Continuous Particulate Matter Research Articles

Feasibility analysis of AERONET lunar AOD for nighttime particulate matter estimation

Several studies have attempted to estimate particulate matter (PM) concentrations using aerosol optical depth (AOD), based on AOD and PM relationships. Owing to the limited availability of nighttime AOD data, PM estimation studies using AOD have focused on daytime. Recently, the Aerosol Robotic Network (AERONET) produced nighttime AOD, called lunar AOD, providing an opportunity to estimate nighttime PM. Nighttime AOD measurements are particularly important as they help fill gaps in our understanding of aerosol variability and its impact on the atmosphere, as there are significant variations in AOD between day and night. In this study, the relationship between lunar AOD and PM was investigated using data from AERONET station, meteorological station, and air pollution station in Seoul Metropolitan area from May 2016 to December 2019, and then PM estimation model was developed covering both daytime and nighttime using random forest machine learning techniques. We have found the differences in the importance of variables affecting the AOD-PM relationship between day and night from the random forest model. The AOD-PM relationship in the daytime was more affected by time-related variables, such as the day of the year among the variables. The new model was developed using additional lunar AOD data to estimate continuous PM concentrations. The results have shown that the model based on lunar AOD data estimated well PM10 and PM2.5 with similar performance of model using solar AOD. The results imply the possibility of seamless near-surface PM concentration data on a large scale once satellites produce nighttime AOD data.

Maternal exposure to particulate matter early in pregnancy and congenital anomalies in offspring: Analysis of concentration-response relationships in a population-based cohort with follow-up throughout childhood

Studies have suggested an association between particulate matter (PM) air pollution and certain congenital anomalies (CAs). However, most studies assumed a linear concentration-response relation and were based on anomalies that were ascertained at birth or up to 1 year of age. We investigated associations between exposures to PM during the first trimester of pregnancy and CAs in 9 organ systems using birth and childhood follow-up data from a leading health care provider in Israel. We conducted a retrospective population-based cohort study among 396,334 births, 2004–2015. Daily PM data at a 1 × 1 km spatial grid were obtained from a satellite-derived prediction models and were linked to the mothers' residential addresses at birth. Adjusted odds ratios (ORs) were estimated with logistic regression models using exposure levels as either continuous or categorical variables. We captured 57,638 isolated CAs with estimated prevalence of 96 and 136 anomalies per 1000 births in the first year of life and by age 6 years, respectively. Analysis of continuous PM with diameter < 2.5 μm (PM2.5) indicated a supra-linear relation with anomalies in the circulatory, respiratory, digestive, genital and integument systems (79 % of CAs). The slope of the concentration-response function was positive and steepest for PM2.5 lower than the median concentration (21.5 μg/m3) and had a less steep or negative slope at higher levels. Similar trends were observed for PM2.5 quartiles. For example, for cardiac anomalies, the ORs were 1.09 (95 % confidence interval: 1.02, 1.15), 1.04 (0.98, 1.10) and 1.00 (0.94, 1.07) for births in the second, third and fourth quartiles, respectively, when compared to the first quartile. In sum, this study adds new evidence for adverse effects of air pollution on neonatal health even with low-level air pollution. Information on late diagnosis of children with anomalies is important in evaluating the burden of disease.

2019 Southeast Asia Transboundary Haze and its Influence on Particulate Matter Variations: A Case Study in Kota Kinabalu, Sabah

&lt;abstract&gt;&lt;p&gt;In 2019, Malaysia faced a deterioration of air quality due to transboundary haze, which brought negative implications, especially for public health. In light of the above scenario, continuous particulate matter (PM&lt;sub&gt;10&lt;/sub&gt;, PM&lt;sub&gt;2.5&lt;/sub&gt; and PM&lt;sub&gt;1&lt;/sub&gt;) and meteorological parameters amid the haze period were taken to unravel the influence of haze on particulate matter variations and to investigate the association between particulate matter concentrations with meteorological parameters and fire hotspots in Kota Kinabalu, where it is rarely studied. Particulate matter and the meteorological parameters were monitored during the haze season, continuously from 21 August–30 September 2019, using AirMate, a ground-based air monitoring equipment. Air mass backward trajectories were simulated using the HYSPLIT Model, and fire hotspot data was obtained from the Greenpeace Global Fire Dashboard. The results showed increasing particulate matter concentrations during the haze period, with PM&lt;sub&gt;2.5&lt;/sub&gt; exceeding the New Ambient Air Quality Standards (2020) on multiple days. For meteorological parameters, all parameters showed a significant weak positive relationship with respective particulate matter. However, the correlation between particulate matter and fire hotspots in Indonesia showed a moderate positive relationship. The backward trajectories simulated indicated the influence of south-westerly winds in transporting the pollutants from fire hotspots in the Indonesia region. Thus, we provide beneficial information about the impacted area during the 2019 transboundary haze episode, where the interactions between the particulate matter variations and the parameters studied were unraveled.&lt;/p&gt;&lt;/abstract&gt;

Evaluation of fixed and adaptive concentration thresholds for particle filter systems.

Particle filtration can effectively reduce indoor concentrations of particulate matter (PM) but may incur high energy use. This study evaluates fixed and adaptive concentration thresholds to automate the operation of filtration systems. Simulated environments were derived from week-long continuous PM measurements from Dylos DC1700 (N=104) and Alphasense OPC-N2 (N=100) particle counters deployed in apartments in Toronto. A fixed threshold of 4.0μg·m-3 resulted in a mean air cleaner runtime of 6.9%-21.0% depending on clean air delivery rate (CADR) and particle sensor, while providing mean concentration reductions of 67%-71% compared to operating the air cleaner constantly (runtime=100%). In most environments, runtime could be further reduced by raising the fixed threshold while resulting in only a modest decrease in absolute and normalized mean exposure reduction. Using an adaptive threshold derived from a k-means clustering approach generally provided substantial exposure reduction while preventing high runtimes. These results were generally insensitive to cleaning power and the monitor used to measure particle concentrations. Reducing the energy usage of particle filter systems will make them a more viable and sustainable means of improving occupant health.

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.

The impact of climate factors on airborne particulate matter removal by plants

Airborne particulate matter (PM) filtration by plants is a process of continuous PM accumulation and periodic washing, in which climate factors plays a key role. However, most of the relevant studies have focused on the impact of single meteorological factors, the influencing mechanism of comprehensive meteorological factors, i.e., climate, on PM filtration by plants remains unclear. Coupled with the i-Tree model, we established a multi-cycle PM removal (PMR) model with the focus on the impact of wind and precipitations on the PM filtration function of plants, so as to inform the suitability of different climates for green space creation. Interactions between relevant parameters were analyzed through simulation. It was found that the PM capture threshold of plants and the time required to reach this threshold both decreased with wind speed (V). The PMR performance of plants increased and then decreased with V, and the optimal V decreased with increasing precipitation interval (T). The performance of different climates in PMR could be ranked as: short T & high V > short T & low V > long T & low V > long T & high V. Within areas characterized by a long T, it is suitable to create green spaces in the places where V is relatively low and with the pattern of large patches and high-density to reduce plants’ exposure V. Additionally, the relative magnitudes of the PMR of different plant species may change with V or T; species selection should match the regional climate. This study can help to clarify the influencing mechanism of climate factors on the PMR performance of plants and provides guidance for creating green spaces for PM control under different climate regimes.

Particulate Matter Monitoring and Assessment through Internet of Things: a Health Information System for Enhanced Living Environments.

People spend most of their time inside buildings. Therefore, indoor air quality monitoring contributes to improve health and well-being. Several studies focus on the critical impact of particulate matter on residential air quality. In 2016, particulate matter caused 412 thousand premature deaths in 41 European countries. This paper presents the development of an affordable health information system for enhanced living environments. The authors propose a cost-effective, modular, scalable, and easy installation solution for particulate matter monitoring. The system is connected to ThingSpeak. It can be installed in any type of building. It requires only a power source and a Wi-Fi network with internet access. The main contribution of this paper is to present the detailed architecture and testing results. The particulate matter monitoring system was installed for one week in a domestic kitchen with an open fireplace. The results showed impact of the biomass burning on indoor air quality. The mean values per day ranged from: 10.53 to 50.62 μg/m3 for PM1.0, 15.35 to 69.37 μg/m3 for PM2.5, and 20.1 to 90.69 μg/m3 for PM10. The maximum values per hour were registered at 13:00: 72.14 μg/m3 for PM1.0, 99.70 μg/m3 for PM2.5, and 132.13 μg/m3 for PM10. Cost-effective sensors do not have the accuracy level of industrial equipment. Therefore, they should not be used for numerical and in-depth accurate characterization of the environment. Nevertheless, continuous particulate matter monitoring provides consistent data series for analysis of indoor air quality evolution.

Kinetic modeling of PM combustion with relative velocity at low-temperature and numerical simulation of continuous regenerating type PM removal device that uses a fluidized bed

The size of particulate matter (PM) generated by combustion has decreased with the improvement of combustion technology. While small PM has a significant negative impact on the human body, it is difficult for a conventional PM removal device to collect small PM. We developed a fluidized bed type PM removal device with a focusing adhesion force. This device collects small PM effectively and can be operated as a continuous regeneration device at low temperature. To further develop this device, it is important to investigate the PM combustion characteristics in this device. The kinetic model constructed in conventional thermogravimetry could not accurately represent the combustion rates of the solid fuel in the fluidized bed. Therefore, a new thermogravimetric apparatus was constructed in this study that generates the direct collision of air with carbon to reproduce the fluidized bed combustion. The influence of the relative velocity between PM and gas on the combustion rate was investigated. The effect of relative velocity was represented as the mass transfer coefficient of kinetic model. It is observed that the combustion rate shows Arrhenius behavior, and kinetic parameters were determined by fitting. The kinetic model was applied to the numerical simulations of the PM removal device. The numerical collection efficiency was in good agreement with the experimental data. PM adhesion and combustion characteristics were investigated in numerical simulations. It is observed that the adhesion rate is high at a low void fraction and that the combustion rate is high at a high relative velocity. The PM combustion amount is high for the high adhesion and combustion rates. The total combustion amount is determined to be 55% of the total amount of PM deposition after 180 min at each set of conditions.

Promoting effect of water vapor on particle matter combustion in a low-temperature continuous regeneration type PM removal device using a fluidized bed

A fluidized bed type particulate matter (PM) removal device has been developed by focusing on the adhesion force under condition of non-water vapor. This device efficiently collects fine PM and can be operated as a low-temperature continuous regeneration device. The exhaust gas of a combustor includes water vapor at concentrations of 5–15 vol%. To further develop this device, the effect of water vapor on the continuous regeneration was investigated. The collection efficiency increases due to the water vapor. The reaction rate constant increases with increasing water vapor and with decreasing PM diameter. It is shown that water vapor promotes PM combustion at 250–400 °C. A smaller PM suits PM collection and combustion because smaller PM results in relatively larger adhesion force and well contacts the oxidant by dispersing it on the bed particles. The continuous regeneration temperature decreases to 380 °C due to the water vapor under optimal conditions.

Impact of Smart Home Portable Air Purification on Average and Peak PM2.5 Concentrations in Small Urban Residences

Sensor-activated, dynamic portable air purifiers are a part of a growing market of smart home technologies aimed at improving energy efficiency and health. For vulnerable populations such as children, elderly and individuals with a pre-existing condition, air purification may reduce daily exposure to harmful concentrations of fine particles. Some new air purifiers are sensor activated such that filtration is triggered by air quality conditions in the space; however, the effectiveness of these &amp;#8216;smart home&amp;#8217; purifiers compared to traditional air purification has not been evaluated in a real-world setting. In summer 2017, a crossover study was completed in small urban residences (n&amp;#61;32), which compared the change in continuous particulate matter less than 2.5 microns in diameter (PM2.5) concentrations across three intervention arms: 1) No Air Purification, 2) Smart Home Purification and 3) Continuous Purification. Overall, continuous purification significantly reduced average PM2.5 compared to baseline and smart home conditions by 1.171 µg/m3and 1.210 µg/m3respectively. However, the average duration participants were exposed to concentrations above 30µg/m3, the activation threshold for the device used in the study, was shortened by 60.8 minutes and 43.8 minutes with Smart Home purification compared to baseline and continuous filtration, respectively. The implication of these findings is that Smart Home purification can reduce peak exposures to PM2.5, but may lead to higher cumulative exposures at lower levels compared to continuous filtration. As a result, Smart Home purification may be best suited to reduce exposures during acute PM2.5-emitting events such as cooking or rush hour traffic.

Estimating daily and intra-daily PM10 and PM2.5 in Israel using a spatio-temporal hybrid modeling approach

Satellite-based particulate matter (PM) models provide spatially and temporally resolved estimations, allowing greater spatial-temporal coverage compared to sparse ground monitoring stations. The spatio-temporal resolution of these models can be improved using aerosol optical depth (AOD) products from various satellite platforms with different overpass times which can capture possible changes in diurnal aerosol concentrations. Israel is characterized by diverse geo-climatic regions and it is subjected to frequent dust storms events. Our goal was to estimate PM10 and PM2.5 concentrations in Israel on daily and intra-daily (mean PM around the Aqua and Terra overpasses) temporal resolutions and to assess the differences between these time windows. A hybrid modeling approach that consists of three stages was used enabling spatially continuous PM estimations at 1 × 1 km spatial resolution. The model was calibrated on a daily basis applying a mixed modeling approach using MODIS-based MAIAC AOD and various spatial and temporal predictors. It was found that in certain urban areas the measured and estimated PM concentrations during the satellite overpass (Terra or Aqua) were higher than the mean daily PM. The models performed well showing cross-validated R2 that ranged between 0.82 and 0.92. Mean estimated PM for the study period (2005–2015) during days with no dust events showed different spatial patterns for the daily and intra-daily estimations and revealed areas in Israel that are affected by high PM concentrations (mainly industrial or dense urban areas). Estimations from these models are useful for epidemiological research and might contribute to environmental regulatory purposes by focusing the efforts of PM pollution reduction at the identified polluted areas.

Particulate Matter Triggers Depressive-Like Response Associated With Modulation of Inflammatory Cytokine Homeostasis and Brain-Derived Neurotrophic Factor Signaling Pathway in Mice

Particulate matter (PM) exposure may contribute to depressive-like response in mice. However, few studies have evaluated the adaptive impacts of long-term PM exposure on depressive-like response associated with systemic inflammation and brain-derived neurotrophic factor (BDNF) signaling pathway. We studied the association among depressive-like behaviors, mRNA levels of pro and anti-inflammatory cytokines, and the expression of BDNF signaling pathway in mice by long-term PM exposure. C57BL/6 male mice were exposed to ambient air alongside control mice breathing air filtered through a high-efficiency air PM (HEPA) filter. Depressive-like behaviors were assessed together with proinflammatory, anti-inflammatory cytokine mRNA levels and the modulation of BDNF pathway in hippocampus and olfactory-bulb of mice exposed to PM for 4, 8, and 12 weeks. Exposure to HEPA-filtered air for 4 weeks may exert antidepressant like effects in mice. Proinflammatory cytokines were up-regulated while the expression of BDNF, its high-affinity receptor tropomyosin-related kinase B (TrkB), and the transcription factor (cyclic adenosine monophosphate)-response element-binding protein (CREB) were down-regulated in ambient air mice. However, after 8 weeks, there was no significant difference in the rate of depressive-like behaviors between the 2 groups. After 12 weeks, mice exposed to ambient air again had a higher rate of depressive-like behaviors, significant up-regulation of proinflammatory cytokines, down-regulation of interleukin-10, BDNF, TrkB, and CREB than HEPA mice. Ultrafine PM in brain tissues of mice exposed to ambient air was observed. Our results suggest continuous high-level PM exposure alters the depressive-like response in mice and induces a damage-repair-imbalance reaction.

SPATIAL AND TEMPORAL BEHAVIOR OF PB, CD, AND ZN RELEASE DURING SHORT TERM LOW INTENSITY RESUSPENSION EVENTS

Sediment as the largest storage and resources of heavy metal plays an important role in the metal remobilisation and release. Continuous particulate matter in suspension increased the level and mobility of metals, of which poses a serious problem particularly to aquatic organisms. The purpose of this research is to investigate the fate and amount of contaminant released through sediment resuspension by using particle entrainment simulator (PES) with low turbulence intensity. The heavy metal release from sediment mixture of sand/silt/clay with percentage of 90/5/5, respectively was studied. In particular, the research paid attention to the contaminant release at the early resuspension stage (i.e. within 3 hr resuspension) by reviewing the metal releases of Zn, Cd and Pb in water column at five elevations from the bed of PES. Results showed that the concentration of remobilised heavy metal during resuspension event for Cd, Zn and Pb was in ranged of 0.034 to 0.139 mg/L, 0.014 to 0.071 mg/L and 0.007 to 0.029 mg/L respectively. The affinities of heavy metal release discussed in this study was Cd &gt; Zn &gt; Pb. Concentrations of the heavy metal fluctuated within the water column and have the lowest values at near bed. The highest concentration observed for Cd and Zn was at one integral length scale from the sediment bed and at t = 120 mins. Even at low turbulence intensity, the heavy metal release was still observed and is significant to the water quality.

Indoor environmental quality index for conservation environments: The importance of including particulate matter

It is commonly known that the conservation state of works of arts exhibited inside museums is strongly influenced by the indoor environmental quality (IEQ). Heritage institutions traditionally record and evaluate their IEQ by monitoring temperature, relative humidity, and -more rarely-light. However, smart use of technology enables monitoring other parameters that give a more complete insight in environmental ‘air aggressiveness’. One of this parameters is particulate matter (PM) and especially its concentration, size distribution and chemical composition. In this work, we present a selection of data sets which were obtained in a measuring campaign performed in the War Heritage Institute in Brussels, Belgium. A continuous monitoring of PM concentration with a light scattering based particle counter was performed. In addition the daily mass concentration and size distribution of airborne PM was monitored by means of Harvard impactors. The chemical composition of sampled PM was inferred from the results of XRF and IC analysis. The insights from these datasets are combined with the results of traditional environmental monitoring (temperature, relative humidity and light intensity), and assessed against the recommended guidelines for conservation environments. By using an integrated approach based on the calculation of an IEQ-index, we present a straightforward methodology to evaluate and visualize the IEQ including also continuous PM monitoring. It is clear from the results of this study how including PM in IEQ analysis allows to identify potential risks for museum collections that remain invisible when only traditional parameters are considered.

Development and field evaluation of an online monitor for near-continuous measurement of iron, manganese, and chromium in coarse airborne particulate matter (PM)

ABSTRACTA novel air sampling monitor was developed for near-continuous (i.e., 2-h time resolution) measurement of iron (Fe), manganese (Mn), and chromium (Cr) concentrations in ambient coarse particulate matter (PM) (i.e., PM10–2.5). The developed monitor consists of two modules: (1) the coarse PM collection module, utilizing two virtual impactors (VIs) connected to a modified BioSampler to collect ambient coarse PM into aqueous slurry samples; (2) the metal concentration measurement module, which quantifies the light absorption of colored complexes formed through the reactions between the soluble and solubilized target metals and pertinent analytical reagents in the collected slurries using a micro volume flow cell (MVFC) coupled with UV/VIS spectrophotometry. The developed monitor was deployed in the field for continuous ambient PM collection and measurements from January to April 2016 to evaluate its performance and reliability. Overall, the developed monitor could achieve accurate and reliable measure...

Correcting respirable photometric particulate measurements using a gravimetric sampling method

According to the National Environmental Management: Air Quality Act of 2004 people have the right to clean air and a healthy environment. Particulate matter (PM) emissions pose a significant health threat. Both indoor and ambient air pollution contribute to the burden of disease associated with poor air quality. This is particularly true within the South African setting where low income households make use of different solid fuels for heating and cooking purposes resulting in high levels of PM emissions. This paper focuses on the evaluation mass concentration measurements recorded by continuous photometric PM instruments within KwaDela, a low income settlement in Mpumalanga located on the South African Highveld. Thus, obtaining a photometric calibration factor for both the DustTrak Model 8530 and the SidePak AM510. Sampling took place during August 2014 for a period of seven days. The photometric and gravimetric instruments were collocated within the indoor environment of selected households. These instruments were all fitted with 10mm Dorr-Oliver Cyclone inlets to obtain the respirable (PM4) cut-point. The study found that both instruments tend to overestimate the indoor particulate mass concentrations when compared to the reference gravimetric method. The estimated photometric calibration factors for the DustTrak Model 8530 and SidePak AM510 are 0.14 (95%Cl: 0.09, 0.15) and 0.24 (95%Cl: 0.16, 0.30) respectively. The overestimation of the photometric measurements is rather significant. It is therefore important that the correction factors are applied to data collected in indoor environments prone to the combustion of solid fuels. The correction factors obtained from this and other studies vary as a result of the environment (ambient, indoor etc.) as well as the aerosol size fraction and the origin thereof. Thus, it is important to considered site specific calibration factors when implementing these photometric light-scattering instruments.

Prediction of instantaneous exhaust particulate concentrations

Gaseous emissions usually are available on a continuous basis from diesel vehicle emissions testing, but particulate matter (PM) emissions are usually only available as a single mass number over a test cycle. Continuous PM emissions are valuable for conformity and hot-spot analyses to support roadway project design and to determine the engine-out PM for after treatment retrofit projects. For diesel vehicles without particulate filters one may argue that carbon monoxide and hydrocarbon emissions may be correlated with the elemental carbon and organic carbon fractions in their exhaust. Methodologies for predicting instantaneous PM production rate from heavy-duty diesel vehicles were developed. These methodologies used combinations of instantaneous and idle carbon monoxide and hydrocarbon production rates with integrated PM production to predict instantaneous PM production rates for each specific vehicle. Comparison of results produced by these methodologies with measured PM productions rates is presented. Apportioning total PM mass over a period of vehicle activity using gaseous emissions is shown to be reliable.

Concentration of Indoor Particulate Matter and Carbon Monoxide among Households Using Biomass Fuels in Sarlahi, Nepal: the Effect of Cooking, Fuel Type, and Season

Concentration of Indoor Particulate Matter and Carbon Monoxide among Households Using Biomass Fuels in Sarlahi, Nepal: the Effect of Cooking, Fuel Type, and SeasonAbstract Number:3018 Patrick N Breysse*, James M Tielsch, Chen Chen, Joanne Katz, Scott L Zeger, Frank C Curriero, Subarna K Khatry, Laxman Shrestha, and Steven C LeClerq Patrick N Breysse* Search for more papers by this author , James M Tielsch Search for more papers by this author , Chen Chen Search for more papers by this author , Joanne Katz Search for more papers by this author , Scott L Zeger Search for more papers by this author , Frank C Curriero Search for more papers by this author , Subarna K Khatry Search for more papers by this author , Laxman Shrestha Search for more papers by this author , and Steven C LeClerq Search for more papers by this author AbstractPurpose: A large (n=3129) cookstove intervention trial is underway in the Sarlahi district of Nepal. The purpose of this paper is to summarize baseline 24-hour indoor particulate matter (PM) and carbon monoxide (CO) concentrations.Methods: 24-hour continuous PM and CO samples were collected in 2871 households (92%) from March 2010 to September 2011. PM was measured passively using the pDR-1000. PM concentration values were humidity corrected and adjusted to PM2.5 equivalents using a subset of co-located gravimetric samples. CO was measured using a LASCAR data-logging CO monitor. Cooking events were identified based on empirical assessment of temporal trends in PM concentration. Regression models were utilized to evaluate the association of PM and CO concentration with cooking, fuel type, season, and household characteristics.Results: The median of daily average PM concentrations was 1334?g/m^3^ (IQR, 1279), median 95th percentile of PM concentration was 4625?g/m^3^ (IQR, 4878), and mean of time above 500?g/m^3^ was 11.04h (95% CI, 10.86—11.22). The median of daily average CO concentrations was 8.2ppm (IQR, 9.2), and median 95th percentile of CO concentration was 36.5ppm (IQR, 56.5). The mean cooking time per day was 5.63h (95% CI, 5.55—5.72), and median difference of average PM concentration between cooking and non-cooking time was 3140?g/m^3^ (IQR, 4093). All PM concentration metrics peaked in the dry season and dipped in the rainy season, while no significant seasonal variation was identified in CO concentration. PM concentration and CO concentration were weakly associated, which varied by fuel type and season. Among major biomass fuels used in Nepal, wood generated the lowest PM concentrations, and crop waste generated the lowest CO concentrations.Conclusions: Baseline PM and CO concentrations are extremely high in the Nepal cookstove trial study homes. PM demonstrated significant variability associated with season and fuel type.

Investigation of time-resolved atmospheric conditions and indoor/outdoor particulate matter concentrations in homes with gas and biomass cook stoves in Nogales, Sonora, Mexico

This paper reports findings from a case study designed to investigate indoor and outdoor air quality in homes near the United States–Mexico border. During the field study, size-resolved continuous particulate matter (PM) concentrations were measured in six homes, while outdoor PM was simultaneously monitored at the same location in Nogales, Sonora, Mexico, during March 14–30, 2009. The purpose of the experiment was to compare PM in homes using different fuels for cooking, gas versus biomass, and to obtain a spatial distribution of outdoor PM in a region where local sources vary significantly (e.g., highway, border crossing, unpaved roads, industry). Continuous PM data were collected every 6 seconds using a valve switching system to sample indoor and outdoor air at each home location. This paper presents the indoor PM data from each home, including the relationship between indoor and outdoor PM. The meteorological conditions associated with elevated ambient PM events in the region are also discussed. Results indicate that indoor air pollution has a strong dependence on cooking fuel, with gas stoves having hourly averaged median PM3 concentrations in the range of 134 to 157 μg m−3 and biomass stoves 163 to 504 μg m−3. Outdoor PM also indicates a large spatial heterogeneity due to the presence of microscale sources and meteorological influences (median PM3: 130 to 770 μg m−3). The former is evident in the median and range of daytime PM values (median PM3: 250 μg m−3, maximum: 9411 μg m−3), while the meteorological influences appear to be dominant during nighttime periods (median PM3: 251 μg m−3, maximum: 10,846 μg m−3). The atmospheric stability is quantified for three nighttime temperature inversion episodes, which were associated with an order of magnitude increase in PM10 at the regulatory monitor in Nogales, AZ (maximum increase: 12 to 474 μg m−3).Implications:Regulatory air quality standards are based on outdoor ambient air measurements. However, a large fraction of time is typically spent indoors where a variety of activities including cooking, heating, tobacco smoking, and cleaning can lead to elevated PM concentrations. This study investigates the influence of meteorology, outdoor PM, and indoor activities on indoor air pollution (IAP) levels in the United States–Mexico border region. Results indicate that cooking fuel type and meteorology greatly influence the IAP in homes, with biomass fuel use causing the largest increase in PM concentration.

Identification of Particulate Matter Sources on an Hourly Time-Scale in a Wood Burning Community

Particulate matter (PM) sources at two different sites in a rural town in New Zealand were investigated on an hourly time-scale. Streaker samplers were used to collect hourly, size-segregated PM(10-2.5) and PM(2.5) samples that were analyzed for elemental content using ion beam analysis techniques. Black carbon concentrations were determined using light reflection and PM(10) concentrations were recorded using colocated continuous PM monitors. PM(10) concentrations at both sites displayed a diurnal pattern, with hourly PM(10) concentration maxima in the evening (7 pm-midnight) and in the morning (7-9 am). One of the monitoring sites experienced consistently higher average PM(10) concentrations during every hour and analysis indicated that katabatic flows across the urban area contributed to the increased concentrations observed. Source apportionment using positive matrix factorization on the hourly data revealed four primary PM(10) sources for each site: biomass burning, motor vehicles, marine aerosol and crustal matter. Biomass burning was the most dominant source at both sites and was responsible for both the evening and morning PM(10) concentration peaks. The use of elemental speciation combined with PM(10) concentrations for source apportionment on an hourly time-scale has never been reported and provides unique and useful information on PM sources for air quality management.