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The Smart City model is now considered one of the opportunities to rethink cities and, in general, the development of urban communities. One of the most relevant themes in the application of the Smart City paradigm is the city/energy relationship and Italian cities are fielding several actions to effectively cope with the energy issues. Nevertheless, actions and projects are often uncritically promoted as ‘smart’, but actually lack innovative contents and methods. Therefore, the aim of this research, of which we present the first findings, is the drafting of a survey, tested through field analysis, of the experimentations of Italian metropolitan areas on the Smart City topic. The in-depth analysis of two case studies, Genoa and Naples, allowed us to compare the actual state of the two cities. We have that they have undertaken a common path in the implementation of strategies to try to transform themselves into Smart Cities, focusing especially on the energy aspects. Tema. Journal of Land Use, Mobility and Environment, Vol 8, N° 2 (2015): Cities, Energy and Built Environment

Europe must move towards a 100% renewable transportation system for climate, energy and sustainability reasons. We estimate the capital and energy required for building and operating a renewable transportation system providing similar services as the EU-28 transport system of 2016. It could be based on: biogas or fuel cell vessels; liquid biogas powered aircrafts; electric railways and fuel cell or electric vehicles between major cities; and car sharing, electric buses and electric two- and three-wheelers, for short journeys. A system of charging posts on the streets and roads for passenger and commercial e-vehicles is studied. Alternatively, a Tracked Electric Vehicle system of continuous power on European roads would improve energy efficiency and the saving of scarce metals (Ni, Li), at a lower cost, if only national roads were electrified. The investment for the construction of the whole system would be 2.3–2.7% of the EU’s GDP per year for 30 years. The new system operation would require 16% less energy than that of 2016, with reduction of 70% in road transport. However, shipping and aviation would demand 162% and 149% more energy, respectively, if liquefied biogas were used as fuel. A type of land transport fully based on trains would provide a similar service to that of an electric vehicle fleet, with a 29% lower energy consumption.

Abstract. Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe datasets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil-fuel combustion and cement production (EFF) are based on energy statistics, while emissions from Land-Use Change (ELUC), including deforestation, are based on combined evidence from land-cover change data, fire activity in regions undergoing deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated for the first time in this budget with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of Dynamic Global Vegetation Models. All uncertainties are reported as ± 1 sigma, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2003–2012), EFF was 8.6 ± 0.4 GtC yr−1, ELUC 0.8 ± 0.5 GtC yr−1, GATM 4.3 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 2.6 ± 0.8 GtC yr−1. For year 2012 alone, EFF grew to 9.7 ± 0.5 GtC yr−1, 2.2% above 2011, reflecting a continued trend in these emissions; GATM was 5.2 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and assuming and ELUC of 0.9 ± 0.5 GtC yr−1 (based on 2001–2010 average), SLAND was 2.5 ± 0.9 GtC yr−1. GATM was high in 2012 compared to the 2003–2012 average, almost entirely reflecting the high EFF. The global atmospheric CO2 concentration reached 392.52 ± 0.10 ppm on average over 2012. We estimate that EFF will increase by 2.1% (1.1–3.1%) to 9.9 ± 0.5 GtC in 2013, 61% above emissions in 1990, based on projections of World Gross Domestic Product and recent changes in the carbon intensity of the economy. With this projection, cumulative emissions of CO2 will reach about 550 ± 60 GtC for 1870–2013, 70% from EFF (390 ± 20 GtC) and 30% from ELUC (160 ± 55 GtC). This paper is intended to provide a baseline to keep track of annual carbon budgets in the future. All data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (10.3334/CDIAC/GCP_2013_v1.1).