scholarly journals Health Risk Analysis of Elemental Components of an Industrially Emitted Respirable Particulate Matter in an Urban Area

2021 ◽  
Vol 18 (7) ◽  
pp. 3653
Author(s):  
Oyewale Mayowa Morakinyo ◽  
Murembiwa Stanley Mukhola ◽  
Matlou Ingrid Mokgobu
Keyword(s):  
South Africa ◽  
Particulate Matter ◽  
Hazard Quotient ◽  
Age Groups ◽  
Air Pollutant ◽  
Chemical Components ◽  
Cancer Risks ◽  
Lifetime Cancer Risk ◽  
Acceptable Limit ◽  
Respirable Particulate

Particulate matter of aerodynamic diameter of less than 2.5 µm (PM2.5) is a recognised carcinogen and a priority air pollutant owing to its respirable and toxic chemical components. There is a dearth of information in South Africa on cancer and non-cancer risks of exposure to heavy metal (HM) content of PM2.5. This study determined the seasonal concentration of HM in PM2.5 and the cancer and non-cancer risks of exposure to HM in PM2.5. Ambient PM2.5 was monitored and samples were collected during the winter and summer months in an industrialized area in South Africa. Concentration levels of nine HMs—As, Cu, Cd, Cr, Fe, Mn, Ni, Pb, and Zn—were determined in the PM2.5 samples using inductive coupled optical emission spectrophotometry. The non-cancer and cancer risks of each metal through the inhalation, ingestion and dermal routes were estimated using the Hazard Quotient and Excess Lifetime Cancer Risk (ELCR), respectively, among infants, children, and adults. Mean concentration of each HM-bound PM2.5 was higher in winter than in summer. The probability of the HM to induce non-cancer effects was higher during winter than in summer. The mean ELCR for HMs in PM2.5 (5.24 × 10−2) was higher than the acceptable limit of 10−6 to 10−4. The carcinogenic risk from As, Cd, Cr, Ni, and Pb were higher than the acceptable limit for all age groups. The risk levels for the carcinogenic HMs followed the order: Cr > As > Cd > Ni > Pb. The findings indicated that the concentrations of HM in PM2.5 demonstrated a season-dependent pattern and could trigger cancer and non-cancer health risks. The formulation of a regulatory standard for HM in South Africa and its enforcement will help in reducing human exposure to HM-bound PM2.5.

scholarly journals Biological Composition of Respirable Particulate Matter in an Industrial Vicinity in South Africa

2019 ◽  
Vol 16 (4) ◽  
pp. 629 ◽  
Author(s):  
Oyewale Morakinyo ◽  
Matlou Mokgobu ◽  
Murembiwa Mukhola ◽  
Tshifhiwa Godobedzha
Keyword(s):  
South Africa ◽  
Particulate Matter ◽  
Health Risks ◽  
Summer Season ◽  
Fusarium Spp ◽  
Adverse Health Outcomes ◽  
Bacteria And Fungi ◽  
Respirable Particulate ◽  
Penicillium Spp ◽  
Bioaerosol Exposure

There is a growing concern that exposure to particulate matter of aerodynamic diameter of less than 2.5 µm (PM2.5) with biological composition (bioaerosols) may play a key role in the prevalence of adverse health outcomes in humans. This study determined the bacterial and fungal concentrations in PM2.5 and their inhalation health risks in an industrial vicinity in South Africa. Samples of PM2.5 collected on a 47-mm glass fiber filter during winter and summer months were analysed for bacterial and fungal content using standard methods. The health risks from inhalation of bioaerosols were done by estimating the age-specific dose rate. The concentration of bacteria (168–378 CFU/m3) was higher than fungi (58–155 CFU/m3). Bacterial and fungal concentrations in PM2.5 were lower in winter than in the summer season. Bacteria identified in summer were similar to those identified in winter: Staphylococcus sp., Bacillus sp., Micrococcus sp., Flavobacterium sp., Klebsiella sp. and Pseudomonas sp. Moreover, the fungal floras identified include Cladosporium spp., Aspergillus spp., Penicillium spp., Fusarium spp. and Alternaria spp. Children inhaled a higher dose of bacterial and fungal aerosols than adults. Bacteria and fungi are part of the bioaerosol components of PM2.5. Bioaerosol exposure may present additional health risks for children.

Vicious Cycle of Economic Growth, Pm2.5 and COVID-19 Case of G7 Countries

2020 ◽  
Author(s):  
Rıdvan Karacan
Keyword(s):  
Economic Growth ◽  
Air Pollution ◽  
Particulate Matter ◽  
Fossil Fuels ◽  
Fine Particulate Matter ◽  
Panel Cointegration ◽  
Air Pollutant ◽  
Population Exposure ◽  
Causality Analysis ◽  
G7 Countries

<p>Today, production is carried out depending on fossil fuels. Fossil fuels pollute the air as they contain high levels of carbon. Many studies have been carried out on the economic costs of air pollution. However, in the present study, unlike the former ones, economic growth's relationship with the COVID-19 virus in addition to air pollution was examined. The COVID-19 virus, which was initially reported in Wuhan, China in December 2019 and affected the whole world, has caused many cases and deaths. Researchers have been going on studying how the virus is transmitted. Some of these studies suggest that the number of virus-related cases increases in regions with a high level of air pollution. Based on this fact, it is thought that air pollution will increase the number of COVID-19 cases in G7 Countries where industrial production is widespread. Therefore, the negative aspects of economic growth, which currently depends on fossil fuels, is tried to be revealed. The research was carried out for the period between 2000-2019. Panel cointegration test and panel causality analysis were used for the empirical analysis. Particulate matter known as PM2.5[1] was used as an indicator of air pollution. Consequently, a positive long-term relationship has been identified between PM2.5 and economic growth. This relationship also affects the number of COVID-19 cases.</p><p><br></p><p><br></p><p>[1] "Fine particulate matter (PM2.5) is an air pollutant that poses the greatest risk to health globally, affecting more people than any other pollutant (WHO, 2018). Chronic exposure to PM2.5 considerably increases the risk of respiratory and cardiovascular diseases in particular (WHO, 2018). For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator" (OECD.Stat).</p>

scholarly journals Exposure to chemical components of fine particulate matter and ozone, and placenta-mediated pregnancy complications in Tokyo: a register-based study

2021 ◽  
Author(s):  
Takehiro Michikawa ◽  
Seiichi Morokuma ◽  
Shin Yamazaki ◽  
Akinori Takami ◽  
Seiji Sugata ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Organic Carbon ◽  
Pregnancy Complications ◽  
Fine Particulate Matter ◽  
First Trimester ◽  
Chemical Components ◽  
Specific Chemical ◽  
Network Database ◽  
Fine Particulate ◽  
Pollutant Concentrations

Abstract Background Maternal exposure to fine particulate matter (PM2.5) was associated with pregnancy complications. However, we still lack comprehensive evidence regarding which specific chemical components of PM2.5 are more harmful for maternal and foetal health. Objective We focused on exposure over the first trimester (0–13 weeks of gestation), which includes the early placentation period, and investigated whether PM2.5 and its components were associated with placenta-mediated pregnancy complications (combined outcome of small for gestational age, preeclampsia, placental abruption, and stillbirth). Methods From 2013 to 2015, we obtained information, from the Japan Perinatal Registry Network database, on 83,454 women who delivered singleton infants within 23 Tokyo wards (≈627 km2). Using daily filter sampling of PM2.5 at one monitoring location, we analysed carbon and ion components, and assigned the first trimester average of the respective pollutant concentrations to each woman. Results The ORs of placenta-mediated pregnancy complications were 1.14 (95% CI = 1.08–1.22) per 0.51 μg/m3 (interquartile range) increase of organic carbon and 1.11 (1.03–1.18) per 0.06 μg/m3 increase of sodium. Organic carbon was also associated with four individual complications. There was no association between ozone and outcome. Significance There were specific components of PM2.5 that have adverse effects on maternal and foetal health.

scholarly journals A cross-sectional study measuring contact patterns using diaries in an urban and a rural community in South Africa, 2018

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jackie Kleynhans ◽  
Stefano Tempia ◽  
Meredith L. McMorrow ◽  
Anne von Gottberg ◽  
Neil A. Martinson ◽  
...  
Keyword(s):  
South Africa ◽  
Age Groups ◽  
Cross Sectional Study ◽  
Rural Site ◽  
Urban Site ◽  
Contact Rate ◽  
Sectional Study ◽  
Cross Sectional ◽  
Contact Rates ◽  
Contact Patterns

Abstract Background Describing contact patterns is crucial to understanding infectious disease transmission dynamics and guiding targeted transmission mitigation interventions. Data on contact patterns in Africa, especially South Africa, are limited. We measured and compared contact patterns in a rural and urban community, South Africa. We assessed participant and contact characteristics associated with differences in contact rates. Methods We conducted a cross-sectional study nested in a prospective household cohort study. We interviewed participants to collect information on persons in contact with for one day. We described self-reported contact rates as median number people contacted per day, assessed differences in contact rates based on participant characteristics using quantile regression, and used a Poisson model to assess differences in contact rates based on contact characteristics within age groups. We also calculated cumulative person hours in contact within age groups at different locations. Results We conducted 535 interviews (269 rural, 266 urban), with 17,252 contacts reported. The overall contact rate was 14 (interquartile range (IQR) 9–33) contacts per day. Those ≤18 years had higher contact rates at the rural site (coefficient 17, 95% confidence interval (95%CI) 10–23) compared to the urban site, for those aged 14–18 years (13, 95%CI 3–23) compared to < 7 years. No differences were observed for adults. There was a strong age-based mixing, with age groups interacting more with similar age groups, but also interaction of participants of all ages with adults. Children aged 14–18 years had the highest cumulative person hours in contact (116.3 rural and 76.4 urban). Conclusions Age played an important role in the number and duration of contact events, with children at the rural site having almost double the contact rate compared to the urban site. These contact rates can be utilized in mathematical models to assess transmission dynamics of infectious diseases in similar communities.

scholarly journals Effect of Different Pollution Parameters and Chemical Components of PM2.5 on Health of Residents of Xinxiang City, China

2021 ◽  
Vol 18 (13) ◽  
pp. 6821
Author(s):  
Shuang Wang ◽  
Mandeep Kaur ◽  
Tengfei Li ◽  
Feng Pan
Keyword(s):  
Particulate Matter ◽  
Carcinogenic Risk ◽  
Water Soluble ◽  
Chemical Components ◽  
Maximum Effect ◽  
Exposure Concentration ◽  
Soluble Ions ◽  
Haze Pollution ◽  
Water Soluble Ions ◽  
Blood Routine

The present study was planned to explore the pollution characteristics, health risks, and influence of atmospheric fine particulate matter (PM2.5) and its components on blood routine parameters in a typical industrial city (Xinxiang City) in China. In this study, 102 effective samples 28 (April–May), 19 (July–August), 27 (September–October), 28 (December–January) of PM2.5 were collected during different seasons from 2017 to 2018. The water-soluble ions and metal elements in PM2.5 were analyzed via ion chromatography and inductively coupled plasma–mass spectrometry. The blood routine physical examination parameters under different polluted weather conditions from January to December 2017 and 2018, the corresponding PM2.5 concentration, temperature, and relative humidity during the same period were collected from Second People’s Hospital of Xinxiang during 2017–2018. Risk assessment was carried out using the generalized additive time series model (GAM). It was used to analyze the influence of PM2.5 concentration and its components on blood routine indicators of the physical examination population. The “mgcv” package in R.3.5.3 statistical software was used for modeling and analysis and used to perform nonparametric smoothing on meteorological indicators such as temperature and humidity. When Akaike’s information criterion (AIC) value is the smallest, the goodness of fit of the model is the highest. Additionally, the US EPA exposure model was used to evaluate the health risks caused by different heavy metals in PM2.5 to the human body through the respiratory pathway, including carcinogenic risk and non-carcinogenic risk. The result showed that the air particulate matter and its chemical components in Xinxiang City were higher in winter as compared to other seasons with an overall trend of winter > spring > autumn > summer. The content of nitrate (NO3−) and sulfate (SO42−) ions in the atmosphere were higher in winter, which, together with ammonium, constitute the main components of water-soluble ions in PM2.5 in Xinxiang City. Source analysis reported that mobile pollution sources (coal combustion emissions, automobile exhaust emissions, and industrial emissions) in Xinxiang City during the winter season contributed more to atmospheric pollution as compared to fixed sources. The results of the risk assessment showed that the non-carcinogenic health risk of heavy metals in fine particulate matter is acceptable to the human body, while among the carcinogenic elements, the order of lifetime carcinogenic risk is arsenic (As) > chromium(Cr) > cadmium (Cd) > cobalt(Co) > nickel (Ni). During periods of haze pollution, the exposure concentration of PM2.5 has a certain lag effect on blood routine parameters. On the day when haze pollution occurs, when the daily average concentration of PM2.5 rises by 10 μg·m−3, hemoglobin (HGB) and platelet count (PLT) increase, respectively, by 9.923% (95% CI, 8.741–11.264) and 0.068% (95% CI, 0.067–0.069). GAM model analysis predicted the maximum effect of PM2.5 exposure concentration on red blood cell count (RBC) and PLT was reached when the hysteresis accumulates for 1d (Lag0). The maximum effect of exposure concentration ofPM2.5 on MONO is reached when the lag accumulation is 3d (Lag2). When the hysteresis accumulates for 6d (Lag5), the exposure concentration of PM2.5 has the greatest effect on HGB. The maximum cumulative effect of PM2.5 on neutrophil count (NEUT) and lymphocyte (LMY) was strongest when the lag was 2d (Lag1). During periods of moderate to severe pollution, the concentration of water-soluble ions and heavy metal elements in PM2.5 increases significantly and has a significant correlation with some blood routine indicators.

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