The countries throughout the Belt and Road region account for more than 60% of the world's population and half of the global economy. Future changes in this area will have significant influences on the global economic growth, industrial structure and resource allocation. In this study, the proportion of the urban population to the total population and the gross domestic product were used to represent the levels of urbanization and economic development, respectively. The population, urbanization and economic levels of the Belt and Road countries for 2020–2050 were projected under the framework of the IPCC's shared socioeconomic pathways(SSPs), and the following conclusions are drawn.(1) The population, urbanization and economic levels in the Belt and Road region will likely increase under all five pathways. The population will increase by 2%–8%/10 a during 2020–2050 and reach 5.0–6.0 billion in 2050. Meanwhile, the urbanization rate will increase by 1.4%–7.5%/10 a and reach 49%–75%. The GDP will increase by 17%–34%/10 a and reach 134–243 trillion USD.(2) Large differences will appear under different scenarios. The SSP1 and SSP5 pathways demonstrate relatively high urbanization and economic levels, but the population size is comparatively smaller; SSP3 shows the opposite trend. Meanwhile, the economy develops slowly under SSP4, but it has a relatively high urbanization level, while SSP2 exhibits an intermediate trend.(3) In 2050, the population will increase relative to 2016 in most countries, and population size in the fastest growing country in Central Asia and the Middle East countries will be more than double. Urbanization will develop rapidly in South Asia, West Asia and Central Asia, and will increase by more than 150% in the fastest growing countries. The economy will grow fastest in South Asia, Southeast Asia and West Asia, and increase by more than 10 times in some counties with rapid economic development. 相似文献
Agriculture is responsible for approximately 25% of anthropogenic global GHG emissions. This significant share highlights the fundamental importance of the agricultural sector in the global GHG emissions reduction challenge. This article develops and tests a methodology for the integration of agricultural and energy systems modelling. The goal of the research is to extend an energy systems modelling approach to agriculture in order to provide richer insights into the dynamics and interactions between the two (e.g. in competition for land-use). We build Agri-TIMES, an agricultural systems module using the TIMES energy systems modelling framework, to model the effect of livestock emissions and explore emissions reduction options. The research focuses on Ireland, which is an interesting test case for two reasons: first, agriculture currently accounts for about 30% of Ireland's GHG emissions, significantly higher than other industrialized countries yet comparable with global levels (here including emissions associated with other land-use change and forestation); second, Ireland is both a complete and reasonably sized agricultural system to act as a test case for this new approach. This article describes the methodology used, the data requirements, and technical assumptions made to facilitate the modelling. It also presents results to illustrate the approach and provide associated initial insights.
Policy relevance
Most of the policy focus with regard to climate mitigation targets has been on reducing energy-related CO2 emissions, which is understandable as they represent by far the largest source of emissions. Non-energy-related GHG emissions – largely from agriculture, industrial processes, and waste – have received significantly less attention in policy discourse. Going forward, however, if significant cuts are made in energy-related CO2 emissions, the role of non-energy-related GHG emissions will grow in importance. It is therefore crucial that climate mitigation analyses and strategies are not limited to the energy system. This article shows the value of using integrated energy and agriculture techno-economic modelling techniques to draw evidence for new comprehensive climate policy strategies able to discern between the full range of technical solutions available. It enables the production of economy-wide least-cost climate mitigation pathways. 相似文献
Previous studies have examined the projected climate types in China by 2100. This study identified the emergence time of climate shifts at a 1?scale over China from 1990 to 2100 and investigated the temporal evolution of K o¨ppen–Geiger climate classifications computed from CMIP5 multi-model outputs. Climate shifts were detected in transition regions(7%–8% of China's land area) by 2010, including rapid replacement of mixed forest(Dwb) by deciduous forest(Dwa) over Northeast China, strong shrinkage of alpine climate type(ET) on the Tibetan Plateau, weak northward expansion of subtropical winterdry climate(Cwa) over Southeast China, and contraction of oceanic climate(Cwb) in Southwest China. Under all future RCP(Representative Concentration Pathway) scenarios, the reduction of Dwb in Northeast China and ET on the Tibetan Plateau was projected to accelerate substantially during 2010–30, and half of the total area occupied by ET in 1990 was projected to be redistributed by 2040. Under the most severe scenario(RCP8.5), sub-polar continental winter dry climate over Northeast China would disappear by 2040–50, ET on the Tibetan Plateau would disappear by 2070, and the climate types in 35.9%and 50.8% of China's land area would change by 2050 and 2100, respectively. The results presented in this paper indicate imperative impacts of anthropogenic climate change on China's ecoregions in future decades. 相似文献
Based on RegCM4, a climate model system, we simulated the distribution of the present climate (1961-1990) and the future climate (2010-2099), under emission scenarios of RCPs over the whole Pearl River Basin. From the climate parameters, a set of mean precipitation, wet day frequency, and mean wet day intensity and several precipitation percentiles are used to assess the expected changes in daily precipitation characteristics for the 21st century. Meanwhile the return values of precipitation intensity with an average return of 5, 10, 20, and 50 years are also used to assess the expected changes in precipitation extremes events in this study. The structure of the change across the precipitation distribution is very coherent between RCP4.5 and RCP8.5. The annual, spring and winter average precipitation decreases while the summer and autumn average precipitation increases. The basic diagnostics of precipitation show that the frequency of precipitation is projected to decrease but the intensity is projected to increase. The wet day percentiles (q90 and q95) also increase, indicating that precipitation extremes intensity will increase in the future. Meanwhile, the 5-year return value tends to increase by 30%-45% in the basins of Liujiang River, Red Water River, Guihe River and Pearl River Delta region, where the 5-year return value of future climate corresponds to the 8- to 10-year return value of the present climate, and the 50-year return value corresponds to the 100-year return value of the present climate over the Pearl River Delta region in the 2080s under RCP8.5, which indicates that the warming environment will give rise to changes in the intensity and frequency of extreme precipitation events. 相似文献
Because climate change challenges the sustainability of important fish populations and the fisheries they support, we need to understand how large scale climatic forcing affects the functioning of marine ecosystems. In the Humboldt Current system (HCS), a main driver of climatic variability is coastally-trapped Kelvin waves (KWs), themselves originating as oceanic equatorial KWs. Here we (i) describe the spatial reorganizations of living organisms in the Humboldt coastal system as affected by oceanic KWs forcing, (ii) quantify the strength of the interactions between the physical and biological component dynamics of the system, (iii) formulate hypotheses on the processes which drive the redistributions of the organisms, and (iv) build scenarios of space occupation in the HCS under varying KW forcing. To address these questions we explore, through bivariate lagged correlations and multivariate statistics, the relationships between time series of oceanic KW amplitude (TAO mooring data and model-resolved baroclinic modes) and coastal Peruvian oceanographic data (SST, coastal upwelled waters extent), anchoveta spatial distribution (mean distance to the coast, spatial concentration of the biomass, mean depth of the schools), and fishing fleet statistics (trip duration, searching duration, number of fishing sets and catch per trip, features of the foraging trajectory as observed by satellite vessel monitoring system). Data sets span all or part of January 1983 to September 2006. The results show that the effects of oceanic KW forcing are significant in all the components of the coastal ecosystem, from oceanography to the behaviour of the top predators – fishers. This result provides evidence for a bottom-up transfer of the behaviours and spatial stucturing through the ecosystem. We propose that contrasting scenarios develop during the passage of upwelling versus downwelling KWs. From a predictive point of view, we show that KW amplitudes observed in the mid-Pacific can be used to forecast which system state will dominate the HCS over the next 2–6 months. Such predictions should be integrated in the Peruvian adaptive fishery management. 相似文献