Keyword search (4,164 papers available)

"uncertainty" Keyword-tagged Publications:

Title Authors PubMed ID
1 Adaptive sliding mode fault-tolerant control of an over-actuated hybrid VTOL fixed-wing UAV under transition flight Wang B; Zhao H; Hu X; Shen Y; Li N; 41475926
ENCS
2 Intolerance of uncertainty, psychological symptoms, and pain in long-term childhood cancer survivors: a report from the Childhood Cancer Survivor Study Alberts NM; Stratton KL; Leisenring WM; Pizzo A; Lamoureux É; Alschuler K; Flynn J; Krull KR; Jibb LA; Nathan PC; Olgin JE; Stinson JN; Armstrong GT; 40699439
PSYCHOLOGY
3 Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks Adcock B; Brugiapaglia S; Dexter N; Moraga S; 39454372
MATHSTATS
4 Exploring the effects of anthropogenic disturbance on predator inspection activity in Trinidadian guppies Brusseau AJP; Feyten LEA; Crane AL; Brown GE; 38476138
BIOLOGY
5 Development and performance assessment of a new opensource Bayesian inference R platform for building energy model calibration Hou D; Zhan D; Wang L; Hassan IG; Sezer N; 37936825
ENCS
6 How uncertainty affects information search among consumers: a curvilinear perspective He S; Rucker DD; 36471868
JMSB
7 UncertaintyFuseNet: Robust uncertainty-aware hierarchical feature fusion model with Ensemble Monte Carlo Dropout for COVID-19 detection Abdar M; Salari S; Qahremani S; Lam HK; Karray F; Hussain S; Khosravi A; Acharya UR; Makarenkov V; Nahavandi S; 36217534
ENCS
8 Development of a DREAM-based inverse model for multi-point source identification in river pollution incidents: Model testing and uncertainty analysis Zhu Y; Chen Z; 36191500
ENCS
9 Viral Anxiety Mediates the Influence of Intolerance of Uncertainty on Adherence to Physical Distancing Among Healthcare Workers in COVID-19 Pandemic Chung S; Lee T; Hong Y; Ahmed O; Silva WAD; Gouin JP; 35733798
PSYCHOLOGY
10 Decision-first modeling should guide decision making for emerging risks Morgan K; Collier ZA; Gilmore E; Schmitt K; 35104915
ENCS
11 Towards a better understanding of deep convolutional neural network processes for recognizing organic chemicals of environmental concern Sun X; Zhang X; Wang L; Li Y; Muir DCG; Zeng EY; 34388923
CHEMBIOCHEM
12 Assessing the regional biogenic methanol emission from spring wheat during the growing season: A Canadian case study Cai M; An C; Guy C; Lu C; Mafakheri F; 34182392
ENCS
13 A robust optimization model for tactical capacity planning in an outpatient setting Aslani N; Kuzgunkaya O; Vidyarthi N; Terekhov D; 33215335
ENCS
14 Qualitative threshold method validation and uncertainty evaluation: A theoretical framework and application to a 40 analytes liquid chromatography-tandem mass spectrometry method Camirand Lemyre F; Desharnais B; Laquerre J; Morel MA; Côté C; Mireault P; Skinner CD; 32476284
CHEMBIOCHEM
15 Quantifying construction waste reduction through the application of prefabrication: a case study in Anhui, China. Hao J, Chen Z, Zhang Z, Loehlein G 32358748
ENCS
16 An ecological framework of neophobia: from cells to organisms to populations. Crane AL, Brown GE, Chivers DP, Ferrari MCO 31599483
BIOLOGY
17 Worldwide contamination of food-crops with mycotoxins: Validity of the widely cited 'FAO estimate' of 25. Eskola M, Kos G, Elliott CT, Hajšlová J, Mayar S, Krska R 31478403
CHEMBIOCHEM
18 Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction. Vorwerk J, Aydin Ü, Wolters CH, Butson CR 31231178
PERFORM

 

Title:Assessing the regional biogenic methanol emission from spring wheat during the growing season: A Canadian case study
Authors:Cai MAn CGuy CLu CMafakheri F
Link:https://pubmed.ncbi.nlm.nih.gov/34182392/
DOI:10.1016/j.envpol.2021.117602
Publication:Environmental pollution (Barking, Essex : 1987)
Keywords:Air pollutantsBiogenic methanolClimate changeEmission assessmentSpring wheatUncertainty and sensitivity
PMID:34182392 Category: Date Added:2021-06-29
Dept Affiliation: ENCS
1 Department of Building, Civil and Environmental Engineering, Faculty of Engineering and Computer Science, Concordia University, Montreal, QC H3G 1M8, Canada.
2 Department of Building, Civil and Environmental Engineering, Faculty of Engineering and Computer Science, Concordia University, Montreal, QC H3G 1M8, Canada. Electronic address: chunjiang.an@concordia.ca.
3 Department of Chemical and Materials Engineering, Concordia University, Montreal, QC H3G 1M8, Canada.
4 Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, SK S4S 0A2, Canada.
5 Concordia Institute for Information Systems Engineering, Concordia University, Montreal, H3G 1M8, Canada.

Description:

As a volatile organic compound existing in the atmosphere, methanol plays a key role in atmospheric chemistry due to its comparatively high abundance and long lifetime. Croplands are a significant source of biogenic methanol, but there is a lack of systematic assessment for the production and emission of methanol from crops in various phases. In this study, methanol emissions from spring wheat during the growing period were estimated using a developed emission model. The temporal and spatial variations of methanol emissions of spring wheat in a Canadian province were investigated. The averaged methanol emission of spring wheat is found to be 37.94 ± 7.5 µg·m-2·h-1, increasing from north to south and exhibiting phenological peak to valley characteristics. Moreover, cold crop districts are projected to be with higher increase in air temperature and consequent methanol emissions during 2020-2099. Furthermore, the seasonality of methanol emissions is found to be positively correlated to concentrations of CO, filterable particulate matter, and PM10 but negatively related to NO2 and O3. The uncertainty and sensitivity analysis results suggest that methanol emissions show a Gamma probabilistic distribution, and growth length, air temperature, solar radiation and leafage are the most important influencing variables. In most cases, methanol emissions increase with air temperature in the range of 3-35 °C while the excessive temperature may result in decreased methanol emissions because of inactivated enzyme activity or increased instant methanol emissions due to heat injury. Notably, induced emission might be the major source of biogenic methanol of mature leaves. The results of this study can be used to develop appropriate strategies for regional emission management of cropping systems.





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