Forecasting China's oil consumption: A comparison of novel nonlinear-dynamic grey model (GM), linear GM, nonlinear GM and metabolism GM

A precise multi-scenario prediction of future population, based on micro-scale census data and localized interpretation of global scenarios, is significant for understanding long-term demographic changes. However, the data used in previous research need to be further refined. Few studies have focused on predicting the sex ratio at birth, which is vitally important for estimating the future size and structure of the population. It is also important to interpret and set parameters for China’s future population development in line with the framework for global shared socioeconomic pathways. This paper, therefore, used the structural population data for provinces, prefectures, and counties from the Sixth National Population Census of China. It comprehensively considered the impact of China’s economic development level, specific population policies, and loss of an only child on key parameters, and localized the population change parameters for different scenarios. A population–development–environment model was used to explain the population change parameters. The population of 340 districts was refined, forecast, and aggregated to the national scale. The results show that the Chinese population is expected to first increase then decrease under the five paths from 2010 to 2050. The aging demographic structure is not reversed under any paths, and the increase or decrease in the urban and rural populations between adjacent node years is closely related to the fertility rate and urbanization speed. We suggest that measures should be taken to encourage childbearing, manage the aging population problem, and reduce the pressure on young and middle-aged people.

Predicting the Future Chinese Population using Shared Socioeconomic Pathways, the Sixth National Population Census, and a PDE Model

With the development of industrialization, fine particulate matter (PM25) severely chills the health of people Studies have shown that the variation of PM25 concentration is related to the Global Navigation Satellite System (GNSS) tropospheric delay Therefore, it is possible to use the widely distributed continuous operation reference station (CORS) to monitor and predict PM25 concentrations with high time resolution In this paper, the zenith wet delay (ZWD) of five CORS located in Baoding, Hebei Province, China, from Sep 2014 to Feb 2015, is calculated firstly Then, the correlation between PM25 and ZWD is investigated Finally, the experimental data including PM25, ZWD, temperature, air pressure, and relative humidity data sampled in one hour are used to establish PM25 concentrations online prediction model based on support vector machine regression (SVMR) model with metabolic method The experimental results show that in autumn and winter, the correlation coefficient between daily-mean PM25 and ZWD is mainly larger than 04, and the correlation coefficient between hourly mean PM25 and ZWD is mainly larger than 03 Meanwhile, in daily cycle analysis, air temperature, air pressure and relative humidity are related to PM25 concentration Finally, Using SVMR model with metabolic method, by combining GNSS and meteorological factors, ideal short-term prediction accuracy is achieved, which shows that the use of GNSS and meteorological factors is potential in predicting PM25 concentration

/pdf/short-term-pm2-5-concentration-prediction-by-combining-gnss-1km1rjwbqi.pdf

Short-Term PM2.5 Concentration Prediction by Combining GNSS and Meteorological Factors

How does the photovoltaic industry contribute to China's carbon neutrality goal? Analysis of a system dynamics simulation

China has implemented the world's largest-ever vegetation restoration program in marginal mountainous areas to sustain life on land. However, land competition between the demand for grain and the need for green has threatened sustainable vegetation restoration. Here, focusing on China's marginal mountainous areas with the highest density of slope cropland, we explore the optimal solution in the trade-offs between green and grain. We find that current vegetation restoration strategies are not sufficiently optimized, which may threaten the survival and development of local farmers and in turn destroy existing vegetation restoration achievements. Through adjusting vegetation restoration objectives carefully tailored to local conditions, the population experiencing grain shortages can be greatly reduced by 51–66% (from 18.26 million to 6.29–8.90 million) compared with the current scheme. The optimal design will alleviate the conflict between grain and green, thereby promoting sustainable ecological restoration in China. Our research provides an important reference for the world's mountainous areas to achieve a win-win situation between green and grain. 

How to Balance Green and Grain in Marginal Mountainous Areas?

Purpose – The purpose of this paper is to apply grey system theory to population system and project China's population.Design/methodology/approach – The paper applies the GM(1,1) model to China's population projections. Two key aspects of the method are crucial for obtaining best accuracy of prediction. They are the choice of the length for the original data to be used in the model and the adoption of the GM(1,1) metabolic model in prediction. The former determines what initial data to be used while the latter describes an iteration process on how to proceed to predict.Findings – The results show that in 2015 China's population will reach 1.37 billion and in 2050 it will be between 1.42 and 1.48 billion, which is in accordance with the latest projections from the UN. The findings show the GM(1,1) metabolic model is an effective mathematical means in population projections.Research limitations/implications – The paper suggests that GM(1,1) metabolic model can provide an effective simulation model for compl...

China's population projections based on GM(1,1) metabolic model

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China's population projections based on GM(1,1) metabolic model