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Promoting the formation of the green lifestyle (GL) is a crucial step in achieving comprehensive green transformation of urban economic and social development. The widespread adoption of GL is influenced by various environmental regulations. Previous research mainly focused on the impact of individual policies on GL from the single policy perspective. The mechanisms of the combined effects of policies have not been thoroughly explored, particularly the contributions of each policy during periods of overlap. This paper takes the dual-policy of the New-type Urbanization Policy (NUP) and Smart City Policy (SCP) in China as an example. It employs panel data collected from 271 cities in China during 2007–2019 and establishes a multi-period difference-in-difference model to identify the combined effects of the dual-policy on residents' GL. Additionally, the Shapley value decomposition method is utilized to identify the contribution magnitude of each policy when they act simultaneously. The following conclusions are yielded. Firstly, the combined effects of dual-policy are more effective than a single policy in influencing residents' GL. Secondly, the Shapley value decomposition method reveals that when both policies are simultaneously implemented, SCP contributes a greater weight compared to NUP. Thirdly, the dual-policy can promote residents' adoption of GL through mechanisms such as green technological innovation, public participation in environmental protection, and the agglomeration of tertiary industries. Fourthly, the impact of dual-policy on residents' GL varies across different types and sizes of cities. This study attempts to unseal the "black box" of how the dual-policy influences residents' GL during the green transformation of cities in China, providing theoretical references for relevant urban policies in other countries and contributing to Chinese solutions and experience to global urban green development. • The dual-policy of NUP and SCP can jointly promote residents' green lifestyle. • The weight of SCP's contribution is higher than NUP's by the Shapely value method. • It explored three potential channels between the dual-policy and GL. • There are heterogeneous effects of dual-policy on GL in different types of cities. [ABSTRACT FROM AUTHOR]

In the past decades, China has observed rapid urbanization, the nation's urban population reached 50% in 2000, and is still in steady increase. Rapid urbanization in China has an adverse impact on urban hydrological processes, particularly in increasing the urban flood risks and causing serious urban flooding losses. Urban flooding also increases health risks such as causing epidemic disease break out, polluting drinking water and damaging the living environment. In the highly urbanized area, non-engineering measurement is the main way for managing urban flood risk, such as flood risk warning. There is no mature method and pilot study for urban flood risk warning, the purpose of this study is to propose the urban flood risk warning method for the rapidly urbanized Chinese cities. This paper first presented an urban flood forecasting model, which produces urban flood inundation index for urban flood risk warning. The model has 5 modules. The drainage system and grid dividing module divides the whole city terrain into drainage systems according to its first-order river system, and delineates the drainage system into grids based on the spatial structure with irregular gridding technique; the precipitation assimilation module assimilates precipitation for every grids which is used as the model input, which could either be the radar based precipitation estimation or interpolated one from rain gauges; runoff production module classifies the surface into pervious and impervious surface, and employs different methods to calculate the runoff respectively; surface runoff routing module routes the surface runoff and determines the inundation index. The routing on surface grid is calculated according to the two dimensional shallow water unsteady flow algorithm, the routing on land channel and special channel is calculated according to the one dimensional unsteady flow algorithm. This paper then proposed the urban flood risk warning method that is called DPSIR model based multiple index fuzzy evaluation warning method, and referred to as DMFEW method. DMFEW first selects 5 evaluation indexes based on the DPSIR model for flood risk warning evaluation, including driving force index, pressure index, state index, impact index and response index. Based on the values of all evaluation indexes, one evaluation index for the whole system evaluation result is determined by using the fuzzy comprehensive evaluation method. The flood risk level is divided into 4 levels, having Level 1 the most serious. Every evaluation index is also categorized as 4 levels, and a linear fuzzy subjection function is proposed to do the fuzzy comprehensive evaluation. Dongguan City is used as the study case to validate the proposed method. The urban flood forecasting model is set up with the topographic data, the city map, the underground pipelines and land cover types, and two flood events are simulated with observed precipitation, one is interpolated from the rain gauges data, and another is estimated by digital weather radar. The simulated results are compared with the investigated water depth, and the results show the model has very good performances. The results are further used for the flood risk warning simulation, and are very reasonable. [ABSTRACT FROM AUTHOR]

It is an urgent challenge to coordinate industrialization and air quality in China since the rapid industrialization over the past forty years caused serious air pollution. In this paper, we measured the industrialization levels of the 31 regions in China from 2003 to 2017 as a sum of per capita gross domestic product (GDP), urban population (% of total), tertiary vs. secondary industry output ratio, non-agricultural output value (% of GDP), non-agricultural employment proportion, and the proportion of added value of manufacturing in the total added value of commodity. We measured air quality as a sum of annual SO 2 , NO 2 and PM 10 concentrations. In general, the industrialization level continuously increased while air pollution was reduced in spite of some fluctuations in China. Our results show air pollution presented N-shape relations with the industrialization level in China in the periods from 2003 to 2008, 2009 to 2013, and 2014 to 2017. Air pollution increases as the industrialization occurs but later deceases as the industrialization level improves. However, air pollution rebounds as the industrialization moves further but this rebound became weaker in recent years. With the association rule mining, we identified ranges of the six indicators for industrialization associated with good and poor air quality, respectively. Using industrialization indicators associated with poor air quality as references, we pointed out differentiated strategies for regions to coordinate the industrialization and air quality protection. • We analyzed industrialization progress & air quality from 2003 to 2017 in China. • Air pollution in China exhibits N-shape relations with industrialization level. • We mined association rules between industrialization indicators and air quality. • Summary of industrialization indicator ranges associated with good/poor air quality. • Differential strategy by region to coordinate development & air quality protection. [ABSTRACT FROM AUTHOR]

Household consumption activities affect energy and water consumption directly and indirectly. Based on input-output modeling, this paper divided Chinese urban and rural residents into 12 groups, and investigated the impact of the consumption activities of residents with different levels of income on China's energy and water consumption from the perspective of consumers. Two main results were found. 1) In 2012, the energy consumption caused by the consumption activities of the highest-income urban residents accounted for 17.3% of the total energy consumption. For water resources, the per capita water withdrawal and consumption of the highest-income urban residents reached 481.21 m3 and 284.45 thousand m3, 6 times more than that of the low-income rural residents. 2) We identified medium and medium-high income urban residents as the key groups of residents. From the perspective of the industrial sectors, the key sectors for high energy consumption and water usage included the Electricity and Agricultural sectors, and we identified the Electricity sector as the key sector for the water and energy nexus of the residential sectors. The conclusions of this paper have pertinence for policymaking, and they provide an appropriate policy basis for guiding residents' energy and water consumption. • Energy and water usage caused by household consumption in China is investigated. • Chinese urban and rural residents in input-output table are divided into 12 groups. • Energy consumption caused by the highest-income urban residents accounted for 17.3%. • Water usage of the highest-income urban residents is 6 times more than that of the low-income rural residents. • Electricity sector as the key sector for the water and energy nexus of the residential sectors. [ABSTRACT FROM AUTHOR]

Low-carbon pilot cities can break the lock-in effect of living carbon emissions, which are an important strategic component of China's response to climate change. Current research on low-carbon pilot cities focuses on the production field. Insufficient attention has been paid to whether low-carbon pilot cities can promote the green transformation of residents' lifestyle. Using panel data of 285 cities in China from 2004 to 2016, this study explores the inducing effect of low-carbon pilot cities on residents' low-carbon choices from holistic and single-dual perspectives based on the difference-in-differences method and the synthetic control method. This study finds that low-carbon pilot cities can promote the green transformation of residents' lifestyle, and this policy has reduced living carbon emissions by approximately 15.3%. The transmission mechanisms are mainly green life consciousness and green habits. The conclusion considers the effects of multi-pilot policies and other living differences during the parallel period and is still valid after robustness testing using propensity score matching difference-in-differences. In addition, the policy has a snowball effect, and is stronger in larger cities. Ultimately, this paper provides useful information for the scientific implementation of carbon emission reduction plans in the field of residents' living and the improvement of the long-term mechanism of pilot cities with both quality and quantity guaranteed. • Low-carbon pilot cities (LCPCs) induce residents to make low-carbon choices. • LCPCs have reduced living carbon emissions by approximately 15.3%. • LCPCs can coexist with other policies to achieve CO 2 reduction. • The mechanisms are mainly green consciousness and green habits. [ABSTRACT FROM AUTHOR]

Reactive nitrogen (Nr) has far-reaching advantages and disadvantages on human beings. Nitrogen footprint (NF) is a tool to quantify the use of Nr in the environment. Food nitrogen footprint (FNF) accounts for the largest proportion of the total NF, and the differences between provinces in China exist objectively. In order to explore the spatial correlation and socio-economic driving factors of China's FNF, this paper uses N-calculator tool to calculate the FNF of 30 provinces in China from 2000 to 2018, and uses exploratory spatial data to analyze the spatial correlation and changes of provincial FNF, The driving factors and spatial effects of FNF change in the province were analyzed by using spatial Durbin panel model and spatial regression partial differential method. The results showed that: (1) There is a significant and stable positive spatial dependence and heterogeneity in the FNF among provinces; (2) The direct effect factors of promoting the growth of FNF in the province are urban household Engel coefficient, per capita disposable income of rural residents and rural household Engel coefficient. The main factors of restraining the growth of FNF in the province are wastewater discharge per unit GDP and per capita GDP; (3) the spillover effect is mainly manifested as the negative effect of the increase of urban household Engel coefficient on neighboring provinces, and the spillover effect of per capita disposable income of urban residents and nitrogen fertilizer application rate per unit grain yield on the growth of FNF of neighboring provinces is significant. From the policy level, it is necessary to guide healthy and scientific eating habits, reduce the proportion of meat and fish in the diet structure, reduce the nitrogen fertilizer application per unit grain yield, and improve the efficiency of chemical fertilizer utilization. When formulating relevant policies, government departments should give consideration to the cooperation between provincial and regional governments. • N-calculator tool is used to calculate the FNF of 30 provinces in China. • Driving factors and spatial effects of FNF change in the province were analyzed. • The spatial Durbin panel model and spatial regression partial differential method are used for the analysis. [ABSTRACT FROM AUTHOR]

Abstract: This paper examines the determinants and consequences of rural to urban registration (hukou) mobility in contemporary China, focusing on the link between social origins, hukou conversion, and the consequences of conversion. In contrast to massive rural–urban migration, hukou conversion is difficult and rare, but childhood urban residence increases the likelihood of achieving an urban hukou. Compared to people with urban origins, hukou converters are more likely to enter tertiary institutions, but are significantly less likely to do so subsequent to hukou conversion. Individual converters from rural origins are more likely to work in non-manual occupations. Collective converters earn significantly less than people with urban origins. Individual converters with rural childhoods, who used to be at the bottom of the society, are significantly happier than other urban residents, although they are less healthy. These results show that the effect of hukou conversion varies across hukou converters from different social origins. [Copyright &y& Elsevier]

This paper analyses the factors influencing consumer-perceived risks of genetically modified (GM) food by using a structural equation model and survey data of urban residents in China. The sample is divided into the acquainted and unacquainted groups according to consumers' objective knowledge level. An integrated analytical framework is developed. The results show that consumers' positive attitude towards GM technology has a significant negative effect on consumer-perceived risks and that more information reaching consumers significantly reduces consumer-perceived risks of GM food only for the unacquainted group. Consumers' trust in government, biotechnology scientists, press media and food companies does not significantly influence consumer-perceived risks of GM food. This is likely because consumers have low trust in the abovementioned stakeholders of GM food. Consumers think that the information reaching them is limited and does not clearly show the advantages and disadvantages of GM food. Consumers' objective knowledge of GM food is also limited. The health risks of GM food are of high concern for both consumer groups. These findings imply that the commercialization of GM crops in China is dependent on providing consumers with adequate and understandable information about GM food and strict supervision measures for food safety. [ABSTRACT FROM AUTHOR]