Monitoring air pollution: use of early warning systems for public health

Knowledge, Attitudes, and Practices Regarding Air Pollution among Medical Students

Background: Air pollution has emerged as a global public health concern. Specifically, in Medellín, Colombia, episodes of elevated air pollution have been documented. Medical students' knowledge of air pollution is paramount for implementing future interventions directed toward patients. The aim of this research was to delineate the knowledge, attitudes, and practices regarding air pollution among medical students at a private university in Medellín. Methods: A cross-sectional study involving 352 medical students was conducted. A questionnaire was administered, generating scores ranging from 0 to 100, where a higher score signified better knowledge, attitudes, and practices. Data were analyzed using frequencies, summary measures, non-parametric tests, and linear regression. Results: In total, 31% rated the education received at the university on the relationship between health and air quality as fair to poor, and 81% perceived the air quality in the city as poor. The knowledge score was 77.8 (IQR 71.1-85.6), with 90% acknowledging that exposure to air pollution increases the risk of various diseases. The attitudes score was 82.1 (IQR 71.8-87.2), and 25.9% believed that air pollution is a multifactorial problem, rendering their actions ineffective. In terms of practices, the score was 50 (IQR 42.9-57.1), indicating that students either did not employ protective measures against pollution or used inappropriate practices such as masks or air purifiers. Regression analysis revealed no association between knowledge and practices. Conclusion: The findings of this study underscore that medical students possess commendable knowledge regarding the health effects of air pollution. However, their adoption of inappropriate practices for self-protection is evident. The lack of correlation between knowledge and practices highlights the necessity of educational initiatives to be complemented by regulatory and cultural interventions.

IoT-based monitoring system and air quality prediction using machine learning for a healthy environment in Cameroon

This paper is aimed at developing an air quality monitoring system using machine learning (ML), Internet of Things (IoT), and other elements to predict the level of particulate matter and gases in the air based on the air quality index (AQI). It is an air quality assessor and therefore a means of achieving the Sustainable Development Goals (SDGs), in particular, SDG 3.9 (substantial reduction of the health impacts of hazardous substances) and SDG 11.6 (reduction of negative impacts on cities and populations). AQI quantifies and informs the public about air pollutants and their adverse effects on public health. The proposed air quality monitoring device is low-cost and operates in real-time. It consists of a hardware unit that detects various pollutants to assess air quality as well as other airborne particles such as carbon dioxide (CO2), methane (CH4), volatile organic compounds (VOCs), nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matter with an aerodynamic diameter of 2.5 microns or less (PM2.5). To predict air quality, the device was deployed from November 1, 2022, to February 4, 2023, in certain bauxite-rich areas of Adamawa and certain volcanic sites in western Cameroon. Therefore, machine learning algorithm models, namely, multiple linear regression (MLR), support vector regression (SVR), random forest regression (RFR), XGBoost (XGB), and K-nearest neighbors (KNN) were applied to analyze the collected concentrations and predict the future state of air quality. The performance of these models was evaluated using mean absolute error (MAE), coefficient of determination (R-square), and root mean square error (RMSE). The obtained data in this study show that these pollutants are present in selected localities albeit to different extents. Moreover, the AQI values obtained range from 10 to 530, with a mean of 132.380 ± 63.705, corresponding to moderate air quality state but may induce an adverse effect on sensitive members of the population. This study revealed that XGB regression performed better in air quality forecasting with the highest R-squared (test score of 0.9991 and train score of 0.9999) and lowest RMSE (test score of 1.5748 and train score of 0. 0073) and MAE (test score of 0.0872 and train score of 0.0020), while the KNN model had the worst prediction (lowest R-squared and highest RMSE and MAE). This embryonic work is a prototype for projects in Cameroon as measurements are underway for a national spread over a longer period of time.

Long-term ozone exposure and mortality in patients with chronic kidney disease: a large cohort study

BACKGROUND

Epidemiologic studies on the effects of long-term exposure to ozone (O3) have shown inconclusive results. It is unclear whether to O3 has an effect on chronic kidney disease (CKD). We investigated the effects of O3 on mortality and renal outcome in CKD.

METHODS

We included 61,073 participants and applied Cox proportional hazards models to examine the effects of ozone on the risk of end-stage renal disease (ESRD) and mortality in a two-pollutants model adjusted for socioeconomic status. We calculated the concentration of ozone exposure one year before enrollment and used inverse distance weighting (IDW) for interpolation, where the exposure was evenly distributed.

RESULTS

In the single pollutant model, O3 was significantly associated with an increased risk of ESRD and all-cause mortality. Based on the O3 concentration from IDW interpolation, this moving O3 average was significantly associated with an increased risk of ESRD and all-cause mortality. In a two-pollutants model, even after we adjusted for other measured pollutants, nitrogen dioxide did not attenuate the result for O3. The hazard ratio (HR) value for the district-level assessment is 1.025 with a 95% confidence interval (CI) of 1.014-1.035, while for the point-level assessment, the HR value is 1.04 with a 95% CI of 1.035-1.045. The impact of ozone on ESRD, hazard ratio (HR) values are, 1.049(95%CI: 1.044-1.054) at the district unit and 1.04 (95%CI: 1.031-1.05) at the individual address of the exposure assessment. The ozone hazard ratio for all-cause mortality was 1.012 (95% confidence interval: 1.008-1.017) for administrative districts and 1.04 (95% confidence interval: 1.031-1.05) for individual addresses.

CONCLUSIONS

This study suggests that long-term ambient O3 increases the risk of ESRD and mortality in CKD. The strategy to decrease O3 emissions will substantially benefit health and the environment.

Knowledge, attitudes, and perception of air pollution in Ireland

Aim

Air pollution remains a major global public health challenge; and Ireland is no exception to the human health implications of exposure ambient air pollutants. Accurate and timely information can be critical to mitigate the harmful effects of air pollution. This study aimed to assess the knowledge, perceptions, and attitudes to poor air quality in Ireland to assist stakeholders in developing and implementing effective communication pieces and policies about the management of air pollution.

Study design

Cross-sectional population-based cohort.

Method

Quantitative data on knowledge, attitudes, and perceptions (KAP) were collected from respondents living across Ireland, and the results were analysed with SPSS (Version 28.0).

Results

Among the 1005 respondents included in this study, the mean [SD] age was 46.1 [15.3] years; 53% were female (n = 530); and 66% and 35% of respondents were aware of air pollution and its adverse effects on health at a national and local level respectively (n = 668 and n = 353 respectively). In addition, there were significant relationships between socio-demographic and air pollution awareness. There were correlation between respondent's age, gender, socio-economic group, and locality in Ireland.

Conclusion

This study demonstrates that environmental health literacy around air pollution in critically lacking among respondents. Given that air pollution is an increasingly important global priority, opportunities need to create to improve reach and impact of communication of air quality health risk and mitigation measures.

TFOS Lifestyle Report: Impact of environmental conditions on the ocular surface

Environmental risk factors that have an impact on the ocular surface were reviewed and associations with age and sex, race/ethnicity, geographical area, seasonality, prevalence and possible interactions between risk factors are reviewed. Environmental factors can be (a) climate-related: temperature, humidity, wind speed, altitude, dew point, ultraviolet light, and allergen or (b) outdoor and indoor pollution: gases, particulate matter, and other sources of airborne pollutants. Temperature affects ocular surface homeostasis directly and indirectly, precipitating ocular surface diseases and/or symptoms, including trachoma. Humidity is negatively associated with dry eye disease. There is little data on wind speed and dewpoint. High altitude and ultraviolet light exposure are associated with pterygium, ocular surface degenerations and neoplastic disease. Pollution is associated with dry eye disease and conjunctivitis. Primary Sjögren syndrome is associated with exposure to chemical solvents. Living within a potential zone of active volcanic eruption is associated with eye irritation. Indoor pollution, "sick" building or house can also be associated with eye irritation. Most ocular surface conditions are multifactorial, and several environmental factors may contribute to specific diseases. A systematic review was conducted to answer the following research question: "What are the associations between outdoor environment pollution and signs or symptoms of dry eye disease in humans?" Dry eye disease is associated with air pollution (from NO2) and soil pollution (from chromium), but not from air pollution from CO or PM10. Future research should adequately account for confounders, follow up over time, and report results separately for ocular surface findings, including signs and symptoms.

Public engagement with air quality data: using health behaviour change theory to support exposure-minimising behaviours

Exposure to air pollution prematurely kills 7 million people globally every year. Policy measures designed to reduce emissions of pollutants, improve ambient air and consequently reduce health impacts, can be effective, but are generally slow to generate change. Individual actions can therefore supplement policy measures and more immediately reduce people's exposure to air pollution. Air quality indices (AQI) are used globally (though not universally) to translate complex air quality data into a single unitless metric, which can be paired with advice to encourage behaviour change. Here we explore, with reference to health behaviour theories, why these are frequently insufficient to instigate individual change. We examine the health behaviour theoretical steps linking air quality data with reduced air pollution exposure and (consequently) improved public health, arguing that a combination of more 'personalised' air quality data and greater public engagement with these data will together better support individual action. Based on this, we present a novel framework, which, when used to shape air quality interventions, has the potential to yield more effective and sustainable interventions to reduce individual exposures and thus reduce the global public health burden of air pollution.

MEDEA randomised intervention study protocol in Cyprus, Greece and Israel for mitigation of desert dust health effects in adults with atrial fibrillation

INTRODUCTION

Mediterranean countries experience frequent desert dust storm (DDS) events originating from neighbouring Sahara and Arabian deserts, which are associated with significant increase in mortality and hospital admissions, mostly from cardiovascular and respiratory diseases. Short-term exposure to ambient air pollution is considered as a trigger for symptomatic exacerbations of pre-existing paroxysmal atrial fibrillation (AF) and other types of heart arrhythmia. The Mitigating the Health Effects of Desert Dust Storms Using Exposure-Reduction Approaches clinical randomised intervention study in adults with AF is funded by EU LIFE+programme to evaluate the efficacy of recommendations aiming to reduce exposure to desert dust and related heart arrhythmia effects.

METHODS AND ANALYSIS

The study is performed in three heavily exposed to desert dust regions of the Eastern Mediterranean: Cyprus, Israel and Crete-Greece. Adults with paroxysmal AF and implanted pacemaker are recruited and randomised to three parallel groups: (a) no intervention, (b) interventions to reduce outdoor exposure to desert dust, (c) interventions to reduce both outdoor and indoor exposure to particulate matter during desert dust episodes. Eligible participants are enrolled on a web-based platform which communicates, alerts and makes exposure reduction recommendations during DDS events. Exposure changes are assessed by novel tools (smartwatches with Global Positioning System and physical activity sensors, air pollution samplers assessing air quality inside and outside participant's homes, etc). Clinical outcomes include the AF burden expressed as the percentage of time with paroxysmal AF over the total study period, the incidence of ventricular arrhythmia episodes as recorded by the participants' pacemakers or cardioverters/defibrillators and the disease-specific Atrial Fibrillation Effect on QualiTy-of-Life questionnaire.

ETHICS AND DISSEMINATION

Local bioethics' authorities approved the study at all sites, according to national legislations (Cyprus: National Bioethics Committee, Data Protection Commissioner and Ministry of Health; Greece, Scientific Committee and Governing Board of the University General Hospital of Heraklion; Israel: Institutional Review Board ('Helsinki committee') of the Soroka University Medical Center). The findings will be publicised in peer-reviewed scientific journals, in international conferences and in professional websites and newsletters. A summary of the results and participants' interviews will be included in a documentary in English, Greek and Hebrew.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Identifier; NCT03503812.

Aerosol Measurement Degradation in Low-Cost Particle Sensors Using Laboratory Calibration and Field Validation

Increasing concern over air pollution has led to the development of low-cost sensors suitable for wide-scale deployment and use by citizen scientists. This project investigated the AirU low-cost particle sensor using two methods: (1) a comparison of pre- and post-deployment calibration equations for 24 devices following use in a field study, and (2) an in-home comparison between 3 AirUs and a reference instrument, the GRIMM 1.109. While differences (and therefore some sensor degradation) were found in the pre- and post-calibration equation comparison, absolute value changes were small and unlikely to affect the quality of results. Comparison tests found that while the AirU did tend to underestimate minimum and overestimate maximum concentrations of particulate matter, ~88% of results fell within ±1 μg/m³ of the GRIMM. While these tests confirm that low-cost sensors such as the AirU do experience some sensor degradation over multiple months of use, they remain a valuable tool for exposure assessment studies. Further work is needed to examine AirU performance in different environments for a comprehensive survey of capability, as well as to determine the source of sensor degradation.

Inter-annual variability of source contributions to PM10, PM2.5, and oxidative potential in an urban background site in the central mediterranean

Airborne particulate matter (PM) is studied because of its effects on human health and climate change. PM long-term characterisation allows identifying trends and evaluating the outcomes of environmental protection policies. This work is aimed to study the inter-annual variability of PM_2.5 and PM₁₀ concentrations and chemical composition in an urban background site (Italy). A dataset of daily PM_2.5 and PM₁₀ was collected in the period 2016-2017, including the content of OC, EC, major water-soluble ions, main metals, and compared to a similar dataset collected in the period 2013-2014. Oxidative potential using DTT assay (dithiothreitol) was evaluated and expressed in DTT_V as 0.39 nmol/min·m³ in PM₁₀ and 0.29 in PM_2.5 nmol/min·m³. PM source apportionment was computed using the EPA PMF5.0 model and source contributions compared with those of a previous dataset collected between 2013 and 2014. Multi linear regression analysis identified which source contributed (p < 0.05) to the oxidative potential of each size fraction. Inter-annual trends were more evident on PM_2.5 with reductions of biomass burning contribution and increases in traffic contribution in the 2016-2017 period. Crustal contributions were similar for the two periods, in both size fractions. Carbonates were comparable in PM₁₀ with a slight increase in PM_2.5. Sea spray decreased in PM₁₀. The DTT_V of PM_2.5 peaked during cold periods, while, the DTT_V of the PM_10-2.5 fraction peaked in summer, suggesting that different sources, with different seasonality, influence OP in the PM_2.5 and PM_10-2.5 fractions. Analysis showed that sea spray, crustal, and carbonates sources contribute ∼13.6% to DTT_V in PM_2.5 and ∼62.4% to DTT_V in PM_10-2.5. Combustion sources (biomass burning and traffic) contribute to the majority of DTT_V (50.6%) in PM_2.5 and contribute for ∼26% to DTT_V in PM_10-2.5. Secondary nitrate contributes to DTT_V in both fine and coarse fraction; secondary sulphate contribute to DTT_V in PM_2.5 with negligible contributions to DTT_V in PM_10-2.5.

Effectiveness of a Protocol to Reduce Children's Exposure to Particulate Matter and NO2 in Schools during Alert Days

Reducing children's exposure to air pollutants should be considered a primary goal, especially for the most vulnerable subjects. The goal of this study was to test the effectiveness of applying a protocol in the event of alert days, i.e., days with forecasted PM₁₀ levels above the EU limit value (50 µg/m³). The test was conducted, before the onset of SARS-CoV-2 restrictions, in a classroom of a primary school in Parma (Italy)-a highly polluted area in Northern Italy. The protocol included indications for the frequency of opening windows and doors, as well as the activation of an air purifier. Teachers and students were asked to apply the protocol only in the event of alert days, while no indications were provided for non-alert days. A monitoring system measuring PM₁, PM_2.5, PM₁₀, CO₂, and NO₂ was deployed in the classroom. Measurements of the same parameters were also performed outdoors near the school. The application of the protocol reduced the indoor/outdoor (I/O) ratio for all toxic pollutants. The reduction was also remarkable for PM₁₀-the most critical air quality parameter in the study area (1.5 and 1.1 for non-alert and alert days, respectively). Indoor concentrations of PM₁₀-especially during non-alert days-were often higher than outdoors, showing a major contribution from resuspension due to the movement of people and personal cloud. The protocol did not cause any increase in indoor CO₂ levels. Our findings showed that the application of a ventilation protocol together with the contribution of an air purifier may represent an effective way to reduce children's exposure to air pollution during severe air pollution episodes. Considering the onset of COVID-19 and the airborne transmission of pathogens, this protocol now has more meaningful implications for children's welfare, and can be integrated with protocols designed as measures against the spread of SARS-CoV-2.

Estimating the Impact of Air Pollution on Healthcare-Seeking Behaviour by Applying a Difference-in-Differences Method to Syndromic Surveillance Data

Syndromic surveillance data were used to estimate the direct impact of air pollution on healthcare-seeking behaviour, between 1 April 2012 and 31 December 2017. A difference-in-differences approach was used to control for spatial and temporal variations that were not due to air pollution and a meta-analysis was conducted to combine estimates from different pollution periods. Significant increases were found in general practitioner (GP) out-of-hours consultations, including a 98% increase (2–386, 95% confidence interval) in acute bronchitis and a 16% (3–30) increase in National Health Service (NHS) 111 calls for eye problems. However, the numbers involved are small; for instance, roughly one extra acute bronchitis consultation in a local authority on a day when air quality is poor. These results provide additional information for healthcare planners on the impacts of localised poor air quality. However, further work is required to identify the separate impact of different pollutants.

Ambient Air Pollution and Kawasaki Disease in Korean Children: A Study of the National Health Insurance Claim Data

Background

Kawasaki disease (KD) is a systemic vasculitis of unknown etiology that primarily affects children under 5 years of age. Some researchers suggested a potential triggering effect of air pollution on KD, but the findings are inconsistent and limited by small sample size. We investigated the association between ambient air pollution and KD among the population of South Korea younger than 5 years using the National Health Insurance claim data between 2007 and 2019.

Methods and Results

We obtained the data regarding particulate matter ≤10 or 2.5 µm in diameter, nitrogen dioxide, sulfur dioxide, carbon monoxide, and ozone from 235 regulatory monitoring stations. Using a time‐stratified case‐crossover design, we performed conditional logistic regression to estimate odds ratios (OR) of KD according to interquartile range increases in each air pollutant concentration on the day of fever onset after adjusting for temperature and relative humidity. We identified 51 486 children treated for KD during the study period. An interquartile range increase (14.67 μg/m³) of particulate matter ≤2.5 µm was positively associated with KD at lag 1 (OR, 1.016; 95% CI, 1.004–1.029). An interquartile range increase (2.79 ppb) of sulfur dioxide concentration was associated with KD at all lag days (OR, 1.018; 95% CI, 1.002–1.034 at lag 0; OR, 1.022; 95% CI, 1.005–1.038 at lag 1; OR, 1.017; 95% CI, 1.001–1.033 at lag 2). Results were qualitatively similar in the second scenario of different fever onset, 2‐pollutant model and sensitivity analyses.

Conclusions

In a KD‐focused national cohort of children, exposure to particulate matter ≤2.5 µm and sulfur dioxide was positively associated with the risk of KD. This finding supports the triggering role of ambient air pollution in the development of KD.

Monitoring Particulate Matter with Wearable Sensors and the Influence on Student Environmental Attitudes

The mobile monitoring of air pollution is a growing field, prospectively filling in spatial gaps while personalizing air-quality-based risk assessment. We developed wearable sensors to record particulate matter (PM), and through a community science approach, students of partnering Chicago high schools monitored PM concentrations during their commutes over a five- and thirteen-day period. Our main objective was to investigate how mobile monitoring influenced students' environmental attitudes and we did this by having the students explore the relationship between PM concentrations and urban vegetation. Urban vegetation was approximated with a normalized difference vegetation index (NDVI) using Landsat 8 satellite imagery. While the linear regression for one partner school indicated a negative correlation between PM and vegetation, the other indicated a positive correlation, contrary to our expectations. Survey responses were scored on the basis of their environmental affinity and knowledge. There were no significant differences between cumulative pre- and post-experiment survey responses at Josephinum Academy, and only one weakly significant difference in survey results at DePaul Prep in the Knowledge category. However, changes within certain attitudinal subscales may possibly suggest that students were inclined to practice more sustainable behaviors, but perhaps lacked the resources to do so.

Pandemic meets pollution: Poor air quality increases deaths by COVID-19

We study the impact of short-term exposure to ambient air pollution on the spread and severity of COVID-19 in Germany. We combine data at the county-by-day level on confirmed cases and deaths with information on local air quality and weather conditions. Following Deryugina et al. (2019), we instrument short-term variation in local concentrations of particulate matter (PM10) by region-specific daily variation in wind directions. We find significant positive effects of PM10 concentration on death numbers from four days before to ten days after the onset of symptoms. Specifically, for elderly patients (80+ years) an increase in ambient PM10 concentration by one standard deviation between two and four days after developing symptoms increases the number of deaths by 19 percent of a standard deviation. In addition, higher levels air pollution raise the number of confirmed cases of COVID-19 for all age groups. The timing of effects surrounding the onset of illness suggests that air pollution affects the severity of already-realized infections. We discuss the implications of our results for immediate policy levers to reduce the exposure and level of ambient air pollution, as well as for cost-benefit considerations of policies aiming at sustainable longer-term reductions of pollution levels.

Spatial variation in the joint effect of extreme heat events and ozone on respiratory hospitalizations in California

Extreme heat and ozone are co-occurring exposures that independently and synergistically increase the risk of respiratory disease. To our knowledge, no joint warning systems consider both risks; understanding their interactive effect can warrant use of comprehensive warning systems to reduce their burden. We examined heterogeneity in joint effects (on the additive scale) between heat and ozone at small geographical scales. A within-community matched design with a Bayesian hierarchical model was applied to study this association at the zip code level. Spatially varying relative risks due to interaction (RERI) were quantified to consider joint effects. Determinants of the spatial variability of effects were assessed using a random effects metaregression to consider the role of demographic/neighborhood characteristics that are known effect modifiers. A total of 817,354 unscheduled respiratory hospitalizations occurred in California from 2004 to 2013 in the May to September period. RERIs revealed no additive interaction when considering overall joint effects. However, when considering the zip code level, certain areas observed strong joint effects. A lower median income, higher percentage of unemployed residents, and exposure to other air pollutants within a zip code drove stronger joint effects; a higher percentage of commuters who walk/bicycle, a marker for neighborhood wealth, showed decreased effects. Results indicate the importance of going beyond average measures to consider spatial variation in the health burden of these exposures and predictors of joint effects. This information can be used to inform early warning systems that consider both heat and ozone to protect populations from these deleterious effects in identified areas.

Associations between air pollutant exposure and renal function: A prospective study of older adults without chronic kidney disease

We used real-world exposure scenarios to evaluate the effect of six ambient air pollutant (PM_2.5, PM₁₀, NO₂, SO₂, CO, and O₃) exposure on renal function among older adults without chronic kidney disease (CKD). We recruited 169 older adults without CKD in Beijing, China, for a longitudinal study from 2016 to 2018. The Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (EPI) equations were employed to derive the estimated glomerular filtration rate (eGFR). A linear mixed-effects model with random intercepts for participants was employed to determine the effects of air pollutants on renal function evaluated on the basis of eGFR and urinary albumin/creatinine ratio at different exposure windows (1-, 2-, 3-, 5-, 7-, 14-, 28-, 45-, and 60-days moving averages). An interquartile range (IQR) increase in NO₂ for was associated with significant decreases of in eGFR (MDRD equation) [percentage changes: -4.49 (95% confidence interval: -8.44, -0.37), -5.51 (-10.43, -0.33), -2.26 (-4.38, -0.08), -3.71 (-6.67, -0.65), -5.44 (-9.58, -1.11), -5.50 (-10.24, -0.51), -6.15 (-10.73, -1.33), and -6.34 (-11.17, -1.25) for 1-, 2-, 5-, 7-, 14-, 28-, 45-, and 60-days moving averages, respectively] and in eGFR (EPI equation) [percentage changes: -5.04 (-7.09, -2.94), -6.25 (-8.81, -3.62), -5.16 (-7.34, -2.92), -5.10 (-7.85, -2.28), -5.83 (-8.23, -3.36), -6.04 (-8.55, -3.47) for 1-, 2-, 14-, 28-, 45-, and 60-days moving averages, respectively]. In two-pollutant model, only the association of NO₂ exposure with eGFR remained robust after adjustment for any other pollutant. This association was stronger for individuals with hypertension for the EPI equation or BMI <25 kg/m² for the MDRD equation at lags 1 and 1-2. Our findings suggest that NO₂ exposure is associated with eGFR reduction among older adults without CKD for short (1-, 2-days) and medium (14-, 28-, 45-, 60-days) term exposure periods; thus, NO₂ exposure may contribute to renal impairment.

From a Low-Cost Air Quality Sensor Network to Decision Support Services: Steps towards Data Calibration and Service Development

Air pollution is a widespread problem due to its impact on both humans and the environment. Providing decision makers with artificial intelligence based solutions requires to monitor the ambient air quality accurately and in a timely manner, as AI models highly depend on the underlying data used to justify the predictions. Unfortunately, in urban contexts, the hyper-locality of air quality, varying from street to street, makes it difficult to monitor using high-end sensors, as the cost of the amount of sensors needed for such local measurements is too high. In addition, development of pollution dispersion models is challenging. The deployment of a low-cost sensor network allows a more dense cover of a region but at the cost of noisier sensing. This paper describes the development and deployment of a low-cost sensor network, discussing its challenges and applications, and is highly motivated by talks with the local municipality and the exploration of new technologies to improve air quality related services. However, before using data from these sources, calibration procedures are needed to ensure that the quality of the data is at a good level. We describe our steps towards developing calibration models and how they benefit the applications identified as important in the talks with the municipality.

Impact of air pollution on renal outcomes: a systematic review and meta-analysis protocol

INTRODUCTION

Chronic kidney disease is a serious and a frequent disease associated with a high risk of morbi-mortality. Although several risk factors have already been well addressed, mostly diabetes and hypertension, many remain underappreciated, such as chronic exposure to air pollution.

METHODS AND ANALYSIS

We will search EMBASE, PubMed, Web of Science, Cochrane Library and CINAHL database, from inception to 31 March 2020, for relevant records using a combination of keywords related to the type of exposure (ozone, carbon monoxide, nitrogen oxides and dioxide, sulfur dioxide, PM_2.5, PM_coarse and PM₁₀) and to the type of outcome (chronic kidney disease, end-stage renal/kidney disease, kidney failure, proteinuria/albuminuria, renal function, renal transplant, kidney graft, kidney transplant failure, nephrotic syndrome and kidney cancer). The review will be reported according to the guidelines of the Meta-analysis Of Observational Studies in Epidemiology. Two independent reviewers will select studies without design or language restrictions, using original data and investigating the association between exposure to one or more of the prespecified air pollutants and subsequent risk of renal outcomes. Using random-effects meta-analyses, we will present pooled summary statistics (HR, OR or beta-coefficients with their respective 95% CI) associated with a standardised increase in each pollutant level. The results will be presented by air pollutant and outcome. Heterogeneity will be assessed using the χ² test on Cochran's Q statistic and quantified by calculating I². The Egger's test and visual inspection of funnel plots will be used to assess publication bias.

ETHICS AND DISSEMINATION

Since primary data are not collected in this study, ethical approval is not required. This review is expected to provide relevant data on the associations between various air pollutants' exposure and renal outcomes. The final report will be published in an international peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42020187956.

Top-Down Estimation of Particulate Matter Emissions from Extreme Tropical Peatland Fires Using Geostationary Satellite Fire Radiative Power Observations

Extreme fires in the peatlands of South East (SE) Asia are arguably the world’s greatest biomass burning events, resulting in some of the worst ambient air pollution ever recorded (PM₁₀ > 3000 µg·m⁻³). The worst of these fires coincide with El Niño related droughts, and include huge areas of smouldering combustion that can persist for months. However, areas of flaming surface vegetation combustion atop peat are also seen, and we show that the largest of these latter fires appear to be the most radiant and intensely smoke-emitting areas of combustion present in such extreme fire episodes. Fire emissions inventories and early warning of the air quality impacts of landscape fire are increasingly based on the fire radiative power (FRP) approach to fire emissions estimation, including for these SE Asia peatland fires. “Top-down” methods estimate total particulate matter emissions directly from FRP observations using so-called “smoke emission coefficients” [C_e; g·MJ⁻¹], but currently no discrimination is made between fire types during such calculations. We show that for a subset of some of the most thermally radiant peatland fires seen during the 2015 El Niño, the most appropriate C_e is around a factor of three lower than currently assumed (~16.8 ± 1.6 g·MJ⁻¹ vs. 52.4 g·MJ⁻¹). Analysis indicates that this difference stems from these highly radiant fires containing areas of substantial flaming combustion, which changes the amount of particulate matter emitted per unit of observable fire radiative heat release in comparison to more smouldering dominated events. We also show that even a single one of these most radiant fires is responsible for almost 10% of the overall particulate matter released during the 2015 fire event, highlighting the importance of this fire type to overall emission totals. Discriminating these different fires types in ways demonstrated herein should thus ultimately improve the accuracy of SE Asian fire emissions estimates derived using the FRP approach, and the air quality modelling which they support.

Air Pollution and Asthma: Critical Targets for Effective Action

Evidence to advocate for cleaner air for people with asthma is not in short supply. We know that air pollution is associated with the development and worsening of the condition and that mitigating interventions can improve respiratory outcomes. We have clear targets, particularly traffic emissions, especially in urban areas, and plenty of potentially effective actions. Road traffic must be reduced, and what remains should be cleaner and greener. Urban green spaces, safe cycle networks and wider pavements will promote active travel and leisure time exercise. Healthcare professionals must ensure people are aware of their air quality, its impact on asthma and the appropriate behaviour to safeguard health. What remains are realistic policies and effective measures, based on the correct scientific evidence, to be taken forth with political courage and investment so that air pollution no longer contributes to the development or worsening of respiratory ill health.

Spatial mapping and size distribution of oxidative potential of particulate matter released by spatially disaggregated sources

The ability of particulate matter (PM) to induce oxidative stress is frequently estimated by acellular oxidative potential (OP) assays, such as ascorbic acid (AA) and 1,4-dithiothreitol (DTT), used as proxy of reactive oxygen species (ROS) generation in biological systems, and particle-bound ROS measurement, such as 2',7'-dichlorodihydrofluorescein (DCFH) assay. In this study, we evaluated the spatial and size distribution of OP results obtained by three OP assays (OP^AA, OP^DCFH and OP^DTT), to qualitative identify the relative relevance of single source contributions in building up OP values and to map the PM potential to induce oxidative stress in living organisms. To this aim, AA, DCFH and DTT assays were applied to size-segregated PM samples, collected by low-pressure cascade impactors, and to PM₁₀ samples collected at 23 different sampling sites (about 1 km between each other) in Terni, an urban and industrial hot-spot of Central Italy, by using recently developed high spatial resolution samplers of PM, which worked in parallel during three monitoring periods (February, April and December 2017). The sampling sites were chosen for representing the main spatially disaggregated sources of PM (vehicular traffic, rail network, domestic heating, power plant for waste treatment, steel plant) present in the study area. The obtained results clearly showed a very different sensitivity of the three assays toward each local PM source. OP^AA was particularly sensitive toward coarse particles released from the railway, OP^DCFH was sensible to fine particles released from the steel plant and domestic biomass heating, and OP^DTT was quite selectively sensitive toward the fine fraction of PM released by industrial and biomass burning sources.

Airborne Aerosols and Human Health: Leapfrogging from Mass Concentration to Oxidative Potential

The mass concentration of atmospheric particulate matter (PM) has been systematically used in epidemiological studies as an indicator of exposure to air pollutants, connecting PM concentrations with a wide variety of human health effects. However, these effects can be hardly explained by using one single parameter, especially because PM is formed by a complex mixture of chemicals. Current research has shown that many of these adverse health effects can be derived from the oxidative stress caused by the deposition of PM in the lungs. The oxidative potential (OP) of the PM, related to the presence of transition metals and organic compounds that can induce the production of reactive oxygen and nitrogen species (ROS/RNS), could be a parameter to evaluate these effects. Therefore, estimating the OP of atmospheric PM would allow us to evaluate and integrate the toxic potential of PM into a unique parameter, which is related to emission sources, size distribution and/or chemical composition. However, the association between PM and particle-induced toxicity is still largely unknown. In this commentary article, we analyze how this new paradigm could help to deal with some unanswered questions related to the impact of atmospheric PM over human health.

Transient risk of ambient fine particulate matter on hourly cardiovascular events in Tainan City, Taiwan

BACKGROUND

The association between daily changes in ambient fine particulate matter (PM2.5) and cardiovascular diseases have been well established in mechanistic, epidemiologic and exposure studies. Only a few studies examined the effect of hourly variations in air pollution on triggering cardiovascular events. Whether the current PM2.5 standards can protect vulnerable individuals with chronic cardiovascular diseases remain uncertain.

METHODS

we conducted a time-stratified, case-crossover study to assess the associations between hourly changes in PM2.5 levels and the vascular disease onset in residents of Tainan City, Taiwan, visiting Emergency Room of Chi Mei Medical Center between January 2006 and December 2016. There were 26,749 cases including 10,310 females (38.5%) and 16,439 males (61.5%) identified. The time of emergency visit was identified as the onset for each case and control cases were selected as the same times on other days, on the same day of the week in the same month and year respectively. Residential address was used to identify the ambient air pollution exposure concentrations from the closest station. Conditional logistic regression with the stepwise selection method was used to estimate adjusted odds ratios (ORs) for the association.

RESULTS

When we only included cases occurring at PM2.5>10 μg/m3 and PM2.5>25 μg/m3, very significant ORs could be observed for 10 μg/m3 increases in PM2.5 at 0 and 1 hour, implying fine particulate exposure could promptly trigger vascular disease events. Moreover, a very clear increase in risk could be observed with cumulative exposure from 0 to 48 hours, especially in those cases where PM2.5>25 μg/m3.

CONCLUSIONS

Our study demonstrated that transient and low concentrations of ambient PM2.5 trigger adult vascular disease events, especially cerebrovascular disease, regardless of age, sex, and exposure timing. Warning and delivery systems should be setup to protect people from these prompt adverse health impacts.

Pollutants and Their Interaction with Diseases of Social Hymenoptera

Many insect species, including social insects, are currently declining in abundance and diversity. Pollutants such as pesticides, heavy metals, or airborne fine particulate matter from agricultural and industrial sources are among the factors driving this decline. While these pollutants can have direct detrimental effects, they can also result in negative interactive effects when social insects are simultaneously exposed to multiple stressors. For example, sublethal effects of pollutants can increase the disease susceptibility of social insects, and thereby jeopardize their survival. Here we review how pesticides, heavy metals, or airborne fine particulate matter interact with social insect physiology and especially the insects’ immune system. We then give an overview of the current knowledge of the interactive effects of these pollutants with pathogens or parasites. While the effects of pesticide exposure on social insects and their interactions with pathogens have been relatively well studied, the effects of other pollutants, such as heavy metals in soil or fine particulate matter from combustion, vehicular transport, agriculture, and coal mining are still largely unknown. We therefore provide an overview of urgently needed knowledge in order to mitigate the decline of social insects.

Vanadium Derivative Exposure Promotes Functional Alterations of VSMCs and Consequent Atherosclerosis via ROS/p38/NF-κB-Mediated IL-6 Production

Vanadium is a transition metal widely distributed in the Earth’s crust, and is a major contaminant in fossil fuels. Its pathological effect and regulation in atherosclerosis remain unclear. We found that intranasal administration of the vanadium derivative NaVO₃ significantly increased plasma and urinary vanadium levels and induced arterial lipid accumulation and atherosclerotic lesions in apolipoprotein E-deficient knockout mice (ApoE^−/−) murine aorta compared to those in vehicle-exposed mice. This was accompanied by an increase in plasma reactive oxygen species (ROS) and interleukin 6 (IL-6) levels and a decrease in the vascular smooth muscle cell (VSMC) differentiation marker protein SM22α in the atherosclerotic lesions. Furthermore, exposure to NaVO₃ or VOSO₄ induced cytosolic ROS generation and IL-6 production in VSMCs and promoted VSMC synthetic differentiation, migration, and proliferation. The anti-oxidant N-acetylcysteine (NAC) not only suppresses IL-6 production and VSMC pathological responses including migration and proliferation but also prevents atherosclerosis in ApoE^−/− mice. Inhibition experiments with NAC and pharmacological inhibitors demonstrated that NaVO₃-induced IL-6 production is signaled by ROS-triggered p38-mediated NF-κB-dependent pathways. Neutralizing anti-IL-6 antibodies impaired NaVO₃-mediated VSMC migration and proliferation. We concluded that NaVO₃ exposure activates the ROS-triggering p38 signaling to selectively induce NF-κB-mediated IL-6 production. These signaling pathways induce VSMC synthetic differentiation, migration, and proliferation, leading to lipid accumulation and atherosclerosis.

Toward an Improved Air Pollution Warning System in Quebec

The nature of pollutants involved in smog episodes can vary significantly in various cities and contexts and will impact local populations differently due to actual exposure and pre-existing sensitivities for cardiovascular or respiratory diseases. While regulated standards and guidance remain important, it is relevant for cities to have local warning systems related to air pollution. The present paper proposes indicators and thresholds for an air pollution warning system in the metropolitan areas of Montreal and Quebec City (Canada). It takes into account past and current local health impacts to launch its public health warnings for short-term episodes. This warning system considers fine particulate matter (PM_2.5) as well as the combined oxidant capacity of ozone and nitrogen dioxide (O_x) as environmental exposures. The methodology used to determine indicators and thresholds consists in identifying extreme excess mortality episodes in the data and then choosing the indicators and thresholds to optimize the detection of these episodes. The thresholds found for the summer were 31 μg/m³ for PM_2.5 and 43 ppb for O_x in Montreal, and 32 μg/m³ and 23 ppb in Quebec City. In winter, thresholds found were 25 μg/m³ and 26 ppb in Montreal, and 33 μg/m³ and 21 ppb in Quebec City. These results are in line with different guidelines existing concerning air quality, but more adapted to the cities examined. In addition, a sensitivity analysis is conducted which suggests that O_x is more determinant than PM_2.5 in detecting excess mortality episodes.

Evaluation of the Impacts of a Phone Warning and Advising System for Individuals Vulnerable to Smog. Evidence from a Randomized Controlled Trial Study in Canada

Smog warning systems are components of adaptation strategies that are adopted by governments around the world to protect their citizens from extreme episodes of air pollution. As part of a growing research stream on the effectiveness of these systems, this article presents the results of a study on the impacts of an automated phone warning and advising system for individuals vulnerable to air pollution. A sample of 1328 individuals were recruited and randomly assigned to treatment and control groups. The treatment group received smog warning while the control group did not. Data were collected via three phone surveys, two before and one after issuing the smog warning. The comparison between treatment and control groups indicates that exposure to a smog warning improved information on the occurrence of smog episodes (n = 484, OR = 5.58, p = 0.00), and knowledge on protective behaviors. Furthermore, members of treatment group were more likely to avoid exposure to smog episodes by spending more time inside with the windows closed than usual (n = 474, OR = 2.03, p = 0.00). Members of treatment group who take medication in the form of aerosol pumps also kept these devices on themselves more frequently than those of control group (n= 109, OR = 2.15, p = 0.03). The system however had no discernible effects on the awareness of air pollution risks, reduction of health symptoms related to smog and the use of health system services. The absence of health benefits could be related to the lower actual exposure to air pollution of such vulnerable groups during winter.

A Novel Method for Improving Air Pollution Prediction Based on Machine Learning Approaches: A Case Study Applied to the Capital City of Tehran

Environmental pollution has mainly been attributed to urbanization and industrial developments across the globe. Air pollution has been marked as one of the major problems of metropolitan areas around the world, especially in Tehran, the capital of Iran, where its administrators and residents have long been struggling with air pollution damage such as the health issues of its citizens. As far as the study area of this research is concerned, a considerable proportion of Tehran air pollution is attributed to PM10 and PM2.5 pollutants. Therefore, the present study was conducted to determine the prediction models to determine air pollutions based on PM10 and PM2.5 pollution concentrations in Tehran. To predict the air-pollution, the data related to day of week, month of year, topography, meteorology, and pollutant rate of two nearest neighbors as the input parameters and machine learning methods were used. These methods include a regression support vector machine, geographically weighted regression, artificial neural network and auto-regressive nonlinear neural network with an external input as the machine learning method for the air pollution prediction. A prediction model was then proposed to improve the afore-mentioned methods, by which the error percentage has been reduced and improved by 57%, 47%, 47% and 94%, respectively. The most reliable algorithm for the prediction of air pollution was autoregressive nonlinear neural network with external input using the proposed prediction model, where its one-day prediction error reached 1.79 µg/m3. Finally, using genetic algorithm, data for day of week, month of year, topography, wind direction, maximum temperature and pollutant rate of the two nearest neighbors were identified as the most effective parameters in the prediction of air pollution.

Air pollution and kidney disease: review of current evidence

Along with amazing technological advances, the industrial revolution of the mid-19th century introduced new sources of pollution. By the mid-20th century, the effects of these changes were beginning to be felt around the world. Among these changes, health problems due to environmental air pollution are increasingly recognized. At the beginning, respiratory and cardiovascular diseases were emphasized. However, accumulated data indicate that every organ system in the body may be involved, and the kidney is no exception. Although research on air pollution and kidney damage is recent, there is now scientific evidence that air pollution harms the kidney. In this holistic review, we have summarized the epidemiology, disease states and mechanisms of air pollution and kidney damage.

Air pollutants and early origins of respiratory diseases

Air pollution is a global health threat and causes millions of human deaths annually. The late onset of respiratory diseases in children and adults due to prenatal or perinatal exposure to air pollutants is emerging as a critical concern in human health. Pregnancy and fetal development stages are highly susceptible to environmental exposure and tend to develop a long-term impact in later life. In this review, we briefly glance at the direct impact of outdoor and indoor air pollutants on lung diseases and pregnancy disorders. We further focus on lung complications in later life with early exposure to air pollutants. Epidemiological evidence is provided to show the association of prenatal or perinatal exposure to air pollutants with various adverse birth outcomes, such as preterm birth, lower birth weight, and lung developmental defects, which further associate with respiratory diseases and reduced lung function in children and adults. Mechanistic evidence is also discussed to support that air pollutants impact various cellular and molecular targets at early life, which link to the pathogenesis and altered immune responses related to abnormal respiratory functions and lung diseases in later life.

Assessing air quality index awareness and use in Mexico City

BACKGROUND

The Mexico City Metropolitan Area has an expansive urban population and a long history of air quality management challenges. Poor air quality has been associated with adverse pulmonary and cardiac health effects, particularly among susceptible populations with underlying disease. In addition to reducing pollution concentrations, risk communication efforts that inform behavior modification have the potential to reduce public health burdens associated with air pollution.

METHODS

This study investigates the utilization of Mexico's IMECA risk communication index to inform air pollution avoidance behavior among the general population living in the Mexico City Metropolitan Area. Individuals were selected via probability sampling and surveyed by phone about their air quality index knowledge, pollution concerns, and individual behaviors.

RESULTS

The results indicated reasonably high awareness of the air quality index (53% of respondents), with greater awareness in urban areas, among older and more educated individuals, and for those who received air quality information from a healthcare provider. Additionally, behavior modification was less influenced by index reports as it was by personal perceptions of air quality, and there was no difference in behavior modification among susceptible and non-susceptible groups.

CONCLUSIONS

Taken together, these results suggest there are opportunities to improve the public health impact of risk communication through an increased focus on susceptible populations and greater encouragement of public action in response to local air quality indices.

Environmental pollution and kidney diseases

The burden of disease and death attributable to environmental pollution is becoming a public health challenge worldwide, especially in developing countries. The kidney is vulnerable to environmental pollutants because most environmental toxins are concentrated by the kidney during filtration. Given the high mortality and morbidity of kidney disease, environmental risk factors and their effect on kidney disease need to be identified. In this Review, we highlight epidemiological evidence for the association between kidney disease and environmental pollutants, including air pollution, heavy metal pollution and other environmental risk factors. We discuss the potential biological mechanisms that link exposure to environmental pollutants to kidney damage and emphasize the contribution of environmental pollution to kidney disease. Regulatory efforts should be made to control environmental pollution and limit individual exposure to preventable or avoidable environmental risk. Population studies with accurate quantification of environmental exposure in polluted regions, particularly in developing countries, might aid our understanding of the dose-response relationship between pollutants and kidney diseases.

Toxicity of Urban PM10 and Relation with Tracers of Biomass Burning

The chemical composition of particles varies with space and time and depends on emission sources, atmospheric chemistry and weather conditions. Evidence suggesting that particles differ in toxicity depending on their chemical composition is growing. This in vitro study investigated the biological effects of PM₁₀ in relation to PM-associated chemicals. PM₁₀ was sampled in ambient air at an urban traffic site (Borgerhout) and a rural background location (Houtem) in Flanders (Belgium). To characterize the toxic potential of PM₁₀, airway epithelial cells (Beas-2B cells) were exposed to particles in vitro. Different endpoints were studied including cell damage and death (cell viability) and the induction of interleukin-8 (IL-8). The mutagenic capacity was assessed using the Ames II Mutagenicity Test. The endotoxin levels in the collected samples were analyzed and the oxidative potential (OP) of PM₁₀ particles was evaluated by electron paramagnetic resonance (EPR) spectroscopy. Chemical characteristics of PM₁₀ included tracers for biomass burning (levoglucosan, mannosan and galactosan), elemental and organic carbon (EC/OC) and polycyclic aromatic hydrocarbons (PAHs). Most samples displayed dose-dependent cytotoxicity and IL-8 induction. Spatial and temporal differences in PM₁₀ toxicity were seen. PM₁₀ collected at the urban site was characterized by increased pro-inflammatory and mutagenic activity as well as higher OP and elevated endotoxin levels compared to the background area. Reduced cell viability (−0.46 < r_s < −0.35, p < 0.01) and IL-8 induction (−0.62 < r_s < −0.67, p < 0.01) were associated with all markers for biomass burning, levoglucosan, mannosan and galactosan. Furthermore, direct and indirect mutagenicity were associated with tracers for biomass burning, OC, EC and PAHs. Multiple regression analyses showed levoglucosan to explain 16% and 28% of the variance in direct and indirect mutagenicity, respectively. Markers for biomass burning were associated with altered cellular responses and increased mutagenic activity. These findings may indicate a role of biomass burning in the observed adverse health effect of particulate matter.

Psychosocial and demographic predictors of adherence and non-adherence to health advice accompanying air quality warning systems: a systematic review

BACKGROUND

Although evidence shows that poor air quality can harm human health, we have a limited understanding about the behavioural impact of air quality forecasts. Our aim was to understand to what extent air quality warning systems influence protective behaviours in the general public, and to identify the demographic and psychosocial factors associated with adherence and non-adherence to the health advice accompanying these warnings.

METHOD

In August 2016 literature was systematically reviewed to find studies assessing intended or actual adherence to health advice accompanying air quality warning systems, and encouraging people to reduce exposure to air pollution. Predictors of adherence to the health advice and/or self-reported reasons for adherence or non-adherence were also systematically reviewed. Studies were included only if they involved participants who were using or were aware of these warning systems. Studies investigating only protective behaviours due to subjective perception of bad air quality alone were excluded. The results were narratively synthesised and discussed within the COM-B theoretical framework.

RESULTS

Twenty-one studies were included in the review: seventeen investigated actual adherence; three investigated intended adherence; one assessed both. Actual adherence to the advice to reduce or reschedule outdoor activities during poor air quality episodes ranged from 9.7% to 57% (Median = 31%), whereas adherence to a wider range of protective behaviours (e.g. avoiding busy roads, taking preventative medication) ranged from 17.7% to 98.1% (Median = 46%). Demographic factors did not consistently predict adherence. However, several psychosocial facilitators of adherence were identified. These include knowledge on where to check air quality indices, beliefs that one's symptoms were due to air pollution, perceived severity of air pollution, and receiving advice from health care professionals. Barriers to adherence included: lack of understanding of the indices, being exposed to health messages that reduced both concern about air pollution and perceived susceptibility, as well as perceived lack of self-efficacy/locus of control, reliance on sensory cues and lack of time.

CONCLUSION

We found frequent suboptimal adherence rates to health advice accompanying air quality alerts. Several psychosocial facilitators and barriers of adherence were identified. To maximise their health effects, health advice needs to target these specific psychosocial factors.

Mitigating the effects of preferentially selected monitoring sites for environmental policy and health risk analysis

The potential effects of air pollution are a major concern both in terms of the environment and in relation to human health. In order to support both environmental and health policy there is a need for accurate estimates of the exposures that populations might experience. The information for this typically comes from environmental monitoring networks but often the locations of monitoring sites are preferentially located in order to detect high levels of pollution. Using the information from such networks has the potential to seriously affect the estimates of pollution that are obtained and that might be used in health risk analyses. In this context, we explore the topic of preferential sampling within a long-standing network in the UK that monitored black smoke due to concerns about its effect on public health, the extent of which came to prominence during the famous London fog of 1952. Abatement measures led to a decline in the levels of black smoke and a subsequent reduction in the number of monitoring locations that were thought necessary to provide the information required for policy support. There is evidence of selection bias during this process with sites being kept in the most polluted areas. We assess the potential for this to affect the estimates of risk associated air pollution and show how using Bayesian spatio-temporal exposure models may be used to attempt to mitigate the effects of preferential sampling in this case.

Effects of an air pollution personal alert system on health service usage in a high-risk general population: a quasi-experimental study using linked data

BACKGROUND

There is no evidence to date on whether an intervention alerting people to high levels of pollution is effective in reducing health service utilisation. We evaluated alert accuracy and the effect of a targeted personal air pollution alert system, airAware, on emergency hospital admissions, emergency department attendances, general practitioner contacts and prescribed medications.

METHODS

Quasi-experimental study describing accuracy of alerts compared with pollution triggers; and comparing relative changes in healthcare utilisation in the intervention group to those who did not sign-up. Participants were people diagnosed with asthma, chronic obstructive pulmonary disease (COPD) or coronary heart disease, resident in an industrial area of south Wales and registered patients at 1 of 4 general practices. Longitudinal anonymised record linked data were modelled for participants and non-participants, adjusting for differences between groups.

RESULTS

During the 2-year intervention period alerts were correctly issued on 208 of 248 occasions; sensitivity was 83.9% (95% CI 78.8% to 87.9%) and specificity 99.5% (95% CI 99.3% to 99.6%). The intervention was associated with a 4-fold increase in admissions for respiratory conditions (incidence rate ratio (IRR) 3.97; 95% CI 1.59 to 9.93) and a near doubling of emergency department attendance (IRR=1.89; 95% CI 1.34 to 2.68).

CONCLUSIONS

The intervention was associated with increased emergency admissions for respiratory conditions. While findings may be context specific, evidence from this evaluation questions the benefits of implementing near real-time personal pollution alert systems for high-risk individuals.

Effects of an air pollution personal alert system on health service usage in a high-risk general population: a quasi-experimental study using linked data

BACKGROUND

There is no evidence to date on whether an intervention alerting people to high levels of pollution is effective in reducing health service utilisation. We evaluated alert accuracy and the effect of a targeted personal air pollution alert system, airAware, on emergency hospital admissions, emergency department attendances, general practitioner contacts and prescribed medications.

METHODS

Quasi-experimental study describing accuracy of alerts compared with pollution triggers; and comparing relative changes in healthcare utilisation in the intervention group to those who did not sign-up. Participants were people diagnosed with asthma, chronic obstructive pulmonary disease (COPD) or coronary heart disease, resident in an industrial area of south Wales and registered patients at 1 of 4 general practices. Longitudinal anonymised record linked data were modelled for participants and non-participants, adjusting for differences between groups.

RESULTS

During the 2-year intervention period alerts were correctly issued on 208 of 248 occasions; sensitivity was 83.9% (95% CI 78.8% to 87.9%) and specificity 99.5% (95% CI 99.3% to 99.6%). The intervention was associated with a 4-fold increase in admissions for respiratory conditions (incidence rate ratio (IRR) 3.97; 95% CI 1.59 to 9.93) and a near doubling of emergency department attendance (IRR=1.89; 95% CI 1.34 to 2.68).

CONCLUSIONS

The intervention was associated with increased emergency admissions for respiratory conditions. While findings may be context specific, evidence from this evaluation questions the benefits of implementing near real-time personal pollution alert systems for high-risk individuals.

The impact of communicating information about air pollution events on public health

Short-term exposure to air pollution has been associated with exacerbation of asthma and chronic obstructive pulmonary disease (COPD). This study investigated the relationship between emergency hospital admissions for asthma, COPD and episodes of poor air quality in an English city (Southampton) from 2008-2013. The city's council provides a forecasting service for poor air quality to individuals with respiratory disease to reduce preventable admissions to hospital and this has been evaluated. Trends in nitrogen dioxide, ozone and particulate matter concentrations were related to hospital admissions data using regression analysis. The impacts of air quality on emergency admissions were quantified using the relative risks associated with each pollutant. Seasonal and weekly trends were apparent for both air pollution and hospital admissions, although there was a weak relationship between the two. The air quality forecasting service proved ineffective at reducing hospital admissions. Improvements to the health forecasting service are necessary to protect the health of susceptible individuals, as there is likely to be an increasing need for such services in the future.

Air pollution and public health: emerging hazards and improved understanding of risk

Despite past improvements in air quality, very large parts of the population in urban areas breathe air that does not meet European standards let alone the health-based World Health Organisation Air Quality Guidelines. Over the last 10 years, there has been a substantial increase in findings that particulate matter (PM) air pollution is not only exerting a greater impact on established health endpoints, but is also associated with a broader number of disease outcomes. Data strongly suggest that effects have no threshold within the studied range of ambient concentrations, can occur at levels close to PM2.5 background concentrations and that they follow a mostly linear concentration-response function. Having firmly established this significant public health problem, there has been an enormous effort to identify what it is in ambient PM that affects health and to understand the underlying biological basis of toxicity by identifying mechanistic pathways-information that in turn will inform policy makers how best to legislate for cleaner air. Another intervention in moving towards a healthier environment depends upon the achieving the right public attitude and behaviour by the use of optimal air pollution monitoring, forecasting and reporting that exploits increasingly sophisticated information systems. Improving air quality is a considerable but not an intractable challenge. Translating the correct scientific evidence into bold, realistic and effective policies undisputedly has the potential to reduce air pollution so that it no longer poses a damaging and costly toll on public health.

Exposure to indoor pollutants and Wheeze and asthma development during early childhood

Background: This review aimed to summarize existing epidemiological evidence of the association between quantitative estimates of indoor air pollution with early childhood respiratory disease. Methods: We carried out a systematic literature search of peer-reviewed epidemiological studies undertaken in “westernized” countries that have assessed exposure to indoor pollutants and asthma and wheeze from infancy up to the age of 5. Results: The search, between January 2004 and February 2014 yielded 1840 studies for consideration. Following application of eligibility criteria to titles and abstracts 22 independent studies were deemed relevant for further review. Two additional studies were next identified through examination of the references’ lists of these studies. Of these 24 selected studies, 16 adopted a prospective cohort design and 8 were case-control studies. Fourteen studies assessed exposure to bio-aerosols, 8 studies assessed exposure to specific air chemicals and two studies assessed exposure to bio-aerosols and air chemicals. Furthermore, 11 studies examined the association of exposure with asthma and 16 with wheeze. Findings indicate that existing studies have reported contradictory effects of indoor pollutants levels and occurrence of asthma/wheeze. Conclusion: Additional research to establish causality and evaluate interventions to prevent disease onset is needed.

Biomarkers of progression of chronic obstructive pulmonary disease (COPD)

Disease progression of chronic obstructive pulmonary disease (COPD) is variable, with some patients having a relatively stable course, while others suffer relentless progression leading to severe breathlessness, frequent acute exacerbations of COPD (AECOPD), respiratory failure and death. Radiological markers such as CT emphysema index, bronchiectasis and coronary artery calcification (CAC) have been linked with increased mortality in COPD patients. Molecular changes in lung tissue reflect alterations in lung pathology that occur with disease progression; however, lung tissue is not routinely accessible. Cell counts (including neutrophils) and mediators in induced sputum have been associated with lung function and risk of exacerbations. Examples of peripheral blood biological markers (biomarkers) include those associated with lung function (reduced CC-16), emphysema severity (increased adiponectin, reduced sRAGE), exacerbations and mortality [increased CRP, fibrinogen, leukocyte count, IL-6, IL-8, and tumor necrosis factor α (TNF-α)] including increased YKL-40 with mortality. Emerging approaches to discovering markers of gene-environment interaction include exhaled breath analysis [volatile organic compounds (VOCs), exhaled breath condensate], cellular and systemic responses to exposure to air pollution, alterations in the lung microbiome, and biomarkers of lung ageing such as telomere length shortening and reduced levels of sirtuins. Overcoming methodological challenges in sampling and quality control will enable more robust yet easily accessible biomarkers to be developed and qualified, in order to optimise personalised medicine in patients with COPD.

Indoor exposure and adverse birth outcomes related to fetal growth, miscarriage and prematurity-a systematic review

The purpose of this review was to summarize existing epidemiological evidence of the association between quantitative estimates of indoor air pollution and all-day personal exposure with adverse birth outcomes including fetal growth, prematurity and miscarriage. We carried out a systematic literature search of MEDLINE and EMBASE databases with the aim of summarizing and evaluating the results of peer-reviewed epidemiological studies undertaken in “westernized” countries that have assessed indoor air pollution and all-day personal exposure with specific quantitative methods. This comprehensive literature search identified 16 independent studies which were deemed relevant for further review and two additional studies were added through searching the reference lists of all included studies. Two reviewers independently and critically appraised all eligible articles using the Critical Appraisal Skills Programme (CASP) tool. Of the 18 selected studies, 14 adopted a prospective cohort design, three were case-controls and one was a retrospective cohort study. In terms of pollutants of interest, seven studies assessed exposure to electro-magnetic fields, four studies assessed exposure to polycyclic aromatic hydrocarbons, four studies assessed PM_2.5 exposure and three studies assessed benzene, phthalates and noise exposure respectively. Furthermore, 12 studies examined infant growth as the main birth outcome of interest, six examined spontaneous abortion and three studies assessed gestational age at birth and preterm delivery. This survey demonstrates that there is insufficient research on the possible association of indoor exposure and early life effects and that further research is needed.

Effects of ambient levels of traffic-derived air pollution on the ocular surface: analysis of symptoms, conjunctival goblet cell count and mucin 5AC gene expression

PURPOSE

To quantify ocular symptoms, goblet cells (GC) and mucin 5AC (MUC5AC) gene expression on the conjunctiva of healthy subjects exposed to ambient levels of traffic-derived air pollution and to estimate its correlation with NO2 and particulate matter smaller than 2.5 μm (PM2.5) levels.

METHODS

Twenty-one taxi drivers or traffic controllers were assessed with the Ocular Surface Disease Index (OSDI) questionnaire and conjunctival impression cytology. MUC5AC mRNA levels were determined based on the cytology of the right eye, and GC density was assessed based on the cytology of the left eye. Mean individual levels of 24-h NO2 and PM2.5 exposure were assessed the day before examination. Possible associations between NO2 or PM2.5 levels, OSDI scores, GC densities and MUC5AC mRNA levels were verified.

RESULTS

The subjects were exposed to mean PM2.5 levels of 35±12 μg/m(3) and mean NO2 levels of 189±47 μg/m(3). OSDI scores were low (7.4±8) and GC densities were 521±257 and 782±322 cell/mm(2) on the bulbar and tarsal conjunctivas, respectively. The mean GC-derived MUC5AC mRNA expression was 14±7 fM/μg of total RNA. A significant and positive correlation was observed between MUC5AC mRNA levels and tarsal GC density (p=0.018). A trend toward association between PM2.5 levels and tarsal GC cell density (p=0.052) was found.

CONCLUSION

Exposure to ambient levels of air pollution impacts conjunctival GC density. An increase in MUC5AC mRNA levels may be part of an adaptive ocular surface response to long-term exposure to air pollution.

A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States

Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created a model to predict ambient particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling. We developed a hybrid approach combining a land use regression model (LUR) selected with a machine learning method, and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals. The PM2.5 data set included 104,172 monthly observations at 1464 monitoring locations with approximately 10% of locations reserved for cross-validation. LUR models were based on remote sensing estimates of PM2.5, land use and traffic indicators. Normalized cross-validated R(2) values for LUR were 0.63 and 0.11 with and without remote sensing, respectively, suggesting remote sensing is a strong predictor of ground-level concentrations. In the models including the BME interpolation of the residuals, cross-validated R(2) were 0.79 for both configurations; the model without remotely sensed data described more fine-scale variation than the model including remote sensing. Our results suggest that our modeling framework can predict ground-level concentrations of PM2.5 at multiple scales over the contiguous U.S.

Nitric oxide and energy metabolism in mammals

Nitric oxide (NO) is a signaling molecule synthesized from L-arginine by NO synthase in animals. Increasing evidence shows that NO regulates the mammalian metabolism of energy substrates and that these effects of NO critically depend on its concentrations at the reaction site and the period of exposure. High concentrations of NO (in the micromolar range) irreversibly inhibit complexes I, II, III, IV, and V in the mitochondrial respiratory chain, whereas physiological levels of NO (in the nanomolar range) reversibly reduce cytochomrome oxidase. Thus, NO reduces oxygen consumption by isolated mitochondria to various extents. In intact cells, through cGMP and AMP-activated protein kinase signaling, physiological levels of NO acutely stimulate uptake and oxidation of glucose and fatty acids by skeletal muscle, heart, liver, and adipose tissue, while inhibiting the synthesis of glucose, glycogen and fat in the insulin-sensitive tissues, and enhancing lipolysis in white adipocytes. Chronic effects of physiological levels of NO in vivo include stimulation of angiogenesis, blood flow, mitochondrial biogenesis, and brown adipocyte development. Modulation of NO-mediated pathways through dietary supplementation with L-arginine or its precursor L-citrulline may provide an effective, practical strategy to prevent and treat metabolic syndrome, including obesity, diabetes, and dyslipidemia in mammals, including humans.

Automated mineralogical analysis of PM10: new parameters for assessing PM toxicity

This work provides the first automated mineralogical/phase assessment of urban airborne PM10 and a new method for determining particle surface mineralogy (PSM), which is a major control on PM toxicity in the lung. PM10 was analyzed on a TEOM filter (Aug.-Sept. 2006 collection) from the London Air Quality Network Bexley, East London, U.K. A cross-section of the filter was analyzed using a QEMSCAN automated mineralogical analysis system which provided 381,981 points of analysis for 14,525 particles over a period of 9 h 54 min. The method had a detection limit for individual mineral components of 0.05 ppm (by area). Particle shape and mineralogical characteristics were determined for particles in the size ranges PM(10-4), PM(4-2.5), and PM(2.5-0.8). The PM(2.5-0.8) fraction contained 2 orders of magnitude more mineral particles than the PM(10-4) and PM(4-2.5) fractions, however the PM(10-4) fraction forms 94% and 79% of the mineral mass and surface area, respectively. PSM of the PM10 was dominated by gypsum (36%), plagioclase (16%), Na sulphates (8%), and Fe-S-O phases (8%) in the PM(10-2.5), which may be important in explaining the toxicity of the coarse fraction. The wider implications of the study are discussed.

Antibacterial performance of nanoscaled visible-light responsive platinum-containing titania photocatalyst in vitro and in vivo

BACKGROUND

Traditional antibacterial photocatalysts are primarily induced by ultraviolet light to elicit antibacterial reactive oxygen species. New generation visible-light responsive photocatalysts were discovered, offering greater opportunity to use photocatalysts as disinfectants in our living environment. Recently, we found that visible-light responsive platinum-containing titania (TiO2-Pt) exerted high performance antibacterial property against soil-borne pathogens even in soil highly contaminated water. However, its physical and photocatalytic properties, and the application in vivo have not been well-characterized.

METHODS

Transmission electron microscopy, energy dispersive spectroscopy, X-ray photoelectron spectroscopy, X-ray diffraction, ultraviolet-visible absorption spectrum and the removal rate of nitrogen oxides were therefore analyzed. The antibacterial performance under in vitro and in vivo conditions was evaluated.

RESULTS

The apparent quantum efficiency for visible light illuminated TiO2-Pt is relatively higher than several other titania photocatalysts. The killing effect achieved approximately 2 log reductions of pathogenic bacteria in vitro. Illumination of injected TiO2-Pt successfully ameliorated the subcutaneous infection in mice.

CONCLUSIONS

This is the first demonstration of in vivo antibacterial use of TiO2-Pt nanoparticles. When compared to nanoparticles of some other visible-light responsive photocatalysts, TiO2-Pt nanoparticles induced less adverse effects such as exacerbated platelet clearance and hepatic cytotoxicity in vivo.

GENERAL SIGNIFICANCE

These findings suggest that the TiO2-Pt may have potential application on the development of an antibacterial material in both in vitro and in vivo settings.