Long-term deterioration mechanism of hot-dip aluminum coating exposed to a coastal-atmospheric environment

2021 ◽  
Vol 280 ◽  
pp. 122516
Author(s):  
Shigenobu Kainuma ◽  
Muye Yang ◽  
Yang Gao ◽  
Mikio Hashimoto
Keyword(s):  
Aluminum Coating ◽  
Atmospheric Environment ◽  
Deterioration Mechanism

scholarly journals A low-cost automized anaerobic chamber for long-term growth experiments and sample handling

2020 ◽  
Author(s):  
Achim J. Herrmann ◽  
Michelle M. Gehringer
Keyword(s):  
Environmental Control ◽  
Low Cost ◽  
Environmental Data ◽  
Atmospheric Environment ◽  
Regular Growth ◽  
Continuous Growth ◽  
Sample Handling ◽  
Hand Column ◽  
Oxygen Sensitive

1AbstractThe handling of oxygen sensitive samples and growth of obligate anaerobic organisms requires the stringent exclusion of oxygen, which is omnipresent in our normal atmospheric environment. Anaerobic workstations (aka. Glove boxes) enable the handling of oxygen sensitive samples during complex procedures, or the long-term incubation of anaerobic organisms. Depending on the application requirements, commercial workstations can cost up to 60.000 €. Here we present the complete build instructions for a highly adaptive, Arduino based, anaerobic workstation for microbial cultivation and sample handling, with features normally found only in high cost commercial solutions. This build can automatically regulate humidity, H2 levels (as oxygen reductant), log the environmental data and purge the airlock. It is built as compact as possible to allow it to fit into regular growth chambers for full environmental control. In our experiments, oxygen levels during the continuous growth of oxygen producing cyanobacteria, stayed under 0.03 % for 21 days without needing user intervention. The modular Arduino controller allows for the easy incorporation of additional regulation parameters, such as CO2 concentration or air pressure. This paper provides researchers with a low cost, entry level workstation for anaerobic sample handling with the flexibility to match their specific experimental needs.Specifications table[please fill in right-hand column of the table below]

Analysing the relationship of CO2 and O2 concentrations and flux patterns in forest soils

2021 ◽  
Author(s):  
Valentin Gartiser ◽  
Verena Lang ◽  
Martin Maier
Keyword(s):  
Diffusion Coefficient ◽  
Organic Material ◽  
West Germany ◽  
Atmospheric Environment ◽  
Concentration Data ◽  
Forest Sites ◽  
Production And Consumption ◽  
Different Depths ◽  
Relationship Of

<p>Soils act as bioreactors for the production and consumption of different gases. CO<sub>2</sub> is usually produced in soils due to the oxidation of organic material. Under aerobic conditions, this production is coupled to a consumption of O<sub>2</sub> resulting in concentration profiles that increase with depth for CO<sub>2</sub> and decrease for O<sub>2</sub>. Depending on the organic material present, the exchange of O<sub>2</sub> and CO<sub>2</sub> is approximately equimolar in well aerated soils. This can be deduced from vertical gradients of both gases which should reflect the ratio of their diffusion coefficient (Massmann 1998). The ratio between the CO<sub>2</sub> and O<sub>2</sub> flux is often called the respiratory coefficient. However, certain soil types or conditions may invoke anaerobe processes that may lead to a decoupling of CO<sub>2</sub> production and O<sub>2</sub> consumption. Such a decoupling can also result from oxidation of minerals or dissolution and relocation of carbonates.</p><p>Here we present long-term data of soil CO<sub>2</sub> and O<sub>2</sub> concentrations from forest sites in South West Germany. Gas samples were collected passively starting 1998 until now using permanently installed gas wells at different depths. The samples were then analysed using gas chromatography for CO<sub>2</sub> and O<sub>2</sub> (and additionally N<sub>2</sub>, Ar, N<sub>2</sub>O, CH<sub>4</sub>, and C<sub>2</sub>H<sub>4</sub>).</p><p>CO<sub>2</sub> and O<sub>2</sub> fluxes were calculated using the gradient approach (Maier et al 2020). At sites with well aerated soils, the observed CO<sub>2</sub> and O<sub>2</sub> fluxes followed a clear linear relationship, with high effluxes of CO<sub>2</sub> corresponding to high influxes of O<sub>2</sub>. The exchange was furthermore approximately equimolar with the calculated fluxes following a -1:1 trend.</p><p>We will compare these data from well aerated soils to concentration data of CO<sub>2</sub> and O<sub>2</sub> from less well-aerated soils with temporally suboxic conditions to further analyse the respiratory coefficient under oxygen limited conditions. Furthermore, diffusion-coefficient-normalised gradients are calculated to obtain information about the stoichiometry of the production and consumption patterns involved.</p><p> </p><p><em>Literature:</em></p><p><em>Maier M, Gartiser V, Schengel A, Lang V. Long Term Soil Gas Monitoring as Tool to Understand Soil Processes. Applied Sciences. 2020; 10(23):8653.</em></p><p><em>Massman, W J. A review of the molecular diffusivities of H<sub>2</sub>O, CO<sub>2</sub>, CH<sub>4</sub>, CO, O<sub>3</sub>, SO<sub>2</sub>, NH<sub>3</sub>, N<sub>2</sub>O, NO, and NO<sub>2</sub> in air, O<sub>2</sub> and N<sub>2</sub> near STP. Atmospheric Environment 1998; 32(6), 1111–1127</em></p><p> </p>

scholarly journals A Spatio-Temporal Analysis of Active Fires over China during 2003–2016

2020 ◽  
Vol 12 (11) ◽  
pp. 1787
Author(s):  
Xikun Wei ◽  
Guojie Wang ◽  
Tiexi Chen ◽  
Daniel Fiifi Tawia Hagan ◽  
Waheed Ullah
Keyword(s):  
Land Cover ◽  
Seasonal Variations ◽  
Urban Areas ◽  
Atmospheric Environment ◽  
Economic Losses ◽  
Change Analysis ◽  
Land Cover Types ◽  
North East ◽  
Spatio Temporal

Fire is a common circumstance in the world. It causes direct casualties and economic losses, and also brings severe negative influences on the atmospheric environment. In the background of climate warming and rising population, it is important to understand the fire responses regarding the spatio-temporal changes. Thus, a long-term change analysis of fires is needed in China. We use the remote sensed MOD14A1/MYD14A1 fire products to analyze the seasonal variations and long-term trends, based on five main land cover types (forest, cropland, grassland, savannas and urban areas). The fires are found to have clear seasonal variations; there are more fires in spring and autumn in vegetated lands, which are related to the amount of dry biomass and temperature. The fire numbers have significantly increased during the study period, especially from spring to autumn, and those have decreased in winter. The long-term fire trends are different when delineated into different land cover types. There are significant increasing fire trends in grasslands and croplands in North, East and Northeast China during the study period. The urban fires also show increasing trends. On the contrary, there are significant decreasing fire trends in forests and savannas in South China where it is most densely vegetated. This study provides an overall analysis of the spatio-temporal fire changes from satellite products, and it may help to understand the fire risk in the changing climate for a better risk management.

scholarly journals Analysis of SO2 Pollution Changes of Beijing-Tianjin-Hebei Region over China Based on OMI Observations from 2006 to 2017

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Zhifang Wang ◽  
Fengjie Zheng ◽  
Wenhao Zhang ◽  
Shutao Wang
Keyword(s):  
Air Quality ◽  
Control Strategies ◽  
Temporal Trends ◽  
Temporal Variations ◽  
Control Measures ◽  
Atmospheric Environment ◽  
Asia Pacific ◽  
Local Policy ◽  
The Government

Sulfur dioxide (SO2) in the planetary boundary layer (PBL) as a kind of gaseous pollutant has a strong effect regarding atmospheric environment, air quality, and climate change. As one of the most polluted regions in China, air quality in Beijing-Tianjin-Hebei (BTH) region has attracted more attention. This paper aims to study the characteristics of SO2 distribution and variation over BTH. Spatial and temporal variations for a long term (2006–2017) over BTH derived from OMI PBL SO2 products were discussed. The temporal trends confirm that the SO2 loading falls from average 0.88 DU to 0.16 DU in the past 12 years. Two ascending fluctuations in 2007 and 2011 appeared to be closely related to the economic stimulus of each five-year plan (FYP). The spatial analysis indicates an imbalanced spatial distribution pattern, with higher SO2 level in the southern BTH and lower in the northern. This is a result of both natural and human factors. Meanwhile, the SO2 concentration demonstrates a decreasing trend with 14.92%, 28.57%, and 27.43% compared with 2006, during the events of 2008 Olympic Games, 2014 Asia-Pacific Economic Cooperation (APEC) summit, and 2015 Military Parade, respectively. The improvement indicates that the direct effect is attributed to a series of long-term and short-term control measures, which have been implemented by the government. The findings of this study are desirable to assist local policy makers in the BTH for drawing up control strategies regarding the mitigation of environmental pollution in the future.

Corrigendum to ‘Mortality and air pollution in Beijing: The long-term relationship’ [Atmospheric Environment 150C (2017) 238–243]

2017 ◽  
Vol 157 ◽  
pp. 167 ◽  
Author(s):  
Guiqian Tang ◽  
Pusheng Zhao ◽  
Yinghong Wang ◽  
Wenkang Gao ◽  
Mengtian Cheng ◽  
...  
Keyword(s):  
Air Pollution ◽  
Atmospheric Environment

scholarly journals LIFE FORMS AND GEOGRAPHICAL DISTRIBUTION OF LICHENS URBAN ECOSYSTEM OF THE CITY OF TIMASHEVSK KRASNODAR TERRITORY

2020 ◽  
pp. 10-14
Author(s):  
S. B. Krivorotov ◽  
O. Yu. Manilova
Keyword(s):  
Air Quality ◽  
Life Forms ◽  
Urban Ecosystem ◽  
Atmospheric Environment ◽  
North West ◽  
The North ◽  
Lichen Biota ◽  
Air Quality Assessment ◽  
The City

Lichens are an important component of phytocenosis since they take part in formation of plant community microclimate, inhabit areas hardly suitable for other organisms, secret acids which retard the growth of some plants, etc. The article presents the results of taxonomic, geographic and environmental analysis of lichen biota in Timashevsk, Krasnodar Krai, Russia. The urban ecosystem accomodates 51 lichen species which belong to 27 genera, 12 families, and 2 groups. Life forms of lichens were detected in urban ecosystem. One of the methods of atmospheric air quality assessment is based on the usage of species composition of lichen biota in the studied urban ecosystem, and on defining of sensitivity of species. The list of lichens for the whole urban ecosystem, as well as for its particular areas, helps provide a solid assessment of the condition of air basin in this area, and compare the air quality on the parts of the explored territory. Therefore, lichens can be used as a bioindicator for long-term surveillance of atmospheric environment in urbanized territories of the North-West Caucasus.

scholarly journals A Wireless Multisensor Node for Long-Term Environmental Parameters Monitoring

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Deguang Li ◽  
Tianhao Wu ◽  
Xiaohui Li ◽  
Qiurui He ◽  
Zhanyou Cui
Keyword(s):  
Environmental Parameters ◽  
Environmental Data ◽  
Atmospheric Environment ◽  
Wireless Sensor ◽  
Wireless Sensor Node ◽  
Automatic Tracking ◽  
Cloud Server ◽  
Environment Parameters ◽  
Tracking Module

Environmental quality is a great concern to everyone, in order to realize the collection, upload, management, and visualization of parameters of atmospheric environment in real time. We propose a cheap, low-power, and fast deployment wireless sensor node for environmental monitoring, consisting of STM32 MCU, ESP8266, light sensor, rain sensor, UV sensor, seven-in-one sensor (including temperature, humidity, PM2.5, PM10, CO2, formaldehyde, and TVOC), and solar automatic tracking module. A customized μC/OS-III runs on the node, which controls the transmission of environment parameters collected by each sensor to the cloud server through the wireless network, and then the server receives, stores, and visualizes the data. In actual test, the node collects data once an hour, and the running power of the node is low and stable. Experimental results show that the node could achieve accurate collection and transmission and display the environmental data, and solar automatic tracking module could meet long-term running of the node in the night and continuous rainy days.

Air Pollution and its potential climate effect in Delhi, India

2020 ◽  
Author(s):  
Ying Chen ◽  
Luke Conibear ◽  
Yu Wang ◽  
Liang Ran ◽  
Jianjun He ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Fine Particles ◽  
Health Effect ◽  
Weekend Effect ◽  
Atmospheric Environment ◽  
Geophysical Research ◽  
Climate Effect ◽  
Premature Deaths ◽  
Health Burden

<p>Delhi, the capital city of India with more than 10 million population, is suffering one of the worst particulate matter (or PM2.5) pollution over the world. Based on continuous observations during 2015-2018, we report that the PM2.5 pollution in Delhi is possibly one of the worst within Indian cities, and responsible for ~10,000 premature deaths of cities per year. Especially during the Diwali Fest, the hourly PM2.5 concentrations went above 1600 ug/m<sup>3</sup>, leading to ~20 extra premature deaths per day (Chen et al., 2019). We find a distinct seasonal variation of PM2.5 mass concentrations and a shift of morning rush hour from winter to summer, but a negligible weekend effect in Delhi. We also report a long-term result of hygroscopicity of PM2.5 in Delhi is about κ= 0.42 ± 0.07 for the first time, indicating much higher potential of cloud droplet activation from fine particles in Delhi compared with other Asian megacities, such as Beijing (κ=0.14–0.23) (Wang and Chen, 2019). It means, in addition to the great health burden, more significant cloud activation and greater influences on climate and hydrologic cycle are expected from fine particles in Delhi.</p><p> </p><p><strong>Method & Data</strong></p><p>             We analysed the PM2.5 observations from US Embassy in Delhi, and used the Integrated Exposure Response Function to estimate the long-term and short-term health effect of PM2.5 exposure with a particular focus on the Diwali Fest period. Together with the temperature, RH and visibility data from the DEL airport in Delhi, we retrieved the 2016-2018 averaged hygroscopicity (κ) in Delhi according to the κ-kÓ§hler and Mie theories. In summary, we firstly retrieve the optical enhancement from visibility and RH, and then retrieve the optical-κ, and finally estimate the κ from the optical-κ. The detailed retrieving method is given in Wang and Chen (2019), this method has been validated in Beijing within an uncertainty of 30%.</p><p><strong> </strong></p><p><strong>Summary</strong></p><p>                Our results show a strong seasonal variation of PM2.5 in Delhi, with severest pollution during the winter. The Diwali and New Year Fests also lead to extreme pollution events, i.e. worse than the ‘Severe’ Level, in the beginning of November and January. These lead to adverse health effect and make Delhi the top-1 health burden city in India. The long-term averaged hygroscopicity of PM2.5 in Delhi is much higher than Beijing and Asian average. This indicate much easier for fine particles serving as cloud condensation nuclei and contributing the climate change and hydrology cycle. Moreover, the high optical enhance factor, f(RH), implies strong direct radiative forcing enhancement and influences on the heterogeneous reactions in Delhi.</p><p><strong> </strong></p><p><strong>Acknowledgement:</strong> We thank NERC Fund supported project (NE/P01531X/1) and the joint scholarship of China Scholarship Council and University of Manchester. We thank the U.S. National Climatic Data Center and AirNow platform maintained by the EPA provide the observations.</p><p> </p><p><strong>References:</strong></p><p>Chen, Y., Wild, O., Conibear, L., Ran, L., He, J., Wang, L., and Wang, Y.: Atmospheric Environment: X, 100052, 10.1016/j.aeaoa.2019.100052, 2019.</p><p>Wang, Y., and Chen, Y.: Geophysical Research Letters, 10.1029/2019GL082339, 2019.</p>

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