Aerosol Science and Engineering最新文献

The size of human speech or cough droplets decides their air-borne transport distance, life span and virus infection risk. We have investigated the measurement accuracy of artificial saliva and saline droplet size for more effective COVID-19 infection control. A spray generator was used for polydisperse droplet generation and a special test chamber was designed for droplet measurement. Saline and artificial saliva were gravimetrically prepared and used to generate droplets. The droplet spray generator and the test chamber were circulated among four metrology institutes (NMC, CMS/ITRI, NIM and KRISS) for droplet size measurement and evaluation of deviations. The composition of artificial saliva was determined by measuring the mass fraction of the inorganic ions. The density of dried artificial saliva droplets was estimated using its composition and the density of each non-volatile component. The volume equivalent diameter (VED) of droplets have been measured by aerodynamic particle sizer (APS) and optical particle size spectrometer (OPSS). As a response to the COVID-19 pandemic, this is the first time that a comparative study among four metrology institutes has been conducted to evaluate the accuracy of saliva and saline droplet size measurement. For artificial saliva droplets measured by OPSS, the deviations from the reference VED (~ 4 μm) were below 5.3%. For saline droplets measured by APS, the deviations from the reference VED were below 10.0%. The potential droplet size measurement errors have been discussed. This work underscores the need for new reference size standards to improve the accuracy and establish traceability in saliva and saline droplet size measurement.

Wet removal is the primary method for the natural removal of atmospheric aerosol particles, and wet removal is a very complex process. According to the PM_2.5, PM₁₀, and meteorological data from 71 cities in China from 2016 to 2018, this study utilizes theoretical analysis methods based on the existing rainfall aerosol removal theory and real-time monitoring data to calculate the measured removal coefficient and theoretical removal coefficient for verification. According to the different rainfall intensities and rainfall times in Guilin, the measured value and the simulated value are verified, and the linear relationship obtained was Λ_s = 1.589 × 10^–5 + 0.609Λ_m, R² = 0.673, and the simulated value approximated to the measured value after correction. The same method was utilized to calculate the theoretical removal coefficient of polydisperse aerosols in 71 cities across the country, and the calculation parameters of the rainfall removal polydisperse aerosol model in different regions were modified.

PM_2.5/PM₁₀ ratio is essential for understanding particulate pollution’s severity and adverse effects on human beings as it reveals how long the particle will stay in the atmosphere and where it will deposit in the human respiratory tract. The present study focuses on the spatio-temporal variability of the PM_2.5/PM₁₀ ratio from nine sites (six in Delhi, one each in Amritsar, Varanasi and Kolkata) in the Indo-Gangetic Plain (IGP) during the last 3 years (2019–2021) before, during, and after the COVID-19 pandemic-induced lockdown in India. Robust statistics such as median and percentiles have been employed to avoid bias due to non-normal distributions. Considerable spatial and temporal variability was seen throughout the 3 years. Amritsar and one site in Delhi exhibited the least temporal variability in PM_2.5/PM₁₀ (~ 10%) annually. However, the highest average variation over the 3 years was ~ 28%, noticed for one site in Delhi. The PM_2.5/PM₁₀ ratio was high (~ 0.6 ± 0.1) during the post-monsoon (Oct–Dec) and winter (Jan–Feb) seasons. The PM_2.5/PM₁₀ ratio was low (~ 0.4 ± 0.1) in the monsoon season (June–Sep.) and pre-monsoon season (Mar–May). Conditional Bivariate Probability Function (CBPF) and Cluster Analysis using Hysplit data were done to assess the local and long-range source of pollutants arriving at a receptor location. The impact of wind speed and relative humidity on the PM_2.5/PM₁₀ ratio was also analysed. The results of this study would help establish an intricate policy framework for cities in the IGP.

The activities of artisans conducted regularly in automobile workshops have been observed to generate pollutants that are not limited to particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs). Thus, this research provided data on the quantification of PAHs coupled with the building of a predictive statistical model for the prediction of benzo[a]pyrene (BaP) in Benin City. The city was divided into four zones, namely North West (NW), North East (NE), South East (SE) and South West (SW), and a total of 180 representative samples were collected from artisans’ workshops in both wet (April to November) and dry (December to March) seasons using an Apex2IS Casella standard pump fitted with a conical inhalable sampling (CIS) head at a flow rate of 3.5L/min for 8 h. Meteorological parameters were collected simultaneously with the PM_2.5 (particles with an aerodynamic diameter of less than or equal to 2.5 µm)_. PAHs were extracted and quantified using Gas Chromatography (GC) fitted with a flame-ionization detection (FID). The annual average concentration of the total PAHs bound to PM_2.5 for the NW, NE, SE, and SW zone were 519.51 (638.78), 109.13 (169.16), 158.89 (178.40) and 77.65 (89.60) ng/m³ for both the wet and dry seasons, respectively. A generalized linear model (GLiM) was used to develop a prediction model for the prediction of (BaP) air concentrations in the NW zone. The results of the selected model among the five trained models obtained with data from NW sampling sites are R² = 0.792 and adjusted R² = 0.746 for model 1, with an overall p-value of 0.01. The proposed model established an approximation to estimate Benzo[a]pyrene (BaP) concentrations in the urban automobile workshops’ atmospheres with reasonable accuracy of 60–72%.

The present research aims to describe the measurement of the changes in air pollutants such as black carbon (BC), PM_2.5, and CO concentrations levels, and estimation of their source apportionment and health risk during normal period (NP) as well as lockdown period (LP) in Jamshedpur city. The urban atmospheric pollutants mostly BC, PM_2.5 and CO concentrations were observed gradual fall during LP. The averaged mass concentration of BC, PM_2.5 and CO was found about 38.46 ± 1.91 µgm⁻³, 176.55 ± 21.72 µgm⁻³, 840 ± 282 ppbv in NP and 9.68 ± 2.36 µgm⁻³, 42.86 ± 18.97 µgm⁻³, 175.88 ± 121.82 ppbv during LP, respectively. BC, PM_2.5, and CO concentrations were shown to be lower during LP as compared to NP. This may be because of prohibited of all human activities due to COVID-19 pandemic. The source apportionment analysis of BC indicated that the biomass burning (62.5%) contribution was high as compared to fossil fuel emission (37.5%) at LP. The air trajectory model showed that most of the air masses were coming from western part of India and also some fresh marine air masses were received at the located position. The health risk for respective health effects of CVM (cardiovascular mortality), LC (lung cancer), LBW (low birth weight), and PLEDSC (percentage lung function decrement of school-aged children) due to exposure to BC was evaluated as 9.76, 4.8, 8.59 and 19.59 PSC in NP and 8.35, 4.1, 7.35 and 16.77 PSC in LP.

Graphical abstract

Particulate matter (PM) has been demonstrated to be hazardous to the human body. Various studies have identified the source of PM, but the aggravating factors have not been thoroughly clarified. As a result, preventing or intervening in this problem is critical. The goal of this study is to assess the overall strength of the evidence for the relationship between relative humidity (RH) and PM to create a plan or guideline using water or humidity technique for dealing with and preventing future PM problems. A comprehensive search of articles published in English was conducted across three electronic databases (PubMed, Scopus, and SpringerLink) in January 2023, using articles available from the inception of the first cluster of COVID-19, on December 1, 2019, until January 12, 2023. Articles were screened against inclusion/exclusion criteria and data from included studies were retrieved and analyzed. Of the 3799 records found, only 52 met the initial inclusion and only 27 articles were included in the final qualitative synthesis. Around forty percent of the studies exhibited the correlation between coarse particulate matter and relative humidity. Half of the total studies found a direct correlation between PM_2.5 and RH, while PM₁₀ and RH have the opposite correlation. Most of the studies demonstrated that the correlation between relative humidity and particulate matter is significant. This study suggests that spraying water or increasing humidity to reduce air pollution may decrease the larger-sized dust particles, but have the opposite effect on smaller-sized particles. Those reviewed studies briefly explained the mechanism behind their results, thus providing insight for further investigation and assisting policymakers in staying on track while producing working models. Both simulations and multivariate studies should be conducted as part of these further investigations. For future research, the use of artificial intelligence (AI) or machine learning model and a meta-analysis between PM chemical components and RH are recommended.

The classical theory for filtering efficiency of air filters is useful in predicting filter performance and designing new air filters. For instance, the formula for filtering efficiency has been proposed based on the theory of the Fan model filter (FMF). The FMF theory has parameters, such as the single fiber diameter, because fiber diameter could determine packing density and thickness of filter media, which have enormous impact on filtering efficiency. However, there are some air filters consisting of coarse and fine fibers. The calculated filtering efficiency of these filters, based on the FMF theory, exhibited a significant difference from the measured value. The objective of this study is to accurately predict the filtering efficiency of an air filter consisting of coarse and fine fibers. To achieve this objective, an empirical formula for filtering efficiency was developed, taking into account the diameter and the weight of the coarse and fine fibers. The empirical formula was expressed as the sum of filtering efficiencies dependent on the coarse and fine fibers, respectively. Results demonstrated that there was little difference between the filtering efficiency predicted by the developed empirical formula and the measured value, falling within the range of deviation observed for commercial filters. Therefore, the developed empirical formula is deemed capable of precisely predicting the performance of commercial filters.

This study aims to characterize the heavy metals in fine particulate matter PM_2.5 in the vicinity of a lead smelter industry in Lamongan, Indonesia. The samples were collected using a dichotomous Gent stacked filter unit sampler. Eighteen elements were identified using energy-dispersive X-ray fluorescence (ED-XRF) for source identification and potential risk assessment. PM_2.5 concentrations ranged from 7.3 to 30.6 µg/m³ with black carbon attributed to 19% of the mass. Pb was found as the dominant heavy metal, with an average concentration of 0.46 µg/m³, followed by other elements S, K, Fe, and Zn. Pb is attributed to an average of 2.7% of PM_2.5. From principal component analysis (PCA), it was found that the potential sources were associated with lead smelter, biomass burning, road dust, vehicles, metal industry, and shipping emission. The results suggested that the lead smelter and metal industry have a major influence on the study area. The health risk assessment was carried out using the hazard quotient (HQ) and excess lifetime cancer risk (ELCR) for Pb, Cr, and Ni. The HQ value and the ELCR value of Pb were found to be slightly higher than the permissible acceptable level. The ELCR value of 1.81 × 10^–6 indicates that approximately two cases of cancer per 1000,000 adult population at Lamongan may occur due to Pb contamination. To minimize the health risks, exposure to heavy metals in PM_2.5 should be avoided as possible and the policy interventions should be implemented to control the lead smelter as major source of Pb pollutants in Lamongan, East Java.

Indoor air cleaning interventions such as bipolar air ionizers have increased lately due to rampant air pollution and the COVID-19 pandemic. Hitherto, the bipolar air ionizer efficacy against particulate pollutants and byproduct ozone emission has not been fully understood and remained a critical concern. Currently, available diverse and complex methods are insufficient to determine commercially available bipolar air ionizer reliability. The National and International market of bipolar air ionizers is proliferating, while safety standards and information are comparatively limited, in such cases, any misleading information by manufacturers could be detrimental to consumers. To focus on those gaps, the present study comprised five different types of commercially available bipolar air ionizers labeled as BAI 1, BAI2, BAI3, BAI4, and BAI5, which were examined against the most concerned indoor particulate pollutants and potential byproduct ozone. Seven days of consecutive experiments were performed in five acrylic boxes, each box assembled with a testing bipolar ionizer model, calibrated air quality monitor, and particulate pollutant source (incense sticks). Two runs/day for each individual bipolar ionizer were performed for up to seven consecutive days. Overall performance was procured from the daily cumulative arithmetic average. All tested bipolar air ionizers models showed notable, up to 80% particulate matter (PM_2.5 and PM₁₀) removal efficiencies. The highest particulate matter removal was associated with bipolar air ionizers model 4 (PM₁₀ 79.7%, PM_2.5 80.4%) and the minimum with BAI model 5 (PM₁₀ 72.2%, PM_2.5 72.3%). Abnormal ozone emission was not observed with any bipolar air ionizer conduction in this study. Almost negligible elevation in background temperature (0.4 °C) and relative humidity (0.6%) were also observed. In conclusion, bipolar air ionizers could be byproduct ozone-free, indoor particulate matter removal, and low maintenance indoor air cleaning option.