Estimating the effects of environmental exposures using a weighted mean of monitoring stations

The health effects of environmental hazards are often examined using time series of the association between a daily response variable (e.g., death) and a daily level of exposure (e.g., temperature). Exposures are usually the average from a network of stations. This gives each station equal importance, and negates the opportunity for some stations to be better measures of exposure. We used a Bayesian hierarchical model that weighted stations using random variables between zero and one. We compared the weighted estimates to the standard model using data on health outcomes (deaths and hospital admissions) and exposures (air pollution and temperature) in Brisbane, Australia. The improvements in model fit were relatively small, and the estimated health effects of pollution were similar using either the standard or weighted estimates. Spatial weighted exposures would be probably more worthwhile when there is either greater spatial detail in the health outcome, or a greater spatial variation in exposure.

Respiratory health effects of diesel particulate matter

Particulate matter (PM) emissions involve a complex mixture of solid and liquid particles suspended in a gas, where it is noted that PM emissions from diesel engines are a major contributor to the ambient air pollution problem. Whilst epidemiological studies have shown a link between increased ambient PM emissions and respiratory morbidity and mortality, studies of this design are not able to identify the PM constituents responsible for driving adverse respiratory health effects. This review explores in detail the physico-chemical properties of diesel particulate matter (DPM), and identifies the constituents of this pollution source that are responsible for the development of respiratory disease. In particular, this review shows that the DPM surface area and adsorbed organic compounds play a significant role in manifesting chemical and cellular processes that if sustained can lead to the development of adverse respiratory health effects. The mechanisms of injury involved included: inflammation, innate and acquired immunity, and oxidative stress. Understanding the mechanisms of lung injury from DPM will enhance efforts to protect at-risk individuals from the harmful respiratory effects of air pollutants.

Traffic-related fine and ultrafine particle exposures of professional drivers and illness : An opportunity to better link exposure science and epidemiology to address an occupational hazard?

Exposures to traffic-related air pollution (TRAP) can be particularly high in transport microenvironments (i.e. in and around vehicles) despite the short durations typically spent there. There is a mounting body of evidence that suggests that this is especially true for fine (b2.5 μm) and ultrafine (b100 nm, UF) particles. Professional drivers, who spend extended periods of time in transport microenvironments due to their job, may incur exposures markedly higher than already elevated non-occupational exposures. Numerous epidemiological studies have shown a raised incidence of adverse health outcomes among professional drivers, and exposure to TRAP has been suggested as one of the possible causal factors. Despite this, data describing the range and determinants of occupational exposures to fine and UF particles are largely conspicuous in their absence. Such information could strengthen attempts to define the aetiology of professional drivers' illnesses as it relates to traffic combustion-derived particles. In this article, we suggest that the drivers' occupational fine and UF particle exposures are an exemplar case where opportunities exist to better link exposure science and epidemiology in addressing questions of causality. The nature of the hazard is first introduced, followed by an overview of the health effects attributable to exposures typical of transport microenvironments. Basic determinants of exposure and reduction strategies are also described, and finally the state of knowledge is briefly summarised along with an outline of the main unanswered questions in the topic area.

Source apportionment of ultrafine and fine particle concentrations in Brisbane, Australia

Purpose: To investigate the significance of sources around measurement sites, assist the development of control strategies for the important sources and mitigate the adverse effects of air pollution due to particle size. Methods: In this study, sampling was conducted at two sites located in urban/industrial and residential areas situated at roadsides along the Brisbane Urban Corridor. Ultrafine and fine particle measurements obtained at the two sites in June-July 2002 were analysed by Positive Matrix Factorization (PMF). Results: Six sources were present, including local traffic, two traffic sources, biomass burning, and two currently unidentified sources. Secondary particles had a significant impact at Site 1, while nitrates, peak traffic hours and main roads located close to the source also affected the results for both sites. Conclusions: This significant traffic corridor exemplifies the type of sources present in heavily trafficked locations and future attempts to control pollution in this type of environment could focus on the sources that were identified.

Socio-economic & environmental impacts of battery driven auto rickshaw at Rajshahi city in Bangladesh

This paper describes the socio-economic and environmental impacts of battery driven Auto Rickshaw at Rajshahi city in Bangladesh. Unemployment problem is one of the major problems in Bangladesh. The number of unemployed people in Bangladesh is 7 lacks. Auto Rickshaw reduces this unemployment problem near about 2%.In this thesis work various questions were asked to the Auto Rickshaw driver in the different point in the Rajshahi city. Then those data were calculated to know their socio economic condition. The average number of passenger per Auto Rickshaw was determined at various places of Rajshahi city (Talaimari mor, Hadir mor, Alupotti, Shaheb bazar zero point, Shodor Hospital mor, Fire brigade mor, CNB mor, Lakshipur mor, Bondo gate, Bornali, Panir tank, Rail gate, Rail Station, Bhodrar mor, Adorsha School mor). Air pollution is a great threat for human health. One of the major causes of the air pollution is the emission from various vehicles, which are running by the burning of the fossil fuel in different internal combustion(IC) engines. All the data’s about emission from various power plants were collected from internet. Then the amounts of emission (CO2, NOX and PM) from different power plant were calculated in terms of kg/km. The energy required by the Auto Rickshaw per km was also calculated. Then the histogram of emission from different vehicles in terms of kg/km was drawn. By analyzing the data and chart, it was found that, battery driven Auto Rickshaw increases income, social status, comfort and decreases unemployment problems.

A basis for inquiry into policy considerations for increasing the application of biophilic urbanism

Urban design that harnesses natural features (such as green roofs and green walls) to improve design outcomes is gaining significant interest, particularly as there is growing evidence of links between human health and wellbeing, and contact with nature. The use of such natural features can provide many significant benefits, such as reduced urban heat island effects, reduced peak energy demand for building cooling, enhanced stormwater attenuation and management, and reduced air pollution and greenhouse gas emissions. The principle of harnessing natural features as functional design elements, particularly in buildings, is becoming known as ‘biophilic urbanism’. Given the potential for global application and benefits for cities from biophilic urbanism, and the growing number of successful examples of this, it is timely to develop enabling policies that help overcome current barriers to implementation. This paper describes a basis for inquiry into policy considerations related to increasing the application of biophilic urbanism. The paper draws on research undertaken as part of the Sustainable Built Environment National Research Centre (SBEnrc) In Australia in partnership with the Western Australian Department of Finance, Parsons Brinckerhoff, Green Roofs Australasia, and Townsville City Council (CitySolar Program). The paper discusses the emergence of a qualitative, mixed-method approach that combines an extensive literature review, stakeholder workshops and interviews, and a detailed study of leading case studies. It highlights the importance of experiential and contextual learnings to inform biophilic urbanism and provides a structure to distil such learnings to benefit other applications.

Sources of ultrafine particles and chemical species along a traffic corridor : comparison of the results from two receptor models

Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. A range of chemical species have been associated with particulate matter and of special concern are the hazardous chemicals that can accentuate health problems. If the sources of such particles can be identified then strategies can be developed for the reduction of air pollution and consequently, the improvement of the quality of life. In this investigation, particle number size distribution data and the concentrations of chemical species were obtained at two sites in Brisbane, Australia. Source apportionment was used to determine the sources (or factors) responsible for the particle size distribution data. The apportionment was performed by Positive Matrix Factorisation (PMF) and Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS), and the results were compared with information from the gaseous chemical composition analysis. Although PCA/APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources identified by both methods include: traffic 1, traffic 2, local traffic, biomass burning, and two unassigned factors. Thus motor vehicle related activities had the most impact on the data with the average contribution from nearly all sources to the measured concentrations higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology which utilised a combination of three types of data related to particulate matter to determine the sources could assist future development of particle emission control and reduction strategies.

Can a “Blue Sky” return to Indian megacities?

Deterioration of air quality in Indian megacities (Delhi, Mumbai or Kolkata) is much more significant than that observed in the megacities of developed countries. Densely packed high-rise buildings restrict the self-cleaning capabilities of Indian megacities. Also, the ever growing number of on-road vehicles, resuspension of the dust, and anthropogenic activities exacerbate the levels of ambient air pollution, which is in turn breathed by urban dwellers. Pollution levels exceeding the standards on a regular basis often result in a notable increase in morbidity and mortality. This article discusses the challenges faced by Indian megacities in their quest for sustainable growth, without compromising the air quality and urban way of life.

Utility of an alternative bicycle commute route of lower proximity to motorised traffic in decreasing exposure to ultra-fine particles, respiratory symptoms and airway inflammation - a structured exposure experiment

Background: Bicycle commuting in an urban environment of high air pollution is known as a potential health risk, especially for susceptible individuals. While risk management strategies aimed to reduce motorised traffic emissions exposure have been suggested, limited studies have assessed the utility of such strategies in real-world circumstances. Objectives: The potential of reducing exposure to ultrafine particles (UFP; < 0.1 µm) during bicycle commuting by lowering interaction with motorised traffic was investigated with real-time air pollution and acute inflammatory measurements in healthy individuals using their typical, and an alternative to their typical, bicycle commute route. Methods: Thirty-five healthy adults (mean ± SD: age = 39 ± 11 yr; 29% female) each completed two return trips of their typical route (HIGH) and a pre-determined altered route of lower interaction with motorised traffic (LOW; determined by the proportion of on-road cycle paths). Particle number concentration (PNC) and diameter (PD) were monitored in real-time in-commute. Acute inflammatory indices of respiratory symptom incidence, lung function and spontaneous sputum (for inflammatory cell analyses) were collected immediately pre-commute, and one and three hours post-commute. Results: LOW resulted in a significant reduction in mean PNC (1.91 x e4 ± 0.93 x e4 ppcc vs. 2.95 x e4 ± 1.50 x e4 ppcc; p ≤ 0.001). Besides incidence of in-commute offensive odour detection (42 vs. 56 %; p = 0.019), incidence of dust and soot observation (33 vs. 47 %; p = 0.038) and nasopharyngeal irritation (31 vs. 41 %; p = 0.007), acute inflammatory indices were not significantly associated to in-commute PNC, nor were these indices reduced with LOW compared to HIGH. Conclusions: Exposure to PNC, and the incidence of offensive odour and nasopharyngeal irritation, can be significantly reduced when utilising a strategy of lowering interaction with motorised traffic whilst bicycle commuting, which may bring important benefits for both healthy and susceptible individuals.

Composition and morphology of particle emissions from in-use aircraft during takeoff and landing

In order to provide realistic data for air pollution inventories and source apportionment at airports, the morphology and composition of ultrafine particles (UFP) in aircraft engine exhaust were measured and characterized. For this purpose, two independent measurement techniques were employed to collect emissions during normal takeoff and landing operations at Brisbane Airport, Australia. PM1 emissions in the airfield were collected on filters and analyzed using the particle-induced X-ray emission (PIXE) technique. Morphological and compositional analyses of individual ultrafine particles in aircraft plumes were performed on silicon nitride membrane grids using transmission electron microscopy (TEM) combined with energy-dispersive X-ray microanalysis (EDX). TEM results showed that the deposited particles were in the range of 5 to 100 nm in diameter, had semisolid spherical shapes and were dominant in the nucleation mode (18 – 20 nm). The EDX analysis showed the main elements in the nucleation particles were C, O, S and Cl. The PIXE analysis of the airfield samples was generally in agreement with the EDX in detecting S, Cl, K, Fe and Si in the particles. The results of this study provide important scientific information on the toxicity of aircraft exhaust and their impact on local air quality.

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

Multi-criteria ranking and source apportionment of airborne particulate matter

Particulate matter research is essential because of the well known significant adverse effects of aerosol particles on human health and the environment. In particular, identification of the origin or sources of particulate matter emissions is of paramount importance in assisting efforts to control and reduce air pollution in the atmosphere. This thesis aims to: identify the sources of particulate matter; compare pollution conditions at urban, rural and roadside receptor sites; combine information about the sources with meteorological conditions at the sites to locate the emission sources; compare sources based on particle size or mass; and ultimately, provide the basis for control and reduction in particulate matter concentrations in the atmosphere. To achieve these objectives, data was obtained from assorted local and international receptor sites over long sampling periods. The samples were analysed using Ion Beam Analysis and Scanning Mobility Particle Sizer methods to measure the particle mass with chemical composition and the particle size distribution, respectively. Advanced data analysis techniques were employed to derive information from large, complex data sets. Multi-Criteria Decision Making (MCDM), a ranking method, drew on data variability to examine the overall trends, and provided the rank ordering of the sites and years that sampling was conducted. Coupled with the receptor model Positive Matrix Factorisation (PMF), the pollution emission sources were identified and meaningful information pertinent to the prioritisation of control and reduction strategies was obtained. This thesis is presented in the thesis by publication format. It includes four refereed papers which together demonstrate a novel combination of data analysis techniques that enabled particulate matter sources to be identified and sampling site/year ranked. The strength of this source identification process was corroborated when the analysis procedure was expanded to encompass multiple receptor sites. Initially applied to identify the contributing sources at roadside and suburban sites in Brisbane, the technique was subsequently applied to three receptor sites (roadside, urban and rural) located in Hong Kong. The comparable results from these international and national sites over several sampling periods indicated similarities in source contributions between receptor site-types, irrespective of global location and suggested the need to apply these methods to air pollution investigations worldwide. Furthermore, an investigation into particle size distribution data was conducted to deduce the sources of aerosol emissions based on particle size and elemental composition. Considering the adverse effects on human health caused by small-sized particles, knowledge of particle size distribution and their elemental composition provides a different perspective on the pollution problem. This thesis clearly illustrates that the application of an innovative combination of advanced data interpretation methods to identify particulate matter sources and rank sampling sites/years provides the basis for the prioritisation of future air pollution control measures. Moreover, this study contributes significantly to knowledge based on chemical composition of airborne particulate matter in Brisbane, Australia and on the identity and plausible locations of the contributing sources. Such novel source apportionment and ranking procedures are ultimately applicable to environmental investigations worldwide.

Health effects of daily airborne particle dose in children : direct association between personal dose and respiratory health effects

Air pollution is a widespread health problem associated with respiratory symptoms. Continuous exposure monitoring was performed to estimate alveolar and tracheobronchial dose, measured as deposited surface area, for 103 children and to evaluate the long-term effects of exposure to airborne particles through spirometry, skin prick tests and measurement of exhaled nitric oxide (eNO). The mean daily alveolar deposited surface area dose received by children was 1.35×103 mm2. The lowest and highest particle number concentrations were found during sleeping and eating time. A significant negative association was found between changes in pulmonary function tests and individual dose estimates. Significant differences were found for asthmatics, children with allergic rhinitis and sensitive to allergens compared to healthy subjects for eNO. Variation is a child’s activity over time appeared to have a strong impact on respiratory outcomes, which indicates that personal monitoring is vital for assessing the expected health effects of exposure to particles.

Extreme temperatures and emergency department admissions for childhood asthma in Brisbane, Australia

Objectives To examine the effect of extreme temperatures on emergency department admissions (EDAs) for childhood asthma. Methods An ecological design was used in this study. A Poisson linear regression model combined with a distributed lag non-linear model was used to quantify the effect of temperature on EDAs for asthma among children aged 0–14 years in Brisbane, Australia, during January 2003–December 2009, while controlling for air pollution, relative humidity, day of the week, season and long-term trends. The model residuals were checked to identify whether there was an added effect due to heat waves or cold spells. Results There were 13 324 EDAs for childhood asthma during the study period. Both hot and cold temperatures were associated with increases in EDAs for childhood asthma, and their effects both appeared to be acute. An added effect of heat waves on EDAs for childhood asthma was observed, but no added effect of cold spells was found. Male children and children aged 0–4 years were most vulnerable to heat effects, while children aged 10–14 years were most vulnerable to cold effects. Conclusions Both hot and cold temperatures seemed to affect EDAs for childhood asthma. As climate change continues, children aged 0–4 years are at particular risk for asthma.

New labour and the environment : too little too late.

New Labour and the environment: too little too late – symbolic success but real failure Achievements: Introduction of the Climate Change Act 2008, Low Carbon Transition Plan, the creation of the Department of Energy and Climate Change, establishment of several ‘green’ quangos and Green Investment Bank, Warm Front Scheme, international leadership on Kyoto and the European Directive for Landfill and Renewable Energy. Disappointments: Increased green house gas emissions that failto meet domestic UK targets, let alone Kyoto; significant increasesin energy and transport emissions; EU air pollution violations; failure to regulate the importation of illegally logged timber and wildlife; increase in chemical agriculture; unwillingness to tackle corporate environmental crime; road expansions and runway projects at the expense of low emission alternative public transport. Biggest broken promises: Global warming, low carbon transport; protection of biodiversity.