scholarly journals Chemical composition of atmospheric aerosols between Moscow and Vladivostok

2007 ◽  
Vol 7 (3) ◽  
pp. 7473-7508 ◽  
Author(s):  
S. Kuokka ◽  
K. Teinilä ◽  
K. Saarnio ◽  
M. Aurela ◽  
M. Sillanpää ◽  
...  

Abstract. The TROICA-9 expedition (Trans-Siberian Observations Into the Chemistry of the Atmosphere) was carried out at the Trans-Siberian railway between Moscow and Vladivostok in October 2005. Measurements of aerosol physical and chemical properties were made from an observatory carriage connected to a passenger train. Black carbon (BC) concentrations in fine particles (PM2.5, aerodynamic diameter <2.5 μm) were measured with an aethalometer using a five-minute time resolution. Concentrations of inorganic ions and some organic compounds (Cl−, NO3−, SO42−, Na+, NH4+, K+, Ca2+, Mg2+, oxalate and methane sulphonate) were measured continuously by using an on-line system with a 15-min time resolution. In addition, particle volume size distributions were determined for particles in the diameter range 3–850 nm using a 10-min. time resolution. The continuous measurements were completed with 24-h. PM2.5 filter samples which were stored in a refrigerator and later analyzed in chemical laboratory. The analyses included mass concentrations of PM2.5, ions, monosaccharide anhydrides (levoglucosan, galactosan and mannosan) and trace elements (Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sb, V and Zn). The mass concentrations of PM2.5 varied in the range of 4.3–34.8 μg m−3 with an average of 21.6 μg m−3. Fine particle mass consisted mainly of BC (average 27.6%), SO42− (13.0%), NH4+ (4.1%), and NO3− (1.4%). One of the major constituents was obviously also organic carbon which was not determined. The contribution of BC was high compared with other studies made in Europe and Asia. High concentrations of ions, BC and particle volume were observed between Moscow and roughly 4000 km east of it, as well as close to Vladivostok, primarily due to local anthropogenic sources. In the natural background area between 4000 and 7200 km distance from Moscow, observed concentrations were low, even though there were local particle sources, such as forest fires, that increased occasionally concentrations. The measurements indicated that during forest fire episodes, most of the aerosol mass consisted of organic particulate matter. Concentrations of biomass burning tracers levoglucosan, oxalate and potassium were elevated close to the forest fire areas observed by the MODIS satellite. The polluted air masses from Asia seem to have significant influences on the concentration levels of fine particles over south-eastern Russia.

2007 ◽  
Vol 7 (18) ◽  
pp. 4793-4805 ◽  
Author(s):  
S. Kuokka ◽  
K. Teinilä ◽  
K. Saarnio ◽  
M. Aurela ◽  
M. Sillanpää ◽  
...  

Abstract. The TROICA-9 expedition (Trans-Siberian Observations Into the Chemistry of the Atmosphere) was carried out at the Trans-Siberian railway between Moscow and Vladivostok in October 2005. Measurements of aerosol physical and chemical properties were made from an observatory carriage connected to a passenger train. Black carbon (BC) concentrations in fine particles (PM2.5, aerodynamic diameter <2.5 μm) were measured with an aethalometer using a five-minute time resolution. Concentrations of inorganic ions and some organic compounds (Cl−, NO3−, SO42−, Na+, NH4+, K+, Ca2+, Mg2+, oxalate and methane sulphonate) were measured continuously by using an on-line system with a 15-min time resolution. In addition, particle volume size distributions were determined for particles in the diameter range 3–850 nm using a 10-min time resolution. The continuous measurements were completed with 24-h PM2.5 filter samples stored in a refrigerator and analyzed later in a chemical laboratory. The analyses included the mass concentrations of PM2.5, ions, monosaccharide anhydrides (levoglucosan, galactosan and mannosan) and trace elements (Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sb, V and Zn). The mass concentrations of PM2.5 varied in the range of 4.3–34.8 μg m−3 with an average of 21.6 μg m−3. Fine particle mass consisted mainly of BC (average 27.6%), SO42− (13.0%), NH4+ (4.1%) and NO3− (1.4%). One of the major constituents was obviously organic carbon which was not determined. The contribution of BC was high compared with other studies made in Europe and Asia. High concentrations of ions, BC and particle volume were observed between Moscow and roughly 4000 km east of it, as well as close to Vladivostok, primarily due to local anthropogenic sources. In the natural background area between 4000 and 7200 km away from Moscow, observed concentrations were low, even though local particle sources, such as forest fires, occasionally increased concentrations. During the measured forest fire episodes, most of the aerosol mass appeared to consist of organic particulate matter. Concentrations of the biomass burning tracers levoglucosan, oxalate and potassium were elevated close to the forest fire areas observed by the MODIS satellite. The polluted air masses from Asia seem to have significant influences on the concentration levels of fine particles over south-eastern Russia.


2017 ◽  
Author(s):  
Cynthia Whaley ◽  
Paul A. Makar ◽  
Mark W. Shephard ◽  
Leiming Zhang ◽  
Junhua Zhang ◽  
...  

Abstract. Atmospheric ammonia (NH3) is a short-lived pollutant that plays an important role in aerosol chemistry and nitrogen deposition. Dominant NH3 emissions are from agriculture and forest fires, both of which are increasing globally. The Alberta Oil Sands region has relatively low ambient NH3 concentrations because of its remote location in northern Canada; however, a previous attempt to model NH3 in the region showed a substantial negative bias compared to satellite column and aircraft observations. Known missing sources of NH3 in the model were re-emission of NH3 from plants and soils (bidirectional flux), and forest fire emissions, but the relative impact of these sources on NH3 concentrations and column totals was unknown. Here we have used a research version of the high-resolution air quality forecasting model, GEM-MACH, to quantify the relative impacts of natural (bidirectional flux of NH3 and forest fire emissions) and anthropogenic (Oil Sands operations, combustion of fossil fuels, and agriculture) sources on ammonia concentrations, both at the surface and aloft, with a focus on the Athabasca Oil Sands region, during a measurement-intensive campaign in the summer of 2013. The addition of fires and bidirectional flux has improved the model bias, slope and correlation coefficients relative to ground, aircraft, and satellite measurements significantly. By running the GEM-MACH model in three configurations and calculating their differences, we find that averaged over Alberta and Saskatchewan during this time period; an average of 23.1 % of surface NH3 came from direct anthropogenic sources, 56.6 % (or 1.24 ppbv) from bidirectional flux (reemission from plants and soils), and 20.3 % (or 0.42 ppbv) from forest fires. In the NH3 total column, an average of 19.5 % came from direct anthropogenic sources, 50.0 % from bidirectional flux, and 30.5 % from forest fires. The addition of bidirectional flux and fire emissions caused the overall average net flux of NH3 across the domain to be positive (upward). It also increased the NH+4 wet deposition by nearly a factor of three during the period simulated. Note that forest fires are very episodic and their contributions will vary significantly for different time periods and regions.


2018 ◽  
Vol 18 (3) ◽  
pp. 2011-2034 ◽  
Author(s):  
Cynthia H. Whaley ◽  
Paul A. Makar ◽  
Mark W. Shephard ◽  
Leiming Zhang ◽  
Junhua Zhang ◽  
...  

Abstract. Atmospheric ammonia (NH3) is a short-lived pollutant that plays an important role in aerosol chemistry and nitrogen deposition. Dominant NH3 emissions are from agriculture and forest fires, both of which are increasing globally. Even remote regions with relatively low ambient NH3 concentrations, such as northern Alberta and Saskatchewan in northern Canada, may be of interest because of industrial oil sands emissions and a sensitive ecological system. A previous attempt to model NH3 in the region showed a substantial negative bias compared to satellite and aircraft observations. Known missing sources of NH3 in the model were re-emission of NH3 from plants and soils (bidirectional flux) and forest fire emissions, but the relative impact of these sources on NH3 concentrations was unknown. Here we have used a research version of the high-resolution air quality forecasting model, GEM-MACH, to quantify the relative impacts of semi-natural (bidirectional flux of NH3 and forest fire emissions) and direct anthropogenic (oil sand operations, combustion of fossil fuels, and agriculture) sources on ammonia volume mixing ratios, both at the surface and aloft, with a focus on the Athabasca Oil Sands region during a measurement-intensive campaign in the summer of 2013. The addition of fires and bidirectional flux to GEM-MACH has improved the model bias, slope, and correlation coefficients relative to ground, aircraft, and satellite NH3 measurements significantly. By running the GEM-MACH-Bidi model in three configurations and calculating their differences, we find that averaged over Alberta and Saskatchewan during this time period an average of 23.1 % of surface NH3 came from direct anthropogenic sources, 56.6 % (or 1.24 ppbv) from bidirectional flux (re-emission from plants and soils), and 20.3 % (or 0.42 ppbv) from forest fires. In the NH3 total column, an average of 19.5 % came from direct anthropogenic sources, 50.0 % from bidirectional flux, and 30.5 % from forest fires. The addition of bidirectional flux and fire emissions caused the overall average net deposition of NHx across the domain to be increased by 24.5 %. Note that forest fires are very episodic and their contributions will vary significantly for different time periods and regions. This study is the first use of the bidirectional flux scheme in GEM-MACH, which could be generalized for other volatile or semi-volatile species. It is also the first time CrIS (Cross-track Infrared Sounder) satellite observations of NH3 have been used for model evaluation, and the first use of fire emissions in GEM-MACH at 2.5 km resolution.


Author(s):  
Ming-Hui Yao ◽  
David J. Smith

The chemical properties of catalysts often depend on the size, shape and structure of the supported metal particles. To characterize these morphological features and relate them to catalysis is one of the main objectives for HREM study of catalysts. However, in plan view imaging, details of the shape and structure of ultra-fine supported particles (<2nm) are often obscured by the overlapping contrast from the support, and supported sub-nanometer particles are sometimes even invisible. Image simulations may help in the interpretation at HREM images of supported particles in particular to extract useful information about the size, shape and structure of the particles. It should also be a useful tool for evaluating the imaging conditions in terms of visibility of supported particles. P. L. Gai et al have studied contrast from metal particles supported on amorphous material using multislice simulations. In order to better understand the influence of a crystalline support on the visibility and apparent morphological features of supported fine particles, we have calculated images of Pt and Re particles supported on TiO2(rutile) in both plan view and profile view.


Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 768
Author(s):  
Jin Pan ◽  
Xiaoming Ou ◽  
Liang Xu

Forest fires are serious disasters that affect countries all over the world. With the progress of image processing, numerous image-based surveillance systems for fires have been installed in forests. The rapid and accurate detection and grading of fire smoke can provide useful information, which helps humans to quickly control and reduce forest losses. Currently, convolutional neural networks (CNN) have yielded excellent performance in image recognition. Previous studies mostly paid attention to CNN-based image classification for fire detection. However, the research of CNN-based region detection and grading of fire is extremely scarce due to a challenging task which locates and segments fire regions using image-level annotations instead of inaccessible pixel-level labels. This paper presents a novel collaborative region detection and grading framework for fire smoke using a weakly supervised fine segmentation and a lightweight Faster R-CNN. The multi-task framework can simultaneously implement the early-stage alarm, region detection, classification, and grading of fire smoke. To provide an accurate segmentation on image-level, we propose the weakly supervised fine segmentation method, which consists of a segmentation network and a decision network. We aggregate image-level information, instead of expensive pixel-level labels, from all training images into the segmentation network, which simultaneously locates and segments fire smoke regions. To train the segmentation network using only image-level annotations, we propose a two-stage weakly supervised learning strategy, in which a novel weakly supervised loss is proposed to roughly detect the region of fire smoke, and a new region-refining segmentation algorithm is further used to accurately identify this region. The decision network incorporating a residual spatial attention module is utilized to predict the category of forest fire smoke. To reduce the complexity of the Faster R-CNN, we first introduced a knowledge distillation technique to compress the structure of this model. To grade forest fire smoke, we used a 3-input/1-output fuzzy system to evaluate the severity level. We evaluated the proposed approach using a developed fire smoke dataset, which included five different scenes varying by the fire smoke level. The proposed method exhibited competitive performance compared to state-of-the-art methods.


2021 ◽  
Vol 13 (1) ◽  
pp. 432
Author(s):  
Aru Han ◽  
Song Qing ◽  
Yongbin Bao ◽  
Li Na ◽  
Yuhai Bao ◽  
...  

An important component in improving the quality of forests is to study the interference intensity of forest fires, in order to describe the intensity of the forest fire and the vegetation recovery, and to improve the monitoring ability of the dynamic change of the forest. Using a forest fire event in Bilahe, Inner Monglia in 2017 as a case study, this study extracted the burned area based on the BAIS2 index of Sentinel-2 data for 2016–2018. The leaf area index (LAI) and fractional vegetation cover (FVC), which are more suitable for monitoring vegetation dynamic changes of a burned area, were calculated by comparing the biophysical and spectral indices. The results showed that patterns of change of LAI and FVC of various land cover types were similar post-fire. The LAI and FVC of forest and grassland were high during the pre-fire and post-fire years. During the fire year, from the fire month (May) through the next 4 months (September), the order of areas of different fire severity in terms of values of LAI and FVC was: low > moderate > high severity. During the post fire year, LAI and FVC increased rapidly in areas of different fire severity, and the ranking of areas of different fire severity in terms of values LAI and FVC was consistent with the trend observed during the pre-fire year. The results of this study can improve the understanding of the mechanisms involved in post-fire vegetation change. By using quantitative inversion, the health trajectory of the ecosystem can be rapidly determined, and therefore this method can play an irreplaceable role in the realization of sustainable development in the study area. Therefore, it is of great scientific significance to quantitatively retrieve vegetation variables by remote sensing.


2021 ◽  
Vol 13 (14) ◽  
pp. 7773
Author(s):  
San Wang ◽  
Hongli Li ◽  
Shukui Niu

The Sichuan province is a key area for forest and grassland fire prevention in China. Forest resources contribute significantly not only to the biological gene pool in the mid latitudes but also in reducing the concentration of greenhouse gases and slowing down global warming. To study and forecast forest fire change trends in a grade I forest fire danger zone in the Sichuan province under climate change, the dynamic impacts of meteorological factors on forest fires in different climatic regions were explored and a model between them was established by using an integral regression in this study. The results showed that the dominant factor behind the area burned was wind speed in three climatic regions, particularly in Ganzi and A’ba with plateau climates. In Ganzi and A’ba, precipitation was mainly responsible for controlling the number of forest fires while it was mainly affected by temperature in Panzhihua and Liangshan with semi-humid subtropical mountain climates. Moreover, the synergistic effect of temperature, precipitation and wind speed was responsible in basin mid-subtropical humid climates with Chengdu as the center and the influence of temperature was slightly higher. The differential forest fire response to meteorological factors was observed in different climatic regions but there was some regularity. The influence of monthly precipitation in the autumn on the area burned in each climatic region was more significant than in other seasons, which verified the hypothesis of a precipitation lag effect. Climate warming and the combined impact of warming effects may lead to more frequent and severe fires.


2021 ◽  
pp. 101053952110317
Author(s):  
Bin Jalaludin ◽  
Frances L. Garden ◽  
Agata Chrzanowska ◽  
Budi Haryanto ◽  
Christine T. Cowie ◽  
...  

Smoke from forest fires can reach hazardous levels for extended periods of time. We aimed to determine if there is an association between particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5) and living in a forest fire–prone province and cognitive function. We used data from the Indonesian Family and Life Survey. Cognitive function was assessed by the Ravens Colored Progressive Matrices (RCPM). We used regression models to estimate associations between PM2.5 and living in a forest fire–prone province and cognitive function. In multivariable models, we found very small positive relationships between PM2.5 levels and RCPM scores (PM2.5 level at year of survey: β = 0.1%; 95% confidence interval [CI] = 0.01% to 0.19%). There were no differences in RCPM scores for children living in forest fire–prone provinces compared with children living in non-forest fire–prone provinces (mean difference = −1.16%, 95% CI = −2.53% to 0.21%). RCPM scores were lower for children who had lived in a forest fire–prone province all their lives compared with children who lived in a non-forest fire–prone province all their life (β = −1.50%; 95% CI = −2.94% to −0.07%). Living in a forest fire–prone province for a prolonged period of time negatively affected cognitive scores after adjusting for individual factors.


Forests ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 29
Author(s):  
Donghyun Kim

This study examined the records of forest fire outbreaks and characteristics over the 518 years of the Joseon Dynasty period (1392–1910) through the analysis of major historical records of Korea. The historical books used in this study were 14 major national historical books, and include the Annals of the Joseon Dynasty (朝鮮王朝實錄), the Diaries of the Royal Secretariat (承政院日記), and the literature was examined, centering on official records of the royal palace in the Joseon Dynasty period. The contents of forest fires recorded in the historical record literature include the overviews of outbreak, forest fire types, and forest fire damage. According to the results of analysis of historical records, the largest forest fire damage was in the forest fire that occurred on the east coast in 1672, in which 65 persons died and in the forest fire that occurred in the same area in 1804, in which 61 persons died and 2600 private houses were destroyed by fire. The causes of fire outbreak were shown to be unknown causes in 42 cases, accidental fires in 10 cases, arson in 3 cases, thunder strike in 3 cases, hunting activities in 2 cases, child playing with fire in 1 case, cultivating activities in 1 case, and house fire in 1 case. Forest fire outbreaks were analyzed by region and by season and according to the results, 56% (39 cases) of the forest fires broke out on the east coast and 73% (46 cases) broke out in the spring. Forest fire policies include those for general forests, those for reserved forests, those for prohibited forests, those for capital city forests, those for royal family’s graves, royal ancestral shrine, and placenta chamber, those for hunting grounds such as martial art teaching fields, and relief policies for people in areas damaged by forest fires, forest fire policies for national defense facilities such as beacon fire stations, and burning and burning control policies for pest control. In conclusion, due to the seriousness of forest fires in the Joseon Dynasty period, the royal authority and local administrative agencies made various forest fire prevention policies, policies for stabilization of the people’s livelihood damaged due to forest fires, and methods to manage major facilities in forests.


Clay Minerals ◽  
2009 ◽  
Vol 44 (2) ◽  
pp. 239-247 ◽  
Author(s):  
P. Nørnberg ◽  
A. L. Vendelboe ◽  
H. P. Gunnlaugsson ◽  
J. P. Merrison ◽  
K. Finster ◽  
...  

AbstractA long-standing unresolved puzzle related to the Danish temperate humid climate is the presence of extended areas with large Fe contents, where goethite and ferrihydrite are present in the topsoil along with hematite and maghemite. Hematite and, particularly, maghemite would normally be interpreted as the result of high temperature as found after forest fires. However, a body of evidence argues against these sites having been exposed to fire. In an attempt to get closer to an explanation of this Fe mineralogy, an experimental forest fire was produced. The results showed a clear mineralogical zonation down to 10 cm depth. This was not observed at the natural sites, which contained a mixture of goethite/ferrihydrite, hematite and maghemite down to 20 cm depth. The experimental forest fire left charcoal and ashes at the topsoil, produced high pH and decreased organic matter content, all of which is in contrast to the natural sites. The conclusion from this work is that the mineralogy of these sites is not consistent with exposure to forest fire, but may instead result from long-term transformation in a reducing environment, possibly involving microbiology.


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