Mass Concentration Measurements Research Articles

Particulate black carbon mass concentrations and the episodic source identification driven by atmospheric blocking effects in Astana, Kazakhstan

Black carbon (BC) is a component of fine particulate matter (PM2.5) that is a key contributor to adverse human health effects and climate forcing. To date, BC mass concentrations and possible sources in Kazakhstan have not been studied. Thus, understanding the temporal variations of BC for a large developing region with a complex climate is useful. In this study, measurements of fine particulate BC mass concentrations in Astana were made from June 2020 to October 2021 by measuring light absorption of PM2.5 on filters. The mean BC concentration was 2.56 ± 1.29 μg m−3 with maximum and minimum monthly mean BC concentrations being 4.56 ± 2.03 μg m−3 and 1.12 ± 0.42 μg m−3 in January 2021 and June 2020, respectively. Temporal analyses of BC, SO2, PM10, NOx, CO, meteorological and atmospheric stability parameters were performed. Aggregated pollutant ‘episodic loadings’ during the heating and non-heating periods were identified. Their relationships with blocking anticyclones and cyclones were investigated by examining the reversal of meridional gradients at 500 hPa geopotential height (GPH) maps and identifying Omega (Ω) and Rex blocking types. Astana has some of the highest BC concentrations of cities worldwide. Seasonal BC source location identification using Conditional Bivariate Probability Function (CBPF) analysis implicated combined heat and power (CHP) plant emissions as the major BC source in Astana. Significant increases in BC concentrations were observed during the cold season due to numerous sources, generally poorer atmospheric dispersion and blocking events. The Concentration Weighted Trajectory (CWT) analysis results showed that the distribution of the 75th percentile of BC during episodic periods actively controlled by blockings exceeding than the entire measurement period, which may reflect cross-border transport and adjacent countries.

Field comparison of dual- and single-spot Aethalometers: equivalent black carbon, light absorption, Ångström exponent and secondary brown carbon estimations

Abstract. The Aethalometer is a widely used instrument for black carbon (BC) mass concentration and light absorption coefficient (babs) measurements around the world. However, field intercomparison of the two popular models, dual-spot (AE33) and single-spot (AE31) Aethalometers, remains limited; in addition, the difference in secondary brown carbon (BrCsec) light absorption estimation between the two models is largely unknown. We performed full-year collocated AE33 and AE31 measurements in a megacity in southern China – Guangzhou. The babs values agree well between the two Aethalometers (R2 > 0.95), with AE33 / AE31 slopes ranging from 0.87 to 1.04 for seven wavelengths. AE33 consistently exhibits lower limits of detection (LODs) than AE31 for time resolutions of 2 to 60 min. The AE33 / AE31 slope for equivalent BC (eBC) was 1.2, implying the need for site-specific post-correction. The absorption Ångström exponent (AAE) obtained from different approaches does not agree very well between the two models, with the biggest discrepancy found in AAE880/950. The estimated BrCsec light absorption at 370 nm (babs370_BrCsec) was calculated using the minimum-R-squared (MRS) method for both Aethalometers. The babs370_BrCsec comparison yields a slope of 0.78 and an R2 of 0.72 between the two models, implying a non-negligible inter-instrument difference. This study highlights the high consistency in babs but less so in AAE between AE31 and AE33 and reveals site-specific correction for eBC estimation and non-negligible difference in BrCsec estimation. The results are valuable for data continuity in long-term Aethalometer measurements when transitioning from the older (AE31) to the newer (AE33) model, as anticipated in permanent global-climate and air-quality stations.

Evaluation of methods for characterizing the fine particulate matter emissions from aircraft and other diffusion flame combustion aerosol sources

The U. S. Environmental Protection Agency in collaboration with the U. S. Air Force Arnold Engineering Development Complex conducted the VAriable Response In Aircraft nvPM Testing (VARIAnT) 3 and 4 test campaigns to compare nonvolatile particulate matter (nvPM) emissions measurements from a variety of diffusion flame combustion aerosol sources (DFCASs), including a Cummins diesel engine, a diesel powered generator, two gas turbine start carts, a J85-GE-5 turbojet engine burning multiple fuels, and a Mini-CAST soot generator. The VARIAnT research program was devised to understand reported variability in the ARP6320A sampling system nvPM measurements. The VARIAnT research program has conducted four test campaigns to date with the VARIAnT 3 and 4 campaigns devoted to: (1) assessing the response of three different black carbon mass analyzers to particles of different size, morphology, and chemical composition; (2) characterizing the particles generated by 6 different combustion sources according to morphology, effective density, and chemical composition; and (3) assessing any significant difference between black carbon as determined by the 3 mass analyzers and the total PM determined via other techniques. Results from VARIAnT 3 and 4 campaigns revealed agreement of about 20% between the Micro-Soot Sensor, the Cavity Attenuated Phase Shift (CAPS PMSSA) monitor and the thermal-optical reference method for elemental carbon (EC) mass, independent of the calibration source used. For the LII-300, the measured mass concentrations in VARIAnT 3 fall within 18% and in VARIAnT 4 fall within 27% of the reference EC mass concentration when calibrated on a combustor rig in VARIAnT 3 and on an LGT-60 start cart in VARIAnT 4, respectively. It was also found that the three mass instrument types (MSS, CAPS PMSSA, and LII-300) can exhibit different BC to reference EC ratios depending on the emission source that appear to correlate to particle geometric mean mobility diameter, morphology, or some other parameter associated with particle geometric mean diameter (GMD) with the LII-300 showing a slightly stronger apparent trend with GMD. Systematic differences in LII-300 measured mass concentrations have been reduced by calibrating with a turbine combustion as a particle source (combustor or turbine engine). With respect to the particle size measurements, the sizing instruments (TSI SMPS, TSI EEPS, and Cambustion DMS 500) were found to be in general agreement in terms of size distributions and concentrations with some exceptions. Gravimetric measurements of the total aerosol mass produced by the various DFCAs differed from the reference EC, BC and integrated particle size distribution measured aerosol masses. The measurements of particle size distributions and single particle analysis performed using the miniSPLAT indicated the presence of larger particles (≳150 nm) having more compact morphologies, higher effective density, and a composition dominated by OC and containing ash. This increased large particle fraction is also associated with higher values of single scattering albedo measured by the CAPS PMSSA instrument and higher OC measurements. These measurements indicate gas turbine engine emissions can be a more heterogeneous mix of particle types beyond the original E−31 assumption that engine exit exhaust particles are mainly composed of black carbon.

Black carbon instrument responses to laboratory generated particles

Accurate measurement of black carbon (BC) particles is vital for climate models as well as air quality assessments. While the need for BC particle measurement has been recognized, standardization of instruments and procedures for ambient measurement is still underway. In this study, we used laboratory generated soot particles to assess nine instruments targeting BC mass concentration measurement. The measurement matrix included different BC concentrations (ranging from atmospheric levels to combustion emission levels), different particle coatings, two particle sources (gas burner and spark generator) and two dilution methods. The nine instruments included six different models: aethalometers AE33 and MA200, thermo-optical OC-EC analysis, multi-angle absorption photometer MAAP 5012, photoacoustic instrument MSS, and soot particle aerosol mass spectrometer SP-AMS. The main discrepancy we observed was that the SP-AMS results were systematically lower, approximately only half of the BC measured by other instruments. A portion of this is explained by particle losses in the aerodynamic lens of the SP-AMS and the parameters used in the data analysis. Some smaller discrepancies were identified for the other instruments, but overall, the median values from were within 25 % of each other. Instruments’ operation principles and covered concentration ranges need to be carefully considered especially in emission measurements where the aerosols can have high temporal variation as well as high BC concentrations. In general, the results can decrease the uncertainties in climate and air quality studies by providing tools for more accurate and comparable BC measurements and when the existing BC data is interpreted.

Towards a hygroscopic growth calibration for low-cost PM2.5 sensors

Abstract. Low-cost particulate matter (PM) sensors continue to grow in popularity, but issues such as aerosol-size-dependent sensitivity drive the need for effective calibration schemes. Here we devise a time-evolving calibration method for the Plantower PMS5003 PM2.5 mass concentration measurements. We use 2 years of measurements from the Berkeley Environmental Air-quality and CO2 Network sensors deployed in San Francisco and Los Angeles in our analysis. The calibration uses a hygroscopic growth correction factor derived from κ-Köhler theory, where the calibration parameters are determined empirically using US Environmental Protection Agency Air Quality System (EPA AQS) reference data at co-location sites during the period from 2021–2022. The parameters are found to vary cyclically through the seasons, and the seasonal cycles match changes in sulfate and elemental carbon PM composition fractions throughout the year. In both regions, the seasonal RH dependence calibration performs better than the uncalibrated data and data calibrated with the EPA's national Plantower calibration algorithm. In the San Francisco Bay Area, the seasonal RH dependence calibration reduces the root mean square error (RMSE) by ∼40 % from the uncalibrated data and maintains a mean bias much smaller than the EPA national calibration scheme (−0.90 vs −2.73 µg m−3). We also find that calibration parameters forecasted beyond those fit with the EPA reference data continue to outperform the uncalibrated data and EPA calibration data, enabling real-time application of the calibration scheme even in the absence of reference data. While the correction greatly improves the data accuracy, non-Gaussian distribution of the residuals suggests that other processes besides hygroscopic growth can be parameterized for future improvement of this calibration.

Identification of Saharan-Dust Intrusions over Sofia, Bulgaria, Using Near-Ground PM10 and PM2.5 Mass Concentration Measurements

Identification of Saharan-Dust Intrusions over Sofia, Bulgaria, Using Near-Ground PM10 and PM2.5 Mass Concentration Measurements

Characteristics of airborne particles in stone quarrying areas: Human exposure assessment and mitigation

This investigation aims to assess the levels of human exposure to airborne particulate matter (PM) in various locations of a natural stone quarry for the first time based on simultaneous measurements of both PM mass and number concentrations (PMC and PNC). A quarry located in Danang city, Vietnam, considered to be a “hotspot” of air pollution in the city, was selected for detailed investigations. Both PMC and PNC were found to be significantly higher (1.2–6.0 times) within the quarry compared to surrounding areas. Mechanical activities during mining, notably crushing, screening, hauling, and loading stones, contributed to increased emissions of PM in the coarser mode (1–10 μm) compared to the accumulation mode (0.1–1 μm) and thus increased deposition of PM1-10 in the human upper respiratory tract. In contrast, combustion activities, especially the diesel engine exhaust from various machines and vehicles used in the quarry, resulted in increased emissions of small particles in the accumulation mode that dominated the PNC and in their deposition in the lower respiratory tract. Simultaneous measurements of PNC and PMC revealed that the PM counts were strongly associated with PM deposition in the alveolar region (accounting for ≈ 76% of total PNC of particles less than 10 μm, N10), while the PM mass concentration was a better indicator of the deposition of PM in the head airway region (≈92% of total PMC of PM10). Overall, this study demonstrates the significance of measuring both PNC and PMC to assess PM exposure levels, regional respiratory doses, and potential health effects associated with human exposure to PM generated from stone quarrying activities. The novelty of this work is the integration of real-time mass and number concentrations of PM over the size range from 20 nm to 10 μm to provide insights into respiratory deposited doses of size-fractionated PM among quarry workers.

Characteristics of Atmospheric Dust Fall Pollution and Its Chemical Composition and Mass Reconstruction in Mentougou District of Beijing

To study the characteristics of atmospheric dust fall pollution in Mentougou District of Beijing, the monthly average monitoring results of 57 atmospheric dust fall samples from two state-controlled ambient air stations in Mentougou District from 2018 to 2022 were collected, and the atmospheric dust fall pollution status and its time variation characteristics in Mentougou District were analyzed. In order to explore the characteristics of chemical components of atmospheric dust fall and the results of quality mass reconstruction and their sources, 57 dust fall samples were collected using the active suction method at the Sanjiadian State-controlled Ambient Air Station. The mass concentration of dust fall and its chemical components were measured, the characteristics of chemical components in atmospheric dust fall were studied, and the mass reconstruction of the main components of atmospheric dust fall was performed using particle mass reconstruction technology. The reliability of the mass reconstruction results and the reasons for its undetermined components were also discussed. The results showed that from 2018 to 2022, the monthly dust fall in Mentougou District of Beijing changed periodically, being the maximum in April or May in spring and the minimum in October or November in autumn, and the maximum monthly dust fall was 3.2 to 8.4 times the minimum monthly dust fall. The order of the quarterly average monthly dust fall was as follows:spring>summer>autumn>winter, and the dust fall mainly came from spring and summer, accounting for 40.1%-43.0% and 23.8%-37.5% of the total annual dust fall, respectively. The annual average monthly dust fall in Mentougou District of Beijing showed a significant downward trend. The dust fall in 2022 had decreased by 52.8% compared with that in 2018, with an average annual decline of 13.2%, which was related to the improvement in the fine management level of urban environmental protection in Beijing in recent years. In 2021, soil dust had a significant impact on dust fall in Mentougou District, with an actual contribution of 44.2%. The chemical components in the atmospheric dust fall in Mentougou District were mainly water-soluble ions, crustal elements, organic carbon(OC), and elemental carbon(EC). The total mass of the measured chemical components accounted for 65.0% of the mass fraction of the dust fall. The secondary organic carbon(SOC) was also an important component of the atmospheric dust fall, and its mass concentration was 13.5 μg·m-3, accounting for 96.4% of the mass fraction of OC. The main components of atmospheric dust fall mass reconstruction were crust element fugitive dust, organic matter(OM), SO42-, NO3-, NH4+, trace elements, EC, and Cl-, with mass concentrations of 34.8, 28.0, 20.6, 15.0, 5.6, 4.3, 3.2, and 2.2 μg·m-3, accounting for 25.5%, 20.6%, 15.1%, 11.1%, 4.1%, 3.2%, 2.3%, and 1.6% of the dust fall quality, respectively. The atmospheric dust fall mainly came from the soil dust, construction cement dust, biomass combustion, waste incineration, and secondary transformation process. The measured mass concentration of atmospheric dust fall had a good correlation with the reconstructed mass concentration of chemical components, and the determination coefficient R2 was 0.8173. The undetermined components in the mass reconstruction results accounted for 16.5% of the dust fall mass, of which the particle bound water(PBW) in the dust fall accounted for 6.2% of the dust fall mass, and the remaining undetermined components might have been related to the unmeasured components, the selected estimation coefficient of OM and crustal elemental dust, the particle size composition, the selected chemical component analysis method, and its measurement error.

Development of a physics-based method for calibration of low-cost particulate matter sensors and comparison with machine learning models

Low cost particulate matter sensors are receiving significant attention as they can be used in large number for spatial and temporal measurement of PM mass and number concentration. However, the data reliability is questionable as these sensors are affected by numerous parameters such as temperature, relative humidity, and hygroscopicity of particles. To ensure accurate and reliable measurement of particulate matter concentrations, performance evaluation and calibration of LCS co-located with reference instrument at site is essential. In this study, the performance of the low-cost sensor (APT Maxima) was evaluated with the reference instrument SASS (Speciation Air Sampling System) sampler for developing suitable calibration factor that include impact of the meteorological parameter such as relative humidity and temperature, and hygroscopicity. In this study, we have demonstrated a systematic physics-based method for calibration of LCS based on κ-Köhler theory and Mie theory. For comparison with statistical models, linear regression and machine learning algorithm were also applied. In physics-based model, calculated total light scattered intensity shows good linearity with reference PM2.5 measurements. Physics based model performed better for both the sites as compared to MLR, kNN, RF, and GB ML algorithms with R2, RMSE, and MAE values of 0.72,18.21, and 13.36 for Bhopal site, and 0.91, 7.84, and 5.76 for Kashmir site, respectively. Study indicates that physics-based approach for LCS calibration is suitable and can be transferable to different sites.

The Potential of Multibeam Sonars as 3D Turbidity and SPM Monitoring Tool in the North Sea

Monitoring turbidity is essential for sustainable coastal management because an increase in turbidity leading to diminishing water clarity has a detrimental ecological impact. Turbidity in coastal waters is strongly dependent on the concentration and physical properties of particles in the water column. In the Belgian part of the North Sea, turbidity and suspended particulate matter (SPM) concentrations have been monitored for decades by satellite remote sensing, but this technique only focuses on the surface layer of the water column. Within the water column, turbidity and SPM concentrations are measured in stations or transects with a suite of optical and acoustic sensors. However, the dynamic nature of SPM variability in coastal areas and the recent construction of offshore windmill parks and dredging and dumping activities justifies the need to monitor natural and human-induced SPM variability in 3D instead. A possible solution lies in modern multibeam echosounders (MBES), which, in addition to seafloor bathymetry data, are also able to deliver acoustic backscatter data from the water column. This study investigates the potential of MBES as a 3D turbidity and SPM monitoring tool. For this purpose, a novel empirical approach is developed, in which 3D MBES water column and in-situ optical sensor datasets were collected during ship transects to yield an empirical relation using linear regression modeling. This relationship was then used to predict SPM volume concentrations from the 3D acoustic measurements, which were further converted to SPM mass concentrations using calculated densities. Our results show that these converted mean mass concentrations at the Kwinte and Westdiep swale areas are within the limits of the reported yearly averages. Moreover, they are in the same order of magnitude as the measured mass concentrations from Niskin water samples during each campaign. While there is still need for further improvement of acquisition and processing workflows, this study presents a promising approach for converting MBES water column data to turbidity and SPM measurements. This opens possibilities for improving future monitoring tools, both in scientific and industrial sectors.

Synergic use of in-situ and remote sensing techniques for comprehensive characterization of aerosol optical and microphysical properties

We report on importance of conducting comprehensive studies of atmospheric aerosol particles, which cannot be done if information from various complementary sensors is unavailable. We present an example for such application and recommend on the types of sensors that should be used in view of the ACTRIS and RI-URBANS new strategies for monitoring at supersites. Although active and passive remote sensing data was not available in continuous mode, we show that synergic use of them with in-situ observations allows for comprehensive study of temporal and height-resolved distribution of aerosol in the lower troposphere and it can be successfully combined to assess biomass burning impact on air quality and optical properties.The analysed period was divided into three episodes based on the measured black carbon (BC) concentration and the prevailing wind direction. The dominant 72-h backward trajectories were ending in western Europe, mid-Atlantic and western Russia, respectively, The in-situ measured mass concentrations of BCtotal and BC apportioned to biomass burning as well as particulate matter (PM) concentrations in accumulation mode were twice higher during the first and last episodes compared to the second episode, representing long-range transport from different source regions. The obtained complementary surface, column-integrated, and layer-derived size distributions and other parameters demonstrate the added value of multisensor analyses.

Characterization of Sprays Generated by the Expansion of Emulsions with Liquid Carbon Dioxide

AbstractExpanding emulsions with liquid CO2 facilitates the creation of aerosols with an average droplet diameter in the low micrometer size range, which is challenging with conventional atomizers. The droplet formation process of the expansion of high‐pressure emulsions was investigated using a plain‐orifice atomizer and different swirl nozzles. The local droplet size and droplet velocities were measured and used to estimate the local Weber number and thus infer the droplet size reduction. Measurements of the local mass concentration in the aerosol showed that, for the swirl nozzle, the highest concentration was found outside of the central axis, indicating radial momentum generated by the swirl nozzle. Furthermore, it was shown that the type of expansion nozzle used has an influence on the resulting median droplet size in the aerosol. For a water mass load of 0.01, the median droplet diameter was reduced from 8 to 3 μm by increasing the swirl number from 0.01 to 0.1.

Occupational exposure to fine particulate matter in the reinforced concrete production and its association with respiratory symptoms and lung function

BackgroundReinforced concrete production is widespread, but little is known about the occupational exposure to fine particulate matter (PM) in such workplaces, including from metalworking and concrete processing. Therefore, the aim was to characterize exposure to fine PM in the typical workplaces of the whole production cycle and to quantify the risk of respiratory symptoms and lung function in a cohort of reinforced concrete parts production industry.MethodsAt a reinforced concrete parts producing facility in Almaty, we collected 50 personal PM2.5 samples from the main exposure sites and the measured mass concentrations using gravimetric method. Workers also completed questionnaires on a detailed working history, respiratory symptoms (chronic obstructive pulmonary disease (COPD) Assessment Tool (CAT)), followed by spirometry. The association of cumulative dose with CAT score and forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) was tested with multiple regression.ResultsThe highest PM2.5 concentrations were found in the concrete-mixing unit (median 1180 µg/m3), followed by metalworking (510 µg/m3), armature workshop (375 µg/m3) and molding site (245 µg/m3), different from the concentrations in the office (29.5 µg/m3), Kruskall-Wallis p < 0.001. Cumulative PM2.5 dose, mg/m3-year (beta 0.10 (95% confidence interval (CI) 0.05; 0.15)) was strongly associated with CAT score, whereas production with FEV1/FVC (beta -4.96 (-8.31; -1.61)), independent of smoking and chronic bronchitis and sex.ConclusionsMixing concrete and metalworks pose the greatest risk for worker’s health in the reinforced concrete production from the inhalational exposure to aerosol, adversely affecting respiratory health.

Size-segregated aerosol measurements during Diwali festival in an elevated background location

Recent studies in the direction of identifying signatures of aerosol emission from fireworks stressed on the need of simultaneous measurements of mass, number and chemical compositional characteristics. Such an identification is tricky when the measurements are performed in an elevated background environment and/or in presence of an additional wide source term. This work studies the modifications in atmospheric aerosol characteristics due to firework induced emissions in Bathinda city of Punjab, North India. This study presents interpretations based on the results obtained from the measurements performed for 14 days covering the days of Diwali festival, 2021 as well as the baseline database gathered from a year-long campaign to measure mass concentration in different size-ranges. Highest mass concentration for the study duration was observed to be PM10- 382 μg/m3, PM2.5–299 μg/m3, PM1- 240 μg/m3, respectively in the month of November 2021. A clear increase of concentration was noted for Diwali days and the averaged concentration for PM10, PM2.5 and PM1 reached to 445 μg/m3, 363 μg/m3 and 304 μg/m3 on Diwali day, respectively. Number size distribution evolution analysis for the data measured from an optical particle counter (size range: 0.25–1 μm) showed that emissions for Diwali days occurred mostly at night times and in smaller size channels (<0.5 μm). Chemical compositional data of selected samples close to Diwali days was interpreted in terms of factor of increase of mass density of collected particles in different size-ranges. Mass density of elements K, Cl, S, Al, Zn, P, Mn, Pb, Br and Zr in PM1 samples was observed to be higher for Diwali days in comparison to their pre-Diwali levels. Few elements viz. Ba, Sr and Nb were found to be only present in the samples taken during Diwali days. In addition to Ba, Sr and Nb, elements V, Mg, Br and Se were observed to be present in PM2.5 and PM10 samples taken during the Diwali days. This study provides combined ambient aerosol characteristics during Diwali days when the air quality was affected by stubble burning as well.

Exploring the potential for continuous measurement of ultrafine particle mass concentration (PM 0.1 ) based on measurements of particle number concentration above 50 nm ( N 50 )

Exploring the potential for continuous measurement of ultrafine particle mass concentration (PM _0.1 ) based on measurements of particle number concentration above 50 nm ( <i>N</i> ₅₀ )

PM0.1 non-bouncing impactor (NBI) for ultrafine particle mass and number measurements

This study designed and tested a 30 L/min PM0.1 non-bouncing impactor (PM0.1 NBI) for ultrafine particle (UFP) mass concentration measurement. The PM0.1 NBI uses a wetted glass fiber filter with continuous water injection to maintain a clean surface, preventing particle loading and bounce effects. Lab tests showed the 30 L/min PM0.1 NBI outperformed the PM0.1 stage of NCTU micro-orifice cascade impactor (NMCI, non-rotating) with a silicon oil-coated aluminum foil substrate in collecting solid particles, as the particle collection efficiency of the latter decreased obviously with increasing particle aerodynamic diameter for particles larger than ca. 300 nm, an apparent particle bounce phenomenon. The ambient field tests showed very close UFP mass concentrations between the PM0.1 NBI sampler (the PM0.1 NBI preceded by 3 stages with 18, 10, and 2.5 μm cutoff sizes) and the reference rotating 10-stages NMCI with the difference of ±0.5 μg/m3 only. In addition, the 3 L/min PM0.1 NBI was combined with a condensation particle counter to measure the UFP number concentrations which were shown to be very close to those of the reference with the difference of ±5% only in the laboratory tests for loaded particle mass up to 300 μg. Good agreement was also found in the field tests. Therefore, the current 3 L/min PM0.1 NBI and the future PM NBI with smaller flow rates (0.2–2.1 L/min) and larger cut-sizes (such as 0.4–0.9 μm) can be used as viable UFP classifiers for improving UFP measurement accuracy both in mass concentrations and number concentrations and reducing the maintenance needs for the UFP classifiers which are important to long-term sampling and monitoring.

Comprehensive characterization of particulate matter emissions produced by a liquid-fueled miniCAST burner

Soot particles generated by a liquid-fueled miniCAST burner, supplied with diesel B7, was characterized for the first time over a total of 34 operating points covering an overall equivalence ratio ( ϕ) range of 0.103-1.645. To characterize the gas and particulate phase emissions, electron microscopy images, mobility-equivalent size distributions and mass concentration of the soot aggregates were recorded, and optical extinction/absorption coefficients of the exhaust were measured. The burner produces soot aggregates with geometric mean diameter size in the range 45-105 nm with primary particle size in the range 18-39 nm. The Ångström absorption exponent ( α) was evaluated in the range 400-1000 nm and was found to increase with ϕ and vary in the range 1.05-2.25. The interposition of a catalytic stripper in the sampling line was found to (i) flatten the shape of the size distribution of aggregates, (ii) oxidize most of the gas phase thus impacting optical extinction coefficients particularly below 400 nm and (iii) decrease α. The soot volume fraction ( fv) was determined by three independent methods: optical absorption, mass deposit and mobility size distribution combined with morphology data. fv evaluated from size mobility data accounting for morphological aspects agreed within 13% with fv measured optically and within 25% with fv evaluated from mass concentration measurements. The precise methodology developed to characterize engine-like soot particles produced by a liquid-fueled miniCAST can now be transposed to study other regular, renewable, and surrogate liquid fuels to investigate their physical and optical properties before considering their large-scale use.

Effects of Gas and Steam Humidity on Particulate Matter Measurements Obtained Using Light-Scattering Sensors.

With the increasing need for particulate matter (PM) monitoring, the demand for light-scattering sensors that allow for real-time measurements of PM is increasing. This light-scattering method involves irradiating light to the aerosols in the atmosphere to analyze the scattered light and measure mass concentrations. Humidity affects the measurement results. The humidity in an outdoor environment may exist as gas or steam, such as fog. While the impact of humidity on the light-scattering measurement remains unclear, an accurate estimation of ambient PM concentration is a practical challenge. Therefore, this study investigated the effects of humidity on light-scattering measurements by analyzing the variation in the PM concentration measured by the sensor when relative humidity was due to gaseous and steam vapor. The gaseous humidity did not cause errors in the PM measurements via the light-scattering method. In contrast, steam humidity, such as that caused by fog, resulted in errors in the PM measurement. The results help determine the factors to be considered before applying a light-scattering sensor in an outdoor environment. Based on these factors, directions for technological development can be presented regarding the correction of measurement errors induced by vapor in outdoor environments.

Optical Physical Parameters of Fine Particulate Matter Based on Light Scattering Method

Following the Internet, the Internet of Things (IoT) has become another revolutionary technology in recent years. In recent years, Internet of Things technology has been applied to various industries such as agricultural production, intelligent transportation and industrial production, including the wireless system network under the Internet of Things technology. The problem of particulate matter pollution has become more and more concerned. However, how to quickly and accurately detect particulate matter concentration has become a research hotspot. The traditional filter membrane weighing method and ray absorption method have many limitations, which cannot meet the requirements of fast and accurate. The measurement of particle mass concentration by light scattering method is a non-contact detection method of particle mass concentration. In this paper, light scattering methods are combined with the theory of IoT wireless systems to discuss the photophysical parameters of tiny particles, such as particle size and density. This paper mainly studies the formation mechanism, particle detection principle and numerical simulation, and the data intelligent analysis of the optical and physical parameters of the particles. The particle size distribution, average particle size and density were obtained by CCD photosensor experiment. The experimental results show that the optical parameters of different particle sizes are accurate and reliable.

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.