scholarly journals Quantifying potential particulate matter intake dose in a low-income community in South Africa

2021 ◽  
Vol 31 (2) ◽  
Author(s):  
Bianca Wernecke ◽  
Roelof P Burger ◽  
Brigitte Language ◽  
Caradee Y Wright ◽  
Stuart J Piketh

Understanding how exposure to particulate matter impacts human health is complex. Personal exposure is a function of the pollution concentrations measured at any given place and time. The health impacts of this exposure are, amongst other factors, determined by how high pollutant concentrations are and what enters the body. This study considered data gathered in the winter of 2013 in a low-income community on the Mpumalanga Highveld, South Africa, which is a geographical area known for its high air pollution levels. Time-activity data collected by GPS monitors worn by individuals in the community were used to understand in which microenvironments people spend most of their time. Eight days’ worth of ambient, indoor and personal particulate matter measurements were paired with individual GPS positioning data for one study participant. We identified pollutant concentrations where the person spent time and how much particulate matter was potentially inhaled in specific micro-environments. Participants spent time in five main micro-environments: (highest rank first) inside a house, directly outside a house, on a dirt road, on a tar road, and on an open field. Exposure to particulate matter concentrations in these micro-environments exceeded the National Ambient Air Quality Standards. Highest exposure was measured inside the dwelling and directly outside the dwelling. When comparing directly- and indirectly derived time-weighted potential intake doses, directly derived intake doses were higher and more likely to represent particulate matter concentrations inhaled by the participant. This study suggests that people living in communities on the Mpumalanga Highveld are exposed to unacceptably high air pollution levels in places in which they spend most of their time. Direct exposure and intake dose assessments are an essential element of environmental health studies to supplement data collected by stationary monitors.

2020 ◽  
Vol 20 (24) ◽  
pp. 15775-15792
Author(s):  
Yiqun Han ◽  
Wu Chen ◽  
Lia Chatzidiakou ◽  
Anika Krause ◽  
Li Yan ◽  
...  

Abstract. Beijing, as a representative megacity in China, is experiencing some of the most severe air pollution episodes in the world, and its fast urbanization has led to substantial urban and peri-urban disparities in both health status and air quality. Uncertainties remain regarding the possible causal links between individual air pollutants and health outcomes, with spatial comparative investigations of these links lacking, particularly in developing megacities. In light of this challenge, Effects of AIR pollution on cardiopuLmonary disEaSe in urban and peri-urban reSidents in Beijing (AIRLESS) was initiated, with the aim of addressing the complex issue of relating multi-pollutant exposure to cardiopulmonary outcomes. This paper presents the novel methodological framework employed in the project, namely (1) the deployment of two panel studies from established cohorts in urban and peri-urban Beijing, with different exposure settings regarding pollution levels and diverse sources; (2) the collection of detailed measurements and biomarkers of participants from a nested case (hypertensive) and control (healthy) study setting; (3) the assessment of indoor and personal exposure to multiple gaseous pollutants and particulate matter at unprecedented spatial and temporal resolution with validated novel sensor technologies; (4) the assessment of ambient air pollution levels in a large-scale field campaign, particularly the chemical composition of particulate matter. Preliminary results showed that there is a large difference between ambient and personal air pollution levels, and the differences varied between seasons and locations. These large differences were reflected on the different health responses between the two panels.


2011 ◽  
Vol 20 (1) ◽  
Author(s):  
C.Y Wright ◽  
R Oosthuizen ◽  
J John ◽  
R.M Garland ◽  
P Albers ◽  
...  

Human exposure to poor air quality is linked to adverse health effects. The largest burden of air pollution-related diseases is in developing countries where air pollution levels are also among the highest in the world. In South Africa, two geographic areas, the Vaal Triangle and the Highveld, have been identified for air quality managementinterventions to ensure compliance with National Air Quality Management Standards and to control potential harmful air pollution impacts on human health. The Highveld Priority Area (HPA) is characterised by intense mining, coal-fired power plants, industries, including iron and steel manufacturing, chemical plants, agricultural activity, motor vehicles and domestic fuel burning. Apart from two previous studies, no respiratory health studies have been carried out in the HPA. This paper describes the results of a recent, comprehensive study of ambient air quality, potential exposure to air pollution and air-related human health among a low income community living in the HPA in order to better understand the impact of air pollution on human health in South Africa.


Author(s):  
William Mueller ◽  
Kraichat Tantrakarnapa ◽  
Helinor Jane Johnston ◽  
Miranda Loh ◽  
Susanne Steinle ◽  
...  

Abstract Background There is a growing evidence that exposure to ambient particulate air pollution during pregnancy is associated with adverse birth outcomes, including reduced birth weight (BW). The objective of this study was to quantify associations between BW and exposure to particulate matter (PM) and biomass burning during pregnancy in Thailand. Methods We collected hourly ambient air pollutant data from ground-based monitors (PM with diameter of <10 µm [PM10], Ozone [O3], and nitrogen dioxide [NO2]), biomass burning from satellite remote sensing data, and individual birth weight data during 2015–2018. We performed a semi-ecological analysis to evaluate the association between mean trimester exposure to air pollutants and biomass burning with BW and low-birth weight (LBW) (<2500 g), adjusting for gestation age, sex, previous pregnancies, mother’s age, heat index, season, year, gaseous pollutant concentrations, and province. We examined potential effect modification of PM10 and biomass burning exposures by sex. Results There were 83,931 eligible births with a mean pregnancy PM10 exposure of 39.7 µg/m3 (standard deviation [SD] = 7.7). The entire pregnancy exposure was associated with reduced BW both for PM10 (−6.81 g per 10 µg/m3 increase in PM10 [95% CI = −12.52 to −1.10]) and biomass burning (−6.34 g per 1 SD increase in fires/km2 [95% CI = −11.35 to −1.34]) only after adjustment for NO2. In contrast with these findings, a reduced odds ratio (OR) of LBW was associated with PM10 exposure only in trimesters one and two, with no relationship across the entire pregnancy period. Associations with biomass burning were limited to increased ORs of LBW with exposure in trimester three, but only for male births. Conclusion Based on our results, we encourage further investigation of air pollution, biomass burning and BW in Thailand and other low-income and middle-income countries.


2019 ◽  
Vol 11 (4) ◽  
pp. 28-41 ◽  
Author(s):  
Cynthia J. ◽  
Saroja M.N. ◽  
Parveen Sultana ◽  
J. Senthil

Humans can be adversely affected by exposure to air pollutants in ambient air. Hence, health-based standards and objectives for a number of pollutants in the air are set by each country. Detection and measurement of contents of the atmosphere are becoming increasingly important. Careful planning of measurements is essential. One of the major factors that influence the representativeness of data collected is the location of monitoring stations. The planning and setting up of a monitoring station are complex and incurs a huge expenditure. An IoT-based real time air pollution monitoring system is proposed to monitor the pollution levels of various pollutants in Coimbatore city. The geographical area is classified as industrial, residential and traffic zones. This article proposes an IoT system that could be deployed at any location and store the measured value in a cloud database, perform pollution analysis, and display the pollution level at any given location.


Author(s):  
Kari A. Weber ◽  
Wei Yang ◽  
Evan Lyons ◽  
David K. Stevenson ◽  
Amy M. Padula ◽  
...  

To investigate preeclampsia etiologies, we examined relationships between greenspace, air pollution, and neighborhood factors. Data were from hospital records and geocoded residences of 77,406 women in San Joaquin Valley, California from 2000 to 2006. Preeclampsia was divided into mild, severe, or superimposed onto pre-existing hypertension. Greenspace within 100 and 500 m residential buffers was estimated from satellite data using normalized difference vegetation index (NDVI). Air quality data were averaged over pregnancy from daily 24-h averages of nitrogen dioxide, particulate matter <10 µm (PM10) and <2.5 µm (PM2.5), and carbon monoxide. Neighborhood socioeconomic (SES) factors included living below the federal poverty level and median annual income using 2000 US Census data. Odds of preeclampsia were estimated using logistic regression. Effect modification was assessed using Wald tests. More greenspace (500 m) was inversely associated with superimposed preeclampsia (OR = 0.57). High PM2.5 and low SES were associated with mild and severe preeclampsia. We observed differences in associations between greenspace (500 m) and superimposed preeclampsia by neighborhood income and between greenspace (500 m) and severe preeclampsia by PM10, overall and among those living in higher SES neighborhoods. Less greenspace, high particulate matter, and high-poverty/low-income neighborhoods were associated with preeclampsia, and effect modification was observed between these exposures. Further research into exposure combinations and preeclampsia is warranted.


Author(s):  
Han Cao ◽  
Bingxiao Li ◽  
Tianlun Gu ◽  
Xiaohui Liu ◽  
Kai Meng ◽  
...  

Evidence regarding the effects of environmental factors on COVID-19 transmission is mixed. We aimed to explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases during the outbreak period throughout China. The number of COVID-19 confirmed cases, air pollutant concentrations, and meteorological factors in China from January 25 to February 29, 2020, (36 days) were extracted from authoritative electronic databases. The associations were estimated for a single-day lag as well as moving averages lag using generalized additive mixed models. Region-specific analyses and meta-analysis were conducted in 5 selected regions from the north to south of China with diverse air pollution levels and weather conditions and sufficient sample size. Nonlinear concentration–response analyses were performed. An increase of each interquartile range in PM2.5, PM10, SO2, NO2, O3, and CO at lag4 corresponded to 1.40 (1.37–1.43), 1.35 (1.32–1.37), 1.01 (1.00–1.02), 1.08 (1.07–1.10), 1.28 (1.27–1.29), and 1.26 (1.24–1.28) ORs of daily new cases, respectively. For 1°C, 1%, and 1 m/s increase in temperature, relative humidity, and wind velocity, the ORs were 0.97 (0.97–0.98), 0.96 (0.96–0.97), and 0.94 (0.92–0.95), respectively. The estimates of PM2.5, PM10, NO2, and all meteorological factors remained significantly after meta-analysis for the five selected regions. The concentration–response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily new cases increasing. Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. Controlling ambient air pollution, especially for PM2.5, PM10, NO2, may be an important component of reducing risk of COVID-19 infection. In addition, as winter months are arriving in China, the meteorological factors may play a negative role in prevention. Therefore, it is significant to implement the public health control measures persistently in case another possible pandemic.


2019 ◽  
Vol 8 (3) ◽  
pp. 7922-7927

In Taiwan country Annan, Chiayi, Giran, and Puzi cities are facing a serious fine particulate matter (PM2.5) issue. To date the impressive advance has been made toward understanding the PM2.5 issue, counting special temporal characterization, driving variables and well-being impacted. However, notable research as has been done on the interaction of the content between the selected cities of Taiwan country for particulate matter (PM2.5) concentration. In this paper, we purposed a visualization technique based on this principle of the visualization, cross-correlation method and also the time-series concentration with particulate matter (PM2.5) for different cities in Taiwan. The visualization also shows that the correlation between the different meteorological factors as well as the different air pollution pollutants for particular cities in Taiwan. This visualization approach helps to determine the concentration of the air pollution levels in different cities and also determine the Pearson correlation, r values of selected cities are Annan, Puzi, Giran, and Wugu.


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