PM10 Monitoring Research Articles

Field Comparison of TSI DustTrak versus TEOM in Two Poultry Houses

Abstract. The TSI DustTrak monitor has been used for particulate matter (PM) monitoring at various animal facilities. The instrument determines PM concentrations based on the principle of light scattering. Several assumptions (e.g., particle size, refractive index, and density) are imposed during the calibration process; however, they may not apply to PM emanating from agricultural settings. In this study, PM10 monitoring was conducted at a broiler house and a layer breeding house with four collocated instruments: three DustTrak monitors and one tapered element oscillating microbalance (TEOM). Being a federal equivalent method (FEM) for PM10 monitoring, TEOM was selected here as a transfer standard for assessing the field performance of DustTrak. Results revealed a good linearity between DustTrak and TEOM PM10 readings (R2 =0.92 and 0.85 in the broiler and layer breeding houses, respectively). However, DustTrak significantly underestimated PM10 concentrations in both houses. To correct for the monitoring bias by DustTrak, an average correction factor was derived from correlation analysis that characterized the ratio of DustTrak’s PM10 response to TEOM’s. The factor was calculated as 0.267 for the broiler house and 0.244 for the layer breeding house. Mie scattering simulation was performed to further verify the derived correction factors. A factor of 0.204 was estimated from the simulation, and it accorded well with experimental results. A dependence of the correction factor on PM10 concentration was noted in both poultry houses, indicating the feasibility of developing a concentration-dependent correction factor for future monitoring efforts. Such a relationship could also be explained by Mie scattering. This study is expected to facilitate a better understanding of the limitations and perspectives of the TSI DustTrak and other light scattering PM monitors for agricultural air quality research. Keywords: DustTrak, Mass concentration, Mie scattering, PM10, Poultry, TEOM.

Design and Development of a Low-Cost, Portable Monitoring Device for Indoor Environment Quality

This article describes the design and development of a low-cost, portable monitoring system for indoor environment quality (IEQ). IEQ is a holistic concept that encompasses elements of indoor air quality (IAQ), indoor lighting quality (ILQ), acoustic comfort, and thermal comfort (temperature and relative humidity). The unit is intended for the monitoring of temperature, humidity, PM2.5, PM10, total VOCs (×3), CO2, CO, illuminance, and sound levels. Experiments were conducted in various environments, including a typical indoor working environment and outdoor pollution, to evaluate the unit’s potential to monitor IEQ parameters. The developed system was successfully able to monitor parameter variations, based on specific events. A custom IEQ index was devised to rate the parameter readings with a simple scoring system to calculate an overall IEQ percentage. The advantages of the proposed system, with respect to commercial units, is associated with better customisation and flexibility to implement a variety of low-cost sensors. Moreover, low-cost sensor modules reduce the overall cost to provide a comprehensive, portable, and real-time monitoring solution. This development facilities researchers and interested enthusiasts to become engaged and proactive in participating in the study, management, and improvement of IEQ.

Hazardous aerosol emissions during agriculture biomass burning season in Son La and Ba Vi regions, Vietnam

Major national emission sources are assessed by characterization of smoke pollution arising due to traditional agriculture, domestic, and cooking activities in the regions of the biggest biomass burning. Measurement campaigns were carried in Son La and Ba Vi regions, Vietnam, during the dry seasons of 2013 and 2015-2016. PM and BC monitoring, aerosol sampling, chemical speciation were conducted to evaluate ambient smoke level, to relate the characteristics of local on-field emissions to regional aerosols, and to identify the dangerous components of smoke composition. The regions Son La and Ba Vi in February-June faced severe levels of air pollution, with critical PM2.5 and PM10 concentrations up to 130 and 167 µg/m3, respectively, significantly exceeding the air quality standards. A wide range of PM mass concentrations was categorized according to the smoke level, supported by the evolution of carbon (OC, EC) fractions as well as ionic species and molecular markers. The level of PM and BC concentrations was seen to be dependent on factors such as weather conditions and precipitation. Non-acid carbonyls, carboxylates, and aliphatic carbon compounds were evolved with increasing smoke intensity, together with carbonates in coarse size fractions, indicating a large impact of smoke emissions and soil lifted up by the intense fires. On-field emissions in both smoldering and flaming phases were assessed in near-source measurements.

Long-Term Coarse Particulate Matter Exposure Is Associated with Asthma among Children in Medicaid.

Short- and long-term fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter [PM2.5]) pollution is associated with asthma development and morbidity, but there are few data on the effects of long-term exposure to coarse PM (PM10-2.5) on respiratory health. To understand the relationship between long-term fine and coarse PM exposure and asthma prevalence and morbidity among children. A semiparametric regression model that incorporated PM2.5 and PM10 monitor data and geographic characteristics was developed to predict 2-year average PM2.5 and PM10-2.5 exposure during the period 2009 to 2010 at the zip-code tabulation area level. Data from 7,810,025 children aged 5 to 20 years enrolled in Medicaid from 2009 to 2010 were used in a log-linear regression model with predicted PM levels to estimate the association between PM exposure and asthma prevalence and morbidity, adjusting for race/ethnicity, sex, age, area-level urbanicity, poverty, education, and unmeasured spatial confounding. Exposure to coarse PM was associated with increased asthma diagnosis prevalence (rate ratio [RR] for 1-μg/m3 increase in coarse PM level, 1.006; 95% confidence interval [CI], 1.001-1.011), hospitalizations (RR, 1.023; 95% CI, 1.003-1.042), and emergency department visits (RR, 1.017; 95% CI, 1.001-1.033) when adjusting for fine PM. Fine PM exposure was more strongly associated with increased asthma prevalence and morbidity than coarse PM. The estimates remained elevated across different levels of spatial confounding adjustment. Among children enrolled in Medicaid, exposure to higher average coarse PM levels is associated with increased asthma prevalence and morbidity. These results suggest the need for direct monitoring of coarse PM and reconsideration of limits on long-term average coarse PM pollution levels.

An advanced technique for outdoor insulation pollution mapping in the israel electric company power grid

The paper presents the IECo (Israel Electric Co) long-term environmental study aimed at development of Digital Dust Sedimentation Model which provides an Outdoor Insulation Pollution Mapping for Local Grid. The Concept of the study is based on the Authors' idea on strong correlation between IEC 60721 Dust Sedimentation Index vs. IEC TC 60815 Site Pollution Severity Indices within considered geographic domain. The developed Pollution Maps have been validated vs. long-term ESDD-NSDD field-measurements and continuous monitoring of PM 10 fraction with correlation factors r=0.830 and r=0.697 respectively. To prove the model reliability the calibration was done for different geographic locations in different time intervals. The first-time developed innovative technology is expected to provide cost benefits with respect to dimensioning and maintenance of outdoor insulators, PV-Plants, and other pollution-sensitive local installations.

SYNCOPE: PACING VERSUS RECORDING IN THE LATER YEARS. A RANDOMIZED PRAGMATIC CLINICAL TRIAL OF STRATEGIES OF PERMANENT PACEMAKER VERSUS IMPLANTABLE CARDIAC MONITOR IN OLDER PATIENTS WITH SYNCOPE

Syncope with bifascicular block may be caused by intermittent complete heart block, but competing diagnoses may co-exist. We tested the hypothesis that in patients with syncope and bifascicular heart block a strategy of empiric permanent pacing (PM) reduces major adverse events more effectively than acting on the results of an implantable cardiac monitor (ICM). 115 patients >50.0 y old with bifascicular block, preserved left ventricular function, and ≥1 syncope in the preceding year were randomized to receive a PM or ICM in a prospective, open label, pragmatic randomized trial. The primary outcome measure was a composite of Major Adverse Study-Related Events (MASRE) over ≥2 years up to study completion. MASRE included death, syncope, symptomatic bradycardia, asymptomatic actionable bradycardia, and device complications. Enrollment ended May 22, 2015 with follow-up ending May 22, 2017. There were 56 and 59 subjects randomized to receive a PM or implantable cardiac monitor ICM in 23 sites (17 Canadian). The PM and ICM groups were similar in age (74±9 vs 77±9 y), sex (20 vs 14 female), lifetime syncopes (medians 2), syncope in prior year (medians 2), duration of symptoms (medians 1 year), no prodrome (40/56 vs 39/59), and baseline systolic BP (137±20 vs 133±21 mmHg). 40 pts had left bundle branch block and 75 had right bundle branch block and a left hemiblock. Patients were followed for median 30 months and 21 exited the study (death 8, withdrew consent after 2 years 6, cancer 4, dementia 3). PM effectively prevented the primary outcome with end study MASRE-free survivals in PM (63%) and ICM (22%) group (figure, left panel, p < 0.001 Wilcoxon). Proportions of pts with syncope were similar in PM and ICM groups (figure, middle panel, 27 vs 31%, p=0.50, Wilcoxon). Other outcomes were far higher in ICM than PM pts: asymptomatic actionable heart block (40% vs 0%, p < 0.001), and symptomatic bradycardia (40% vs 0%, p < 0.001). Fully 35/59 ICM pts (59%) crossed over to PM. There were 5 pacemaker complications requiring reintervention. In on treatment analysis syncope-free survival was far higher in the PM group (80% vs 50%, figure, right panel, p=0.002, Wilcoxon). Syncope recurs frequently in elderly pts with few but recent syncopal spells and bifascicular block. Permanent pacing compared to ICM is a preferred strategy due to high crossover rates from ICM to PM, and on-treatment efficacy in prevention of syncope by PM.

Seasonal ambient particulate matter and population health outcomes among communities impacted by road dust in British Columbia, Canada

ABSTRACTIn recent years, many air quality monitoring programs have favored measurement of particles less than 2.5 µm (PM2.5) over particles less than 10 µm (PM10) in light of evidence that health impacts are mostly from the fine fraction. However, the coarse fraction (PM10-2.5) may have independent health impacts that support continued measurement of PM10 in some areas, such as those affected by road dust. The objective of this study was to evaluate the associations between different measures of daily PM exposure and two daily indicators of population health in seven communities in British Columbia, Canada, where road dust is an ongoing concern. The measures of exposure were PM10, PM2.5, PM10-2.5, PM2.5 adjusted for PM10-2.5, and PM10-2.5 adjusted for PM2.5. The indicators of population health were dispensations of the respiratory reliever medication salbutamol sulfate and nonaccidental mortality. This study followed a time-series design using Poisson regression over a 2003–2015 study period, with analyses stratified by three seasons: residential woodsmoke in winter; road dust in spring; and wildfire smoke in summer. A random-effects meta-analysis was conducted to establish a pooled estimate. Overall, an interquartile range increase in daily PM10-2.5 was associated with a 3.6% [1.6, 5.6] increase in nonaccidental mortality during the road dust season, which was reduced to 3.1% [0.8, 5.4] after adjustment for PM2.5. The adjusted coarse fraction had no effect on salbutamol dispensations in any season. However, an interquartile range increase in PM2.5 was associated with a 2.7% [2.0, 3.4] increase in dispensations during the wildfire season. These analyses suggest different impacts of different PM fractions by season, with a robust association between the coarse fraction and nonaccidental mortality in communities and periods affected by road dust. We recommend that PM10 monitoring networks be maintained in these communities to provide feedback for future dust mitigation programs.Implications: There was a significant association between daily concentrations of the coarse fraction and nonaccidental mortality during the road dust season, even after adjustment for the fine fraction. The acute and chronic health effects associated with exposure to the coarse fraction remain unclear, which supports the maintenance of PM10 monitoring networks to allow for further research in communities affected by sources such as road dust.

Effectiveness of an array of porous fences to reduce sand flux: Oceano Dunes, Oceano CA

Arrays of porous fences, ≈12 ha in 2014 and ≈ 15 ha in 2015, were constructed in the Oceano Dunes State Vehicular Recreation Area to evaluate their effectiveness to reduce sand flux and affect local PM10 dust concentrations. The 1.22 m high, ≥244 m long, ≈50% porous fences were placed 10 fence heights apart in 2014 and 7 in 2015. Measurements of sand flux through the arrays indicated that it diminished exponentially with increasing distance, reaching equilibrium at ≈93 fence heights for the 10 h spacing and ≈27 fence heights for the 7 h spacing. Fences spaced 7 h apart reduced sand flux for the entire area by 78%, and 86% for the area ≥27 h. Fences spaced at 10 h reduced sand flux for the entire area by 40%, and 56% for the area ≥93 h. PM10 monitoring upwind and downwind of the array and in the absence of the array in 2015, indicated that the downwind PM10 concentration was less than the upwind for the fence array, whereas in the absence of fences PM10 increased in the downwind direction over the same fetch distance, suggesting the presence of the fences was reducing the flux of PM10 from within the fence array.

Acute stress shifts the balance between controlled and automatic processes in prospective memory

In everyday life we frequently rely on our abilities to postpone intentions until later occasions (prospective memory; PM) and to deactivate completed intentions even in stressful situations. Yet, little is known about the effects of acute stress on these abilities. In the present work we investigated the impact of acute stress on PM functioning under high task demands. (1) Different from previous studies, in which intention deactivation required mostly low processing demands, we used salient focal PM cues to induce high processing demands during intention-deactivation phases. (2) We systematically manipulated PM-monitoring demands in a nonfocal PM task that required participants to monitor for either one or six specific syllables that could occur in ongoing-task words. Eighty participants underwent the Trier Social Stress Test, a standardized stress induction protocol, or a standardized control situation, before performing a computerized PM task. Our primary interests were whether PM performance, PM-monitoring costs, aftereffects of completed intentions and/or commission-error risk would differ between stressed and non-stressed individuals and whether these effects would differ under varying task demands.Results revealed that PM performance and aftereffects of completed intentions during subsequent performance were not affected by acute stress induction, replicating previous findings. Under high demands on intention deactivation (focal condition), however, acute stress produced a nominal increase in erroneous PM responses after intention completion (commission errors). Most importantly, under high demands on PM monitoring (nonfocal condition), acute stress led to a substantial reduction in PM-monitoring costs. These findings support ideas of selective and demand-dependent effects of acute stress on cognitive functioning. Under high task demands, acute stress might induce a shift in processing strategy towards resource-saving behavior, which seems to increase the efficiency of PM performance (reduced monitoring costs), but might increase initial susceptibility to automatic response activation after intention completion.

Estimating Particulate Matter using satellite based aerosol optical depth and meteorological variables in Malaysia

The insufficient number of ground-based stations for measuring Particulate Matter <10μm (PM10) in the developing countries hinders PM10 monitoring at a regional scale. The present study aims to develop empirical models for PM10 estimation from space over Malaysia using aerosol optical depth (AOD550) and meteorological (surface temperature, relative humidity and atmospheric stability) data (retrieved or estimated) from Moderate Resolution Imaging Spectroradiometer (MODIS) during the period 2007–2011. The MODIS retrievals are found to be satisfactorily correlated with ground-based measurements at Malaysia. Multiple linear regressions (MLR) and Artificial Neural Network (ANN) techniques are utilized to develop the empirical models for PM10 estimation. The model development and training are performed via comparison with measured PM10 at 29 stations over Malaysia and reveal that the ANN provides slightly higher accuracy with R2=0.71 and RMSE=11.61μgm−3 compared to the MLR method (R2=0.66 and RMSE=12.39μgm−3). Stepwise regression analysis performed on the MLR method reveals that the MODIS AOD550 is the most important parameter for PM10 estimations (R2=0.59 and RMSE=13.61μgm−3); however, the inclusion of the meteorological parameters in the MLR increases the accuracy of the retrievals (R2=0.66, RMSE=12.39μgm−3). The estimated PM10 concentrations are finally validated against surface measurements at 16 stations resulting in similar performance from the ANN model (R2=0.58, RMSE=10.16μgm−3) and MLR technique (R2=0.56, RMSE=10.58μgm−3). The significant accuracy that has been attained in PM10 estimations from space allows us to assess the pollution levels in Malaysia and map the PM10 distribution at large spatial and temporal scales.

Based on Light Scattering Method Online Monitoring and Evaluation of PM10 in Public Places from Qinhuangdao, China

Based on Light Scattering Method Online Monitoring and Evaluation of PM10 in Public Places from Qinhuangdao, China

Re-construction of the shut-down PM10 monitoring stations for the reliable assessment of PM10 in Berlin using fuzzy modelling and data transformation.

A dense monitoring network is vital for the reliable assessment of PM10 in different parts of an urban area. In this study, a new idea is employed for the re-construction of the 20 shut-down PM10 monitoring stations of Berlin. It endeavours to find the non-linear relationship between the hourly PM10 concentration of both the still operating and the shut-down PM10 monitoring stations by using a fuzzy modelling technique, called modified active learning method (MALM). In addition, the simulations were performed by using not only raw PM10 databases but also log-transformed PM10 databases for skewness reduction. According to the results of hourly PM10 simulation (root mean square error about 13.0μg/m3, correlation coefficient 0.88), the shut-down stations have been appropriately simulated and the idea of dense monitoring network development by the re-construction of the shut-down stations was realised. The results of simulations using raw and log-transformed databases showed that data transformation has no significant effect on the performance of MALM in the simulation of shut-down PM10 stations. By the combination of the 11 still operating stations and the 20 re-constructed stations, a dense monitoring network was generated for Berlin and was utilised for the calculation of the reliable monthly and mean annual PM10 concentration for five different PM10 zones in Berlin (the suburban-background, urban-background, urban-traffic, rural-background and suburban-traffic areas). The results showed that the mean annual concentration of PM10 at the five zones increased by about 13.0% in 2014 (26.3μg/m3) in comparison with 2013 (23.3μg/m3). Furthermore, the mean annual concentration of PM10 in the traffic lanes of the suburban (2013 25.0μg/m3, 2014 26.9μg/m3) and urban (2013 27.7μg/m3, 2014 31.3μg/m3) areas is about 14 and 20% higher than the PM10 concentration of suburban-background (2013 21.3μg/m3, 2014 24.5μg/m3) and urban-background (2013 23.0μg/m3, 2014 26.1μg/m3) areas, respectively.

Modeling spatiotemporal distribution of PM10 using HJ-1 CCD data in Luoyang, China

Previous studies have proved that the statistical models between satellite-retrieved aerosol optical depth (AOD) and ground-level PM10 provide a feasible and effective way to obtain the extensive and continuous spatial distribution of ground-level PM10. The two-year annual mean PM10 was 119.9 ± 66.5 μg/m3 from 2014 to 2015, which significantly exceeded the annual WHO IT-1 standard for PM10 (70 μg/m3), and the mean AOD was 0.56 ± 0.21 in Luoyang. Statistical models were proposed using a combination of HJ-1 (Environment Satellite 1) CCD (charge-coupled device) AOD and PM10 acquired at monitoring sites. The fitting analysis of PM10 and AOD shows that PM10 agrees well with AOD, and the linear regression model is the most accurate one. By the land-use function analysis of PM10 hotspots using Google Earth, it is apparent that the prevalence of industrial or bare soil areas is the key factor in determining anthropogenic pollutant emissions. In view of the small HJ-1 data available for analyzing and the limitation of dark target algorithm in the season with sparse vegetation cover, further investigation should be conducted for a more accurate understanding of the PM10 monitoring. Despite the limitations of this work, the results prove the feasibility of retrieving remote sensing images for monitoring regional aerosol pollution, together with ground-level data. The combination of satellite images, ground monitoring and Google earth can help to better understand the spatial distributions and sources of PM on a regional scale.

Evaluation of new low-cost particle monitors for PM2.5 concentrations measurements

Sixty-six, new, low-cost Speck monitors were collocated with a Grimm 1.109 particle spectrometer and CO loggers during one indoor and two outdoor monitoring campaigns to assess the ability of the monitors to measure the PM concentrations under real use conditions. The limit of detection of the monitors was calculated, and the monitors’ bias and precision, as well as the results’ reproducibility, were determined. Correlation coefficients of 0.3 and 0.2 observed between the Speck units and the Grimm instrument during indoor and outdoor measurements were increased by separating the data into sets affected by different sources. When the ambient data were divided into combustion and non-combustion aerosol, the mean r2 increased to 0.5 and 0.4 for indoor and outdoor combustion periods data, respectively. Also, averaging the data to improve the signal to noise ratio increases the correlation for low PM concentrations. For outdoor data, the correlation increased to 0.5 when the data were averaged to hourly averages. Between the Specks, the correlation was >0.9 indoors, showing a high degree of reproducibility among the results. The limit of detection was calculated using the method of Wallace et al. (2011) and was found to be 10µgm−3 at a 99% confidence level for 1-minute data. The mean bias values showed a PM overestimation of 200% for indoor data, and 500% for outdoor data relative to the Grimm values. However, these values are influenced by the low measured PM concentrations. The RMSE of Specks was about 10µgm−3 and the concentrations were often about this value. The overall precision was 8.8±1.7% indoors and 12.2±6.2% outdoors, suggesting its independence from changing ambient conditions. The Speck monitors may be suitable for use in indoor and outdoor PM monitoring programs, depending on the required performance to meet the goals of the study. The instrument has a large bias at low concentrations, making it unsuitable for background measurements or for measurements in clean environments. Even at concentrations over the LOD, it is necessary to assess the bias for expected particle sources before any instrument deployment.

Comparison of electrostatic charge and beta attenuation mass monitors for continuous airborne PM10 monitoring under field conditions

An electrostatic PM10 mass monitor (EPMM) used for wireless continuous airborne particulate matter monitoring was developed and evaluated in our previous work. However, differences in measured PM10 mass concentrations between the electrostatic charge and the beta ray attenuation methods due to the frequent occurrence of high humidity and temperature in the ambient air in Thailand’s have not been extensively studied in our previous work; and in the literature, it would be necessary to compare the output of the EPMM against the beta ray attenuation mass monitor. In this study, we evaluated the performance of the EPMM simultaneously with a commercially available FH62C14 Beta gauge continuous ambient particulate monitor, Thermo Fisher Scientific Inc., for PM10 measurements at ambient condition in the field. The measurements were made at Yupparaj Wittayalai School, Si Phum, Mueang, Chiang Mai, Thailand from November 16-23, 2015. They showed that the averages of PM10 mass concentrations measured by the EPMM linearly correlate very well with the PM10 mass concentrations measured by the FH62C14. The slopes were 0.9620 and 1.0649 for 1 and 24-hour, respectively, and R2 of 0.8634 and 0.9889 for 1 and 24-hour, respectively. Finally, this comparison proved to be particularly useful in the refinement and design of the EPMM.

Size distribution, directional source contributions and pollution status of PM from Chengdu, China during a long-term sampling campaign

Long-term and synchronous monitoring of PM10 and PM2.5 was conducted in Chengdu in China from 2007 to 2013. The levels, variations, compositions and size distributions were investigated. The sources were quantified by two-way and three-way receptor models (PMF2, ME2-2way and ME2-3way). Consistent results were found: the primary source categories contributed 63.4% (PMF2), 64.8% (ME2-2way) and 66.8% (ME2-3way) to PM10, and contributed 60.9% (PMF2), 65.5% (ME2-2way) and 61.0% (ME2-3way) to PM2.5. Secondary sources contributed 31.8% (PMF2), 32.9% (ME2-2way) and 31.7% (ME2-3way) to PM10, and 35.0% (PMF2), 33.8% (ME2-2way) and 36.0% (ME2-3way) to PM2.5. The size distribution of source categories was estimated better by the ME2-3way method. The three-way model can simultaneously consider chemical species, temporal variability and PM sizes, while a two-way model independently computes datasets of different sizes. A method called source directional apportionment (SDA) was employed to quantify the contributions from various directions for each source category. Crustal dust from east-north-east (ENE) contributed the highest to both PM10 (12.7%) and PM2.5 (9.7%) in Chengdu, followed by the crustal dust from south-east (SE) for PM10 (9.8%) and secondary nitrate & secondary organic carbon from ENE for PM2.5 (9.6%). Source contributions from different directions are associated with meteorological conditions, source locations and emission patterns during the sampling period. These findings and methods provide useful tools to better understand PM pollution status and to develop effective pollution control strategies.

National-Scale Estimates of Ground-Level PM2.5 Concentration in China Using Geographically Weighted Regression Based on 3 km Resolution MODIS AOD

High spatial resolution estimating of exposure to particulate matter 2.5 (PM2.5) is currently very limited in China. This study uses the newly released nationwide, hourly PM2.5 concentrations to create a nationwide, geographically weighted regression (GWR) model to estimate ground-level PM2.5 concentrations in China. A3 km resolution aerosol optical depth (AOD) product from MODIS is used as the primary predictor. Fire emissions detected by MODIS fire count were considered in the model development process. Additionally, meteorological features were used as covariates in the model to improve the estimation of ground-level PM2.5 concentrations. The model performed well and explained 81% of the daily PM2.5 concentration variations in model predictions, and the cross validations R2 is 0.79. The cross-validated root mean squared error (RMSE) of the model was 18.6 μg/m3.Annual PM2.5 concentrations retrieved by the MODIS 3 km AOD product indicated that most of the residential community areas exceeded the new annual Chinese PM2.5 National Standard level 2. Estimated high-resolution national-scale daily PM2.5 maps are useful to identify severe air pollution episodes and determine health risk assessments. These results suggest that this approach is useful for estimating large-scale ground-level PM2.5 distributions, especially for regions without PM monitoring sites.

A comparative study of human exposures to household air pollution from commonly used cookstoves in Sri Lanka

Solid fuel burning cookstoves are a major source of household air pollution (HAP) and a significant environmental health risk in Sri Lanka. We report results of the first field study in Sri Lanka to include direct measurements of both real-time indoor concentrations and personal exposures of fine particulate matter (PM2.5 ) in households using the two most common stove types in Sri Lanka. A purposive sample of 53 households was selected in the rural community of Kopiwatta in central Sri Lanka, roughly balanced for stove type (traditional or improved 'Anagi') and ventilation (chimney present or absent). At each household, 48-h continuous real-time measurements of indoor kitchen PM2.5 and personal (primary cook) PM2.5 concentrations were measured using the RTI MicroPEM™ personal exposure monitor. Questionnaires were used to collect data related to household demographics, characteristics, and self-reported health symptoms. All primary cooks were female and of an average age of 47years, with 66% having completed primary education. Median income was slightly over half the national median monthly income. Use of Anagi stoves was positively associated with a higher education level of the primary cook (P=0.026), although not associated with household income (P=0.18). The MicroPEM monitors were well-received by participants, and this study's valid data capture rate exceeded 97%. Participant wearing compliance during waking hours was on average 87.2% on Day 1 and 83.3% on Day 2. Periods of non-compliance occurred solely during non-cooking times. The measured median 48-h average indoor PM2.5 concentration for householdswith Anagi stoves was 64μg/m3 if a chimney was present and 181μg/m3 if not. For households using traditional stoves, these values were 70μg/m3 if a chimney was present and 371μg/m3 if not. Overall, measured indoor PM2.5 concentrations ranged from a minimum of 33μg/m3 to a maximum of 940μg/m3 , while personal exposure concentrations ranged from 34 to 522μg/m3 . Linear mixed effects modeling of the dependence of indoor concentrations on stove type and presence or absence of chimney showed a significant chimney effect (65% reduction; P<0.001) and an almost significant stove effect (24% reduction; P=0.054). Primary cooks in households without chimneys were exposed to substantially higher levels of HAP than those in households with chimneys, while exposures in households with traditional stoves were moderately higher than those with improved Anagi stoves. As expected, simultaneously measuring both indoor concentrations and personal exposure levels indicate significant exposure misclassification bias will likely result from the use of a stationary monitor as a proxy for personal exposure. While personal exposure monitoring is more complex and expensive than deploying simple stationary devices, the value an active personal PM monitor like the MicroPEM adds to an exposure study should be considered in future study designs.

Air quality assessment along urban transport corridor in megacity

Urban traffic emission is one of the grievous problems faced by people in urban centres of developing countries like India. Inspite of bad air quality, people are forced to live in air-polluted areas of megacities like Delhi. The present study is an effort to analyse the air quality of some selected areas along major urban transport corridors in Delhi. On the basis of land-use pattern, five locations, i.e., Rithala, Pitampura, Kashmiri Gate, Jhilmil, and Panchsheel Enclave were selected to conduct the research study. The study included the monitoring of CO, NOx, SO2 and PM at all the identified locations for 12 hrs (8:00 to 20:00). The monitored data of each location was used to estimate the composite air quality index (CAQI). The highest value of CAQI was observed at Jhilmil (140) followed by Kashmiri Gate (127), Pitampura (109), Rithala (104) and Panchsheel Encalve (103). Upon comparing the CAQI of all the selected locations with the rating scale of air quality index, it was found that all the selected locations were under severe air pollution condition, a clear representative of the unhealthy condition of people residing in these particular areas.

Discontinuous and Continuous Indoor Air Quality Monitoring in Homes with Fireplaces or Wood Stoves as Heating System.

Around 50% of the world’s population, particularly in developing countries, uses biomass as one of the most common fuels. Biomass combustion releases a considerable amount of various incomplete combustion products, including particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs). The paper presents the results of Indoor Air Quality (IAQ) measurements in six houses equipped with wood burning stoves or fireplaces as heating systems. The houses were monitored for 48-h periods in order to collect PM10 samples and measure PAH concentrations. The average, the maximum and the lowest values of the 12-h PM10 concentration were 68.6 μg/m3, 350.7 μg/m3 and 16.8 μg/m3 respectively. The average benzo[a]pyrene 12-h concentration was 9.4 ng/m3, while the maximum and the minimum values were 24.0 ng/m3 and 1.5 ng/m3, respectively. Continuous monitoring of PM10, PAHs, Ultra Fine Particle (UFP) and Total Volatile Organic Compounds (TVOC) was performed in order to study the progress of pollution phenomena due to biomass burning, their trends and contributions to IAQ. The results show a great heterogeneity of impacts on IAQ in terms of magnitude and behavior of the considered pollutants’ concentrations. This variability is determined by not only different combustion technologies or biomass quality, but overall by different ignition mode, feeding and flame management, which can also be different for the same house. Moreover, room dimensions and ventilation were significant factors for pollution dispersion. The increase of PM10, UFP and PAH concentrations, during lighting, was always detected and relevant. Continuous monitoring allowed singling out contributions of other domestic sources of considered pollutants such as cooking and cigarettes. Cooking contribution produced an impact on IAQ in same cases higher than that of the biomass heating system.