Environmental context Carbon tetrachloride in the background atmosphere is a significant environmental concern, responsible for ~10% of observed stratospheric ozone depletion. Atmospheric concentrations of CCl4 are higher than expected from currently identified emission sources: largely residual emissions from production, transport and use. Additional sources are required to balance the expected atmospheric destruction of CCl4 and may contribute to a slower-than-expected recovery of the Antarctic ozone ‘hole’. Abstract Global (1978–2012) and Australian (1996–2011) carbon tetrachloride emissions are estimated from atmospheric observations of CCl4 using data from the Advanced Global Atmospheric Gases Experiment (AGAGE) global network, in particular from Cape Grim, Tasmania. Global and Australian emissions are in decline in response to Montreal Protocol restrictions on CCl4 production and consumption for dispersive uses in the developed and developing world. However, atmospheric data-derived emissions are significantly larger than ‘bottom-up’ estimates from direct and indirect CCl4 production, CCl4 transportation and use. Australian CCl4 emissions are not a result of these sources, and the identification of the origin of Australian emissions may provide a clue to the origin of some of these ‘missing’ global sources.

The Australian Air Quality Forecasting System (AAQFS) is the culmination of a 3-yr project to develop a numerical primitive equation system for generating high-resolution (1–5 km) short-term (24–36 h) forecasts for the Australian coastal cities of Melbourne and Sydney. Forecasts are generated 2 times per day for a range of primary and secondary air pollutants, including ozone, nitrogen dioxide, carbon monoxide, sulfur dioxide, and particles that are less than 10 μm in diameter (PM10). A preliminary assessment of system performance has been undertaken using forecasts generated over a 3-month demonstration period. For the priority pollutant ozone it was found that AAQFS achieved a coefficient of determination of 0.65 and 0.57 for forecasts of peak daily 1-h concentration in Melbourne and Sydney, respectively. The probability of detection and false-alarm rate were 0.71 and 0.55, respectively, for a 60-ppb forecast threshold in Melbourne. A similar level of skill was achieved for Sydney. System performance is also promising for the primary gaseous pollutants. Further development is required before the system can be used to forecast PM10 confidently, with a systematic overprediction of 24-h PM10 concentration occurring during the winter months.

Climate change has been predicted to affect future air quality, with inevitable consequences for health. Quantifying the health effects of air pollution under a changing climate is crucial to provide evidence for actions to safeguard future populations. In this paper, we review published methods for quantifying health impacts to identify optimal approaches and ways in which existing challenges facing this line of research can be addressed. Most studies have employed a simplified methodology, while only a few have reported sensitivity analyses to assess sources of uncertainty. The limited investigations that do exist suggest that examining the health risk estimates should particularly take into account the uncertainty associated with future air pollution emissions scenarios, concentration-response functions, and future population growth and age structures. Knowledge gaps identified for future research include future health impacts from extreme air pollution events, interactions between temperature and air pollution effects on public health under a changing climate, and how population adaptation and behavioural changes in a warmer climate may modify exposure to air pollution and health consequences.Electronic supplementary materialThe online version of this article (doi:10.1007/s00484-012-0625-8) contains supplementary material, which is available to authorized users.

China, India, Climate change, International negotiations, Development,

Soil moisture has important effects on fuel availability, but is often assessed using drought indices at coarse spatial resolution, without accounting for the fine-scale spatial effects of terrain and canopy variation on forest floor moisture. In this study, we examined the spatial variability of air temperature, litter temperature and near-surface soil moisture (θ, 0–100 mm) using data from field experiments at 17 sites in south-east Australia, covering a range of topographic aspects and vegetation types, within climates from semiarid to wet montane. Temperatures and θ in mountainous environments were found to vary at much finer spatial scales than typical drought index grid dimensions (several kilometres). Using terrain elevation, local insolation ratio and plant area index, we developed semi-empirical microclimate models for air and litter temperatures, then used modelled temperatures as input into calculations of the Keetch–Byram Drought Index, a widely used index of soil moisture deficit. Drought index results based on predicted litter temperature were found to explain 91% of the spatial variation in near-surface soil moisture at our experimental sites. These results suggest the potential for routine hillslope-scale predictions of forest floor moisture status, which may be useful in the management of fire, particularly prescribed burning, in complex terrain.