Aerosol measurement: the use of optical light scattering for the determination of particulate size distribution, and particulate mass, including the semi-volatile fraction

The concentration of particulate matter in the barn air and its influence on the content of heavy metals in milk

Heavy metals are one of the components of smog, which is mainly the product of burning fossil fuels in residential buildings. These elements, introduced into the body of cattle by inhalation, may enter the milk. The goal of this study was to assess the impact of particulate pollution in the atmospheric air on the concentration of particulate matter in the air of a dairy cattle barn and on the content of selected heavy metals in milk from cows present in the building. Measurements were taken between November and April (148 measurement days). The calculations carried out showed a high correlation (RS = + 0.95) between the concentrations of particulates measured outside and inside the barn, which is indicative of a significant impact of the atmospheric air on the particulate pollution level of the livestock building. The number of days in excess of the daily standard for PM10 inside was 51. The conducted analysis of the chemical composition of the milk collected under high particulate pollution (February) showed that the permitted lead level had been exceeded-21.93 µg/kg (norm 20.00 µg/kg).

Representativeness of the particulate matter pollution assessed by an official monitoring station of air quality in Santiago, Chile: projection to human health

Santiago, capital city of Chile, presents air pollution problems for decades mainly by particulate matter, which significantly affects population health, despite national authority efforts to improve air quality. Different properties of the particulate matter (PM₁₀, PM_2.5 and PM₁ fractions, particle surface and number) were measured with an optical spectrometer. The sampling was done during spring 2019 at different sites within the official representative area of Independencia monitoring station (ORMS-IS). The results of this study evidence large variations in PM mass concentration at small-scale areas within the ORMS-IS representative zone, which reports the same value for the total area. Results from PM properties such as PM₁, particle number and particle surface distribution show that these properties should be incorporated in regular monitoring in order to improve the understanding of the effects of these factors on human health. The use of urban-climate canopy-layer models in a portion of the sampled area around the monitoring station demonstrates the influence of street geometry, building densities and vegetation covers on wind velocity and direction. These factors, consequently, have an effect on the potential for air pollutants concentrations. The results of this study evidence the existence of hot spots of PM pollution within the area of representativeness of the ORMS-IS. This result is relevant from the point of view of human health and contributes to improve the effectiveness of emission reduction policies.

Summary of PM2.5 measurement artifacts associated with the Teledyne T640 PM Mass Monitor under controlled chamber experimental conditions using polydisperse ammonium sulfate aerosols and biomass smoke

Particulate matter (PM) is a major primary pollutant emitted during wildland fires that has the potential to pose significant health risks to individuals/communities who live and work in areas impacted by smoke events. Limiting exposure is the principle measure available to mitigate health impacts of smoke and therefore the accurate determination of ambient PM concentrations during wildland fire events is critical to protecting public health. However, monitoring air pollutants in smoke impacted environments has proven challenging in that measurement interferences or sampling conditions can result in both positive and negative artifacts. The EPA has performed research on methods for the measurement of PM2.5 in a series of laboratory-based studies including evaluation in smoke. This manuscript will summarize the results of the laboratory-based evaluation of federal equivalent method (FEM) monitors for PM2.5 with particular attention being given to the Teledyne-API Model T640 PM Mass monitor, as compared to the filter-based federal reference method (FRM). The T640 is an optical-based PM monitor and has been gaining wide use by state and local agencies in monitoring for PM2.5 U.S. National Ambient Air Quality Standards (NAAQS) attainment. At present, the T640 (includes both T640 and T640×) comprises ~44% of the PM2.5 FEM monitors in U.S. regulatory monitoring networks. In addition, the T640 has increasingly been employed for the higher time resolution comparison/evaluation of low-cost PM sensors including during smoke impacted events. Results from controlled non-smoke laboratory studies using generated ammonium sulfate aerosols demonstrated a generally negative T640 measurement artifact that was significantly related to the PM2.5 concentration and particle size distribution. Results from biomass burning chamber studies demonstrated positive and negative artifacts significantly associated with PM2.5 concentration and optical wavelength-dependent absorption properties of the smoke aerosol.Implications: The results detailed in this paper will provide state and local air monitoring agencies with the tools and knowledge to address PM2.5 measurement challenges in areas frequently impacted by wildland fire smoke. The observed large positive and negative artifacts in the T640 PM mass determination have the potential to result in false exceedances of the PM2.5 NAAQS or in the disqualification of monitoring data through an exceptional event designation. In addition, the observed artifacts in smoke impacted air will have a detrimental effect on providing reliable public information when wildfires occur and also in identifying reference measurements for small sensor evaluation studies. Other PM2.5 FEMs such as the BAM-1022 perform better in smoke and are comparable to the filter-based FRM. Care must be taken in choosing high time resolution FEM monitors that will be operated at smoke impacted sites. Accurate methods, such as the FRM and BAM-1022 will reduce the burden of developing and reviewing exceptional event request packages, data loss/disqualification, and provide states with tools to adequately evaluate public exposure risks and provide accurate public health messaging during wildfire/smoke events.

A Novel Optical Instrument for Measuring Mass Concentration and Particle Size in Real Time

Particle mass and particulate size are two important parameters used to characterize the aerosol. Currently, there are a few methods for measuring particle mass concentration and particle size. However, the existing methods have their own shortcomings. In this article, we describe a novel laser scattering instrument that measures mass concentration and particle size in real time over a wide concentration range. This instrument combines laser scattering and time-of-flight aerodynamics in one optical device. There are two innovations in this paper: (1) Two APD detectors are used to receive scattered light. One receives forward-scattered light and the other receives side-scattered light. The advantage is that the sensitivity of the detector is increased greatly, and the ratio of forward and side scattering is used to further obtain the size and shape information of the particles. (2) In order to measure the high concentrations of aerosol, a high-speed ADC and FPGA is combined to achieve an anti-overlap algorithm objective. It has been verified by experiments that the anti-overlapping algorithm can effectively improve the applicability of the aerodynamic particle size spectrometer under high concentration conditions.

Direct-reading instruments for aerosols: A review for occupational health and safety professionals part 1: Instruments and good practices

With advances in technology, there are an increasing number of direct-reading instruments available to occupational health and safety professionals to evaluate occupational aerosol exposures. Despite the wide array of direct-reading instruments available to professionals, the adoption of direct-reading technology to monitor workplace exposures has been limited, partly due to a lack of knowledge on how the instruments operate, how to select an appropriate instrument, and challenges in data analysis techniques. This paper presents a review of direct-reading aerosol instruments available to occupational health and safety professionals, describes the principles of operation, guides instrument selection based on the workplace and exposure, and discusses data analysis techniques to overcome these barriers to adoption. This paper does not cover all direct-reading instruments for aerosols but only those that an occupational health and safety professional could use in a workplace to evaluate exposures. Therefore, this paper focuses on instruments that have the most potential for workplace use due to their robustness, past workplace use, and price with regard to return on investment. The instruments covered in this paper include those that measure aerosol number concentration, mass concentration, and aerosol size distributions.

Seasonal variations of particle number concentration and its relationship with PM2.5 mass concentration in industrial-residential airshed

The smaller particles that dominate the particle number concentration (PNC) in the ambient air only contribute to a small percentage of particulate matter (PM) mass concentration although present in high particle number concentration. These small particles may be neglected upon assessing the health impacts of the PM. Hence, the knowledge on the particle number concentration size distribution deserves greater attention than the particulate mass concentration. This study investigates the measurement of the particle mass concentrations (PM_2.5) and PNC of 0.27 μm < Dp < 4.50 μm during the southwest (SW), inter-monsoon (IM) and northeast (NE) monsoons in the industrial-residential airshed of Skudai, Johor Bahru, Malaysia. The PM_2.5 mass concentrations and PNC were measured using a multi-channel GRIMM Environmental Dust Monitor (GRIMM EDM-SVC 365) equipped with a global positioning system. Diurnal variations, statistical analysis and regression plots were utilised from a six-month hourly data set to examine the patterns of the PNC size distributions and its relationships with the PM_2.5 mass concentration. The overall mean PM_2.5 mass concentration was 21.85 μg m^-3, with the 24 h mean values of 26.80 μg m^-3, 26.08 μg m^-3 and 13.76 μg m^-3 for the SW, IM and NE monsoons, respectively. It was found that the hourly mean of PNC was recorded at the highest concentration during the SW monsoon (373.20 # cm^-3). The particles in the accumulation mode (Dp < 1.0 μm) were the prevalent form of the particle number concentration (94-98%). The scatter plots between the PM_2.5 mass concentration and particle number size distribution showed that the PNC mode of 0.27 < Dp < 1.0 μm has the highest correlation value of r² = 0.87 due to the emission from the anthropogenic activities. The results of this study highlight the importance of the PNC measurement in the seasonal variations of the PM_2.5 pollution, indicating the significance of the regional-scale emission control actions in the local air quality management.

Ultra-high resolution particle size measurement based on scattering spectrum analysis-simulation and experiment

This paper focuses on the properties of light scattering spectra from a spherical particle and their application for particle size measurement. The influence of particle size and scattering angle on the scattering spectra are investigated and simulated. An ultra-resolution particle dimension measurement method was proposed based on detecting the peak of scattering spectra. An accurate spectral peak location strategy based on the spectral shape features is adopted to reduce the spectra peak positioning error caused by dispersion. The size of smaller particle is measured by locating a wide scattering spectral peak at a larger scattering angle to achieve higher measurement sensitivity, while the size of larger particle is measured by locating a narrow scattering spectral peak at a smaller angle to achieve a larger measurement range. If the spectral resolution of the spectrometer is 0.8 nm, the particle size resolution of 1.1 nm and 8.3 nm are achieved for measured particles with sizes ranging from 0.25µm to 1µm and measured particles with sizes ranging from 1µm to 10µm, respectively. And if the spectrometer with picometer resolution is used, the particle size resolution is expected to be on the order of picometers.

Characteristics and health effects of particulate matter emitted from a waste sorting plant

Solid waste components can be recycled in waste paper and cardboard sorting plants (WPCSP) through a multistep process. This work collected 15 samples every six days from each of the 9 points selected to study the processes taking place in a WPCSP (135 particulate matter samples total). Examining the concentration and size fraction of particulate matter (i.e., PM₁, PM_2.5 and PM₁₀) in WPCSP is an essential issue to notify policy makers about the health impacts on exposed workers. The major activities for increasing of the concentration of PM in various processing units in the WPCSP, especially in hand-picking routes I and II were related to manual dismantling, mechanical grinding, mechanical agitation, and separation and movement of waste. The results of this work showed that a negative correlation between temperature and particulate matter size followed the order PM₁₀ > PM_2.5 > PM₁. Exposure to PM_2.5 and PM₁₀ in the WPCSP lead to possible risk (HI = 5.561 and LTCRs = 3.41 × 10^-6 to 9.43 × 10^-5 for PM_2.5 and HI = 7.454 for PM₁₀). The exposure duration and the previous concentrations had the most effect on the ILCRs and HQs for PM_2.5 and PM₁₀ in all sampling sites. Hence, because WPCSP are infected indoor environments (I/O ratio > 1), the use of control methods such as isolation of units, misting systems, blower systems equipped with bag houses, protective equipment, a mechanical ventilation system, and additional natural ventilation can reduce the amount of suspended PM, enhance worker safety, and increase the recycling rate.

Combining Sun-Photometer, PM Monitor and SMPS to Inverse the Missing Columnar AVSD and Analyze Its Characteristics in Central China

Columnar aerosol volume size distribution (AVSD) is an important atmospheric parameter that shows aerosol microphysical properties and can be used to analyze the impact of aerosols on the radiation budget balance, as well as regional climate effects. Usually, columnar AVSD can be obtained by using a sun photometer, but its observation conditions are relatively strict, and the columnar AVSD will be missing in cloudy or hazy weather due to cloud cover and other factors. This study introduces a novel algorithm for inversion of missing columnar AVSD under haze periods by using a machine learning approach and other ground-based observations. The principle is as follows. We are based on joint observational experiments. Since the scanning mobility particle sizer (SMPS) and particulate matter (PM) monitor sample the surface data, they can be stitched together to obtain the surface AVSD according to their observation range. Additionally, the sun-photometer scans the whole sky, so it can obtain columnar AVSD and aerosol optical depth (AOD). Then we use the back propagation neural network (BPNN) model to establish the relationship between the surface AVSD and the columnar AVSD and add AOD as a constraint. Next, the model is trained with the observation data of the same period. After the model training is completed, the surface AVSD and AOD can be used to invert the missing columnar AVSD during the haze period. In experiments on the 2015 dataset, the results show that the correlation coefficient and root mean square error between our model inversion results and the original sun photometer observations were 0.967 and 0.008 in winter, 0.968 and 0.010 in spring, 0.969 and 0.013 in summer, 0.972 and 0.007 in autumn, respectively. It shows a generally good performance that can be applied to the four seasons. Furthermore, the method was applied to fill the missing columnar AVSD of Wuhan, a city in central China, under adverse weather conditions. The final results were shown to be consistent with the climatic characteristics of Wuhan. Therefore, it can indeed solve the problem that sun photometer observations are heavily dependent on weather conditions, contributing to a more comprehensive study of the effects of aerosols on climate and radiation balance.

Seasonal Distribution of Atmospheric Coarse and Fine Particulate Matter in a Medium-Sized City of Northern China

Atmospheric particulate matter (PM) was measured continuously at an urban site in Baoji city in northern China in 2018 to investigate the seasonal distribution characteristics. Coarse PM (PM_2.5–10) was more prevalent in spring, substantially due to the regional transport of dust. High loadings of coarse PM were found at night compared to daytime, which could result from high production and unfavorable dispersion conditions. Fine PM (PM_2.5) constituted, on average, 54% of the total PM mass concentration, whereas it contributed more than 97% of the total PM number concentration. The number and mass concentrations of fine PM increased substantially in the winter, which was possibly due to the enhanced production of atmospheric secondary processes and coal combustion. Precursor gaseous pollutants and meteorology greatly influenced the PM distributions. Fine PM was associated more strongly with gas pollutants than coarse PM, which suggested that it largely originated from secondary production and combustion sources. High relative humidity appeared to promote the production of fine PM, whereas it facilitated the removal of coarse PM. This study highlights that different air-pollution control strategies should be used for coarse and fine PM according to the distribution characteristics and influencing factors in similar medium-sized urban areas.

Spatial Distribution of Aerosol Characteristics over the South Atlantic and Southern Ocean Using Multiyear (2004–2021) Measurements from Russian Antarctic Expeditions

Since 2004, we have carried out yearly measurements of physicochemical aerosol characteristics onboard research vessels at Southern Hemisphere high latitudes (34–72° S; 45° W–110° E). In this work, we statistically generalize the results from multiyear (2004–2021) measurements in this area of the aerosol optical depth (AOD) of the atmosphere, concentrations of aerosol and equivalent black carbon (EBC), as well as the ionic composition of aerosol. A common regularity was that the aerosol characteristics decreased with increasing latitude up to the Antarctic coast, where the aerosol content corresponded to the global background level. Between Africa and Antarctica, AOD decreased from 0.07 to 0.024, the particle volume decreased from 5.5 to 0.55 µm3/cm3, EBC decreased from 68.1 to 17.4 ng/m3, and the summed ion concentration decreased from 24.5 to 2.5 µg/m3. Against the background of the common tendency of the latitude decrease in aerosol characteristics, we discerned a secondary maximum (AOD and ion concentrations) or a plateau (aerosol and EBC concentrations). The obtained spatial distribution of aerosol characteristics qualitatively agreed with the model-based MERRA-2 reanalysis data, but showed quantitative differences: the model AOD values were overestimated (by 0.015, on average); while the EBC concentrations were underestimated (by 21.7 ng/m3). An interesting feature was found in the aerosol spatial distribution in the region of Antarctic islands: at a distance of 300 km from the islands, the concentrations of EBC decreased on average by 29%, while the aerosol content increased by a factor of 2.5.

Large spatio-temporal variations of size-resolved particulate matter and volatile organic compounds in urban area with heavy traffic

A monitoring campaign, the first of this kind for a heavy traffic urban area of Vietnam, was conducted which generated nearly 200 daily filter samples of PM_2.5, PM₁₀, and black carbon (BC), 1300 online hourly PMx (PM₁₀, PM_2.5, and PM₁), 900 hourly/bi-hourly BTEX data, 700 h of traffic counts, and online meteorology records. PMx and BTEX levels show large horizontal gradients across this small urban area of 300 m width suggesting that the pollution data should be generated with sufficient spatial resolutions for assessment of the exposure and health effects. This paper focuses on analyzing PMx with reference to the previously published BTEX to provide a more complete picture of the traffic-related pollution in the area. Spatio-temporal variations of pollutants are analyzed in relation to traffic flows and fleet compositions, weekday-weekend effects, local and regional meteorology. PM₁₀ and BTEX levels had larger variations between the sites indicating their stronger associations with the traffic activities than the finer particles. Twenty-four-hour (24 h) PM_2.5 levels ranged between 19 and 191 µg/m³ with high PM₁/PM_2.5 ratios of above 0.8 at ambient site (AA) and above 0.7 at roadsides. Multivariate relationship analysis (PCA) for the bi-hourly datasets of meteorology, traffic flows, and pollutant levels indicated overwhelming influence of on-road traffic fleet compositions on the roadside pollutants levels. At AA, PCA results showed a complex interaction between local emissions, meteorological conditions, and regional/long-range transport. Higher pollution levels were associated with the airmass types having the continental origin and pathways.

Effects of aerosol particle size on the measurement of airborne PM2.5 with a low-cost particulate matter sensor (LCPMS) in a laboratory chamber

Previous validation studies found a good linear correlation between the low-cost particulate matter sensors (LCPMS) and other research grade particulate matter (PM) monitors. This study aimed to determine if different particle size bins of PM would affect the linear relationship and agreement between the Dylos DC1700 (LCPMS) particle count measurements (converted to PM2.5 mass concentrations) and the Grimm 11R (research grade instrument) mass concentration measurements. Three size groups of PM2.5 (mass median aerodynamic diameters (MMAD): < 1 µm, 1-2 µm, and > 2 µm) were generated inside a laboratory chamber, controlled for temperature and relative humidity, by dispersing sodium chloride crystals through a nebulizer. A linear regression comparing 1-min average PM2.5 particle counts from the Dylos DC1700 (Dylos) to the Grimm 11R (Grimm) mass concentrations was estimated by particle size group. The slope for the linear regression was found to increase as MMAD increased (< 1 µm, 0.75 (R2 = 0.95); 1-2 µm, 0.90 (R2 = 0.93); and > 2 µm, 1.03 (R2 = 0.94). The linear slopes were used to convert Dylos counts to mass concentration, and the agreement between converted Dylos mass and Grimm mass was estimated. The absolute relative error between converted Dylos mass and the Grimm mass was smaller in the < 1 µm group (16%) and 1-2 µm group (16%) compared to the > 2 µm group (32%). Therefore, the bias between converted Dylos mass and Grimm mass varied by size group. Future studies examining particle size bins over a wider range of coarse particles (> 2.5 µm) would provide useful information for accurately converting LCPMS counts to mass concentration.

Particulate matter exposure in biomass-burning homes of different communities of Brahmaputra Valley

Biomass burning for cooking prevalent in the developing countries is an issue which has been a concern for the past several decades for the noxious emissions and subsequent effects on the health of women and children due to the exposure of particulate matter (PM) and other gases. In this study, PM (PM₁, PM_2.5, and PM₁₀) were measured in biomass-burning households for different communities of Brahmaputra Valley region northeast India by a 31-channel aerosol spectrometer. The levels of emission of PM in the case of different community households were found to be significantly different. Also, the emission characteristics of different cooking time of the day were found to be different across communities. The emission levels in the biomass-burning households were compared with emission in household using "clean" LPG fuel, and it was found that the biomass fuels emitted 10-12 times more PM_2.5 and 6-7 times more PM₁₀. The number densities of the emission were found to be more with smaller sizes of particulates which could explain why such biomass-burning emissions can pose with greater health risks. The exposure doses were calculated and were found to be about three times higher in biomass-burning houses than "clean" LPG fuel. It is important to note that the exposure from biomass burning while cooking has a gender perspective. The woman of the house generally takes care of the activities in the kitchen and get exposed to the noxious PM and the gases. Children often accompany their mothers and face the same fate.

Volumetric monitoring of airborne particulate matter concentration using smartphone-based digital holographic microscopy and deep learning

Airborne particulate matter (PM) has become a global environmental issue. This PM has harmful effects on public health and precision industries. Conventional air-quality monitoring methods usually utilize expensive equipment, and they are cumbersome to handle for accurate and high throughput measurements. In addition, commercial particle counters have technical limitations in high-concentration measurement, and data fluctuations are induced during air sampling. In this study, a novel smartphone-based technique for monitoring airborne PM concentrations was developed using smartphone-based digital holographic microscopy (S-DHM) and deep learning network called Holo-SpeckleNet. Holographic speckle images of various PM concentrations were recorded by the S-DHM system. The recorded speckle images and the corresponding ground truth PM concentrations were used to train deep learning algorithms consisting of a deep autoencoder and regression layers. The performance of the proposed smartphone-based PM monitoring technique was validated through hyperparameter optimization. The developed S-DHM integrated with Holo-SpeckleNet can be smartly and effectively utilized for portable PM monitoring and safety alarm provision under perilous environmental conditions.

Coastal meteorology on the dispersion of air particles at the Bachok GAW Station

Meteorology over coastal region is a driving factor to the concentration of air particles and reactive gases. This study aims to conduct a research to determine the level of year-round air particles and the interaction of the meteorological driving factors with the particle number and mass in 2018, which is moderately influenced by Southeast Asian haze. We obtained the measurement data for particle number count (PNC), mass, reactive gases, and meteorological factors from a Global Atmospheric Watch (GAW) station located at Bachok Marine Research Center, Bachok, Kelantan, Malaysia. For various timeseries and correlation analyses, a 60-second resolution of the data has been averaged hourly and daily and visualized further. Our results showed the slight difference in particle behavior that is either measured by unit mass or number count at the study area. Diurnal variations showed that particles were generally high during morning and night periods. Spike was observed in August for PM_2.5/PNC_2.5 and PM₁₀/PNC₁₀ and in November for PM_Coarse/PNC_Coarse. From a polar plot, the particles came from two distinct sources (e.g., seaside and roadside) at the local scale. Regional wind vector shows two distinct wind-blown directions from northeast and southwest. The air mases were transported from northeast (e.g., Philippines, mainland China, and Taiwan) or southwest (e.g., Sumatra) region. Correlation analysis shows that relative humidity, wind direction, and pressure influence the increase in particles, whereas negative correlation with temperature is observed, and wind speed may have a potential role on the decline of particle concentration. The particles at the study area was highly influenced by the changes in regional wind direction and speed.

High particulate matter burden by cigarillos: A laser spectrometric analysis of second-hand smoke of common brands with and without filter

Although the global tobacco market of cigarillos is substantial, little is known about their particulate matter (PM) emissions. For exposure risk assessment of cigarillos, the PM fractions PM10, PM2.5, and PM1 of eight cigarillo brands (four with filters) and a reference cigarette were measured. For this purpose, second-hand smoke was generated by an automatic smoke pump in a measuring chamber with a volume of 2.88 m³. The mean particle concentrations of the cigarillos ranged from 2783 μg/m³ to 6686 μg/m³ for PM10, from 2767 μg/m³ to 6585 μg/m³ for PM2.5, and from 2441 to 4680 μg/m³ for PM1. Mean concentrations of the reference cigarette for PM10, PM2.5, and PM1 were 4400 μg/m³, 4335 μg/m³, and 3289 μg/m³, respectively. Filter-tipped cigarillos showed between 5% and 38% lower PM10 and PM2.5 levels, respectively, and between 4% and 30% lower PM1 levels. Our findings show generally high PM emissions for all investigated tobacco products. Therefore, the declaration of PM amounts to government authorities should be mandatory for all tobacco products. Policymakers should ensure that corresponding information will be provided in the future.

Marathon race performance increases the amount of particulate matter deposited in the respiratory system of runners: an incentive for "clean air marathon runs"

Background

In the last decades, marathon running has become a popular form of physical activity among people around the world. It should be noticed that the main marathon races are performed in large cities, where air quality varies considerably. It is well established that breathing polluted air results in a number of harmful effects to the human body. However, there have been no studies to show the impact of marathon run performance on the amount of the deposition of varied fractions of airborne particulate matter (PM) in the respiratory tract of runners. This is why the present study sought to determine the impact of marathon run performance in the air of varying quality on the deposition of the PM₁, PM_2.5, PM₁₀ in the respiratory tract in humans.

Methods

The PM₁, PM_2.5 and PM₁₀ deposition was determined in an “average runner” (with marathon performance time 4 h: 30 min) and in an “elite marathon runner” (with marathon performance time 2 h: 00 min) at rest, and during a marathon race, based on own measurements of the PM content in the air and the size-resolved DF(d) profile concept.

Results

We have shown that breathing air containing 50 µg m⁻³ PM₁₀ (a borderline value according to the 2006 WHO standard - still valid) at minute ventilation (V_E) equal to 8 L min⁻¹ when at rest, resulted in PM₁₀deposition rate of approximately 9 µg h⁻¹, but a marathon run of an average marathon runner with the V_E = 62 L min⁻¹ increased the deposition rate up to 45 µg h⁻¹. In the elite runner, marathon run with the V_E= 115 L min⁻¹ increased PM₁₀ deposition rate to 83 µg h⁻¹. Interestingly, breathing the air containing 50 µg m⁻³of PM₁₀ at the V_E = 115 L min⁻¹by the elite marathon runner during the race resulted in the same PM₁₀deposition rate as the breathing highly polluted air containing as much as 466 µg m⁻³ of PM₁₀ when at rest. Furthermore, the total PM₁₀ deposition in the respiratory tract during a marathon race in average runners is about 22% greater (203 / 166 = 1.22) than in elite runners. According to our calculations, the concentration of PM₁₀in the air during a marathon race that would allow one not to exceed the PM₁₀ deposition rate of 9 µg h⁻¹should be lower than 10 µg m⁻³ in the case of an average runner, and it should be lower than 5.5 µg m⁻³ in the case of an elite runner.

Conclusions

We conclude that a marathon run drastically increases the rate of deposition of the airborne PM in the respiratory tract of the runners, as a consequence of the huge V_E generated during the race. A decrease of the PM content in the air attenuates this rate. Based on our calculations, we postulate that the PM₁₀ content in the air during a “clean air marathon run”, involving elite marathon runners, should be below 5.5 µg m⁻³.

Accurate real-time monitoring of high particulate matter concentration based on holographic speckles and deep learning

Accurate real-time monitoring of particulate matter (PM) has emerged as a global issue due to the hazardous effects of PM on public health and industry. However, conventional PM monitoring techniques are usually cumbersome and require expensive equipments. In this study, Holo-SpeckleNet is proposed as a fast and accurate PM concentration measurement technique with high throughput using a deep learning based holographic speckle pattern analysis. Speckle pattern datasets of PMs for a wide range of PM concentrations were acquired by using a digital in-line holography microscopy system. Deep autoencoder and regression algorithms were trained with the captured speckle pattern datasets to directly measure PM concentration from speckle pattern images without any air intake device and time-consuming post image processing. The proposed technique was applied to predict various PM concentrations using the test datasets, optimize hyperparameters, and compare its performance with a convolutional neural network (CNN) algorithm. As a result, high PM concentration values can be measured over air quality index of 150, above which human exposure is unhealthy. In addition, the proposed technique exhibits higher measurement accuracy and less overfitting than the CNN with a relative error of 7.46 ± 3.92%. It can be applied to design a compact air quality monitoring device for highly accurate and real-time measurement of PM concentrations under hazardous environment, such as factories or construction sites.

Review of the Newly Developed, Mobile Optical Sensors for Real-Time Measurement of the Atmospheric Particulate Matter Concentration

Due to the adverse effects on human health and the environment, air quality monitoring, specifically particulate matter (PM), has received increased attention over the last decades. Most of the research and policy actions have been focused on decreasing PM pollution and the development of air monitoring technologies, resulting in a decline of total ambient PM concentrations. For these reasons, there is a continually increasing interest in mobile, low-cost, and real-time PM detection instruments in both indoor and outdoor environments. However, to the best of the authors’ knowledge, there is no recent literature review on the development of newly designed mobile and compact optical PM sensors. With this aim, this paper gives an overview of the most recent advances in mobile optical particle counters (OPCs) and camera-based optical devices to detect particulate matter concentration. Firstly, the paper summarizes the particulate matter effects on human health and the environment and introduces the major particulate matter classes, sources, and characteristics. Then, it illustrates the different theories, detection methods, and operating principles of the newly developed portable optical sensors based on light scattering (OPCs) and image processing (camera-based sensors), including their advantages and disadvantages. A discussion concludes the review by comparing different novel optical devices in terms of structures, parameters, and detection sensitivity.

Enhanced detection and sizing algorithm to improve LOAC optical particle counter performances

The light optical aerosols counter (LOAC) instrument is an optical aerosol counter that allows atmospheric particles from 0.2 to 50 µm to be individually counted and classified by size. The scattered light due to the interaction between a particle and a laser beam is captured by photodiodes and produces an electric pulse. Detecting these pulses and measuring their amplitude is a key process to measure the particle size. This paper first details the current method to achieve such estimation and proposes a correlation algorithm to improve the detection and the assessment of particle sizes. In the last section, some test results are presented to demonstrate the performance of this new algorithm.

Low-cost air pollution monitoring system-an opportunity for reducing the health risk associated with physical activity in polluted air

The issue of air pollution by particulate matter (PM) concerns many places in the world. At the same time, many residents undertake physical activity (recreation, rehabilitation, sport) in the open air. Generally, the amount of dust concentration depends on both the place (center or periphery of the city) and the time of day. In the present study we describe the outcome of monitoring of the state of air pollution by particle matter (PM₁₀) in the Kraków agglomeration area in order to show that it can provide information concerning air quality in the area where people practice varied kinds of sports in the open air. The measurements of PM₁₀ have been made by a few stations with identical construction working as one network. The details of the air pollution monitoring system and its data quality verification have been described. The network stations made multipoint observations across the Kraków Metropolitan Area during the year 2017 in eight locations. The locations selected represent a diverse spectrum of terrain conditions in which the Kraków agglomeration community undertakes physical activity. For most months of 2017, the minimum monthly average 4-hour PM₁₀ concentrations were recorded between 10–14 h, regardless of location, whereas the maximum was between 18–22. We also noticed a huge differences in the average monthly value of PM₁₀ in some locations within the Kraków agglomeration—ranging between 4.9–339.0 µg m⁻³. This indicates that some regions of the city are more suitable for performance of physical activity in the open air than others. In conclusion, we postulate that a low-cost air pollution monitoring system is capable of providing valuable information concerning air quality in a given region, which seems to be of importance also to people who practice varied sports activities in the open air.

Effects of dust phenomenon on heavy metals in raw milk in western Iran

Introduction. After the Iraq war, the dust phenomenon has increased in western Iran. Our study aimed to evaluate the effect of the dust phenomenon on the content of heavy metals in raw milk in Ilam province. Study objects and methods. The dust samples were collected during one year. The concentrations of dust particles were determined with the Enviro Check Laser System, using the Dust Monitor Check. The concentration of heavy metals in dust was determined by using the high volume air samplers and glass fiber filters. Results and discussion. Heavy metals (lead, arsenic, zinc, copper, and iron) were measured at four sampling sites in raw milk by the atomic absorption method. The mean and standard deviations of dust particulate matter (PM10 and PM2.5) were 105.6 ± 90.5 and 25.9 ± 15.4 μg/m3, respectively. The amounts of arsenic, zinc, lead, and copper were higher in the spring and summer. Lead levels in western and southern regions were higher than those in the east, center, and north. Conclusion. We found similar trends for arsenic, zinc, copper, and iron in raw milk. Our results showed the potential effect of the dust phenomenon on the presence of heavy metals in raw milk.

Estimating radiative impacts of black carbon associated with mixing state in the lower atmosphere over the northern North China Plain

Black carbon (BC) exerts important radiative effects over regions with intensive emissions. This study presents in-situ aircraft measurements of BC vertical profiles including mass loading, size distribution and mixing state, spanning a range of pollution levels in both warm and cold seasons over Beijing. The development of planetary boundary layer (PBL) influenced the properties of pollutants at low levels, and regional transport from the southwest elevated the pollution at higher altitudes. Thicker coatings of BC were associated with higher pollution in the PBL, where interactions between BC and other substances intensively took place. Considering the mixing state of BC, the absorption efficiency could be potentially increased by up to 86% and 60% in the PBL and lower free troposphere, respectively. Including a column-integrated absorption enhancement, the in-situ constrained absorption aerosol optical depth at wavelength 870 nm (AAOD₈₇₀) improved the agreement with AERONET by 28%, but the in-situ measurement remained 19% lower. A radiative transfer model finds a BC heating rate of 0.1-0.3 K/d and 0.5-3.1 K/d for less and more polluted environments respectively, and the BC coating effect could positively introduce a +0.1-4.2 Wm^-2 radiative forcing. The presence of aerosol layer enhanced the positive vertical gradient of heating rate by redistributing the actinic flux. In particular, this gradient was further enhanced by introducing thickly-coated BC at higher level during the regional transport events, which may promote the temperature inversion and further depress the PBL development on polluted days.

The impact of smog on the concentration of particulate matter in the antelope house in the Silesian zoological garden

Persistent negligence in the field of environmental protection in Poland as well as strong dependance of the energy sector on the fossil fuels have led to serious pollution of the air with particulate matter, which at high concentrations is capable of penetrating into the buildings. The aim of this study is to assess the impact of particulate airborne pollution on the concentration of particulate matter inside the antelope house in the Silesian Zoological Garden located within the Upper Silesia in Poland. The research was conducted from February to May in 2018. The records taken in the research period show that the concentration of PM10 exceeded the level of 50 µg/m³ outside the building during 26 days and 11 days when it comes to the concentration of particulate matter inside the antelope house. The quantity of particulate matter in the antelope house is strongly correlated with the concentration of the particles in the air. Despite fitting existing ventilation system with a filter that reduces the dust level by 60% during the highest level of smog, particulate matter concentration in the antelope house exceeded acceptable limit for PM10 more than twofold. Particle size-fraction analysis revealed that as much as 85% of the particles detected in the studied compartment constitute PM2.5.

High Particulate Matter Burden of Cigarettes from the United Arab Emirates and Germany: Are There Country-Specific Differences?

Although the big tobacco companies offer the same cigarette brands across countries, little is known about the potential regional differences of the particulate matter (PM) emissions of apparently equal brands. PM emissions of three cigarette brands (Marlboro Gold, Winston Red resp. Classic, Parliament Platinum resp. Night Blue) from the United Arab Emirates (UAE) and Germany were analysed. Second-hand smoke was produced in a 2.88 m³ measuring cabin by an automatic environmental tobacco smoke emitter. PM size fractions PM₁₀, PM_2.5, and PM₁ were detected in real-time using laser aerosol spectrometry. Depending on the PM fraction Marlboro cigarettes from UAE showed 33%-35% higher PM amounts. Moreover, Winston cigarettes from UAE showed distinctly higher PM values (28-31%) than the German counterparts. The "lighter" Parliament from UAE emitted 3%-9% more PM than the German one. The measured mean PM₁₀ values laid between 778 and 1163 µg/m³ (mean PM_2.5: 777-1161 µg/m³; mean PM₁: 724-1074 µg/m³). That means smoking in enclosed rooms causes massive PM burden. The PM emission of equal or similar tobacco products from different countries can differ distinctly. Hence, the declaration of PM emission values, besides nicotine, tar, and carbon monoxide amounts, should be obligatory worldwide. Furthermore, complete information about the ingredients and production processes of tobacco products should be provided to health officials and the public. This can help to minimise or ban substances or product designs that make smoking even more harmful, and to enhance the awareness of the risks of smoking.

Laboratory and field evaluation of real-time and near real-time PM2.5 smoke monitors

Increases in large wildfire frequency and intensity and a longer fire season in the western United States are resulting in a significant increase in air pollution, including concentrations of PM_2.5 (particulate matter <2.5 µm in aerodynamic diameter) that pose significant health risks to nearby communities. During wildfires, government agencies monitor PM_2.5 mass concentrations providing information and actions needed to protect affected communities; this requires continuously measuring instruments. This study assessed the performance of seven candidate instruments: (1) Met One Environmental beta attenuation monitor (EBAM), (2) Met One ES model 642 (ES642), (3) Grimm Environmental Dust Monitor 164 (EDM), (4) Thermo ADR 1500 (ADR), (5) TSI DRX model 8543 (DRX), (6) Dylos 1700 (Dylos), and (7) Purple Air II (PA-II) in comparison with a BAM 1020 (BAM) reference instrument. With the exception of the EBAM, all candidates use light scattering to determine PM_2.5 mass concentrations. Our comparison study included environmental chamber and field components, with two of each candidate instrument operating next to the reference instrument. The chamber component involved 6 days of comparisons for biomass combustion emissions. The field component involved operating all instruments in an air monitoring station for 39.5 days with hourly average relative humidity (RH) ranging from 19% to 98%. Goals were to assess instrument precision and accuracy and effects of RH, elemental carbon (EC), and organic carbon (OC) concentrations. All replicate candidate instruments showed high hourly correlations (R² ≥ 0.80) and higher daily average correlations (R² ≥ 0.90), where all instruments correlated well (R² ≥ 0.80) with the reference. The DRX and Purple Air overestimated PM_2.5 mass concentrations by a factor of ~two. Differences between candidates and reference were more pronounced at higher PM_2.5 concentrations. All optical instruments were affected by high RH and by the EC/OC ratio. Equations to convert candidate instruments data to FEM BAM type data are provided to enhance the usability of data from candidate instruments.Implications: This study tested the performance of seven candidate PM_2.5 mass concentration measuring instruments in two settings - environmental chamber and field. The instruments were tested to determine their suitability for use during biomass combustion events and the effects of RH, PM mass concentrations, and concentrations of EC and OC on their performance. The accuracy and precision of each monitor and effect of RH, PM concentration, EC and OC concentrations are varied. The data show that most of these candidate instruments are suitable for measuring PM_2.5 concentration during biomass combustions with a proper correction factor for each instrument type.

Short-term associations between size-fractionated particulate air pollution and COPD mortality in Shanghai, China

Particulate air pollution is a continuing challenge in China, and its adverse effects on chronic obstructive pulmonary disease (COPD) have been widely reported. However, epidemiological evidence on the associations between size-fractionated particle number concentrations (PNCs) and COPD mortality is limited. In this study, we utilized a time-series approach to investigate the associations between PNCs of particles at 0.25-10 μm in diameter and COPD mortality in Shanghai, China. Quasi-Poisson regression generalized additive models were applied to evaluate these associations, with adjustment of time trend, day of week, holidays, temperature and relative humidity. Stratification analyses were performed by season and gender. There were a total of 3238 deaths due to COPD during the study period. We found that daily COPD deaths were significantly associated with PNCs of particles <0.5 μm, and the magnitude of associations increased with decreasing particle size. An interquartile range (IQR) increase in PNC_0.25-0.28, PNC_0.28-0.3, PNC_0.3-0.35, PNC_0.35-0.4, PNC_0.4-0.45 and PNC_0.45--0.5 was associated with increments of 7.51% (95%CI: 2.45%, 12.81%), 7.22% (95%CI: 2.16%, 12.53%), 6.95% (95%CI: 1.81%, 12.35%), 6.26% (95%CI: 1.25%, 11.52%), 5.24% (95%CI: 0.56%, 10.13%) and 4.15% (95%CI: 0.14%, 8.32%), respectively. The associations remained robustness after controlling for the mass concentrations of gaseous air pollutants. In stratification analyses, significant associations between PNCs and COPD mortality were observed in the cold seasons, and in males. Our results suggested that particles <0.5 μm in diameter might be most responsible for the adverse effects of particulate air pollution on COPD mortality, and COPD patients are more susceptible to PM air pollution in the cold seasons, especially for males.

Particulate matter emissions of less harmful-looking super-slim size cigarettes appealing to women: a laser spectrometric analysis of second-hand smoke

Slim tobacco products shall appear by their look less harmful. In 2013, the European Union ministers discussed to ban them. However, only a ban on small package sizes was realized. To add more data for exposure risk assessment of slim tobacco products, the particulate matter (PM) amount in second-hand smoke (SHS) of super-slim size cigarettes compared with a king size brand was investigated. PM amount of four super-slim size cigarette types of the brand Couture was analysed in comparison with the king-size reference cigarette. Therefore, SHS was produced in an enclosed space with a volume of 2.88 m³ by an automatic environmental tobacco smoke emitter. PM size fractions PM₁₀, PM_2.5 and PM₁ were measured in real time using a laser aerosol spectrometer. SHS of Couture Gold contained about 36% and Couture Purple about 28% more PM than the reference cigarette. In contrast, Couture Green emitted about 37% and Couture Silver about 53% less PM than the reference cigarette. Depending on the brand, the PM_2.5 mean concentrations increased up to 1538 μg/m³. This exceeds the 24-h mean concentration of at most 25 μg/m³ according to the WHO Air quality guidelines about 62-fold. Smoking in enclosed rooms leads to a massive increase of PM. The PM pollution by slim-size tobacco products are substantial and sometimes higher than by king size tobacco products. Therefore, SHS exposure from slim-size tobacco products is not less harmful to health. Decision makers should take this aspect in consideration.

Satellite-Derived 1-km-Resolution PM1 Concentrations from 2014 to 2018 across China

Particulate matter with aerodynamic diameters ≤1 μm (PM₁) has a greater impact on the human health but has been less studied due to fewer ground observations. This study attempts to improve the retrieval accuracy and spatial resolution of satellite-based PM₁ estimates using the new ground-based monitoring network in China. Therefore, a space-time extremely randomized trees (STET) model is first developed to estimate PM₁ concentrations at a 1 km spatial resolution from 2014 to 2018 across mainland China. The STET model can derive daily PM₁ concentrations with an average across-validation coefficient of determination of 0.77, a low root-mean-square error of 14.6 μg/m³, and a mean absolute error of 8.9 μg/m³. PM₁ concentrations are generally low in most areas of China, except for the North China Plain and Sichuan Basin where intense human activities and poor natural conditions are prevalent, especially in winter. Moreover, PM₁ pollution has greatly decreased over the past 5 years, benefiting from emission control in China. The STET model, incorporating the spatiotemporal information, shows superior performance in PM₁ estimates relative to previous studies. This high-resolution and high-quality PM₁ data set in China (i.e., ChinaHighPM₁) can be greatly useful for air pollution studies in medium- or small-scale areas.

Estimation of PM10 Levels and Sources in Air Quality Networks by Digital Analysis of Smartphone Camera Images Taken from Samples Deposited on Filters

This paper explores the performance of smartphone cameras as low-cost and easily accessible tools to provide information about the levels and origin of particulate matter (PM) in ambient air. We tested the concept by digital analysis of the images of daily PM₁₀ (particles with diameters 10 µm and smaller) samples captured on glass fibre filters by high-volume aerosol samplers at urban and rural locations belonging to the air quality monitoring network of Extremadura (Spain) for one year. The images were taken by placing the filters inside a box designed to maintain controlled and reproducible light conditions. Digital image analysis was carried out by a mobile colour-sensing application using red, green, blue/hue, saturation, value/hue, saturation, luminance (RGB/HSV/HSL) parameters, that were processed through statistical procedures, directly or transformed to greyscale. The results of the study show that digital image analysis of the filters can roughly estimate the concentration of PM₁₀ within an air quality network, based on a significant linear correlation between the concentration of PM₁₀ measured by an official gravimetric method and the colour parameters of the filters’ images, with better results in the case of the saturation parameter (S_HSV). The methodology based on digital analysis can discriminate urban and rural sampling locations affected by different local particle-emitting sources and is also able to identify the presence of remote sources such as Saharan dust outbreaks in both urban and rural locations. The proposed methodology can be considered as a useful complement to the aerosol sampling equipment of air quality network field units for a quick estimation of PM₁₀ in the ambient air, through a simple, accessible and low-cost procedure, with further miniaturization potential.

Urban vegetation and particle air pollution: Experimental campaigns in a traffic hotspot

This work presents the main results of two experimental campaigns carried out in summer and winter seasons in a complex pollution hotspot near a large park, El Retiro, in Madrid (Spain). These campaigns were aimed at understanding the microscale spatio-temporal variation of ambient concentration levels in areas with high pollution values to obtain data to validate models on the effect of urban trees on particulate matter concentrations. Two different measuring approaches have been used. The first one was static, with instruments continuously characterizing the meteorological variables and the particulate matter concentration outside and inside the park. During the summer campaign, the particulate matter concentration was clearly influenced by a Saharan dust outbreak during the period 23 June to 10 July 2016, when most of the particulate matter was in the fraction PM_2.5-10. During the winter campaign, the mass concentrations were related to the meteorological conditions and the high atmospheric stability. The second approach was a dynamic case with mobile measurements by portable instruments. During the summer campaign, a DustTrak instrument was used to measure PM₁₀ and PM_2.5 in different transects close to and inside the park at different distances from the traffic lane. It was observed a decrease in the concentrations up to 25% at 20 m and 50% at 200 m. High PM₁₀ values were linked to dust resuspension caused by recreational activities and to a Saharan dust outbreak. The highest PM values were measured at the Independencia square, an area with many bus stops and high traffic density. During the winter campaign, three microaethalometers were used for Black Carbon measurement. Both pollutants also showed a reduction in their concentrations when moving towards inside the park. For PM₁₀ and PM_2.5, reductions up to 50% were observed, while for BC this reduction was smaller, about 20%.

Identifying Single Particles in Air Using a 3D-Integrated Solid-State Pore

Solid-state micro- and nanopores are a versatile sensor platform capable of detecting single particles in electrolyte solution by cross-pore ionic current. Here we report on a use of this technology to identify airborne particulate matter. The detection concept lies in an electrophoretic control of air-floating particles captured in liquid to deliver them into a pore detector via microfluidic channels. We demonstrate resistive pulse measurements to machine-learning-based discriminations of intragranular contents of cypress and cedar pollens at a single-particle level. This all-electrical-sensor technique would pave a new venue toward real-time monitoring of single particles and molecules in air.

Particulate Matter Emissions of Four Different Cigarette Types of One Popular Brand: Influence of Tobacco Strength and Additives

The inhalation of particulate matter (PM) in second-hand smoke (SHS) is hazardous to health of smokers and non-smokers. Tobacco strength (amount of tar, nicotine, and carbon monoxide) and different additives might have an effect on the amount of PM. This study aimed to investigate the influence of tobacco strength or additives on PM. Four cigarette types of the brand Marlboro with different strengths and with or without additives were analyzed in comparison to the 3R4F reference cigarette. SHS was generated by an automatic environmental tobacco smoke emitter (AETSE) in an enclosed space with a volume of 2.88 m³. PM concentrations (PM10, PM2.5, PM₁) were measured with a laser aerosol spectrometer followed by statistical analysis. The two strongest Marlboro brands (Red and Red without additives) showed the highest PM concentrations of all tested cigarettes. The measured mean concentrations Cmean of PM10 increased up to 1458 µg/m³ for the Marlboro Red without additives (PM2.5: 1452 µg/m³, PM₁: 1263 µg/m³). The similarly strong Marlboro Red showed very similar PM values. The second strongest type Marlboro Gold showed 36% (PM10, PM2.5) and 32% (PM₁) lower values, respectively. The "lightest" type Marlboro Silver Blue showed 54% (PM10, PM2.5) or 50% (PM₁) lower PM values. The results indicate that the lower the tar, nicotine, and carbon monoxide amounts, as well as the longer the cigarette filter, the lower are the PM levels. An influence of additives could not be determined.

Particulate matter emissions of four types of one cigarette brand with and without additives: a laser spectrometric particulate matter analysis of secondhand smoke

OBJECTIVE

Inhaled particulate matter (PM) in secondhand smoke (SHS) is deleterious for smokers and non-smokers. Different additives in cigarettes might effect the amount of PM. This study aimed to assess the influence of additives on the PM emissions from different cigarette types in SHS.

DESIGN

An experimental study of PM measuring in SHS of cigarettes without exposition of any person.

METHOD

The concentrations of PM (PM10, PM2.5 and PM1) in SHS of four different types of cigarettes of the brand Lucky Strike, two types with additives (Original Red, Original Blue) and two types without additives (Straight Red, Straight Blue), in comparison to the reference cigarette 3R4F were analysed. An automatic environmental tobacco smoke emitter generated SHS in an enclosed space with a volume of 2.88 m3. PM was measured with a laser aerosol spectrometer (Grimm model 1.109). Afterwards, the measuring values of the four Lucky Strike brands and the reference cigarette were statistically evaluated and visualised.

RESULTS

Lucky Strike Straight Blue, a cigarette type without additives and lower tar amount, showed 10% to 25% lower PM mean values compared with the other tested Lucky Strike products, but 21% (PM1) respectively 27% (PM2.5,PM10) higher mean values than the reference cigarette. The PM mean of all measured smoke-free baseline values (clean air) was 1.6 µg/m³. It increased up to about 1800 µg/m³ for the reference cigarette and up to about 3070 µg/m³ for the Lucky Strike Original Blue.

CONCLUSIONS

The findings of this study show the massive increase of PM amount by smoking cigarettes in enclosed spaces and suggest that additives in tobacco products increase the PM amount in SHS. For validation, further comparative studies are necessary focusing on the comparison of the PM concentration of cigarettes with and without additives.

IMPLICATIONS

Due to the exposure to SHS, 890 000 people die each year worldwide. PM in SHS endangers the health of both non-smokers and smokers. This study considers the effect of additives like aromatics and humectant agents in cigarettes on PM in SHS. Do additives in tobacco products increase the amount of PM?

Mortality burden attributable to PM1 in Zhejiang province, China

BACKGROUND

Limited evidence is available on the health effects of particulate matter with an aerodynamic diameter of <1 μm (PM₁), mainly due to the lack of its ground measurement worldwide.

OBJECTIVES

To identify and examine the mortality risks and mortality burdens associated with PM₁, PM_2.5, and PM₁₀ in Zhejiang province, China.

METHODS

We collected daily data regarding all-cause (stratified by age and gender), cardiovascular, stroke, respiratory, and chronic obstructive pulmonary disease (COPD) mortality, and PM₁, PM_2.5, and PM₁₀, from 11 cities in Zhejiang province, China during 2013 and 2017. We used a quasi-Poisson regression model to estimate city-specific associations between mortality and PM concentrations. Then we used a random-effect meta-analysis to pool the provincial estimates. To show the mortality burdens of PM₁, PM_2.5, and PM₁₀, we calculated the mortality fractions and deaths attributable to these PMs.

RESULTS

Daily concentrations of PM₁, PM_2.5, and PM₁₀ ranged between 0-199 μg/m³, 0-218 μg/m³, and 0-254 μg/m³, respectively; Mortality effects were significant in lag 0-2 days. The relative risks for all-cause mortality were 1.0064 (95% CI: 1.0034, 1.0094), 1.0061 (95% CI: 1.0034, 1.0089), and 1.0060 (95% CI: 1.0038, 1.0083) associated with a 10 μg/m³ increase in PM₁, PM_2.5, and PM₁₀, respectively. Age- and gender-stratified analysis shows that elderly people (aged 65+) and females are more sensitive to PMs. The mortality fractions of all-cause mortality were estimated to be 2.39% (95% CI: 1.28, 3.48) attributable to PM₁, 2.53% (95% CI: 1.42, 3.63) attributable to PM_2.5, and 3.08% (95% CI: 1.95, 4.19) attributable to PM₁₀. The ratios of attributable cause-specific deaths for PM₁/PM_2.5, PM₁/PM₁₀, and PM_2.5/PM₁₀ were higher than the ratios of their respective concentrations.

CONCLUSIONS

PM₁, PM_2.5 and PM₁₀ are risk factors of all-cause, cardiovascular, stroke, respiratory, and COPD mortality. PM₁ accounts for the vast majority of short-term PM_2.5- and PM₁₀-induced mortality. Our analyses support the notion that smaller size fractions of PM have a more toxic mortality impacts, which suggests to develop strategies to prevent and control PM₁ in China, such as to foster strict regulations for automobile and industrial emissions.

Health risk assessment due to biomass smoke exposure in Indian indoor environment: An empirical approach using lung deposition model

The paper subsumes a framework that assesses health risk due to exposure to different fuel combustion through articulation of modern microscopic techniques, empirical equations, lung diagnostic tools and a pre-existing model that has been extrapolated to futuristic aspects (within controlled conditions). The framework was tested on 132 household cooks belonging to different age groups and using different types of fuel. The inhalable fraction released during fuel combustion varied in morphological characteristics and deposition site. Micrographs obtained using Scanning Electron Microscope (SEM) analysis of (biomass smoke) soot indicates aggregate formation attributing to a higher level of health risk. Further, abnormal ventilatory function along with higher risk (RR > 1) was more evident within biomass fuel users. The condition further exacerbates while using dung cakes due to high levels of emissions (294.3 particles/liter) that deposit in the upper respiratory tract (0.0899). Further, the population attributable risk percent (79%) calculated on the basis of cooking behavior suggests a 'rural culture' health determinant as clean fuel usage is not practiced as an outcome of low literacy and poor income in the region. These preliminary findings highlight the drudgery of impuissant women who are exposed to high particulate emissions on a regular basis which results in reduced lung function. Nevertheless, further cogitation is required to eliminate the limitations in this study and explore further linkages between exposure and vulnerable group to generate meaningful policy recommendations.

Particulate matter emissions of different brands of mentholated cigarettes

Inhaling particulate matter (PM) in environmental tobacco smoke (ETS) endangers the health of nonsmokers. Menthol, an additive in cigarettes, attenuates respiratory irritation of tobacco smoke. It reduces perceptibility of smoke and therefore passive smokers may inhale ETS unnoticed. To investigate a possible effect of menthol on PM concentrations (PM₁₀, PM_2.5, and PM₁), ETS of four mentholated cigarette brands (Elixyr Menthol, Winston Menthol, Reyno Classic, and Pall Mall Menthol Blast) with varying menthol content was analyzed. ETS was generated in a standardized way using an automatic environmental tobacco smoke emitter (AETSE), followed by laser aerosol spectrometry. This analysis shows that the tested cigarette brands, despite having different menthol concentrations, do not show differences with regard to PM emissions, with the exception of Reyno Classic, which shows an increased emission, although the menthol level ranged in the midfield. More than 90% of the emitted particles had a size smaller than or equal to 1 µm. Regardless of the menthol level, the count median diameter (CMD) and the mass median diameter (MMD) were found to be 0.3 µm and 0.5 µm, respectively. These results point out that there is no effect of menthol on PM emission and that other additives might influence the increased PM emission of Reyno Classic.

IMPLICATIONS

Particulate matter (PM) in ETS endangers the health of nonsmokers and smokers. This study considers the effect of menthol, an additive in cigarettes, on PM emissions. Does menthol increase the amount of PM? Due to the exposure to secondhand smoke nearly 900,000 people die each year worldwide. The aim of the study is to measure the particle concentration (L^-1), mass concentration (µg m^-3), and dust mass fractions shown as PM₁₀, PM_2.5, and PM₁ of five different cigarette brands, including four with different menthol concentrations and one menthol-free reference cigarette, in a well-established standardized system.

Estimating spatiotemporal distribution of PM1 concentrations in China with satellite remote sensing, meteorology, and land use information

BACKGROUND

PM₁ might be more hazardous than PM_2.5 (particulate matter with an aerodynamic diameter ≤ 1 μm and ≤2.5 μm, respectively). However, studies on PM₁ concentrations and its health effects are limited due to a lack of PM₁ monitoring data.

OBJECTIVES

To estimate spatial and temporal variations of PM₁ concentrations in China during 2005-2014 using satellite remote sensing, meteorology, and land use information.

METHODS

Two types of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) data, Dark Target (DT) and Deep Blue (DB), were combined. Generalised additive model (GAM) was developed to link ground-monitored PM₁ data with AOD data and other spatial and temporal predictors (e.g., urban cover, forest cover and calendar month). A 10-fold cross-validation was performed to assess the predictive ability.

RESULTS

The results of 10-fold cross-validation showed R² and Root Mean Squared Error (RMSE) for monthly prediction were 71% and 13.0 μg/m³, respectively. For seasonal prediction, the R² and RMSE were 77% and 11.4 μg/m³, respectively. The predicted annual mean concentration of PM₁ across China was 26.9 μg/m³. The PM₁ level was highest in winter while lowest in summer. Generally, the PM₁ levels in entire China did not substantially change during the past decade. Regarding local heavy polluted regions, PM₁ levels increased substantially in the South-Western Hebei and Beijing-Tianjin region.

CONCLUSIONS

GAM with satellite-retrieved AOD, meteorology, and land use information has high predictive ability to estimate ground-level PM₁. Ambient PM₁ reached high levels in China during the past decade. The estimated results can be applied to evaluate the health effects of PM₁.

Air quality measurements-From rubber bands to tapping the rainbow

It is axiomatic that good measurements are integral to good public policy for environmental protection. The generalized term for "measurements" includes sampling and quantitation, data integrity, documentation, network design, sponsorship, operations, archiving, and accessing for applications. Each of these components has evolved and advanced over the last 200 years as knowledge of atmospheric chemistry and physics has matured. Air quality was first detected by what people could see and smell in contaminated air. Gaseous pollutants were found to react with certain materials or chemicals, changing the color of dissolved reagents such that their light absorption at selected wavelengths could be related to both the pollutant chemistry and its concentration. Airborne particles have challenged the development of a variety of sensory devices and laboratory assays for characterization of their enormous range of physical and chemical properties. Advanced electronics made possible the sampling, concentration, and detection of gases and particles, both in situ and in laboratory analysis of collected samples. Accurate and precise measurements by these methods have made possible advanced air quality management practices that led to decreasing concentrations over time. New technologies are leading to smaller and cheaper measurement systems that can further expand and enhance current air pollution monitoring networks.

IMPLICATIONS

Ambient air quality measurement systems have a large influence on air quality management by determining compliance, tracking trends, elucidating pollutant transport and transformation, and relating concentrations to adverse effects. These systems consist of more than just instrumentation, and involve extensive support efforts for siting, maintenance, calibration, auditing, data validation, data management and access, and data interpretation. These requirements have largely been attained for criteria pollutants regulated by National Ambient Air Quality Standards, but they are rarely attained for nonroutine measurements and research studies.

Particulate matter pollution over China and the effects of control policies

China is one of the regions with highest PM_2.5 concentration in the world. In this study, we review the spatio-temporal distribution of PM_2.5 mass concentration and components in China and the effect of control measures on PM_2.5 concentrations. Annual averaged PM_2.5 concentrations in Central-Eastern China reached over 100μgm^-3, in some regions even over 150μgm^-3. In 2013, only 4.1% of the cities attained the annual average standard of 35μgm^-3. Aitken mode particles tend to dominate the total particle number concentration. Depending on the location and time of the year, new particle formation (NPF) has been observed to take place between about 10 and 60% of the days. In most locations, NPF was less frequent at high PM mass loadings. The secondary inorganic particles (i.e., sulfate, nitrate and ammonium) ranked the highest fraction among the PM_2.5 species, followed by organic matters (OM), crustal species and element carbon (EC), which accounted for 6-50%, 15-51%, 5-41% and 2-12% of PM_2.5, respectively. In response to serious particulate matter pollution, China has taken aggressive steps to improve air quality in the last decade. As a result, the national emissions of primary PM_2.5, sulfur dioxide (SO₂), and nitrogen oxides (NO_X) have been decreasing since 2005, 2006, and 2011, respectively. The emission control policies implemented in the last decade could result in noticeable reduction in PM_2.5 concentrations, contributing to the decreasing PM_2.5 trends observed in Beijing, Shanghai, and Guangzhou. However, the control policies issued before 2010 are insufficient to improve PM_2.5 air quality notably in future. An optimal mix of energy-saving and end-of-pipe control measures should be implemented, more ambitious control policies for NMVOC and NH₃ should be enforced, and special control measures in winter should be applied. 40-70% emissions should be cut off to attain PM_2.5 standard.

Exposure to air pollutants during commuting in London: Are there inequalities among different socio-economic groups?

People with low income often experience higher exposures to air pollutants. We compared the exposure to particulate matter (PM₁, PM_2.5 and PM₁₀), Black Carbon (BC) and ultrafine particles (PNCs; 0.02-1μm) for typical commutes by car, bus and underground from 4 London areas with different levels of income deprivation (G₁ to G₄, from most to least deprived). The highest BC and PM concentrations were found in G₁ while the highest PNC in G₃. Lowest concentrations for all pollutants were observed in G₂. We found no systematic relationship between income deprivation and pollutant concentrations, suggesting that differences between transport modes are a stronger influence. The underground showed the highest PM concentrations, followed by buses and a much lower concentrations in cars. BC concentrations in the underground were overestimated due to Fe interference. BC concentrations were also higher in buses than cars because of a lower infiltration of outside pollutants into the car cabin. PNCs were highest in buses, closely followed by cars, but lowest in underground due to the absence of combustion sources. Concentration in the road modes (car and bus) were governed by the traffic conditions (such as traffic flow interruptions) at the specific road section. Exposures were reduced in trains with non-openable windows compared to those with openable windows. People from less income-deprived areas have a predominant use of car, receiving the lowest doses (RDD<1μgh^-1) during commute but generating the largest emissions per commuter. Conversely, commuters from high income-deprived areas have a major reliance on the bus, receiving higher exposures (RDD between 1.52 and 3.49μgh^-1) while generating less emission per person. These findings suggest an aspect of environmental injustice and a need to incorporate the socioeconomic dimension in life-course exposure assessments.

Characterization of particulate matter binding peptides screened from phage display

Particulate matter (PM), especially particulates with diameters of less than 2.5 μm, can penetrate the alveolar region and increase the risk of respiratory diseases. This has stimulated research efforts to develop detection methods so that counter measures can be taken. In this study, four PM binding peptides were obtained by phage display and binding characteristics of these peptides were investigated using the peptide array. The strongest binding peptide, WQDFGAVRSTRS, displayed a binding property, measured in terms of spot intensity, 11.4 times higher than that of the negative control, AAAAA. Inductively coupled plasma mass spectrometry (ICPMS) analysis of the transition metal compounds in the PM bound to the peptide spots was performed, and two peptides showed higher binding towards Cu and Zn compounds in PM. These results suggest that the screened peptides could serve as an indicator of transition metal compounds, which are related to adverse health effects, contained in PM.

Evaluation of the Alphasense Optical Particle Counter (OPC-N2) and the Grimm Portable Aerosol Spectrometer (PAS-1.108)

We compared the performance of a low-cost (∼$500), compact optical particle counter (OPC, OPC-N2, Alphasense) to another OPC (PAS-1.108, Grimm Technologies) and reference instruments. We measured the detection efficiency of the OPCs by size from 0.5 to 5 μm for monodispersed, polystyrene latex (PSL) spheres. We then compared number and mass concentrations measured with the OPCs to those measured with reference instruments for three aerosols: salt, welding fume and Arizona road dust. The OPC-N2 detection efficiency for monodispersed was similar to the PAS-1.108 for particles larger than 0.8 μm (minimum of 79% at 1 μm and maximum of 101% at 3 μm). For 0.5-μm particles, the detection efficiency of OPCN2 was underestimated at 78%, whereas PAS-1.108 overestimated concentrations by 183%. The mass concentrations from the OPCs were linear (r ≥ 0.97) with those from the reference instruments for all aerosols, although the slope and intercept were different. The mass concentrations were overestimated for dust (OPC-N2, slope = 1.6; PAS-1.108, slope = 2.7) and underestimated for welding fume (OPC-N2, slope = 0.05; PAS-1.108, slope = 0.4). The coefficient of variation (CV, precision) for OPC-N2 for all experiments was between 4.2% and 16%. These findings suggest that, given site-specific calibrations, the OPC-N2 can provide number and mass concentrations similar to the PAS-1.108 for particles larger than 1 μm.

Practicalities of mapping PM10 and PM2.5 concentrations on city-wide scales using a portable particulate monitor

Fine particulate matter is considered to be the most significant ambient air pollutant in terms of potential health impacts. Therefore, it is important that regulators are able to accurately assess the exposure of populations to PM₁₀ and PM_2.5 across municipal areas. We report on the practicalities of using a laser light scattering portable particulate monitor (Turnkey Instruments DustMate), in combination with a GPS, to map PM₁₀ and PM_2.5 concentrations on city-wide scales in Newcastle upon Tyne/Gateshead (UK), during a series of walking surveys. A heated inlet is necessary to remove moisture droplets from the sampled air prior to analysis by the instrument, though this also results in the loss of volatile particulate components, particularly from the PM_2.5 fraction. A co-location calibration study was carried out with a reference urban background Tapered Element Oscillating Micro-Balance/Filter Dynamics Measuring System (TEOM-FDMS) system in Newcastle that is part of the UK's Automatic Urban and Rural Network (AURN) of air quality monitoring stations. For PM₁₀, orthogonal regression of the DustMate against TEOM-FDMS data gave a slope and intercept of 1.02 ± 0.06 and -3.7 ± 1.2, respectively (R² = 0.73), whereas for PM_2.5, the respective values were 0.78 ± 0.06 and -0.63 ± 0.55 (R² = 0.79). These parameters are comparable to literature calibration studies using this technology. There was good agreement between simultaneous samples taken using two DustMate instruments: for PM₁₀, a slope and intercept of 1.05 ± 0.03 and 0.36 ± 0.5, respectively (R² = 0.73), were obtained, whereas for the PM_2.5, the respective values were 0.79 ± 0.01 and 0.19 ± 0.06 (R² = 0.86). Correction factors based on the slope and intercepts obtained from the calibration exercise were applied to raw data collected from the DustMate. An annually-normalised correction procedure was then used to account for different background particulate concentrations on different sampling days. These corrected PM₁₀ and PM_2.5 concentrations and corresponding GPS coordinates were displayed on a base map using Google Fusion Tables and Google Earth Professional. Almost all areas surveyed in Newcastle/Gateshead were well below the EU Air Quality Standards for PM₁₀ and PM_2.5.

Particle size and chemical constituents of ambient particulate pollution associated with cardiovascular mortality in Guangzhou, China

Though significant associations between particulate matter (PM) air pollution and cardiovascular diseases have been widely reported, it remains unclear what characteristics, such as particle size and chemical constituents, may be responsible for the effects. A time-series model was applied to examine the cardiovascular effects of particle size (for the period of 2009-2011) and chemical constituents (2007-2010) in Guangzhou, we controlled for potential confounders in the model, such as time trends, day of the week, public holidays, meteorological factors and influenza epidemic. We found significant associations of cardiovascular mortality with PM10, PM2.5 and PM1; the excess risk (ER) was 6.10% (95% CI: 1.76%, 10.64%), 6.11% (95% CI: 1.76%, 10.64%) and 6.48% (95% CI: 2.10%, 11.06%) for per IQR increase in PM10, PM2.5 and PM1 at moving averages for the current day and the previous 3 days (lag03), respectively. We did not find significant effects of PM2.5-10 and PM1-2.5. For PM2.5 constituents, we found that organic carbon, elemental carbon, sulfate, nitrate and ammonium were significantly associated with cardiovascular mortality, the corresponding ER for an IQR concentration increase at lag03 was 1.13% (95% CI: 0.10%, 2.17%), 2.77% (95% CI: 0.72%, 4.86%), 2.21% (95% CI: 1.05%, 3.38%), 1.98% (95% CI: 0.54%, 3.44%), and 3.38% (95% CI: 1.56%, 5.23%), respectively. These results were robust to adjustment of other air pollutants and they remained consistent in various sensitivity analyses by changing model parameters. Our study suggests that PM1 and constituents from combustion and secondary aerosols might be important characteristics of PM pollution associated with cardiovascular mortality in Guangzhou.