scholarly journals Weakness of Correlation Effect Manifestation in BaNi2As2: An ARPES and LDA + DMFT Study

2021 ◽  
Author(s):  
Nikita S. Pavlov ◽  
Timur K. Kim ◽  
Alexander Yaresko ◽  
Ki-Young Choi ◽  
Igor A. Nekrasov ◽  
...  
Keyword(s):  
Correlation Effect

scholarly journals Assessing the Environmental Impact and Cost of the Tourism-Induced CO2, NOx, SOx Emission in China

2021 ◽  
Vol 13 (2) ◽  
pp. 604
Author(s):  
Yalan Shi ◽  
Miaojing Yu
Keyword(s):  
Environmental Impact ◽  
Environmental Impacts ◽  
Full Range ◽  
Correlation Effect ◽  
Tourism Industry ◽  
Pollutant Emissions ◽  
Travel Agency ◽  
Sustainable Mobility ◽  
Industrial Sectors ◽  
Direct Emission

Tourism, as one economic activity, results in a full range of environmental impacts globally as well as in China. However, the evaluation of environmental impacts is insufficient because of the strong correlation effect between tourism and other industries. This study attempted to assess the environmental impact and cost of the tourism-induced pollutant emissions (in a broad sense) at the national scale through constructing the environmental-economic input-output model. Our results suggested that the China’s total emission of CO2, NOx, SOx related to tourism industry increased from 42 × 106 t, 162 kt, 345 kt in 1995 to 157 × 106 t, 527 kt, 854 kt in 2009. The indirect CO2, NOx, and SOx emissions of tourism and related industries were nearly 6.8–11 times of their direct emission in travel agency. Most of these indirect emissions (73% of CO2 in 2009, 54% of NOx in 1995, 62% of SOx in 2009) are derived from the energy plants and industrial sectors. The sustainable tourism should largely depend on the realization of sustainable mobility and transportation, through the low-emission behavior and energy-saving technology. The emission reduction cost of tourism industry in China was 30,170 and 172,812 million CNY in 1995 and 2009, accounting for nearly 14% of the total tourism revenue.

scholarly journals Overcapacity Risk of China’s Coal Power Industry: A Comprehensive Assessment and Driving Factors

2021 ◽  
Vol 13 (3) ◽  
pp. 1426
Author(s):  
Delu Wang ◽  
Xun Xue ◽  
Yadong Wang
Keyword(s):  
Evaluation Model ◽  
Supply And Demand ◽  
Correlation Effect ◽  
Power Industry ◽  
Environmental Benefits ◽  
Risk Level ◽  
Correlation Based Feature Selection ◽  
Coal Power ◽  
And Control ◽  
The Impact

The comprehensive and accurate monitoring of coal power overcapacity is the key link and an important foundation for the prevention and control of overcapacity. The previous research fails to fully consider the impact of the industry correlation effect; making it difficult to reflect the state of overcapacity accurately. In this paper; we comprehensively consider the fundamentals; supply; demand; economic and environmental performance of the coal power industry and its upstream; downstream; competitive; and complementary industries to construct an index system for assessing coal power overcapacity risk. Besides; a new evaluation model based on a correlation-based feature selection-association rules-data envelopment analysis (CFS-ARs-DEA) integrated algorithm is proposed by using a data-driven model. The results show that from 2008 to 2017; the risk of coal power overcapacity in China presented a cyclical feature of “decline-rise-decline”, and the risk level has remained high in recent years. In addition to the impact of supply and demand; the environmental benefits and fundamentals of related industries also have a significant impact on coal power overcapacity. Therefore; it is necessary to monitor and govern coal power overcapacity from the overall perspective of the industrial network, and coordinate the advancement of environmental protection and overcapacity control.

scholarly journals Weeds as Pathogen Hosts and Disease Risk for Crops in the Wake of a Reduced Use of Herbicides: Evidence from Yam (Dioscorea alata) Fields and Colletotrichum Pathogens in the Tropics

2021 ◽  
Vol 7 (4) ◽  
pp. 283
Author(s):  
Pauline Dentika ◽  
Harry Ozier-Lafontaine ◽  
Laurent Penet
Keyword(s):  
Weed Management ◽  
Natural Experiment ◽  
Disease Risk ◽  
Cropping Systems ◽  
Correlation Effect ◽  
Local Scale ◽  
Potential Control ◽  
Weed Host ◽  
Species Characteristics ◽  
The Tropics

The transition toward sustainable agriculture requires rethinking cropping systems in the light of less intensive and chemically reliant practices. Weed management is one of the target practices to evolve cropping systems with decreased impact on the environment. While softened management will lead to increased weeds/crops coexistence, it is of importance to assess the relative benefits and drawbacks of new practices. Among the potential drawbacks of weeds/crops coexistence, disease risk may increase if weeds are hosting pathogens. In this study, we assessed the potential of weeds for hosting pathogenic generalist fungi known to translate into disease in crops. We first describe prevalence in fields after harvest and relate prevalence to species characteristics and communities. Then, we directly test the idea that weeds serve as inoculums sources during cropping with a natural experiment. This study highlights variation in host skill among feral weeds for Colletotrichum species, including potential congeneric sub-specialization on different weeds within communities. Last, prevalence within fields was more correlated to focal crop inoculation rates compared to local weed load, but there was a significant correlation effect with prevalence on weeds in the vicinity of fields, suggesting that weeds are mediating disease levels at the local scale, too. Results pointed to the importance of weed host skill in disease risk yet open the door to the potential control of pathogens via targeted weed management.

Ab initio calculation of [OH−;e+] system with consideration of electron correlation effect

1994 ◽  
Vol 101 (7) ◽  
pp. 5925-5928 ◽  
Author(s):  
Masanori Tachikawa ◽  
Hiroshi Sainowo ◽  
Kaoru Iguchi ◽  
Kazunari Suzuki
Keyword(s):  
Ab Initio ◽  
Electron Correlation ◽  
Ab Initio Calculation ◽  
Correlation Effect ◽  
Electron Correlation Effect
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