Background: There is no consensus whether tobacco smoking increases risk of tuberculosis (TB) infection, disease, or mortality. Whether this is so has substantial implications for tobacco and TB control policies.Objective: To quantify the relationship between active tobacco smoking and TB infection, pulmonary disease, and mortality using meta-analytic methods.

Ozone and particle pollution are of concern for the Sydney basin, in particular during warm months (November to March) when pollution levels can exceed national standards. Previous studies on the relationship between synoptic circulation and air quality focused on high pollution days or aggregated air quality conditions over the region as a whole. This study provides both temporal and spatial analyses of the synoptic processes affecting warm-month ozone and particle pollution in Sydney. A warm-month synoptic catalogue was developed by applying the self-organising map method to the NCEP/NCAR geopotential height reanalysis for south-east Australia. The catalogue was linked to mesoscale meteorological features such as drainage flows and sea breezes, and subsequently to the spatial variability in air quality across the Sydney basin. The typical synoptic types commonly associated with high or low ozone and PM 10 levels, as well as variations in visibility, were identified. The results suggest that, due to Sydney's subtropical coastal-basin environment, the interaction between mesoand synoptic-scale features determine local air quality conditions in the region, rather than the synoptic conditions alone. Emissions from bushfires appear to have considerable impacts on the synoptic modulation to visibility and PM 10 levels, with such impacts tending to be more at a local scale. In contrast, no comparable impacts were found for ozone pollution. For ozone and visibility, the probability for an exceedance day under some synoptic types varied considerably over time, implying that there might have been a shift in the role of synoptic modulation to local air quality associated with changes in air emissions profiles. This study provides a leap in our understanding of the relationship between synoptic circulation and air quality in a coastal-basin environment. The results are useful for improving air quality forecasting in Sydney, with the methodology developed readily applicable to similar regions elsewhere.

We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (<1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

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The coupled Conformal Cubic Atmospheric Model (CCAM) and Chemical Transport Model (CTM) (CCAM-CTM) was undertaken with eleven emission scenarios segregated from the 2008 New South Wales Greater Metropolitan Region (NSW GMR) Air Emission Inventory to predict major source contributions to ambient PM 2.5 and exposure in the NSW GMR. Model results illustrate that populated areas in the NSW GMR are characterised with annual average PM 2.5 of 6-7 µg/m 3 , while natural sources including biogenic emissions, sea salt and wind-blown dust contribute 2-4 µg/m 3 to it. Summer and winter regional average PM 2.5 ranges from 5.2-6.1 µg/m 3 and 3.7-7.7 µg/m 3 across Sydney East, Sydney Northwest, Sydney Southwest, Illawarra and Newcastle regions. Secondary inorganic aerosols (particulate nitrate, sulphate and ammonium) and sodium account for up to 23% and 18% of total PM 2.5 mass in both summer and winter. The increase in elemental carbon (EC) mass from summer to winter is found across all regions but particularly remarkable in the Sydney East region. Among human-made sources, "wood heaters" is the first or second major source contributing to total PM 2.5 and EC mass across Sydney in winter. "On-road mobile vehicles" is the top contributor to EC mass across regions, and it also has significant contributions to total PM 2.5 mass, particulate nitrate and sulphate mass in the Sydney East region. "Power stations" is identified to be the third major contributor to the summer total PM 2.5 mass across regions, and the first or second contributor to sulphate and ammonium mass in both summer and winter. "Non-road diesel and marine" plays a relatively important role in EC mass across regions except Illawarra. "Industry" is identified to be the first or second major contributor to sulphate and ammonium mass, and the second or third major contributor to total PM 2.5 mass across regions. By multiplying modelled predictions with Australian Bureau of Statistics 1-km resolution gridded population data, the natural and human-made sources are found to contribute 60% (3.55 µg/m 3 ) and 40% (2.41 µg/m 3 ) to the population-weighted annual average PM 2.5 (5.96 µg/m 3 ). Major source groups "wood heaters", "industry", "on-road motor vehicles", "power stations" and "non-road diesel and marine" accounts for 31%, 26%, 19%, 17% and 6% of the total human-made sources contribution, respectively. The results in this study enhance the quantitative understanding of major source contributions to ambient PM 2.5 and its major chemical components. A greater understanding of the contribution of the major sources to PM 2.5 exposures is the basis for air quality management interventions aiming to deliver improved public health outcomes.