Drivers of farm-level adaptation to climate change in Africa: an evaluation by a composite index of potential adoption

Over recent decades, there has been increasing levels of research dedicated to assess drivers of farm-level uptake of adaptation strategies to climate change. The main purpose of this research being to determine how policy intervention can most effectively increase adoption. This paper aims to synthesise this past research in order to scale up uptake of farm-level adaptation strategies through a composite index of potential adoption in Africa. In doing so, we review the estimated coefficients of econometric regressions in 42 case studies published in peer-review journals to identify the factors that regularly explain adoption. We find that these common factors can be grouped into seven components, that is human capital, financial resources, infrastructure and technology, social interaction and governance, food security, dependence on agriculture and attitudes towards the environment. Using national-level indicators of these seven categories, we develop a composite index to inform potential adoption and test the robustness of the index in an in-depth sensitivity analysis. The results show that the highest likelihood of adoption of farm-level adaptation strategies is in Northern African countries namely Tunisia, Egypt, Algeria and Morocco and in Southern African countries such as South Africa and Botswana. Conversely, they indicate that the lowest likelihood of adoption is situated in nations of the Sahel and Horn of Africa and in nations that have recently experienced conflict. We conclude that adoption is associated predominantly with governance, civil rights, financial resources and education. However, it is not necessarily driven by the magnitude of climate change impacts on agricultural production.     

The Effect of Ethanol Fuel on the Emissions of Vehicles over a Wide Range of Temperatures

ABSTRACT

The emissions from a fleet of 11 vehicles, including three from the State of Alaska, were tested at 75, 0, and -20 °F with base gasolines and E10 gasolines, that is, gasolines with 10% by volume ethanol added. The data for the changes in emissions for the test run at 75 °F are included, since most other studies on the effects of E10 gasoline on emissions were run at that temperature. The three Alaskan vehicles were also tested at 20 °F. The testing followed the Federal Test Procedure, and regulated emissions—CO, total hydrocarbons (THC), and nitrogen oxides (NO_x)—CO₂, speciated organics, and fuel economy were measured. A total of 490 FTP tests were run. The data obtained indicated that with most vehicles, at the temperatures tested, improvements in both CO and THC emissions were obtained with the use of E10 fuel. At the lowest temperature used, -20 °F, most vehicles had an increase in NO emissions with the use of E10 fuel. At the other temperatures, however, more vehicles showed a decrease in NO_x emissions with the use of E10. With all vehicles at all temperatures tested, the emissions of acetaldehyde increased significantly when E10 fuel was used. The highest increase was about 8 to 1. Benzene, formaldehyde, and 1,3 butadiene showed both increases and decreases in the emissions when using E10 fuel. Unexpected results were obtained with the fuel economy, with about half of the tests showing an increase in fuel economy with the use of E10 fuel.     

Estimating prevalence using composites

We are interested in estimating the fraction of a population that possesses a certain trait, such as the presence of a chemical contaminant in a lake. A composite sample drawn from a population has the trait in question whenever one or more of the individual samples making up the composite has the trait. Let the true fraction of the population that is contaminated be p. Classical estimators of p, such as the MLE and the jackknife, have been shown to be biased. In this study, we introduce a new shrinking estimator which can be used when doing composite sampling. The properties of this estimator are investigated and compared with those of the MLE and the jackknife.     

Combined effects of deltamethrin, temperature and salinity on oxidative stress biomarkers and acetylcholinesterase activity in the black tiger shrimp (Penaeus monodon)

This study aimed to investigate the interactions of two abiotic factors (temperature and salinity) and deltamethrin (pyrethroid pesticide) exposure on some oxidative stress biomarkers as well as on acetylcholinesterase activity (AChE) in hepatopancreas, gills and muscle of black tiger shrimp (Penaeus monodon). A combination of three temperatures (24, 29 and 34 °C), two salinities (15 and 25 ppt), and the absence or presence of 0.1 μg L⁻¹ deltamethrin was applied on shrimp during 4 d under laboratory conditions. Lipid peroxidation level (LPO) and glutathione S-transferase activity (GST) were not affected by combined effect of temperature, salinity and deltamethrin in any of the studied tissues. Deltamethrin impaired other tested oxidative stress biomarkers, i.e. total glutathione (tGSH), catalase (CAT), glutathione peroxidase (GPx). tGSH level significantly increased in hepatopancreas due to deltamethrin exposure mainly at 34 °C, while pesticide effects on tGSH and CAT activity in gills were influenced by both temperature and salinity. In addition, GPx activity in hepatopancreas decreased after deltamethrin treatment mainly at 24 °C. Finally, AChE in muscle was strongly inhibited by deltamethrin at all tested temperatures and salinities. These novel findings demonstrate that interactions between abiotic factors and a commonly used pesticide exposure should be taken into account when analyzing some widespread biomarkers in black tiger shrimp.     

A New Test Method for Determining Biodegradation of Plastic Material Under Controlled Aerobic Conditions in a Soil-Simulation Solid Environment

A new test method is described for assessing biodegradation of plastic material under simulated soil conditions. An inert substrate can be activated with soil extract and nutrient and used in place of soil in biodegradation tests. The biodegradation level is evaluated by determining the carbon dioxide (CO₂) production released by the test reactors. Effects of substrate nature, solution pH, nutrient composition, soil extract concentration, and activation duration on CO₂ production were investigated, and the experimental conditions were optimized. Results obtained with cellulose showed a biodegradation rate of 80% within 28 days. Moreover, with this kind of substrate, reaction products and residues can be easily extracted and analysed.     

Modelling Easily Biodegradability of Materials in Liquid Medium-Relationship Between Structure and Biodegradability

In the present project, twenty materials (e.g., polyhydroxybutyrate-hydroxyvalerate, polycaprolactone, cellulose acetate, polyacticacid, polyethylene), representing varied biodegradability levels were studied. An aerobic respirometric test, based on the CEN Draft, was setup. The biodegradability of each plastic film was evaluated by measuring the percentage of carbon converted into CO₂ during 35 days. The values of the CO₂ production were plotted versus days as a cumulative function. In order to reduce its number of points, the cumulative curve was modeled using a sigmoïd function (Hill sigmoïd). This model was compared to one found in the literature. A _i ² test showed that the biodegradation curve was more accurately fitted with the model than the previous one. Three kinetic parameters were determined by this Hill model: one represents the maximal percentage of carbon converted into CO₂, the second the half-life time in days of the degrading part of the material and the third one the curve radius.In addition, the following analyses were carried out on each sample: elemental analysis, thickness, hydrophobicity and surface free energy measurements. In order to compress the information and to keep only relevant pieces, these parameters were submitted to a Principal Component Analysis. PCA found linear combinations of variables that describe major trends in the data. The two principal components which separate groups of materials were closely related to a chemical and a physical axis respectively. Materials showing a high biodegradability were related to high oxygen (and nitrogen) contents and low hydrophobicity: Material thickness did not influence the likeliness to biodegradability described by the maximum biodegradation rate. Finally, this study established the correlation between the biodegradation and the structure of biopolymers.     

An ecotoxicological view on neurotoxicity assessment

The numbers of potential neurotoxicants in the environment are raising and pose a great risk for humans and the environment. Currently neurotoxicity assessment is mostly performed to predict and prevent harm to human populations. Despite all the efforts invested in the last years in developing novel in vitro or in silico test systems, in vivo tests with rodents are still the only accepted test for neurotoxicity risk assessment in Europe. Despite an increasing number of reports of species showing altered behaviour, neurotoxicity assessment for species in the environment is not required and therefore mostly not performed. Considering the increasing numbers of environmental contaminants with potential neurotoxic potential, eco-neurotoxicity should be also considered in risk assessment. In order to do so novel test systems are needed that can cope with species differences within ecosystems. In the field, online-biomonitoring systems using behavioural information could be used to detect neurotoxic effects and effect-directed analyses could be applied to identify the neurotoxicants causing the effect. Additionally, toxic pressure calculations in combination with mixture modelling could use environmental chemical monitoring data to predict adverse effects and prioritize pollutants for laboratory testing. Cheminformatics based on computational toxicological data from in vitro and in vivo studies could help to identify potential neurotoxicants. An array of in vitro assays covering different modes of action could be applied to screen compounds for neurotoxicity. The selection of in vitro assays could be guided by AOPs relevant for eco-neurotoxicity. In order to be able to perform risk assessment for eco-neurotoxicity, methods need to focus on the most sensitive species in an ecosystem. A test battery using species from different trophic levels might be the best approach. To implement eco-neurotoxicity assessment into European risk assessment, cheminformatics and in vitro screening tests could be used as first approach to identify eco-neurotoxic pollutants. In a second step, a small species test battery could be applied to assess the risks of ecosystems.