Modelling growth rate of Penaeus monodon Fabricius in intensively managed ponds: effects of temperature, pond age and stocking density

Records of shrimp growth and water quality made during 12 crops from each of 48 ponds, over a period of 6.5 years, were provided by a Queensland, Australia, commercial shrimp farm, These data were analysed with a new growth model derived from the Gompertz model. The results indicate that water temperature, mortality and pond age significantly affect growth rates. After 180 days, shrimp reach 34 g at constant 30 degrees C, but only 15 g after the same amount of time at 20 degrees C. Mortality, through thinning the density of shrimp in the ponds, increased the growth rate, but the effect is small. With continual production, growth rates at first remained steady, then appeared to decrease for the sixth and seventh crop, after which they have increased steadily with each crop. It appears that conservative pond management, together with a gradual improvement in husbandry techniques, particularly feed management, brought about this change. This has encouraging implications for the long-term sustainability of the farming methods used. The growth model can be used to predict productivity, and hence, profitability, of new aquaculture locations or new production strategies.

Atmospheric visibility and PM10 as indicators of new particle formation in an urban environment

It is well-known that new particle formation (NPF) in the atmosphere is inhibited by pre-existing particles in the air that act as condensation sinks to decrease the concentration and, thus, the supersaturation of precursor gases. In this study, we investigate the effects of two parameters - atmospheric visibility, expressed as the particle back-scatter coefficient (BSP), and PM10 particulate mass concentration, on the occurrences of NPF events in an urban environment where the majority of precursor gases originate from motor vehicle and industrial sources. This is the first attempt to derive direct relationships between each of these two parameters and the occurrence of NPF. NPF events were identified from data obtained with a neutral cluster and air ion spectrometer over 245 days within a calendar year. Bayesian logistic regression was used to determine the probability of observing NPF as functions of BSP and PM10. We show that the BSP at 08 h on a given day is a reliable indicator of an NPF event later that day. The posterior median probability of observing an NPF event was greater than 0.5 (95%) when the BSP at 08 h was less than 6.8 Mm-1.

Insights into the growth of newly formed particles in a subtropical urban environment

The role of different chemical compounds, particularly organics, involved in the new particle formation (NPF) and its consequent growth are not fully understood. Therefore, this study was conducted to investigate the chemical composition of aerosol particles during NPF events in an urban subtropical environment. Aerosol chemical composition was measured along with particle number size distribution (PNSD) and several other air quality parameters at five sites across an urban subtropical environment. An Aerodyne compact Time-of-Flight Aerosol Mass Spectrometer (c-TOF-AMS) and a TSI Scanning Mobility Particle Sizer (SMPS) measured aerosol chemical composition (particles above 50 nm in vacuum aerodynamic diameter) and PNSD (particles within 9-414 nm in mobility diameter), respectively. Five NPF events, with growth rates in the range 3.3-4.6 nm, were detected at two of the sites. The NPF events happened on relatively warmer days with lower condensation sink (CS). Temporal percent fractions of organics increased after the particles grew enough to have a significant contribution to particles volume, while the mass fraction of ammonium and sulphate decreased. This uncovered the important role of organics in the growth of newly formed particles. Three organic markers, factors f43, f44 and f57, were calculated and the f44 vs f43 trends were compared between nucleation and non-nucleation days. K-means cluster analysis was performed on f44 vs f43 data and it was found that they follow different patterns on nucleation days compared to non-nucleation days, whereby f43 decreased for vehicle emission generated particles, while both f44 and f43 decreased for NPF generated particles. It was found for the first time that vehicle generated and newly formed particles cluster in different locations on f44 vs f43 plot and this finding can be potentially used as a tool for source apportionment of measured particles.

Survival analysis of time-to-event data in respiratory health research studies

This article provides a review of techniques for the analysis of survival data arising from respiratory health studies. Popular techniques such as the Kaplan–Meier survival plot and the Cox proportional hazards model are presented and illustrated using data from a lung cancer study. Advanced issues are also discussed, including parametric proportional hazards models, accelerated failure time models, time-varying explanatory variables, simultaneous analysis of multiple types of outcome events and the restricted mean survival time, a novel measure of the effect of treatment.