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Workers' health is jeopardized in steel rolling workshops due to the production of particulate matter. These particles' physicochemical properties have a direct impact on their effects on human health, emphasizing the importance of understanding these properties for exposure control. This study investigated particulate matter emissions in hot and cold steel rolling workshops, focusing on mass concentrations, particle size distributions, and elemental compositions. The findings revealed that particles predominantly range from 0.3 to 1.0 μm in size, with irregular block-like and fibrous morphologies. Elemental analysis showed distinct compositions: the main components in the hot rolling workshop were oxygen, calcium, silicon, carbon, and iron while those in the cold rolling workshop were oxygen, silicon, aluminum, carbon, and iron. The particulate matter concentrations were higher in the hot rolling workshop than in the cold rolling workshop. The Rosin–Rammler particle size distribution function was applied to characterize particle size distribution at emission sources. This paper highlights the dynamic variations and spatial distribution patterns of particulate matter during rolling processes, providing key data for understanding particulate matter behavior in industrial environments and informing targeted pollution control strategies. [ABSTRACT FROM AUTHOR]

As the wealth of evidence grows as to the negative impact of indoor air quality on human health, it has become increasingly urgent to investigate and characterise sources of air pollution within the home. Fine particulate matter with a diameter of 2.5 µm or less (PM2.5) is a key cause for concern, and cooking is known to be one of the most significant sources of domestic PM2.5. In this study, the aim was to demonstrate the efficacy of combining experimental techniques and cutting-edge High-Performance Computing (HPC) to characterise the dispersion of PM2.5 during stir-frying within a kitchen laboratory. This was carried out using both experimental measurement with low-cost sensors and high-fidelity Computational Fluid Dynamics (CFD) modelling, in which Lagrangian Stochastic Methods were used to model particle dispersion. Experimental results showed considerable spatio-temporal variation across the kitchen, with PM2.5 mass concentrations in some regions elevated over 1000 μg m − 3 above the baseline. This demonstrated both the impact that even a short-term cooking event can have on indoor air quality and the need to factor in such strong spatio-temporal variations when assessing exposure risk in such settings. The computational results were promising, with a reasonable approximation of the experimental data shown at the majority of monitoring points, and future improvements to and applications of the model are suggested. [ABSTRACT FROM AUTHOR]

Protection from nuclear biochemical aerosol and air pollution pays attention to aerosol mass concentration. The concentration of upstream aerosol of the commonly used filtration efficiency detection device for high-efficiency filter materials is low, making it insufficient for detecting the filtration efficiency of high-efficiency filter materials. This study designed and built a set of filtration efficiency detection devices for high-efficiency filter materials based on mass concentration. By adjusting the oil bath temperature, injection pressure, the degree of spiral-separator separation, as well as the number and size of nozzles, we investigated the effects of each condition on the concentration and particle size distribution of aerosol generation. As a result, the oil mist generator of the device can stably generate high-concentration aerosol with a mass concentration of up to 1587.9 mg/m3 and a number concentration of up to 107–108 P/cm3. The high-concentration aerosol generated can meet the E11–U15 filter material performance requirements. [ABSTRACT FROM AUTHOR]

Emissions from thermal power plants have always been the central consideration for environmental protection. Existing optical sensors in thermal power plants usually measure the total mass concentration of the particulate matter (PM) by a single-wavelength laser, bearing intrinsic errors owing to the variation in particle size distribution (PSD). However, the total mass concentration alone cannot characterize all the harmful effects of the air pollution caused by the power plant. Therefore, it is necessary to measure the mass concentration and PSD simultaneously, based on which we can obtain multi-particle-size channel mass concentration. To achieve this, we designed an optical sensor based on the three-wavelength technique and tested its performance in a practical environment. Results showed that the prototype cannot only correctly measure the mass concentration of the emitted PM but also determine the mean diameter and standard deviation of the PSDs. Hence, the mass concentrations of PM10, PM2.5, and PM1 are calculated, and the air pollutants emission by a thermal power plant can be estimated comprehensively. [ABSTRACT FROM AUTHOR]

Highlights: What are the main findings? The job exposure matrix (JEM) provides annual means of PM10 concentrations for Parisian subway workers. Annual PM10 concentrations are estimated over the period of 2004–2020. What is the implication of the main finding? The JEM approach is relevant to assess occupational long-term exposure to subway PM10. The JEM will allow to examen the health effects of long-term exposure to subway PM10. Introduction: Health effects after long-term exposure to subway particulate matter (PM) remain unknown due to the lack of individual PM exposure data. This study aimed to apply the job exposure matrix (JEM) approach to retrospectively assess occupational exposure to PM in the Parisian subway. Methods: Job, the line and sector of the transport network, as well as calendar period were four JEM dimensions. For each combination of these dimensions, we generated statistical models to estimate the annual average PM10 concentration using data from an exhaustive inventory of the PM measurement campaigns conducted between 2004 and 2020 in the Parisian subway and historical data from the Parisian air pollution monitoring network. The resulting JEM and its exposure estimates were critically examined by experts using the uncertainty analysis framework. Results: The resulting JEM allows for the assignment of the estimated annual PM10 concentration to three types of professionals working in the subway: locomotive operators, station agents, and security guards. The estimates' precision and validity depend on the amount and quality of PM10 measurement data used in the job-, line-, and sector-specific models. Models using large amounts of personal exposure measurement data produced rather robust exposure estimates compared to models with lacunary data (i.e., in security guards). The analysis of uncertainty around the exposure estimates allows for the identification of the sources of uncertainty and parameters to be addressed in the future in order to refine and/or improve the JEM. Conclusions: The JEM approach seems relevant for the retrospective exposure assessment of subway workers. When applied to available data on PM10, it allows for the estimation of this exposure in locomotive operators and station agents with an acceptable validity. Conversely, for security guards, the current estimates have insufficient validity to recommend their use in an epidemiological study. Therefore, the current JEM should be considered as a valid prototype, which shall be further improved using more robust measurements for some jobs. This JEM can also be further refined by considering additional exposure determinants. [ABSTRACT FROM AUTHOR]

Low-cost sensors (LCSs) for particulate matter (PM) concentrations have attracted the interest of researchers, supplementing their efforts to quantify PM in higher spatiotemporal resolution. The precision of PM mass concentration measurements from PMS 5003 sensors has been widely documented, though limited information is available regarding their size selectivity and number concentration measurement accuracy. In this work, PMS 5003 sensors, along with a Federal Referral Methods (FRM) sampler (Grimm spectrometer), were deployed across three sites with different atmospheric profiles, an urban (Germanou) and a background (UPat) site in Patras (Greece), and a semi-arid site in Almería (Spain, PSA). The LCSs particle number concentration measurements were investigated for different size bins. Findings for particles with diameter between 0.3 and 10 μm suggest that particle size significantly affected the LCSs' response. The LCSs could accurately detect number concentrations for particles smaller than 1 μm in the urban (R2 = 0.9) and background sites (R2 = 0.92), while a modest correlation was found with the reference instrument in the semi-arid area (R2 = 0.69). However, their performance was rather poor (R2 < 0.31) for coarser aerosol fractions at all sites. Moreover, during periods when coarse particles were dominant, i.e., dust events, PMS 5003 sensors were unable to report accurate number distributions (R2 values < 0.47) and systematically underestimated particle number concentrations. The results indicate that several questions arise concerning the sensors' capabilities to estimate PM2.5 and PM10 concentrations, since their size distribution did not agree with the reference instruments. [ABSTRACT FROM AUTHOR]

Investigating the vertical distribution of mineral dust masses and their microphysical properties is crucial for accurately assessing the climate effects of dust. However, there are limited studies related to relevant in situ observations over dust source areas. In this study, the near-surface vertical characteristics (within 500 m a.g.l) of dust mass concentrations in five size fractions (PMs: TSP, PM10, PM4, PM2.5, and PM1) were investigated using an unmanned aerial vehicle (UAV) in Tazhong (TZ) in the Taklimakan Desert (TD) in July 2021. To the best of our knowledge, the vertical profiles of particle number concentration (PNC), effective radius (Reff), and volume concentration (Cv) were obtained for the first time by UAV over the TD. Four scenarios of clear sky, floating dust, blowing sand, and dust storm were selected based on the classification criteria for PMs. The PMs, PNC, Reff, and Cv decreased with height for all scenarios. From clear-sky to dust-storm scenarios PMs, PNC, Reff, and Cv in the column gradually increased. Reff (Cv) increased from 1.15 μm (0.08 μm3/μm2) to 4.53 μm (0.74 μm3/μm2). The diurnal variations of PMs, PNC, and Reff (Cv) revealed a unimodal pattern, with the peak occurring between 13:00 and 16:00, due to the evolution of wind speed and the atmospheric boundary layer in TZ. Unexpectedly, among the three postprecipitation scenarios (P1, P2, and P3), the PNC of P2 was smaller than those of P1 and P3. The Reff (Cv) for P2 was similar to or greater than that for dust storms, which may be associated with moist dust particles on the ground surface being carried into the air by wind. These investigations add to our understanding of the mineral dust vertical characteristics over the source area, and provide a meaningful reference for colocated lidar inversion and dust simulations. [ABSTRACT FROM AUTHOR]

A kitchen is an important part of a residence, and air quality in kitchens is a major factor affecting residents' health and performance. Its influence is especially more evident in kitchens with typical Chinese cooking. Thus, it is important to understand distribution characteristics of oil fume particles in Chinese kitchens, and research on typical Chinese kitchen environments and movement characteristics of soot particles should be emphasized. Therefore, to understand the air pollution in kitchen environments, a full-scale experimental platform was built based on common Chinese-style residential kitchens to monitor the soot particles, explore the space–time distribution characteristics of the soot particles, and analyze the variation characteristics and distribution laws of number concentration (NC) and mass concentration (MC). The results indicated that NC0.3μm value fluctuated slightly during the whole cooking process, while NC0.3μm~0.5μm and NC0.5μm~1.0μm fluctuated sharply. During the peak period, NC0.3μm~0.5μm and NC0.5μm~1.0μm were significantly higher than those at the beginning and end of cooking (p < 0.05), and there was no significant difference between values of NC0.3μm~0.5μm and NC0.5μm~1.0μm at the beginning and end of cooking (p > 0.05 for both). NC0.3μm and NC0.3μm~0.5μm were significantly different between each position (p < 0.05 for all). There were also significant differences in NC0.3μm between pure meat dishes, pure vegetable dishes, and mixed dishes (p < 0.001). The proportion of cooking meat will significantly affect the composition and concentration of lampblack particles. Type of dishes is an important influencing factor for the emission rates of particulate pollutants. Small-sized lampblack particles were more likely to diffuse to the surroundings and affected the air quality of the whole room. Particulate matter in the kitchen space during the frying process is more harmful to the health of personnel. [ABSTRACT FROM AUTHOR]

The paper deals with the measurement of individual size components of particulate matter focusing on typical particle size, mass, and number concentrations primarily in the city of Košice (Slovak republic) and the surrounding countryside. The deployment of the sensor IPS-7100 in the 2nd half of December 2022 allowed us to measure the particles smaller than the detection limit of other low-cost optical sensors—namely SPS30 and SEN54. The results show that although the mass concentration of ultrafine particles is negligible in comparison to fine and coarse particles, in terms of number concentration ultrafine particles make up the dominant component of particulate matter, which stands as a warning from the health point of view. [ABSTRACT FROM AUTHOR]

Chainsaw operation is associated with several hazards, including exposure to wood dust, a risk factor which requires serious attention due to health impacts such as respiratory disease. This study aims to investigate the effect of saw chain type and wood species on the mass concentration of airborne wood dust during chainsaw cross-cutting operations. Real-time inhalable and respirable dust measurements in the breathing zone of the chainsaw operator were carried out using a desktop aerosol monitor. Three types of cutter shape (semi chisel, full chisel, and chamfer chisel) and four types of wood species (oak, beech, spruce, and fir) were used in the experiments. The split-plot ANOVA results showed that both respirable and inhalable mass concentrations of wood dust were affected exclusively by wood species. No statistically significant differences were found among particular levels of cutter shape. The highest average mass concentrations of airborne dust were generated by the combination of oak wood and a full chisel cutter. [ABSTRACT FROM AUTHOR]

The regularly reported associations between particulate matter (PM) exposure, and morbidity and mortality due to respiratory, cardiovascular, cancer, and metabolic diseases have led to the reduction in recommended outdoor PM10 and PM2.5 exposure limits. However, indoor PM10 and PM2.5 concentrations in subway systems in many cities are often higher than outdoor concentrations. The effects of these exposures on subway workers and passengers are not well known, mainly because of the challenges in exposure assessment and the lack of longitudinal studies combining comprehensive exposure and health surveillance. To fulfill this gap, we made an inventory of the PM measurement campaigns conducted in the Parisian subway since 2004. We identified 5856 PM2.5 and 18,148 PM10 results from both personal and stationary air sample measurements that we centralized in a database along with contextual information of each measurement. This database has extensive coverage of the subway network and will enable descriptive and analytical studies of indoor PM exposure in the Parisian subway and its potential effects on human health. [ABSTRACT FROM AUTHOR]

Mass concentration is a commonly used but insufficient metric to evaluate the particulate matter (PM) exposure hazard. Recent studies have declared that small particles have more serious impacts on human health than big particles given the same mass concentration. However, state-of-the-art PM sensors cannot provide explicit information of the particle size for further analysis. In this work, we adopt Sauter mean diameter (SMD) as a key metric to reflect the particle size besides the mass concentration. To measure SMD, an effective optical sensing method and a proof-of-concept prototype sensor are proposed by using dual wavelengths technology. In the proposed method, a non-linear conversion model is developed to improve the SMD measurement accuracy for aerosol samples of different particle size distributions and reflective indices based on multiple scattering channels. In the experiment of Di-Ethyl-Hexyl-Sebacate (DEHS) aerosols, the outputs of our prototype sensor demonstrated a good agreement with existing laboratory reference instruments with maximum SMD measurement error down to 7.04%. Furthermore, the simplicity, feasibility and low-cost features of this new method present great potential for distributed PM monitoring, to support sophisticated human exposure hazard assessment. [ABSTRACT FROM AUTHOR]

During 2020–2021, a comprehensive experiment was conducted to study the composition of near-surface atmospheric aerosol in Moscow. The paper considers the experimental data together with synoptic and meteorological conditions. Attention is focused on six episodes of extremely high aerosol mass concentration values: in March and October 2020, as well in March, April, May and July 2021. In all these cases (and only in them), the average daily mass concentration of PM10 aerosol exceeded the Maximum Permissible Concentration (MPC) value (according to Russian standards, 60 μg/m3). The origin of the aerosol during these periods of extreme pollution is revealed, which is the main result of the work. It was shown that the July episode of 2021 was associated with a local intensive anthropogenic source that arose as a result of the active dismantling and demolition of multistory industrial buildings. The remaining spring and autumn episodes were caused by atmospheric transport of both smoke aerosol from various regions with strong biomass fires and dust aerosol from arid zones of the south of European territory of Russia (ETR) with dust wind storms. The cases of atmospheric pollution transport to Moscow region from the other regions are confirmed with the help of air mass transport trajectories (HYSPLIT 4 model) and MERRA-2 reanalysis data on black carbon and/or dust distribution in the atmosphere over ETR. Differences in the elemental composition of the near-surface aerosol of Moscow air during periods with extremely high aerosol concentrations are analyzed in comparison with each other and with unperturbed conditions for the season. [ABSTRACT FROM AUTHOR]

Background: Air pollution is a major global environmental risk factor. Since people spend most of their time indoors, the sole measure of outdoor concentrations is not sufficient to assess total exposure to air pollution. Therefore, the arising interest by the international community to indoor-outdoor relationships has led to the development of various techniques for the study of emission and exchange parameters among ambient and non-ambient pollutants. However, a standardised method is still lacking due to the complex release and dispersion of pollutants and the site conditions among studies. Methods: This review attempts to fill this gap to some extent by focusing on the analysis of the variety of site-specific approaches for the assessment of particulate matter in work and life environments. Results: First, the main analogies and differences between indoor and outdoor particles emerging from several studies are briefly described. Commonly-used indicators, sampling methods, and other approaches are compared. Second, recommendations for further studies based on recent results in order to improve the assessment and management of those issues are provided. Conclusions: This review is a step towards a comprehensive understanding of indoor and outdoor exposures which may stimulate the development of innovative tools for further epidemiological and multidisciplinary research. [ABSTRACT FROM AUTHOR]

Meteorological parameters such as relative humidity have a significant impact on the precision of PM2.5 measurement instruments based on light scattering. Instead of adding meteorological sensors or dehumidification devices used widely in commercial PM2.5 measurement instruments, a novel particle sensor based on multi-angle light scattering and data fusion is proposed to eliminate the effect of meteorological factors. Three photodiodes are employed to collect the scattered light flux at three distinct angles. Weather index is defined as the ratio of scattered light fluxes collected at the 40° and 55° angles, which can be used to distinguish the mass median diameter variation caused by different meteorological parameters. Simulations based on Lorenz-Mie theory and field experiments establish the feasibility of this scheme. Experimental results indicate that mass median diameter has less effect on the photodiode at the 55° angle in comparison with photodiodes at the 40° angle and 140° angle. After correction using the weather index, the photodiode at the 40° angle yielded the best results followed by photodiodes at the 55° angle and the 140° angle. [ABSTRACT FROM AUTHOR]

Particulate matter is a serious source of air pollution in urban areas, where it exerts adverse effects on human health. This article focuses on the study of subduction of shelterbelts for atmospheric particulates. The results suggest that (1) the PM mass concentration is higher in the morning or both morning and noon inside the shelterbelts and lower mass concentrations at other times; (2) the particle mass concentration inside shelterbelt is higher than outside; (3) the particle interception efficiency of the two forest belts over the three months in descending order was PM10 > PM1 > PM2.5; and (4) the two shelterbelts captured air pollutants at rates of 1496.285 and 909.075 kg/month and the major atmospheric pollutant in Beijing city is PM10. Future research directions are to study PM mass concentration variation of shelterbelt with different tree species and different configuration. [ABSTRACT FROM AUTHOR]

The classes and concentrations of volatile organic compounds (VOC) released from fresh and decaying strawberries were investigated and compared. In this study, a total of 147 strawberry volatiles were quantified before and after nine days of storage to explore differences in the aroma profile between fresh strawberries (storage days (SRD) of 0, 1, and 3) and those that had started to decay (SRD = 6 and 9). In terms of concentration, seven compounds dominated the aroma profile of fresh strawberries (relative composition (RC) up to 97.4% by mass, sum concentration): (1) ethyl acetate = 518 mg·m-3, (2) methyl acetate = 239 mg·m-3, (3) ethyl butyrate = 13.5 mg·m-3, (4) methyl butyrate = 11.1 mg·m-3, (5) acetaldehyde = 24.9 mg·m-3, (6) acetic acid = 15.2 mg·m-3, and (7) acetone = 13.9 mg·m-3. In contrast, two alcohols dominated the aroma profile of decayed samples (RC up to 98.6%): (1) ethyl alcohol = 94.2 mg·m-3 and (2) isobutyl alcohol = 289 mg·m-3. Alternatively; if the aroma profiles are re-evaluated by summing odor activity values (SOAV); four ester compounds ((1) ethyl butyrate (6,160); (2) ethyl hexanoate (3,608); (3) ethyl isovalerate (1,592); and (4) ethyl 2-methylbutyrate (942)) were identified as the key constituents of fresh strawberry aroma (SRD-0). As the strawberries began to decay; isobutyl alcohol recorded the maximum OAV of 114 (relative proportion (RP) (SRD = 6) = 58.3%). However, as the decay process continued, the total OAV dropped further by 3 to 4 orders of magnitude--decreasing to 196 on SRD = 6 to 7.37 on SRD = 9. The overall results of this study confirm dramatic changes in the aroma profile of strawberries over time, especially with the onset of decay. [ABSTRACT FROM AUTHOR]

Pneumatic conveying is a standard transportation technique for bulk materials in various industrial fields. Flow metering is crucial for the efficient and reliable operation of such systems and for process control. Capacitive measurement systems are often proposed for this application. In this method, electrodes are placed on the conveyor systems transport line and capacitive signals are sensed. The design of the sensor with regard to the arrangement and the number of electrodes as well as the evaluation of the capacitive sensor signals can be divided into two categories. Calibration-based flow meters use regression methods for signal processing, which are parametrized from calibration measurements on test rigs. Their performance is limited by the extend of the calibration measurements. Electrical capacitance tomography based flow meters use model-based signal processing techniques to obtain estimates about the spatial material distribution within the sensor. In contrast to their calibration-based counterparts, this approach requires more effort with respect to modeling and instrumentation, as typically a larger number of measurement signals has to be acquired. In this work we present a comparative analysis of the two approaches, which is based on measurement experiments and a holistic system model for flow metering. For the model-based analysis Monte Carlo simulations are conducted, where randomly generated pneumatic conveying flow patterns are simulated to analyze the sensor and algorithm behavior. The results demonstrate the potential benefit of electrical capacitance tomography based flow meters over a calibration-based instrument design. [ABSTRACT FROM AUTHOR]

We present the mapping at fine spatial scale of aerosol optical properties using a mobile laboratory equipped with LIDAR (Light Detection And Ranging), sun photometer and in situ instruments for performing on-road measurements. The mobile campaign was conducted from 9 May to 19 May 2017 and had the main objective of mapping the distribution of pollutants in the Beijing and North China Plain (NCP) region. The highest AOD (Aerosol Optical Depth) at 440 nm of 1.34 and 1.9 were recorded during two heavy pollution episodes on 18 May and 19 May 2017, respectively. The lowest Planetary Boundary Layer (PBL) heights (0.5–1.5 km) were recorded during the heavy pollution events, correlating with the highest AOD and southern winds. The transport of desert dust from the Gobi Desert was captured during the mobile measurements, impacting Beijing during 9–13 May 2017. Exploring the NCP outside Beijing provided datasets for regions with scarce ground measurements and allowed the mapping of high aerosol concentrations when passing polluted cities in the NCP (Baoding, Tianjin and Tangshan) and along the Binhai New Area. For the first time, we provide mass concentration profiles from the synergy of LIDAR, sun photometer and in situ measurements. The case study along the Binhai New Area revealed mean extinction coefficients of 0.14 ± 0.10 km−1 at 532 nm and a mass concentration of 80 ± 62 μg/m3 in the PBL (<2 km). The highest extinction (0.56 km−1) and mass concentrations (404 μg/m3) were found in the industrial Binhai New Area. The PM10 and PM2.5 fractions of the total mass concentration profiles were separated using the columnar size distribution, derived from the sun photometer measurements. This study offers unique mobile datasets of the aerosol optical properties in the NCP for future applications, such as satellite validation and air quality studies. [ABSTRACT FROM AUTHOR]

Respirable particulate matter air pollution is positively associated with SARS-CoV-2 mortality. Real-time and accurate monitoring of particle concentration changes is the first step to prevent and control air pollution from inhalable particles. In this research, a new light scattering instrument has been developed to detect the mass concentration of inhalable particles. This instrument couples the forward small-angle single particle counting method with the lateral group particle photometry method in a single device. The mass concentration of four sizes of inhalable particles in the environment can be detected simultaneously in a large area in real-time without using a particle impactor. Different from the traditional light scattering instrument, this new optical instrument can detect darker particles with strong light absorption, and the measurement results mainly depend on the particle size and ignore the properties of the particles. Comparative experiments have shown that the instrument can detect particles with different properties by simply calibrating the environmental density parameters, and the measurement results have good stability and accuracy. [ABSTRACT FROM AUTHOR]

The health impacts of suspended particulate matter (SPM) are significantly associated with size-the smaller the aerosol particles, the stronger the biological effect. Quantitative evaluation of fine and ultrafine particles (FP and UFP) is, therefore, an integral part of ongoing epidemiological studies. The mass concentrations of SPM fractions (especially PM 2.5 , PM 1.0 , PM 0.25 ) were measured in an industrial area using cascade personal samplers and a gravimetric method, and their mass ratio was determined. The results of PM 2.5 , PM 1.0 were also compared with the reference measurement at stationary stations. The mean ratios PM 2.5 /SPM, PM 1.0 /SPM, and PM 1.0 /PM 2.5 were 0.76, 0.65, and 0.86, respectively. Surprisingly, a mass dominance of UFP with an aerodynamic diameter <0.25 μm (PM 0.25 ) was found with mean ratios of 0.43, 0.57, 0.67 in SPM, PM 2.5 and PM 1.0 . The method used showed satisfactory agreement in comparison with reference measurements. The respirable fraction may consist predominantly of UFP. Despite the measures currently being taken to improve air quality, the most biologically efficient UFP can escape and remain in the air. UFP are currently determined primarily as particle number as opposed to the mass concentration used for conventional fractions. This complicates their mutual comparison and determination of individual fraction ratios.

Particulate matter (PM) of different sizes and elemental composition is a leading contributor to indoor and outdoor air pollution in residential areas. We sought to investigate similarities between indoor and outdoor PM 2.5 in three residential areas near a ferromanganese smelter in Meyerton to apportion the emission source(s). Indoor and outdoor PM 2.5 samples were collected concurrently, using GilAir300 plus samplers, at a flow rate of 2.75 L/min. PM 2.5 was collected on polycarbonate membrane filters housed in 37 mm cassettes coupled with PM 2.5 cyclones. Scanning electron microscopy coupled with energy-dispersive spectroscopy was used to study the morphology, and inductively coupled plasma-mass spectroscopy was used to analyse the elemental composition of the PM 2.5 . Mean indoor and outdoor PM 2.5 mass concentrations were 10.99 and 24.95 µg/m 3 , respectively. Mean outdoor mass concentration was 2.27-fold higher than the indoor concentration. Indoor samples consisted of irregular and agglomerated particles, ranging from 0.09 to 1.06 µm, whereas outdoor samples consisted of irregular and spherical particles, ranging from 0.10 to 0.70 µm. Indoor and outdoor PM 2.5 were dominated by manganese, silicon, and iron, however, outdoor PM 2.5 had the highest concentration of all elements. The ferromanganese smelter was identified as the potential main contributing source of PM 2.5 of different physicochemical properties.

A homemade portable no-blind zone laser detection and ranging (lidar) system was designed to map the three-dimensional (3D) distribution of aerosols based on a dual-field-of-view (FOV) receiver system. This innovative lidar prototype has a space resolution of 7.5 m and a time resolution of 30 s. A blind zone of zero meters, and a transition zone of approximately 60 m were realized with careful optical alignments, and were rather meaningful to the lower atmosphere observation. With a scanning platform, the lidar system was used to locate the industrial pollution sources at ground level. The primary parameters of the transmitter, receivers, and detectors are described in this paper. Acquiring a whole return signal of this lidar system represents the key step to the retrieval of aerosol distribution with applying a linear joining method to the two FOV signals. The vertical profiles of aerosols were retrieved by the traditional Fernald method and verified by real-time observations. To effectively and reliably retrieve the horizontal distributions of aerosols, a composition of the Fernald method and the slope method were applied. In this way, a priori assumptions of even atmospheric conditions and the already-known reference point in the lidar equation were avoided. No-blind-zone vertical in-situ observation of aerosol illustrated a detailed evolution from almost 0 m to higher altitudes. No-blind-zone detection provided tiny structures of pollution distribution in lower atmosphere, which is closely related to human health. Horizontal field scanning experiments were also conducted in the Shandong Province. The results showed a high accuracy of aerosol mass movement by this lidar system. An effective quantitative way to locate pollution sources distribution was paved with the portable lidar system after validation by the mass concentration of suspended particulate matter from a ground air quality station. [ABSTRACT FROM AUTHOR]

Under the condition of ultra-low emission for power plants, the particulate matter concentration is significantly lower than that of typical power plants a decade ago, which posed new challenges for the particulate matter monitoring of stationary emission. The monitoring of particulate matter mass concentration based on ensemble light scattering has been found affected by particle size. Thus, this study develops a method of using the scattering angular distribution to obtain the real-time particle size, and then correct the particulate matter concentration with the real-time measured particle size. In this study, a real-time aerosol concentration and particle size measurement setup is constructed with a fixed detector at the forward direction and a rotating detector. The mass concentration is measured by the fixed detector, and the particle size is measured from the intensity ratio of the two detectors. The simulations show that the particle size has power law functionality with the angular spacing of the ripple structure according to Mie theory. Four quartz aerosols with different particle size are tested during the experiment, and the particle size measured from the ripple width is compared with the mass median size measured by an electrical low pressure impactor (ELPI). Both techniques have the same measurement tendency, and the measurement deviation by the ripple width method compared with ELPI is less than 15%. Finally, the measurement error of the real-time mass concentration is reduced from 38% to 18% with correction of the simultaneously measured particle size when particle size has changed. [ABSTRACT FROM AUTHOR]