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

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

Measuring Aerosol Phase Changes and Hygroscopicity with a Microresonator Mass Sensor.

The interaction between atmospheric aerosol particles and water vapor influences aerosol size, phase, and composition, parameters which critically influence their impacts in the atmosphere. Methods to accurately measure aerosol water uptake for a wide range of particle types are therefore merited. We present here a new method for characterizing aerosol hygroscopicity, an impaction stage containing a microelectromechanical systems (MEMS) microresonator. We find that deliquescence and efflorescence relative humidities (RHs) of sodium chloride and ammonium sulfate are easily diagnosed via changes in resonant frequency and peak sharpness. These agree well with literature values and thermodynamic models. Furthermore, we demonstrate that, unlike other resonator-based techniques, full hygroscopic growth curves can be derived, including for an inorganic-organic mixture (sodium chloride and malonic acid) which remains liquid at all RHs. The response of the microresonator frequency to temperature and particle mechanical properties and the resulting limitations when measuring hygroscopicity are discussed. MEMS resonators show great potential as miniaturized ambient aerosol mass monitors, and future work will consider the applicability of our approach to complex ambient samples. The technique also offers an alternative to established methods for accurate thermodynamic measurements in the laboratory

Linking e-health records, patient-reported symptoms and environmental exposure data to characterise and model COPD exacerbations: protocol for the COPE study.

INTRODUCTION: Relationships between exacerbations of chronic obstructive pulmonary disease (COPD) and environmental factors such as temperature, humidity and air pollution are not well characterised, due in part to oversimplification in the assignment of exposure estimates to individuals and populations. New developments in miniature environmental sensors mean that patients can now carry a personal air quality monitor for long periods of time as they go about their daily lives. This creates the potential for capturing a direct link between individual activities, environmental exposures and the health of patients with COPD. Direct associations then have the potential to be scaled up to population levels and tested using advanced human exposure models linked to electronic health records. METHODS AND ANALYSIS: This study has 5 stages: (1) development and deployment of personal air monitors; (2) recruitment and monitoring of a cohort of 160 patients with COPD for up to 6 months with recruitment of participants through the Clinical Practice Research Datalink (CPRD); (3) statistical associations between personal exposure with COPD-related health outcomes; (4) validation of a time-activity exposure model and (5) development of a COPD prediction model for London. ETHICS AND DISSEMINATION: The Research Ethics Committee for Camden and Islington has provided ethical approval for the conduct of the study. Approval has also been granted by National Health Service (NHS) Research and Development and the Independent Scientific Advisory Committee. The results of the study will be disseminated through appropriate conference presentations and peer-reviewed journals.This work is funded by the Medical Research Council (MR/L019744/1). MRC-PHE funding has been obtained for a pilot study to collect blood and sputum samples on a subset of 20 participants. Enrolment will take place at The Royal Brompton and Harefield (RBH) and Guy's and St Thomas' (GSTT) NHS Foundation Trusts. Support will be provided by the Respiratory Clinical Research Facility at RBH and the Lane Fox Unit at GSTT. The project is a portfolio adopted by the National Institute for Health Research (NIHR) UK Clinical Research Network (CRN). Additional support was provided by the NIHR Biomedical Research Centre based at GSTT and King's College London.This is the final version of the article. It first appeared from the BMJ Publishing Group via http://dx.doi.org/10.1136/bmjopen-2016-01133

iDirac: a field-portable instrument for long-term autonomous measurements of isoprene and selected VOCs

The iDirac is a new instrument to measure selected hydrocarbons in the remote atmosphere. A robust design is central to its specifications, with portability, power efficiency, low gas consumption and autonomy as the other driving factors in the instrument development. The iDirac is a dual-column isothermal oven gas chromatograph with photoionisation detection (GC-PID). The instrument is designed and built in-house. It features a modular design, with the novel use of open-source technology for accurate instrument control. Currently configured to measure biogenic isoprene, the system is suitable for a range of compounds. For isoprene measurements in the field, the instrument precision (relative standard deviation) is ±10 %, with a limit of detection down to 38 pmol mol−1 (or ppt). The instrument was first tested in the field in 2015 during a ground-based campaign, and has since shown itself suitable for deployment in a variety of environments and platforms. This paper describes the instrument design, operation and performance based on laboratory tests in a controlled environment as well as during deployments in forests in Malaysian Borneo and central England

Using low-cost sensor technologies and advanced computational methods to improve dose estimations in health panel studies: results of the AIRLESS project.

BACKGROUND: Air pollution epidemiology has primarily relied on fixed outdoor air quality monitoring networks and static populations. METHODS: Taking advantage of recent advancements in sensor technologies and computational techniques, this paper presents a novel methodological approach that improves dose estimations of multiple air pollutants in large-scale health studies. We show the results of an intensive field campaign that measured personal exposures to gaseous pollutants and particulate matter of a health panel of 251 participants residing in urban and peri-urban Beijing with 60 personal air quality monitors (PAMs). Outdoor air pollution measurements were collected in monitoring stations close to the participants' residential addresses. Based on parameters collected with the PAMs, we developed an advanced computational model that automatically classified time-activity-location patterns of each individual during daily life at high spatial and temporal resolution. RESULTS: Applying this methodological approach in two established cohorts, we found substantial differences between doses estimated from outdoor and personal air quality measurements. The PAM measurements also significantly reduced the correlation between pollutant species often observed in static outdoor measurements, reducing confounding effects. CONCLUSIONS: Future work will utilise these improved dose estimations to investigate the underlying mechanisms of air pollution on cardio-pulmonary health outcomes using detailed medical biomarkers in a way that has not been possible before.This project is funded under the Newton Fund Programme awarded by Natural Environmental Research Council (NERC Grant NE/N007018/1) with support from Medical Research Council (MRC) and by the National Natural Science Foundation of China (NSFC Grant 81571130100). The NSFC funding is mainly used to support the field work in China, and NERC funding is mainly used for coordination and the further analysis

Constraining emission estimates of carbon monoxide using a perturbed emissions ensemble with observations: a focus on Beijing

Funder: Tsinghua University Initiative Scientific Research ProgramFunder: National Centre for Atmospheric Science; doi: http://dx.doi.org/10.13039/501100000662Funder: Met Office; doi: http://dx.doi.org/10.13039/501100000847Abstract: The reliability of air quality simulations has a strong dependence on the input emissions inventories, which are associated with various sources of uncertainties, particularly in regions undergoing rapid emission changes where inventories can be ‘out of date’ almost as soon as they are compiled. This work provides a new methodology for updating emissions inventories by source sector using air quality ensemble simulations and observations from a dense monitoring network. It is adopted to determine the short-term trends in carbon monoxide (CO) emissions, an important pollutant and precursor to tropospheric ozone, in a study area centred around Beijing following the implementation of clean air policies. We sample the uncertainties associated with using an a priori emissions inventory for the year 2013 in air quality simulations of 2016, using an atmospheric dispersion model combined with a perturbed emissions ensemble (PEE), which is constructed based on expert-elicited uncertainty ranges for individual source sectors in the inventory. By comparing the simulation outputs with observational constraints, we are able to constrain the emissions of key source sectors relative to those in the a priori emissions inventory. From 2013 to 2016, we find a 44–88% reduction in the transport sector emissions (0.92–4.4×105 Mg in 2016) and a minimum 61% decrease in residential sector emissions (<3.5×105 Mg in 2016) within the study area. We also provide evidence that the night-time fraction of traffic sources in 2016 was higher than that in the 2013 emissions inventory. This study shows the applicability of PEEs and high-resolution observations in providing timely updates of emission estimates by source sector

Analysis of the variability of airborne particulate matter with prevailing meteorological conditions across a semi-urban environment using a network of low-cost air quality sensors.

The concentrations of fine and coarse fractions of airborne particulate matter (PM) and meteorological variables (wind speed, wind direction, temperature and relative humidity) were measured at six selected locations in Ile Ife, a prominent university town in Nigeria using a network of low-cost air quality (AQ) sensor units. The objective of the deployment was to collate baseline air quality data and assess the impact of prevailing meteorological conditions on PM concentrations in selected residential communities downwind of an iron smelting facility. The raw data obtained from OPC-N2 of the AQ sensor units was corrected using the RH correction factor developed based k-Kohler theory. This PM (corrected) fast time resolution data (20 s) from the AQ sensor units were used to create daily averages. The overall mean mass concentrations for PM2.5 and PM10 were 213.3, 44.1, 23.8, 27.7, 20.2 and 41.5 μg/m3 and; 439.9, 107.1, 55.0, 72.4, 45.5 and 112.0 μg/m3 for Fasina (Iron-Steel Smelting Factory, ISSF), Modomo, Eleweran, Fire Service, O.A.U. staff quarters and Obafemi Awolowo University Teaching and Research Farm (OAUTRF), respectively. PM concentration and wind speed showed a negative exponential distribution curve with the lowest exponential fit coefficient of determination (R2) values of 0.08 for PM2.5 and 0.03 for PM10 during nighttime periods at Eleweran and Fire service sites, respectively. The relationship between PM concentration and temperature gave a decay curve indicating that higher PM concentrations were observed at lower temperatures. The exponential distribution curve for the relationship between PM concentration and relative humidity (RH) showed that PM concentrations do not vary for RH 80 % for both day and nighttime. The performances of the MLR model were slightly poor and as such not too reliable for predicting the concentration but useful for improving predictive model accuracy when other variables contributing to the variability of PM is considered. The study concluded that the anthropogenic and industrial activities at the smelting factory contribute significantly to the elevated PM mass concentration measured at the study locations

A new processing scheme for ultra-high resolution direct infusion mass spectrometry data

High resolution, high accuracy mass spectrometry is widely used to characterise environmental or biological samples with highly complex composition enabling the identification of chemical composition of often unknown compounds. Despite instrumental advancements, the accurate molecular assignment of compounds acquired in high resolution mass spectra remains time consuming and requires automated algorithms, especially for samples covering a wide mass range and large numbers of compounds. A new processing scheme is introduced implementing filtering methods based on element assignment, instrumental error, and blank subtraction. Optional post-processing incorporates common ion selection across replicate measurements and shoulder ion removal. The scheme allows both positive and negative direct infusion electrospray ionisation (ESI) and atmospheric pressure photoionisation (APPI) acquisition with the same programs. An example application to atmospheric organic aerosol samples using an Orbitrap mass spectrometer is reported for both ionisation techniques resulting in final spectra with 0.8% and 8.4% of the peaks retained from the raw spectra for APPI positive and ESI negative acquisition, respectively.This work was supported by the European Research Council (ERC starting grant 279405) and by the U.K. Natural Environment Research Council (NERC grant NE/H52449X/1). ATZ thanks the Natural Sciences and Engineering Research Council of Canada, the Sir Winston Churchill Society of Edmonton, and the Cambridge Trust for PhD funding. IK was supported by a M. Curie Intra-European fellowship (project no. 254319

Intercomparison of nitrous acid (HONO) measurement techniques in a megacity (Beijing)

Nitrous acid (HONO) is a key determinant of the daytime radical budget in the daytime boundary layer, with quantitative measurement required to understand OH radical abundance. Accurate and precise measurements of HONO are therefore needed; however HONO is a challenging compound to measure in the field, in particular in a chemically complex and highly polluted environment. Here we report an intercomparison exercise between HONO measurements performed by two wet chemical techniques (the commercially available a long-path absorption photometer (LOPAP) and a custom-built instrument) and two broadband cavity-enhanced absorption spectrophotometer (BBCEAS) instruments at an urban location in Beijing. In addition, we report a comparison of HONO measurements performed by a time-of-flight chemical ionization mass spectrometer (ToF-CIMS) and a selected ion flow tube mass spectrometer (SIFT-MS) to the more established techniques (wet chemical and BBCEAS). The key finding from the current work was that all instruments agree on the temporal trends and variability in HONO (r2 > 0.97), yet they displayed some divergence in absolute concentrations, with the wet chemical methods consistently higher overall than the BBCEAS systems by between 12&thinsp;% and 39&thinsp;%. We found no evidence for any systematic bias in any of the instruments, with the exception of measurements near instrument detection limits. The causes of the divergence in absolute HONO concentrations were unclear, and may in part have been due to spatial variability, i.e. differences in instrument location and/or inlet position, but this observation may have been more associative than casual