Estimates of CO₂ fluxes for Cape Town

Nickless et al. (2018) recently provided the results of an atmospheric inversion carried out for the city of Cape Town with the objective of obtaining estimates of weekly CO2 fluxes at a spatial resolution of 1 km × 1 km. This approach incorporates the best information available on what the fluxes are believed to be from anthropogenic and natural sources, together with estimates of the uncertainty around these estimates, and uses measurements of CO2 concentrations to improve on these estimates. CO2 concentrations were measured, by means of Picarro Cavity Ring-down Spectroscopy (CRDS) analysers, from March 2012 until July 2013 at Robben Island and Hangklip lighthouses. These measurements allow the inversion to correct the prior estimates of the fluxes. The CO2 fluxes can be converted into CO2 concentrations by means of an atmospheric transport model – the inversion attempts to improve these modelled concentrations. Measurements at the Cape Point Global Atmospheric Watch Station were used to estimate the background CO2 concentration

Spatial and temporal disaggregation of anthropogenic CO2 emissions from the City of Cape Town

Abstract This paper describes the methodology used to spatially and temporally disaggregate carbon dioxide emission estimates for the City of Cape Town, to be used for a city-scale atmospheric inversion estimating carbon dioxide fluxes. Fossil fuel emissions were broken down into emissions from road transport, domestic emissions, industrial emissions, and airport and harbour emissions. Using spatially explicit information on vehicle counts, and an hourly scaling factor, vehicle emissions estimates were obtained for the city. Domestic emissions from fossil fuel burning were estimated from household fuel usage information and spatially disaggregated population data from the 2011 national census. Fuel usage data were used to derive industrial emissions from listed activities, which included emissions from power generation, and these were distributed spatially according to the source point locations. The emissions from the Cape Town harbour and the international airport were determined from vessel and aircraft count data, respectively. For each emission type, error estimates were determined through error propagation techniques. The total fossil fuel emission field for the city was obtained by summing the spatial layers for each emission type, accumulated for the period of interest. These results will be used in a city-scale inversion study, and this method implemented in the future for a national atmospheric inversion study

Virtual reality clinical-experimental tests of compassion treatment techniques to reduce paranoia

Paranoia may build on negative beliefs held both about the self and others. Compassionate imagery may be one way of reducing such negative beliefs, and hence paranoia. Two studies tested this idea, one targeting compassion for the self and one targeting compassion for others. Two-hundred individuals from the general population scoring highly for paranoia were recruited. The studies used a randomised controlled experimental design, with embedded tests for mediation. Study one targeted self-compassion via creation of a compassionate coach (CC) image. Study two targeted compassion for others via loving kindness meditation (LKM). Individuals repeatedly entered neutral virtual reality social environments. Changes in compassion and paranoia were assessed. Compared to controls, the CC group increased in self-compassion (group difference = 2.12, C.I. = 1.57;2.67, p = <0.0001, d = 1.4) and decreased in paranoia (group difference = −1.73, C.I. = −2.48; −0.98, p = <0.0001, d = 0.8). Change in self-compassion explained 57% of change in paranoia. Compared to controls, the LKM group increased their compassion for others (group difference = 3.26, C.I. = 2.72;3.80, p = <0.0001, d = 1.7), and decreased in paranoia (group difference = −1.70, C.I. = −2.50; −0.89, p = <0.0001, d = 0.8). Change in compassion for others explained 67% of change in paranoia. Targeting negative beliefs about the self and others using compassionate imagery causes reductions in paranoia. Tests in clinical populations are indicated

Insomnia, negative affect, and psychotic experiences: Modelling pathways over time in a clinical observational study

Insomnia has been shown to contribute to the development of psychotic experiences, predominantly via increasing negative affect. However, the role of insomnia in the persistence of psychotic experiences is yet to be investigated in a clinical population. Furthermore, other plausible influences, such as psychotic experiences contributing to insomnia, remain to be evaluated. This study tests the role of insomnia as a predictor of persistence of psychotic experiences versus other potential causal routes. Twenty-nine patients aged 18–30 with non-affective psychosis completed three assessments over three months of their insomnia, negative affect, and psychotic experiences. Mixed effect models allowed comparisons between hypothesis-based models (comprising insomnia as predictor, negative affect as mediator, and psychotic experiences as outcome) and oppositional models, where relationships were reversed. The results supported the hypothesised mediation model above models where negative affect was primary. Insomnia was also found to be a stronger predictor of later hallucinations than vice versa, although a bidirectional relationship was indicated between insomnia and paranoia. In conclusion, insomnia predicts persistence of psychotic experiences over time to the same or greater extent than psychotic experiences contribute to insomnia. This supports insomnia as a potential intervention target in psychosis

Influence of spatial environment on maze learning in an African mole-rat

In subterranean species where excavation is energetically expensive, efficient spatial navigation is vital to reducing the costs of locating important resources such as food and mates. While spatial navigational ability is positively correlated with sociality in subterranean mammals, we have a less clear understanding of the role of habitat complexity on navigational ability. We tested spatial navigational ability and memory in 12-18 month captive Natal mole-rats (Cryptomys hottentotus natalensis) maintained in a simple environment with no environmental enrichment and newly captured wild individuals from natural, complex burrow systems. In maze trials, mole-rats captured freshly from the wild made significantly fewer navigational errors, were more likely to successfully navigate the maze, travelled shorter distances and as a consequence, completed the maze in less time. Male mole-rats from both experimental treatments were more likely to complete the maze than females. Memory retention of the maze was tested on day two, seven, 30 and 60 respectively. The results were variable, although both groups showed a significant memory retention 60 days after testing. Our results highlight the potential importance of the environment (microhabitat complexity) on spatial cognitive performance in mole-rats.A grant from the University of the Witwatersrand to MJW.http://www.springerlink.com/content/1435-9448

Mixed effects approach to the analysis of the stepped wedge cluster randomised trial—Investigating the confounding effect of time through simulation

<div><p>Background</p><p>A stepped wedge cluster randomised trial (SWCRT) is a multicentred study which allows an intervention to be rolled out at sites in a random order. Once the intervention is initiated at a site, all participants within that site remain exposed to the intervention for the remainder of the study.</p><p>The time since the start of the study (“calendar time”) may affect outcome measures through underlying time trends or periodicity. The time since the intervention was introduced to a site (“exposure time”) may also affect outcomes cumulatively for successful interventions, possibly in addition to a step change when the intervention began.</p><p>Methods</p><p>Motivated by a SWCRT of self-monitoring for bipolar disorder, we conducted a simulation study to compare model formulations to analyse data from a SWCRT under 36 different scenarios in which time was related to the outcome (improvement in mood score). The aim was to find a model specification that would produce reliable estimates of intervention effects under different scenarios. Nine different formulations of a linear mixed effects model were fitted to these datasets. These models varied in the specification of calendar and exposure times.</p><p>Results</p><p>Modelling the effects of the intervention was best accomplished by including terms for both calendar time and exposure time. Treating time as categorical (a separate parameter for each measurement time-step) achieved the best coverage probabilities and low bias, but at a cost of wider confidence intervals compared to simpler models for those scenarios which were sufficiently modelled by fewer parameters. Treating time as continuous and including a quadratic time term performed similarly well, with slightly larger variations in coverage probability, but narrower confidence intervals and in some cases lower bias. The impact of misspecifying the covariance structure was comparatively small.</p><p>Conclusions</p><p>We recommend that unless there is a priori information to indicate the form of the relationship between time and outcomes, data from SWCRTs should be analysed with a linear mixed effects model that includes separate categorical terms for calendar time and exposure time. Prespecified sensitivity analyses should consider the different formulations of these time effects in the model, to assess their impact on estimates of intervention effects.</p></div