Suchergebnisse

The quantification of the effect of climate change mitigation actions is avery useful exercise that can be used to meet a variety of objectives, such asinforming policy design, enhancing policy implementation, assessing policyeffectiveness, justifying budget allocation, and attracting climate finance. Itis also a reporting requirement according to the reporting framework of theUnited Nations Framework Convention on Climate Change (UNFCCC) andthe Monitoring Mechanism Regulation of the European Union (EU) aboutclimate change relevant information. However, the reporting of emissionssavings associated to mitigation actions by EU Member States is not com-plete, according to recent technical reports of the European EnvironmentalAgency. The purpose of this paper is to present a methodological frameworkthat can be used to quantify the effect (i.e. emission reductions) of themitigation actions. It is based on comprehensive and transparent models andformulas that could be easily tracked and reproduced. The proposed frame-work could be easily applied by EU Member States, but also by other non-EUcountries, to enhance the reporting of climate change related informationto European Commission and UN bodies. By applying the methodologicalframework for Greece, as a case study, it was possible to estimate the effectof implemented policies and measures for historical years (ex-post analysis),but also to estimate the projected effect (ex-ante analysis) of implemented,adopted and planned policies for future years (e.g. 2030).

Abstract
We aimed at analyzing dose-response relationship between occupational exposure to a mixture of nanomaterials (NMs) and effect biomarkers measured according to the NanoExplore protocol in exhaled breath condensate (EBC, local pulmonary level)) and urine (systemic level) of 141 workers. Two exposure metrics: particle number concentration (PNC) and lung deposited surface area (LDSA) were monitored using DiSCMini for 2-4 8h-workshifts. Biological samples were collected twice, before and after exposure monitoring. We assumed that current or short-term exposure to NMs is associated in a linear dose-response manner to the effect biomarker concentration. We analyzed each biomarker separately, using the multilevel mixed-effects interval regression models to properly manage the biomarker concentrations the LOD or in the interval between the LOD and the limit of quantification. We used directed acyclic graphs to identify all potential confounders: age, smoking status, medication status, and study center. Center and the participant's ID were modeled as random effect variables. For IL-10, IL-1β and TNF-α in EBC we observed consistent positive dose-response relationships with both PNC and LDSA. For urinary Total Antioxidant Power the relationship was consistently negative. For MDA, KL-6, hs-CRP or NOTyr in EBC and urinary MDA and 8-Isoprostane, no relationship was found. These results suggest an activation of the innate immune response rather than oxidative stress as the main effect of the mixture of NM investigated. This study offers new insights into the dose-response relationship between exposure to NMs and possible indicators of early and long-term biological alterations in the cohort of recruited workers.