Integrate Risk From Climate Change in China Under Global Warming of 1.5 and 2.0 °C.

Abstract

Abstract. Risk of climate‐related impacts results from the interaction of climate‐related hazards (including hazardous events and trends) with the vulnerability and exposure of human and natural systems. Despite the commitment of the Paris Agreement, the integrate research on climate change risk combining risk‐causing factors and risk‐bearing bodies, the regional differences in climate impacts are still missing. In this paper we provide a quantitative assessment of hazards and socioeconomic risks of extreme events, risks of risk‐bearing bodies in China under global warming of 1.5 and 2.0 °C based on future climate scenarios, and quantitative evaluation theory for climate change risk. For severe heat waves, hazards might significantly intensify. Affected population under 2.0 °C warming might increase by more than 60% compared to that of 1.5 °C. Hazards of severe droughts and floods might strengthen under Representative Concentration Pathway 8.5 scenario. Economic losses might double between warming levels of 1.5 and 2.0 °C, and the population affected by severe floods might continuously increase. Under the integrate effects of multiple disasters, the regions with high population and economic risks would be concentrated in eastern China. The scope would gradually expand to the west with socioeconomic development and intensification of extreme events. High ecological risks might be concentrated in the southern regions of the Yangtze River Basin, while the ecological risk in northern China would expand. High agriculture yield risks might be distributed mainly in south of the North China Plain, the Sichuan Basin, south of the Yangtze River, and west of Northwest China, and the risk levels might continuously increase.

Policy assessments for the carbon emission flows and sustainability of Bitcoin blockchain operation in China

“…As one of the largest energy consuming countries on the planet, China is a key signatory of the Paris Agreement 18 – 20 . However, without appropriate interventions and feasible policies, the intensive Bitcoin blockchain operation in China can quickly grow as a threat that could potentially undermine the emission reduction effort taken place in the country 10 .

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“…In comparison to its counterparts, SD modeling has two main advantages in carbon emission flow assessment: first, by combining the feedback loops of stock and flow parameters, SD is able to capture and reproduce the endogenous dynamics of complex system elements, which enables the simulation and estimation of specific industry operations 6 – 8 . In addition, since the SD-based model is focused on disequilibrium dynamics of the complex system 9 , 10 , intended policies can be adjusted for scenario policy effectiveness evaluation. Consequently, based on system dynamics modeling, we develop the Bitcoin blockchain carbon emission model (BBCE) to assess the carbon emission flows of the Bitcoin network operation in China under different scenarios.…”

Impacts of 1.5 °C and 2 °C Global Warming on Net Primary Productivity and Carbon Balance in China’s Terrestrial Ecosystems

“…Most of the research focused on mean and extreme climate change [21,22] and the impacts of future 2 • C warming on the hydrological cycle and water resource in China [22][23][24]. A few recent studies in China suggested the high ecological risks in the Yangtze River Basin and northern China [25]. Some studies indicated that grassland productivity would increase under the 1.5 • C and 2 • C warming scenarios due to the increased precipitation and atmospheric CO 2 concentration [26].…”

Future Flood Risk Assessment under the Effects of Land Use and Climate Change in the Tiaoxi Basin

“…Under the eight climate models, the results show that the estimated runoff in the period 2020-2050 is consistently greater than the baseline period of 2000-2019, with an average increase of 10~25%. Wu shows that high risks might be concentrated in the southern regions of the Yangtze River Basin from a perspective across China [62]. As a downstream sub-watershed of the Yangtze basin, we took the Tiaoxi watershed as the study area and proved the same point from the perspective of a local basin.…”