Multilayered Modeling of Particulate Matter Removal by a Growing Forest over Time, From Plant Surface Deposition to Washoff via Rainfall

2014 ◽  
Vol 48 (18) ◽  
pp. 10785-10794 ◽  
Author(s):  
Thomas Schaubroeck ◽  
Gaby Deckmyn ◽  
Johan Neirynck ◽  
Jeroen Staelens ◽  
Sandy Adriaenssens ◽  
...  
2017 ◽  
Vol 51 (11) ◽  
pp. 6610-6610 ◽  
Author(s):  
Thomas Schaubroeck ◽  
Gaby Deckmyn ◽  
Johan Neirynck ◽  
Jeroen Staelens ◽  
Sandy Adriaenssens ◽  
...  

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Romie Tignat-Perrier ◽  
Aurélien Dommergue ◽  
Alban Thollot ◽  
Christoph Keuschnig ◽  
Olivier Magand ◽  
...  

Abstract The atmosphere is an important route for transporting and disseminating microorganisms over short and long distances. Understanding how microorganisms are distributed in the atmosphere is critical due to their role in public health, meteorology and atmospheric chemistry. In order to determine the dominant processes that structure airborne microbial communities, we investigated the diversity and abundance of both bacteria and fungi from the PM10 particle size (particulate matter of 10 micrometers or less in diameter) as well as particulate matter chemistry and local meteorological characteristics over time at nine different meteorological stations around the world. The bacterial genera Bacillus and Sphingomonas as well as the fungal species Pseudotaeniolina globaosa and Cladophialophora proteae were the most abundant taxa of the dataset, although their relative abundances varied greatly based on sampling site. Bacterial and fungal concentration was the highest at the high-altitude and semi-arid plateau of Namco (China; 3.56 × 106 ± 3.01 × 106 cells/m3) and at the high-altitude and vegetated mountain peak Storm-Peak (Colorado, USA; 8.78 × 104 ± 6.49 × 104 cells/m3), respectively. Surrounding ecosystems, especially within a 50 km perimeter of our sampling stations, were the main contributors to the composition of airborne microbial communities. Temporal stability in the composition of airborne microbial communities was mainly explained by the diversity and evenness of the surrounding landscapes and the wind direction variability over time. Airborne microbial communities appear to be the result of large inputs from nearby sources with possible low and diluted inputs from distant sources.


2020 ◽  
Vol 8 (9) ◽  
pp. 1449
Author(s):  
Steven Gayder ◽  
Michael Parcey ◽  
Darlene Nesbitt ◽  
Alan J. Castle ◽  
Antonet M. Svircev

Bacteriophages are viruses capable of recognizing with high specificity, propagating inside of, and destroying their bacterial hosts. The phage lytic life cycle makes phages attractive as tools to selectively kill pathogenic bacteria with minimal impact on the surrounding microbiome. To effectively harness the potential of phages in therapy, it is critical to understand the phage–host dynamics and how these interactions can change in complex populations. Our model examined the interactions between the plant pathogen Erwinia amylovora, the antagonistic epiphyte Pantoea agglomerans, and the bacteriophages that infect and kill both species. P. agglomerans strains are used as a phage carrier; their role is to deliver and propagate the bacteriophages on the plant surface prior to the arrival of the pathogen. Using liquid cultures, the populations of the pathogen, carrier, and phages were tracked over time with quantitative real-time PCR. The jumbo Myoviridae phage ϕEa35-70 synergized with both the Myoviridae ϕEa21-4 and Podoviridae ϕEa46-1-A1 and was most effective in combination at reducing E. amylovora growth over 24 h. Phage ϕEa35-70, however, also reduced the growth of P. agglomerans. Phage cocktails of ϕEa21-4, ϕEa46-1-A1, and ϕEa35-70 at multiplicities of infections (MOIs) of 10, 1, and 0.01, respectively, no longer inhibited growth of P. agglomerans. When this cocktail was grown with P. agglomerans for 8 h prior to pathogen introduction, pathogen growth was reduced by over four log units over 24 h. These findings present a novel approach to study complex phage–host dynamics that can be exploited to create more effective phage-based therapies.


Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 238 ◽  
Author(s):  
Minjoong J. Kim

This study focuses on the changes over time in the relationship between surface temperature and particulate matter (PM) concentration over Seoul using long-term observational data. Correlation coefficients between the daily mean PM10 concentration and surface temperature were calculated to investigate the relationship between the two. The PM10 and temperature displayed a strong positive correlation, suggesting the increase in PM was driven by large-scale synoptic patterns accompanying such high temperatures. It was found that the correlation coefficient in 2002–2009 was significantly higher than that of 2010–2017, indicating that the relationship between PM10 concentration and temperature has weakened over time in recent decades. Correlation coefficients between daily averaged temperature and the PM10 of each year were calculated to account for the decreased correlation in the most recent decade. We found that the correlation coefficients between surface temperature and PM of each year exhibited a clear negative correlation with the longitudinal position of the Siberian High, suggesting that the position of the Siberian High might affect the strength of the relationship between PM concentration and temperature over Seoul. We also found that the eastward shift of the Siberian High reduces the standard deviation of pressure over Seoul, indicating reduction of synoptic perturbation. These results imply that the eastward shift of the Siberian High in recent decades might weaken the relationship between the PM and surface temperature over Seoul. This study suggests that the relationship between PM and meteorological variables is changing over time through changes in large climate variability.


2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Anders C Erickson ◽  
Michael Brauer ◽  
Tanya Christidis ◽  
Daniel Crouse ◽  
Scott Weichenthal ◽  
...  

Author(s):  
María Victoria Toro

One of the main concerns when it comes to mitigating the effects of the concentration of the particulate matter PMx in an area of study is the fact to determine its behavior over time, overcoming both physical and mathematical limitations in terms of a phenomenon of dispersion. Therefore, this chapter develops and analyzes a model based on the principles of evolutionary computation (EC) in order to determine the space-time behavior of the concentration of the particulate matter PMx in a study area. The proposed model has three submodels within an integrated solution, which constitute the individual to evolve. The transformation of the possible solutions or generational population is made by using an asynchronous evolutionary model, due to genetic dependency between substructures. The proposed model was validated for configurations of n sources of emissions and m monitoring stations that measure the quality of the air in a study area.


Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6374
Author(s):  
Sung Su Jo ◽  
Sang Ho Lee ◽  
Yountaik Leem

This study analyzed the changes in particulate matter concentrations according to land-use over time and the spatial characteristics of the distribution of particulate matter concentrations using big data of particulate matter in Daejeon, Korea, measured by Private Air Quality Monitoring Smart Sensors (PAQMSSs). Land-uses were classified into residential, commercial, industrial, and green groups according to the primary land-use around the 650-m sensor radius. Data on particulate matter with an aerodynamic diameter <10 µm (PM10) and <2.5 µm (PM2.5) were captured by PAQMSSs from September‒October (i.e., fall) in 2019. Differences and variation characteristics of particulate matter concentrations between time periods and land-uses were analyzed and spatial mobility characteristics of the particulate matter concentrations over time were analyzed. The results indicate that the particulate matter concentrations in Daejeon decreased in the order of industrial, housing, commercial and green groups overall; however, the concentrations of the commercial group were higher than those of the residential group during 21:00–23:00, which reflected the vital nighttime lifestyle in the commercial group in Korea. Second, the green group showed the lowest particulate matter concentration and the industrial group showed the highest concentration. Third, the highest particulate matter concentrations were in urban areas where commercial and business functions were centered and in the vicinity of industrial complexes. Finally, over time, the PM10 concentrations were clearly high at noon and low at night, whereas the PM2.5 concentrations were similar at certain areas.


2020 ◽  
Vol 268 ◽  
pp. 122134 ◽  
Author(s):  
Cristina García-Florentino ◽  
Maite Maguregui ◽  
Jose Antonio Carrero ◽  
Héctor Morillas ◽  
Gorka Arana ◽  
...  

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