Spatial Distribution of China’s Industrial Output Values under Global Warming Scenarios RCP4.5 and RCP8.5

Qian Xue,Wei Song

doi:10.3390/ijgi9120724

Abstract

Climatic changes significantly impact the socio-economic system. Compared with research on the impacts of climate change on the agricultural economic system, researches on the impacts on the industrial economic system are still scarce. This is mainly because of the difficulties in matching climate data with socio-economic data in terms of spatiotemporal resolution, which has greatly limited the exposure degree assessment and the risk assessment of industrial economic systems. In view of this, based on remote sensing inversion and multi-source data fusion, we generated kilometer-grid data of China’s industrial output in 2010 and built the spatial distribution model of industrial output, based on random forest, to simulate the spatial distribution of China’s industrial output under different climate change scenarios. The results showed that (1) our built spatial distribution simulation model of China’s industrial output under different climate change scenarios had an accuracy of up to 93.77%; (2) from 2010 to 2050, the total growth of China’s industrial output under scenario RCP8.5 is estimated to be 4.797% higher than that under scenario RCP4.5; and (3) the increasing rate of the average annual growth rate of China’s industrial output slows down significantly under both scenarios from 2030 to 2050, and the average annual growth rate will decrease by 7.31 and 6.54%, respectively, under scenarios RCP8.5 and RCP4.5 compared with that from 2010 to 2020.

Highlights

Since the 1980s, global changes, marked by global warming, have gradually been attracting significant attention worldwide [1]
This study builds the spatial distribution models of the industrial output value under different climate change scenarios based on machine learning by combination with the random forest model (Formula 5)
26 sets of climate modes were extensively selected based on the current climate modes and climate scenarios in coupled model Intercomparison Project Phase 5 (CMIP5); subsequently, five optimal climate modes (i.e., CMCC-CM, MIROC5, MIROC-ESM, MRI-CGCM3, and MPI-ESM-LR) were selected according to the simulation capabilities and differences of all modes for different climate scenarios to predict air temperature and precipitation during 2000–2050 under different climate change scenarios in China

Summary

Introduction

Since the 1980s, global changes, marked by global warming, have gradually been attracting significant attention worldwide [1]. Since climatic changes have considerable impacts on natural ecosystems and economic systems [2], coping with the impacts of global warming has become an important issue for all countries striving for sustainable development [3] Against this background, measures to reduce greenhouse gas emissions are becoming increasingly important for the development of a sustainable industrial economy. Climatic changes can result in increased or decreased agricultural production, affecting the price of agricultural products and, the costs of the processing and manufacturing industries that use these agricultural products as main raw materials. From another angle, demand and supply changes may affect the industrial economy. Against the background of the predicted continuous climate warming in the future, industrial production will face several obstacles such as intensified resource exhaustion and frequent extreme climate events, resulting in a greater overall sensitivity to climate change

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