessing tools, such as spatial joins and heatmaps, were combined with descriptive statistics and nonparametric statistical tests. Although it was not possible to establish a representative monitoring network due to the uneven spatial distribution of monitoring sites, a large part of the intended area was covered by monitoring sites. Thus, the data provide a good overview of the nitrate pollution in the region and shed light on influencing factors. Spatial impacts, such as land cover and use and hydrogeological conditions, as well as seasonal impacts were statistically evidenced with the citizen science data. Furthermore, the consistency of the data with the measurement results of established measurement initiatives confirm the quality of the citizen science dataset. Accordingly, citizen science can be used to investigate spatial and temporal factors influencing nitrogen pollution, and thus contributes to water conservation research as an innovative approach.
Ruins and Remains as a Background: Natural Catastrophes, Abandonment of Medieval Villages, and the Perspective of Civilization during the 20th Century in the Central Apennines (Abruzzi Region, Central Italy)
Authors: Galadini Fabrizio
Published: August 2022

The resettlement of villages strongly damaged by catastrophes during the 20th century played a key role in the modification of the Apennine landscape in Italy. Following their abandonment, the remains of the medieval settlements progressively deteriorated in their ruined condition, becoming ghost villages often made of sparse portions of buildings, traces of outer walls, and isolated vestiges of ancient monuments colonized by vegetation. Five cases of central Apennine abandoned villages in the Abruzzi region (Frattura, Sperone, Albe, Salle, and Gessopalena) were investigated, combining information on the local adverse geological conditions with the historical reconstruction of their abandonment and resettlement, based on archive documents from the 19th and 20th centuries. The history of these localities was conditioned by two strong earthquakes that struck the Abruzzi region in 1915 (magnitude 7.1) and 1933 (magnitude 5.9), and by slope instability. In all cases, abandonment and resettlement produced new villages against the background of ancient ruins and remains. In conclusion, the paper discusses the potential use of the material traces of local histories with educational aims. Geological evidence of natural hazards, remains of the abandoned settlements and resettled villages could be arranged in museums aimed at increasing the awareness of natural hazards and risks.
Human Exceptionalist Thinking about Climate Change
Authors: Betz Nicole , Coley John D.
Published: August 2022

Although global climate change poses a real and looming threat to both human societies and the natural world, large gaps in understanding exist between the general public and the scientific community. One factor contributing to such gaps could be the use of intuitive thinking to understand complex phenomena. In two studies, we explore climate change understanding and engagement through the lens of an intuitive pattern of thinking, human exceptionalism, which refers to the tendency to infer that humans are exceptional to, and separable from, the rest of the natural world. In both studies, undergraduates thought about global climate change in human exceptionalist ways that were orthogonal to accuracy—for example, they correctly think that humans uniquely contribute to climate change compared to other organisms, but incorrectly think that humans will be uniquely immune to the effects of global climate change. Moreover, human exceptionalist thinking has real-world consequences; it was negatively associated with eco-friendly attitudes and behaviors, and negatively predicted individuals’ attribution of damage from recent hurricanes (i.e., hurricanes Michael and Florence) to global climate change. Finally, we demonstrated that increasing the salience of connections between humans and global climate change reduced human exceptionalism. Findings suggest that intuitive thinking in general, and human exceptionalism in particular, make important contributions to how we understand and reason about global climate change, and may be promising targets for interventions aimed at increasing pro-environmental attitudes and behaviors.
Unlocking Barriers to Circular Economy: An ISM-Based Approach to Contextualizing Dependencies
Authors: Jensen Steffen Foldager , Kristensen Jesper Hemdrup , Uhrenholt Jonas Nygaard , Rincón Maria Camila , Adamsen Sofie , Waehrens Brian Vejrum
Published: August 2022

Despite it being imperative to a sustainable development, a circular economy remains scarcely adopted by companies. Barriers towards this are extensively explored yet with little focus on their mutual dependencies. Neglecting dependencies is argued to cause suboptimization and lead to unsuccessful circular projects. To counter this and strengthen companies in assessing dependencies among context-dependent barriers towards a circular transition, this study proposes a practice-oriented approach based on an interpretive structural modelling methodology. This is validated through a case study with a Danish mechatronics manufacturer with which fourteen semi-structured interviews, a survey, and a workshop were conducted. Findings reveal an interwoven network of barriers with numerous chain mechanisms across managerial, market-related, financial, technical, and regulative aspects, which underpins the need to approach the circular transition systemically. Furthermore, the study demonstrates the ability of the methodology to facilitate discussions and assist industrial practitioners, both on a strategic and operational level, in systematically untangling the complex interrelations to identify root causes for inertia and prioritize mitigation measures.
Carbon Emissions in the Yellow River Basin: Analysis of Spatiotemporal Evolution Characteristics and Influencing Factors Based on a Logarithmic Mean Divisia Index (LMDI) Decomposition Method
Authors: Liu Ke , Xie Xinyue , Zhao Mingxue , Zhou Qian
Published: August 2022

The “14th Five-Year Plan” period is a critical period and a window to obtain emission peak and carbon neutrality in China. The Yellow River Basin, a vital location for population activities and economic growth, is significant to China’s emission peak by 2030. Analyzing carbon emissions patterns and decomposing the influencing factors can provide theoretical support for reducing carbon emissions. Based on the energy consumption data from 2000–2019, the method recommended by Intergovernmental Panel on Climate Change (IPCC) is used to calculate the carbon emissions in the Yellow River Basin. The Logarithmic Mean Divisia Index (LMDI) decomposition method decomposes the influence degree of each influencing factor. The conclusions are as follows: First, The Yellow River Basin has not yet reached the peak of carbon emissions. Regional carbon emissions trends are different. Second, Shandong, Shanxi, Henan and Inner Mongolia consistently ranked in the top four in total carbon emissions, with low carbon emission efficiency. Third, Economic development has the most significant contribution to carbon emissions; other factors have various effects on nine provinces.
Aging Population Spatial Distribution Discrepancy and Impacting Factor
Authors: Zhang Ke , Sun Hao , Li Xiangyu
Published: August 2022

The phenomenon of population aging is gradually spreading around the world. Consequently, it is leading to unsustainable economic development due to the decline of the labor force. Therefore, many people identify the aging population from national and intercontinental levels, as it would not be possible to recognize specific population spatial distribution characteristics and impacting factors in a province or state because of the spatial and temporal differences. In this paper, Jiangsu Province was selected as the study area to represent its aging population’s spatial characteristics and to identify the spatial heterogeneity with impacting factor by Geographically Weighted Regression (GWR), as well as to determine the impacting situation by marginal effect. The results show the following: (1) The impact factor’s spatial heterogeneity from the cities in Jiangsu Province is small but occurs in the city groups, while the impacting situation is the same in the north, central and south city groups, showing a disparity among them. (2) There is a significant change in the impact factor’s influence from 2010 to 2020. (3) The social–economic factor negatively relates to the aging population in 2020, with an interval value of [−1.0585, −1.0632]. This finding indicates that the spatial heterogeneity of the aging population at the province level is not the same as that at the national level. Therefore, we need to consider the local situation more. These findings further provide an empirical basis for the province-level study of the aging population, which differs from the national level.
A Comparative Analysis of the Acquisition Transaction of Management Information Systems through Virtual and Face-to-Face Negotiations—The Perspective of Green IT Industry in Poland
Authors: Wachnik Bartosz , Krupa Aleksandra , Santarek Krzysztof
Published: August 2022

The COVID-19 pandemic that began in 2020 has significantly impacted businesses, regardless of size or industry. The hybrid and remote working models have moved all meetings with potential and existing suppliers to an online environment. This also applies to small- and medium-sized enterprises (SMEs), which have had to adapt themselves to the new situation and implement the solutions necessary to survive on the market. On the other hand, clients have become more aware of the environment and its changes. Customers are trying to be more eco-friendly, by choosing and moving towards Green IT. Thus, this needs to be considered. The acquisition of management information systems (MIS) in the pandemic era is based only on virtual meetings. The main goals of this paper were the identification of the changes in the negotiations caused by the COVID-19 pandemic, the transformation of this process into virtual environment, discussion of the possibility of using Green IT in addition to Management Information Systems, and the changes caused by the pandemic. The article was prepared based on the results of qualitative research using the case study method. The comparative analysis includes purposely selected cloud-based Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) systems’ acquisition processes, presented from the clients’ perspective. The research was conducted in 2021, based on the authors’ practical experience, and presents four cases. This research illustrates the negotiations concerning an acquisition transaction pre-pandemic and during the pandemic. Finally, the conclusions and main differences caused by the pandemic in the acquisition transaction process of management information systems (MIS) are presented.
Sustainability Accounting Studies: A Metasynthesis
Authors: Gil-Marín Miseldra , Vega-Muñoz Alejandro , Contreras-Barraza Nicolás , Salazar-Sepúlveda Guido , Vera-Ruiz Sandra , Losada Analia Verónica
Published: August 2022

This review article seeks to discuss the sustainability accounting concept by examining previously conducted studies on this topic in order to understand its thematic progress in the academic literature. This study is a metasynthesis, where, in the identification phase, 334 documents published in the Web of Science (WoS) database are selected, and in the literature review stages, 15 re-reviews are selected according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) method. The results reveal that businesses, academia, and regulatory bodies do not recognize a homogeneous terminology when it comes to sustainability accounting. There is a variety of synonyms that complicate the disclosure of activities carried out by companies in the pursuit of the sustainability development goals (SDGs), with SDGs 5, 6, 13, 14, and 15 being analyzed in the academic literature in relation to the sustainability accounting concept. For future research directions, the review articles analyzed suggest examining the concrete effects produced by practices related to sustainability performance in companies, linking the relevance of understanding the sustainability reports related to the sustainability performance of companies.
Research on the Spatial Agglomeration of Commodity Trading Markets and Its Influencing Factors in China
Authors: Xie Shouhong , Li Hanbing
Published: August 2022

Spatial agglomeration, as a phenomenon of commodity trading markets, reflects regional economic development in China. This study explores the spatial agglomeration of commodity trading markets and analyzes its influencing factors. Based on the panel data of 30 provinces in China from 2010 to 2019, this article first calculated the location quotient of the transaction volume of commodity trading markets and analyzed their temporal and spatial trends. Finally, a spatial econometric model was used to conduct an empirical examination of the influencing factors determining the spatial agglomeration of commodity trading markets. The results show that the agglomeration pattern of China’s commodity trading markets has changed significantly from 2010 to 2019. In terms of geographic variations, we discovered that the eastern region has a higher degree of commodity trading market concentration than the central and western regions. In terms of influencing factors, this study found that the level of economic development, the degree of openness, and the development of private industrial enterprises still positively affect the spatial agglomeration of commodity trading markets. However, the level of social consumption has no significant impact. Based on these findings, this article puts forward relevant policy recommendations to promote the further development of China’s commodity exchange market.
Selenium Application Decreases the Enrichment and Human Exposure Risk of Cadmium in the Leaf of Jute (Corchorus capsularis L.) Planted in Uncontaminated Purple Soil
Authors: Liu Dan , Tao Lei , Li Xiang , Xiong Chunmei , Yang Xiaoxia , Nie Qingyu , Lin Junjie
Published: August 2022

The effects of soil selenium (Se) application on the enrichment and human exposure risk of heavy metals in the jute (Corchorus capsularis L.) leaf have attracted extensive attention. The jute was planted with or without soil Se addition for 265 days. The jute leaf was harvested seven times during the experiment to determine the content of lead (Pb), cadmium (Cd), and Se. The results showed that the enrichment ability ranked Cd > Se > Pb. Cd in the jute leaf exceeded the average pollutant limit in GB2762-2017 by 1.37 times without Se application. The Se application is conducive to an increase of Se by 88.11–202.79%, contrarily reducing Cd by 35.40–38.32% and Pb by 9.58–26.57%. In general, the risk quotients (HQ) of Cd and Pb were decreased and less than 1 with Se treatment. Thus, the human exposure risk of Cd and Pb is negligible when ingesting the jute leaf via diet. It is suggested that Se can be applied to inhibit the enrichment of Cd and Pb in the jute production process to reduce the potential exposure risk of Cd and Pb to the human body and increase economic and nutritional values by raising Se levels in the jute leaf.
Post-Occupancy Evaluation of Green Technologies for a High-Rise Building Based on User Experience
Authors: Ye Changqing , Yao Linfeng , Meng Yuan , Zhang Yu , He Guoqing
Published: August 2022

Post-occupancy evaluations of buildings help us understand the effectiveness of building designs. Most of such evaluations focus on the overall building performance and on the indoor air environment, and few focus on individual technologies. In this paper, we report a user experience-based evaluation on multiple green technologies applied in a high-rise building constructed 17 years ago. These technologies include a circular building design, innovative floor plans, a corridor-type, double-skin facade with cavity shading, and three-dimensional greening design. Data were obtained through a questionnaire for the building occupants and on-site measurements of environmental variables. The results show that the occupants were most satisfied with the three-dimensional greening, natural lighting and ventilation in the public spaces, and the sound and thermal environment of the rooms with the double facade. They were not satisfied with room ventilation, solar shading, or lighting adjustment provided by the double facade. In addition, the aesthetic appearance of the circular building was not recognized by the occupants, who appeared to pay more attention to its space efficiency than the external appearance. This was true especially for older occupants. The users expressed a strong demand for outdoor leisure spaces and green vegetation. However, the practicality and functionality of three-dimensional greening, along with the interference of the glass curtain wall on vegetation growth, calls for more attention to the design. The female occupants were found to be more sensitive to the thermal and acoustic environment. Based on these results, we provide recommendations on the maintenance of the building and the future design of these measures.
Data-Driven Resource Efficiency Evaluation and Improvement of the Logistics Industry in 30 Chinese Provinces and Cities
Authors: Ding Heping , Guo Yuxia , Wu Xue , Wang Cui , Zhang Yu , Liu Hongjun , Liu Yujia , Lin Aiyong , Hu Fagang
Published: August 2022

Improving the logistics industry’s resource efficiency (LIRE) is one of the most significant measures for ensuring sustainable development. We offer a data-driven technique for analyzing and optimizing the LIRE to improve it and achieve sustainable development. A LIRE index system is built based on relevant data gathering and a complete examination of the economy, society, and environment. The Super-EBM-Undesirable model was used to calculate the LIRE; the Global Malmquist–Luenberger index model was used to calculate the LIRE’s dynamic change characteristics, and ArcGIS and spatial autocorrelation models were used to analyze the LIRE’s spatial evolution pattern. The LIRE in 30 Chinese provinces and cities from 2011 to 2019 is used to illustrate the method implementation process. The results indicate the following: (1) The overall LIRE is low, with an average value of 0.717, and there are regional variances with a decreasing gradient pattern of “East–Northeast–Central–West”. (2) Changes in pure technical efficiency have a bigger impact in general; increasing technical efficiency is the LIRE’s principal motivator. (3) Improving the LIRE should take spatial spillover and inhibitory effects into account. This study provides theoretical and methodological support for the evaluation and optimization of the LIRE and a theoretical foundation for the logistics industry’s sustainable development (LISD).
A Hybrid MCDM for the Location of Urban Distribution Centers under Uncertainty: A Case Study of Casablanca, Morocco
Authors: Bennani Maha , Jawab Fouad , Hani Yasmina , ElMhamedi Abderrahman , Amegouz Driss
Published: August 2022

In this article, the main subject is the problem of the location of Urban Distribution Centers (UDC) in an environment characterized by uncertainty. Thus, a decision support process based on fuzzy multi-criteria methods (F-MCDM) will be proposed as the solution. The CATWOE method is used for identifying the Stakeholders (PPs) concerned by the localization. Furthermore, direct interviews and the review of the literature help to enhance the decision criteria. The use of the F-SWARA method made it possible to weight the criteria by taking into consideration the opinion of the PPs. The F-ENTROPY method corrected the subjectivity of the weights given by the first method. The hybridization of the two is a first in the literature in this field and allows precise and realistic results. In the end, the different alternatives obtained by the F-VIKOR method are ranked. This approach was applied to the city of Casablanca, which is extremely impacted by the negative externalities of urban freight transport. The results of this study showed that zone four (AIN SBAA) is the best zone to implement the UDC in the city of Casablanca. The sensitivity analysis validated the robustness of the model.
A Strategy for Conservation of Springsnails in Nevada and Utah, USA
Authors: Stevens Lawrence E. , Holcomb Kathryn , Crookshanks Chris , Sada Donald W. , Jenness Jeff , Szabo Kristin
Published: August 2022

The Nevada and Utah Springsnail Conservation Strategy (the Strategy) is a comprehensive and proactive 10-year plan to protect 103 species of truncatelloidean springsnails and their habitats (primarily springs). Springsnails are tiny, aquatic, and often locally endemic truncatelloidea and cerithioidean snails threatened by both local and regional stressors. A bi-state agreement (the Agreement) was forged by state and federal agencies and The Nature Conservancy (TNC) in 2018 in a manner consistent with U.S. Fish and Wildlife Service (USFWS) conservation criteria. Successful achievement of Agreement objectives will protect springsnails and their habitats in the two states, precluding the need for a federal listing of those species. The objectives of the Agreement are to: (1) compile springsnail ecology and distribution data into a single database; (2) identify, assess, and reduce threats to the taxa and their habitats; (3) maintain, enhance, and restore spring habitats; (4) develop and maintain a springsnail conservation team (SCT); and (5) create an effective education and outreach program for landowners, agencies, and the general public. The SCT held in-person and multiple virtual meetings in 2019–2020 to initiate the Strategy, introduce and clarify member roles, and pursue the integration of available information. The SCT assembled information and literature on each taxon in the two states into the Springs Online database (springsdata.org), a password-protected, easily used online information management system for archiving and reporting on springs-dependent species taxonomy, distribution, associated species, and population and conservation status data. The information gathered was used to generate conservation reports for individual species that can be readily updated as new information emerges. Within each Agreement objective, we describe issues to ensure springsnail species representation, resiliency, and redundancy, which are USFWS metrics of population integrity. We describe springsnail diversity and distribution, the threats and challenges to effective springsnail conservation, and the process the SCT is using to address those issues. Development of the Strategy enables the SCT to monitor, prioritize, and readily report on springsnail conservation progress over the decadal life of the Agreement. As one of the largest springs and springs-dependent species conservation efforts in the world, the context and development of the Strategy provide key lessons for other such efforts.
Study on the Evolution of the Spatial-Temporal Pattern and the Influencing Mechanism of the Green Development Level of the Shandong Peninsula Urban Agglomeration
Authors: Jiang Shuguang , Yu Huilu , Li Zehong , Geng Biao , Li Ting
Published: August 2022

Improving the level of green development is an inevitable requirement for promoting the construction of an ecological civilization. In this paper, through a green development level evaluation index system, the CRITIC weight method is used to comprehensively evaluate and analyze the green development level of the Shandong Peninsula Urban Agglomeration from 2007 to 2019. On this basis, a panel data model was constructed to analyze the key influencing factors of the green development level of the Shandong Peninsula Urban Agglomeration. Studies have shown that (1) the level of green development in the Shandong Peninsula Urban Agglomeration from 2007 to 2019 has been steadily improved, but the overall level is still at a low level, with significant differences among the cities. (2) Qingdao and Jinan are the two growth poles of the green development level of Shandong Peninsula Urban Agglomeration. The dual-core leading effect is obvious, forming a spatial pattern in which the green development level of the eastern and central regions is higher than that of other regions’ green development level. (3) Weihai, Dongying, and Qingdao are high-level cities of green development, while Jinan, Yantai, Zibo, Tai’an, and Linyi are medium-level cities of green development. The green development level of other cities is relatively low, and the high-level cities of green development are mostly the Jiaodong economic circle and provincial capital economic circle. (4) Industrial structure, scientific and technological innovation, and government policies are the critical factors in promoting the green development of the Shandong Peninsula Urban Agglomeration.
Sustainable Luxury Consumers’ Preferences and Segments: Conjoint and Cluster Analyses
Authors: Chang Wen-Yun , Taecharungroj Viriya , Kapasuwan Supara
Published: August 2022

Sustainable luxury is an emerging concept that has gained traction in the industry. However, limited studies have explored the preferences of consumers towards sustainable luxury products. Therefore, the first objective of this research was to identify the sustainable luxury attributes that appeal to the consumers, while the second objective was to segment consumers based on their sustainability and luxury preferences. Data were collected from 354 consumers in Thailand and Taiwan; preferences were determined using a choice-based conjoint analysis. K-means clustering was performed to identify sustainable luxury consumers as customizers, perfectionists, legacy lovers, zero-waste warriors, transparency trackers, and green operators. This research is the first to shed light on the multiplicity of sustainable luxury consumers. It also indicates the role of sustainable information in decision making.
Life Cycle Assessment of a Circularity Case Study Using Additive Manufacturing
Authors: Gouveia Joana R. , Pinto Sara M. , Campos Sara , Matos João R. , Costa Catarina , Dutra Thiago Assis , Esteves Sílvia , Oliveira Luís
Published: August 2022

Currently, considering the rising concern in climate change, there is a clear necessity for technologies that can prolong the useful life of products through the ability to repair, re-manufacture and refurbish. As such, additive manufacturing has been a subject of research due to its design and resource consumption capabilities. However, there is a lack of more detailed information regarding environmental performances, especially in Directed Energy Deposition technology. The present paper presents a life-cycle assessment of the production and use of Directed Energy Deposition, making use of foreground data to build a life-cycle inventory and quantify the potential impacts. The equipment is analyzed for its refurbishment capabilities on an obsolete mold, and compared with the environmental impact of producing a new mold through conventional technology. The compiled inventory with detailed and primary information will enrich the current literature on this technology. The impact results show that the robot, deposition table and security cell are the most relevant subsystems for the system production impacts. In the refurbishment analysis, the refurbished mold part has lower impacts than the conventionally produced, thus showing that there is great potential in using additive manufacturing for circular economy loops.
Poultry Slaughterhouse Wastewater Treatment Using an Integrated Biological and Electrocoagulation Treatment System: Process Optimisation Using Response Surface Methodology
Authors: Ngobeni Philadelphia Vutivi , Gutu Larryngeai , Basitere Moses , Harding Theo , Ikumi David
Published: August 2022

The feasibility of a biological (EcoflushTM) and/or electrocoagulation (EC) treatment system in removing chemical oxygen demand (COD) and fats, oils, and grease (FOG) from poultry slaughterhouse wastewater (PSW) were studied. The response surface methodology (RSM) was used to identify the optimum operating condition for EC and its integration with EcoflushTM as a pre-treatment for the removal of lipids. The optimum operating conditions were obtained at a pH of 3.05, a current density of 66.9 A/m2, 74-min of treatment time, and without Ecoflush™. These conditions produced a high-quality clarified effluent after 92.4% COD reduction and 99% FOG reduction. The treatment with EcoflushTM only resulted in 85–99% FOG reduction, 20–50% COD reduction, and odourless effluent. However, the combination of both processes (EcoflushTM and EC) did not yield a significant difference (F test, p > 0.05) when compared to the performance of EC alone. Despite the low removal percentages of nitrogen and phosphorus, the present study proved that EC is an effective method for the removal of COD and FOG, rendering an effluent that meets the permissible discharge standards for the City of Cape Town. The novel Ecoflush™ also proved to be very efficient in the removal of FOG from PSW.
Bacterial Isolates from Greek Sites and Their Efficacy in Degrading Petroleum
Authors: Ntroumpogianni Georgia C. , Giannoutsou Eleni , Karagouni Amalia D. , Savvides Alexandros L.
Published: August 2022

Polycyclic aromatic hydrocarbons (PAHs) are a major organic pollutant, not only because they do not self-degenerate but also because they accumulate in the food chain and give rise to serious repercussions in terms of biodiversity sustainability. Petroleum-degrading bacteria have long been used as a promising solution in the effort to biodegrade crude oil. In this study, new isolates from specific Greek environments displaying various levels of crude oil contamination, as well as isolates belonging to the ATHUBA collection, were thoroughly investigated for their capacity to degrade crude oil. Furthermore, the presence of nahH and alkJ genes in the above bacterial isolates, as well as their ability to form agglomerates or release surfactants, was investigated. Two consortia were formed, and their ability to degrade crude oil was tested, achieving similar degrading capacities as those observed with the individual strains. A Pseudomonas plecoglossicida isolate demonstrated the highest percentage (76.7%) ability to degrade crude oil. The biodegradation rate of this isolate was further evaluated by measuring the alkanes/hopanes ratio over a period of ten days, exhibiting a higher degradation rate in short-chain (C11–C21) alkanes, whereas a decrease in the ratio was observed when the number of carbons in petroleum increased. This is the first detailed report on bacterial communities in oil-polluted areas of Greece that contain a variety of bacteria with the ability to degrade PAHs in contaminated sites and may provide a novel alternative to various bioremediation processes or be used as inocula in autochthonous bioaugmentation procedures for crude oil biodegradation.