Four policies might close the gap between the global GHG emissions expected for 2020 on the basis of current (2013) policies and the reduced emissions that will be needed if the long-term global temperature increase can be kept below the 2 °C internationally agreed limit. The four policies are (1) specific energy efficiency measures, (2) closure of the least-efficient coal-fired power plants, (3) minimizing methane emissions from upstream oil and gas production, and (4) accelerating the (partial) phase-out of subsidies to fossil-fuel consumption. In this article we test the hypothesis of the International Energy Agency (IEA) that these policies will not result in a loss of gross domestic product (GDP) and we estimate their employment effects using the E3MG global macro-econometric model. Using a set of scenarios we assess each policy individually and then consider the outcomes if all four policies were implemented simultaneously. We find that the policies are insufficient to close the emissions gap, with an overall emission reduction that is 30% less than that found by the IEA. World GDP is 0.5% higher in 2020, with about 6 million net jobs created by 2020 and unemployment reduced.
Policy relevance
The gap between GHG emissions expected under the Copenhagen and Cancun Agreements and that needed for emissions trajectories to have a reasonable chance of reaching the 2 °C target requires additional policies if it is to be closed. This article uses a global simulation model E3MG to analyse a set of policies proposed by the IEA to close the gap and assesses their macroeconomic effects as well as their feasibility in closing the gap. It complements the IEA assessment by estimating the GDP and employment implications separately by the different policies year by year to 2020, by major industries, and by 21 world regions. 相似文献
This article assesses Japan's carbon budgets up to 2100 in the global efforts to achieve the 2?°C target under different effort-sharing approaches based on long-term GHG mitigation scenarios published in 13 studies. The article also presents exemplary emission trajectories for Japan to stay within the calculated budget.The literature data allow for an in-depth analysis of four effort-sharing categories. For a 450?ppm CO2e stabilization level, the remaining carbon budgets for 2014–2100 were negative for the effort-sharing category that emphasizes historical responsibility and capability. For the other three, including the reference ‘Cost-effectiveness’ category, which showed the highest budget range among all categories, the calculated remaining budgets (20th and 80th percentile ranges) would run out in 21–29 years if the current emission levels were to continue. A 550?ppm CO2e stabilization level increases the budgets by 6–17 years-equivalent of the current emissions, depending on the effort-sharing category. Exemplary emissions trajectories staying within the calculated budgets were also analysed for ‘Equality’, ‘Staged’ and ‘Cost-effectiveness’ categories. For a 450?ppm CO2e stabilization level, Japan's GHG emissions would need to phase out sometime between 2045 and 2080, and the emission reductions in 2030 would be at least 16–29% below 1990 levels even for the most lenient ‘Cost-effectiveness’ category, and 29–36% for the ‘Equality’ category. The start year for accelerated emissions reductions and the emissions convergence level in the long term have major impact on the emissions reduction rates that need to be achieved, particularly in the case of smaller budgets.Policy relevanceIn previous climate mitigation target formulation processes for 2020 and 2030 in Japan, neither equity principles nor long-term management of cumulative GHG emissions was at the centre of discussion. This article quantitatively assesses how much more GHGs Japan can emit by 2100 to achieve the 2?°C target in light of different effort-sharing approaches, and how Japan's GHG emissions can be managed up to 2100. The long-term implications of recent energy policy developments following the Fukushima nuclear disaster for the calculated carbon budgets are also discussed. 相似文献
Kajan subvolcanic rocks in the Urumieh–Dokhtar magmatic arc (UDMA), Central Iran, form a Late Miocene-Pliocene shallow-level intrusion. These subvolcanics correspond to a variety of intermediate and felsic rocks, comprising quartz diorite, quartz monzodiorite, tonalite and granite. These lithologies are medium-K calc-alkaline, with SiO2 (wt.%) varying from 52% (wt.%) to 75 (wt.%). The major element chemical data also show that MgO, CaO, TiO2, P2O5, MnO, Al2O3 and Fe2O3 define linear trends with negative slopes against SiO2, whilst Na2O and K2O are positively correlated with silica. Contents of incompatible trace elements (e.g. Ba, Rb, Nb, La and Zr) become higher with increasing SiO2, whereas Sr shows an opposite behaviour. Chondrite-normalized multi-element patterns show enrichment in LILE relative to HFSE and troughs in Nb, P and Ti. These observations are typical of subduction related magmas that formed in an active continental margin. The Kajan rocks show a strong affinity with calc-alkaline arc magmas, confirmed by REE fractionation (LaN/YbN = 4.5–6.4) with moderate HREE fractionation (SmN/YbN = 1.08–1.57). The negative Eu anomaly (Eu/Eu* <1), the low to moderate Sr content (< 400 ppm) and the Dy/Yb values reflect plagioclase and hornblende (+- clinopyroxene) fractionation from a calc-alkaline melt Whole–rock Sr and Nd isotope analyses show that the 87Sr/86Sr initial ratios vary from 0.704432 to 0.705989, and the 143Nd/144Nd initial ratios go from 0.512722 to 0.512813. All the studied samples have similar Sr-Nd isotopes, indicating an origin from a similar source, with granite samples that has more radiogenic Sr and low radiogenic Nd isotopes, suggesting a minor interaction with upper crust during magma ascent. The Kajan subvolcanic rocks plot within the depleted mantle quadrant of the conventional Sr-Nd isotope diagram, a compositional region corresponding to mantle-derived igneous rocks. 相似文献
Invasive plants pose significant threats to biodiversity and ecosystem function globally, leading to costly monitoring and management effort. While remote sensing promises cost-effective, robust and repeatable monitoring tools to support intervention, it has been largely restricted to airborne platforms that have higher spatial and spectral resolutions, but which lack the coverage and versatility of satellite-based platforms. This study tests the ability of the WorldView-2 (WV2) eight-band satellite sensor for detecting the invasive shrub mesquite (Prosopis spp.) in the north-west Pilbara region of Australia. Detectability was challenged by the target taxa being largely defoliated by a leaf-tying biological control agent (Gelechiidae: Evippe sp. #1) and the presence of other shrubs and trees. Variable importance in the projection (VIP) scores identified bands offering greatest capacity for discrimination were those covering the near-infrared, red, and red-edge wavelengths. Wavelengths between 400 nm and 630 nm (coastal blue, blue, green, yellow) were not useful for species level discrimination in this case. Classification accuracy was tested on three band sets (simulated standard multispectral, all bands, and bands with VIP scores ≥1). Overall accuracies were comparable amongst all band-sets (Kappa = 0.71–0.77). However, mesquite omission rates were unacceptably high (21.3%) when using all eight bands relative to the simulated standard multispectral band-set (9.5%) and the band-set informed by VIP scores (11.9%). An incremental cover evaluation on the latter identified most omissions to be for objects <16 m2. Mesquite omissions reduced to 2.6% and overall accuracy significantly improved (Kappa = 0.88) when these objects were left out of the confusion matrix calculations. Very high mapping accuracy of objects >16 m2 allows application for mapping mesquite shrubs and coalesced stands, the former not previously possible, even with 3 m resolution hyperspectral imagery. WV2 imagery offers excellent portability potential for detecting other species where spectral/spatial resolution or coverage has been an impediment. New generation satellite sensors are removing barriers previously preventing widespread adoption of remote sensing technologies in natural resource management. 相似文献
There is a pressing need to determine the relationships between driving variables and landscape transformations. Human activities shape landscapes and turn them into complex assemblages of highly diverse structures. Other factors, including climate and topography, also play significant roles in landscape transitions, and identifying the interactions among the variables is critical to environmental management. This study analyzed the configurations and spatial-temporal processes of landscape changes from 1998 to 2011 under different anthropogenic disturbances, identified the main variables that determine the landscape patterns and transitions, and quantified the relationships between pairs of driver sets. Landsat images of Baicheng and Tekes from 1998, 2006 and 2011 were used to classify landscapes by supervised classification. Redundancy analysis (RDA) and variation partitioning were performed to identify the main driving forces and to quantify the unique, shared, and total explained variation of the sets of variables. The results indicate that the proportions of otherwise identical landscapes in Baicheng and Tekes were very different. The area of the grassland in Tekes was much larger than that of the cropland; however, the differences between the grassland and cropland in Baicheng were not as pronounced. Much of the grassland in Tekes was located in an area that was near residents, whereas most of the grassland in Baicheng was far from residents. The slope, elevation, annual precipitation, annual temperature, and distance to the nearest resident were strong driving forces influencing the patterns and transitions of the landscapes. The results of the variation partitioning indicated complex interrelationships among all of the pairs of driver sets. All of the variable sets had significant explanatory roles, most of which had both unique and shared variations with the others. The results of this study can assist policy makers and planners in implementing sustainable landscape management and effective protection strategies. 相似文献
As an important canopy structure indicator, leaf area index (LAI) proved to be of considerable implications for forest ecosystem and ecological studies, and efficient techniques for accurate LAI acquisitions have long been highlighted. Airborne light detection and ranging (LiDAR), often termed as airborne laser scanning (ALS), once was extensively investigated for this task but showed limited performance due to its low sampling density. Now, ALS systems exhibit more competing capacities such as high density and multi-return sampling, and hence, people began to ask the questions like—“can ALS now work better on the task of LAI prediction?” As a re-examination, this study investigated the feasibility of LAI retrievals at the individual tree level based on high density and multi-return ALS, by directly considering the vertical distributions of laser points lying within each tree crown instead of by proposing feature variables such as quantiles involving laser point distribution modes at the plot level. The examination was operated in the case of four tree species (i.e. Picea abies, Pinus sylvestris, Populus tremula and Quercus robur) in a mixed forest, with their LAI-related reference data collected by using static terrestrial laser scanning (TLS). In light of the differences between ALS- and TLS-based LAI characterizations, the methods of voxelization of 3D scattered laser points, effective LAI (LAIe) that does not distinguish branches from canopies and unified cumulative LAI (ucLAI) that is often used to characterize the vertical profiles of crown leaf area densities (LADs) was used; then, the relationships between the ALS- and TLS-derived LAIes were determined, and so did ucLAIs. Tests indicated that the tree-level LAIes for the four tree species can be estimated based on the used airborne LiDAR (R2 = 0.07, 0.26, 0.43 and 0.21, respectively) and their ucLAIs can also be derived. Overall, this study has validated the usage of the contemporary high density multi-return airborne LiDARs for LAIe and LAD profile retrievals at the individual tree level, and the contribution are of high potential for advancing forest ecosystem modeling and ecological understanding. 相似文献