Analysis of the global warming dynamics from temperature time series

Global warming is the observed increase of the average temperature of the Earth. The primary cause of this phenomenon is the release of the greenhouse gases by burning of fossil fuels, land cleaning, agriculture, among others, leading to the increase of the so-called greenhouse effect. An approach to deal with this important problem is the time series analysis. In this regard, different techniques can be applied to evaluate the global warming dynamics. This kind of analysis allows one to make better predictions increasing our comprehension of the phenomenon. This article applies nonlinear tools to analyze temperature time series establishing state space reconstruction and prediction. Since noise contamination is unavoidable in data acquisition, it is important to employ robust techniques. The method of delay coordinates is employed for state space reconstruction and delay parameters are evaluated using the method of average mutual information and the method of false nearest neighbors. Afterwards, the simple nonlinear prediction method is employed to estimate temperatures of the future. Temperature time series from different places of the planet are used. Initially, the approach is verified considering known parts of the time series and afterwards, results are extrapolated for future values estimating temperature until 2028. Results show that these techniques are interesting to estimate temperature time history, presenting coherent estimations.     

What are the barriers to successful community-based climate change adaptation? A review of grey literature

ABSTRACT

Across the Global South, community-based adaptation (CBA) projects are increasingly being implemented in an effort to respond effectively and sustainably to the impacts of climate change, with a particular focus on people’s livelihoods. Despite an increase in the number of CBA projects being implemented, detailed analysis and evaluation of their efficacy and the barriers faced in achieving successful outcomes is lacking. This study draws on an analysis of grey literature (i.e. project and donor reports) to explore the barriers faced in achieving effective CBA. An extensive global search of online project evaluations yielded 25 documents comprising 69 projects from which this analysis is based. This paper first presents an overview of the 69 projects and highlights any trends. Second, this paper describes the barriers to CBA according to three broad themes: socio-political, resource, and physical systems and processes. Following this is a discussion of the most prevalent barriers: cognitive and behavioural, financial, and human resources. Third, this paper discusses the key findings elucidated from this review. This includes the need for greater sharing of project reports and findings so lessons can be learned across spatial and temporal scales, and the disparity between critical academic literature on CBA and what is implemented in practice.     

Impact of bioenergy crops in a carbon dioxide constrained world: an application of the MiniCAM energy-agriculture and land use model

In the coming century, modern bioenergy crops have the potential to play a crucial role in the global energy mix, especially under policies to reduce carbon dioxide emissions as proposed by many in the international community. Previous studies have not fully addressed many of the dynamic interactions and effects of a policy-induced expansion of bioenergy crop production, particularly on crop yields and human food demand. This study combines an updated agriculture and land use (AgLU) model with a well-developed energy-economic model to provide an analysis of the effects of bioenergy crops on energy, agricultural and land use systems. The results indicate that carbon dioxide mitigation policies can stimulate a large production of bioenergy crops, dependent on the level of the policy. This production of bioenergy crops can lead to several impacts on the agriculture and land use system: decreases in forestland and unmanaged land, decreases in the average yield of food crops, increases in the prices of food crops, and decreases in the level of human demand of calories.

The benefits of the Kyoto Protocol to developing countries

The Kyoto Protocol relies on incentive-based regulations layered underneath a global cap on net emissions of greenhouse gases. Within the Kyoto Protocol are opportunities and constraints for signatory nations. Of concern to developing nations are the constraints the Kyoto Protocol could place on future growth. We examine the constraints and the opportunities offered to developing countries within the Kyoto Protocol. By identifying the potential costs and benefits the Kyoto Protocol has to offer to developing countries and by examining the incentives each create, we hope to spark serious investigations into ways to minimize the potential costs of entering the Kyoto Protocol and take full advantage of the potential benefits.

Modelling forest management within a global vegetation model—Part 2: Model validation from a tree to a continental scale

The construction of a new forest management module (FMM) within the ORCHIDEE global vegetation model (GVM) allows a realistic simulation of biomass changes during the life cycle of a forest, which makes many biomass datasets suitable as validation data for the coupled ORCHIDEE-FM GVM. This study uses three datasets to validate ORCHIDEE-FM at different temporal and spatial scales: permanent monitoring plots, yield tables, and the French national inventory data. The last dataset has sufficient geospatial coverage to allow a novel type of validation: inventory plots can be used to produce continuous maps that can be compared to continuous simulations for regional trends in standing volumes and volume increments. ORCHIDEE-FM performs better than simple statistical models for stand-level variables, which include tree density, basal area, standing volume, average circumference and height, when management intensity and initial conditions are known: model efficiency is improved by an average of 0.11, and its average bias does not exceed 25%. The performance of the model is less satisfying for tree-level variables, including extreme circumferences, tree circumference distribution and competition indices, or when management and initial conditions are unknown. At the regional level, when climate forcing is accurate for precipitation, ORCHIDEE-FM is able to reproduce most productivity patterns in France, such as the local lows of needleleaves in the Parisian basin and of broadleaves in south-central France. The simulation of water stress effects on biomass in the Mediterranean region, however, remains problematic, as does the simulation of the wood increment for coniferous trees. These pitfalls pertain to the general ORCHIDEE model rather than to the FMM. Overall, with an average bias seldom exceeding 40%, the performance of ORCHIDEE-FM is deemed reliable to use it as a new modelling tool in the study of the effects of interactions between forest management and climate on biomass stocks of forests across a range of scales from plot to country.     

Inverse calculation approaches for source determination in hazardous chemical releases

Source determination is vital in decision making and emergency planning involving hazardous chemical releases. This work was concentrated on inverse calculation approaches for source determination as well as current trends and future perspectives. In this paper, these different approaches are reviewed by dividing them into two categories: probability modeling methods and optimization modeling methods. The traits of these approaches are comparatively analyzed. Then it is shown how these approaches behave when applied to practical cases, and their feasibility, applicability, stability, and limitation in determining the location and strength are presented. It is argued that when experimenting with potential terrorist attacks involving hazardous chemical releases, observation points should be around the main line of the downwind direction when the source is known; while the uniform distribution of observation points is an efficient solution for unknown incidents. Probability modeling methods are demonstrated to be insufficient during emergency responses due to their lacking of enough prior information of unknown parameters, while optimization modeling methods are efficient and become a new trend in source determination. Findings reflect an urgent need for the development of high-accuracy detectors and further research of data transmission techniques in order to ensure the validity of these approaches.     

Potential world garbage and waste carbon sequestration

To offset the carbon dioxide released by fossil fuels, a proposed sequestration strategy relies on burying garbage and waste in landfills. This paper roughly estimates the current annual world supply of carbonaceous waste to be 35.5 billion metric tons and to contain about 18 billion metric tons of carbon. If landfills received all of this waste, sequestration of more than 5.6 billion metric tons of carbon seems theoretically possible—an amount well in excess of the 3.3 billion metric tons which the atmosphere is currently gaining.     

Translating habitat class to land cover to map area of habitat of terrestrial vertebrates

Area of habitat (AOH) is defined as the “habitat available to a species, that is, habitat within its range” and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups.     

Characteristics of plankton Hg bioaccumulations based on a global data set and the implications for aquatic systems with aggravating nutrient imbalance

• Hg bioaccumulation by phytoplankton varies among aquatic ecosystems. • Active Hg uptake may exist for the phytoplankton in aquatic ecosystems. • Impacts of nutrient imbalance on food chain Hg transfer should be addressed. The bioaccumulation of mercury (Hg) in aquatic ecosystem poses a potential health risk to human being and aquatic organism. Bioaccumulations by plankton represent a crucial process of Hg transfer from water to aquatic food chain. However, the current understanding of major factors affecting Hg accumulation by plankton is inadequate. In this study, a data set of 89 aquatic ecosystems worldwide, including inland water, nearshore water and open sea, was established. Key factors influencing plankton Hg bioaccumulation (i.e., plankton species, cell sizes and biomasses) were discussed. The results indicated that total Hg (THg) and methylmercury (MeHg) concentrations in plankton in inland waters were significantly higher than those in nearshore waters and open seas. Bioaccumulation factors for the logarithm of THg and MeHg of phytoplankton were 2.4–6.0 and 2.6–6.7 L/kg, respectively, in all aquatic ecosystems. They could be further biomagnified by a factor of 2.1–15.1 and 5.3–28.2 from phytoplankton to zooplankton. Higher MeHg concentrations were observed with the increases of cell size for both phyto- and zooplankton. A contrasting trend was observed between the plankton biomasses and BAF_MeHg, with a positive relationship for zooplankton and a negative relationship for phytoplankton. Plankton physiologic traits impose constraints on the rates of nutrients and contaminants obtaining process from water. Nowadays, many aquatic ecosystems are facing rapid shifts in nutrient compositions. We suggested that these potential influences on the growth and composition of plankton should be incorporated in future aquatic Hg modeling and ecological risk assessments.