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The effects of climate change and greenhouse gases (GHG) emissions are one of the deep concerns today. The energy generation sector contributes significantly to these emissions, potentiating the climate change and the vulnerability of society and the environment. To attain the Paris Agreement goals, the decarbonization of energy sector at global scale may be a solution, which includes the insertion of more renewable sources in the energy mix. In this sense, the increase on generation by wind energy is a feasible option to achieve these targets. Although the wind energy is considered a “cleaner” source and “free of CO 2 emissions”, when its entire life cycle is considered, it is possible to verify that certain stages, namely the equipment manufacturing and decommissioning, have different and significant contributions in terms of inputs and energy consumption, but also gases emissions and environmental impacts. Thereby, the aim of this research is to present a systematic literature review of wind farms life cycle assessments, the relevant aspects related to CO2 emissions and resource consumption are highlighted, and improvements in process and advantages of equipment reusing in end of service for diminishing the effects of climate change are discussed.

This research analyzes the evolution of CO2 emissions per capita in a sample of 141 countries during the period 1970–2014. The study develops a spatially augmented Green Solow model by taking into consideration technological externalities and interdependence in the process of production, which ultimately implies that CO2 emissions in an economy are affected by the economic characteristics in neighboring countries. The empirical model predicts convergence in CO2 emissions among countries which is examined by means of modern dynamic spatial panel econometric techniques. The multimodal distribution of the CO2 emissions is consistent with the existence of three spatial clubs. The space-time dynamics of the three clubs are analyzed by means of the Local Directional Moran Scatterplot and spatial panel model with heterogeneous parameters. Our analysis reveals the hypothesis of spatial convergence clubs is more consistent with the data than the hypothesis of conditional convergence.

District Heating Systems (DHS) are a solution for the supply of heating and cooling in urban areas. Thanks to the possibility of exploiting multiple energy sources, a well-designed and well-operated DHS can allow primary energy savings, CO2 emissions reduction and integration of renewable energy sources for the heat generation. However, each DHS has its own peculiarities and its conversion and distribution efficiency is affected by several factors, including design parameters as well as operational choices and potential unexpected behaviours. Performance indicators calculated on a statistically relevant set of DHS can provide useful insights on their range of variability. This paper analyzes the performance of several DHS, by calculating the primary energy factor and the CO2 emission factor of the heat supplied to the users, using the current methodology defined by the European Standards. The results show that the efficiency of DHS is mainly affected by the energy source and the conversion technologies, but also the network losses have a crucial impact on the overall performance. The majority of the DHS included in this analysis supply heat to the users with a primary energy factor in the range 0.9–1.8 and a CO2 emission factor between 0 and 0.30 kg/kWh. The operation of Combined Heat and Power generation units connected to DHS needs to be analyzed with reference to the characteristics of the electricity available on the National Power Grid.

In this note, we establish an alternative reference scenario based on an ARFIMA model estimated using global CO2 emissions from 1750 to 2013. These new reference forecasts are free from additional assumptions on demographic and economic variables, often used in most reference forecasts. Instead, we only rely on the properties of the underlying stochastic process for global CO2 emissions that are, in this sense, closer to fundamentals. Our reference forecasts are clearly below the levels proposed by other reference scenarios available in the literature. This is important, as it suggests that the ongoing policy goals are actually easier to reach than what is implied by the standard reference scenarios. Having lower and more realistic reference emissions projections gives a truer assessment of the policy efforts that are needed, and highlights the lower costs involved in mitigation efforts, thereby maximizing the likelihood of more widespread environmental policy efforts.