The effects of global climate change on the cycling and processes of persistent organic pollutants (POPs) in the North Sea

The fate and cycling of two selected legacy persistent organic pollutants (POPs), PCB 153 and gamma-HCH, in the North Sea in the 21st century have been modelled with combined hydrodynamic and fate and transport ocean models
(HAMSOM and FANTOM, respectively). To investigate the impact of climate variability on POPs in the North Sea in the 21st century, future scenario model runs for three 10-year periods to the year 2100 using plausible levels of both in
situ concentrations and atmospheric, river and open boundary inputs are performed. This slice mode under a moderate scenario (A1B) is sufficient to provide a basis for further analysis. For the HAMSOM and atmospheric forcing, results of the IPCC A1B (SRES) 21st century scenario are utilized, where surface forcing is provided by the REMO downscaling of the ECHAM5 global atmospheric model, and open boundary conditions are provided by the MPIOM global ocean model.
Dry gas deposition and volatilization of gamma-HCH increase in the future relative to the present by up to 20% (in the spring and summer months for deposition and in summer for volatilization). In the water column, total mass of
gamma-HCH and PCB 153 remain fairly steady in all three runs. In sediment,
gamma-HCH increases in the future runs, relative to the present, while PCB 153 in sediment decreases exponentially in all three runs, but even faster in the future, due to the increased number of storms, increased duration of gale wind conditions and increased water and air temperatures, all of which are the result of climate change. Annual net sinks exceed sources at the ends of all periods.
Overall, the model results indicate that the climate change scenarios considered here generally have a negligible influence on the simulated fate and transport of the two POPs in the North Sea, although the increased number and magnitude of storms in the 21st century will result in POP resuspension and ensuing revolatilization events. Trends in emissions from primary and secondary sources will remain the key driver of levels of these contaminants over time.

How well do we understand and evaluate climate change feedback processes?

Processes in the climate system that can either amplify or dampen the climate response to an external perturbation are referred to as climate feedbacks. Climate sensitivity estimates depend critically on radiative feedbacks associated with water vapor, lapse rate, clouds, snow, and sea ice, and global estimates of these feedbacks differ among general circulation models. By reviewing recent observational, numerical, and theoretical studies, this paper shows that there has been progress since the Third Assessment Report of the Intergovernmental Panel on Climate Change in (i) the understanding of the physical mechanisms involved in these feedbacks, (ii) the interpretation of intermodel differences in global estimates of these feedbacks, and (iii) the development of methodologies of evaluation of these feedbacks (or of some components) using observations. This suggests that continuing developments in climate feedback research will progressively help make it possible to constrain the GCMs’ range of climate feedbacks and climate sensitivity through an ensemble of diagnostics based on physical understanding and observations.

Understanding the processes governing climate variability and change, climate predictability and the probability of extreme events

The purpose of Research Theme 4 (RT4) was to advance understanding of the basic science issues at the heart of the ENSEMBLES project, focusing on the key processes that govern climate variability and change, and that determine the predictability of climate. Particular attention was given to understanding linear and non-linear feedbacks that may lead to climate surprises,and to understanding the factors that govern the probability of extreme events. Improved understanding of these issues will contribute significantly to the quantification and reduction of uncertainty in seasonal to decadal predictions and projections of climate change. RT4 exploited the ENSEMBLES integrations (stream 1) performed in RT2A as well as undertaking its own experimentation to explore key processes within the climate system. It was working at the cutting edge of problems related to climate feedbacks, the interaction between climate variability and climate change � especially how climate change pertains to extreme events, and the predictability of the climate system on a range of time-scales. The statisticalmethodologies developed for extreme event analysis are new and state-of-the-art. The RT4-coordinated experiments, which have been conducted with six different atmospheric GCMs forced by common timeinvariant sea surface temperature (SST) and sea-ice fields (removing some sources of inter-model variability), are designed to help to understand model uncertainty (rather than scenario or initial condition uncertainty) in predictions of the response to greenhouse-gas-induced warming. RT4 links strongly with RT5 on the evaluation of the ENSEMBLES prediction system and feeds back its results to RT1 to guide improvements in the Earth system models and, through its research on predictability, to steer the development of methods for initialising the ensembles

Modelling climate change: the role of unresolved processes

Our understanding of the climate system has been revolutionized recently, by the development of sophisticated computer models. The predictions of such models are used to formulate international protocols, intended to mitigate the severity of global warming and its impacts. Yet, these models are not perfect representations of reality, because they remove from explicit consideration many physical processes which are known to be key aspects of the climate system, but which are too small or fast to be modelled. The purpose of this paper is to give a personal perspective of the current state of knowledge regarding the problem of unresolved scales in climate models. A recent novel solution to the problem is discussed, in which it is proposed, somewhat counter-intuitively, that the performance of models may be improved by adding random noise to represent the unresolved processes.

Change escalation processes and complex adaptive systems: from incremental reconfigurations to discontinuous restructuring

This study examines when “incremental” change is likely to trigger “discontinuous” change, using the lens of complex adaptive systems theory. Going beyond the simulations and case studies through which complex adaptive systems have been approached so far, we study the relationship between incremental organizational reconfigurations and discontinuous organizational restructurings using a large-scale database of U.S. Fortune 50 industrial corporations. We develop two types of escalation process in organizations: accumulation and perturbation. Under ordinary conditions, it is perturbation rather than the accumulation that is more likely to trigger subsequent discontinuous change. Consistent with complex adaptive systems theory, organizations are more sensitive to both accumulation and perturbation in conditions of heightened disequilibrium. Contrary to expectations, highly interconnected organizations are not more liable to discontinuous change. We conclude with implications for further research, especially the need to attend to the potential role of managerial design and coping when transferring complex adaptive systems theory from natural systems to organizational systems.

Intelligence is related to specific processes in visual change detection: Fixed-links modeling of hit rate and reaction time

By means of fixed-links modeling, the present study identified different processes of visual short-term memory (VSTM) functioning and investigated how these processes are related to intelligence. We conducted an experiment where the participants were presented with a color change detection task. Task complexity was manipulated through varying the number of presented stimuli (set size). We collected hit rate and reaction time (RT) as indicators for the amount of information retained in VSTM and speed of VSTM scanning, respectively. Due to the impurity of these measures, however, the variability in hit rate and RT was assumed to consist not only of genuine variance due to individual differences in VSTM retention and VSTM scanning but also of other, non-experimental portions of variance. Therefore, we identified two qualitatively different types of components for both hit rate and RT: (1) non-experimental components representing processes that remained constant irrespective of set size and (2) experimental components reflecting processes that increased as a function of set size. For RT, intelligence was negatively associated with the non-experimental components, but was unrelated to the experimental components assumed to represent variability in VSTM scanning speed. This finding indicates that individual differences in basic processing speed, rather than in speed of VSTM scanning, differentiates between high- and low-intelligent individuals. For hit rate, the experimental component constituting individual differences in VSTM retention was positively related to intelligence. The non-experimental components of hit rate, representing variability in basal processes, however, were not associated with intelligence. By decomposing VSTM functioning into non-experimental and experimental components, significant associations with intelligence were revealed that otherwise might have been obscured.

An updated synthesis of the observed and projected impacts of climate change on the chemical, physical and biological processes in the oceans

The 5th Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) states with very high certainty that anthropogenic emissions have caused measurable changes in the physical ocean environment. These changes are summarized with special focus on those that are predicted to have the strongest, most direct effects on ocean biological processes; namely, ocean warming and associated phenomena (including stratification and sea level rise) as well as deoxygenation and ocean acidification. The biological effects of these changes are then discussed for microbes (including phytoplankton), plants, animals, warm and cold-water corals, and ecosystems. The IPCC AR5 highlighted several areas related to both the physical and biological processes that required further research. As a rapidly developing field, there have been many pertinent studies published since the cut off dates for the AR5, which have increased our understanding of the processes at work. This study undertook an extensive review of recently published literature to update the findings of the AR5 and provide a synthesized review on the main issues facing future oceans. The level of detail provided in the AR5 and subsequent work provided a basis for constructing projections of the state of ocean ecosystems in 2100 under two the Representative Concentration Pathways RCP4.5 and 8.5. Finally the review highlights notable additions, clarifications and points of departure from AR5 provided by subsequent studies.

Adherence to a lifestyle physical activity program: Trends over time and associations with processes of change and physical activity

Research on lifestyle physical activity interventions suggests that they help individuals meet the new recommendations for physical activity made by the Centers for Disease Control and Prevention (CDC) and the American College of Sports Medicine (ACSM). The purpose of this research was to describe the rates of adherence to two lifestyle physical activity intervention arms and to examine the association between adherence and outcome variables, using data from Project PRIME, a lifestyle physical activity intervention based on the transtheoretical model and conducted by the Cooper Institute of Aerobics Research, Dallas, Texas. Participants were 250 sedentary healthy adults, aged 35 to 70 years, primarily non-Hispanic White, and in the contemplation and preparation stages of readiness to change. They were randomized to a group (PRIME G) or a mail- and telephone-delivered condition (PRIME C). Adherence measures included attending class (PRIME G), completing a monthly telephone call with a health educator (PRIME C), and completing homework assignments and self-monitoring minutes of moderate- to vigorous physical activity (both groups). In the first results paper, adherence over time and between conditions was examined: Attendance in group, completing the monthly telephone call, and homework completion decreased over time, and participants in PRIME G were more likely to complete homework than those in PRIME C. Paper 2 aimed to determine whether the adherence measures predicted achievement of the CDC/ACSM physical activity guideline. In separate models for the two conditions, a latent variable measuring adherence was found to predict achievement of the guideline. Paper 3 examined the association between adherence measures and the transtheoretical model's processes of change within each condition. For both, participants who completed at least two thirds of the homework assignments improved their use of the processes of change more than those who completed less than that amount. These results suggest that encouraging adherence to a lifestyle physical activity intervention, at least among already motivated volunteers, may increase the likelihood of beneficial changes in the outcomes. ^

Evaluation of a Change Detection Methodology by Means of Binary Thresholding Algorithms and Informational Fusion Processes

Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth?s resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution.

Overcoming resistance to change in business innovation processes

This paper summarizes the experience gained in dealing with resistance to change appeared in the companies when they develop innovative processes related to the adoption of new technologies, tools, equipment, infrastructure and methodologies. Technological innovation is rapidly absorbed by society on a personal level. But at the enterprise level, resistance to innovation can occur at any hierarchical level of the company and may appear with different intensity. Depending on the type of enterprise, the hierarchical level of the employee, the intensity of resistance and other factors, the measures taken are different. In this paper we summarize our experience in the cataloging of the resistance to innovation in terms of impact on workers and showing how technology education and business training can help overcome these resistance forces. This paper describes the experience acquired over 22 projects deployed in the period 2005 to 2011 and that has affected a total of 264 workers of different cultural, technological, business and hierarchical levels.

Processes for identifying regional influences of and responses to increasing atmospheric CO2 and climate change : the MINK project /

"TR052A-H."