Dust Pollution Research Articles

Risk Factors and Preventive Measures for Cardiovascular Diseases.

Background: Cardiovascular diseases are the most frequent cause of death worldwide. The aim of this study was to identify and demonstrate correlations between mortality data and etiological factors in EU countries. The relationships presented could thus provide a better understanding of etiological factors and possible points for interventions to prevent cardiovascular diseases. The focus was on the following diseases: hypertensive heart disease, atrial flutter/atrial fibrillation, myocardial infarction, and ischemic heart disease, as well as heart failure. Methods: The data in this study come from WHO databases. Connections between the mortality rates and the possible influencing factors were analyzed. The significant factors from the correlation analysis were simultaneously evaluated using a stepwise multiple regression analysis. Results: Analysis of hypertensive heart disease in women reveals the following factors to be significant: drug expenses, health expenses on gross domestic product, and smoking. For men, population density, first admission to a drug treatment center, and drug expenses per person emerged as important factors. Admission to drug treatment centers and length of hospitalization were significant factors for atrial fibrillation and flutter. Fine dust pollution was the most important factor in heart failure. The most important influencing factor for myocardial infarction and ischemic heart disease is nitrogen dioxide concentration. For women, the second highest value is health expenses, followed by the number of outpatient contacts per year. For men, outpatient contacts are in second place. Conclusions: Prevention measures must be taken by the government. The extent to which population density has an influence on cardiovascular diseases should be examined in more detail. In order to reduce the number of initial admissions to drug treatment centers, behavioral prevention related to drug use could be improved.

Concentration, Pollution Level, and Sources of Heavy Metals from Household Dust in Ramadi City, Iraq

Researchers and environmental managers have been interested in household dust pollution because exposure to heavy metals has a detrimental effect on health. This study aims to determine heavy metals concentrations (Cd, Cr, Cu, Ni, Pb and Zn), pollution level, and their potential sources in the household dust of Ramadi City, Iraq. The dust was collected from 35 houses. The atomic absorption spectrophotometry method was used to measure concentrations of heavy metals in the dust. The following was the order of the heavy metal mean concentration: Zn > Ni > Cu > Pb > Cr > Cd. These metals’ mean concentrations are below background guidelines. The descending order of the EF values for the measured metals is as follows: Ni (6.35) > Cu (5.40) > Pb (1.53 > Cr (1.24) > Zn (1.14) > Cd (0.84). Results of the calculation of CF for metals measured in house dust in Ramadi City showed values of less than 1 (CF < 1 indicating a minimum contamination level. Based on the results of multivariate statistics (correlation matrix, cluster and principle components analysis), sources of Cr, Cu, Ni and Zn are indoor anthropogenic sources while the sources of Cd and Pb are outdoor anthropogenic.

Characteristics of fine dust pollution PM₂.₅ in Hanoi in 2021

Fine particulate matter (PM2.5) is one of the most dangerous pollutions in the atmosphere in the Hanoi capital. PM2.5 fine dust pollution characteristics in Hanoi in the duration from 5/2021 to 3/2022 have been studied. The concentration of main chemical elements (such as As, Br, Ca, Cd, Ce, Cl, Cu, Fe, K, Mn, Pb, S, Sr, Ti, Zn, Zr…), main water-soluble ions (such as Na+, NH4+, K+, Mg2+, Ca2+, SO42-, Cl-, NO3-, F-, NO2-) and black carbon (BC) in the PM2.5 sample have been analyzed. The average PM2.5 fine dust concentration was (78.09 ± 51.71) µg/m3 and ranged from 17.55 to 271.39 µg/m3. PM2.5 tends to increase and is about 3.12 times larger than Who Air Quality Guidelines 2005 (25 µg/m3 for PM2.5 24h). The average PM2.5 concentration in the rainy season from 5/2021 to 9/2021 was (51.97 ± 16.40) µg/m3. This value for the dry season from 10/2021 to 3/2022 was (104.70 ± 61.19) µg/m3. It is much higher than that in the rainy season about 2.01 times. The major contributors were the secondary components such as NH4+, SO42-, NO3- and BC... The main pollution contribution sources and the potential pollution areas map have been identified. This research shows a worrying picture of fine dust PM2.5 in Hanoi in the studying duration.

Prediction of Dust Emissions in Highway Subgrade-Filling Construction Based on Deep Neural Network

Dust pollution can harm the urban environment and the health of citizens. Each stage in highway construction generates unorganized dust emissions to varying degrees, which complicates their quantification. To precisely forecast dust emissions during the construction of highway subgrades and reduce the associated pollution risks, this study introduces a predictive model based on a deep neural network (DNN) for dust emissions during highway subgrade-filling operations. Dust concentration is treated as a nonlinear multivariate problem, with predictive indicators encompassing particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), ground surface temperature, wind speed, air temperature, surface pressure, and relative humidity. Using a DNN model, this study forecasts the concentrations of PM2.5 and PM10 at highway construction sites. Based on a highway project in Hebei Province, this study predicts dust-emission concentrations via field monitoring conducted using self-developed equipment. The model’s predictions exhibit a small mean-absolute-percentage error and root-mean-square error compared with the actual values, and the model’s accuracy significantly surpasses that of conventional regression models. Accurate forecasting can facilitate the timely control of dust concentrations at construction sites, thus facilitating more environmentally friendly and efficient construction. Doi: 10.28991/HIJ-2024-05-02-03 Full Text: PDF

Assessing the Air Pollution Tolerance Index of Urban Plantation: A Case Study Conducted along High-Traffic Roadways

Road transport and traffic congestion significantly contribute to dust pollution, which negatively impacts the growth of roadside plants in urban areas. This study aims to quantify the air pollution tolerance index (APTI) and analyze the impacts of dust deposition on different plant species and trees planted along a busy urban roadside in Lahore, Pakistan by considering seasonal variations. The APTI of each species is determined based on inputs of various biochemical parameters (leaf extract pH, ascorbic acid content, relative water content, and total chlorophyll levels), including dust deposition. In this study, laboratory analysis techniques are employed to assess these factors in selected plant species such as Mangifera indica, Saraca asoca, Cassia fistula, and Syzygium cumini. A statistical analysis is conducted to understand the pairwise correlation between various parameters and the APTI at significant and non-significant levels. Additionally, uncertainties in the inputs and APTI are addressed through a probabilistic analysis using the Monte Carlo simulation method. This study unveils seasonal variations in key parameters among selected plant species. Almost all biochemical parameters exhibit higher averages during the rainy season, followed by the summer and winter. Conversely, dust deposition on plants follows an inverse trend, with values ranging from 0.19 to 4.8 g/cm2, peaking during winter, notably in Mangifera indica. APTI values, ranging from 9.39 to 14.75, indicate varying sensitivity levels across species, from sensitive (Syzygium cumini) to intermediate tolerance (Mangifera indica). Interestingly, plants display increased tolerance during regular traffic hours, reflecting a 0.9 to 5% difference between the APTI at peak and regular traffic hours. Moreover, a significant negative correlation (−0.86 at p < 0.05 level) between APTI values and dust deposition suggests a heightened sensitivity to pollutants during the winter. These insights into the relationship between dust pollution and plant susceptibility will help decision makers in the selection of resilient plants for urban areas and improve air quality.

Investigation of glycine leaching for gold extraction from Witwatersrand gold mine tailings with permanganate pre-treatment

The Southern African region contains abundant gold tailing heaps that are an environmental concern due to dust pollution and chemical contamination of nearby water bodies. Nevertheless, these heaps contain gold with potential to be extracted for financial gain. In this study, the feasibility of extraction of gold from a Witwatersrand gold tailings using glycine was investigated using a two-level full factorial design. Effects of variables such as glycine concentration at levels of 0.5-1.5 M with a solid-liquid ratio of 50-200 g/L were investigated. Although the solid-liquid ratio used in this study was below the industrial norm, it provides a starting point for investigating the applicability of this technology. To enhance the gold extraction, potassium permanganate pretreatment and copper ion addition were adopted. The results revealed that 91.4% gold extraction was achieved after 24 h pre-treatment of the tailings using 2 g/L potassium permanganate followed by subsequent leaching using 1.5 M glycine at pH 12, with 50 g/L solid-liquid ratio and 2 g/L copper ions. Statistically, the solid-liquid ratio and potassium permanganate pre-treatment of the tailings were found to be significant at 95% confidence interval, whilst interactions of copper ions and glycine concentration were significant factors. The work demonstrates that potassium permanganate pre-treatment prior to glycine leaching of low-grade secondary gold resources, such as tailings, can be beneficial. Furthermore, the methodology developed in this work provides an opportunity for further investigation of the recovery of gold hosted in complex mineralogical matrices.

A comprehensive evaluation method for dust pollution: Digital image processing and deep learning approach

Dust pollution poses a grave threat to both the environment and human health, especially in mining operations. To combat this issue, a novel evaluation method is proposed, integrating grayscale average (GA) analysis and deep learning (DL) in image classification. By utilizing a self-designed dust diffusion simulation system, 300 sample images were generated for analysis. The GA method establishes a correlation between grayscale average and dust mass, while incorporating fractal dimension (FD) enhances classification criteria. Both GA and DL methods were trained and compared, yielding promising results with a testing accuracy of 92.2 % and high precision, recall, and F1-score values. This approach not only demonstrates efficacy in classifying dust pollution but also presents a versatile solution applicable beyond mining to diverse dust-contaminated work environments. By combining image processing and deep learning, it offers an automated and reliable system for environmental monitoring, thereby enhancing safety standards and health outcomes in affected industries. Ultimately, this innovative method signifies a significant advancement towards mitigating dust pollution and ensuring sustainable industrial practices.

Study on the Law of True Triaxial Hydraulic Fracturing by Acoustic Emission Monitoring.

Hydraulic fracturing generates fractures in a coal seam, which has been extensively used in coal mining and disaster management. To study the influences of water injection pressure and time on the propagation of hydraulic fracture, we conducted true triaxial hydraulic fracturing experiments under acoustic emission monitoring. Five briquette specimens were prepared by molding the mixture of coal powder, cement, river sand, and distilled water under 60 MPa to simulate the properties of coal seam. True triaxial loading was used to simulate the in situ stress environment of the coal seam. Hydraulic fracturing experiments on the test specimens were conducted under different water injection pressures and times. The following conclusions have been drawn. At the fixed injection time, increasing water injection pressure promotes the propagation of hydraulic fracture and the migration of water in the coal seam after the fractures are connected. The number of fractures increases from 3 to 8 as the water injected pressure increased from 3 to 9 MPa. Under the constant water injection pressure, the increase in longitudinal wave velocity in the test specimen decreases with the prolongation of water injection time. When the water reaches the action boundary of the water injection pressure, the water stops moving. At this moment, the water injection time has no effect on the longitudinal wave velocity anymore. The fracturing influence range can be increased by increasing the water injection pressure to produce a fracture network of a large radius with many fractures. Appropriately prolonging hydraulic fracturing time can ensure that the fracturing fluid fully moistens the coal seam and thus effectively reduces dust pollution.

Study on preparation and properties of mineral compound suppressant

To address the problem of coal mine dust pollution, the performance characterisation method was used to optimise the C3 dust suppressor. On this basis, two dust suppressants suitable for different climatic conditions were prepared by adding 8 groups of OP-10 and SDS surfactants with different concentrations, namely D5, which is suitable for dry areas and has excellent permeability, and E6, which is suitable for wet areas and has excellent resistance to rain erosion. The results show that compared with single dust suppressant, D5 with 0.5% OP-10 and E6 with 0.6% SDS have neutral PH, the rate of wind erosion is lower than 0.2% at 20 m/s, and the cured layer shell is well preserved with good wettability, adhesion and curability. Observed by scanning electron microscope (SEM), the coal dust particles bonded tightly after spraying D5 and E6, which could effectively improve the dust suppression efficiency.

Dust Pollution in Urban Areas: Current Trends and Implications for Human Health and Outdoor Physical Activities

Dust Pollution in Urban Areas: Current Trends and Implications for Human Health and Outdoor Physical Activities

Sustainable Livestock Production: Screening Analysis and Pilot Implementation of a Biofilm in Piggery Biofilters for Mitigation of Ammonia and Hydrogen Sulfide Emissions

One of the most noticeable problems associated with the close location of piggeries is gaseous compounds emission. Ammonia and hydrogen sulfide emissions affect the quality of life of people living in the vicinity of such facilities. Among the diverse methods for managing and controlling malodorous substances, biological methods, which involve the utilization of microbiological agents, are widely employed. The use of bacterial strains is a relatively simple, low-cost, and ecological method. The study aimed to conduct a preliminary evaluation of the implementation of a novel consortium of deodorizing bacteria. The study involved the selection of bacteria, assessment of the antagonistic properties, implementation of the inoculum in a mesh-filled biofilter, and analysis of ammonia, hydrogen sulfide, and fine dust content in the air before and after passing through the mature biological bed. The results obtained demonstrate the effectiveness of the biofiltration bed in reducing ammonia levels, with a maximum decrease observed at 73.90%. For hydrogen sulfide, a removal efficiency of >72.08% was observed. Reduction in fine dust pollution also decreased from a level of 3.75 mg/m3 to 1.06 mg/m3. The study’s findings demonstrate the promising potential of utilizing a consortium of deodorizing bacteria as an effective approach to mitigating emissions from piggeries.

Law of respirable dust pollution induced by cutting-advancing support in a fully mechanized mining face and spatial stereoscopic dust control and removal technology

Law of respirable dust pollution induced by cutting-advancing support in a fully mechanized mining face and spatial stereoscopic dust control and removal technology

Research on the Dust Transport Law in Large Mining Height Fully Mechanized Mining Face

The fully mechanized mining face with high mining height has always been a high-risk area for coal mine dust pollution. In order to further understand the spatiotemporal transport law of dust in the zoning of the high mining height fully mechanized mining face, the 122109 high mining height fully mechanized mining face of Caojiatan Coal Mine was taken as the research object. Numerical simulation method was used to simulate and analyze the dust transport situation of the 122109 fully mechanized mining machine drum single dust source, the hydraulic support moving frame single dust source, and the superposition of all dust sources in forward and backward wind cutting coal. The research results can guide the ventilation layout design in the early stage of the mine and the dust control in the comprehensive mining process, which is of great significance for the construction of safe and green mines.

Phytoncidal activity of the needles of Juniperus L. representatives in the technogenic conditions of the city of Dnipro

The territory of the Dnipro urban agglomeration is one of the most polluted in Ukraine. The high concentration of industrial enterprises, roads, density of residential buildings and urban population are factors of anthropogenic pressure on urban ecosystems that significantly affect the quality of the habitat of living organisms and human life. Therefore, an urgent problem of modern urban planning and urban amenities is compliance with sanitary requirements for landscaping residential and industrial areas. The creation of decorative compositions with a predominance of tree and shrub species ensures the landscape attractiveness of the city, reduces the level of noise and dust pollution, improves temperature and wind conditions, improves public health by normalizing the psychological state of people and purifying the city air with phytoncides of plants, especially conifers. Taking into account the high decorative qualities and resistance of junipers to adverse climatic conditions, the aim of the study was to analyze the annual dynamics of phytoncidal activity of Juniperus media V. D. Dmitriev «Blue gold» and J. sabina L. «Tamariscifolia» needles in conditionally clean and polluted by vehicle emissions areas of Dnipro city. The plant material was collected at 4 monitoring points in Dnipro, 1 was a conditional control, and the other 3 were experimental plots with different levels of vehicle traffic. Needles were sampled at all periods of shoot ontogeny. The phytoncidal activity was determined by the method of «steaming» microbial test cultures with volatile needle secretions on test cultures of Staphylococcus epidermidis, Staphylococcus aureus, Micrococcus sp., Bacillus subtilis, Esherechia coli, Pseudomonas fluorescens, Candida albicans. The results of the study show that the dynamics of phytoncidal activity of J. media and J. sabina needles during the year is the same in plants growing in a conditionally clean area and under the influence of motor vehicle traffic: the amount of released phytoncides increases in spring, during the period of intensive shoot growth, reaches a maximum at the stage of slowing down their growth (in summer), decreases in autumn, with the cessation of growth processes, and is minimal in winter, when there is no shoot growth. It has been shown that in a clean area, needle extracts of both representatives of the genus Juniperus have the greatest inhibitory effect on the growth of S. aureus colonies, and under the influence of vehicle emissions, the phytoncidal activity is highest against S. aureus and S. epidermidis strains. It was found that out of the two studied representatives of the genus Juniperus, J. media has the highest stability of the ability to secrete phytoncides under conditions of motor vehicle traffic load, which we recommend for use in urban landscaping.

Carbon based sensors for air quality monitoring networks; middle east perspective.

IoT-based Sensors networks play a pivotal role in improving air quality monitoring in the Middle East. They provide real-time data, enabling precise tracking of pollution trends, informed decision-making, and increased public awareness. Air quality and dust pollution in the Middle East region may leads to various health issues, particularly among vulnerable populations. IoT-based Sensors networks help mitigate health risks by offering timely and accurate air quality data. Air pollution affects not only human health but also the region's ecosystems and contributes to climate change. The economic implications of deteriorated air quality include healthcare costs and decreased productivity, underscore the need for effective monitoring and mitigation. IoT-based data can guide policymakers to align with Sustainable Development Goals (SDGs) related to health, clean water, and climate action. The conventional monitor based standard air quality instruments provide limited spatial coverage so there is strong need to continue research integrated with low-cost sensor technologies to make air quality monitoring more accessible, even in resource-constrained regions. IoT-based Sensors networks monitoring helps in understanding these environmental impacts. Among these IoT-based Sensors networks, sensors are of vital importance. With the evolution of sensors technologies, different types of sensors materials are available. Among this carbon based sensors are widely used for air quality monitoring. Carbon nanomaterial-based sensors (CNS) and carbon nanotubes (CNTs) as adsorbents exhibit unique capabilities in the measurement of air pollutants. These sensors are used to detect gaseous pollutants that includes oxides of nitrogen and Sulphur, and ozone, and volatile organic compounds (VOCs). This study provides comprehensive review of integration of carbon nanomaterials based sensors in IoT based network for better air quality monitoring and exploring the potential of machine learning and artificial intelligence for advanced data analysis, pollution source identification, integration of satellite and ground-based networks and future forecasting to design effective mitigation strategies. By prioritizing these recommendations, the Middle East and other regions, can further leverage IoT-based systems to improve air quality monitoring, safeguard public health, protect the environment, and contribute to sustainable development in the region.

Optimal Preparation and Performance Study of Eco-Friendly Composite Chemical Dust Suppressants: A Case Study in a Construction Site in Chengdu.

To mitigate dust pollution generated during various stages of construction activities and reduce the environmental and health hazards posed by airborne dust, this study utilized hydroxyethyl cellulose, glycerol, and isomeric tridecyl alcohol polyoxyethylene ether as raw materials to formulate a composite chemical dust suppressant. The properties of the dust suppressant were characterized through analysis. Employing single-factor experiments, the optimal proportions of the binder, water-retaining agent, and surfactant for the composite dust suppressant were determined. Subsequently, a response surface model was established, and, after analysis and optimization, the optimal mass ratios of each component in the composite dust suppressant were obtained. Under optimal ratios, the physicochemical properties and wind erosion resistance of the composite dust suppressant were analyzed. Finally, the practical application of the suppressant was validated through on-site trials at a construction site. This study revealed that the optimal formulation for the dust suppressant was as follows: 0.2% hydroxyethyl cellulose, 2.097% glycerol, 0.693% isomeric tridecyl alcohol polyoxyethylene ether, and the remainder was pure water. The suppressant is non-toxic, non-corrosive, environmentally friendly, and exhibits excellent moisture retention and bonding properties compared to water. The research findings provide valuable insights for addressing dust pollution issues on construction sites.

Enhancing Mechanical Properties and Microstructures of Mass-Manufactured Sand Concrete by Incorporating Granite Powder.

The production of manufactured sand and stone processing can cause dust pollution due to the generation of a significant amount of stone powder. This dust (mainly granite powder) was collected and incorporated as a cement replacement into mass-manufactured sand concrete in order to enhance the mechanical properties and microstructures. The heat of the hydration was measured by adding the granite powder into the cementitious material system. The mechanical properties, autogenous shrinkage, and pore structures of the concrete were tested. The results showed that the mechanical strength of the concrete increased first and then decreased with the increase in granite powder content. By replacing the 5% cement with the granite powder, the 28 d compressive and flexural strength increased by 17.6% and 20.9%, respectively. The autogenous shrinkage was mitigated by the incorporation of the 10% granite powder and decreased by 19.7%. The mechanism of the granite powder in the concrete was studied by X-ray diffraction (XRD), scanning electron microscopy (SEM), and mercury intrusion porosimetry (MIP). The porosity decreased significantly within the 10% granite powder. A microstructure analysis did not reveal a change in the type of hydration products but rather that the granite powder played a role in the microcrystalline nucleation during the hydration process.

Use of measurement results from a mobile laboratory in the diagnostics of anthropogenic environment - linear ordering of objects using the TOPSIS method

The measurements of the concentrations of gaseous and dust pollutants in the anthropogenic environment are an important element of environmental monitoring and for determining directions of preventive activities in the field of health protection. The article presents the results involving the concentrations of suspended dust and gaseous pollutants in the outdoor air, which were recorded at three measuring stations of air quality in the Silesian and Opole voivodeships (Wodzisław Śląski, Zabrze, Kędzierzyn-Koźle). The results were supplemented with the values recorded by the mobile laboratory located at the Center for Continuing Education - Branch of the Silesian University of Technology in Rybnik. The research results were used for a synthetic assessment of the threat level to the anthropogenic environment. In the computational layer, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was employed, which is included in the group of methods for solving multi-criteria decision-making problems (Multi Attribute Decision Making).

The Ecological Risk Assessment of Foodborne Disease Outbreaks in Yazd Province, Iran

Background: Ecological conditions can change infection routes and increase the risks of outbreaks. The aim of this study is risk assessment of foodborne disease outbreaks based on dispersed regional climatic and demographic variables in Yazd Province, Iran. Methods: In this cross-sectional study, data of temporal climatic parameters and regional demographic factors linked to bacterial foodborne diseases were addressed. A multi-level regression analysis model was used to detect associations between the risk of outbreaks and ecological risk factors; the relationships were verified using (P<0.05). Results: Significant associations were observed between the outbreaks and age )P<0.001(, community type (P<0.001), temperature (P=0.04), rainfall (P=0.03) and dust pollution (P<0.001) in scattered parts of the province. The maximum rate of outbreaks was seen in spring, while the frequency of the outbreaks increased during April and October, compared to other months of the year (2012–2016). Conclusion: Consequences have revealed interventions of the environmental exposures in transmissions of microbial agents by complex ecological processes that caused the outbreaks.

Experimental study of dust emission intensity from the surface of the alluvium beach

The paper presents data on the current state of waste storage facilities of mining and processing plants in Kryvyi Rih. They are complex, environmentally hazardous hydraulic structures. When assessing the extent of dust pollution from tailing ponds, it is extremely important to know the intensity of dust emissions from the surface of the alluvium beach. This parameter is the basic one in all prognostic models used to predict environmental pollution. The paper presents the results of experimental studies to determine the wind speed at which the removal of dry dust particles from the surface of the beach of a tailing pond begins, as well as the intensity of dust removal from the surface of the beach for dry sand and wet sand. The experimental studies conducted in the laboratory allowed obtaining data on the intensity of dust emission from the surface of the tailing dump beach. The results obtained by the authors make it possible to more accurately assess the degree of environmental dustiness using predictive models. The data on determining the intensity of dust formation for sand of different moisture content will be useful for determining the effectiveness of dust suppression by supplying water to the beach surface.