scholarly journals 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

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)

The Concentration Characteristics of PM10 and PM2.5 in Eight Cities of China in March, 2013

2013 ◽  
Vol 807-809 ◽  
pp. 20-23 ◽  
Author(s):  
Tao Sheng ◽  
Jian Wu Shi ◽  
Sen Lin Tian ◽  
Li Mei Bi ◽  
Hao Deng ◽  
...  
Keyword(s):  
Air Quality ◽  
Wind Speed ◽  
Relative Humidity ◽  
Negative Correlation ◽  
Ambient Air ◽  
Quality Standard ◽  
Meteorological Factor ◽  
Urban Air ◽  
Ambient Air Quality ◽  
Ambient Air Quality Standard

According to the information of air quality which published by the urban air quality real-time publishing platform, the concentration characteristics of PM10 and PM2.5 were studied in Kunming (KM), Changsha (CS), Hangzhou (HZ), Shanghai (SH), Harbin (HEB), Beijing (BJ), Wuhan (WH) and Guangzhou (GZ). The results show that the concentrations of PM10 and PM2.5 exceeded the Ambient Air Quality Standard (GB3095-2012) in varying degrees in March, 2013. The concentrations of PM10 in Wuhan is the highest, reached 164μg/m3, exceeded the standard by 9.3%; the concentrations of PM2.5 is much higher in Wuhan, Changsha and Beijing, the average concentrations were 96μg/m3, 103μg/m3 and 110μg/m3, exceeded the standard by 28.0%, 37.3% and 46.7% respectively. The correlation of PM10 with PM2.5 in most of these cities was good in March. The correlation analysis of pollutant with meteorological factor in Hangzhou, Shanghai, Beijing and Guangzhou was also studied, the results show that the concentrations of PM10 and PM2.5 are weakly positive correlation with temperature in the four cities, negative correlation with relative humidity without Beijing, and negative correlation with wind speed.

scholarly journals Long-Term Atmospheric Visibility Trends and Characteristics of 31 Provincial Capital Cities in China during 1957–2016

Atmosphere ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 318 ◽  
Author(s):  
Weicong Fu ◽  
Ziru Chen ◽  
Zhipeng Zhu ◽  
Qunyue Liu ◽  
Jinda Qi ◽  
...  
Keyword(s):  
Air Quality ◽  
Socioeconomic Factors ◽  
Urban Areas ◽  
Meteorological Factors ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
Capital Cities ◽  
The Public ◽  
Provincial Capital

Millions of pulmonary diseases, respiratory diseases, and premature deaths are caused by poor ambient air quality in developing countries, especially in China. A proven indicator of ambient air quality, atmospheric visibility (AV), has displayed continuous decline in China’s urban areas. A better understanding of the characteristics and the factors affecting AV can help the public and policy makers manage their life and work. In this study, long-term AV trends (from 1957–2016, excluding 1965–1972) and spatial characteristics of 31 provincial capital cities (PCCs) of China (excluding Taipei, Hong Kong, and Macau) were investigated. Seasonal and annual mean values of AV, percentage of ‘good’ (≥20 km) and ‘bad’ AV (<10 km), cumulative percentiles and the correlation between AV, socioeconomic factors, air pollutants and meteorological factors were analyzed in this study. Results showed that annual mean AV of the 31 PCCs in China were 14.30 km, with a declining rate of −1.07 km/decade. The AV of the 31 PCCs declined dramatically between 1973–1986, then plateaued between 1987–2006, and rebounded slightly after 2007. Correlation analysis showed that impact factors (e.g., urban size, industrial activities, residents’ activities, urban greening, air quality, and meteorological factors) contributed to the variation of AV. We also reveal that residents’ activities are the primary direct socioeconomic factors on AV. This study hopes to help the public fully understand the characteristics of AV and make recommendations about improving the air environment in China’s urban areas.

scholarly journals DINAMIKA KUALITAS UDARA AMBIEN SELAMA MASA PANDEMI COVID-19 DI KAWASAN INDONESIA TOURISM DEVELOPMENT CORPORATION NUSA DUA BALI

2021 ◽  
Vol 15 (1) ◽  
pp. 124
Author(s):  
Ika Sulistiani ◽  
I GD Yudha Partama ◽  
Sang Putu Kaler Surata ◽  
I Ketut Sumantra
Keyword(s):  
Air Quality ◽  
Wind Speed ◽  
Meteorological Factors ◽  
Ambient Air ◽  
Meteorological Factor ◽  
Ambient Air Quality ◽  
Air Concentration ◽  
Direct Reading ◽  
New Normal ◽  
Normal Period

The Covid-19 pandemic has increased the improvement of air quality in various countries in the world, such as China, Italy, New York, India, Spain and Korea. This study aims to compare ambient air quality during the Covid-19 pandemic with new normal and normal periods, assess the effect of meteorological factors on ambient air quality, and map the spatial distribution of ambient air quality during the normal, Covid-19 pandemic and new normal in the ITDC Nusa Dua area. Air concentration parameter data and meteorological factors were collected using the midget impinger and direct reading method in 2019 (normal period), March and May 2020 (Covid-19 pandemic period) and July, September, and November 2020 (new normal period). Furthermore, comparing air quality using the Anova test, assessing the effect of meteorological factors on air quality using a linear regression test, and mapping the distribution of ambient air using the ArcGis 10.8 application. The analysis showed that the air quality during the Covid-19 pandemic and the new normal was significantly different from the normal period. The concentrations of SO2, NO2, NH3, CO, TSP and H2S during the Covid-19 pandemic and normal just decreased while the O3 concentration increased compared to the normal period. The meteorological factor that affects air quality is the wind speed, the higher the wind speed the lower the O3 concentration. Map of the distribution of spatial concentrations of SO2, NO2, NH3, CO, O3 and H2S in the normal, Covid-19 pandemic and new normal, lowest at the coast point of the peninsula and the highest distribution at the ITDC roundabout, bima statue or influence TSP is the highest spatial concentration of normal distribution at the ITDC roundabout and the bima statue, while the Covid-19 pandemic and normal are only at the coast point of the peninsula beach.Keywords: ambient air quality; Covid-19; pandemic; tourism.

scholarly journals Multivariate Statistical Analysis of Atmospheric Dispersion of BTX Compounds at Sanathnagar, Hyderabad.

2020 ◽  
Vol 9 (1) ◽  
pp. 631-635
Keyword(s):  
Cluster Analysis ◽  
Air Quality ◽  
Meteorological Factors ◽  
Principal Component ◽  
Ambient Air ◽  
Quality Parameters ◽  
Ambient Air Pollution ◽  
Ambient Air Quality ◽  
Multivariate Statistical ◽  
Benzene Toluene

Sanathnagar, located in the centre of Hyderabad city, is taken as a case study to assess the meteorological factors influencing the air quality parameters Benzene, Toluene, Xylene (BTX compounds) and to identify the significant sources of pollution using the interspecies ratios. A data of ten years (2007- 2017) from Central Pollution control board (CPCB), Hyderabad, Telangana state is studied. TX compounds coming under Volatile Organic Compounds (VOC) were considered as the air quality parameters, seasons as cases and concerning meteorological factors such as Atmospheric Temperature AT (0C), Relative Humidity RH(%), Wind Speed WS (m/s), Wind Direction WD (deg), Sun Radiation SR (w/m2 ), Barometric Pressure BP (mm/Hg). Multivariate statistical techniques, namely Principal Component Analysis (PCA), and Cluster Analysis are used in this study with the help of IBM SPSS 26. The KMO test sampling adequacy found to be higher than 0.5, and the Bartlett test showed lesser value than 0.00, hence proving the results of the analysis are satisfactory. From BTX ratios it was observed that T/B was much higher than one and X/B been minimal value for all seasons indicating traffic pollution as a significant source of ambient air pollution in the study area. On the other hand, the correlation matrix states that a positive correlation between meteorological factors and ambient air quality parameters are as follows: SR- Benzene, Xylene; BPToluene; WS- Benzene, Toluene, and Xylene and the factors with a negative correlation on parameters are WD, RH, AT. PCA states that ambient air quality parameters are influenced by meteorological factors such as SR, RH, WS, WD (major influencers) and BP, AT (moderator influencers). Whereas in Cluster Analysis major influencers are WS, AT, RH and moderate are WP, SR, BP respectively. Therefore, PCA and CA results have shown similar trends in the categorization of meteorological influencers.

scholarly journals Investigating a Low-Cost Dryer Designed for Low-Cost PM Sensors Measuring Ambient Air Quality

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 804
Author(s):  
Abdul Samad ◽  
Freddy Ernesto Melchor Mimiaga ◽  
Bernd Laquai ◽  
Ulrich Vogt
Keyword(s):  
Air Quality ◽  
Relative Humidity ◽  
Urban Areas ◽  
Low Cost ◽  
Test Chamber ◽  
Ambient Air ◽  
High Relative Humidity ◽  
Ambient Air Quality ◽  
Drying Efficiency ◽  
The Impact

Air pollution in urban areas is a huge concern that demands an efficient air quality control to ensure health quality standards. The hotspots can be located by increasing spatial distribution of ambient air quality monitoring for which the low-cost sensors can be used. However, it is well-known that many factors influence their results. For low-cost Particulate Matter (PM) sensors, high relative humidity can have a significant impact on data quality. In order to eliminate or reduce the impact of high relative humidity on the results obtained from low-cost PM sensors, a low-cost dryer was developed and its effectiveness was investigated. For this purpose, a test chamber was designed, and low-cost PM sensors as well as professional reference devices were installed. A vaporizer regulated the humid conditions in the test chamber. The low-cost dryer heated the sample air with a manually adjustable intensity depending on the voltage. Different voltages were tested to find the optimum one with least energy consumption and maximum drying efficiency. The low-cost PM sensors with and without the low-cost dryer were compared. The experimental results verified that using the low-cost dryer reduced the influence of relative humidity on the low-cost PM sensor results.

Application of Electron Optics to Characterization of Particulate Pollutants

1972 ◽  
Vol 30 ◽  
pp. 364-365
Author(s):  
J. B. Moran ◽  
J. L. Miller
Keyword(s):  
Air Quality ◽  
Quality Standards ◽  
Ambient Air ◽  
Hazardous Substances ◽  
Fuel Additives ◽  
Ambient Air Quality ◽  
Air Quality Standards ◽  
Emission Standards ◽  
Stationary Sources ◽  
Ambient Air Quality Standards

The Clean Air Act Amendments of 1970 provide the basis for a dramatic change in Federal air quality programs. The Act establishes new standards for motor vehicles and requires EPA to establish national ambient air quality standards, standards of performance for new stationary sources of pollution, and standards for stationary sources emitting hazardous substances. Further, it establishes procedures which allow states to set emission standards for existing sources in order to achieve national ambient air quality standards. The Act also permits the Administrator of EPA to register fuels and fuel additives and to regulate the use of motor vehicle fuels or fuel additives which pose a hazard to public health or welfare.National air quality standards for particulate matter have been established. Asbestos, mercury, and beryllium have been designated as hazardous air pollutants for which Federal emission standards have been proposed.

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