Increase Of Urbanization Rate Research Articles

Impact of Urbanization on Carbon Dioxide Emissions—Evidence from 136 Countries and Regions

Urbanization affects economic production activities and energy demand, as well as lifestyle and consumption behavior, affecting carbon dioxide emissions. This study constructs the System Generalized Method of Moments (Sys-GMM) model of the impact of urbanization rate on carbon dioxide emissions based on panel data of 136 countries and regions in the world from 1990 to 2020, grounded on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. This study found that (1) there is a negative relationship between urbanization rate and CO2 emissions from 1990 to 2020. (2) The impact of the urbanization rate on CO2 emissions is heterogeneous. An increase in urbanization rate in non-OECD countries significantly reduces CO2 emissions, while the effect is not significant in OECD countries. (3) The carbon intensity of fossil energy consumption moderates the relationship between urbanization rate and CO2 emissions, weakening the effect of urbanization rate on CO2 emissions. Based on these findings, policy recommendations such as promoting urbanization and increasing the regulation and control of fossil energy carbon intensity are proposed.

The Transformation of Rural Areas Located in China’s Agricultural Heritage Systems under the Evolution of Urban–Rural Relationships

The sustainable logic between the Agricultural Heritage System (AHS) and environmental synergy has been significantly changing with China’s urban–rural relationship shift from binary opposition to a stronger network exchange. During the process of transformation, China’s AHS rural areas encounter two major development trends and social realities, i.e., whether to continue conventional characteristic agricultural development or detach from conventional characteristic agricultural resources to achieve industrial transformation. Our aim is to analyze the structure, identity and functional transformation characteristics of AHS rural areas from the urban and rural scale, as well as to build an explanatory framework for transformation mechanisms. A total of 109 counties and five cases of important AHS areas in China are taken as research objects, combining quantitative and qualitative analyses to analyze the transformation of AHS rural areas from two aspects. On the one hand, for changes in single development elements, there are three development elements and corresponding transformation dimensions: (1) Land structure: there is a synergistic change between the increase in urbanization rate and the loss of rural land, with associated changes in space and production structure. (2) Population identity: the rural population loss in high-urbanization-level areas is severe, where farmers are combined or separated from traditional agriculture. (3) Industry function: the trend of non-agricultural development of the industrial economy is obvious, and the traditional functions of agriculture are facing a continuation or a deep transformation. On the other hand, for relations among development elements, combined with a regression analysis and field investigation, we try to explain how the development elements and characteristic elements influence each other while working together on the transformation of AHS rural areas. The transformation depends on the path of the original industrial structure, while the urban–rural income ratio, regional distribution and land urbanization rate all positively stimulate the transformation from agricultural industries to non-agricultural ones. Moreover, the transformation of AHS rural areas is also affected by the characteristic elements of their special agricultural heritage, specifically, whether the heritage is scalable, scarce or socialized, etc., and these special attributes can determine the different development forms of heritage elements in the modern agricultural industrial system.

Data-driven tracking control design with reinforcement learning involving a wastewater treatment application

With the increase of urbanization rate, the problem of water shortage and pollution is more and more serious. It is important to improve the efficiency of wastewater treatment to protect the urban ecological environment. The wastewater treatment process involves a variety of biochemical reactions and has strong time-vary dynamics. The concentration design in the wastewater treatment process can be regarded as a tracking control problem for a class of nonlinear systems. In order to solve this problem, this paper develops an intelligent control method with tracking goal representation heuristic dynamic programming (T-GrHDP) by combining the GrHDP with a novel tracking framework. A model network is built by using a dataset consisting of real input and output data of the controlled object, which can overcome the dependence on the system dynamic. In order to improve the learning efficiency of the proposed algorithm, we introduce the goal network to provide more effective information for the critic network. The classical actor-critic scheme in reinforcement learning is used to obtain the approximate optimal control strategy. By introducing some necessary lemmas and assumptions, the convergence of the proposed algorithm is proved. Finally, the T-GrHDP method is successfully applied in two industrial simulations including the wastewater treatment system.

Urbanization, Industrial Structure Upgrading, and Lottery Consumption based on the Sustainable Development of the Emerging Markets: Evidence from China

Steady progress in urbanization and continuous industrial structure upgrading are important pillars for emerging economies to achieve sustainable development. As an important means of enhancing national economic development, the lottery industry has always been highly valued by all countries. For China, how to promote the sustainability of the lottery industry so as to improve residents’ subjective wellbeing and life satisfaction is particularly critical. The purpose of this study is to explore the impact of urbanization and industrial structure upgrade on lottery consumption. Based on provincial panel data running from 2008 to 2019 in China, it uses two-way fixed effects to make empirical analysis. The results show that the increase in urbanization rate and tertiary industry share has significantly positive effects on lottery consumption; the impact of urbanization and the proportion of the tertiary industry on lottery consumption would vary in categories of lottery tickets; the urbanization and tertiary industry share have a greater role in promoting lottery sales in the eastern region, followed by the central region, and finally the western region. Accordingly, this article proposes policy recommendations to promote the coordinated development of the lottery industry and other related industries in China.

A Spatio-temporal Bayesian model to estimate risk and influencing factors related to tuberculosis in Chongqing, China, 2014–2020

BackgroundTuberculosis (TB) is a serious infectious disease that is one of the leading causes of death worldwide. This study aimed to investigate the spatial and temporal distribution patterns and potential influencing factors of TB incidence risk, and to provide a scientific basis for the prevention and control of TB.MethodsWe collected reported cases of TB in 38 districts and counties in Chongqing from 2014 to 2020 and data on environment, population characteristics and economic factors during the same period. By constructing a Bayesian spatio-temporal model, we explored the spatio-temporal distribution pattern of TB incidence risk and potential influencing factors, identified key areas and key populations affected by TB, compared the spatio-temporal distribution characteristics of TB in populations with different characteristics, and explored the differences in the influence of various social and environmental factors.ResultsThe high-risk areas for TB incidence in Chongqing from 2014 to 2020 were mainly concentrated in southeastern and northeastern regions of Chongqing, and the overall relative risk (RR) of TB showed a decreasing trend during the study period, while RR of TB in main urban area and southeast of Chongqing showed an increasing trend. The RR of TB was relatively high in the main urban area for the female population and the population aged 0–29 years, and the RR of TB for the population aged 30–44 years in the main urban area and the population aged 60 years or older in southeast of Chongqing had an increasing trend, respectively. For each 1 μg/m3 increase in SO2 and 1% increase in the number of low-income per 1000 non-agricultural households (LINA per 1000 persons), the RR of TB increased by 0.35% (95% CI: 0.08–0.61%) and 0.07% (95% CI: 0.05–0.10%), respectively. And LINA per 1000 persons had the greatest impact on the female population and the over 60 years old age group. Although each 1% increase in urbanization rate (UR) was associated with 0.15% (95% CI: 0.11–0.17%) reduction in the RR of TB in the whole population, the RR increased by 0.18% (95% CI: 0.16–0.21%) in the female population and 0.37% (95% CI: 0.34–0.45%) in the 0–29 age group.ConclusionThis study showed that high-risk areas for TB were concentrated in the southeastern and northeastern regions of Chongqing, and that the elderly population was a key population for TB incidence. There were spatial and temporal differences in the incidence of TB in populations with different characteristics, and various socio-environmental factors had different effects on different populations. Local governments should focus on areas and populations at high risk of TB and develop targeted prevention interventions based on the characteristics of different populations.

Study on Contribution of Carbon Emission Intensity Based on Oaxaca-blinder Decomposition Method by Big Data Evaluation in Different Economic Level Cities of Shandong Province

We studied the difference in carbon emission intensity by the Oaxaca blinder decomposition method with the panel data of 17 prefecture level cities in Shandong Province from 2007 to 2016. Per capita GDP, industrial structure, urbanization level, and energy consumption intensity are important factors affecting carbon emission intensity. The increase in urbanization rate and energy consumption intensity leads to an increase in carbon emission intensity. The reduction of the proportion of secondary industry in low-level cities is conducive to the reduction of carbon emission intensity. At the same time, we selected factors from the economic, energy, and social indicators in the low-level city rating system to reveal the contribution of different factors to the difference in carbon emission intensity. This is helpful to narrow the gap among the cities, accelerate the transformation from low-carbon cities to non-carbon cities, and realize the economic development of low-level cities.

Impact Analysis of Population Aging on Public Education Financial Expenditure in China

The problem of China’s aging population is becoming increasingly serious, which brings a variety of social and economic issues. This paper constructed the theoretical framework and analyzed the impact mechanism of the population aging on local public education financial expenditure, and selected provincial panel data from 2010 to 2020 for empirical testing. It is found that population aging has a significant negative impact on local public education financial expenditure, and that with every 1% increase in old-age dependency ratio, local public education financial expenditure will decrease by 0.304%. The increase of urbanization rate has a significant positive impact on local public education financial expenditure, and with every 1% increase in urbanization rate, the local public education financial expenditure will increase by 0.215%. The test of impact mechanism shows that local government fiscal revenue and public expenditure for the elderly has the mediating effect in the impact of population aging on local public education financial expenditure, and the mediating effect of public expenditure for the elderly is stronger. The conclusions of the research can help provide policy implications for solving the declining level of local government public education financial expenditure in the context of an ageing population, and provide theoretical support to improve the rational allocation of fiscal public expenditure.

Urbanization and poverty in Sub-Saharan Africa: evidence from dynamic panel data analysis of selected urbanizing countries

Urbanization in Sub-Saharan Africa (SSA) is generally highlighted as a puzzle that deviates from the stylized facts in the literature. Using data from a panel of 29 urbanizing countries in SSA from 1985 to 2019, the study employs the two-step system generalized methods of moments to investigate the effect of urbanization on the Poverty Headcount ratio and Poverty Gap. The estimated urbanization elasticities of poverty indicate that at growth rates, a 1 percentage point increase in urbanization rate induces 0.04 and 0.05 (0.07 and 0.09) percentage points decrease in the Poverty Headcount ratio and Poverty Gap in the short-run (long-run), respectively. Similarly, at levels, a 1 percent increase in urbanization level induces 0.22 and 0.32 (0.60 and 0.68) percent decrease in the Poverty Headcount ratio and Poverty Gap in the short-run (long-run), respectively. Consistently, these results show stronger effect of urbanization on the depth of poverty relative to the incidence of poverty. These findings reappraise the literature on the urbanization of poverty in SSA as well as provide a nuanced understanding of the effect of urbanization on the different class of poverty measures. Notwithstanding, the poverty reduction potential of urbanization is not automatic and requires enormous investment in public infrastructure to achieve.

Studying Sharp Changes of Urban Landscape: Concession Within Agricultural, Hydraulic, and Maritime Public Domain in Kelibia City, Northern Tunisia

Coastal cities are desirable places to live and work which results in ongoing and increasing urbanization. In southern Mediterranean countries, coastal urbanization often occurs on croplands. This expansion is frequently on most productive croplands and emerges as an important sustainability concern. The aim of this study is to quantify urban growth over lands in Kelibia city, a coastal region in Tunisia that is one of the most threatened Mediterranean regions. We describe the changes in urban structures during the period of 2012–2016 by using Multi dates Pleiades images and using Otsu binary and sample-based Edge segmentation. Otsu segmentation showed higher accuracy than Edge segmentation method. Based on Otsu binary maps, urban areas were quantified in two dates. The results illustrated a dramatic increase of urban areas at the expense of agricultural land, maritime public domain (MPD) and hydraulic public domain (HPD). Analysis of parameters for urban sprawl quantification evaluated a sharp increase of urbanization rate, intensity, and dynamic degree. FRAGSTAT metrics described the change of landscape structure due to the increase of fragmentation pace, compactness degree, shape complexity, and proximity reduction. This significant urban change in extent and structure during a short temporal scale could be considered as a serious issue. For this reason, the implementation of systematic strategies for urban monitoring requires citizen awareness, law enforcement, and scientific supervision to mitigate land consumption, reduce flooding vulnerability, and to control the environmental impacts of urbanization.

BP Neural Network-Based Big Data Intelligent Travel Algorithm and Its Application

With the increase of urbanization rate, a large number of people flood into cities, increasing pressure of urban traffic, and problems accumulated in the taxi industry are gradually prominent. The phenomenon of crowded queue for taxi is frequent in peak hours, and vehicles patrol and sweep streets during peak hours. The key to solve these problems lies in mastering the rules and patterns of taxi travel and finding the factors affecting the relationship between taxi supply and demand. It is difficult to effectively understand taxi travel as a whole due to the large number of taxis and their large scale and strong mobility. Comprehensive application of trajectory data mining method can extract the spatiotemporal characteristics of massive taxi trajectory data and reveal the nature of its occurrence. This paper mainly focuses on the problems faced by urban traffic governance, such as the mismatch between data sources and demand systems, the uncoordinated operation of comprehensive transportation system, and the difficulty in sharing big data resources between government and enterprises. With massive data resources across departments, this paper designed a networked intelligent computing platform for big data of urban transportation integrated with various modes of transportation to sense the operation situation of urban comprehensive transportation system in real time, accurately grasp the space-time distribution of urban transportation supply and demand, and significantly improve the ability of coordinated operation, organization, and management of transportation in large cities. It also effectively enhances the quality of transportation information sharing and integration services and comprehensively improves the efficiency and overall carrying capacity of the urban comprehensive transportation system.

A Study on the Relationship Between Land Finance and Housing Price in Urbanization Process: An Empirical Analysis of 182 Cities in China Based on Threshold Panel Models

Abstract Scholars have a variety of theoretical explanations for housing price growth. However, few scholars have studied the internal influence mechanism among urbanization, land finance, and housing price. Based on the data of 182 prefecture-level cities from 2009 to 2016, this paper studies the influence of land finance on housing price under different urbanization rate levels. The study finds that with the increase of urbanization rate, the effect of land finance on housing price presents a “U” shape. Specifically, an increase in land finance by 1% results in a corresponding increase in average housing price by 0.18%, with relatively low urbanization rate, 0.06% with medium level of urbanization rate, and 0.38% with high level of urbanization rate.

Impacts of urbanization on carbon emissions: An empirical analysis from OECD countries

The impacts of urbanization on carbon emissions have attracted widespread attention for a long time. Quantitative research on the impacts is of great significance for formulating carbon reduction policy. Based on the dynamic panel autoregressive distribution lag (ARDL) model, we systematically study the general and heterogeneous long-run equilibrium relationships, short-run dynamic relationships, impact mechanism and lag effect between urbanization and three carbon emission dimensions in OECD high-income countries during long period. The main empirical results indicate that developed countries tend to have the same negative impacts of urbanization on carbon emissions, although there are differences in the endowments of different countries. The impact is relatively weak, for each percentage point increase in urbanization rate, CO 2 emissions per capita decrease by 0.015%, total CO 2 emissions decrease by 0.012%, and CO 2 emission intensity decrease by 0.009%. All member countries have achieved the decoupling of urbanization and carbon emissions. Urbanization affects carbon emissions by affecting economic growth, energy efficiency, and final energy consumption structure. This paper further reveals the multi-level impacts of urbanization on carbon emissions and provides policy implications of achieving carbon reduction through urbanization's agglomeration effect for government decision makers. • Estimate the impact of urbanization on carbon emissions based on panel ARDL model. • Analyze general & heterogeneous long-, short-run relationship and impact mechanism. • Urbanization decreases carbon emissions but the impact is weak in OECD countries. • Developed economies have achieved the decoupling of urbanization and CO 2 emissions. • Promote urbanization process and exert its scale effect to reduce carbon emissions.

The Relationship between Urbanization and Domestic Energy Consumption: An Empirical Study of Shandong Province, China

The rapid development of urbanization has led to a rapid increase in total energy consumption. The proportion of domestic energy consumption to total energy consumption has gradually increased and has become the major driving force for energy consumption. With the pressure from urbanization and domestic energy consumption, it is necessary to study the impact of urbanization on domestic energy consumption of the regional level and to explore the function paths of these two factors. The findings are helpful to realize sustainable development based on the actual situation analysis, horizontal survey data and statistical yearbook panel data. The current situation and changing trends in domestic energy consumption of Shandong Province are systematically examined through field investigation and survey questionnaire. The time-series econometric model is applied to analyze the relationship between urbanization rate and total domestic energy consumption. The research results show that the total domestic energy consumption and urbanization rate of Shandong are generally increasing. The urbanization rate development and domestic energy consumption have a long-term stable and balanced relationship. An increase in urbanization rate can cause an increase in domestic energy consumption. There is a slight difference between the average total energy consumption levels of urban and rural residents, but their energy consumption structures differ a lot. These findings provide basic data support and reference for local governments to formulate energy- conservation and emission-reduction policies.

Study on the impact of energy rebound effect on carbon emission reduction at different stages of urbanization in China

Analyzing the influence of energy rebound effect on carbon emissions at different urbanization stages is of great significance to improve the effectiveness of emission reduction polices. In this paper, the energy rebound effect is classified into the short-term energy rebound effect and the long-term energy rebound effect. Based on the environmental Kuznets curve, the nonlinear programming model of urbanization, energy rebound effect and carbon emissions is established to analyzed the influence mechanism of energy rebound effect on carbon emissions at different stages of urbanization. We further discuss how to avoid the impact of energy rebound effect on carbon emission reduction. The results show that: (1) The influence of short-term energy rebound effect on carbon emissions is greater than long-term energy rebound effect, and both of them decrease with the increase of urbanization rate. (2) The “discretionary” and “hitchhiking” behavior of local governments in formulating environmental policies will lead to the “Matthew Effect” of energy rebound effect. (3) Investment bias and factor market distortion could increase energy rebound effect, and they have obvious substitution effect. (4) The decentralization of power by local governments is an effective measure to suppress energy rebound effect. The analysis above could help local governments to formulate policies, suppressing the influence of energy rebound effect and promoting carbon emission reduction.

Assessing the resilience of the belt and road countries and its spatial heterogeneity: A comprehensive approach.

Regional resilience refers to the resilience of a country or region against the ecological environment, social economy, and other internal and external natural factors and human factors in the process of development. When this resilience is lower than a certain critical threshold, the country or region will be in a fragile state. The comprehensive embodiment of ecological resilience, social resilience, and economic resilience of a country or region is regional resilience. Due to the wide range of countries along “the Belt and Road”, differences in natural background conditions and stages of economic and social development among different countries lead to different degrees of vulnerability, and the improvement of resilience is conducive to reducing vulnerability. At the same time, the research on the measurement and differentiation characteristics of regional resilience is of considerable significance to solve the weak foundation of environmental management and the lack of ability to deal with climate change of “the Belt and Road” countries. In this study, by using entropy weighting method and multi-index comprehensive evaluation method, 24 specific indicators are selected from three different dimensions: ecology, economy, and society, to construct a comprehensive evaluation index system about “the Belt and Road” countries resilience, and to evaluate the comprehensive resilience and spatial heterogeneity characteristics of China and 64 countries along “the Belt and Road”, and use multiple linear regression analysis to identify the main influencing factors of comprehensive resilience and analyze its influencing mechanism. According to the research, the overall resilience level of “the Belt and Road” countries shows prominent differentiation characteristics of “extreme difference”, the countries with low and low recovery status account for the vast majority; and the spatial differentiation characteristics of the levels of ecological resilience, economic resilience, and social resilience of countries along “the Belt and Road” are quite different. In countries with high levels of economic development, their comprehensive resilience is significantly higher than that of countries with low levels of economic development. There is no inevitable connection between a country’s economic growth rate and its comprehensive resilience level. At the same time, the relationship between resource richness and comprehensive resilience of countries is not apparent, but for those countries that are over-dependent on resources, the level of resilience is generally below. There is a certain degree of correspondence between urbanization rate and comprehensive resilience, that is, the comprehensive resilience will increase with the increase of urbanization rate. When the urbanization rate rises to a certain level, the level of comprehensive resilience does not change much. In this study, it provides scientific guidance for enriching regional resilience and national sustainable development theory, solving the fragile ecological environment foundation of “the Belt and Road” countries, speeding up the transformation of economic growth mode and dealing with a series of social problems.

Driving force heterogeneity of urban PM2.5 pollution: Evidence from the Yangtze River Delta, China

Abstract As one of the largest metropolitan regions in the world and the most dynamic urban agglomeration in China, the air pollution in the Yangtze River Delta (YRD) is attracting attentions. This paper examined the driving factors of PM2.5 pollution of 26 prefecture-level cities in the YRD from 2006 to 2016, based on the perspective of population development and its three factors: population size, population quality, and population structure. The quantile regression model was applied to systematically investigate the heterogeneity of the causes of urban PM2.5 pollution under different quantile levels. The empirical results showed that the increase of urbanization rate (a representative indicator of population size) and the urban disposable income per capita (a representative indicator of population quality) significantly reduced the PM2.5 pollution. The PM2.5 emissions increased correspondingly with the expansion of population structure indicators. Moreover, the effects of population development on the PM2.5 pollution in YRD cities had both homogeneity and heterogeneity. The homogeneity was supported by the fact that the impacts of most population variables decreased with increasing quantile level. This indicated that the PM2.5 pollution was more sensitive to population development when the pollution level was low. The heterogeneity relied on two aspects: firstly, the key driving factors of PM2.5 pollution differed in cities with same pollution level; secondly, with increasing pollution levels, the impacts of different population development factors on PM2.5 pollution presented different trends. Policy recommendations from the perspective of population development are provided for prefecture-level cities to control PM2.5 pollution.

Impact of Influencing Factors on CO2 Emissions in the Yangtze River Delta during Urbanization

The Yangtze River Delta (YRD) is China’s largest urban agglomeration with a rapid urbanization process. This paper analyzes the dynamic relationship between urbanization rate, energy intensity, GDP per capita, and population with CO2 emissions in YRD over 1990–2011 based on the extended STIRPAT model, impulse response function, and variance decomposition. A support vector machine model was constructed to further predict the scenarios of YRD’s CO2 emissions from 2015–2020. The results show that YRD’s CO2 emissions continuously increased during the sample period and are predicted to increase over 2015–2020. Energy intensity is the most influential factor, both in the short and long term, and the total population contributes the least. However, the influencing magnitude of energy intensity tends to decrease in the long term. The increase of urbanization rate is still accompanied by the increase of CO2 emissions in YRD, but an inverted-U shape relationship between them may exist in the long term. The contribution of GDP per capita to CO2 emissions is higher than the population and urbanization rate, and its contribution rate for CO2 emissions is growing. The Kuznets curve does not exist in the current YRD.

Urbanization level, changes of housing price and residential sales

There is a certain correlation between the level of urbanization, the change of commercial house price and the rate of housing sales. This paper, based on the national data of 31 provinces from 2005 to 2014, adopts the panel empirical model and arrives at the following conclusion. Every 1% increase in urbanization rate leads to 1.49% decrease in housing sales rate of estate enterprises; every 1% raise in house price brings 0.501% raise in housing sales rate; every 1% raise in the number of estate enterprises results in 0.060% increase in housing sales rate; it is also found if the investment rate in estate development increases every 1%, the sales rate will increase by 0.796%; and if the proportion of land value increment tax increases by 1%, the sales rate will drop in turn by 0.027%.

Water scarcity as a global public dilemma: Public fiscal policies towards rainwater harvesting

Factors such as population growth rate, industrialization, increase in urbanization rate, unplanned urbanization, consumption of pesticides, climate change, which are experienced during the history of mankind, cause environmental pollution affecting future generations especially water resources. This situation, which constitutes a global public problem in today's world, has particularly reached threatening levels for usable/potable water resources. Under the prediction that the world will face 40% water scarcity by 2030, it is important that the rainwater will be stored and made usable. The article includes the applied fiscal policies around the world (e.g. public standards/practices, public incentive policies, output/result-oriented policies). The article presents the current situation in Turkey and suggests the legal regulation.

The Effects of Natural Resources on Urbanization, Concentration, and Living Standards in Africa

Summary This paper examines the effects of natural resource abundance on urbanization and living standards in Africa. Our central hypothesis is that the exploitation of natural resources in a context of poor governance quality creates the conditions for rapid urbanization and urban concentration, and ultimately lowers living standards in primal cities. Using a large panel of African countries, our results show that an increase in the share of natural resources leads to a rapid increase in urbanization and urban concentration, even after taking into account endogeneity issues, or after using more exogenous measures of resource dependency. The paper also establishes a negative association between the resource abundance, the quality of life in large cities and the degree of informality via the increase in urbanization rate and urban concentration. Importantly, we have established that these results mostly hold in the context of bad governance. More specifically, the resource-led urbanization and concentration booms take place mainly in countries characterized by poor governance records. Furthermore, poor governance quality is associated with a more detrimental effect of urbanization and urban concentration on the quality of life in African cities. These results suggest that ongoing transformations experienced by these countries call for complementary policies to ensure a more balanced and efficient urbanization process.