Carbon market and technology transfer: statistical analysis for exploring implications

The impact of clean development mechanism (CDM) projects on climate change technology transfer (CCTT), which is essential for developing countries to achieve higher mitigation targets and move towards more sustainable paths, has been, until now, inadequately understood and analysed. The aim of this paper is to analyse the carbon market contribution to CCTT, mainly through the CDM, so as to stimulate developing countries towards the deployment and diffusion of low-carbon technologies that fulfil their sustainability goals. Indeed, relatively few studies deal with the assessment of the CDM contribution to CCTT, mainly through desk analysis and empirical evaluations on project design documents. To the best of our knowledge, there are no studies dealing with CCTT through CDM projects using statistical approaches. The added value of this article is the use of statistical analysis, time series analysis and multiple linear regression to analyse carbon market experiences in selected cross-representative developing countries. This assessment indicated the very heterogeneous CCTT across CDM project types, varying significantly in terms of reliance on imported technology, mix of equipment and knowledge and source countries for the technology.     

Contents Volume 9

Volume Contents

Contents Volume 9     

Biochemical and histopathological ultrastructural changes caused by ZnO nanoparticles in mice

Five week-old mice were divided into a vehicle control group, and groups exposed to ZnO nanoparticles at low (0.5 g/kg), middle (1 g/kg), high (3 g/kg), and exceptionally high-dose (5 g/kg). After the first, second, third, and fourth weeks’ of exposure, blood biochemistry, histopathology, and electron microscopic ultrastructural changes in liver, kidney and spleen were investigated. Increased alkaline phosphatase activities were observed in all treated mice being statistically significant at higher dose. No changes were observed in the serum glutamic pyruvic transaminase, serum glutamic oxaloacetic transaminase, creatinine, blood urea nitrogen, and lipid levels. During the first and second weeks of the treatment, effects on the cytoarchitecture of liver, kidney, and spleen were not perceived while during the third and fouth weeks of treatment sporadic mild effects were seen. Ultrastructural electron microscopic changes in liver, kidney, and spleen were not observed for the low-dose group on the first, second, third, and fourth weeks, suggesting that exposure to ZnO nanoparticles at low dose is safe. Long-term (i.e., more than 28 days) exposure to the exceptionally high-dose resulted in sporadic changes in nuclear chromatin condensation, irregular nuclear membrane, polymorphic mitochondria, mitochondrial swelling, and vacuolation. ZnO nanoparticles could be well tolerated and no death occurred in any group of treated mice.     

Integrated Traffic and Emission Simulation: a Model Calibration Approach Using Aggregate Information

Environmental impacts of road traffic have attracted increasing attention in project-level traffic planning and management. The conventional approach considers emission impact analysis as a separate process in addition to traffic modeling. This paper first introduces our research effort to integrate traffic, emission, and dispersion processes into a common distributed computational framework, which makes it efficient to quantify and analyze correlations among dynamic traffic conditions, emission impacts, and air quality consequences. A model calibration approach is particularly proposed when on-road or in-lab instantaneous emission measurements are not directly available. Microscopic traffic simulation is applied to generate dynamic vehicle states at the second-by-second level. Using aggregate emission estimation as standard reference, a numerical optimization scheme on the basis of a stochastic gradient approximation algorithm is applied to find optimal parameters for the dynamic emission model. The calibrated model has been validated on several road networks with traffic states generated by the same simulation model. The results show that with proper formulation of the optimization objective function, the estimated dynamic emission model can capture the trends of aggregate emission patterns of traffic fleets and predict local emission and air quality at higher temporal and spatial resolutions.     

Evaluating the environmental effects of economic openness: evidence from SAARC countries

Environmental Science and Pollution Research - This study investigates the possible environmental effects of economic openness, such as economic growth, foreign direct investment (FDI) inflows, and...     

Application of enrichment factor,geoaccumulation index,and ecological risk index in assessing the elemental pollution status of surface sediments

Environmental Geochemistry and Health - Sediment can accumulate trace elements in the environment. This study profiled the magnitude of As, Ba, Cd, Co, Cu, Cr, Ni, Pb, Se, and Zn pollution in...