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 The impacts of commissioning coal-fired power stations on air quality in South Africa: insights from ambient monitoring stations

2020 ◽  
Vol 30 (2) ◽  
Author(s):  
Itumeleng P. Morosele ◽  
Kristy E. Langerman
Keyword(s):  
South Africa ◽  
Air Quality ◽  
Ambient Air ◽  
Monitoring Station ◽  
Ambient Air Quality ◽  
Power Station ◽  
Power Stations ◽  
Ambient Pollution ◽  
Pollution Concentrations ◽  
Monitoring Stations

The South African electricity sector is known for its heavy reliance on coal. The aim of this study is to assess the impacts of increasing SO2 and PM emissions from the three return-to-service power stations (Komati, Camden and Grootvlei), and the newly constructed Medupi power station on ambient air quality measured in the vicinities of these power stations. Trends in ambient pollution concentrations were determined using Theil-Sen analysis. The correlation between the emissions and ambient pollution concentrations at nearby monitoring stations was determined with the Spearman partial rank correlation coefficient.  Lastly, compliance of ambient pollution concentrations with the South Africa National Ambient Air Quality Standards was assessed. Few statistically significant trends in ambient SO2 and PM10 concentrations are found, and there is little correlation between increasing power station emissions and ambient pollutant concentrations in the vicinity. It is only at Camden monitoring station where there are increases in PM10 concentrations from the direction of Camden power station, and at Grootvlei monitoring station where increasing SO2 concentrations are from the directions of Grootvlei and Lethabo power stations. A strong, positive correlation between power station emissions and ambient concentrations exists only for SO2 at Grootvlei monitoring station and PM10 at Medupi monitoring station (although it is likely that the correlation at Medupi is related to construction and vehicle activity, and not emissions from Medupi power station stacks). It is concluded that the establishment of monitoring stations in the vicinities of power stations is necessary but not sufficient to monitor their impact on air quality in the surrounds.

scholarly journals Air quality indicators from the Environmental Performance Index: potential use and limitations in South Africa

2017 ◽  
Vol 27 (1) ◽  
Author(s):  
RM Garland ◽  
M Naidoo ◽  
B Sibiya ◽  
R Oosthuizen
Keyword(s):  
South Africa ◽  
Air Quality ◽  
Quality Indicators ◽  
Environmental Performance ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
Environmental Performance Index ◽  
Time Period ◽  
Source Data ◽  
Potential Use

In responding to deteriorating air quality, many countries, including South Africa, have implemented national programmes that aim to manage and regulate ambient air quality, and the emissions of air pollutants. One aspect within these management strategies is effective communication to stakeholders, including the general public, with regard to the state and trend of ambient air quality in South Africa. Currently, information on ambient air quality is communicated through ambient mass concentration values, as well as number of exceedances of South African National Ambient Standards. However, these do not directly communicate the potential impact on human health and the ecosystem. To this end, the use of air quality indicators is seen as a potential way to achieve communication to stakeholders in a simplified, yet scientifically defensible manner. Air quality indicators and their source data from the Environmental Performance Index (EPI) were interrogated to understand their potential use in South Africa. An assessment of four air quality indicators, together with their source data, showed improvements in air quality over the time period studied, though the input data do have uncertainties. The source data for the PM indicators, which came from a global dataset, underestimated the annual PM2.5 concentrations in the Highveld Priority Area and Vaal Triangle Airshed Priority Area over the time period studied (2009-2014) by ~3.7 times. This highlights a key limitation of national-scale indicators and input data, that while the data used by the EPI are a well-thought out estimate of a country’s air quality profile, they remain a generalised estimate. The assumptions and uncertainty inherent in such an ambitious global-wide attempt make the estimates inaccurate for countries without proper emissions tracking and accounting and few monitoring stations, such as South Africa. Thus, the inputs and resultant indicators should be used with caution until such a time that local and ground-truthed data and inputs can be utilised.

scholarly journals Assessment of ambient air pollution in the Waterberg Priority Area 2012-2015

2016 ◽  
Vol 26 (1) ◽  
pp. 21-28 ◽  
Author(s):  
G.T. Feig ◽  
S. Naidoo ◽  
N. Ncgukana
Keyword(s):  
Air Quality ◽  
Monitoring Network ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Local Source ◽  
Ambient Air Quality ◽  
Priority Area ◽  
Hourly Data ◽  
Ambient Concentrations ◽  
Monitoring Stations

The Waterberg Priority Area ambient air quality monitoring network was established in 2012 to monitor the ambient air quality in the Waterberg Air Quality Priority Area. Three monitoring stations were established in Lephalale, Thabazimbi and Mokopane. The monitoring stations measure the concentrations of PM10, PM2.5, SO2, NOx, CO, O3, BTEX and meteorological parameters. Hourly data for a 31 month period (October 2012-April 2015) was obtained from the South African Air Quality Information System (SAAQIS) and analysed to assess patterns in atmospheric concentrations, including seasonal and diurnal patterns of the ambient concentrations and to assess the impacts that such reported pollution concentration may have. Local source regions for SO2, PM10, PM2.5 and O3 were identified and trends in the recorded concentrations are discussed.

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 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.

Respiratory Symptoms and Spirometric Observations in Relation to Atmospheric Pollutants in a Sample of Urban Population

2000 ◽  
Vol 12 (2) ◽  
pp. 58-64 ◽  
Author(s):  
K. Satish Kumar ◽  
C.E. Prasad ◽  
N. Balakrishna ◽  
K. Visweswara Rao ◽  
P. Uma Maheswara Reddy
Keyword(s):  
Air Quality ◽  
Respiratory Symptoms ◽  
Ambient Air ◽  
Air Pollutant ◽  
Control Measures ◽  
Atmospheric Pollutants ◽  
Quality Data ◽  
Ambient Air Quality ◽  
Group I ◽  
The Mean

The prevalence of respiratory problems and the ventilatory functions in subjects belonging to three sample areas with different levels of pollution was studied to ascertain if there is any association between air pollutant levels and abnormal ventilatory functions. The predominant activity existing in that area served as the basis for stratification of the city into industrial (Group I), commercial (Group II) and residential (Group III) areas. Ambient air quality data of suspended particulate matter SPM, SO2 and NOx of the three sample areas were measured using standard methods. 216 men included in the study were administered the American Thoracic Society - Division of Lung Diseases ATS-DLD respiratory questionnaire, clinically examined and subjected to routine laboratory investigations. Spirometry and salbutamol reversibility tests were performed as per the ATS guidelines 1991. The mean and peak levels of SPM in the commercial area and the peak levels in the residential area were higher than the National Ambient Air Quality Standards (NAAQS). The mean and peak levels of NOx and SO2 in all the three areas were lower than the NAAQS. A high prevalence of ∼ 30-50% of respiratory symptoms was reported in the present study. Respiratory and ventilatory abnormalities were higher in the commercial areas, which are associated with the higher mean and peak levels of SO 2 and the peak levels of NOx. The pollution control measures should also aim at the peak levels of pollutants as they have been shown to exacerbate the respiratory symptoms in the present study. Asia Pac J Public Health 2000;12(2): 58-64

Forecasts using Box–Jenkins models for the ambient air quality data of Delhi City

2008 ◽  
Vol 157 (1-4) ◽  
pp. 105-112 ◽  
Author(s):  
Pragati Sharma ◽  
Avinash Chandra ◽  
S. C. Kaushik
Keyword(s):  
Air Quality ◽  
Ambient Air ◽  
Quality Data ◽  
Ambient Air Quality ◽  
Air Quality Data
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