A Characterization and Cell Toxicity Assessment of Particulate Pollutants from Road Traffic Sites in Kano State, Nigeria

Emerging African countries are characterized by explosive population growth and urbanization, which threaten environmental sustainability. This study comparatively characterized ambient aerosols and assessed cytotoxicity to facilitate improving health and environmental policy. Twenty-four air samples were collected at high and low-density traffic sites in Kano State using polysulfone and stainless steel filters attached to an automated pump. The physico-chemical properties of particulate matter were determined using scanning electron microscopy and energy dispersive X-ray analysis (SEM-EDX). In vitro, their potential toxicity was assessed using macrophages and cell fixation with staining. Results showed 51.7% of particles as PM2.5, with the highest particle concentration in mixed sites (urban and industrial). Particle classification into four groups by elemental composition and structure showed: Si, Al, and Ca 58–67%; other fibres, Fe, S, Mo, and Zn 1–17%; non-sand non-fibres 23–56%; and silicone-based fibres 2–28%. The abundant elements are: Si, Al, Ca, Ce, Ti, Fe, Cl, Pb, and Mn. The lowest viability on cytotoxicity assessment was recorded in mixed site M2. The majority of households were located within 50 m of air sampling sites. Proximity to traffic sites worsens health, as evidenced in cytotoxicity findings. We recommend improved urban planning and intensification of emissions control.

Improving PM2.5 Concentration Forecast with the Identification of Temperature Inversion

The rapid development of industrialization and urbanization has had a substantial impact on the increasing air pollution in many populated cities around the globe. Intensive research has shown that ambient aerosols, especially the fine particulate matter PM2.5, are highly correlated with human respiratory diseases. It is critical to analyze, forecast, and mitigate PM2.5 concentrations. One of the typical meteorological phenomena seducing PM2.5 concentrations to accumulate is temperature inversion which forms a warm-air cap to blockade the surface pollutants from dissipating. This paper analyzes the meteorological patterns which coincide with temperature inversion and proposes two machine learning classifiers for temperature inversion classification. A separate multivariate regression model is trained for the class with or without manifesting temperature inversion phenomena, in order to improve PM2.5 forecasting performance. We chose Puli township as the studied site, which is a basin city easily trapping PM2.5 concentrations. The experimental results with the dataset spanning from 1 January 2016 to 31 December 2019 show that the proposed temperature inversion classifiers exhibit satisfactory performance in F1-Score, and the regression models trained from the classified datasets can significantly improve the PM2.5 concentration forecast as compared to the model using a single dataset without considering the temperature inversion factor.

Regularized inversion of aerosol hygroscopic growth factor probability density function: Application to humidity-controlled fast integrated mobility spectrometer measurements

Aerosol hygroscopic growth plays an important role in atmospheric particle chemistry and the effects of aerosol on radiation and hence climate. The hygroscopic growth is often characterized by a growth factor probability density function (GF-PDF), where the growth factor is defined as the ratio of the particle size at a specified relative humidity to its dry size. Parametric, least-square methods are the most widely used algorithms for inverting the GF-PDF from measurements of humidified tandem differential mobility analyzers (HTDMA) and have been recently applied to the GF-PDF inversion from measurements of the humidity-controlled fast integrated mobility spectrometer (HFIMS). However, these least square methods suffer from noise amplification due to the lack of regularization in solving the ill-posed problem, resulting in significant fluctuations in the retrieved GF-PDF and even occasional failures of convergence. In this study, we introduce nonparametric, regularized methods to invert aerosol GF-PDF and apply them to HFIMS measurements. Based on the HFIMS kernel function, the forward convolution is transformed into a matrix-based form, which facilitates the application of the nonparametric inversion methods with regularizations, including Tikhonov regularization and Twomey’s iterative regularization. Inversions of the GF-PDF using the nonparameteric methods with regularization are demonstrated using HFIMS measurements simulated from representative GF-PDFs of ambient aerosols. The characteristics of reconstructed GF-PDFs resulting from different inversion methods, including previously developed least-square methods, are quantitively compared. The result shows that Twomey’s method generally outperforms other inversion methods. The capabilities of the Twomey’s method in reconstructing the pre-defined GF-PDFs and recovering the mode parameters are validated.

Rapid measurement of RH-dependent aerosol hygroscopic growth using a humidity-controlled fast integrated mobility spectrometer (HFIMS)

The ability of aerosol particles to uptake water (hygroscopic growth) is an important determinant of aerosol optical properties and radiative effects. Aerosol hygroscopic growth is traditionally measured by humidified tandem differential mobility analyzers (HTDMA), in which size-selected dry particles are exposed to elevated relative humidity (RH), and the size distribution of humidified particles is subsequently measured using a scanning mobility particle sizer. As a scanning mobility particle sizer can measure only one particle size at a time, HTDMA measurements are time consuming, and ambient measurements are often limited to a single RH level. Pinterich et al. (2017b) showed that fast measurements of aerosol hygroscopic growth are possible using a humidity-controlled fast integrated mobility spectrometer (HFIMS). In HFIMS, the size distribution of humidified particles is rapidly captured by a water-based fast integrated mobility spectrometer (WFIMS), leading to a factor of ∼10 increase in measurement time resolution. In this study we present a prototype HFIMS that extends fast hygroscopic growth measurements to a wide range of atmospherically relevant RH values, allowing for more comprehensive characterizations of aerosol hygroscopic growth. A dual-channel humidifier consisting of two humidity conditioners in parallel is employed such that aerosol RH can be quickly stepped among different RH levels by sampling from alternating conditioners. The measurement sequence is also optimized to minimize the transition time between different particle sizes. The HFIMS is capable of measuring aerosol hygroscopic growth of six particle diameters under five RH levels ranging from 20 % to 85 % (30 separate measurements) every 25 min. The performance of this HFIMS is characterized and validated using laboratory-generated ammonium sulfate aerosol standards. Measurements of ambient aerosols are shown to demonstrate the capability of HFIMS to capture the rapid evolution of aerosol hygroscopic growth and its dependence on both size and RH.

Kinetics and impacting factors of HO₂ uptake onto submicron atmospheric aerosols during the 2019 Air QUAlity Study (AQUAS) in Yokohama, Japan

HO2 uptake kinetics onto ambient aerosols play pivotal roles in tropospheric chemistry but are not fully understood. Field measurements of aerosol chemical and physical properties should be linked to molecular-level kinetics; however, given that the HO2 reactivity of ambient aerosols is low, traditional analytical techniques are unable to achieve this goal. We developed an online approach to precisely investigate the lower-limit values of (i) the HO2 reactivities of ambient gases and aerosols and (ii) HO2 uptake coefficients onto ambient aerosols (γ) during the 2019 Air QUAlity Study (AQUAS) in Yokohama, Japan. We identified the effects of individual chemical components of ambient aerosols on γ. The results were verified in laboratory studies on individual chemical components: transition metals play a key role in HO2 uptake processes, and chemical components indirectly influence such processes (i.e., by altering aerosol surface properties or providing active sites), with smaller particles tending to yield higher γ values than larger particles owing to the limitation of gas-phase diffusion being smaller with micrometer particles and the distribution of depleting species such as transition metal ions being mostly distributed in accumulation mode of aerosol. The modeling of γ utilized transition metal chemistry derived by previous studies, further confirming our conclusion. However, owing to the high NO concentrations in Yokohama, peroxy radical loss onto submicron aerosols has a negligible impact on O3 production rate and sensitivity regime.

A highly efficient cloth facemask

Wearing masks and face coverings helps reduce transmission of respiratory diseases. Much prior research on mask filtration efficiency has focused on fabric type, with less consideration given to mask design and shape. Here, we present evidence that increasing the mouth-mask separation distance engenders an increase in the mask-fabric filtration efficiency towards expiratory aerosols emitted via vocalization, which we attribute to a decrease in the expiratory jet velocity and expansion of the breath-mask contact area. We further assess the performance of a new reusable cloth facemask design, originally made for, but not exclusive to, professional singers and having a large mouth-mask separation distance. With proper fitting, these masks achieve overall filtering efficiencies of >93% for both exhaled expiratory aerosols >0.5 microns in diameter from singing and speaking and for inhaled ambient aerosols, better than surgical masks and approaching N95 respirators. Air exchange between the mask deadspace and the ambient environment limits the extent of CO2 buildup and in inhaled air and maintains O2 levels near ambient. The mask design also provides for less inhibited mouth and jaw movement and lower relative humidity, suggesting it may provide a more palatable, high-efficiency alternative to medical-grade masks for the public.

A method for liquid spectrophotometric measurement of total and water-soluble iron and copper in ambient aerosols

Determination of transition metals in ambient aerosols is important due to their toxicity to human health. However, the traditional measurement techniques for metal analysis are often costly and require sophisticated instruments. In this study, we developed and verified relatively low-cost liquid spectrophotometric methods for the measurements of iron (Fe) and copper (Cu), the two most abundant transition metals in ambient fine particulate matter (PM2.5). For Fe analysis, we utilized a ferrozine-based colorimetric method, which has been frequently used for water-soluble (WS) Fe determination, and further extended this approach for the measurement of total Fe (water-soluble + water-insoluble). In this method, Fe is quantified through the formation of a light-absorbing ferrozine–Fe(II) complex (absorbance at 562 nm). A similar colorimetric method, which forms a bathocuproine–Cu(I) complex absorbing light at 484 nm, was developed and examined for measurement of WS and total Cu. These methods were applied to 24 h integrated filter samples collected in urban Atlanta. Based on PM2.5 ambient aerosols, total and water-soluble Fe and Cu concentrations were in good agreement with inductively coupled plasma mass spectrometry (ICP-MS) measurements (slopes 1.0±0.1, r2>0.89). The water-soluble components, operationally defined as those species in the aqueous filter extract that pass through a 0.45 µm filter, were further characterized by ultrafiltration, which showed that roughly 85 % of both the Fe and Cu in the water-soluble fraction was composed of species smaller than nominally 4 nm.