Ambient Particulate Matter Measurements Research Articles

Measurement of ambient particulate matter (PM1.0, PM2.5 and PM10) in Khulna City of Bangladesh and their implications for human health

Atmospheric particles have been significantly affecting urban air quality and urban-oriented living in an increasing share of the population in Bangladesh. This study assessed the concentration of PM1.0, PM2.5, and PM10 in Khulna, one of the largest cities in Bangladesh located near the Bay of Bengal. The maximum average concentrations were recorded 415 ± 184.01 µg/m3 for PM10, 302 ± 109.89 µg/m3 for PM2.5, and 143 ± 45.05 µg/m3 for PM1.0. These values are several times higher than the World Health Organization air quality standard and Bangladesh National Ambient Air Quality Standard. According to the size and fractional distribution of PM, most of the monitoring locations were dominated by fine particles. Carcinogenic and non-carcinogenic risks due to exposure to ambient PM1.0, PM2.5 and PM10 were also quantified to illustrate the relevant potential human health risks. The excess lifetime cancer risk (ELCR) values of PM1.0 ranged from 8.6E0–4 to 6.0E–07 and PM2.5 varied between 8.6E–04 and 6.0E–07 exceeded the allowable limit at every location indicating the potential cancer-developing risk to the urban population. The health quotient (HQ) values also crossed the least permissible value at most of the locations depicting strong non-carcinogenic risks. Average HQ values of PM2.5 varied from 1.07 to 20.13 while PM10 ranged from 0.44 to 8.3. This research revealed children and elderly people as the most vulnerable age groups with the highest carcinogenic risks through exposure to atmospheric PM in Khulna city. Therefore, air pollution reduction plans and risk mitigation strategies should be developed and implemented by the government authorities.Graphical

Online measurement of PM from residential wood heaters in a dilution tunnel

ABSTRACT 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.

Developing a Relative Humidity Correction for Low-Cost Sensors Measuring Ambient Particulate Matter.

There is increasing concern about the health impacts of ambient Particulate Matter (PM) exposure. Traditional monitoring networks, because of their sparseness, cannot provide sufficient spatial-temporal measurements characteristic of ambient PM. Recent studies have shown portable low-cost devices (e.g., optical particle counters, OPCs) can help address this issue; however, their application under ambient conditions can be affected by high relative humidity (RH) conditions. Here, we show how, by exploiting the measured particle size distribution information rather than PM as has been suggested elsewhere, a correction can be derived which not only significantly improves sensor performance but which also retains fundamental information on particle composition. A particle size distribution–based correction algorithm, founded on -Köhler theory, was developed to account for the influence of RH on sensor measurements. The application of the correction algorithm, which assumed physically reasonable values, resulted in a significant improvement, with the overestimation of PM measurements reduced from a factor of ~5 before correction to 1.05 after correction. We conclude that a correction based on particle size distribution, rather than PM mass, is required to properly account for RH effects and enable low cost optical PM sensors to provide reliable ambient PM measurements.

Respiratory hospitalizations in association with fine PM and its components in New York State

Despite observed geographic and temporal variation in particulate matter (PM)-related health morbidities, only a small number of epidemiologic studies have evaluated the relation between PM2.5 chemical constituents and respiratory disease. Most assessments are limited by inadequate spatial and temporal resolution of ambient PM measurements and/or by their approaches to examine the role of specific PM components on health outcomes. In a case-crossover analysis using daily average ambient PM2.5 total mass and species estimates derived from the Community Multiscale Air Quality (CMAQ) model and available observations, we examined the association between the chemical components of PM (including elemental and organic carbon, sulfate, nitrate, ammonium, and other remaining) and respiratory hospitalizations in New York State. We evaluated relationships between levels (low, medium, high) of PM constituent mass fractions, and assessed modification of the PM2.5–hospitalization association via models stratified by mass fractions of both primary and secondary PM components. In our results, average daily PM2.5 concentrations in New York State were generally lower than the 24-hr average National Ambient Air Quality Standard (NAAQS). Year-round analyses showed statistically significant positive associations between respiratory hospitalizations and PM2.5 total mass, sulfate, nitrate, and ammonium concentrations at multiple exposure lags (0.5–2.0% per interquartile range [IQR] increase). Primarily in the summer months, the greatest associations with respiratory hospitalizations were observed per IQR increase in the secondary species sulfate and ammonium concentrations at lags of 1–4 days (1.0–2.0%). Although there were subtle differences in associations observed between mass fraction tertiles, there was no strong evidence to support modification of the PM2.5-respiratory disease association by a particular constituent. We conclude that ambient concentrations of PM2.5 and secondary aerosols including sulfate, ammonium, and nitrate were positively associated with respiratory hospitalizations, although patterns varied by season. Exposure to specific fine PM constituents is a plausible risk factor for respiratory hospitalization in New York State.Implications: The association between ambient concentrations of PM2.5 components has been evaluated in only a small number of epidemiologic studies with refined spatial and temporal scale data. In New York State, fine PM and several of its constituents, including sulfate, ammonium, and nitrate, were positively associated with respiratory hospitalizations. Results suggest that PM species relationships and their influence on respiratory endpoints are complex and season dependent. Additional work is needed to better understand the relative toxicity of PM species, and to further explore the role of co-pollutant relationships and exposure prediction error on observed PM–respiratory disease associations.

Effect of humidity and temperature on filter and gravimetric measurement of ambient particulate matter in a balance room

To assess the effects of the alteration of humidity and (or) temperature on weight of filters without and with ambient particulate matter in a balance room. The mass of blank dust sampling filters were weighed under (18 +/- 1) degrees C and (28 +/- 1) degrees C respectively, with the humidity varying from 35% relative humidity (RH) to 100% RH in a balance room. Then the blank filters were divided into two groups and were used to sample total dust and respirable dust. After sampling, the loaded filters were re-weighed under above conditions and the mass difference before and after the sampling were compared and analyzed. The vibration of the average mass of filters varied from 0.10 to 0.13 mg and from 0.06 to 0.09 mg under the temperatures of (18 +/- 1) degrees C and (28 +/- 1) degrees C respectively; When both the temperature and humidity changed, it varied from 0.12 to 0.16 mg. The deviation of average mass difference ranged from 0.07 to 0.10 mg and from 0.04 to 0.08 mg under the two temperatures mentioned above; When both the temperature and humidity changed, it varied from 0.09 to 0.14 mg. The average mass of blank filters and loaded filters were all positively correlated with the change of humidity (P < 0.01). No effects of humidity on the average mass difference of the loaded filters were observed. The average mass differences of loaded filters and blank filters under (18 +/- 1) degrees C were significantly higher than that under (28 +/- 1) degrees C (P < 0.01) when humidity was not changed. The alteration of humidity and (or) temperature in a balance room attributes to the deviation of the measurement of the mass of filters and thus affects the gravimetric measurements of ambient particulate matter.

Assessing sources of variability in measurement of ambient particulate matter

AbstractParticulate matter (PM), a component of ambient air pollution, has been the subject of United States Environmental Protection Agency regulation in part due to many epidemiological studies examining its connection with health. Better understanding the PM measurement process and its dependence on location, time, and other factors is important for both modifying regulations and better understanding its effects on health. In light of this, in this paper, we will explore sources of variability in measuring PM including spatial, temporal and meteorological effects. In addition, we will assess the degree to which there is heterogeneity in the variability of the micro‐scale processes, which may suggest important unmeasured processes, and the degree to which there is unexplained heterogeneity in space and time. We use Bayesian hierarchical models and restrict attention to the greater Pittsburgh (USA) area in 1996. The analyses indicated no spatial dependence after accounting for other sources of variability and also indicated heterogeneity in the variability of the micro‐scale processes over time and space. Weather and temporal effects were very important and there was substantial heterogeneity in these effects across sites. Copyright © 2001 John Wiley &amp; Sons, Ltd.

Large Particle Size Distribution in Five U.S. Cities and the Effect on a New Ambient Participate Matter Standard (PM10)

A mobile aerosol-sampling system was used to determine the large particle ambient aerosol size distribution (up to approximately 100 μm particle diameter) in five cities across the United States: Birmingham, Alabama; Research Triangle Park, North Carolina; Philadelphia, Pennsylvania; Phoenix, Arizona; and Riverside, California. A mobile wide range aerosol classifier (WRAC) developed at the University of Florida was used. The study shows that any measurement of ambient particulate matter with a size-fractionating inlet sampler will be influenced by the ambient particle size distribution. Mass distribution measurements determined by the WRAC were compared with mass measurements obtained simultaneously using TSP Hi-Vol and 15 μm cut-size inhalable particulate network samplers. Aerosol size-classification results showed the presence of a large particle mass mode at all sites sampled. The position and magnitude of the large particle mode varied and was not a simple function of concentration. The percentage of ...