The Complex Nonlinear Causal Coupling Patterns between PM2.5 and Meteorological Factors in Tibetan Plateau: A Case Study in Xining

Mapping Intimacies ◽

10.21203/rs.3.rs-634756/v1 ◽

2021 ◽

Author(s):

Zhixiao Zou ◽

Changxiu Cheng ◽

Shi Shen

Keyword(s):

Air Quality ◽

Relative Humidity ◽

Meteorological Factors ◽

Mapping Method ◽

State Space Method ◽

Autumn And Winter ◽

Nonlinear State ◽

Space Method ◽

Main Factor

Abstract PM2.5 pollution influences the population health and people’s daily life. Because meteorological factors are main factor affecting the formation of PM2.5, the interaction between PM2.5 and meteorological factors needs to be better understood, both for air quality management and for PM2.5 projection. Here, we use a nonlinear state space method called the convergent cross mapping method to identify the complex coupling patterns between PM2.5 and meteorological factors in a plateau city: Xining. The results prove that PM2.5-meteorological coupling patterns change with seasons and PM2.5-meteorological coupling patterns are fixed in spring, autumn and winter. In spring, there is a negative unidirectional effect from precipitation to PM2.5 and a negative bidirectional effect between relative humidity and PM2.5. In autumn, there are some negative bidirectional effects between PM2.5 and relative humidity, precipitation, and air pressure, while solar radiation has a positive bidirectional effect on PM2.5. In winter, there are negative bidirectional couplings between PM2.5 and wind speed and temperature and a positive bidirectional coupling between relative humidity and PM2.5. Furthermore, relative humidity is a consistent driving factor affecting PM2.5. Air quality managers may alleviate PM2.5 by increasing relative humidity. Thus, the results provide a meteorological means for improving air quality in plateau cities.

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EVALUATION OF METEOROLOGICAL FACTORS INFLUENCE ON BENZENE ACCIDENTAL POLLUTION. CASE STUDY: BACAU CITY 2008

Journal of Engineering Studies and Research ◽

10.29081/jesr.v23i1.257 ◽

2018 ◽

Vol 23 (1) ◽

Author(s):

DOINA CAPSA ◽

VALENTIN NEDEFF ◽

NARCIS BARSAN ◽

Emilian Mosnegutu ◽

DANA CHITIMUS

Keyword(s):

Air Quality ◽

Urban Areas ◽

Meteorological Factors ◽

Pollutant Dispersion ◽

Meteorological Factor ◽

Climatic Conditions ◽

Green Areas ◽

Accidental Pollution ◽

Industrial Waste Management

<p>Air quality depends on the type and size of industrial activities, traffic intensity, municipal and industrial waste management etc. In addition, air quality in urban areas depends by the green areas management, population density, climatic conditions and geographic. This paper study the correlations between the most important meteorological factors, humidity, temperature, wind and benzene accidental pollution, with influence on pollutant dispersion (related to 2008). The correlation were performed by taken in to considerations the accidental benzene pollution recorded in 2008 in Bacau City and meteorological factor recorded at the regional meteorological station.</p>

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Behavior of the Average Concentrations As Well As Their PM10 and PM2.5 Variability in the Metropolitan Area of Lima, Peru: Case Study February and July 2016

International Journal of Environmental Science and Development ◽

10.18178/ijesd.2021.12.7.1341 ◽

2021 ◽

Vol 12 (7) ◽

pp. 204-213

Author(s):

Reátegui-Romero Warren ◽

F. Zaldivar-Alvarez Walter ◽

Pacsi–Valdivia Sergio ◽

R. Sánchez-Ccoyllo Odón ◽

E. García-Rivero Alberto ◽

...

Keyword(s):

Particulate Matter ◽

Air Quality ◽

Relative Humidity ◽

Metropolitan Area ◽

Vehicular Traffic ◽

Northern Area ◽

The North ◽

Pm10 And Pm2.5 ◽

Traffic Behavior

This research focused on analyzing the behavior of the hourly average concentrations of PM10 and PM2.5 in relation to vehicular traffic, as well as the effect of relative humidity on these concentrations. Measurements of hourly particulate matter concentrations were recorded by the National Meteorology and Hydrology Service of Peru (SENAMHI) at five surface air quality stations. The profiles of PM10 concentrations are related to traffic behavior, showing high levels of concentrations at peak hours, while the PM2.5 profiles are flatter and better related to traffic in February (summer). The decrease in relative humidity between 80 to 65% in the mornings has a greater effect on the increase in PM10 and PM2.5 concentrations in February than in July (winter), and the increase in relative humidity between 65 to 80 % in the afternoon, it has a greater effect on the decrease in the concentration of PM2.5 in February than in July. The air quality in the north (PPD and CRB stations) and east (SJL station) of the Metropolitan Area of Lima (MAL) are the most polluted. The factors that relate PM10 concentrations with the Peruvian standard in February at these stations were 2.79, 1.78 and 1.26, and in July 2.74, 1.28 and 1.36 respectively. The highest and lowest variability of PM10 and PM2.5 in February and July occurred in the northern area (PPD and SMP stations).

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EVALUATION OF METEOROLOGICAL FACTORS INFLUENCE ON BENZENE ACCIDENTAL POLLUTION. CASE STUDY: BACAU CITY 2008

Journal of Engineering Studies and Research ◽

10.29081/jesr.v23i1.87 ◽

2017 ◽

Vol 23 (1) ◽

pp. 12-19

Author(s):

DOINA CAPSA ◽

VALENTIN NEDEFF ◽

NARCIS BARSAN ◽

EMILIAN MOSNEGUTU ◽

DANA CHITIMUS

Keyword(s):

Air Quality ◽

Urban Areas ◽

Meteorological Factors ◽

Pollutant Dispersion ◽

Meteorological Factor ◽

Climatic Conditions ◽

Green Areas ◽

Accidental Pollution ◽

Industrial Waste Management

Air quality depends on the type and size of industrial activities, traffic intensity, municipal and industrial waste management etc. In addition, air quality in urban areas depends by the green areas management, population density, climatic conditions and geographic. This paper study the correlations between the most important meteorological factors, humidity, temperature, wind and benzene accidental pollution, with influence on pollutant dispersion (related to 2008). The correlation were performed by taken in to considerations the accidental benzene pollution recorded in 2008 in Bacau City and meteorological factor recorded at the regional meteorological station.

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The Analysis of Meteorological Factors and Ambient Air Quality (PM10, CO, SO2, NO2, and O3) with the Incidence of Acute Respiratory Infection (ARI) in Tangerang City, Indonesia During 2010-2019

International Journal of Advancement in Life Sciences Research ◽

10.31632/ijalsr.2021.v04i04.002 ◽

2021 ◽

Vol 4 (4) ◽

Author(s):

Muhammad Zulfikar Adha ◽

Talitha El Zhafira Hadi

Keyword(s):

Air Quality ◽

Relative Humidity ◽

Correlation Analysis ◽

Respiratory Infection ◽

Acute Respiratory Infection ◽

Meteorological Factors ◽

Sun Exposure ◽

Ambient Air ◽

Ambient Air Quality ◽

Regression Test

Tangerang City is a city with a high population, vehicles, and industries, so the pollutant emissions in the air are increasing. It has a high contribution in the occurrence of ARI (Acute Respiratory Infection). These pollutants are PM10, CO, SO2, NO2, and O3. In addition, meteorological factors such as air temperature, relative humidity, rainfall, wind velocity, and the length of sun exposure also affect the occurrence of the disease. Research Purposes: The purpose of this research is to find out how the correlation between meteorological factors and ambient air quality with the incidence of ARI in Tangerang City during 2010 to 2019. Research Methodology: This research uses analytic observational research, quantitative approaches, and retrospective cohort study design, also ecological study. The population used as a sample is all the data of meteorological factors, ambient air quality, and the incidence of ARI in Tangerang City during 2010 to 2019. Correlation analysis was performed using regression correlation analysis, simple linear regression test, and multiple linear regression test. Research Result: The result showed that meteorological factors and ambient air quality associated with the incidence of ARI are relative humidity (p = 0,039), rainfall (p = 0,044), wind velocity (p = 0,033), the length of sun exposure (p = 0,042), PM10(p = 0,024), CO (p = 0,040), NO2(p = 0,049), and O3(p = 0,039). KEYWORDS: Meteorological factors, Ambient air quality, Acute respiratory infection (ARI)

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Spatiotemporal Relationships between Air Quality and Multiple Meteorological Parameters in 221 Chinese Cities

Complexity ◽

10.1155/2020/6829142 ◽

2020 ◽

Vol 2020 ◽

pp. 1-25 ◽

Cited By ~ 1

Author(s):

Mengyi Ji ◽

Yuying Jiang ◽

Xiping Han ◽

Luo Liu ◽

Xinliang Xu ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Relative Humidity ◽

Meteorological Factors ◽

Southern China ◽

Great Influence ◽

Pollution Prevention ◽

Spatial And Temporal Variation ◽

Factors Affecting ◽

Temporal Differences

Air quality in China is characterized by significant spatial and temporal differences, which are directly related to local meteorological conditions. This study used air quality monitoring data, namely, the air pollution index (API) and air quality index (AQI) between 2005 and 2018, together with meteorological data and identified key meteorological factors that affected the spatial and temporal variation of air quality using a random forest algorithm. The spatial and temporal differences in the threshold values of different meteorological factors affecting the concentrations of PM2.5, PM10, SO2, CO, NO2, and O3 were identified. The AQI has the advantages of facilitating higher index values than the API. The air quality showed an improvement from 2005 to 2018. Wind direction and precipitation were the most important meteorological factors affecting the air quality in northern and southern China, respectively, which to some extent reflected the causes and degradation mechanisms of air pollution in the two regions. There were significant spatial and temporal differences in the effects of meteorological factors on the concentrations of different pollutants. The influence of atmospheric pressure on pollutant concentration differed between the east and west. Precipitation and relative humidity in most cities had significant impacts on PM2.5 and PM10. The influence of relative humidity was most significant for SO2 and it also had a great influence on O3, while wind speed had a great influence on NO2. The results of the study confirm the meteorological sensitivity of air quality and provide support for the implementation of regional air pollution prevention and control initiatives.

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Relation Between Microclimate and Air Quality in the Extensively Reared Turkey House

Macedonian Veterinary Review ◽

10.1515/macvetrev-2017-0015 ◽

2017 ◽

Vol 40 (1) ◽

pp. 83-90

Author(s):

Mario Ostović ◽

Sven Menčik ◽

Ivica Ravić ◽

Slavko Žužul ◽

Željko Pavičić ◽

...

Keyword(s):

Carbon Dioxide ◽

Air Quality ◽

Relative Humidity ◽

Air Temperature ◽

Indoor Air ◽

Animal Health ◽

Airflow Rate ◽

Carbon Dioxide Concentrations ◽

Bacteria And Fungi

Abstract Good air quality in poultry houses is crucial for animal health and productivity. In these houses, air is generally contaminated with noxious gases and microorganisms, the concentrations of which depend on numerous factors including microclimate. In this case study, the relation between microclimate and air concentrations of noxious gases and microorganisms was investigated in extensively reared turkey house. The study was carried out at a family household in Dalmatia hinterland, Croatia, with 50.3±3.1 turkeys kept in the house during the study period. Air temperature, relative humidity, airflow rate, concentrations of ammonia, carbon dioxide, bacteria and fungi in indoor air were measured three times per month from September to December, in the morning, prior to releasing turkeys out for grazing. Air temperature ranged from 9.73 to 26.98 °C, relative humidity from 63.29% to 75.08%, and airflow rate from 0.11 to 0.17 m/s. Lowest ammonia and carbon dioxide concentrations were measured in September (2.17 ppm and 550 ppm, respectively) and highest in December (4.50 ppm and 900 ppm, respectively). Bacterial and fungal counts were lowest in December (2.51×105 CFU/m3 and 3.27×103 CFU/m3 air, respectively) and highest in September (6.85×105 CFU/m3 and 1.06x105 CFU/m3 air, respectively). Air temperature and relative humidity showed negative correlation with concentrations of noxious gases and positive correlation with air microorganisms (P<0.05 all).

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