Visualization of particulate matters in air using lensless microscopy

Outdoor near-roadway, community and residential pollen, carbon dioxide and particulate matter measurements in the urban core of an agricultural region in central CA

A numerical particulate matter (PM) measurement model is developed to characterize and evaluate PM sampling methods. Simulations are conducted using the model to evaluate currently widely used PM samplers, including Federal Reference Method (FRM) samplers. The simulations show that current PM samplers are very vulnerable to both changes in measurement target (i.e., natural variability of particle size distribution) and the sampler’s design, manufacturing, and operating conditions, potentially resulting in significant errors in the monitoring data. The numerical model is used in conjunction with two types of commercially available PM monitoring devices to form a Comprehensive Particulate Matter Monitoring System (CPMMS). The first type of device can be any mass-based PM monitor with a well-defined sampling efficiency curve. The second type of device is one capable of measuring particle size distribution with a reasonably good relative accuracy between size categories but not necessarily accurate in measuring absolute mass concentrations. This study shows that CPMMS can produce much higher quality PM monitoring data than the current PM samplers under the same conditions. In addition, unlike past and current PM monitoring data such as total suspended particulates, coarse PM (PM10), fine PM (PM2.5), etc., the CPMMS monitoring data will survive changes in PM regulatory definition. A new concept, dosimetry-based PM metrics and standards, is proposed to define ambient PM level based on the deposition fraction of particles in the human respiratory tract. The dosimetry-based PM metrics is more meaningful because it correlates the ambient PM level with the portion that can be deposited in the respiratory tract without an arbitrary cutoff particle diameter. CPMMS makes dosimetry-based PM metrics and standards feasible.

Nowadays particle size and mass concentration measurements are the important parameter of the ambient air quality standards of several countries. The regulatory limits of mass concentration of particulate matter (PM) for the size classes of PM2.5 and PM10, i.e., particle sizes of less than or equal to 2.5 and 10 μm in aerodynamic diameter, respectively in air are defined on yearly and hourly time-weighted-average basis. However, these limits are different in different regulations of the countries. Both of the parameters relate with the human health, climate and other issues, therefore accurate and precise measurement of these parameters are very important. Despite this, so far not much work has progressed in national metrology institutes (NMIs) worldwide on calibration and traceability issue of PM measurements. In this paper in context of PM measurement traceability, we present systematically the (1) air quality regulation in different countries, (2) reference methods for size and mass measurements, (3) variation/error and limitations of PM measurements based on the current results in this study and previously published results, (4) current status of PM size and mass calibration facility, (5) expected uncertainty in PM measurements, (6) add-on uncertainty in other parameters of national ambient air quality standards due to PM measurements, (7) where does traceability of PM issue stand against other parameters of air quality standards and its impact on health and climate, (8) NMIs working on this issue, (9) status at Bureau International des Poids et Mesures (BIPM), France and (10) conclusion. The aim of this paper is to better understand the importance of international system of units (SI) traceability issue in PM measurements, so wherever and whenever it is measured, should be acceptable everywhere, and data should be comparable for improving air quality and thus the quality of life. Funding agencies should be aware of this issue, and accept the results from the principle investigators and team only when their results have the traceability link to SI. NMIs should make program to involve industries in gas and aerosol metrology work to fulfill the requirement of calibration and standards. The regulatory authorities/ministry should work together with NMIs to improve the data quality of ambient measurements. This will greatly help to better make the policies and decisions on the related impacts. These were also the ultimate goals of “one-day pre-AdMet workshop” organized at National Physical Laboratory, New Delhi, India on February 20th, 2013.

Estimating multi-annual PM2.5 air pollution levels using sVOC soil tests: Ashkelon South, Israel as a case study

Characteristics of indoor air pollution and estimation of respiratory dosage under varied fuel-type and kitchen-type in the rural areas of Telangana state in India

Brain Fog: Does Air Pollution Make Us Less Productive?

Abstract. Modern-Era Retrospective analysis for Research and Applications v.2 (MERRA-2), Copernicus Atmosphere Monitoring Service Operational Analysis (CAMS-OA), and a high-resolution regional Weather Research and Forecasting model coupled with chemistry (WRF-Chem) were used to evaluate natural and anthropogenic particulate matter (PM) air pollution in the Middle East (ME) during 2015–2016. Two Moderate Resolution Imaging Spectrometer (MODIS) retrievals – combined product Deep Blue and Deep Target (MODIS-DB&DT) and Multi-Angle Implementation of Atmospheric Correction (MAIAC) – and Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) observations as well as in situ PM measurements for 2016 were used for validation of the WRF-Chem output and both assimilation products. MERRA-2 and CAMS-OA assimilate AOD observations. WRF-Chem is a free-running model, but dust emission in WRF-Chem is tuned to fit AOD and aerosol volume size distributions obtained from AERONET. MERRA-2 was used to construct WRF-Chem initial and boundary conditions both for meteorology and chemical and aerosol species. SO2 emissions in WRF-Chem are based on the novel OMI-HTAP SO2 emission dataset. The correlation with the AERONET AOD is highest for MERRA-2 (0.72–0.91), MAIAC (0.63–0.96), and CAMS-OA (0.65–0.87), followed by MODIS-DB&DT (0.56–0.84) and WRF-Chem (0.43–0.85). However, CAMS-OA has a relatively high positive mean bias with respect to AERONET AOD. The spatial distributions of seasonally averaged AODs from WRF-Chem, assimilation products, and MAIAC are well correlated with MODIS-DB&DT AOD product. MAIAC has the highest correlation (R=0.8), followed by MERRA-2 (R=0.66), CAMS-OA (R=0.65), and WRF-Chem (R=0.61). WRF-Chem, MERRA-2, and MAIAC underestimate and CAMS-OA overestimates MODIS-DB&DT AOD. The simulated and observed PM concentrations might differ by a factor of 2 because it is more challenging for the model and the assimilation products to reproduce PM concentration measured within the city. Although aerosol fields in WRF-Chem and assimilation products are entirely consistent, WRF-Chem is preferable for analysis of regional air quality over the ME due to its higher spatial resolution and better SO2 emissions. The WRF-Chem’s PM background concentrations exceed the World Health Organization (WHO) guidelines over the entire ME. Mineral dust is the major contributor to PM (≈75 %–95 %) compared to other aerosol types. Near and downwind from the SO2 emission sources, nondust aerosols (primarily sulfate) contribute up to 30 % to PM2.5. The contribution of sea salt to PM in coastal regions can reach 5 %. The contributions of organic matter, black carbon and organic carbon to PM over the Middle East are insignificant. In the major cities over the Arabian Peninsula, the 90th percentile of PM10 and PM2.5 (particles with diameters less than 10 and 2.5 µm, respectively) daily mean surface concentrations exceed the corresponding Kingdom of Saudi Arabia air quality limits. The contribution of the nondust component to PM2.5 is <25 %, which limits the emission control effect on air quality. The mitigation of the dust effect on air quality requires the development of environment-based approaches like growing tree belts around the cities and enhancing in-city vegetation cover. The WRF-Chem configuration presented in this study could be a prototype of a future air quality forecast system that warns the population against air pollution hazards.

Critical aspects of the uncertainty budget in the gravimetric PM measurements

This study combined on-site measurement and model simulation to characterize the spatial distribution of indoor particulate matter (PM) in a single room with stratified flow fields. The concentration of PM spatially distributed in a single room with natural ventilation was measured at different heights for different PM sizes. This study revealed that the PM concentration varied with height and time. Moreover, chamber test results showed that by burning Chinese worship incense, fine particles (PM0–4) accounted for 97.33% of total PM with an average emission factor of 39.54 mg/g. The results were then applied to determine the gross emission of PM and describe its spatial distribution in a single room. Model simulation results indicated that only a small amount of PM flowed out of the room due to the trap by an indoor vortex under natural ventilation. The results are crucial for characterizing the stratified PM concentration and determining the sites for PM monitoring in indoor environments.

Systematic review of UAV-assisted airborne particulate matter measurement in urban areas

Attention has been paid to low-cost, light-scattering-based particulate matter (PM) sensors, which provide PM measurements in order to supplement a small number of expensive air quality monitoring stations. However, low-cost PM sensors produce measurement data of questionable quality. In this paper, we evaluate the performance of low-cost PM sensors, specifically PurpleAir PA-II units. To evaluate the PurpleAir PA-II units, we use accurate air quality data measured from monitoring stations within close proximity to the PA-II units as reference. By means of linear regression, we compare PurpleAir PA-II units with air quality monitors. From the result, PurpleAir PA-II units have high correlations (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ≥ 0.84) with nephelometers, which are based on the principle of light-scattering, and thus the PurpleAir PA-II is a sufficient substitute for nephelometers. PurpleAir PA-II units have a good agreement (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.72 and 0.89) with MetOne BAM 1020 monitors based on beta ray attenuation but show a non-linear behavior. Furthermore, there is an essential observation that the PurpleAir PA-II unit needs to have significantly high precision in order to have a high correlation with an expensive reference monitor and thus be used supplementally. The considered PurpleAir PA-II units overestimate PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub> concentrations compared with air quality reference monitors. Therefore, a calibration algorithm for PurpleAir PA-II units should be considered to give a correct air quality index at sites considered in this paper. However, our results show the PurpleAir PA-II to be a promising low-cost air quality sensor for supplementing a conventional air quality sensing network with expensive monitors.

Abstract: Introduction. Air pollution with particulate matter (PM) is a serious global problem. In the Russian Federation, regular field measurements of PMs in the ambient air are carried out only in a number of cities, and the data, as a rule, are not systematized. Aim of the study: retrospective analysis of the data set on concentrations of fine particles in the ambient air of the city of Kazan. Methods. Retrospective analysis of pollution by fine fractions of suspended solids in the ambient air of Kazan in the period from 2016 to 2020 has been carried out. To study the effect of individual factors (time period (year), measurement time during the day, climatic conditions, the presence of other pollutants) on the pollution levels PM 10 and PM 2.5, regression analysis was applied based on the method of mixed models. Results. The PM 10 concentrations remained stable over a 5-year period, while the PM 2.5 concentrations decreased. At the same time, an increase in the maximum annual concentrations of both fractions was observed. The concentrations of PM 10 and PM 2.5 significantly depended on weather factors. The presence of nitrogen oxides and organic carbon in the ambient air was associated with significantly higher concentrations of PM 10 and PM 2.5. Conclusion. A statistically significant upward trend in the dynamics of the years of the maximum annual values for both fractions of suspended particles can increase health risks. Secondary pollutants (nitrogen oxides, organic carbon) is an important factor for the formation of secondary particles in the ambient air. Implementation of preventive measures in relation to industrial emissions, regional urban planning policy and a scientifically based program of social and hygienic monitoring are the most important tools for effective management of health risks caused by exposure to fine particles.

The U.S. Environmental Protection Agency (US EPA) requires residential wood heaters (RWHs) to meet particulate matter (PM) emission limits in order to lower ambient concentrations and reduce public exposure. The current US EPA dilution tunnel PM measurement methods for RWHs were developed several decades ago and use manual filter samples to generate a single PM value for tests that can last more than 12 hours for stoves and 30 hours for central heating appliances. This approach results in averaging periods of high and low emissions together and provides limited data on emissions over the entire burn profile. Over the last decade, the U.S. ambient fine particulate monitoring network has transitioned to the routine use of online automated methods. However, stationary source measurement methods have not made this transition. There are no substantial technical issues in implementing real-time automated methods to measure PM for RWH emission certification purposes. The Thermo Scientific Tapered Element Oscillating Microbalance (TEOM™) has been widely used for ambient PM measurements. It is a true inertial mass measurement with high time resolution and sensitivity. This work compares measurements obtained using a Thermo 1400 or 1405 TEOM with ASTM E2515 manual filter samples, the current US EPA Federal Reference Method, for 172 test runs across a wide range of stoves and PM loading conditions. The TEOM measurements used the same filter media, similar filter face velocities, and filter temperatures as manual methods. PM measurements were well correlated (R2 > 0.9), with TEOM values typically lower by 5% to 10%. TEOM data capture was high, with filter changes resulting in ~5 minutes of lost data, usually once or twice during a multi-hour test. We discuss differences between the two methods, such as post-sampling equilibration and measurement of PM on sample train surfaces (probe “catch”). We also provide examples of substantial non-water semi-volatile mass loss during sampling. Implications: Measurement methods for continuous PM and our understanding of their performance has dramatically improved over the last thirty years. Highly time-resolved measurements of PM from residential wood heating appliances in an appliance certification testing context provide additional insight into both appliance performance and the suitability of the test method to assess that performance. This continuous measurement approach offers new opportunities to replace traditional US regulatory PM sampling integrated manual source methods like ASTM E2515 or EPA Method 5G testing. For measurement of combustion products that can have a wide range of physical and chemical characteristics, the TEOM’s actual mass measurement principle has advantages over the sensitivity of surrogate methods to different aerosols for use in a regulatory program. Although the TEOM is commonly used to measure ambient PM, it can readily be configured to meet the needs of continuous emission testing.

USEPA’s recent promulgation of the Clean Air Interstate Rule (CAIR) and Clean Air Mercury Rule (CAMR), and the designation of domestic fine particulate non-attainment areas, has spurred interest in adding particulate matter (PM) and mercury continuous emission monitoring systems (CEMS) to US power plants. While much of this interest has centered at least initially on pulverized coal-fired boiler units, the burgeoning integrated gasification combined cycle (IGCC) power market will likely also face the challenge of applying these new air emission measurement technologies. This paper will address the regulatory drivers which will encourage application of the PM and mercury CEMS on IGCC facilities, and it will discuss and evaluate the various measurement technologies/equipment available to comply with the new continuous emission measurement requirements. It will also summarize how various monitoring equipment suppliers have responded to this regulatory initiative. Finally, it will offer strategies to reduce the attendant risks and uncertainties associated with applying what are essentially emerging measurement technologies — technologies that will be tasked with demonstrating compliance with well-defined, strict air emission limitations.

Exposure to ambient particulate matter (PM) air pollution is a leading risk factor for morbidity and mortality, associated with up to 8.9 million deaths/year worldwide. Measurement of personal exposure to PM is hindered by poor spatial resolution of monitoring networks. Low-cost PM sensors may improve monitoring resolution in a cost-effective manner but there are doubts regarding data reliability. PM sensor boxes were constructed using four low-cost PM micro-sensor models. Three boxes were deployed at each of two schools in Southampton, UK, for around one year and sensor performance was analysed. Comparison of sensor readings with a nearby background station showed moderate to good correlation (0.61 < r < 0.88, p < 0.0001), but indicated that low-cost sensor performance varies with different PM sources and background concentrations, and to a lesser extent relative humidity and temperature. This may have implications for their potential use in different locations. Data also indicates that these sensors can track short-lived events of pollution, especially in conjunction with wind data. We conclude that, with appropriate consideration of potential confounding factors, low-cost PM sensors may be suitable for PM monitoring where reference-standard equipment is not available or feasible, and that they may be useful in studying spatially localised airborne PM concentrations.