The air quality index based on measurements of mobile air quality monitoring station at the waste-to-energy incineration plant PLTSa Bantargebang

Abstract Ambient air quality monitoring at waste-to-energy incineration pilot plant PLTSa Bantargebang is performed using a mobile monitoring station. The mobile monitoring station is equipped with meteorological and emission (CO, O3, NO2, PM10, PM2.5, and SO2) measurement. The monitoring was performed for 24 hour with 1 minute intervals. The emission measurement data was analyzed using Indonesian Air pollution standard index regulation (PermenLHK P.14/2020). The CO, O3, NO2, PM10, and SO2 index were in good category (1-50), while the PM2.5 index was classified as moderate (65.992). The results show that the air quality at PLTSa Bantargebang is still acceptable for human health.

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A data-driven approach for optimal design of integrated air quality monitoring network in a chemical cluster

Royal Society Open Science ◽

10.1098/rsos.180889 ◽

2018 ◽

Vol 5 (9) ◽

pp. 180889 ◽

Cited By ~ 2

Author(s):

Zhengqiu Zhu ◽

Bin Chen ◽

Sihang Qiu ◽

Rongxiao Wang ◽

Yiping Wang ◽

...

Keyword(s):

Air Quality ◽

Measurement Data ◽

Monitoring Network ◽

Quality Monitoring ◽

Data Driven ◽

Atmospheric Environment ◽

Illustrative Case ◽

Air Quality Monitoring ◽

Detection Capability ◽

Data Driven Approach

The chemical industry is of paramount importance to the world economy and this industrial sector represents a substantial income source for developing countries. However, the chemical plants producing inside an industrial district pose a great threat to the surrounding atmospheric environment and human health. Therefore, designing an appropriate and available air quality monitoring network (AQMN) is essential for assessing the effectiveness of deployed pollution-controlling strategies and facilities. As monitoring facilities located at inappropriate sites would affect data validity, a two-stage data-driven approach constituted of a spatio-temporal technique (i.e. Bayesian maximum entropy) and a multi-objective optimization model (i.e. maximum concentration detection capability and maximum dosage detection capability) is proposed in this paper. The approach aims at optimizing the design of an AQMN formed by gas sensor modules. Owing to the lack of long-term measurement data, our developed atmospheric dispersion simulation system was employed to generate simulated data for the above method. Finally, an illustrative case study was implemented to illustrate the feasibility of the proposed approach, and results imply that this work is able to design an appropriate AQMN with acceptable accuracy and efficiency.

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Nghiên cứu ảnh hưởng của hiện tượng nghịch nhiệt đến hàm lượng bụi PM2.5 trong môi trường không khí tại Hà Nội

VNU Journal of Science Earth and Environmental Sciences ◽

10.25073/2588-1094/vnuees.4289 ◽

2018 ◽

Vol 34 (3) ◽

Cited By ~ 1

Author(s):

Trinh Thi Tham

Keyword(s):

Air Quality ◽

Statistical Difference ◽

Heat Rate ◽

Ambient Air ◽

Quality Monitoring ◽

Air Quality Monitoring ◽

Heat Temperature ◽

Effects Of Temperature ◽

Temperature Inversions ◽

The Impact

In this study, we assessed effects of temperature inversions on air quality in Hanoi, is the capital of Vietnam with the business development speed also as urbanization high in year near here. Temperature inversions occur frequently in the cooler seasons, exacerbating the impact of emissions and diffusions from industry and traffic. This research used concentration of PM2.5 data gathered from 02 automatic air quality monitoring station located North Centre for Environmental Monitoring, Vietnam environment administration and U.S Embassy Hanoi. The data on the change of temperature in the depth was collected from the meteorological stations Hanoi in 2017 aimed to analyze the frequency of the temperature rating of the Heat Rate of the Heat Temperature and the Heat of the temperature inversions and impacts of that on concentration of PM2.5 in the atmosphere. The results also revealed that there was statistical difference (Sig. <0,05) between PM2.5 levels in the ambient air on the inversion days and those on the normal day.

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An assessment of ambient air quality using AQI and exceedance factor for Udaipur City, Rajasthan (India)

WEENTECH Proceedings in Energy ◽

10.32438/wpe.102021 ◽

2021 ◽

pp. 94-106

Author(s):

Porush Kumar ◽

Kuldeep ◽

Nilima Gautam

Keyword(s):

Air Pollution ◽

Air Quality ◽

Pollution Control ◽

Urban Air Pollution ◽

Ambient Air ◽

Quality Monitoring ◽

Urban Air ◽

Air Quality Monitoring ◽

Ambient Air Quality ◽

Control Board

Air pollution is a severe issue of concern worldwide due to its most significant environmental risk to human health today. All substances that appear in excessive amounts in the environment, such as PM10, NO2, or SO2, may be associated with severe health problems. Anthropogenic sources of these pollutants are mainly responsible for the deterioration of urban air quality. These sources include stationary point sources, mobile sources, waste disposal landfills, open burning, and similar others. Due to these pollutants, people are at increased risk of various serious diseases like breathing problems and heart disease, and the death rate due to these diseases can also increase. Hence, air quality monitoring is essential in urban areas to control and regulate the emission of these pollutants to reduce the health impacts on human beings. Udaipur has been selected for the assessment of air quality with monitored air quality data. Air quality monitoring stations in Udaipur city are operated by the CPCB (Central Pollution Control Board) and RSPCB (Rajasthan State Pollution Control Board). The purpose of this study is to characterize the level of urban air pollution through the measurement of PM10, NO2, or SO2 in Udaipur city, Rajasthan (India). Four sampling locations were selected for Udaipur city to assess the effect of urban air pollution and ambient air quality, and it was monitored for a year from 1st January 2019 to 31st December 2019. The air quality index has been calculated with measured values of PM10, NO2, and SO2. The concentration of PM10 is at a critical level of pollution and primarily responsible for bad air quality and high air quality Index in Udaipur city.

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