Field performance of a nephelometer in rural kitchens: effects of high humidity excursions and correlations to gravimetric analyses

Performance assessment of NOVA SDS011 low-cost PM sensor in various microenvironments

Over the last 10 years, as a possible alternative to the conventional approach to air quality monitoring, real-time monitoring systems that use low-cost sensors and sensor platforms have been frequently applied. Generally, the long-term characteristics of low-cost PM sensors and monitoring have not been thoroughly documented except for a few widely used sensors and monitors. This article addresses the laboratory and field validation of three low-cost PM monitors of the same type that use the NOVA SDS011 PM sensor module over a 1-year period. In outdoor environments, we co-located low-cost PM monitors with GRIMM EDM180 monitors at the National Air Quality Monitoring stations. In indoor environments, we co-located them with a Turnkey Osiris PM monitor. Several performance aspects of the PM monitors were examined: operational data coverage, linearity of response, accuracy, precision, and inter-sensor variability. The obtained results show that inter-monitor R values were typically higher than 0.95 regardless of the environment. The tested monitors demonstrate high linearity in comparison with PM₁₀ and PM_2.5 concentrations measured in outdoor air with reference-equivalent instrumentation with R² values ranging from 0.52 up to 0.83. In addition, very good agreement (R² values ranging from 0.93 up to 0.97) with the gravimetric PM₁₀ and PM_2.5 method is obtained in the indoor environment (30 < RH < 70%). High RH (over 70%) negatively affected the PM monitors' response, especially in the case of PM₁₀ concentrations (high overestimation).

A Comparison of Particulate Exposure Levels during Taxi, Bus, and Metro Commuting among Four Chinese Megacities

Exposure to inhalable particulate matter pollution is a hazard to human health. Many studies have examined the in-transit particulate matter pollution across multiple travel modes. However, limited information is available on the comparison of in-transit exposure among cities that experience different climates and weather patterns. This study aimed to examine the variations in in-cabin particle concentrations during taxi, bus, and metro commutes among four megacities located in the inland and coastal areas of China. To this end, we employed a portable monitoring approach to measure in-transit particle concentrations and the corresponding transit conditions using spatiotemporal information. The results highlighted significant differences in in-cabin particle concentrations among the four cities, indicating that PM concentrations varied in an ascending order of, and the ratios of different-sized particle concentrations varied in a descending order of CS, SZ, GZ, and WH. Variations in in-cabin particle concentrations during bus and metro transits between cities were mainly positively associated with urban background particle concentrations. Unlike those in bus and metro transit, in-cabin PM concentrations in taxi transit were negatively associated with urban precipitation and wind speed. The variations in particle concentrations during the trip were significantly associated with passenger density, posture, the in-cabin location of investigators, and window condition, some of which showed interactive effects. Our findings suggest that improving the urban background environment is essential for reducing particulate pollution in public transport microenvironments. Moreover, optimizing the scheduling of buses and the distribution of bus stops might contribute to mitigating the in-cabin exposure levels in transit. With reference to our methods and insights, policymakers and other researchers may further explore in-transit exposure to particle pollution in different cities.

Sources of error and variability in particulate matter sensor network measurements

The quality of mass concentration estimates from increasingly popular networks of low-cost particulate matter sensors depends on accurate conversion of sensor output (e.g., voltage) into gravimetric-equivalent mass concentration, typically using a calibration procedure. This study evaluates two important sources of variability that lead to error in estimating gravimetric-equivalent mass concentration: the temporal changes in sensor calibration and the spatial and temporal variability in gravimetric correction factors. A 40-node sensor network was deployed in a heavy vehicle manufacturing facility for 8 months. At a central location in the facility, particulate matter was continuously measured with three sensors of the network and a traditional, higher-cost photometer, determining the calibration slope and intercept needed to translate sensor output to photometric-equivalent mass concentration. Throughout the facility, during three intensive sampling campaigns, respirable mass concentrations were measured with gravimetric samplers and photometers to determine correction factors needed to adjust photometric-equivalent to gravimetric-equivalent mass concentration. Both field-determined sensor calibration slopes and intercepts were statistically different than those estimated in the laboratory (α = 0.05), emphasizing the importance of aerosol properties when converting voltage to photometric-equivalent mass concentration and the need for field calibration to determine slope. Evidence suggested the sensors' weekly field calibration slope decreased and intercept increased, indicating the sensors were deteriorating over time. The mean correction factor in the cutting and shot blasting area (2.9) was substantially and statistically lower than that in the machining and welding area (4.6; p = 0.01). Therefore, different correction factors should be determined near different occupational processes to accurately estimate particle mass concentrations.

Variation in gravimetric correction factors for nephelometer-derived estimates of personal exposure to PM2.5

Many portable monitors for quantifying mass concentrations of particulate matter air pollution rely on aerosol light scattering as the measurement method; however, the relationship between scattered light (what is measured) and aerosol mass concentration (the metric of interest) is a complex function of the refractive index, size distribution, and shape of the particles. In this study, we compared 33-h personal PM_2.5 concentrations measured simultaneously using nephelometry (personal DataRAM pDR-1200) and gravimetric filter sampling for working adults (44 participants, 249 samples). Nephelometer- and filter-derived 33-h average PM_2.5 concentrations were correlated (Spearman's ρ = 0.77); however, the nephelometer-derived concentration was within 20% of the filter-derived concentration for only 13% of samples. The nephelometer/filter ratio, which is used to correct light-scattering measurements to a gravimetric sample, had a median value of 0.52 and varied by over a factor of three (10th percentile = 0.35, 90^th percentile = 1.1). When 33-h samples with >50% of 10-s average nephelometer readings below the nephelometer limit of detection were removed from the dataset during sensitivity analyses, the fraction of nephelometer-derived concentrations that were within 20% of the filter-derived concentration increased to 25%. We also evaluated how much the accuracy of nephelometer-derived concentrations improved after applying: (1) a median correction factor derived from a subset of 44 gravimetric samples, (2) participant-specific correction factors derived from one same from each subject, and (3) correction factors predicted using linear models based on other variables recorded during the study. Each approach independently increased the fraction of nephelometer-derived concentrations that were within 20% of the filter-derived concentration to approximately 45%. These results illustrate the challenges with using light scattering (without correction to a concurrent gravimetric sample) to estimate personal exposure to PM_2.5 mass among mobile adults exposed to low daily average concentrations (median = 8 μg m^-3 in this study).

Assessment of PM2.5 monitoring using MicroPEM: A validation study in a city with elevated PM2.5 levels

Portable monitors such as MicroPEM can accurately characterize personal exposure of pollutants, which is critical for linking exposure and health effects of air pollution. The RTI (RTI International, Research Triangle Park, NC, USA) MicroPEM V3.2A provides both real-time fine particulate matter (PM_2.5) concentrations and time-integrated PM samples collected onto Teflon filters that can be used to correct real-time data as well as allow further lab chemical analysis of species on filters (e.g., metal, black carbon). Due to the optical reflectivity of local PM sources can be very different from available standard reference particles used for calibration by RTI, there is a need for gravimetric correction and validation at each study location. However, assessments of MicroPEM have been limited in locations with severe air pollution, such as Beijing. We selected a variety of weather and air quality conditions, including both clear and hazy days in Beijing, to compare PM_2.5 data among MicroPEMs as well as between MicroPEM and other types of samplers. We also compared MicroPEM real-time PM_2.5 concentrations with data from nearby fixed-sites. The results show MicroPEM performed well across a wide range of PM_2.5 concentrations (6-461 μg/m³) and MicroPEM data, after gravimetric correction, were consistent with those from moderate-volume samplers. Good agreement was also found between real-time data from MicroPEM and fixed-site data. The present study covered a wide range of pollution levels in actual environments and validated the usage of MicroPEM as a PM_2.5 monitor in locations with elevated PM_2.5 levels.

Evaluating the feasibility of a personal particle exposure monitor in outdoor and indoor microenvironments in Shanghai, China

Existing particulate matter (PM) monitors have too low spatiotemporal resolution to properly characterize individual exposure doses. In order to support health impact assessment, it is essential to develop a better method to assess individual exposure by taking account of varied environments in which people spend their time. Compact light-scattering PM monitors can potentially fill this need. This study was conducted to evaluate feasibility of a low-cost PM monitor (Plantower PMS 7003) in indoor and roadside outdoor microenvironments compared to research-grade instruments in Shanghai, China. The monitors exhibited excellent performance with a high linear response and low bias values both in outdoor and indoor tests. The monitors also showed little confounding bias in low relative humidity environments. Taking into account the accessibility and portability of this monitor, the monitors were able to detect the dynamic nature of individual exposures and provide data and knowledge about human exposure assessments.

Comparison of real-time instruments and gravimetric method when measuring particulate matter in a residential building

This study used several real-time and filter-based aerosol instruments to measure PM_2.5 levels in a high-rise residential green building in the Northeastern US and compared performance of those instruments. PM_2.5 24-hr average concentrations were determined using a Personal Modular Impactor (PMI) with 2.5 µm cut (SKC Inc., Eighty Four, PA) and a direct reading pDR-1500 (Thermo Scientific, Franklin, MA) as well as its filter. 1-hr average PM_2.5 concentrations were measured in the same apartments with an Aerotrak Optical Particle Counter (OPC) (model 8220, TSI, Inc., Shoreview, MN) and a DustTrak DRX mass monitor (model 8534, TSI, Inc., Shoreview, MN). OPC and DRX measurements were compared with concurrent 1-hr mass concentration from the pDR-1500. The pDR-1500 direct reading showed approximately 40% higher particle mass concentration compared to its own filter (n = 41), and 25% higher PM_2.5 mass concentration compared to the PMI_2.5 filter. The pDR-1500 direct reading and PMI_2.5 in non-smoking homes (self-reported) were not significantly different (n = 10, R² = 0.937), while the difference between measurements for smoking homes was 44% (n = 31, R² = 0.773). Both OPC and DRX data had substantial and significant systematic and proportional biases compared with pDR-1500 readings. However, these methods were highly correlated: R² = 0.936 for OPC versus pDR-1500 reading and R² = 0.863 for DRX versus pDR-1500 reading. The data suggest that accuracy of aerosol mass concentrations from direct-reading instruments in indoor environments depends on the instrument, and that correction factors can be used to reduce biases of these real-time monitors in residential green buildings with similar aerosol properties.

IMPLICATIONS

This study used several real-time and filter-based aerosol instruments to measure PM_2.5 levels in a high-rise residential green building in the northeastern United States and compared performance of those instruments. The data show that while the use of real-time monitors is convenient for measurement of airborne PM at short time scales, the accuracy of those monitors depends on a particular instrument. Bias correction factors identified in this paper could provide guidance for other studies using direct-reading instruments to measure PM concentrations.

Within-microenvironment exposure to particulate matter and health effects in children with asthma: a pilot study utilizing real-time personal monitoring with GPS interface

BACKGROUND

Most particulate matter (PM) and health studies in children with asthma use exposures averaged over the course of a day and do not take into account spatial/temporal variability that presumably occurs as children move from home, into transit and then school microenvironments. The objectives of this work were to identify increases in morning PM exposure occurring within home, transit and school microenvironments and determine their associations with asthma-related inflammation and rescue medication use.

METHODS

In 2007-2008, thirty Denver-area schoolchildren with asthma performed personal PM exposure monitoring using a real-time sensor integrated with a geographic information system (GIS) to apportion exposures to home, transit and school microenvironments. Concurrently, daily monitoring of the airway inflammatory biomarker urinary leukotriene E4 (uLTE₄) and albuterol usage was performed.

RESULTS

Mean PM exposures each morning were relatively well correlated between microenvironments for subject samples (0.3 < r < 0.8), thus limiting use of this exposure metric to attribute health effects to PM exposure in specific microenvironments. Within-microenvironment increases in exposure, such as would be characterized by one or a series of transient spikes or a sustained increase in concentration (exposure event), however, were not strongly correlated between microenvironments (|r| < 0.25). On days when children were exposed to a ≥ 5μg/m³ exposure event during transit, they demonstrated a 24.0 % increase in uLTE₄ (95 % CI: 1.5 %, 51.5 %) and a 9.7 % (-5.9 %, 27.9 %) increase in albuterol usage compared to days without transit exposure events. Associations between exposure events and health outcomes in home and school microenvironments tended to be positive as well, but weaker than for transit.

CONCLUSIONS

School children with asthma moving across morning microenvironments experience spatially heterogeneous PM exposures with potentially varying health effects.

Evaluation of Diesel Exhaust Continuous Monitors in Controlled Environmental Conditions

Diesel exhaust (DE) contains a variety of toxic air pollutants, including diesel particulate matter (DPM) and gaseous contaminants (e.g., carbon monoxide (CO)). DPM is dominated by fine (PM2.5) and ultrafine particles (UFP), and can be representatively determined by its thermal-optical refractory as elemental carbon (EC) or light-absorbing characteristics as black carbon (BC). The currently accepted reference method for sampling and analysis of occupational exposure to DPM is the National Institute for Occupational Safety and Health (NIOSH) Method 5040. However, this method cannot provide in-situ short-term measurements of DPM. Thus, real-time monitors are gaining attention to better examine DE exposures in occupational settings. However, real-time monitors are subject to changing environmental conditions. Field measurements have reported interferences in optical sensors and subsequent real-time readings, under conditions of high humidity and abrupt temperature changes. To begin dealing with these issues, we completed a controlled study to evaluate five real-time monitors: Airtec real-time DPM/EC Monitor, TSI SidePak Personal Aerosol Monitor AM510 (PM2.5), TSI Condensation Particle Counter 3007, microAeth AE51 BC Aethalometer, and Langan T15n CO Measurer. Tests were conducted under different temperatures (55, 70, and 80°F), relative humidity (10, 40, and 80%), and DPM concentrations (50 and 200 μg/m(3)) in a controlled exposure facility. The 2-hr averaged EC measurements from the Airtec instrument showed relatively good agreement with NIOSH Method 5040 (R(2) = 0.84; slope = 1.17±0.06; N = 27) and reported ∼17% higher EC concentrations than the NIOSH reference method. Temperature, relative humidity, and DPM levels did not significantly affect relative differences in 2-hr averaged EC concentrations obtained by the Airtec instrument vs. the NIOSH method (p < 0.05). Multiple linear regression analyses, based on 1-min averaged data, suggested combined effects of up to 5% from relative humidity and temperature on real-time measurements. The overall deviations of these real-time monitors from the NIOSH method results were ≤20%. However, simultaneous monitoring of temperature and relative humidity is recommended in field investigations to understand and correct for environmental impacts on real-time monitoring data.

Humidity and gravimetric equivalency adjustments for nephelometer-based particulate matter measurements of emissions from solid biomass fuel use in cookstoves

Great uncertainty exists around indoor biomass burning exposure-disease relationships due to lack of detailed exposure data in large health outcome studies. Passive nephelometers can be used to estimate high particulate matter (PM) concentrations during cooking in low resource environments. Since passive nephelometers do not have a collection filter they are not subject to sampler overload. Nephelometric concentration readings can be biased due to particle growth in high humid environments and differences in compositional and size dependent aerosol characteristics. This paper explores relative humidity (RH) and gravimetric equivalency adjustment approaches to be used for the pDR-1000 used to assess indoor PM concentrations for a cookstove intervention trial in Nepal. Three approaches to humidity adjustment performed equivalently (similar root mean squared error). For gravimetric conversion, the new linear regression equation with log-transformed variables performed better than the traditional linear equation. In addition, gravimetric conversion equations utilizing a spline or quadratic term were examined. We propose a humidity adjustment equation encompassing the entire RH range instead of adjusting for RH above an arbitrary 60% threshold. Furthermore, we propose new integrated RH and gravimetric conversion methods because they have one response variable (gravimetric PM_2.5 concentration), do not contain an RH threshold, and is straightforward.

Biomass smoke in Burkina Faso: what is the relationship between particulate matter, carbon monoxide, and kitchen characteristics?

In Burkina Faso where cooking with biomass is very common, little information exists regarding kitchen characteristics and their impact on air pollutant levels. The measurement of air pollutants such as respirable particulate matter (PM10), an important component of biomass smoke that has been linked to adverse health outcomes, can also pose challenges in terms of cost and the type of equipment needed. Carbon monoxide could potentially be a more economical and simpler measure of air pollution. The focus of this study was to first assess the association of kitchen characteristics with measured PM10 and CO levels and second, the relationship of PM10 with CO concentrations, across these different kitchen characteristics in households in Nouna, Burkina Faso. Twenty-four-hour concentrations of PM10 (area) were measured with portable monitors and CO (area and personal) estimated using color dosimeter tubes. Data on kitchen characteristics were collected through surveys. Most households used both wood and charcoal burned in three-stone and charcoal stoves. Mean outdoor kitchen PM10 levels were relatively high (774 μg/m(3), 95 % CI 329-1,218 μg/m(3)), but lower than indoor concentrations (Satterthwaite t value, -6.14; p < 0.0001). In multivariable analyses, outdoor kitchens were negatively associated with PM10 (OR = 0.06, 95 % CI 0.02-0.16, p value <0.0001) and CO (OR = 0.03, 95 % CI 0.01-0.11, p value <0.0001) concentrations. Strong area PM10 and area CO correlations were found with indoor kitchens (Spearman's r = 0.82, p < 0.0001), indoor stove use (Spearman's r = 0.82, p < 0.0001), and the presence of a smoker in the household (Spearman's r = 0.83, p < 0.0001). Weak correlations between area PM10 and personal CO levels were observed with three-stone (Spearman's r = 0.23, p = 0.008) and improved stoves (Spearman's r = 0.34, p = 0.003). This indicates that the extensive use of biomass fuels and multiple stove types for cooking still produce relatively high levels of exposure, even outdoors, suggesting that both fuel subsidies and stove improvement programs are likely necessary to address this problem. These findings also indicate that area CO color dosimeter tubes could be a useful measure of area PM10 concentrations when levels are influenced by strong emission sources or when used in indoors. The weaker correlation observed between area PM10 and personal CO levels suggests that area exposures are not as useful as proxies for personal exposures, which can vary widely from those recorded by stationary monitors.

Optimization approaches to ameliorate humidity and vibration related issues using the microAeth black carbon monitor for personal exposure measurement

Exposure to ambient black carbon (BC) is associated with adverse health effects. Black carbon levels display large spatial and temporal variability in many settings, such as cities and rural households where fossil fuel and biomass, respectively, are commonly burned for transportation, heat and cooking. This paper addresses the optimization of the miniaturized personal BC monitor, the microAeth® for use in epidemiology studies. To address false positive and negative peaks in real time BC concentrations resulting from changes in temperature and humidity, an inlet with a diffusion drier was developed. In addition, we developed data cleaning algorithms to address occasional false positive and negative fluctuations in BC readings related to physical vibration, due in part to both dirt accumulations in the optical inserts and degraded components. These methods were successfully used to process real-time BC data generated from a cohort of 9-10 year old children (N= 54) in NYC, who wore 1 or 2 microAeth units for six 24hr time periods. Two hour and daily BC averages after data cleaning were consistent with averaged raw data (slopes near 1 with R =0.99, p<0.001; R= 0.95, p<0.001, respectively), strongly suggesting that the false positive and negative excursions balance each other out when averaged for at least 2 hrs. Data cleaning of identified suspect events allows more confidence in the interpretation of the real-time personal monitoring data generated in environmental exposure studies, with mean percent difference <10% for 19 duplicate deployments.

Spatiotemporal aspects of real-time PM(2.5): low- and middle-income neighborhoods in Bangalore, India

We measured outdoor fine particulate matter (PM(2.5)) concentrations in a low- and a nearby middle-income neighborhood in Bangalore, India. Each neighborhood included sampling locations near and not near a major road. One-minute average concentrations were recorded for 168 days during September 2008 to May 2009 using a gravimetric-corrected nephelometer. We also measured wind speed and direction, and PM(2.5) concentration as a function of distance from road. Average concentrations are 21-46% higher in the low- than in the middle-income neighborhood, and exhibit differing spatiotemporal patterns. For example, in the middle-income neighborhood, median concentrations are higher near-road than not near-road (56 versus 50 μg m(-3)); in the low-income neighborhood, the reverse holds (68 μg m(-3) near-road, 74 μg m(-3) not near-road), likely because of within-neighborhood residential emissions (e.g., cooking; trash combustion). A moving-average subtraction method used to infer local- versus urban-scale emissions confirms that local emissions are greater in the low-income neighborhood than in the middle-income neighborhood; however, relative contributions from local sources vary by time-of-day. Real-time relative humidity correction factors are important for accurately interpreting real-time nephelometer data.

Validation of continuous particle monitors for personal, indoor, and outdoor exposures

Continuous monitors can be used to supplement traditional filter-based methods of determining personal exposure to air pollutants. They have the advantages of being able to identify nearby sources and detect temporal changes on a time scale of a few minutes. The Windsor Ontario Exposure Assessment Study (WOEAS) adopted an approach of using multiple continuous monitors to measure indoor, outdoor (near-residential) and personal exposures to PM₂.₅, ultrafine particles and black carbon. About 48 adults and households were sampled for five consecutive 24-h periods in summer and winter 2005, and another 48 asthmatic children for five consecutive 24-h periods in summer and winter 2006. This article addresses the laboratory and field validation of these continuous monitors. A companion article (Wheeler et al., 2010) provides similar analyses for the 24-h integrated methods, as well as providing an overview of the objectives and study design. The four continuous monitors were the DustTrak (Model 8520, TSI, St. Paul, MN, USA) and personal DataRAM (pDR) (ThermoScientific, Waltham, MA, USA) for PM₂.₅; the P-Trak (Model 8525, TSI) for ultrafine particles; and the Aethalometer (AE-42, Magee Scientific, Berkeley, CA, USA) for black carbon (BC). All monitors were tested in multiple co-location studies involving as many as 16 monitors of a given type to determine their limits of detection as well as bias and precision. The effect of concentration and electronic drift on bias and precision were determined from both the collocated studies and the full field study. The effect of rapid changes in environmental conditions on switching an instrument from indoor to outdoor sampling was also studied. The use of multiple instruments for outdoor sampling was valuable in identifying occasional poor performance by one instrument and in better determining local contributions to the spatial variation of particulate pollution. Both the DustTrak and pDR were shown to be in reasonable agreement (R² of 90 and 70%, respectively) with the gravimetric PM₂.₅ method. Both instruments had limits of detection of about 5 μg/m³. The DustTrak and pDR had multiplicative biases of about 2.5 and 1.6, respectively, compared with the gravimetric samplers. However, their average bias-corrected precisions were <10%, indicating that a proper correction for bias would bring them into very good agreement with standard methods. Although no standard methods exist to establish the bias of the Aethalometer and P-Trak, the precision was within 20% for the Aethalometer and within 10% for the P-Trak. These findings suggest that all four instruments can supply useful information in environmental studies.

Development of a method for personal, spatiotemporal exposure assessment

This work describes the development and evaluation of a high resolution, space and time-referenced sampling method for personal exposure assessment to airborne particulate matter (PM). This method integrates continuous measures of personal PM levels with the corresponding location-activity (i.e. work/school, home, transit) of the subject. Monitoring equipment include a small, portable global positioning system (GPS) receiver, a miniature aerosol nephelometer, and an ambient temperature monitor to estimate the location, time, and magnitude of personal exposure to particulate matter air pollution. Precision and accuracy of each component, as well as the integrated method performance were tested in a combination of laboratory and field tests. Spatial data was apportioned into pre-determined location-activity categories (i.e. work/school, home, transit) with a simple, temporospatially-based algorithm. The apportioning algorithm was extremely effective with an overall accuracy of 99.6%. This method allows examination of an individual's estimated exposure through space and time, which may provide new insights into exposure-activity relationships not possible with traditional exposure assessment techniques (i.e., time-integrated, filter-based measurements). Furthermore, the method is applicable to any contaminant or stressor that can be measured on an individual with a direct-reading sensor.