Investigating the impact of London's ultra low emission zone on children's health: children's health in London and Luton (CHILL) protocol for a prospective parallel cohort study.

BACKGROUND: Air pollution harms health across the life course. Children are at particular risk of adverse effects during development, which may impact on health in later life. Interventions that improve air quality are urgently needed both to improve public health now, and prevent longer-term increased vulnerability to chronic disease. Low Emission Zones are a public health policy intervention aimed at reducing traffic-derived contributions to urban air pollution, but evidence that they deliver health benefits is lacking. We describe a natural experiment study (CHILL: Children's Health in London and Luton) to evaluate the impacts of the introduction of London's Ultra Low Emission Zone (ULEZ) on children's health. METHODS: CHILL is a prospective two-arm parallel longitudinal cohort study recruiting children at age 6-9 years from primary schools in Central London (the focus of the first phase of the ULEZ) and Luton (a comparator site), with the primary outcome being the impact of changes in annual air pollutant exposures (nitrogen oxides [NOx], nitrogen dioxide [NO2], particulate matter with a diameter of less than 2.5micrograms [PM2.5], and less than 10 micrograms [PM10]) across the two sites on lung function growth, measured as post-bronchodilator forced expiratory volume in one second (FEV1) over five years. Secondary outcomes include physical activity, cognitive development, mental health, quality of life, health inequalities, and a range of respiratory and health economic data. DISCUSSION: CHILL's prospective parallel cohort design will enable robust conclusions to be drawn on the effectiveness of the ULEZ at improving air quality and delivering improvements in children's respiratory health. With increasing proportions of the world's population now living in large urban areas exceeding World Health Organisation air pollution limit guidelines, our study findings will have important implications for the design and implementation of Low Emission and Clean Air Zones in the UK, and worldwide. CLINICALTRIALS: GOV: NCT04695093 (05/01/2021).

Comparing human exposure to fine particulate matter in low and high-income countries: A systematic review of studies measuring personal PM2.5 exposure.

BACKGROUND: Due to the adverse health effects of air pollution, researchers have advocated for personal exposure measurements whereby individuals carry portable monitors in order to better characterise and understand the sources of people's pollution exposure. OBJECTIVES: The aim of this systematic review is to assess the differences in the magnitude and sources of personal PM2.5 exposures experienced between countries at contrasting levels of income. METHODS: This review summarised studies that measured participants personal exposure by carrying a PM2.5 monitor throughout their typical day. Personal PM2.5 exposures were summarised to indicate the distribution of exposures measured within each country income category (based on low (LIC), lower-middle (LMIC), upper-middle (UMIC), and high (HIC) income countries) and between different groups (i.e. gender, age, urban or rural residents). RESULTS: From the 2259 search results, there were 140 studies that met our criteria. Overall, personal PM2.5 exposures in HICs were lower compared to other countries, with UMICs exposures being slightly lower than exposures measured in LMICs or LICs. 34% of measured groups in HICs reported below the ambient World Health Organisation 24-h PM2.5 guideline of 15 µg/m3, compared to only 1% of UMICs and 0% of LMICs and LICs. There was no difference between rural and urban participant exposures in HICs, but there were noticeably higher exposures recorded in rural areas compared to urban areas in non-HICs, due to significant household sources of PM2.5 in rural locations. In HICs, studies reported that secondhand smoke, ambient pollution infiltrating indoors, and traffic emissions were the dominant contributors to personal exposures. While, in non-HICs, household cooking and heating with biomass and coal were reported as the most important sources. CONCLUSION: This review revealed a growing literature of personal PM2.5 exposure studies, which highlighted a large variability in exposures recorded and severe inequalities in geographical and social population subgroups.

Urban street dust in the Middle East oldest oil refinery zone: Oxidative potential, source apportionment، and health risk assessment of potentially toxic elements.

The current study is the intented to investigate the intensity of pollution, source characterization, oxidative potential, and human health risks of fourteen potentially toxic elements in the street dust of the Middle East oldest oil refinery zone. Thirty five street dust samples were collected from various regions in Abadan and Khorramshahr cities. The mean concentration of As, Mo, Cu, Pb, Hg, Zn, Cd, and Sb in Abadan street dust were 5.55, 3.39, 83.68, 49.82, 4493.54, 281.24, 1.15,and 1.17, while in Khorramshahr As, Mo, Cu, Pb, Hg, Zn, Cd, and Sb were.14, 2.58, 74.35, 56.50, 0.74, 214.26, 0.62, and 1.18, respectively. The concentration of these elements in both cities is higher than the local background values. Potential ecological risk index and pollution load index at all stations of both cities are greater than 1, indicating a high pollution load in the study area. Calculated enrichment factor showed high enrichment of Hg, Sb, Cd, Mo, Cu, Pb, and Zn in both areas. Of particular concern is the enrichment factor for mercury which proved to be 3370.54 ppb in the vicinity of the petrochemical unit in Abadan city (EF > 40). The results of positive matrix factorization receptor model together with geochemical maps and multivariate statistics indicated that industrial activities (especially petrochemical industries) are responsible for Hg, Cu, and Zn pollution, while exhaust emissions are responsible for Mo, Pb, Cd, and Sb, and natural sources for Al, Cr, Mn, Fe, Co, and Ni. The percentage of OPAA in the region ranged from 15.1 to 26.4 and OPGSH ranged from 9.5 to 24.4. The percentage of OPTOTAL/µg (OPAA/µg + OPGSH/µg) values varied between 0.6 and 1. The health risk evaluation models indicated that specific attention should be paid to Hg, Cd, Pb, and Zn and that the higher oxidative potential of street dust recovered from polluted locations is also a matter of concern in Abadan and Khorramshahr Cities.

Physico-chemical properties and reactive oxygen species generation by respirable coal dust: Implication for human health risk assessment.

This study investigates the mineralogy, micro-morphology, chemical characteristics and oxidation toxicity of respirable dusts generated in underground coal mines. The active sampling was applied to collect airborne particulates with aerodynamic diameter <4 µm (PM4) at depth greater than 500 m from earth surface. The average mass concentration of PM4 was extremely higher than recommended values. QXRD and FESEM-EDS analyses were applied to study the micro-mineralogy and micro-morphology of respirable dusts. The chemical analysis by ICP-MS revealed an enrichment of V, Cr, Cu, Zn, As, Ag, Cd and Sb in respirable dust compared with the background environment and world coals. The EPA's health risk model showed that the health risk posed by Cr and Co in all workplaces exceeded the acceptable risk value for human health. The synthetic respiratory tract lining fluid (RTLF) model was utilized to achieve a novel insight into the toxicity of respirable coal dust. The result showed an overall depletion of lung surface antioxidants with the decreasing trend of ascorbic acid > reduced glutathione >> urate, implying low- to medium level of oxidative stress. The result of this study can be applied globally by decision-makers to decrease hazardous exposure of mine workers to respirable dust.

The role of burden of disease assessment in tracking progress towards achieving WHO global air quality guidelines.

OBJECTIVES: More than 90% of the global population live in areas exceeding the PM2.5 air quality guidelines (AQGs). We provide an overview of the ambient PM2.5-related burden of disease (BoD) studies along with scenario analysis in the framework of the WHO AQG update on the estimated reduction in the BoD if AQGs were achieved globally. METHODS: We reviewed the literature for large-scale studies for the BoD attributed to ambient PM2.5. Moreover, we used the latest WHO statistics to calculate the BoD at current levels and the scenarios of aligning with interim targets and AQG levels. RESULTS: The most recent BoD studies (2010 onwards) share a similar methodology, but there are differences in the input data which affect the estimates for attributable deaths (2.9-8.9 million deaths annually). Moreover, we found that if AQGs were achieved, the estimated BoD would be reduced by up to 50% in total deaths worldwide. CONCLUSIONS: Understanding the BoD across countries, especially in those that do not align with the AQGs, is essential in order to inform actions to reduce air pollution globally.

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.

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.

Socioeconomic and ethnic inequalities in exposure to air and noise pollution in London.

BACKGROUND: Transport-related air and noise pollution, exposures linked to adverse health outcomes, varies within cities potentially resulting in exposure inequalities. Relatively little is known regarding inequalities in personal exposure to air pollution or transport-related noise. OBJECTIVES: Our objectives were to quantify socioeconomic and ethnic inequalities in London in 1) air pollution exposure at residence compared to personal exposure; and 2) transport-related noise at residence from different sources. METHODS: We used individual-level data from the London Travel Demand Survey (n = 45,079) between 2006 and 2010. We modeled residential (CMAQ-urban) and personal (London Hybrid Exposure Model) particulate matter <2.5 µm and nitrogen dioxide (NO2), road-traffic noise at residence (TRANEX) and identified those within 50 dB noise contours of railways and Heathrow airport. We analyzed relationships between household income, area-level income deprivation and ethnicity with air and noise pollution using quantile and logistic regression. RESULTS: We observed inverse patterns in inequalities in air pollution when estimated at residence versus personal exposure with respect to household income (categorical, 8 groups). Compared to the lowest income group (<£10,000), the highest group (>£75,000) had lower residential NO2 (-1.3 (95% CI -2.1, -0.6) µg/m3 in the 95th exposure quantile) but higher personal NO2 exposure (1.9 (95% CI 1.6, 2.3) µg/m3 in the 95th quantile), which was driven largely by transport mode and duration. Inequalities in residential exposure to NO2 with respect to area-level deprivation were larger at lower exposure quantiles (e.g. estimate for NO2 5.1 (95% CI 4.6, 5.5) at quantile 0.15 versus 1.9 (95% CI 1.1, 2.6) at quantile 0.95), reflecting low-deprivation, high residential NO2 areas in the city centre. Air pollution exposure at residence consistently overestimated personal exposure; this overestimation varied with age, household income, and area-level income deprivation. Inequalities in road traffic noise were generally small. In logistic regression models, the odds of living within a 50 dB contour of aircraft noise were highest in individuals with the highest household income, white ethnicity, and with the lowest area-level income deprivation. Odds of living within a 50 dB contour of rail noise were 19% (95% CI 3, 37) higher for black compared to white individuals. CONCLUSIONS: Socioeconomic inequalities in air pollution exposure were different for modeled residential versus personal exposure, which has important implications for environmental justice and confounding in epidemiology studies. Exposure misclassification was dependent on several factors related to health, a potential source of bias in epidemiological studies. Quantile regression revealed that socioeconomic and ethnic inequalities in air pollution are often not uniform across the exposure distribution.

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

Research confirming the detrimental impact poor ambient air quality and episodes of abnormally high pollutants has on public health, plus differential susceptibility, calls for improved understanding of this complex topic among all walks of society. The public and particularly, vulnerable groups, should be aware of their quality of air, enabling action to be taken in the event of increased pollution. Policy makers must have a sound awareness of current air quality and future trends, to identify issues, guide policies and monitor their effectiveness. These attitudes are dependent upon air pollution monitoring, forecasting and reporting, serving all interested parties. Apart from the underlying national regulatory obligation a country has in reporting air quality information, data output serves several purposes. This review focuses on provision of real-time data and advanced warnings of potentially health-damaging events, in the form of national air quality indices and proactive alert services. Some of the challenges associated with designing these systems include technical issues associated with the complexity of air pollution and its science. These include inability to provide precise exposure concentrations or guidance on long-term/cumulative exposures or effects from pollutant combinations. Other issues relate to the degree to which people are aware and positively respond to these services. Looking to the future, mobile devices such as cellular phones, equipped with sensing applications have potential to provide dynamic, temporally and spatially precise exposure measures for the mass population. The ultimate aim should be to empower people to modify behaviour-for example, when to increase medication, the route/mode of transport taken to school or work or the appropriate time to pursue outdoor activities-in a way that protects their health as well as the quality of the air they breathe.

The London low emission zone baseline study.

On February 4, 2008, the world's largest low emission zone (LEZ) was established. At 2644 km2, the zone encompasses most of Greater London. It restricts the entry of the oldest and most polluting diesel vehicles, including heavy-goods vehicles (haulage trucks), buses and coaches, larger vans, and minibuses. It does not apply to cars or motorcycles. The LEZ scheme will introduce increasingly stringent Euro emissions standards over time. The creation of this zone presented a unique opportunity to estimate the effects of a stepwise reduction in vehicle emissions on air quality and health. Before undertaking such an investigation, robust baseline data were gathered on air quality and the oxidative activity and metal content of particulate matter (PM) from air pollution monitors located in Greater London. In addition, methods were developed for using databases of electronic primary-care records in order to evaluate the zone's health effects. Our study began in 2007, using information about the planned restrictions in an agreed-upon LEZ scenario and year-on-year changes in the vehicle fleet in models to predict air pollution concentrations in London for the years 2005, 2008, and 2010. Based on this detailed emissions and air pollution modeling, the areas in London were then identified that were expected to show the greatest changes in air pollution concentrations and population exposures after the implementation of the LEZ. Using these predictions, the best placement of a pollution monitoring network was determined and the feasibility of evaluating the health effects using electronic primary-care records was assessed. To measure baseline pollutant concentrations before the implementation of the LEZ, a comprehensive monitoring network was established close to major roadways and intersections. Output-difference plots from statistical modeling for 2010 indicated seven key areas likely to experience the greatest change in concentrations of nitrogen dioxide (NO2) (at least 3 microg/m3) and of PM with an aerodynamic diameter < or = 10 microm (PM10) (at least 0.75 microg/m3) as a result of the LEZ; these suggested that the clearest signals of change were most likely to be measured near roadsides. The seven key areas were also likely to be of importance in carrying out a study to assess the health outcomes of an air quality intervention like the LEZ. Of the seven key areas, two already had monitoring sites with a full complement of equipment, four had monitoring sites that required upgrades of existing equipment, and one required a completely new installation. With the upgrades and new installations in place, fully ratified (verified) pollutant data (for PM10, PM with an aerodynamic diameter < or = 2.5 microm [PM2.5], nitrogen oxides [NOx], and ozone [O3] at all sites as well as for particle number, black smoke [BS], carbon monoxide [CO], and sulfur dioxide [SO2] at selected sites) were then collected for analysis. In addition, the seven key monitoring sites were supported by other sites in the London Air Quality Network (LAQN). From these, a robust set of baseline air quality data was produced. Data from automatic and manual traffic counters as well as automatic license-plate recognition cameras were used to compile detailed vehicle profiles. This enabled us to establish more precise associations between ambient pollutant concentrations and vehicle emissions. An additional goal of the study was to collect baseline PM data in order to test the hypothesis that changes in traffic densities and vehicle mixes caused by the LEZ would affect the oxidative potential and metal content of ambient PM10 and PM2.5. The resulting baseline PM data set was the first to describe, in detail, the oxidative potential and metal content of the PM10 and PM2.5 of a major city's airshed. PM in London has considerable oxidative potential; clear differences in this measure were found from site to site, with evidence that the oxidative potential of both PM10 and PM2.5 at roadside monitoring sites was higher than at urban background locations. In the PM10 samples this increased oxidative activity appeared to be associated with increased concentrations of copper (Cu), barium (Ba), and bathophenanthroline disulfonate-mobilized iron (BPS Fe) in the roadside samples. In the PM2.5 samples, no simple association could be seen, suggesting that other unmeasured components were driving the increased oxidative potential in this fraction of the roadside samples. These data suggest that two components were contributing to the oxidative potential of roadside PM, namely Cu and BPS Fe in the coarse fraction of PM (PM with an aerodynamic diameter of 2.5 microm to 10 microm; PM(2.5-10)) and an unidentified redox catalyst in PM2.5. The data derived for this baseline study confirmed key observations from a more limited spatial mapping exercise published in our earlier HEI report on the introduction of the London's Congestion Charging Scheme (CCS) in 2003 (Kelly et al. 2011a,b). In addition, the data set in the current report provided robust baseline information on the oxidative potential and metal content of PM found in the London airshed in the period before implementation of the LEZ; the finding that a proportion of the oxidative potential appears in the PM coarse mode and is apparently related to brake wear raises important issues regarding the nature of traffic management schemes. The final goal of this baseline study was to establish the feasibility, in ethical and operational terms, of using the U.K.'s electronic primary-care records to evaluate the effects of the LEZ on human health outcomes. Data on consultations and prescriptions were compiled from a pilot group of general practices (13 distributed across London, with 100,000 patients; 29 situated in the inner London Borough of Lambeth, with 200,000 patients). Ethics approvals were obtained to link individual primary-care records to modeled NOx concentrations by means of post-codes. (To preserve anonymity, the postcodes were removed before delivery to the research team.) A wide range of NOx exposures was found across London as well as within and between the practices examined. Although we observed little association between NOx exposure and smoking status, a positive relationship was found between exposure and increased socioeconomic deprivation. The health outcomes we chose to study were asthma, chronic obstructive pulmonary disease, wheeze, hay fever, upper and lower respiratory tract infections, ischemic heart disease, heart failure, and atrial fibrillation. These outcomes were measured as prevalence or incidence. Their distributions by age, sex, socioeconomic deprivation, ethnicity, and smoking were found to accord with those reported in the epidemiology literature. No cross-sectional positive associations were found between exposure to NOx and any of the studied health outcomes; some associations were significantly negative. After the pilot study, a suitable primary-care database of London patients was identified, the General Practice Research Database responsible for giving us access to these data agreed to collaborate in the evaluation of the LEZ, and an acceptable method of ensuring privacy of the records was agreed upon. The database included about 350,000 patients who had remained at the same address over the four-year period of the study. Power calculations for a controlled longitudinal analysis were then performed, indicating that for outcomes such as consultations for respiratory illnesses or prescriptions for asthma there was sufficient power to identify a 5% to 10% reduction in consultations for patients most exposed to the intervention compared with patients presumed to not be exposed to it. In conclusion, the work undertaken in this study provides a good foundation for future LEZ evaluations. Our extensive monitoring network, measuring a comprehensive set of pollutants (and a range of particle metrics), will continue to provide a valuable tool both for assessing the impact of LEZ regulations on air quality in London and for furthering understanding of the link between PM's composition and toxicity. Finally, we believe that in combination with our modeling of the predicted population-based changes in pollution exposure in London, the use of primary-care databases forms a sound basis and has sufficient statistical power for the evaluation of the potential impact of the LEZ on human health.

The shocking cost of turnover in health care.

Review of turnover costs at a major medical center helps health care managers gain insights about the magnitude and determinants of this managerial challenge and assess the implications for organizational effectiveness. Here, turnover includes hiring, training, and productivity loss costs. Minimum cost of turnover represented a loss of >5 percent of the total annual operating budget. Editor's Note: This article is being reprinted with permission from Health Care Management Review 29(1), 2-7.

Hazard and risk assessment of a nanoparticulate cerium oxide-based diesel fuel additive - a case study.

Envirox is a scientifically and commercially proven diesel fuel combustion catalyst based on nanoparticulate cerium oxide and has been demonstrated to reduce fuel consumption, greenhouse gas emissions (CO(2)), and particulate emissions when added to diesel at levels of 5 mg/L. Studies have confirmed the adverse effects of particulates on respiratory and cardiac health, and while the use of Envirox contributes to a reduction in the particulate content in the air, it is necessary to demonstrate that the addition of Envirox does not alter the intrinsic toxicity of particles emitted in the exhaust. The purpose of this study was to evaluate the safety in use of Envirox by addressing the classical risk paradigm. Hazard assessment has been addressed by examining a range of in vitro cell and cell-free endpoints to assess the toxicity of cerium oxide nanoparticles as well as particulates emitted from engines using Envirox. Exposure assessment has taken data from modeling studies and from airborne monitoring sites in London and Newcastle adjacent to routes where vehicles using Envirox passed. Data have demonstrated that for the exposure levels measured, the estimated internal dose for a referential human in a chronic exposure situation is much lower than the no-observed-effect level (NOEL) in the in vitro toxicity studies. Exposure to nano-size cerium oxide as a result of the addition of Envirox to diesel fuel at the current levels of exposure in ambient air is therefore unlikely to lead to pulmonary oxidative stress and inflammation, which are the precursors for respiratory and cardiac health problems.

The shocking cost of turnover in health care.

Review of turnover costs at a major medical center helps health care managers gain insights about the magnitude and determinants of this managerial challenge and assess the implications for organizational effectiveness. Here, turnover includes hiring, training, and productivity loss costs. Minimum cost of turnover represented a loss of >5 percent of the total annual operating budget.