Dust Levels Research Articles

Analysis of Air and Water Quality at Coal Harbor in Muaro Jambi Regency

Secondary data obtained from the Safety, Health and Environment Department of PT. Winner Prima Sekata (PT. WPS) in Kemingking Dalam Village, Taman Rajo District, Muaro Jambi Regency, in 2022 it was discovered that there were cases of Acute respiratory infections (ARI). Therefore, a study was carried out regarding the analysis of air quality and water quality at the coal port location in Muaro Jambi Regency to determine the extent of the environmental impacts resulting from coal loading and unloading and stockpile activities at the Talang Duku port, Jambi Province. The research was conducted using quantitative survey and descriptive methods. Data analysis is quantitative in nature with the aim of testing predetermined hypotheses. Dust measurement results obtained between 7.98 - 10.00 mg/m3, The allowable dust threshold value is in accordance with the Minister of Manpower Circular Number. SE.01/MEN/1997 concerning the NAB of Chemicals in Workplace Air is 0.9 mg/m. So the dust level in the Muaro Jambi coal port working area exceeds the quality standards set by the Minister of Manpower. Results of calculating the output water pollution index pH and TSS at the PT Outlet point. The WPS of port locations in the period March – June 2023 in each month has a Pij value of 1.08, which means the average pH and TSS value of output water from PT. WPS is at status 1.0 < 1.09 < 5.0 with the description Lightly Polluted. Based on processing with SPSS version 27 using the One way Anova test, it was found that Fcount then H0 was rejected.

Third mortality follow-up of the Mallinckrodt uranium processing workers, 1942–2019

Introduction Mallinckrodt Chemical Works was a uranium processing facility during the Manhattan Project from 1942 to 1966. Thousands of workers were exposed to low-dose-rates of ionizing radiation from external and internal sources. This third follow-up of 2514 White male employees updates cancer and noncancer mortality potentially associated with radiation and silica dust. Materials and methods Individual, annualized organ doses were estimated from film badge records (n monitored = 2514), occupational chest x-rays (n = 2514), uranium urinalysis (n = 1868), radium intake through radon breath measurements (n = 487), and radon ambient measurements (n = 1356). Silica dust exposure from pitchblende processing was estimated (n = 1317). Vital status and cause of death determination through 2019 relied upon the National Death Index and Social Security Administration Epidemiological Vital Status Service. The analysis included standardized mortality ratios (SMRs), Cox proportional hazards, and Poisson regression models. Results Vital status was confirmed for 99.4% of workers (84.0% deceased). For a dose weighting factor of 1 for intakes of uranium, radium, and radon decay products, the mean and median lung doses were 65.6 and 29.9 mGy, respectively. SMRs indicated a difference in health outcomes between salaried and hourly workers, and more brain cancer deaths than expected [SMR: 1.79; 95% confidence interval (CI): 1.14, 2.70]. No association was seen between radiation and lung cancer [hazard ratio (HR) at 100 mGy: 0.93; 95%CI: 0.78, 1.11]. The relationship between radiation and kidney cancer observed in the previous follow-up was maintained (HR at 100 mGy: 2.07; 95%CI: 1.12, 3.79). Cardiovascular disease (CVD) also increased significantly with heart dose (HR at 100 mGy: 1.11; 95%CI: 1.02, 1.21). Exposures to dust ≥23.6 mg/m3-year were associated with nonmalignant kidney disease (NMKD) (HR: 3.02; 95%CI: 1.12, 8.16) and kidney cancer combined with NMKD (HR: 2.46; 95%CI: 1.04, 5.81), though without evidence of a dose-response per 100 mg/m3-year. Conclusions This third follow-up of Mallinckrodt uranium processors reinforced the results of the previous studies. There was an excess of brain cancers compared with the US population, although no radiation dose-response was detected. The association between radiation and kidney cancer remained, though potentially due to few cases at higher doses. The association between levels of silica dust ≥23.6 mg/m3-year and NMKD also remained. No association was observed between radiation and lung cancer. A positive dose-response was observed between radiation and CVD; however, this association may be confounded by smoking, which was unmeasured. Future work will pool these data with other uranium processing worker cohorts within the Million Person Study.

Bacterial contamination of coffee and personal exposure to inhalable dust and endotoxin in primary coffee processing factories in Ethiopia.

Endotoxins from gram-negative bacteria might be released when the coffee cherries are processed and may cause respiratory health problems among workers in the coffee industry. The relationship between bacterial contamination and occupational exposure to endotoxin levels has not been thoroughly explored previously in primary coffee processing factories in Ethiopia, or elsewhere. The aim of this study was to characterize the level of personal endotoxin exposure and its relations with bacterial contamination of coffee cherries in such factories in Ethiopia. A cross-sectional study was conducted from March 2020 - February 2021 in 9 primary coffee processing factories in 3 regions in Ethiopia. A total of 180 personal air samples were collected to analyze workers' exposure to inhalable dust and endotoxin. Correlation tests were performed to assess the relationship between total bacteria and endotoxin levels and between inhalable dust and endotoxin levels. The geometric mean (GM) of personal inhalable dust exposure among machine room workers and hand pickers were 9.58mg/m3 and 2.56mg/m3, respectively. The overall GM of endotoxin exposure among machine room workers and hand pickers were 10,198 EU/m3 and 780 EU/m3, respectively. Gram-negative bacteria were found in all 54 coffee samples. The correlation between inhalable dust and endotoxin exposure was significant (r=0.80; P <0.01). About 92% of the samples from hand pickers and all samples from machine room workers exceeded the occupational exposure limit of 90 EU/m3 recommended by the Dutch Expert Committee on Occupational Standards. Prevention and control of bacterial contamination of the coffee in primary coffee processing are suggested to reduce endotoxin exposure that might cause respiratory health problems among coffee workers.

A new imputation method for population mean in the presence of missing data based on a transformed variable with applications to air pollution data in Chiang Mai, Thailand

Introduction: Chiang Mai’s air pollution has risen to number one in the world for the highest level of fine particulate matter which further exacerbates the damage to human health. Fine particulate matter can enter the human body and blood circulation, destroying organ systems, increasing the risk for chronic disease and cancer, despite not having smoking habits or other morbidities. The Thai government must sort out this issue before it is too late as the whole nation’s health is at risk due to excessive dust levels higher than standard guidelines. Collection of pollution data can help us to come up with solutions and prevent it from turning into a hazardous situation. Unfortunately, pollution data are missing and need to be dealt with before analysis to obtain accurate results. Materials and methods: A new method of imputation for estimating population mean based on a transformed variable has been suggested under simple random sampling without replacement and the uniform nonresponse mechanism. The bias and mean square error of the proposed estimator are investigated up to the first order of approximation. The performance of the proposed estimator is studied via applications to air pollution data in Chiang Mai, Thailand. Results: The proposed estimator shows the best performance, giving the least bias and mean square error for all levels of sampling fractions. For the results from application the estimated value of sulfur dioxide from Particulate Matter 2.5 (PM2.5), the Percentage Relative Efficiency (PRE) is higher than all existing estimators by at least 16%. For the estimated PM2.5 from PM10 the PRE is higher than all existing estimators by at least 1600%, an extremely significant difference exhibiting similarity to real values. Conclusion: The proposed imputation technique based on the transformed auxiliary variable can be helpful for imputing missing values and improving the efficiency of the estimators.

Health Risk Assessment of Inhalable Dust Exposure during the Welding and Grinding Process of Subway Aluminum Alloy Components

The subway factory industry is developing rapidly in China, but there are some occupational health risk assessments of inhalable dust in this industry. Therefore, this study aimed to explore the contamination level and health risks of dust in an aluminum alloy body workshop of subway factories in Hunan Province, China. A total of 160 dust samples were collected from the welding and grinding areas. The main elements of PM10 were analyzed. The health risks of aluminum dust and PM2.5 were evaluated. The Monte Carlo method was adopted to compare the sensitivity of the Hazard Quota (HQ) of aluminum dust and carcinogenic risk (CR) of PM2.5 to the exposure parameters for workers. The results showed that the PM10 concentration in the grinding area was higher, while the PM2.5 concentration in the welding area was higher. The metal element with a mass fraction of 27.7% was aluminum. In both areas, the probability of the aluminum dust HQ exceeding 1 was approximately 17% and 68%, respectively. The PM2.5 CR exceeded the acceptable upper limit value (1.0 × 10−4). The main risk factor of aluminum dust HQ was concentration, while the main risk factors of PM2.5 CR were concentration and exposure duration. These findings provide basic data for enhancing health risk management in the subway industry.

Rapid estimation of tire-wear particle concentration in road dust using PM10 and traffic data in a ternary plot

Air pollution, a pressing global issue, is significantly exacerbated by airborne particulate matter (PM), affecting air quality and human health. Urban vehicular activities majorly contribute to PM rise through both exhaust and non-exhaust emissions. Despite strides in managing exhaust emissions, non-exhaust particles, such as tire wear particles (TWP) remain under-addressed. This research proposes a method for estimating TWP concentrations using PM10 data and traffic activity, which could offer a valuable tool for controlling roadside fine particles and TWP. This paper introduces a ternary plotting technique and step-by-step procedure to estimate TWP levels in road dust using only PM10 and traffic data. Traditional analysis of TWP via pyrolysis-gas chromatography–mass spectrometry is complex and time-consuming. Hence, our proposed approach presents an alternate method that leverages readily accessible PM and traffic data, providing critical information for road management interpretation. The triangular plot analysis demonstrated a linear correlation: [log(Traffic) + 2]–[250,000/TWP–13]–0.18PM10. While the resulting correlation may vary based on specific road conditions, the method can be tailored to different regions, offering insights into efficient estimation of TWP concentrations and promoting improved roadside pollution management.

Evaluation of Selected Heavy Metals in Indoor Dust and Interior Painted Walls of Nursery Schools in Nairobi County, Kenya

School playgrounds found in painted environments have become death chambers for millions of innocent children who unknowingly ingest toxic metals. The objective of this study is to determine the levels of the heavy metals in paint chips from painted interior walls and indoor dust samples from 14 selected nursery schools in Nairobi County. The paint chips and indoor dust samples collected were digested using the Environmental Protection Agency method SW846 3050B then analyzed using Flame Atomic Absorption Spectrometry. Iron (Fe) had the highest concentrations in both the paint chip from interior walls and the indoor dust while Cadmium (Cd) had the lowest concentration followed by Chromium (Cr), Lead (Pb) and Zinc (Zn) respectively. 50% of the nursery schools had Lead (Pb) concentrations that exceeded the 90 µg/g limit set by KEBS. For Cadmium (Cd) and Chromium (Cr), the concentration in the nursery schools and the indoor dust was below the 200 µg/g used in Germany. Generally, the correlation between the various metal pairs for the samples analyzed showed a non-significant correlation with exception of Lead - Iron (Pb-Fe) and Chromium - Cadmium (Cr-Cd) for the indoor dust samples from pre-schools. The t-tests carried out show that levels of the heavy metals in the paint chip did not differ significantly with the levels in the indoor dust for nursery schools at 95% confidence level.

Heavy metals contamination, receptor model-based sources identification, sources-specific ecological and health risks in road dust of a highly developed city.

The present study quantified Ni, Cu, Cr, Pb, Cd, As, Zn, and Fe levels in road dust collected from a variety of sites in Tangail, Bangladesh. The goal of this study was to use a matrix factorization model to identify the specific origin of these components and to evaluate the ecological and health hazards associated with each potential origin. The inductively coupled plasma mass spectrometry was used to determine the concentrations of Cu, Ni, Cr, Pb, As, Zn, Cd, and Fe. The average concentrations of these elements were found to be 30.77 ± 8.80, 25.17 ± 6.78, 39.49 ± 12.53, 28.74 ± 7.84, 1.90 ± 0.79, 158.30 ± 28.25, 2.42 ± 0.69, and 18,185.53 ± 4215.61 mg/kg, respectively. Compared to the top continental crust, the mean values of Cu, Pb, Zn, and Cd were 1.09, 1.69, 2.36, and 26.88 times higher, respectively. According to the Nemerow integrated pollution index (NIPI), pollution load index (PLI), Nemerow integrated risk index (NIRI), and potential ecological risk (PER), 84%, 42%, 30%, and 16% of sampling areas, respectively, which possessed severe contamination. PMF model revealed that Cu (43%), Fe (69.3%), and Cd (69.2%) were mainly released from mixed sources, natural sources, and traffic emission, respectively. Traffic emission posed high and moderate risks for modified NIRI and potential ecological risks. The calculated PMF model-based health hazards indicated that the cancer risk value for traffic emission, natural, and mixed sources had been greater than (1.0E-04), indicating probable cancer risks and that traffic emission posed 38% risk to adult males where 37% for both adult females and children.

Soiling mitigation potential of glass coatings and tracker routines in the desert climate of Saudi Arabia

AbstractHigh levels of airborne dust, frequent dust storms and infrequent rain events are some of the reasons why soiling can drastically reduce the energy yield of photovoltaic modules in desert areas. There are ongoing and increasing efforts to identify appropriate and economically feasible strategies that can be used to mitigate soiling in deserts. Both innovative tracking with adapted resting positions during night and anti‐soiling coatings (ASCs) are considered as potential solutions to reduce soiling. In this study, the individual mitigation potential of both ASC and tracking routines as well as the combination of the two approaches are investigated. For this, outdoor exposure tests were carried out in desert region of Saudi Arabia. Coated and uncoated glass samples were tested in different tilt configurations: fixed, 1‐axis tracking with horizontal stowage (facing the sky) and 1‐axis tracking with vertical stowage during the night. Both methods indicate significant soiling reductions, especially for the combined solution of ASC and tracking with vertical night stowage, where soiling losses can be reduced by up to 85%. In addition, it has been shown that the relative ASC performance can be improved when using vertical night stowage compared to fixed tilt or standard 1‐axis tracking scenarios.

Prediction of water quality under the impacts of fine dust and sand storm events using an experimental model and multivariate regression analysis

Many regions of the world, especially arid and semiarid areas, occasionally experience fine dust and sandstorms, known environmental problems that make normal life difficult. Since the intrusion of large amounts of dust into treatment plants may significantly change the water quality indices, the main goal of this study was to estimate these indices during the events, which can help decision-makers to improve water quality. To achieve relationships using nonlinear multivariate regression analysis, a long-term (three years: April 2017–February 2020) experimental study of water quality parameters including total dissolved solids (TDS), hydrogen content (pH), electrical conductivity (EC), chlorine (Cl), total hardness, sodium (Na), and magnesium (Mg) for water samples from wastewater treatment plants in Sistan region (Iran) was conducted where is one of the most popular regions in the world with high amount of annual fine dust level. Analysis of ANOVA showed that of all the independent parameters considered in this study, water quality parameters strongly correlated with monthly mean sand and dust storm index (SDSI), wind speed, temperature, and the number of monthly windy days. For the regression analysis, 25 months of data were used for the simulation process and 10 months for validation. The final results showed that the relationships obtained from the nonlinear multivariate regression analysis could predict the water quality indices very well (with R2 more than 0.75) except for Mg with R2 equal to 0.55. In addition, the maximum mean relative error belongs to Mg (10.8%) and then Na (9.9%) whereas the minimum mean relative error belongs to pH (2.6%) and then EC (2.9%).

Dimethylsiloxanes in dust from nine indoor microenvironments of Henan Province: Occurrence and human exposure assessment

Dimethylsiloxanes (MSs) are widely used in daily life and industry, with indoors being the main release site. Detecting the levels of MSs in indoor dust is essential for assessing the risks of human exposure. In this study, the content of MSs (D3–D8 and L3–L16) was quantified in indoor dust samples from nine microenvironments of Henan Province. The detection frequency of the targets ranged from 5.00 % to 100 %. The sum concentration of dimethylsiloxanes (TSi) was in a range of 463–3.32 × 104 ng·g−1 (median: 1.92 × 103 ng·g−1). The sum concentration of linear dimethylsiloxanes (TLSi) from all microenvironments was higher than the sum concentration of cyclic dimethylsiloxanes (TCSi), which was consistent with previously reported results. D7 and D8 were the main cyclic dimethylsiloxane, which had similar sources based on Spearman correlation analysis (p < 0.001). Moreover, D8 was detected with high levels in indoor dust for the first time, which warrants further exploration. L8–L16 were the main linear dimethylsiloxanes, which may have been due to their widespread use in electronic equipment and office equipment. The Spearman analysis found that total organic carbon (TOC) in indoor dust had weak effect on MSs. Additionally, relatively high MS levels were recorded in high people-flow working microenvironments. Accordingly, the exposure doses of MSs via indoor dust intake were estimated for different age groups using the model of worst-case exposure and median concentration. Toddlers had the highest EDIs (95th percentile concentration, 90.7 ng·kg−1-bw·d−1) to MSs.

The Sources of Polycyclic Aromatic Hydrocarbons in Road Dust and Their Potential Hazard

Polycyclic aromatic hydrocarbons (PAHs) are persistent organic pollutants (POPs) found in the environment, posing significant health concerns for the population. This research aimed to assess the PAH levels in road dust near bus stops, identify their sources, and evaluate potential health risks. The analysis involved the use of a gas chromatography–flame ionization detector (GC-FID) to measure PAHs and absolute principal component score-multiple linear regression (APCS-MLR) for source apportionment of PAHs. The results indicated that the measured PAHs concentrations in road dust ranged from 137.8 to 5813 ng g−1, with Indeno[1,2,3-c,d]pyrene having the highest PAHs concentrations. The study identified three main sources of PAHs such as oil spills, fuel combustion, and coal burning, determined through APCS-MLR modeling. Further analysis revealed that the aggregate incremental lifetime cancer risk (ILCR) for children and adults were 2.16 × 10−6 and 2.08 × 10−6, respectively. Additionally, the hazard index (HI) for children exceeded that of adults, suggesting greater vulnerability to the potential health effects of PAH exposure. The findings indicate that long-term exposure to PAHs may negatively impact lung function and increase the risk of cancer and skin diseases. As a result, it is crucial for the local government to implement effective measures aimed at improving fuel quality and promoting green public transportation within the city. These initiatives may help mitigate PAH emissions and safeguard public health.

The effect of vegetation cover on dust concentration: Case study (Constantine, Algeria)

Even though urban greenery is crucial in maintaining a healthy and pollution-free environment, metropolitan areas are facing a significant threat from pollution, particularly dust particles. Therefore, this study used the advanced remote sensing techniques to explore the relationship between dust concentration and vegetation cover in Constantine, Algeria. As urban development continues to encroach upon green spaces, pollution, especially dust particles, has emerged as a pressing concern in metropolitan areas. This study used data from USGS and GLOvis for climate analysis, while Landsat images from GEE were employed for accurate mapping. Multiple years of comprehensive datasets were collected, including land cover maps, Aridity Index (AI), precipitation data, and Normalized Difference Vegetation Index (NDVI) maps, which underwent thorough analysis. NDVI and Dust Index (DI) were employed to evaluate the impact of vegetation on dust concentration. The result showed that the presence of vegetation directly affects dust levels, and DI exhibits variations over time in relation to the values of NDVI. This study highlights the critical significance of preserving and enhancing urban greenery to mitigate dust pollution and foster a healthier environment.

Study of Particular Air Quality and Meteorological Parameters at a Construction Site

The construction industry is a major contributor to dust, greenhouse gases, and other air pollutants. Implementing effective and sustainable practices in managing construction site operations can greatly mitigate the environmental effects of a project. To achieve this, a collaboration between a scientific research institution and a construction company enabled the real-time monitoring of air quality parameters at a construction site using Internet of Things (IoT) technologies. They implemented an IoT-based system framework that integrated a distributed sensor network to collect real-time data from the construction site. Various sensors were utilized to gather data on the concentration of NO2 and particulate matter (PM2.5 and PM10), as well as meteorological parameters such as wind speed, wind direction, humidity, pressure, and temperature. The real-time measurements yielded insights into the level of air pollution at the construction site and its association with earth excavation, the primary construction activity. This information can be utilized to manage excavation work and reduce the levels of polluting gases (NO2) and suspended particles. By conducting an on-site monitoring of these three pollutants, the study discovered that the dust levels resulting from excavation activities were relatively high. When comparing the wind direction with NO2 and PM concentrations, it was concluded that earth excavation significantly influenced the air quality in the construction area. However, in terms of the primary factors affecting NO2 and construction dust concentrations, the analysis revealed that meteorological factors did not exhibit a significant correlation with NO2 and dust levels at the construction site. The multiple linear regression (MLR) and the artificial neural network (ANN) models for predicting PM2.5, PM10 and NO2 concentration in air using meteorological parameters as predictors were applied. The ANN model showed greater accordance with the measured concentrations in air than the MLR model.

Evaluation of Almond Harvest Dust Abatement Strategies Using an Aerial Drone Particle Monitoring System

This study demonstrates the feasibility of a mobile aerial drone particle monitoring system (DPMS) to measure and detect changes in harvest dust levels based on moderate adjustments to harvester settings. When compared to an earlier harvester, a new harvester operated at standard settings produced 35% fewer PM2.5s, 32% fewer PM10s, and 42% fewer TSPs. Increasing the ground speed had an adverse effect on dust mitigation, while reducing it by half only offered a slightly more favorable margin. The mutual effects of some meteorological factors were found to be slightly correlated with PM10 and TSP readings and caused significant variability in PM2.5 readings. The current findings show similar trends to PM reduction estimates of previous studies, with only a nominal difference of 10 to 15% points. Overall, the DPMS was found to perform well within an acceptable statistical confidence level. The use of DPMSs could reduce the logistical needs, complexity issues, and feedback times often experienced using the Federal Reference Method (FRM). Further investigation is needed to verify its robustness and to develop potential correlations with the FRM under different orchard location and management practices. At this stage, the current aerial DPMS should be considered a rapid screening tool not to replace the FRM, but rather to complement it in evaluating the feasibility of dust abatement strategies for the almond industry.

Faktor yang Berhubungan dengan Gejala Sick Building Syndrome

Background: Sick Building Syndrome (SBS) is a syndrome caused by the work environment. SBS is stated as a health problem in the work environment which is related to poor indoor air quality. The Central Java Provincial Health Office building is in the city center so it is an environment prone to air pollution. The purpose of this study was to determine the factors that influence SBS symptoms in Central Java Provincial Health Office employees. Methods: This study uses an analytic study type with a cross-sectional approach. The sample in this study were 73 respondents. The sampling technique used purposive sampling technique. The instruments used were questionnaires and measurements. The data analysis used the chi square statistical test. Results: The results of this study showed that among the 73 respondents there was a relationship between age and SBS symptoms (p=0.020), there was a relationship between gender and SBS symptoms (p=0.010), there was a relationship between years of service and SBS symptoms (p=0.020 ), there was a relationship between room temperature and SBS symptoms (p=0.007), there was a relationship between the number of bacteria and SBS symptoms (p=0.004), there was no relationship between room air humidity and dust levels and SBS symptoms. Conclusion: Age, gender, length of service, and number of bacteria are factors associated with SBS symptoms. In an effort to reduce the risk of SBS symptoms, workers need to relax body muscles, optimize the use of AC, increase AC maintenance, turn off the AC for a moment and open windows periodically.

Atmospheric heating in the US from saharan dust: Tracking the June 2020 event with surface and satellite observations

In June 2020, a record level of Saharan dust was transported across the Atlantic Ocean impacting air quality in the Caribbean Basin and the United States (US). Satellite images showed the transport, while a series of ground-based monitoring stations captured the surface impacts as the Saharan dust was transported to the Caribbean basin and then moved into the Southern (Houston, Texas; WL), Eastern (Bone, North Carolina; APP) and Midwestern (Bondville, Illinois; BND) US. The present study characterizes the Saharan dust event (SDE) using a comprehensive set of satellite observations and in-situ measurements of particulate matter (PM), and aerosol optical properties (AOPs; σscat: scattering coefficient, σabs: absorption coefficient, SAE: scattering Ångström exponent and AAE: absorption Ångström exponent). The Saharan dust intrusion was identified at each site by a marked increase in σscat, and AAE and a simultaneous decrease in SAE. A maximum hourly average PM2.5 concentration and σscat (525 nm) of 97.5 μg m−3 and 190 Mm−1 was observed at WL during the SDE. The maximum hourly average σscat (550 nm) for PM10 size cut of 215 and 66.9 Mm−1 was observed at APP and BND, respectively, during the SDE. The AAE at each site reached above 1.3 with an average value of 1.39 ± 0.35, 3.34 ± 0.56 and 1.65 ± 0.27 at WL, APP, and BND, respectively, during the SDE, whereas the average SAE dropped below 0.5 at WL and APP and below 0.9 at BND. The results demonstrated that the identification of SDE using AOPs depends largely on the location of the measurement, which determines the background characteristics of a site. The results suggest that other intensive AOPs like asymmetry parameter (g) and single scattering albedo Ångström exponent (SSAAE) can also be exploited to characterize SDE. Aerosol radiative forcing (ARF) estimates indicate that the SDE resulted in the heating of the atmosphere (+5.37 to +11.8 W m−2) at the rate of 0.11–0.24 K day−1 at the US sites. This atmospheric heating from transported Saharan dust can alter the regional atmospheric dynamics and is relevant to understand potential changes in regional climate.

Effects of atmospheric dust particles on common medicinal plants in an industrial area of West Bengal, India.

The exposure of atmospheric dust particles on four common medicinal plants (Ocimum sanctum, Andrographis paniculata, Catharanthus roseous, and Kaempferia galanga, which are available in the study area and cultivated by the local people for medicinal purposes) affects their growth, levels of essential biochemical constituents and heavy metal concentration. The plant species were grown by pot cultivation in an industrial area with high levels of coal dust to assess the capacity of heavy metals accumulation in their leaves and changes in allometry and biochemical parameters. The results showed that annual average SPM and dustfall varied between 195.88 to 645.97 μg/m3 and 17.55 to 41.16 g/m2/month, respectively. Dustfall at different polluted sites was 2.4, 2.1, 1.5, 1.4, and 2.3 times higher than at the control site. The most prevalent heavy metal in atmospheric particulate matter was Zn, followed by Pb, Ni, Cu, Co, and Cd. Plant allometry measurements such as height, stem width, root length, petiole length, and leaf area are shown to have a strong and significant (p<0.05) negative correlation with dustfall and SPM. Total chlorophyll and RWC were inversely proportional to the dust load present in all the species. Except for Andrographis paniculata, chlorophyll and leaf-extracted pH of plant species were moderately correlated with APTI, whereas no correlation was noticed for ascorbic acid. A positive correlation between SPM and heavy metals in leaves was observed. The results implied that the cultivation and collection of medicinal plants from the study area could be potentially toxic to human health.

Pozzolanic properties of marble industrial waste and its used in concrete

Concrete needs to use alternative materials to reduce cement content to limit the effect of carbon emissions. Marble dust as a waste of the marble industry has very fine grains. X-Ray Fluorescence (X-RF) method was conducted to determine the mineral properties of marble dust. Marble dust was found to contain 98.62% Calcium Oxide (CaO), 0.17% Sulfur Trioxide (SO3) and some elements in small levels. To determine the impact of marble dust on the mechanical characteristics of concrete, an experimental study was conducted. Test specimens were made with four different levels of marble dust, namely 0%, 5%, 10%, and 15%. The experimental results showed that the optimum usage was 6.62% by weight of cement which gave the advantage of increasing the compressive strength of concrete by 11.77%.

Pollution Characteristics and Risk Assessment of Heavy Metals in Surface Dusts and Surrounding Green Land Soils from Yellow River Custom Tourist Line in Lanzhou

In order to investigate the contamination levels of dust and its surrounding green land soil heavy metal pollution and potential ecological and health risks in the scenic areas of urban waterfront parks, the gardens, squares, and theme parks of the Yellow River Custom Tourist Line in Lanzhou were selected as the research area, using 27 dust samples and 26 soil samples from its surrounding green lands. The contamination characteristics and potential ecological risks of eight heavy metals (Cr, Ni, Cu, Zn, As, Cd, Hg, and Pb) were evaluated using the geo-accumulation index (Igeo), single-factor pollution index (Pi), Nemerow integrated pollution index (PN), and improved potential ecological risk index (RI). The human health risk assessment was also evaluated using the exposure risk model. The results showed that the average concentrations of the other heavy metals in the surface dusts were higher than the background values of Gansu Province and Lanzhou City, except that the As mean concentrations in the surface dusts and the surrounding green land soils were slightly lower than the Gansu Province background values. For its surrounding green land soils, the mean concentrations of the other heavy metals (Cu, Zn, Cd, Hg, and Pb) exceeded the soil background values of Gansu Province and Lanzhou City, whereas the Cr and Ni mean concentrations were lower than their corresponding soil background values of Gansu Province and Lanzhou City. The geo-accumulation and single-factor pollution indices demonstrated that a slight to moderate pollution of Cr, Cu, Zn, Cd, Hg, and Pb occurred in surface dusts, and Cu, Zn, Cd, Hg, and Pb appeared in varying degrees of contamination levels in its surrounding green land soils. The Nemerow integrated pollution index analysis manifested that the overall contamination status of the study areas was between slightly and heavily polluted. The potential ecological risk index suggested that Cd and Hg were recognized as significant pollutant elements and that the RI of the other heavy metals were all below 40, presenting slight ecological risk. The health risk assessment indicated that ingestion was the dominant exposure pathway for heavy metals from the surface dusts and the surrounding green land soils, and no carcinogenic and noncarcinogenic risks posed threats to adults and children.