Journal of Research in Environmental Science and Toxicology

Abstract

The majority of studies on the health effects of air pollution are based on outdoor ambient exposures, primarily due to the need to support emission control programs and the availability of population-based data. On the other hand, there is a sizable body of research on indoor air quality that focuses more on personal exposures. This assessment focuses on the effects of fine particles to combine these two aspects of pollution-related health effects. However, the fundamental ideas can be applied to any pollutant. The goals are to figure out how sensitive epidemiological studies are to including personal exposure information and how much data is needed to do so. Polluted outdoor air and a variety of indoor sources contribute to indoor air pollution, with environmental tobacco smoke (ETS) probably being the most toxic and widespread. There are sufficient data on air infiltration from the outside, but there are insufficient data on indoor sources and effects, and all of these data are based on surveys of small samples of individual buildings. Probabilistic methods must be used to aggregate these data because epidemiology is based on populations. Additionally, accurate estimates of the quality of the air in the surrounding area are required. In this paper, ranges of outdoor air quality, variable infiltration rates, and ranges of indoor source strength are used to generate hypothetical personal exposures. Two kinds of mortality studies are used to examine these uncertainties: cross-sectional analysis of annual mortality rates among locations and time series analysis of daily deaths in a given location. Using quasi-Monte Carlo techniques, effects on dose-response functions are examined using regressions of simulated mortality on personal exposures, which are affected by all of these uncertainties. The working hypothesis is that long-term cross-sectional studies are the only ones that can use indoor sources because they stay relatively constant over time. The simulated mortality regression coefficients are diminished by exposure uncertainty; The effects of "true" and hypothesized exposures are compared using correlations. Both types of simulated mortality studies have similar regression coefficient attenuation for a given level of exposure uncertainty; however, because cross-sectional studies use indoor sources, they are more sensitive, to the point where regression coefficients may be driven to zero. The distribution of indoor sources across cities, particularly for ETS, is the most pressing requirement for data confirmation.

Keywords

Enrichment factor (EF), Trace elements, Power plants, Chemical fractionation, Principal component analysis (PCA)

INTRODUCTION

Particulate matter (PM) is one of the most dangerous pollutants in the atmosphere. Due to their impact on visibility and climate change, ambient particles have a significant impact on air quality. The combustion processes of fossil fuels are the primary anthropogenic sources of fine particles.

The fate of potentially harmful trace elements in coalfired power plants has piqued the interest of researchers in recent years. As, Be, Cl, Cr, Cd, Co, Hg, Mn, Ni, Pb, Sb, and Se have been identified as posing a threat to human health (Hazardous Air Pollutants, or HAPs). These elements fell into one of the following categories according to the International Agency for Research on Cancer (IARC). Group 1: agents that can cause cancer in humans, like As, Be, Cr, Cd, and Ni; group 2: Cl, Co, and Pb, substances likely to cause cancer in humans; and group three: unable to be classified as human carcinogenic—Se. The elements Hg, Mn, and Sb are poisonous. Sb is also thought to be cancer-causing (Albert Mathieu et al., 2017).

Currently, electrostatic precipitators with a high retention efficiency (>99.9%) are installed in all Poland's power plants. The amount of ambient total suspended particulates (TSP) is now largely attributable to fly ash that escapes power plant electrostatic precipitators. Due to their low charging efficiency, fine particles may still penetrate up to 15%. Consumption issues related to air quality in the vicinity of coal combustion sources will get worse due to the high rate of coal (Anspach Renee R et al., 1988).

Coal-based global industry and energy production are significant contributors to air pollution. Municipal and traffic emissions, domestic coal burning, vegetative burning (wood combustion and agricultural burns), open-air refuse burning, and re-suspension of dust were among the other significant contributors (Bassett Andrew Mark et al., 2018)( Beagan Brenda L et al., 2000).

There are three general trends in the distribution of trace elements during the combustion of coal: waste gas, solid waste, and fly ash The properties of trace compounds and the effectiveness of dust control systems have an impact on the streams. According to other studies, the fly ash produced by coal combustion processes primarily contains Cr, Cu, Mn, Ni, Pb, and Zn among the trace elements released by power plants.

DISCUSSION

Typically, elemental associations with various fractions are determined through partial and sequential extractions. In a review by Smichowski et al., some fractionation schemes for airborne particulate matter (APM) were summarized. 18]. A modified Tessier's scheme for chemical extraction that was optimized by Fernandez-Espinosa et al. was derived for our work. This method of extraction was chosen because it is better suited for filter-collected fine urban particles and provides conditions that are closer to the deposition and solubilization processes that take place in the human lung. Four fractions are distinguished by the element's mobility in the scheme (Table 1). The first fraction, F1, is highly mobile and water-soluble; The second, F2, is mobile but bound to carbonates, oxides, and metals that can be reduced. The third, F3, is less mobile and is bound to organic matter, oxidizable metals, and sulfides; the fourth is residual and is not mobile; it is permanently linked to minerals. One of the most effective strategies for predicting the conditions under which ecosystem contamination can occur is currently a quantitative evaluation of these forms known as fractionation analysis ( Beagan Brenda et al., 2000).

There is still a very limited amount of scientific data on the chemical composition of PM1, including fractionation analyses of trace elements. This is a consequence of the specialized troubles of an examination, test assortment and furthermore, more as of late, an absence of point by point meaning of the logical points of fractionation research.

In particular, the following components are included in this paper: 1) a comparison of the levels of PM1 in the vicinity of four distinct operating power plants; ( 2) a chemical fractionation of the PM1 containing the trace elements As, Cd, Co, Cr, Hg, Mn, Ni, Pb, Sb, and Se, which were collected from locations close to the chosen power plants; ( 3) a statistical examination of the correlation coefficients to demonstrate the connection between the enrichment factors (EF) and the trace elements; and (4) a principal component analysis (PCA) to find out where these elements might come from in this area.

The sampling locations were in the southern part of Poland. Three of them, P1, P3, and P4, are located in Upper Silesia's industrial macroregion, while P2 is approximately. 70 kilometers from the macroregion in the west. The study area and sampling locations in the vicinity of the four chosen power plants are depicted (Betancourt Joseph R et al., 2006). The first location, designated as P1 in Golejów (50°08,37.87 N; 18°32'15.76' E), is in a Rybnik neighborhood that is close to a power plant with 1775 MW of installed capacity. There are 2300 people living in Location P1. The second point, designated P2, is located at 50°45,35,41 N. 17°56'20.43' E), is in the rural area of the village of Wärkle, close to a power plant with 1492 MW of capacity. "Wierkle" is in the Gmina Dobrze Wielki administrative district, which is in Opole County, Opole Voivodship. It is a village with 520 people living there. The third point, designated P3 (50°12,33.46 N), 19°28,28.77 E), is in a rural area of the village of Czyówka, close to a power plant with a 786 MW capacity. Czyówka is a village in Chrzanów County, Lesser Poland Voivodship, that is located in the administrative district of Gmina Trzebinia. There are 702 people living in the village. The fourth point, designated P4 (50°13,48.90 N), 19°13'24.45' E), is in the Jaworzno city suburb near a power plant with 1345 MW of installed capacity. Near Katowice, the city of Jaworzno has a population of 95,500 people (Bleakley Alan et al., 2008).

P1 had the highest average PM1 concentration of 12.78 g/m3. Meanwhile, the average PM1 concentrations at the other sampling points ranged from 8.13 to 8.74 g/ m3. The sum of the four fractions that represent the total concentration of metal in the submicron particles is shown in Table 3. Additionally, the range of the lowest and highest concentrations is shown. As, Cr, and Pb—all of which are known to cause cancer in humans—had the highest concentrations among the trace elements gathered at all of the locations. As, Cr, Pb, Mn, Se, Ni, Sb, Cd, Hg, and Co are the most likely carcinogenic and toxic elements in relation to the average total content. However, there is currently no global regulation regarding a submicron particulate PM1 standard for ambient air. Primary particles produced by combustion result in the formation of atmospheric particles smaller than 1 m (Bochatay Naïke et al., 2020). There are two modes of this particle size fraction: the nucleation mode (combustion engine vehicle particles) and the accumulation mode (photochemical smog particles and combustion). Submicron particles cannot be effectively controlled by the existing standards for ambient air quality, which are limited to mechanically produced PM2.5 and PM10 fractions. The distinction between the effects of PM2.5 and PM1 aerosol sources demonstrates that PM1 can provide a more accurate estimation of anthropogenic particles (Braun Lundy et al., 2017).

CONCLUSION

Coal combustion is one of the primary sources of power all over the world. The fate of human-hazardous trace elements in coal-fired power plants requires scientific attention. Submicron particles collected in the vicinity of hard coal-fired power plants in southern Poland were the subject of this investigation. These included mobility, trace element composition, and concentration. Additionally, source identification was the subject of this study. PM1 concentrations ranged on average from 8.13 to 12.78 g/m3.

Information on the total content of trace elements in PM1 is necessary but insufficient for determining the overall levels of pollution and danger. The four fractions were separated using sequential chemical extraction (highly mobile—F1; mobile—F2; not mobile (F4) and less mobile (F3) Cd, Mn, and Sb were the highly mobile elements (F1) that were particularly harmful to humans. In both the highly mobile and mobile fractions (F1 and F2), only Pb showed a high distribution. While the not mobile fraction (F4) contained the majority of As, Co, Cr, Hg, Ni, and Se, As, Cd, Sb, and Se had enrichment factors greater than 100, indicating that they played a significant role in anthropogenic sources. Cr, Hg, and Pb were enriched in a moderate way. Ni can come from soil or road dust resuspension, as well as mixed anthropogenic and geogenic sources, according to EF 20. Co, on the other hand, is thought to mostly come from crust.

PCA was used to identify sources first for each fraction separately, then for all fractions. Three significant sources of trace elements were identified based on the highest PCA loading: combustion of fossil fuels, mixed anthropogenic and crustal sources, and vehicle emissions

For improved exposure-related health risk assessments, the findings also emphasize the significance of further research into submicron and fine particle-bound elements in PM typical of industrial sources (such as power and coking plants).

ACKNOWLEDGEMENT

None

CONFLICT OF INTEREST

None