Susceptibility of hypertensive individuals to acute blood pressure increases in response to personal-level environmental temperature decrease.

BACKGROUND: Environmental temperature is negatively associated with blood pressure (BP), and hypertension may exacerbate this association. The aim of this study is to investigate whether hypertensive individuals are more susceptible to acute BP increases following temperature decrease than non-hypertensive individuals. METHODS: The study panel consisted of 126 hypertensive and 125 non-hypertensive (n = 251) elderly participants who completed 940 clinical visits during the winter of 2016 and summer of 2017 in Beijing, China. Personal-level environmental temperature (PET) was continuously monitored for each participant with a portable sensor platform. We associated systolic BP (SBP) and diastolic BP (DBP) with the average PET over 24 h before clinical visits using linear mixed-effects models and explored hourly lag patterns for the associations using distributed lag models. RESULTS: We found that per 1 °C decrease in PET, hypertensive individuals showed an average (95 % confidence interval) increase of 0.96 (0.72, 1.19) and 0.28 (0.13, 0.42) mmHg for SBP and DBP, respectively; and non-hypertensive participants showed significantly smaller increases of 0.28 (0.03, 0.53) mmHg SBP and 0.14 (-0.01, 0.30) mmHg DBP. A lag pattern analysis showed that for hypertensive individuals, the increases in SBP and DBP were greatest following lag 1 h PET decrease and gradually attenuated up to lag 10 h exposure. No significant BP change was observed in non-hypertensive individuals associated with lag 1-24 h PET exposure. The enhanced increase in PET-associated BP in hypertensive participants (i.e., susceptibility) was more significant in winter than in summer. CONCLUSIONS: We found that a decrease in environmental temperature was associated with acute BP increases and these associations diminished over time, disappearing after approximately 10 hours. This implies that any intervention measures to prevent BP increases due to temperature drop should be implemented as soon as possible. Such timely interventions are particularly needed for hypertensive individuals especially during the cold season due to their increased susceptibility.

Atmospheric isoprene measurements reveal larger-than-expected Southern Ocean emissions.

Isoprene is a key trace component of the atmosphere emitted by vegetation and other organisms. It is highly reactive and can impact atmospheric composition and climate by affecting the greenhouse gases ozone and methane and secondary organic aerosol formation. Marine fluxes are poorly constrained due to the paucity of long-term measurements; this in turn limits our understanding of isoprene cycling in the ocean. Here we present the analysis of isoprene concentrations in the atmosphere measured across the Southern Ocean over 4 months in the summertime. Some of the highest concentrations ( >500 ppt) originated from the marginal ice zone in the Ross and Amundsen seas, indicating the marginal ice zone is a significant source of isoprene at high latitudes. Using the United Kingdom Earth System Model we show that current estimates of sea-to-air isoprene fluxes underestimate observed isoprene by a factor >20. A daytime source of isoprene is required to reconcile models with observations. The model presented here suggests such an increase in isoprene emissions would lead to >8% decrease in the hydroxyl radical in regions of the Southern Ocean, with implications for our understanding of atmospheric oxidation and composition in remote environments, often used as proxies for the pre-industrial atmosphere.

Understanding the patterns and health impact of indoor air pollutant exposures in Bradford, UK: a study protocol.

INTRODUCTION: Relative to outdoor air pollution, there is little evidence examining the composition and concentrations of indoor air pollution and its associated health impacts. The INGENIOUS project aims to provide the comprehensive understanding of indoor air pollution in UK homes. METHODS AND ANALYSIS: 'Real Home Assessment' is a cross-sectional, multimethod study within INGENIOUS. This study monitors indoor air pollutants over 2 weeks using low-cost sensors placed in three rooms in 300 Born in Bradford (BiB) households. Building audits are completed by researchers, and participants are asked to complete a home survey and a health and behaviour questionnaire, in addition to recording household activities and health symptoms on at least 1 weekday and 1 weekend day. A subsample of 150 households will receive more intensive measurements of volatile organic compound and particulate matter for 3 days. Qualitative interviews conducted with 30 participants will identify key barriers and enablers of effective ventilation practices. Outdoor air pollution is measured in 14 locations across Bradford to explore relationships between indoor and outdoor air quality. Data will be analysed to explore total concentrations of indoor air pollutants, how these vary with building characteristics, and whether they are related to health symptoms. Interviews will be analysed through content and thematic analysis. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the NHS Health Research Authority Yorkshire and the Humber (Bradford Leeds) Research Ethics Committee (22/YH/0288). We will disseminate findings using our websites, social media, publications and conferences. Data will be open access through the BiB, the Open Science Framework and the UK Data Service.

Spatiotemporal distribution of pollutants and impact of local meteorology on source influence on pollutants' level in a traffic air-shed in Lagos megacity, Nigeria.

Pollution from vehicular emissions is a major cause of poor air quality observed in many urban and semi-urban towns and cities. As such, this study was conducted to assess air quality and the spatiotemporal distribution of vehicular and traffic-related pollutants in several air sheds of Lagos megacity, the economic nerve centre of Nigeria. A setup of low-cost air quality sensors comprising five (5) units was deployed between November 2018 and February 2019 within traffic corridors in the heart of the city. Diurnal variation of pollutants indicated that carbon dioxide (CO2) peaked during the early hours of the day, total oxide (Ox = NO2+O3) peaked at mid-day while carbon monoxide (CO) had two distinct peaks which correspond to morning and evening rush hours. Nitrogen dioxide (NO2) concentration peaked during evening hours. Average concentrations are NO2 (97.1 ± 9.7) ppb, Ox (78.6 ± 27.2) ppb, CO2 (450.1 ± 31.2) ppm, and CO (2285.63 ± 743.7) ppb. Average concentrations of pollutants were above thresholds set by the World Health Organization (WHO) except for NO2 which was within the range permissible limits. The implication of this is that the atmosphere is polluted due to elevated concentrations of airborne pollutants, an indication which is of both health and environmental concern. The air quality index (AQI) indicates that the quality of ambient air varies from good to very unhealthy for Ox, and unhealthy to very unhealthy for CO, while AQI for PM2.5 and PM10 showed hazardous at all the sampling locations except at UNILAG where it is unhealthy for the sensitive group. For all of the sampling sites, conditional bivariate probability function (CBPF) plots show a significant agreement with the location of known pollution sources.

Associations of air pollution mixtures with ambulatory blood pressure: The MobiliSense sensor-based study.

Air pollution is acknowledged as a determinant of blood pressure (BP), supporting the hypothesis that air pollution, via hypertension and other mechanisms, has detrimental effects on human health. Previous studies evaluating the associations between air pollution exposure and BP did not consider the effect that air pollutant mixtures may have on BP. We investigated the effect of exposure to single species or their synergistic effects as air pollution mixture on ambulatory BP. Using portable sensors, we measured personal concentrations of black carbon (BC), nitrogen dioxide (NO2), nitrogen monoxide (NO), carbon monoxide (CO), ozone (O3), and particles with aerodynamic diameters below 2.5 µm (PM2.5). We simultaneously collected ambulatory BP measurements (30-min intervals, N = 3319) of 221 participants over one day of their lives. Air pollution concentrations were averaged over 5 min to 1 h before each BP measurement, and inhaled doses were estimated across the same exposure windows using estimated ventilation rates. Fixed-effect linear models as well as quantile G-computation techniques were applied to associate air pollutants' individual and combined effects with BP, adjusting for potential confounders. In mixture models, a quartile increase in air pollutant concentrations (BC, NO2, NO, CO, and O3) in the previous 5 min was associated with a 1.92 mmHg (95% CI: 0.63, 3.20) higher systolic BP (SBP), while 30-min and 1-h exposures were not associated with SBP. However, the effects on diastolic BP (DBP) were inconsistent across exposure windows. Unlike concentration mixtures, inhalation mixtures in the previous 5 min to 1 h were associated with increased SBP. Out-of-home BC and O3 concentrations were more strongly associated with ambulatory BP outcomes than in-home concentrations. In contrast, only the in-home concentration of CO reduced DBP in stratified analyses. This study shows that exposure to a mixture of air pollutants (concentration and inhalation) was associated with elevated SBP.

Identifying Patterns and Sources of Fine and Ultrafine Particulate Matter in London Using Mobile Measurements of Lung-Deposited Surface Area.

We performed more than a year of mobile, 1 Hz measurements of lung-deposited surface area (LDSA, the surface area of 20-400 nm diameter particles, deposited in alveolar regions of lungs) and optically assessed fine particulate matter (PM2.5), black carbon (BC), and nitrogen dioxide (NO2) in central London. We spatially correlated these pollutants to two urban emission sources: major roadways and restaurants. We show that optical PM2.5 is an ineffective indicator of tailpipe emissions on major roadways, where we do observe statistically higher LDSA, BC, and NO2. Additionally, we find pollutant hot spots in commercial neighborhoods with more restaurants. A low LDSA (15 µm2 cm-3) occurs in areas with fewer major roadways and restaurants, while the highest LDSA (25 µm2 cm-3) occurs in areas with more of both sources. By isolating areas that are higher in one source than the other, we demonstrate the comparable impacts of traffic and restaurants on LDSA. Ratios of hyperlocal enhancements (ΔLDSA:ΔBC and ΔLDSA:ΔNO2) are higher in commercial neighborhoods than on major roadways, further demonstrating the influence of restaurant emissions on LDSA. We demonstrate the added value of using particle surface in identifying hyperlocal patterns of health-relevant PM components, especially in areas with strong vehicular emissions where the high LDSA does not translate to high PM2.5.

Automated classification of time-activity-location patterns for improved estimation of personal exposure to air pollution.

BACKGROUND: Air pollution epidemiology has primarily relied on measurements from fixed outdoor air quality monitoring stations to derive population-scale exposure. Characterisation of individual time-activity-location patterns is critical for accurate estimations of personal exposure and dose because pollutant concentrations and inhalation rates vary significantly by location and activity. METHODS: We developed and evaluated an automated model to classify major exposure-related microenvironments (home, work, other static, in-transit) and separated them into indoor and outdoor locations, sleeping activity and five modes of transport (walking, cycling, car, bus, metro/train) with multidisciplinary methods from the fields of movement ecology and artificial intelligence. As input parameters, we used GPS coordinates, accelerometry, and noise, collected at 1 min intervals with a validated Personal Air quality Monitor (PAM) carried by 35 volunteers for one week each. The model classifications were then evaluated against manual time-activity logs kept by participants. RESULTS: Overall, the model performed reliably in classifying home, work, and other indoor microenvironments (F1-score>0.70) but only moderately well for sleeping and visits to outdoor microenvironments (F1-score=0.57 and 0.3 respectively). Random forest approaches performed very well in classifying modes of transport (F1-score>0.91). We found that the performance of the automated methods significantly surpassed those of manual logs. CONCLUSIONS: Automated models for time-activity classification can markedly improve exposure metrics. Such models can be developed in many programming languages, and if well formulated can have general applicability in large-scale health studies, providing a comprehensive picture of environmental health risks during daily life with readily gathered parameters from smartphone technologies.

Personal exposure to air pollution and respiratory health of COPD patients in London.

Previous studies have investigated the effects of air pollution on chronic obstructive pulmonary disease (COPD) patients using either fixed-site measurements or a limited number of personal measurements, usually for one pollutant and a short time period. These limitations may introduce bias and distort the epidemiological associations as they do not account for all the potential sources or the temporal variability of pollution.We used detailed information on individuals' exposure to various pollutants measured at fine spatiotemporal scale to obtain more reliable effect estimates. A panel of 115 patients was followed up for an average continuous period of 128 days carrying a personal monitor specifically designed for this project that measured temperature, nitrogen dioxide (NO2), ozone (O3), nitric oxide (NO), carbon monoxide (CO), and particulate matter with aerodynamic diameter <2.5 and <10 µm at 1-min time resolution. Each patient recorded daily information on respiratory symptoms and measured peak expiratory flow (PEF). A pulmonologist combined related data to define a binary variable denoting an "exacerbation". The exposure-response associations were assessed with mixed effects models.We found that gaseous pollutants were associated with a deterioration in patients' health. We observed an increase of 16.4% (95% CI 8.6-24.6%), 9.4% (95% CI 5.4-13.6%) and 7.6% (95% CI 3.0-12.4%) in the odds of exacerbation for an interquartile range increase in NO2, NO and CO, respectively. Similar results were obtained for cough and sputum. O3 was found to have adverse associations with PEF and breathlessness. No association was observed between particulate matter and any outcome.Our findings suggest that, when considering total personal exposure to air pollutants, mainly the gaseous pollutants affect COPD patients' health.

Key Role of NO3 Radicals in the Production of Isoprene Nitrates and Nitrooxyorganosulfates in Beijing.

The formation of isoprene nitrates (IsN) can lead to significant secondary organic aerosol (SOA) production and they can act as reservoirs of atmospheric nitrogen oxides. In this work, we estimate the rate of production of IsN from the reactions of isoprene with OH and NO3 radicals during the summertime in Beijing. While OH dominates the loss of isoprene during the day, NO3 plays an increasingly important role in the production of IsN from the early afternoon onwards. Unusually low NO concentrations during the afternoon resulted in NO3 mixing ratios of ca. 2 pptv at approximately 15:00, which we estimate to account for around a third of the total IsN production in the gas phase. Heterogeneous uptake of IsN produces nitrooxyorganosulfates (NOS). Two mono-nitrated NOS were correlated with particulate sulfate concentrations and appear to be formed from sequential NO3 and OH oxidation. Di- and tri-nitrated isoprene-related NOS, formed from multiple NO3 oxidation steps, peaked during the night. This work highlights that NO3 chemistry can play a key role in driving biogenic-anthropogenic interactive chemistry in Beijing with respect to the formation of IsN during both the day and night.

Source-Receptor Relationship Revealed by the Halted Traffic and Aggravated Haze in Beijing during the COVID-19 Lockdown.

The COVID-19 outbreak greatly limited human activities and reduced primary emissions particularly from urban on-road vehicles but coincided with Beijing experiencing "pandemic haze," raising the public concerns about the effectiveness of imposed traffic policies to improve the air quality. This paper explores the relationship between local vehicle emissions and the winter haze in Beijing before and during the COVID-19 lockdown based on an integrated analysis framework, which combines a real-time on-road emission inventory, in situ air quality observations, and a localized numerical modeling system. We found that traffic emissions decreased substantially during the COVID-19 pandemic, but its imbalanced emission abatement of NOx (76%, 125.3 Mg/day) and volatile organic compounds (VOCs, 53%, 52.9 Mg/day) led to a significant rise of atmospheric oxidants in urban areas, resulting in a modest increase in secondary aerosols due to inadequate precursors, which still offset reduced primary emissions. Moreover, the enhanced oxidizing capacity in the surrounding regions greatly increased the secondary particles with relatively abundant precursors, which was transported into Beijing and mainly responsible for the aggravated haze pollution. We recommend that mitigation policies should focus on accelerating VOC emission reduction and synchronously controlling regional sources to release the benefits of local traffic emission control.

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.

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 % while stronger relationship was noticed with higher PM concentration 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.

Modelling the effect of the 2018 summer heatwave and drought on isoprene emissions in a UK woodland.

Projected future climatic extremes such as heatwaves and droughts are expected to have major impacts on emissions and concentrations of biogenic volatile organic compounds (bVOCs) with potential implications for air quality, climate and human health. While the effects of changing temperature and photosynthetically active radiation (PAR) on the synthesis and emission of isoprene, the most abundant of these bVOCs, are well known, the role of other environmental factors such as soil moisture stress are not fully understood and are therefore poorly represented in land surface models. As part of the Wytham Isoprene iDirac Oak Tree Measurements campaign, continuous measurements of isoprene mixing ratio were made throughout the summer of 2018 in Wytham Woods, a mixed deciduous woodland in southern England. During this time, the United Kingdom experienced a prolonged heatwave and drought, and isoprene mixing ratios were observed to increase by more than 400% at Wytham Woods under these conditions. We applied the state-of-the-art FORest Canopy-Atmosphere Transfer canopy exchange model to investigate the processes leading to these elevated concentrations. We found that although current isoprene emissions algorithms reproduced observed mixing ratios in the canopy before and after the heatwave, the model underestimated observations by ~40% during the heatwave-drought period implying that models may substantially underestimate the release of isoprene to the atmosphere in future cases of mild or moderate drought. Stress-induced emissions of isoprene based on leaf temperature and soil water content (SWC) were incorporated into current emissions algorithms leading to significant improvements in model output. A combination of SWC, leaf temperature and rewetting emission bursts provided the best model-measurement fit with a 50% improvement compared to the baseline model. Our results highlight the need for more long-term ecosystem-scale observations to enable improved model representation of atmosphere-biosphere interactions in a changing global climate.

Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments.

The inaccurate quantification of personal exposure to air pollution introduces error and bias in health estimations, severely limiting causal inference in epidemiological research worldwide. Rapid advancements in affordable, miniaturised air pollution sensor technologies offer the potential to address this limitation by capturing the high variability of personal exposure during daily life in large-scale studies with unprecedented spatial and temporal resolution. However, concerns remain regarding the suitability of novel sensing technologies for scientific and policy purposes. In this paper we characterise the performance of a portable personal air quality monitor (PAM) that integrates multiple miniaturised sensors for nitrogen oxides (NO x ), carbon monoxide (CO), ozone (O3) and particulate matter (PM) measurements along with temperature, relative humidity, acceleration, noise and GPS sensors. Overall, the air pollution sensors showed high reproducibility (mean R ¯ 2 = 0.93, min-max: 0.80-1.00) and excellent agreement with standard instrumentation (mean R ¯ 2 = 0.82, min-max: 0.54-0.99) in outdoor, indoor and commuting microenvironments across seasons and different geographical settings. An important outcome of this study is that the error of the PAM is significantly smaller than the error introduced when estimating personal exposure based on sparsely distributed outdoor fixed monitoring stations. Hence, novel sensing technologies such as the ones demonstrated here can revolutionise health studies by providing highly resolved reliable exposure metrics at a large scale to investigate the underlying mechanisms of the effects of air pollution on health.

Associations among particulate matter, hazardous air pollutants and methane emissions from the Aliso Canyon natural gas storage facility during the 2015 blowout.

In October of 2015, a large underground storage well at the Aliso Canyon natural gas storage facility experienced a massive methane leak (also referred to as "natural gas blowout"), which resulted in the largest ever anthropogenic release of methane from a single point source in the United States. Additional sampling conducted during the event revealed unique gas and particle concentrations in ambient air and a characteristic "fingerprint" of metals in the indoor dust samples similar to samples taken at the blowout site. We further investigated the association between the Aliso Canyon natural gas storage site and several measured air pollutants by: (a) conducting additional emission source studies using meteorological data and correlations between particulate matter, methane, and hazardous air pollutants (HAPs) collected during the natural gas blowout at distances ranging from 1.2 to 7.3 km due south of well SS25, (b) identifying the unique i/n-pentane ratio signature associated with emissions from the blowout event, and (c) identifying characteristics unique to the homes that tested positive for air pollutants using data collected from extensive indoor environmental assessment surveys. Results of air quality samples collected near Aliso Canyon during the final weeks of the event revealed that elevated levels of several HAP compounds were likely influenced by the active natural gas blowout. Furthermore, the final attempts to plug the well during the days preceding the well kill were associated with particle emissions likely from the well site. Together, this investigation suggests uncontrolled leaks or blowout events at natural gas storage facilities have the potential to release harmful pollutants with adverse health and environmental consequences into proximate communities. With this evidence, our recommendations include facility-specific meteorological and air quality data-collection equipment installed at natural gas storage facilities and support of environmental surveillance after severe off-normal operation events.

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.

A nocturnal atmospheric loss of CH2I2 in the remote marine boundary layer.

Ocean emissions of inorganic and organic iodine compounds drive the biogeochemical cycle of iodine and produce reactive ozone-destroying iodine radicals that influence the oxidizing capacity of the atmosphere. Di-iodomethane (CH2I2) and chloro-iodomethane (CH2ICl) are the two most important organic iodine precursors in the marine boundary layer. Ship-borne measurements made during the TORERO (Tropical Ocean tRoposphere Exchange of Reactive halogens and Oxygenated VOC) field campaign in the east tropical Pacific Ocean in January/February 2012 revealed strong diurnal cycles of CH2I2 and CH2ICl in air and of CH2I2 in seawater. Both compounds are known to undergo rapid photolysis during the day, but models assume no night-time atmospheric losses. Surprisingly, the diurnal cycle of CH2I2 was lower in amplitude than that of CH2ICl, despite its faster photolysis rate. We speculate that night-time loss of CH2I2 occurs due to reaction with NO3 radicals. Indirect results from a laboratory study under ambient atmospheric boundary layer conditions indicate a k CH2I2+NO3 of ≤4 × 10-13 cm3 molecule-1 s-1; a previous kinetic study carried out at ≤100 Torr found k CH2I2+NO3 of 4 × 10-13 cm3 molecule-1 s-1. Using the 1-dimensional atmospheric THAMO model driven by sea-air fluxes calculated from the seawater and air measurements (averaging 1.8 +/- 0.8 nmol m-2 d-1 for CH2I2 and 3.7 +/- 0.8 nmol m-2 d-1 for CH2ICl), we show that the model overestimates night-time CH2I2 by >60 % but reaches good agreement with the measurements when the CH2I2 + NO3 reaction is included at 2-4 × 10-13 cm3 molecule-1 s-1. We conclude that the reaction has a significant effect on CH2I2 and helps reconcile observed and modeled concentrations. We recommend further direct measurements of this reaction under atmospheric conditions, including of product branching ratios.

An evaluation tool kit of air quality micro-sensing units.

Recent developments in sensory and communication technologies have made the development of portable air-quality (AQ) micro-sensing units (MSUs) feasible. These MSUs allow AQ measurements in many new applications, such as ambulatory exposure analyses and citizen science. Typically, the performance of these devices is assessed using the mean error or correlation coefficients with respect to a laboratory equipment. However, these criteria do not represent how such sensors perform outside of laboratory conditions in large-scale field applications, and do not cover all aspects of possible differences in performance between the sensor-based and standardized equipment, or changes in performance over time. This paper presents a comprehensive Sensor Evaluation Toolbox (SET) for evaluating AQ MSUs by a range of criteria, to better assess their performance in varied applications and environments. Within the SET are included four new schemes for evaluating sensors' capability to: locate pollution sources; represent the pollution level on a coarse scale; capture the high temporal variability of the observed pollutant and their reliability. Each of the evaluation criteria allows for assessing sensors' performance in a different way, together constituting a holistic evaluation of the suitability and usability of the sensors in a wide range of applications. Application of the SET on measurements acquired by 25 MSUs deployed in eight cities across Europe showed that the suggested schemes facilitates a comprehensive cross platform analysis that can be used to determine and compare the sensors' performance. The SET was implemented in R and the code is available on the first author's website.