scholarly journals Evaluation and Selection of Materials for Particulate Matter MEMS Sensors by Using Hybrid MCDM Methods

2018 ◽  
Vol 10 (10) ◽  
pp. 3451 ◽  
Author(s):  
Chi-Yo Huang ◽  
Pei-Han Chung ◽  
Joseph Shyu ◽  
Yao-Hua Ho ◽  
Chao-Hsin Wu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Gas Sensors ◽  
Multiple Criteria Decision Making ◽  
Manufacturing Processes ◽  
Portable Devices ◽  
Analytic Framework ◽  
Mems Sensors ◽  
Micro Electro Mechanical Systems ◽  
Selection Of

Air pollution poses serious problems as global industrialization continues to thrive. Since air pollution has grave impacts on human health, industry experts are starting to fathom how to integrate particulate matter (PM) sensors into portable devices; however, traditional micro-electro-mechanical systems (MEMS) gas sensors are too large. To overcome this challenge, experts from industry and academia have recently begun to investigate replacing the traditional etching techniques used on MEMS with semiconductor-based manufacturing processes and materials, such as gallium nitride (GaN), gallium arsenide (GaAs), and silicon. However, studies showing how to systematically evaluate and select suitable materials are rare in the literature. Therefore, this study aims to propose an analytic framework based on multiple criteria decision making (MCDM) to evaluate and select the most suitable materials for fabricating PM sensors. An empirical study based on recent research was conducted to demonstrate the feasibility of our analytic framework. The results provide an invaluable future reference for research institutes and providers.

AMBIENT PARTICULATE MATTER (PM10 AND PM2.5) AIR POLLUTION IN DESNIANSKY DISTRICT IN KYIV

2017 ◽  
Vol 2017 (67) ◽  
pp. 31-37
Author(s):  
O. Turos ◽  
◽  
T. Maremukha ◽  
I. Kobzarenko ◽  
A. Petrosian ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Ambient Particulate Matter ◽  
Pm10 And Pm2.5

Vicious Cycle of Economic Growth, Pm2.5 and COVID-19 Case of G7 Countries

2020 ◽  
Author(s):  
Rıdvan Karacan
Keyword(s):  
Economic Growth ◽  
Air Pollution ◽  
Particulate Matter ◽  
Fossil Fuels ◽  
Fine Particulate Matter ◽  
Panel Cointegration ◽  
Air Pollutant ◽  
Population Exposure ◽  
Causality Analysis ◽  
G7 Countries

<p>Today, production is carried out depending on fossil fuels. Fossil fuels pollute the air as they contain high levels of carbon. Many studies have been carried out on the economic costs of air pollution. However, in the present study, unlike the former ones, economic growth's relationship with the COVID-19 virus in addition to air pollution was examined. The COVID-19 virus, which was initially reported in Wuhan, China in December 2019 and affected the whole world, has caused many cases and deaths. Researchers have been going on studying how the virus is transmitted. Some of these studies suggest that the number of virus-related cases increases in regions with a high level of air pollution. Based on this fact, it is thought that air pollution will increase the number of COVID-19 cases in G7 Countries where industrial production is widespread. Therefore, the negative aspects of economic growth, which currently depends on fossil fuels, is tried to be revealed. The research was carried out for the period between 2000-2019. Panel cointegration test and panel causality analysis were used for the empirical analysis. Particulate matter known as PM2.5[1] was used as an indicator of air pollution. Consequently, a positive long-term relationship has been identified between PM2.5 and economic growth. This relationship also affects the number of COVID-19 cases.</p><p><br></p><p><br></p><p>[1] "Fine particulate matter (PM2.5) is an air pollutant that poses the greatest risk to health globally, affecting more people than any other pollutant (WHO, 2018). Chronic exposure to PM2.5 considerably increases the risk of respiratory and cardiovascular diseases in particular (WHO, 2018). For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator" (OECD.Stat).</p>

Emerging Challenges of Air Pollution and Particulate Matter in China, India, and Pakistan and Mitigating Solutions

2021 ◽  
pp. 125851
Author(s):  
Muhammad Naveed Anwar ◽  
Muneeba Shabbir ◽  
Eza Tahir ◽  
Mahnoor Iftikhar ◽  
Hira Saif ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter

scholarly journals A Multiple Criteria Decision Making Method to Weight the Sustainability Criteria of System Selection for Surface Mining

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3066
Author(s):  
Michał Patyk ◽  
Przemysław Bodziony ◽  
Zbigniew Krysa
Keyword(s):  
Decision Making ◽  
Performance Assessment ◽  
Multiple Criteria Decision Making ◽  
Surface Mining ◽  
Open Pit ◽  
Mining Equipment ◽  
Surface Mines ◽  
Mining Conditions ◽  
And Performance ◽  
Selection Of

Selection and assessment of mining equipment used in open pit rock mines relies chiefly on estimates of overall exploitation cost. The rational arrangement of mining equipment and systems comprising loading machines, haul trucks and crushing plants should be preceded by a thorough analysis of technical and economic aspects, such as investment outlays and the costs of further exploitation, which largely determine the costs of mining operations and the deposit value. Additionally, the operational parameters of the mining equipment ought to be considered. In this study, a universal set of evaluation criteria has been developed, and an evaluation method has been applied for the selection of surface mining equipment and the processing system to be operated in specific mining conditions, defined by the user. The objective of this study is to develop and apply the new methodology of multi-criteria selection of open pit rock mining equipment based on multiple criteria decision-making (MCDM) procedures, to enable the optimization of loading, handling and crushing processes. The methodology, underpinned by the principles of MCDM, provides the dedicated ranking procedures, including the ELECTRE III. The applied methodology allows the alternative options (variants) to be ranked accordingly. Ultimately, a more universal methodology is developed, applicable in other surface mines where geological and mining conditions are similar. It may prove particularly useful in selection and performance assessment of mining equipment and process line configurations in mining of low-quality rock deposits. Therefore, we undertook to develop universal criteria and applications for the selection and performance assessment of process machines for surface mines, taking into account environmental aspects as well as deposit quality.

scholarly journals A global association between Covid-19 cases and airborne particulate matter at regional level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Angelo Solimini ◽  
F. Filipponi ◽  
D. Alunni Fegatelli ◽  
B. Caputo ◽  
C. M. De Marco ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Negative Binomial ◽  
Numerical Models ◽  
Regional Level ◽  
Pollution Level ◽  
Observation Data ◽  
Cumulative Number ◽  
Mixed Effect

AbstractEvidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM10, PM2.5), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m3 increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM2.5 and PM10 respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.

scholarly journals Classifying the Biological Status of Honeybee Workers Using Gas Sensors

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 166
Author(s):  
Jakub T. Wilk ◽  
Beata Bąk ◽  
Piotr Artiemjew ◽  
Jerzy Wilde ◽  
Maciej Siuda
Keyword(s):  
Gas Sensors ◽  
Laboratory Tests ◽  
Test Chamber ◽  
Ambient Air ◽  
True Positive Rate ◽  
True Positive ◽  
Positive Rate ◽  
Parameters Of Accuracy ◽  
Selection Of

Honeybee workers have a specific smell depending on the age of workers and the biological status of the colony. Laboratory tests were carried out at the Department of Apiculture at UWM Olsztyn, using gas sensors installed in two twin prototype multi-sensor detectors. The study aimed to compare the responses of sensors to the odor of old worker bees (3–6 weeks old), young ones (0–1 days old), and those from long-term queenless colonies. From the experimental colonies, 10 samples of 100 workers were taken for each group and placed successively in the research chambers for the duration of the study. Old workers came from outer nest combs, young workers from hatching out brood in an incubator, and laying worker bees from long-term queenless colonies from brood combs (with laying worker bee’s eggs, humped brood, and drones). Each probe was measured for 10 min, and then immediately for another 10 min ambient air was given to regenerate sensors. The results were analyzed using 10 different classifiers. Research has shown that the devices can distinguish between the biological status of bees. The effectiveness of distinguishing between classes, determined by the parameters of accuracy balanced and true positive rate, of 0.763 and 0.742 in the case of the best euclidean.1nn classifier, may be satisfactory in the context of practical beekeeping. Depending on the environment accompanying the tested objects (a type of insert in the test chamber), the introduction of other classifiers as well as baseline correction methods may be considered, while the selection of the appropriate classifier for the task may be of great importance for the effectiveness of the classification.

scholarly journals Multi-Criteria Analysis for the Selection of the Optimal Mining Design Solution—A Case Study on Quarry “Tambura”

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3200
Author(s):  
Branimir Farkaš ◽  
Ana Hrastov
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Open Pit ◽  
Design Solution ◽  
Mine Design ◽  
Promethee Ii ◽  
Mining Design ◽  
Quarry Mine ◽  
Selection Of

Mining design is usually evaluated with different multiple-criteria decision-making (MCDM) methods when it comes to large open pit or underground ore mines, but it is not used on quarry sites. Since Croatia is mostly mining stone, the implementation of such methods in decision making of the quarry mine design is imperative but left out. In this paper, the PROMETHEE II and AHP decision-making methods are implemented on the quarry site to find out the best final quarry design contour. By implementing the MCDM methods, the best quarry model was chosen based on 22 different criteria parameters out of three final quarry designs. The chosen model is not only financially sound but also has the least environmental impact.

Robust Environmental Sensing Using UAVs

2021 ◽  
Vol 2 (4) ◽  
pp. 1-20
Author(s):  
Ahmed Boubrima ◽  
Edward W. Knightly
Keyword(s):  
Air Pollution ◽  
Gas Sensors ◽  
High Performance ◽  
Weather Conditions ◽  
Ambient Air ◽  
Mission Planning ◽  
Pollution Monitoring ◽  
Compound Pollution ◽  
Planning Algorithm

In this article, we first investigate the quality of aerial air pollution measurements and characterize the main error sources of drone-mounted gas sensors. To that end, we build ASTRO+, an aerial-ground pollution monitoring platform, and use it to collect a comprehensive dataset of both aerial and reference air pollution measurements. We show that the dynamic airflow caused by drones affects temperature and humidity levels of the ambient air, which then affect the measurement quality of gas sensors. Then, in the second part of this article, we leverage the effects of weather conditions on pollution measurements’ quality in order to design an unmanned aerial vehicle mission planning algorithm that adapts the trajectory of the drones while taking into account the quality of aerial measurements. We evaluate our mission planning approach based on a Volatile Organic Compound pollution dataset and show a high-performance improvement that is maintained even when pollution dynamics are high.

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