Relaxing Hukou - Increased Labor Mobility and China’s Economic Geography

China’s Hukou system poses severe restrictions on labor mobility. This paper assesses the consequences of relaxing these restrictions for China’s internal economic geography. We base our analysis on a new economic geography model. First, we obtain estimates of the important model parameters on the basis of information on 264 of China’s prefecture cities over the period 1999-2005. Second, and by using our estimation results as input, we simulate various long-run scenarios of China’s internal economic geography that differ in their degree of interregional labor mobility. We find that increased labor mobility will lead to more pronounced core-periphery outcomes. Interestingly, these agglomerations are not necessarily along the coastal regions. Given the increased importance of China’s internal market, firms agglomerate in the populous heartland of China. China’s internal demand will be the most important determinant of its future economic geography.Empirical and Theoretical Methods

People, place, enterprise: proceedings of the first annual conference on Olympic Legacy 8 and 9 May 2008

The Olympic Legacy: People, Place, Enterprise conference took place at the University of Greenwich in May 2008. The first in a series of annual conferences, it brought together leading academics, policy makers and practitioners to debate the lasting legacy of the games. The conference had four themes: social and cultural regeneration; Olympic tourism; enterprise, including social enterprise and skills development, and education, providing a multi-dimensional perspective on the likely impacts of the forthcoming London Olympics

A baseline appraisal of water-dependant ecosystem services, the roles they play within desakota livelihood systems and their potential sensitivity to climate change

This report forms part of a larger research programme on 'Reinterpreting the Urban-Rural Continuum', which conceptualises and investigates current knowledge and research gaps concerning 'the role that ecosystems services play in the livelihoods of the poor in regions undergoing rapid change'. The report aims to conduct a baseline appraisal of water-dependant ecosystem services, the roles they play within desakota livelihood systems and their potential sensitivity to climate change. The appraisal is conducted at three spatial scales: global, regional (four consortia areas), and meso scale (case studies within the four regions). At all three scales of analysis water resources form the interweaving theme because water provides a vital provisioning service for people, supports all other ecosystem processes and because water resources are forecast to be severely affected under climate change scenarios. This report, combined with an Endnote library of over 1100 scientific papers, provides an annotated bibliography of water-dependant ecosystem services, the roles they play within desakota livelihood systems and their potential sensitivity to climate change. After an introductory, section, Section 2 of the report defines water-related ecosystem services and how these are affected by human activities. Current knowledge and research gaps are then explored in relation to global scale climate and related hydrological changes (e.g. floods, droughts, flow regimes) (section 3). The report then discusses the impacts of climate changes on the ESPA regions, emphasising potential responses of biomes to the combined effects of climate change and human activities (particularly land use and management), and how these effects coupled with water store and flow regime manipulation by humans may affect the functioning of catchments and their ecosystem services (section 4). Finally, at the meso-scale, case studies are presented from within the ESPA regions to illustrate the close coupling of human activities and catchment performance in the context of environmental change (section 5). At the end of each section, research needs are identified and justified. These research needs are then amalgamated in section 6

Spatial and Temporal Analysis of Big Dataset on PM2.5 Air Pollution in Beijing, China, 2014 to 2018

Air particulate matter (PM2.5) pollution is a critical environment problem worldwide and also in Beijing, China. We gathered five-year PM2.5 contaminate concentrations from 2014 to 2018, from the Beijing Municipal Environmental Monitoring Center and China Air Quality Real-time Distribution Platform. This is a big dataset, and we collected with crawler technology from Python programming. After examining the quality of the recorded data, we determined to conduct the temporal and spatial analysis using 27 observation stations located in both urban and suburb area in the municipality of Beijing. The big dataset of five-year hourly PM2.5 concentrations was sorted to actionable datasets (Selected Datasets and Seasonal Average Selected Datasets) with the help of Python programming. Linear Regression based Fundamental Data Analysis was conducted as the first part of temporal analysis in R studio to gather the temporal patterns of five-year seasonal PM2.5 contaminant concentrations on each observation sites. As the second part of temporal analysis, the Principal Component Analysis (PCA) was conducted in MATLAB to gather the patterns of variations of entire five-year PM2.5 contaminant concentration on each of the sites. Geographic Information System (GIS) was utilized to study the spatial pattern of air pollution distribution from the selected 27 observation sites during selected time periods. The results of this research are, 1) PM2.5 pollutions in winter are the most severe or the highest in each of the natural years. 2) PM2.5 pollution concentrations in Beijing were gradually decrease during 2014 to 2018. 3) In terms of a five-year time perspective, the improvements of air quality and reduction of PM2.5 contaminant appeared in all the seasons based on Fundamental Data Analysis. 4) PM2.5 contaminant concentrations in summer are significantly less than other seasons. 5) The least PM2.5 pollutant influenced area is north and northwest regions in Beijing, and the most PM2.5 pollutant influenced area is south and southeast areas in Beijing. 6) Vehicle concentration and traffic congestion is not the significant impact factor of PM2.5 pollutions in Beijing. 7) Heating supply of buildings and houses generated great contributions to the PM2.5 contaminant concentration in Beijing. While, in the background of rigorous emission reduction policy and management operations by the municipal government, contribution of heating supplies is gradually decreasing. 8) Human activities have limited contributions to the PM2.5 contaminants in Beijing. Meanwhile, type and quantity of fossil fuel energy consumptions might contribute large amount of air pollutions

Chemical transport model ozone simulations for spring 2001 over the western Pacific: Regional ozone production and its global impacts

The spatial and temporal variation in ozone production over major source regions in East Asia during the NASA Transport and Chemical Evolution over the Pacific (TRACE-P) measurement campaign in spring 2001 is assessed using a global chemical transport model. There is a strong latitudinal gradient in ozone production in springtime, driven by regional photochemistry, which rapidly diminishes as the season progresses. The great variability in meteorological conditions characteristic of East Asia in springtime leads to large daily variability in regional ozone formation, but we find that it has relatively little impact on the total global production. We note that transport processes effectively modulate and thus stabilize total ozone production through their influence over its location. However, the impact on the global ozone burden, important for assessing the effects of precursor emissions on tropospheric oxidizing capacity and climate, is sensitive to local meteorology through the effects of location on chemical lifetime. Stagnant, anticyclonic conditions conducive to substantial boundary layer ozone production typically allow little lifting of precursors into the free troposphere where greater ozone production could occur, and the consequent shorter chemical lifetime for ozone leads to relatively small impacts on global ozone. Conversely, cyclonic conditions with heavy cloud cover suppressing regional ozone production are often associated with substantial cloud convection, enhancing subsequent production in the free troposphere where chemical lifetimes are longer, and the impacts on global ozone are correspondingly greater. We find that ozone formation in the boundary layer and free troposphere outside the region of precursor emissions dominates total gross production from these sources in springtime, and that it makes a big contribution to the long range transport of ozone, which is greatest in this season

Forecasting China's regional energy demand by 2030: A Bayesian approach

China has been the largest energy consumer in the world, and its future energy demand is of concern to policy makers. With the data from 30 provinces during 1995–2012, this study employs a hierarchical Bayesian approach to present the probabilistic forecasts of energy demand at the provincial and national levels. The results show that the hierarchical Bayesian approach is effective for energy forecasting by taking model uncertainty, regional heterogeneity, and cross-sectional dependence into account. The eastern and central areas would peak their energy demand in all the scenarios, while the western area would continue to increase its demand in the high growth scenario. For the country as a whole, the maximum energy demand could appear before 2030, reaching 4.97/5.25 billion tons of standard coal equivalent in the low/high growth scenario. However, rapid economic development would keep national energy demand growing. The proposed Bayesian model also serves as an input for the development of effective energy policies. The analysis suggests that most western provinces still have great potential for energy intensity reduction. The energy-intensive industries should be cut down to improve energy efficiency, and the development of renewable energy is essential

A systematic review of empirical methods for modelling sectoral carbon emissions in China

© 2019 Elsevier Ltd A number of empirical methods have been developed to study China's sectoral carbon emissions (CSCE). Measuring these emissions is important for climate change mitigation. While several articles have reviewed specific methods, few attempts conduct a systematic analysis of all the major research methods. In total 807 papers were published on CSCE research between 1997 and 2017. The primary source of literature for this analysis was taken from the Web of Science database. Based on a bibliometric analysis using knowledge mapping with the software CiteSpace, the review identified five common families of methods: 1) environmentally-extended input-output analysis (EE-IOA), 2) index decomposition analysis (IDA), 3) econometrics, 4) carbon emission control efficiency evaluation and 5) simulation. The research revealed the main trends in each family of methods and has visualized this research into ten research clusters. In addition, the paper provides a direct comparison of all methods. The research results can help scholars quickly identify and compare different methods for addressing specific research questions