The objective of this study is to identify the feasibility of using rhamnolipid biosurfactant to remediate heavy metals contained in manganese nodules collected from the Clarion-Clipperton Fracture Zone, Pacific Ocean. Deep-sea manganese nodules may represent one of the most important future natural resources for heavy metals due to the depletion of resources on land. Since international marine environment guidelines for deep-sea mining will be set up by international organisations in the 2020s, remediation technologies are urgently required for deep-sea mining tailings. We show that rhamnolipid biosurfactant is an environmentally friendly substance and can be successfully used for the remediation of heavy metals in deep-sea mining tailings under various reaction conditions. Rhamnolipids therefore represent a useful extracting agent for heavy metals in deep-sea mining tailings. The removal of nickel (Ni), copper (Cu), and cadmium (Cd) would be enhanced in the presence of rhamnolipids with specific reaction times and concentrations. Future actual remediation technologies should be developed using rhamnolipid biosurfactant on the basis of these results.

Over the last few years, intensive agriculture has often been denounced as a source of negative effects, particularly at the environmental and health level (overexploitation of natural resources, degradation of their quality, appearance and development of several diseases, etc.). Reducing the excessive use of agricultural inputs for the protection of the environment and the preservation of human and animal health is a social requirement nowadays. Investing in more sustainable agricultural models which make it possible to reduce, or even eliminate the risks, has become urgent. A possible solution may be to resort to agroecological systems. In order to be sustainable, these new systems must be performant at the agronomic, economic, social, and environmental levels. There is a multitude of tools for assessing the sustainability of agricultural systems. These tools are inappropriate for organic and agroecological systems, and do not make it possible to measure the agroecological transition performance of farms (Trabelsi et al. Environ Sci Pollut Res 23:139–156, 2016; Trabelsi 2017). This research project aims to design a decision support tool in order to help farms throughout the agroecological transition process, to assess the performance of this transition, and to put forward improvement scenarios. Contrary to other assessment methods, ESSIMAGE (Evaluation and Simulation of Agroecological Systems) is based on both pressure and impact indicators, and takes the specificities of agricultural production systems into account. It is a dynamic tool which not only makes it possible to assess farm performance at the present moment but also to consider the future by putting forward possible alternative improvement scenarios and by simulating their consequences at a later stage. ESSIMAGE is based on the interaction of two elements: agro-environmental, social, and economic indicators, and the GIS (Geographic Information System) software. This tool has been tested as part of a CASDAR “Post-MAET Gimone” (agriculture.gouv.fr/ministere/mobilisation-collective-pour-lagroecologie.) project on the subject of “Collective mobilization for agroecology” by using farm data, most of the farms having been involved in an agro-environmental measure for the progressive reduction of phytosanitary treatments since 2008. It has made it possible to compare the agroecological performances of these farms with an optimal situation, as well as with each other. Considering the research objectives and the approaches discussed, this study is an original step in the development of agricultural management strategies in favor of agroecology.

Globalization is increasingly a driving force behind vibrant economies around the world. This paper discusses the impact of globalization and natural resources on economic growth from 1970 to 2014 in Pakistan. Based on an auto-regressive distributive lag (ARDL) model, the paper infers that globalization promotes economic growth in Pakistan. Natural resources also contribute to economic growth, as the causality results suggest bi-directional causality between globalization and use of natural resources. Policy implications are that countries should emphasize security, increase exports, encourage technological strength, and increase its intellectual management capacity.

The “resource curse” phenomenon has been the subject of extensive research, with its causes and transmission mechanisms primarily examined from the perspectives of economic development and rent seeking. Education is a major factor contributing to economically sustainable development, owing to its potential for improving cognition and skill levels and thereby enhancing worker productivity. The crowding-out or crowding-in effect of natural resource dependence on public education spending has been identified as one of the key mechanisms of the resource curse or blessing. Using panel data from 31 Chinese provinces, this empirical study revealed a positive correlation between natural resource dependence and public education expenditure, demonstrating the impact of the crowding-in effect, exerted by natural resource dependence, on public education expenditure. Abundant natural resources can provide funds for education expenditure. The sample was further divided into eastern and central and western regions. The results indicate that the crowding-out effect of natural resource dependence only affects public education expenditure in the Eastern region, while the crowding-in effect of natural resource dependence on public education expenditure in the central and western regions. Research shows that the regional differences of crowding-out or crowding-in effect are very obvious, so the government should adopt transfer payment to promote balanced regional development. Better economic and social policies will help to translate wealth from natural resources into economic growth. Thus, a “resource blessing” may emerge to replace the “resource curse.” Fairly distributed and higher quality education will enhance human capital, thereby promoting economic growth from its current resource-driven pattern to a knowledge-driven pattern.

The ecological footprint, a measure of human demand on earth’s ecosystems, represents the amount of biologically productive land and sea area that is necessary to supply the resources a human population consumes and to mitigate associated waste. This study estimates the impact of economic growth and natural resources on Pakistan’s ecological footprint using an autoregressive distributive lag (ARDL) model for long-run estimation. The empirical findings indicate that natural resources have a positive effect on an ecological footprint that deteriorates environmental quality and that natural resources help to support the environmental Kuznets hypothesis (EKC). Bidirectional causality is found between natural resources and the ecological footprint, along with a long-run causality between biocapacity and the ecological footprint. The innovative findings have important implications for policy.