Ambient Air Quality Assessment via Comprehensive Evaluation through Automatic Weight Determining

2014 ◽  
Vol 955-959 ◽  
pp. 1764-1767
Author(s):  
Dai Ying Li
Keyword(s):  
Mathematical Model ◽  
Air Quality ◽  
Quality Evaluation ◽  
Comprehensive Evaluation ◽  
Ambient Air ◽  
Quality Data ◽  
Ambient Air Quality ◽  
Air Quality Assessment ◽  
Viable Approach ◽  
The Mathematical Model

A mathematical model is built for air quality evaluation, which has taken PM2.5, PM10, SO2, NO2, CO and O3six parameters into consideration. The comprehensive air quality evaluation is carried out via standard deviation method and principle component analysis method; automatic weight determining has been discussed. Correlations of the factors are considered and a preprocess procedure is issued to eliminate the effects. Ambient air quality data of eleven cities are taken as an example and the comprehensive evaluation results are compared, which shows the mathematical model provides a viable approach to environmental assessment.

scholarly journals Ambient Air Quality Assessment of Orlu, Southeastern, Nigeria

2017 ◽  
Vol 17 (9) ◽  
pp. 441-457 ◽  
Author(s):  
Ibe Francis Ch ◽  
Opara Alexander ◽  
Njoku Pascal Chu ◽  
Alinnor Jude Ikech
Keyword(s):  
Air Quality ◽  
Quality Assessment ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
Southeastern Nigeria ◽  
Air Quality Assessment

scholarly journals Research on Air Quality Analysis Based on Cluster Methods

2021 ◽  
Vol 898 (1) ◽  
pp. 012024
Author(s):  
Zhaoni Li ◽  
Jian Zheng
Keyword(s):  
Air Quality ◽  
Ambient Air ◽  
Quality Analysis ◽  
Quality Data ◽  
Ambient Air Quality ◽  
Republic Of China ◽  
Pollution Levels ◽  
Analysis Process ◽  
Cluster Methods ◽  
The Impact

Abstract Research on air quality analysis is a hot field. Here we describe an analysis process based on cluster methods for the data of ambient air quality. In this paper, we use the process to cluster on the air quality data which from the National Urban Air Quality Report in December 2020 on the official website of the Ministry of Ecology and Environment of the People’s Republic of China. We find that cities in different clusters with different main pollutants and pollution levels. Ambient air quality analysis aims to provide guidance for reducing the impact of air pollution on health.

scholarly journals Ambient air quality data reported at Sasol Secunda monitoring stations during COVID-19 lockdown – Mpumalanga, South Africa

2021 ◽  
Vol 31 (1) ◽  
Author(s):  
Andrew Venter ◽  
Sandra De Vos
Keyword(s):  
South Africa ◽  
Air Quality ◽  
Ambient Air ◽  
Human Behaviour ◽  
Quality Data ◽  
Ambient Air Quality ◽  
Industrial Facilities ◽  
Ambient Temperatures ◽  
Pollutant Concentrations ◽  
Monitoring Stations

Various local and international research has been published on the effects of COVID-19 lockdown on ambient air quality. In most cases, a reduction in ambient NOx and PM concentrations have been observed with varying changes in ambient SO2 levels. Secunda, located in the Highveld Priority Area in Mpumalanga, South Africa is known for its large industrial facilities utilising coal as primary feedstock. The towns of Secunda and eMbalenhle provide the majority of the workforce to Sasol and has therefore been the focus of this study. The ambient air quality in the Secunda region was assessed due to the changes in human behaviour during lockdown, familiarity with the Sasol facility and the strategic locations of ambient air quality stations.Results show a clear decrease in ambient CO, NO2 and PM concentrations, especially during the first two weeks of lockdown. Only subtle changes were observed for ambient H2S and SO2 pollutant concentrations at the ambient monitoring stations. An increasing trend in all ambient species was observed towards the end and post lockdown, in contrast to declining ambient temperatures with the onset of winter. This is also contrary to the reduction in emissions from the factory that conducted annual maintenance in the month following lockdown (phase shutdown). This article concludes that human behaviour has a material local ambient impact on CO, NO2 and PM pollutant species, while H2S concentration profiles are more directly related to the industrial complex’s levels of activity. Ambient SO2 trends did not show a similar correlation with the facility’s activities (as H2S), but a stronger correlation was observed with the diverse local and regional sources in close proximity to Secunda and eMbalenhle. The influence of better dispersion especially on a local scale, brought about by more effective emission heights, is considered material. Moreover, meteorological factors, on local air quality, has been shown to be a material contributor to observed ambient air quality levels in the study domain

scholarly journals Land Use and Ambient Air Quality in Bahir Dar and Hawassa, Ethiopia

2018 ◽  
Vol 11 ◽  
pp. 117862211775213 ◽  
Author(s):  
Oluwasinaayomi Faith Kasim ◽  
Muluneh Woldetisadik Abshare ◽  
Truphena Eshibukule Mukuna ◽  
Bolanle Wahab
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Ambient Air ◽  
Urban Land Use ◽  
Quality Data ◽  
Bahir Dar ◽  
Ambient Air Quality ◽  
Industrial Land Use ◽  
Residential Land Use ◽  
Mean Concentration

Land use, air pollution, and climate change are closely related. This article analysed the contributions of urban land use to ambient air quality in Bahir Dar and Hawassa cities. A total of 32 geo-referenced locations, 16 each in Bahir Dar and Hawassa, representing different land uses, were assessed for carbon monoxide (CO), carbon dioxide (CO2), and volatile organic compound (VOC). CO2 concentration (ppm) for Bahir Dar and Hawassa ranged from 385.10 ± 15.34 ppm (recreational land use) to 555.50 ± 80.79 ppm (commercial land use) and 388.07 ± 19.79 ppm (recreational land use) to 444.50 ± 54.05 ppm (industrial land use), respectively, whereas mean concentration of CO was 0.01 ± 0.01 ppm (recreational land use) to 2.59 ± 0.69 ppm (circulation land use) and 0.12 ± 0.11 ppm (recreational land use) to 4.66 ± 1.41 ppm (circulation land use), respectively. The VOC values were 882.10 ± 147.05 ppm (residential land use) to 1436.00 ± 932.06 ppm (institutional land use) and 1377.30 ± 233.23 ppm (institutional land use) to 2132.33 ± 739.71 ppm (circulation land use). Inadequate monitoring, occasioned by dearth of equipment, poor urban management strategy, fossil fuel combustion, and aged vehicles were some of the factors responsible for the observed concentrations. Elevated levels of CO, CO2, and VOC in the atmosphere have a significant impact on global warming, with adverse effects on human health. Capacity for monitoring, analysis, reporting, and validation of air quality data in the cities should be strengthened.

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