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description Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2021Publisher:MDPI AG Authors: Aitian Tao; Ang Tian; He Yang; Jing An;doi: 10.3390/su132313205
In recent years, the rapid development of the rare earth industry has had a serious impact on the environment. Some enterprises have taken measures to improve the production process. In order to explore the sustainability of this industry and these improvements’ environmental benefits, this paper combines emergy analysis and lifecycle assessment to evaluate and compare the production process of rare-earth oxides considering the three aspects of emergy flow, pollutant emissions, and emergy-based indicators. Changes in the emergy of pollutant emissions before and after improvement of the production process are discussed. The results show that the greatest inputs in the mining and beneficiation stage and smelting separation stage are labor force and service and non-renewable resources, respectively. These two production stages are highly dependent on external input and have weak competitiveness. Both stages place great pressure on the environment, so the bastnasite production process would be unsustainable in the long term. After the improvement, the environmental impact of the production process for bastnaesite changed significantly, indicating that the improvement effect of the wastewater treatment facilities and the change of fuel from coal to natural gas is remarkable.
Sustainability arrow_drop_down SustainabilityOther literature type . 2021License: CC BYData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su132313205&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!
more_vert Sustainability arrow_drop_down SustainabilityOther literature type . 2021License: CC BYData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su132313205&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022Publisher:Elsevier BV Authors:Ahmed, Asam;
Ge, Tianshu;Ahmed, Asam
Ahmed, Asam in OpenAIREPeng, Jinqing;
Yan, Wei-Cheng; +2 AuthorsPeng, Jinqing
Peng, Jinqing in OpenAIREAhmed, Asam;
Ge, Tianshu;Ahmed, Asam
Ahmed, Asam in OpenAIREPeng, Jinqing;
Yan, Wei-Cheng; Tee, Boon Tuan;Peng, Jinqing
Peng, Jinqing in OpenAIREYou, Siming;
You, Siming
You, Siming in OpenAIREDecarbonizing the building sector is extremely important to mitigating climate change as the sector contributes 40% of the overall energy consumption and 36% of the total greenhouse gas emissions in the world. Net-zero energy buildings are one of the promising decarbonization attempts due to their potential of decreasing the use of energy and increasing the total share of renewable energy. To achieve a net-zero energy building, it is necessary to decrease the energy demand by applying efficiency enhancement measures and using renewable energy sources. Net-zero energy buildings can be classified into four models (Net-Zero Site Energy buildings, Net-Zero Emissions buildings, Net-Zero Source Energy buildings, and Net-Zero Cost Energy buildings). A variety of technical, financial, and environmental factors should be considered during the decision-making process of net-zero energy building development, justifying the use of multi-criteria decision analysis methods for the design of net-zero energy buildings. This paper also discussed the contributions of renewable energy generation (hydropower, wind energy, solar, heat pumps, and bioenergy) to the development of net-zero energy buildings and reviewed its role in tackling the decarbonization challenge. Cost-benefit analysis and life cycle assessment of building designs were reviewed to shape the priorities of future development. It is important to develop a universal decision instrument for optimum design and operation of net-zero energy buildings.
CORE arrow_drop_down CORE (RIOXX-UK Aggregator)Article . 2022License: CC BY NC NDData sources: CORE (RIOXX-UK Aggregator)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.enbuild.2021.111755&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 263 citations 263 popularity Top 1% influence Top 1% impulse Top 0.1% Powered by BIP!
more_vert CORE arrow_drop_down CORE (RIOXX-UK Aggregator)Article . 2022License: CC BY NC NDData sources: CORE (RIOXX-UK Aggregator)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.enbuild.2021.111755&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2020Publisher:MDPI AG Authors: Chen, Huangxin; Lin, Hang; Zou, Wenjie;doi: 10.3390/su12083284
Innovation ability has become one of the core elements in the pursuit of China’s green growth, and high-tech industries are playing a leading role in technological innovation in China. With the rapid development of China’s high-tech industries, their innovation efficiency has attracted widespread attention. This article aims to illustrate a shared inputs two-stage network Data Envelopment Analysis (DEA), to measure the innovation efficiency of high-tech industries in China’s 29 provinces from 1999 to 2018. The results indicate that there are obvious differences in the innovation efficiency of the provinces. The technology development efficiency, the technical transformation efficiency, and the overall innovation efficiency of the developed east coast provinces are generally higher than those of the backward central and western provinces. This article further applies the spatial econometrics model to analyze the factors influencing the innovation efficiency of high-tech industries. We have found that government support, R&D input intensity, industries aggregation, economic extroversion, and the level of development of the modern service industries cause varying degrees of impact on innovation efficiency.
Sustainability arrow_drop_down SustainabilityOther literature type . 2020License: CC BYFull-Text: http://www.mdpi.com/2071-1050/12/8/3284/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su12083284&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 65 citations 65 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Sustainability arrow_drop_down SustainabilityOther literature type . 2020License: CC BYFull-Text: http://www.mdpi.com/2071-1050/12/8/3284/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su12083284&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2021Publisher:MDPI AG doi: 10.3390/su13105753
This study uses the structured–pragmatics–situational case study approach to explore the intrinsic mechanism of enterprise digital enablement using affordance theory and how traditional enterprises enable customers to participate in value co-creation through information technology, then realize business model innovation and maintain continuous consumption. The study revealed the following: (1) Product affordance drives customers’ original willingness to engage in value co-creation in four dimensions: economy, reliability, uniqueness, and selectivity; (2) The visibility, convenience, association, and persistence of the platform affordance enhance users’ abilities to engage in value co-creation; (3) The interaction of affordance, structural enablement, and digital enablement drives the interaction of willingness and capability to engage in value co-creation; and (4) User participation behaviors in value co-creation can be divided into three dimensions (informational, actionable, and attitudinal participation)and four stages. The findings explain how traditional enterprises use IT enablement to promote business model innovation of customer participation in value co-creation and enrich the theories of digital enablement. The conclusions reveal the managerial implications of the ways, paths, and mechanism of business model innovation by IT enabling customers to participate in value co-creation.
Sustainability arrow_drop_down SustainabilityOther literature type . 2021License: CC BYFull-Text: http://www.mdpi.com/2071-1050/13/10/5753/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su13105753&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 9 citations 9 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Sustainability arrow_drop_down SustainabilityOther literature type . 2021License: CC BYFull-Text: http://www.mdpi.com/2071-1050/13/10/5753/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su13105753&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2023Publisher:MDPI AG Zhu, Yaozong; Wang, Yezhu; Zhou, Baohuan; Hu, Xiaoli; Xie, Yundong;doi: 10.3390/su15043484
Large amounts of CO2 from human socioeconomic activities threaten environmental sustainability. Moreover, uncontrolled resource use and lack of relevant technology exacerbate this issue. For this reason, carbon capture, utilization, and storage (CCUS) technology has gained worldwide attention. Many scholars have researched CCUS, but few have used CCUS patent bibliometric analysis from a unified perspective. This article aims to provide a conclusive analysis for CCUS researchers and policymakers, as well as summarize the innovation trends, technological distribution, and topic evolution. Based on 11,915 pieces of patent data from the Derwent Innovations Index, we used bibliometric analysis and data mining methods to conduct research on four dimensions: overall trend, geographical distribution, patentees, and patent content. The results of this article are as follows. CCUS has entered a rapid development stage since 2013. Patents are mainly distributed geographically in China, the US, and Japan, especially in heavy industries such as energy and electricity. Large enterprises hold patents with a relatively stable network of cooperators and attach great importance to international patent protection. A total of 12 topics were identified through clustering, and these topics gradually shifted from technicalities to commercialization, and from industrial production to all aspects of people’s daily lives.
Sustainability arrow_drop_down SustainabilityOther literature type . 2023License: CC BYFull-Text: http://www.mdpi.com/2071-1050/15/4/3484/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su15043484&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 8 citations 8 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Sustainability arrow_drop_down SustainabilityOther literature type . 2023License: CC BYFull-Text: http://www.mdpi.com/2071-1050/15/4/3484/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su15043484&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2015Publisher:Korean Society for Microbiology and Biotechnology Liming Luo; Fang Liang; Yahong Geng; Kui Du; Yeguang Li;Xiaobin Wen;
Xiaobin Wen
Xiaobin Wen in OpenAIREpmid: 26323272
To understand the effects of physicochemical factors on nitrite transformation by microalgae, a lipid-rich Chlorella with high nitrite tolerance was cultured with 8 mmol/l sodium nitrite as sole nitrogen source under different conditions. The results showed that nitrite transformation was mainly dependent on the metabolic activities of algal cells rather than oxidation of nitrite by dissolved oxygen. Light intensity, temperature, pH, NaHCO3 concentrations, and initial cell densities had significant effects on the rate of nitrite transformation. Single-factor experiments revealed that the optimum conditions for nitrite transformation were light intensity: 300 μmol/m(2); temperature: 30°C; pH: 7-8; NaHCO3 concentration: 2.0 g/l; and initial cell density: 0.15 g/l; and the highest nitrite transformation rate of 1.36 mmol/l/d was achieved. There was a positive correlation between nitrite transformation rate and the growth of Chlorella. The relationship between nitrite transformation rate (mg/l/d) and biomass productivity (g/l/d) could be described by the regression equation y = 61.3x (R(2) = 0.9665), meaning that 61.3 mg N element was assimilated by 1.0 g dry biomass on average, which indicated that the nitrite transformation is a process of consuming nitrite as nitrogen source by Chlorella. The results demonstrated that the Chlorella suspension was able to assimilate nitrite efficiently, which implied the feasibility of using flue gas for mass production of Chlorella without preliminary removal of NOX.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.4014/jmb.1505.05102&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 7 citations 7 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.4014/jmb.1505.05102&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2019 China (People's Republic of), Hong Kong, China (People's Republic of)Publisher:Elsevier BV Ren, S; Luo, F; Lin, L; Hsu, SC; Li, XI;handle: 10397/101128
Abstract With promising benefits such as traffic emission reduction, traffic congestion alleviation, and parking problem solving, Electric Vehicle (EV)-sharing systems have attracted large attentions in recent years. Different from other business modes, customers in sharing economy systems are usually price sensitive. Therefore, it is possible to shift the usage of shared EVs through a well-designed Dynamic Pricing Scheme (DPS), with the objective of maximizing the system operator's total profit. In this study, we propose a novel DPS for a large-scale EV-sharing network to address the EV unbalancing issue and satisfy the vehicle-grid-integration (VGI) service based on accurate station-level demand prediction. The proposed DPS is formulated as a complex optimization problem, which includes two Price Adjustment Level (PAL) decision variables for every origin-destination pair of stations. The two PALs are employed to affect the EV-sharing demand and travel time between each station pair, respectively. Physical and operational constraints from both EV demand and VGI service aspects are also included in the proposed model. Two case study are conducted to validate the effectiveness of the proposed method.
Hong Kong Polytechni... arrow_drop_down Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)Article . 2023License: CC BY NC NDFull-Text: http://hdl.handle.net/10397/101128Data sources: Bielefeld Academic Search Engine (BASE)International Journal of Production EconomicsArticle . 2019 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.ijpe.2019.06.020&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 67 citations 67 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Hong Kong Polytechni... arrow_drop_down Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)Article . 2023License: CC BY NC NDFull-Text: http://hdl.handle.net/10397/101128Data sources: Bielefeld Academic Search Engine (BASE)International Journal of Production EconomicsArticle . 2019 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.ijpe.2019.06.020&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2021Publisher:MDPI AG Authors:Rana Muhammad Adnan;
Rana Muhammad Adnan
Rana Muhammad Adnan in OpenAIREAbolfazl Jaafari;
Abolfazl Jaafari
Abolfazl Jaafari in OpenAIREAadhityaa Mohanavelu;
Aadhityaa Mohanavelu
Aadhityaa Mohanavelu in OpenAIREOzgur Kisi;
+1 AuthorsOzgur Kisi
Ozgur Kisi in OpenAIRERana Muhammad Adnan;
Rana Muhammad Adnan
Rana Muhammad Adnan in OpenAIREAbolfazl Jaafari;
Abolfazl Jaafari
Abolfazl Jaafari in OpenAIREAadhityaa Mohanavelu;
Aadhityaa Mohanavelu
Aadhityaa Mohanavelu in OpenAIREOzgur Kisi;
Ozgur Kisi
Ozgur Kisi in OpenAIREAhmed Elbeltagi;
Ahmed Elbeltagi
Ahmed Elbeltagi in OpenAIREdoi: 10.3390/su13115877
The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.
Sustainability arrow_drop_down SustainabilityOther literature type . 2021License: CC BYFull-Text: http://www.mdpi.com/2071-1050/13/11/5877/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su13115877&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 47 citations 47 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Sustainability arrow_drop_down SustainabilityOther literature type . 2021License: CC BYFull-Text: http://www.mdpi.com/2071-1050/13/11/5877/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su13115877&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2015 United KingdomPublisher:American Chemical Society (ACS) Authors:Zhu, Ying;
Zhu, Ying
Zhu, Ying in OpenAIRETao, Shu;
Price, Oliver R.;Tao, Shu
Tao, Shu in OpenAIREShen, Huizhong;
+2 AuthorsShen, Huizhong
Shen, Huizhong in OpenAIREZhu, Ying;
Zhu, Ying
Zhu, Ying in OpenAIRETao, Shu;
Price, Oliver R.;Tao, Shu
Tao, Shu in OpenAIREShen, Huizhong;
Shen, Huizhong
Shen, Huizhong in OpenAIREJones, Kevin C.;
Jones, Kevin C.
Jones, Kevin C. in OpenAIRESweetman, Andrew J.;
Sweetman, Andrew J.
Sweetman, Andrew J. in OpenAIREpmid: 25942589
SESAMe v3.0, a spatially explicit multimedia fate model with 50 × 50 km(2) resolution, has been developed for China to predict environmental concentrations of benzo[a]pyrene (BaP) using an atmospheric emission inventory for 2007. Model predictions are compared with environmental monitoring data obtained from an extensive review of the literature. The model performs well in predicting multimedia concentrations and distributions. Predicted concentrations are compared with guideline values; highest values with some exceedances occur mainly in the North China Plain, Mid Inner Mongolia, and parts of three northeast provinces, Xi'an, Shanghai, and south of Jiangsu province, East Sichuan Basin, middle of Guizhou and Guangzhou. Two potential future scenarios have been assessed using SESAMe v3.0 for 2030 as BaP emission is reduced by (1) technological improvement for coal consumption in energy production and industry sectors in Scenario 1 (Sc1) and (2) technological improvement and control of indoor biomass burning for cooking and indoor space heating and prohibition of open burning of biomass in 2030 in Scenario 2 (Sc2). Sc2 is more efficient in reducing the areas with exceedance of guideline values. Use of SESAMe v3.0 provides insights on future research needs and can inform decision making on options for source reduction.
Lancaster EPrints arrow_drop_down Lancaster University: Lancaster EprintsArticle . 2015License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1021/acs.est.5b00474&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 46 citations 46 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Lancaster EPrints arrow_drop_down Lancaster University: Lancaster EprintsArticle . 2015License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2017 France, France, France, United Kingdom, France, Netherlands, Russian Federation, France, France, France, France, France, FrancePublisher:Elsevier BV Publicly fundedFunded by:RSF | Large-scale digital soil ..., ARC | Dynamic soil landscape ca...RSF| Large-scale digital soil mapping based on remote sensing data ,ARC| Dynamic soil landscape carbon modellingAuthors:Minasny, Budiman;
Malone, Brendan P.;Minasny, Budiman
Minasny, Budiman in OpenAIREMcbratney, Alex B.;
Angers, Denis A.; +30 AuthorsMcbratney, Alex B.
Mcbratney, Alex B. in OpenAIREMinasny, Budiman;
Malone, Brendan P.;Minasny, Budiman
Minasny, Budiman in OpenAIREMcbratney, Alex B.;
Angers, Denis A.;Mcbratney, Alex B.
Mcbratney, Alex B. in OpenAIREArrouays, Dominique;
Chambers, Adam;Arrouays, Dominique
Arrouays, Dominique in OpenAIREChaplot, Vincent;
Chen, Zueng-Sang;Chaplot, Vincent
Chaplot, Vincent in OpenAIRECheng, Kun;
Cheng, Kun
Cheng, Kun in OpenAIREDas, Bhabani S.;
Das, Bhabani S.
Das, Bhabani S. in OpenAIREField, Damien J.;
Gimona, Alessandro;Field, Damien J.
Field, Damien J. in OpenAIREHedley, Carolyn B.;
Hong, Suk Young; Mandal, Biswapati;Hedley, Carolyn B.
Hedley, Carolyn B. in OpenAIREMarchant, Ben P.;
Marchant, Ben P.
Marchant, Ben P. in OpenAIREMartin, Manuel;
Mcconkey, Brian G.;Martin, Manuel
Martin, Manuel in OpenAIREMulder, Vera Leatitia;
Mulder, Vera Leatitia
Mulder, Vera Leatitia in OpenAIREO'Rourke, Sharon;
O'Rourke, Sharon
O'Rourke, Sharon in OpenAIRERicher-De-Forges, Anne C;
Odeh, Inakwu;Richer-De-Forges, Anne C
Richer-De-Forges, Anne C in OpenAIREPadarian, José;
Paustian, Keith; Pan, Genxing;Padarian, José
Padarian, José in OpenAIREPoggio, Laura;
Poggio, Laura
Poggio, Laura in OpenAIRESavin, Igor;
Stolbovoy, Vladimir;Savin, Igor
Savin, Igor in OpenAIREStockmann, Uta;
Stockmann, Uta
Stockmann, Uta in OpenAIRESulaeman, Yiyi;
Tsui, Chun-Chih;Sulaeman, Yiyi
Sulaeman, Yiyi in OpenAIREVågen, Tor-Gunnar;
Vågen, Tor-Gunnar
Vågen, Tor-Gunnar in OpenAIREvan Wesemael, Bas;
Winowiecki, Leigh;van Wesemael, Bas
van Wesemael, Bas in OpenAIREThe ‘4 per mille Soils for Food Security and Climate’ was launched at the COP21 with an aspiration to increase global soil organic matter stocks by 4 per 1000 (or 0.4 %) per year as a compensation for the global emissions of greenhouse gases by anthropogenic sources. This paper surveyed the soil organic carbon (SOC) stock estimates and sequestration potentials from 20 regions in the world (New Zealand, Chile, South Africa, Australia, Tanzania, Indonesia, Kenya, Nigeria, India, China Taiwan, South Korea, China Mainland, United States of America, France, Canada, Belgium, England & Wales, Ireland, Scotland, and Russia). We asked whether the 4 per mille initiative is feasible for the region. The outcomes highlight region specific efforts and scopes for soil carbon sequestration. Reported soil C sequestration rates globally show that under best management practices, 4 per mille or even higher sequestration rates can be accomplished. High C sequestration rates (up to 10 per mille) can be achieved for soils with low initial SOC stock (topsoil less than 30 t C ha− 1), and at the first twenty years after implementation of best management practices. In addition, areas which have reached equilibrium will not be able to further increase their sequestration. We found that most studies on SOC sequestration only consider topsoil (up to 0.3 m depth), as it is considered to be most affected by management techniques. The 4 per mille number was based on a blanket calculation of the whole global soil profile C stock, however the potential to increase SOC is mostly on managed agricultural lands. If we consider 4 per mille in the top 1m of global agricultural soils, SOC sequestration is between 2-3 Gt C year− 1, which effectively offset 20–35% of global anthropogenic greenhouse gas emissions. As a strategy for climate change mitigation, soil carbon sequestration buys time over the next ten to twenty years while other effective sequestration and low carbon technologies become viable. The challenge for cropping farmers is to find disruptive technologies that will further improve soil condition and deliver increased soil carbon. Progress in 4 per mille requires collaboration and communication between scientists, farmers, policy makers, and marketeers.
NERC Open Research A... arrow_drop_down Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2017License: CC BY NDFull-Text: https://hal.science/hal-01480573Data sources: Bielefeld Academic Search Engine (BASE)École Polytechnique, Université Paris-Saclay: HALArticle . 2017License: CC BY NDFull-Text: https://hal.science/hal-01480573Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2017License: CC BY NDFull-Text: https://hal.science/hal-01480573Data sources: Bielefeld Academic Search Engine (BASE)Natural Environment Research Council: NERC Open Research ArchiveArticle . 2017License: CC BY NC NDData sources: Bielefeld Academic Search Engine (BASE)INRIA a CCSD electronic archive serverArticle . 2017Data sources: INRIA a CCSD electronic archive serverWageningen Staff PublicationsArticle . 2017License: CC BY NC NDData sources: Wageningen Staff PublicationsInstitut National de la Recherche Agronomique: ProdINRAArticle . 2017License: CC BY NDData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 2K citations 1,540 popularity Top 0.01% influence Top 0.1% impulse Top 0.01% Powered by BIP!
more_vert NERC Open Research A... arrow_drop_down Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2017License: CC BY NDFull-Text: https://hal.science/hal-01480573Data sources: Bielefeld Academic Search Engine (BASE)École Polytechnique, Université Paris-Saclay: HALArticle . 2017License: CC BY NDFull-Text: https://hal.science/hal-01480573Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2017License: CC BY NDFull-Text: https://hal.science/hal-01480573Data sources: Bielefeld Academic Search Engine (BASE)Natural Environment Research Council: NERC Open Research ArchiveArticle . 2017License: CC BY NC NDData sources: Bielefeld Academic Search Engine (BASE)INRIA a CCSD electronic archive serverArticle . 2017Data sources: INRIA a CCSD electronic archive serverWageningen Staff PublicationsArticle . 2017License: CC BY NC NDData sources: Wageningen Staff PublicationsInstitut National de la Recherche Agronomique: ProdINRAArticle . 2017License: CC BY NDData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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