The impact of local sources and meteorological factors on nitrogen oxide and particulate matter concentrations: A case study of the Day of Atonement in Israel

The meteorological factors play an important role to influence the concentration of the particulate matters. The path analysis method is employed to investigate the influence of meteorological factors (including atmospheric temperature ( AT), relative humidity ( RH), and wind speed ( WS)) on particulate matters (including PM2.5 and PM10) in Dazhou city. The following results are obtained: (1) The direct path coefficients of AT, RH, and WS to PM2.5 and PM10 are all negative, which means that the concentration of particulate matters would be declined following with the increasing of AT, RH, and WS. (2) The meteorological factors would explain about 17.43 and 16.52% variance of PM2.5 and PM10, respectively. However, 82.57% variance of PM2.5 and 83.48% variance of PM10 would be determined by non-meteorological factors. (3) AT and WS are the most important meteorological factors to modulate the concentration of particulate matters. AT would explain 12.73 and 8.78% variance of PM2.5 and PM10, respectively. WS would explain 6.54 and 8.69% variance of PM2.5 and PM10, respectively. (4) According to the absolute value of the determination coefficients, the main influence on the concentration of PM2.5 is the direct influence by AT and the impact on the concentration of PM10 is by the combined contribution of meteorological factors.

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The evaluation on artificial neural networks (ANN) and multiple linear regressions (MLR) models over particulate matter (PM10) variability during haze and non-haze episodes: A decade case study

Malaysian Journal of Fundamental and Applied Sciences ◽

10.11113/mjfas.v15n2.1004 ◽

2019 ◽

Vol 15 (2) ◽

pp. 164-172 ◽

Cited By ~ 1

Author(s):

Ku Mohd Kalkausar Ku Yusof ◽

Azman Azid ◽

Muhamad Shirwan Abdullah Sani ◽

Mohd Saiful Samsudin ◽

Siti Noor Syuhada Muhammad Amin ◽

...

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Particulate Matter ◽

Meteorological Factors ◽

Model Development ◽

Eastern Region ◽

Multiple Linear Regressions ◽

Artificial Neural ◽

Linear Regressions

The comprehensives of particulate matter studies are needed in predicting future haze occurrences in Malaysia. This paper presents the application of Artificial Neural Networks (ANN) and Multiple Linear Regressions (MLR) coupled with sensitivity analysis (SA) in order to recognize the pollutant relationship status over particulate matter (PM10) in eastern region. Eight monitoring studies were used, involving 14 input parameters as independent variables including meteorological factors. In order to investigate the efficiency of ANN and MLR performance, two different weather circumstances were selected; haze and non-haze. The performance evaluation was characterized into two steps. Firstly, two models were developed based on ANN and MLR which denoted as full model, with all parameters (14 variables) were used as the input. SA was used as additional feature to rank the most contributed parameter to PM10 variations in both situations. Next, the model development was evaluated based on selected model, where only significant variables were selected as input. Three mathematical indices were introduced (R2, RMSE and SSE) to compare on both techniques. From the findings, ANN performed better in full and selected model, with both models were completely showed a significant result during hazy and non-hazy. On top of that, UVb and carbon monoxide were both variables that mutually predicted by ANN and MLR during hazy and non-hazy days, respectively. The precise predictions were required in helping any related agency to emphasize on pollutant that essentially contributed to PM10 variations, especially during haze period.

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Effects of particulate matter on respiratory disease and the impact of meteorological factors in Busan, Korea

Respiratory Medicine ◽

10.1016/j.rmed.2017.02.010 ◽

2017 ◽

Vol 124 ◽

pp. 79-87 ◽

Cited By ~ 50

Author(s):

Eun-Jung Jo ◽

Woo-Seop Lee ◽

Hyun-Young Jo ◽

Chang-Hoon Kim ◽

Jung-Seop Eom ◽

...

Keyword(s):

Particulate Matter ◽

Respiratory Disease ◽

Meteorological Factors ◽

The Impact

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Particulate Matter 10 (PM10) Is Associated with Epistaxis in Children and Adults

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18094809 ◽

2021 ◽

Vol 18 (9) ◽

pp. 4809

Author(s):

Kyungsoo Kim ◽

Il-Youp Kwak ◽

Hyunjin Min

Keyword(s):

Particulate Matter ◽

Environmental Factor ◽

Meteorological Factors ◽

Pm10 Concentration ◽

Cumulative Number ◽

Atmospheric Concentration ◽

Concentration Data ◽

Research Attention ◽

Korea Meteorological Administration ◽

The Impact

The impact of atmospheric concentration of particulate matter ≤10 μm in diameter (PM10) continues to attract research attention. This study aimed to evaluate the effects of meteorological factors, including PM10 concentration, on epistaxis presentation in children and adults. We reviewed the data from 1557 days and 2273 cases of epistaxis between January 2015 and December 2019. Eligible patients were stratified by age into the children (age ≤17 years) and adult groups. The main outcome was the incidence and cumulative number of epistaxis presentations in hospital per day and month. Meteorological factors and PM10 concentration data were obtained from the Korea Meteorological Administration. Several meteorological factors were associated with epistaxis presentation in hospital; however, these associations differed between children and adults. Only PM10 concentration was consistently associated with daily epistaxis presentation in hospital among both children and adults. Additionally, PM10 concentration was associated with the daily cumulative number of epistaxis presentations in hospital in children and adults. Furthermore, the monthly mean PM10 concentration was significantly associated with the total number of epistaxis presentations in the corresponding month. PM10 concentration should be regarded as an important environmental factor that may affect epistaxis in both children and adults.

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Analyzing Characteristics of Particulate Matter Pollution in Open-Pit Coal Mines: Implications for Green Mining

Energies ◽

10.3390/en14092680 ◽

2021 ◽

Vol 14 (9) ◽

pp. 2680

Author(s):

Huaiting Luo ◽

Wei Zhou ◽

Izhar Mithal Jiskani ◽

Zhiming Wang

Keyword(s):

Particulate Matter ◽

Wind Speed ◽

Temperature Difference ◽

Meteorological Factors ◽

Coal Mines ◽

Ambient Air ◽

Average Concentration ◽

Open Pit ◽

Particulate Pollution ◽

The Impact

The particulate pollution in the open-pit coal mines of China is particularly severe in winter. The aim of this study is to understand the pollution characteristics of particulate matter (PM) in winter and provide a basis for the prevention and control of particulate pollution. We took the problem of PM concentration at the bottom of the Haerwusu Open-pit Coal Mine (HOCM) as the research object. Dust monitoring equipment at two measurement points at different heights were positioned for continuous monitoring of the PM concentration. The data for three months were gathered. Statistical analyses were performed to analyze the variation characteristics of the PM and its relationship with meteorological factors. The results show that the average PM concentration in the study area is below the average daily limit of the China National Ambient Air Quality Standard (GB 3095-2012). However, the average concentration of PM10 exceeded the national limit in December. The order of PM concentration is observed as December > January > February. The correlation of PM is found to be positive with humidity and negative with wind speed. Temperature is found to be positively correlated with PM in December, while it is negative in January. At the same time, the temperature difference in December is negatively correlated with PM concentration. Under the combined action of multiple meteorological factors, the magnitude of the impact on the PM concentration at the bottom of the pit in winter is humidity > temperature > wind speed > temperature difference (inverse temperature intensity). In conclusion, PM2.5 is found to be more sensitive to environmental factors. The results of this study are particularly useful to progress in green mining.

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Five-Year Analysis of Air Pollution in Istanbul Including Also the Impact of the COVID-19 Pandemic

Journal of İzmir Chest Hospital ◽

10.5222/igh.2021.78941 ◽

2021 ◽

Author(s):

Nilüfer Aykaç ◽

Pınar Pazarlı Bostan ◽

Sabri Serhan Olcay ◽

Berker Öztürk

Keyword(s):

Air Pollution ◽

Particulate Matter ◽

Air Quality ◽

Nitrogen Oxide ◽

Air Pollutants ◽

World Health ◽

Limit Values ◽

Public Data ◽

Health Organization ◽

The Impact

INTRODUCTION: Particulate matter, sulfur dioxide, ozone, and nitrogen oxide compounds are the main air pollutants. The purpose of this research is to analyze the five-year air quality of Istanbul and examine the effect of movement restrictions due to the COVID-19 pandemic on pollutants. METHODS: The public data of the National Air Quality Observation Network has been utilized. The research has been conducted based on the five-year daily averages of PM10, NO2, and NOx pollutants for Istanbul between 2016 - 2020. The data of stations which measured for 75% and more throughout the year has been used. The effect of lockdowns enforced due to COVID-19 was revealed by comparing data of pollutants from April and May of 2020 to the same period in 2019. RESULTS: There were 12 stations between 2016 – 2018, and 39 stations in 2019 and 2020 which measured particulate matter and nitrogen oxide compounds. Only 9 stations reached the standard of measuring pollution for 75% and more throughout the year. The PM10, NO2, and NOx levels measured by all the 9 stations between 2016 - 2020 are above the limit values set by the World Health Organization (WHO). The lockdowns in 2020 have not been helping improvements in air pollution issue. However, there have been regressions of 33.4%, 59.6%, and 52.6% in the overall average particulate matter, nitrogen oxide, and nitrogen dioxide concentrations during the lockdowns between 23-26 of April, 1-3 of May, and 23-26 of May, respectively. DISCUSSION AND CONCLUSION: The air pollution issue in Istanbul has not improved in a meaningful and significant manner for the last five years. There is a significant deficiency in measuring traffic pollution. It has been found that two days long lockdowns and physical movement restrictions due to COVID-19 have significantly contributed to a significant regression in the overall concentration of air pollutants.

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