Survey of China's Urban Consumption

FromDecember1998toJune1999,theChinaMarketSupervisionundertheStateStatisticsBureauconductedsurveysontheconsumptiontrendsandlivesofChina'surbanresidentsamong5,000consumersin20cities,includingBeijing,Shanghai,Chengdu,Guangzhou,Wuhan,Naming,Qingdao,Dalia...

CO_2 Emission Induced by Urban Household Consumption in China

Household consumption is one of the important factors that induce COL emission. Based on input-output model, this article calculated the intensity of CO2 emission of different income groups and seven provinces in China, and then estimated total CO2 emission induced by urban household consumption from 1995 to 2004 in China based on statistic data of household living expenditure. The results show that CO2 emission per capita induced by household consumption had increased from 1583 to 2498 kg CO2 during 1995-2004. The ratio of consumption-induced CO2 emission to total CO2 emission had risen from 19% to 30% in the past decade. Indirect CO2 emission accounted for an important part of the consumption-induced emission, the ratio of indirect emission to consumption-induced emission had risen from 69% to 79% during the same period. A significant difference in consumption-induced CO2 emission across different income groups and different regions has been observed. COs emission per capita of higher income groups and developed regions increased faster than that of lower income groups and developing regions. Changing lifestyle has driven significant increase in CO2 emission. Especially, increases in private transport expenditure （for example, vehicle expenditure） and house building expenditure are key driving factors of growth in consumption-induced COL emission. There are big differences in the amount of CO2 emission induced by change in lifestyle across different income groups and provinces. It can be expected that lower income households and developing regions will increase consumption to improve their livings with income growth in the future, which may induce much more CO2 emission. A reasonable level of CO2 emission is necessary to satisfy human needs and to improve living standard, but a noticeable fact is that CO2 emission per capita induced by household consumption in developed areas of China had reached a quite high level. Adjustment in lifestyle towards a low-carbon society is in urgent need.

Multi-variable grey model (MGM(1,n,q)) based on genetic algorithm and its application in urban water consumption

Urban water consumption has some characteristics of grey because it is influenced by economy, population, standard of living and so on. The multi-variable grey model (MGM(1,n)), as the expansion and complement of GM(1,1) model, reveals the relationship between restriction and stimulation among variables, and the genetic algorithm has the whole optimal and parallel characteristics. In this paper, the parameter q of MGM(1,n) model was optimized, and a multi-variable grey model (MGM(1,n,q)) was built by using the genetic algorithm. The model was validated by examining the urban water consumption from 1990 to 2003 in Dalian City. The result indicated that the multi-variable grey model (MGM(1,n,q)) based on genetic algorithm was better than MGM(1,n) model, and the MGM(1,n) model was better than MGM(1,1) model.

Urban Fresh Water Resources Consumption of China

From the point of view of urban consumption behavior, urban fresh water consumption could be classified as three types, namely, direct, indirect and induced water consumption. A calculation approach of urban flesh water consumption was presented based on the theory of urban basic material consumption and the input-output method, which was utilized to calculate urban fresh water consumption of China, and to analyze its structural change and causes. The results show that the total urban flesh water consumption increased 561.7× 10^9m^3, and the proportion to the total national flesh water resources increased by 20 percentage points from 1952 to 2005. The proportion of direct and induced water consumption had been continuously rising, and it increased by 15 and 35 percentage points separately from 1952 to 2005, while the proportion of indirect water consumption decreased by 50 percentage points. Urban indi- rect water consumption was mainly related to urban grain, beef and mutton consumption, and urban induced water consumption had a close relationship with the amount of carbon emission per capita. Finally, some countermeasures were put forward to realize sustainable utilization of urban fresh water resources in China.

Calculation and decomposition of regional household energy consumption in China:based on perspectives of urbanization and residents' consumption

Demographic urbanization caused great changes in scale of residents' consumption and residents' lifestyle and then impacted changes of regional household energy consumption. This paper expanded Logarithmic Mean Decomposition Index method through introducing variables of urbanization and residential consumption into the model. It also analyzed the influences of six factors as energy structure, energy intensity, population scale, urbanization, residential consumption, and consumption inhibit on regional household energy consumption. Results showed that in 2003-2012, impact of urbanization on regional household energy consumption of Chinese three areas was significantly higher than population size. The "population gathered in eastern region" phenomenon caused eastern region getting the largest population scale effect. Driving force of residential consumption on regional household energy consumption was much higher than the other five effects. Due to the comparative advantage of residential consumption compared with government consumption, investment, and net export, the decrease of consumption ratio promoted the growth of regional household energy consumption. Energy intensity in Chinese three regions kept reducing in 2003-2012. The progress of energy utilization technology slowed the growth of regional household energy consumption, and energy intensity effect was most significant in the central region.

Quantitative study on the urban fresh water consumption since Chinese rapid urbanization

The development of urbanization has a close relationship with fresh water resources, especially in the rapid urbanization period. By analyzing the course of the urhanization development and the experience of international urbanization development, the paper confirms the starting time of the rapid urbanization. Based on the ecotogical theory; urban fresh water consumption is composed of three types： the direct, the indirect and the induced water consumption. And the paper constructs calculation model of the indirect and the induced water consumption. Using the related statistics data, the paper makes an empirical research on the changes of the amount and structure of water consumption. Then it discusses the correlation between the water consumption and the amount of urban population, and the result shows that the amount of the water consumption arid the urban population have a remarkable correlation with the exception of the amount of the indirect water consumption, and the curves fake on quadratic functian form. Last, from the urban fimction point of view; the paper anatomizes the cause of the urban water consumption changes.

Short-Term Forecasting of Urban Water Consumption Based on the Largest Lyapunov Exponent

An approach for short-term forecasting of municipal water consumption was presented based on the largest Lyapunov exponent of chaos theory. The chaotic characteristics of time series of urban water consumption were examined by means of the largest Lyapunov exponent and correlation dimension. By using the largest Lyapunov exponent a short-term forecasting model for urban water consumption was developed, which was compared with the artificial neural network (ANN) approach in a case study. The result indicates that the model based on the largest Lyapunov exponent has higher prediction precision and forecasting stability than the ANN method, and its forecasting mean relative error is 9.6% within its maximum predictable time scale while it is 60.6% beyond the scale.

Trade-offs between prosperity and urban land per capita in major world cities

Globally,urban land expands at a faster rate than the corresponding urban population,which comes at a cost of agricultural and natural land.Wealth has been identified as an underlying driver of this trend,but it is unclear whether more prosperous cities inevitably have a greater urban land consumption.Here,we map urban pros-perity indicators to their relevant Sustainable Development Goals(SDGs)for 64 major world cities and relate these to the corresponding urban land consumption(defined here as built-up land per capita).Results indicate a moderately-weak but significant correlation between overall prosperity and urban land consumption(Spear-man’s correlation,𝜌ρ=0.47,p<0.001),suggesting a trade-offbetween both.In addition,we find a regional clustering,with for example cities with relatively low prosperity and low urban land consumption in Africa,and cities with high prosperity and low-to-medium urban land consumption in Europe.The moderately-weak correlation in combination with these regional differences suggests that the observed trade-offis avertable and that other drivers moderate this relation.Consequently,cities can increase their prosperity without additional environmental consequences entailing land take and the conversion of natural and agricultural land.

Electricity consumption patterns within cities:application of a data-driven settlement characterization method

Urban areas presently consume around 75%of global primary energy supply,which is expected to significantly increase in the future due to urban growth.Having sustainable,universal energy access is a pressing challenge for most parts of the globe.Understanding urban energy consumption patterns may help to address the challenges to urban sustainability and energy security.However,urban energy analyses are severely limited by the lack of urban energy data.Such datasets are virtually non-existent for the developing countries.As per current projections,most of the new urban growth is bound to occur in these data-starved regions.Hence,there is an urgent need of research methods for monitoring and quantifying urban energy utilization patterns.Here,we apply a data-driven approach to characterize urban settlements based on their formality,which is then used to assess intraurban urban energy consumption in Johannesburg,South Africa;Sana’a,Yemen;and Ndola,Zambia.Electricity is the fastest growing energy fuel.By analyzing the relationship between the settlement types and the corresponding nighttime light emission,a proxy of electricity consumption,we assess the differential electricity consumption patterns.Our study presents a simple and scalable solution to fill the present data void to understand intra-city electricity consumption patterns.

Optimal City Size in China:An Extended Empirical Study from the Perspective of Energy Consumption

The optimal city size has always been a heated topic for debate in China. Given the background of global warming and fossil fuel crisis, it is argued that the issue should be considered from not only the perspective of economic benefits of a city but should also consider the energy consumption efficiency of the city. On the basis of the energy consumption data of 286 cities at the prefectural level and above in Chinese mainland except Lasa, which are obtained from the EU Emission Database for Global Atmospheric Research(EDGAR), this paper carries out an empirical analysis on the relationship between the city size and the energy consumption efficiency of the city. Then based on this analysis, the paper further examines the economic benefits, social benefits, and environment quality of cities in different scales, and the findings reveal that large cities with 2 – 5 million population have the highest efficiency in all these aspects.