Population,urbanization and economic scenarios over the Belt and Road region under the Shared Socioeconomic Pathways

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%/10a during 2020-2050 and reach 5.0-6.0 billion in 2050.Meanwhile,the urbanization rate will increase by 1.4%-7.5%/10a and reach 49%-75%.The GDP will increase by 17%-34%/10a 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.

Impacts and risks of“realistic”global warming projections for the 21st century

The IPCC AR6 assessment of the impacts and risks associated with projected climate changes for the 21st century is both alarming and ambiguous.According to computer projections,global surface temperature may warm from 1.3℃to 8.0℃by 2100,depending on the global climate model(GCM)and the shared socioeconomic pathway(SSP)scenario used for the simulations.Actual climate-change hazards are estimated to be high and very high if the global surface temperature rises,respectively,more than 2.0℃and 3.0℃above pre-industrial levels.Recent studies,however,showed that a substantial number of CMIP6 GCMs run“too hot”because they appear to be too sensitive to radiative forcing,and that the high/extreme emission scenarios SSP3-7.0 and SSP5-8.5 are to be rejected because judged to be unlikely and highly unlikely,respectively.Yet,the IPCC AR6 mostly focused on such alarmistic scenarios for risk assessments.This paper examines the impacts and risks of“realistic”climate change projections for the 21st century generated by assessing the theoretical models and integrating them with the existing empirical knowledge on global warming and the various natural cycles of climate change that have been recorded by a variety of scientists and historians.This is achieved by combining the SSP2-4.5 scenario(which is the most likely SSP according to the current policies reported by the International Energy Agency)and empirically optimized climate modeling.According to recent research,the GCM macro-ensemble that best hindcast the global surface warming observed from 1980 to 1990 to 2012–2022 should be made up of models that are characterized by a low equilibrium climate sensitivity(ECS)(1.5℃<ECS≤3.0℃),in contrast to the IPCC AR6 likely and very likely ECS ranges at 2.5–4.0℃and 2.0–5.0℃,respectively.I show that the low-ECS macro-GCM with the SSP2-4.5 scenario projects a global surface temperature warming of 1.68–3.09℃by 2080–2100 instead of 1.98–3.82℃obtained with the GCMs with ECS in the 2.5–4.0℃range.However,if the global surface temperature records are affected by significant non-climatic warm biases—as suggested by satellite-based lower troposphere temperature records and current studies on urban heat island effects—the same climate simulations should be scaled down by about 30%,resulting in a warming of about 1.18–2.16℃by 2080–2100.Furthermore,similar moderate warming estimates(1.15–2.52℃)are also projected by alternative empirically derived models that aim to recreate the decadal-to-millennial natural climatic oscillations,which the GCMs do not reproduce.The proposed methodologies aim to simulate hypothetical models supposed to optimally hindcast the actual available data.The obtained climate projections show that the expected global surface warming for the 21st-century will likely be mild,that is,no more than 2.5–3.0℃and,on average,likely below the 2.0℃threshold.This should allow for the mitigation and management of the most dangerous climate-change related hazards through appropriate low-cost adaptation policies.In conclusion,enforcing expensive decarbonization and net-zero emission scenarios,such as SSP1-2.6,is not required because the Paris Agreement temperature target of keeping global warming<2℃throughout the 21st century should be compatible also with moderate and pragmatic shared socioeconomic pathways such as the SSP2-4.5.

Simulation of China’s potential rice yields by coupling land system evolution and climate change

Land systems and climate,which are the key elements of agricultural production and key drivers of crop yields,affect the quality of arable land.However,a quantitative model to reveal the mechanism of how potential grain yields are affected by macro-scale arable land evolution and climate change has not yet been developed.In this study,we constructed a Grey Prediction Model-Future Land Use Simulation(GM-FLUS),which combined land system evolution with climate change data,to simulate changes in China’s land system over the next 40 years.We improved the Global Agro-Ecological Zone(GAEZ)model,estimated China’s potential rice yields and their spatial distribution in the next 40 years under four scenarios(shared socioeconomic pathway SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5)of the Sixth International Coupling Model Intercomparison Project,analysed the spatiotemporal variations in the potential rice yields and their drivers,and provided appropriate suggestions for increasing rice yields.The simulation results indicated an increase in China’s potential rice yields during 2020–2060 under the SSP1-2.6 and SSP3-7.0 scenarios and a decrease under the SSP2-4.5 and SSP5-8.5 scenarios.Moreover,China’s development strategy of“achieving carbon peaking by 2030 and carbon neutrality by 2060”was similar to the SSP1-2.6 scenario,under which rice yields were relatively stable.Furthermore,under China’s arable land protection policy,China’s paddy field area will change slightly during 2020–2060,and potential rice yields will be influenced by climate.Under the four climate change scenarios,air temperature increased and was negatively correlated with potential rice yields in main rice-producing regions.Additionally,potential rice yields were positively correlated with precipitation,which increased stably under the SSP1-2.6 and SSP3-7.0scenarios and decreased under the SSP2-4.5 and SSP5-8.5 scenarios.These results suggest that the development of heat-resistant rice varieties and the implementation of measures that will mitigate the impacts of future temperature increases on rice yields are important for the conservation of paddy fields.Additionally,improving irrigation and drainage facilities is necessary to irrigate drought-prone paddy fields and drain flooded water.

Projecting the proliferation risk of Oncomelania hupensis in China driven by SSPs:A multi-scenario comparison and integrated modeling study

Climate change has been known to cause variations in the geographically suitable areas for the schistosome-transmitting Oncomelania hupensis(O.hupensis).The spread of snails not only depends on the degree of warming but also on the socioeconomic development of the next few decades.Shared socioeconomic pathways(SSPs)published by CMIP6 consider carbon emission pathways as well as influences of distinct types of social development and land use on the regional climate,providing the possibility to accurately evaluate the impact of socioeconomic development and climate variation on the spread of O.hupensis.This study employed SSP126,SSP245,SSP370,and SSP585 and the correlative approach to explore the impacts of climate change and socioeconomic development on the potential diffusion areas for O.hupensis in China.The results exhibited strong evidence that O.hupensis will spread in the north of the middle and lower reaches of the Yangtze River and disappear from a small part of its current southern habitat,whereas in Sichuan and Yunnan,O.hupensis may spread slightly to the southeast.The projection also demonstrated that fossil fuel-driven development(SSP585)will be more conducive to the spread of O.hupensis breeding sites in the 2030s,whereas the continuous increase in snail breeding habitats under the regional rivalry path(SSP370)may lead to great challenges in snail control in the long term(2020-2080).

A multi-model assessment of climate change damage in China and the world

Quantifying climate damage is essential to informing rational climate policies,but only a few studies have systematically compared the climate damage estimates made by different models,especially for China.In this study,we used three widely applied integrated assessment models-FUND,RICE,and PAGE-to estimate the damage under coupled shared socioeconomic pathways and representative concentration pathways(RCPs).Results show that the costs of climate damage constitute approximately 1.5%and 0.7%of China's GDP and global GDP per 1℃ temperature rise on average,respectively.Mitigation can reduce climate risk by lowering the average estimate and worst-case effects of climate damage.Compared with business-as-usual emissions(RCP8.5),the 2℃ target will reduce the average estimate of climate damage for China and the world by 93%and 87%,respectively,and by 80%and 84%,respectively,in the worst-case situation.Sectorial analysis of climate damage highlights the inconsistency of sector scope and significant parameter uncertainties in damage modules,requiring further improvement to integrate subfield research advances,particularly for damage related to rising sea levels and cooling energy demand.