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In the context of significant environmental changes, the urgency of adopting green innovation has become increasingly apparent as a central mechanism for adjusting industrial structures in China. This transition serves not only as a crucial way to address pressing environmental challenges, but also as a fundamental strategy to improve the ecological efficiency of urban areas. Existing research mainly keeps a close eye on the unidirectional relationship between variables such as technological innovation and environmental protection. There is less relevant literature that has researched the cointegration relationship among green innovation, industrial structure, and eco-efficiency of cities. The essential role of green innovation and industrial structure in reaching a higher eco-efficiency of city are discussed in this research and the relationship among these three variables are analyzed by the evidence from cities in China from 2011 to 2019. The fact that the variables are cointegrated in the long run is evidenced by the results for the full sample. The sub-sample results report that in the eastern region, green innovation, industrial structure upgrading, and industrial structure rationalization could improve urban eco-efficiency. However, in Midwest regions where economic development is relatively backward, green innovation's effect on urban eco-efficiency is not in a significant positive way. The results obtained in this paper have implications for different cities in China to formulate corresponding policies on green innovation, industrial structure, and urban eco-efficiency. [ABSTRACT FROM AUTHOR]

This research empirically investigates the static and dynamic impacts of firms' digital transformation on environmental, social, and governance (ESG) performance by employing data of listed Chinese companies from 2011 to 2020 via estimations of propensity score matching and difference in differences. First, we find that digital transformation does some good to improve firms' ESG, which is confirmed after conducting several robustness tests. Second, digital transformation benefits the three aspects of ESG (environmental performance, social responsibility, and governance), and its impact is dynamic, promote ESG two years after the digital reform. Third, the impact of digital transformation on ESG is not constant among different firms. Specifically, digital transformation's impact on ESG is stronger among firms located in western or central regions of China and to those in polluting and competitive industries, as well as among non‐stated‐owned enterprises. [ABSTRACT FROM AUTHOR]

In order to meet the strategic goals of carbon peak and carbon neutralization on schedule, it is crucial to examine the effects and limitations of green finance on the green transformation of industry. This research utilizes the entropy method, the Global Malmquist–Luenberger technique, and panel data of 30 provinces in China from 2005 to 2018 to estimate the extent of industrial green transformation and green finance development in each province. It builds static and dynamic panel models to experimentally examine the effect of green finance on industrial green transformation. After introducing environmental regulation (ER), this paper presents how ER influences the link between green finance and industrial green transformation. The research finds the following. (1) According to geographical differences in the growth of green finance and industrial green transformation, the economically developed east region is more advanced than the central and west regions, and the central region is more advanced than the west region. (2) Green finance has a significantly positive impact on industrial green transformation, and this positive influence has certain continuity and inertia. (3) Environmental regulation has a favorable impact on the link between green finance and industrial green transformation; specifically, a rise in the level of environmental regulation stimulates the process of green finance that boosts industrial green transformation. The policy recommendations herein offer reference for the construction of China's green financial system and the promotion of industrial green transformation for CSR. [ABSTRACT FROM AUTHOR]

This research investigates the bidirectional cointegration relationship between environmental, social, and governance (ESG) performance and corporate green innovation with a panel of 770 Chinese listed firms during the 2011–2020. We find that there exists a long‐run bidirectional comovement between ESG performance and corporate green innovation output. ESG performance exerts a short‐run and long‐run causal link with green innovation output. The panel cointegration test and VECM estimation also support that ESG performance moves together with green innovation output for clean industries, while ESG performance only presents a long‐run relationship to green invention patents output for pollution industries. Our findings offer important value for policymakers and enterprises to propose an effective strategy to stimulate green innovation and improve ESG score. [ABSTRACT FROM AUTHOR]

This research conducts an empirical study on arbitrage opportunities in the crude oil futures market of Shanghai International Energy Exchange in the period of China's economic change, 2020–2022. We use the daily closing price data of crude oil futures sc2303 and sc2212 to test whether there is a statistical arbitrage opportunity in China's crude oil futures market. Taking the most commonly used 12 + 6 rolling window mode in statistical arbitrage, we select several one-year periods that pass the cointegration test during the formation period and apply the optimal opening, closing, and stop loss thresholds based on the highest yield during the formation period to the trading period. Finally, we draw the following conclusions: (i) the pair trading strategy based on the cointegration model is profitable in China's crude oil futures market; (ii) the 12 + 6 window model can be applied to the pair trading strategy based on China's crude oil futures. Our research proves the effectiveness of pair trading strategy in China's crude oil futures market for institutional and individual investors. [ABSTRACT FROM AUTHOR]

In this study, we use the spatial econometric model with panel data to investigate the mechanism and effect of economic growth on public health in Western China. The research results show that the spatial agglomeration effects are significant on the public health performance in Western China. Economic growth significantly promotes local public health status during the range of our sample data, leading to reduced human mortality. Environmental pollution significantly increases human mortality not only in local province but also in neighboring provinces. As GRP per capita of a province continues to increase, the impact of environmental pollution on increasing human mortality has diminished gradually. Moreover, improving the level of technological progress and healthcare services significantly improve public health. Interestingly, as GRP per capita of a province continues to increase, the impact of technological progress and healthcare services on decreasing human mortality has gradually weakened. [ABSTRACT FROM AUTHOR]

Countries around the world are facing enormous challenges in their economic and social development as COVID‐19 continues to spread, resulting in slower economic recovery in the post‐pandemic era. Considering the impact of economic growth on future sustainable development in this new era, green economic recovery (GER) can achieve a win‐win situation between economic recovery and environmental improvement and bring forth environmentally sustainable economic growth. This research first lists related COVID‐19 literature surveys and GER policies in the post‐pandemic era in China. Based on a comparative study of the international experience of GER policy practices, this paper then analyzes the opportunities and challenges China faces for GER and puts forward countermeasures and suggestions on how to promote its sustainable development in the post‐epidemic era. We believe our research presents useful enlightenments for sustainable economic and social development in the post‐epidemic era. [ABSTRACT FROM AUTHOR]

Green finance is a novel financial model that strikes a balance between economic gains and environmental preservation, and it is crucial in encouraging industrial companies to move towards environmentally friendly development. This paper examines the impact of green finance on the green transformation of industrial enterprises using the data of China's A-share listed industrial enterprises from 2009 to 2019. The study adopts a propensity score matching method and a difference-in-difference method (PSM-DID), based on the Green Credit Guidance (2012 Guidance) issued by China as a quasi natural experiment. The results suggest that: (1) Green finance contributes significantly to improving the green production efficiency of industrial enterprises. (2) Although the current impact of green finance on the green innovation of industrial enterprises is not statistically significant, it exhibits a positive influence in the subsequent period. (3) The results of the heterogeneity analysis show that the impact of green finance on the green transformation of industrial enterprises is asymmetric, with more emphasis on state-owned enterprises, enterprises with severe financial constraints, and enterprises with low industrial concentration. As a result, our study makes recommendations on how to best link CSR, green finance, and industrial green transformation. • We investigate the impact of green finance on green transformation of industrial enterprises. • Using the data of China's A-share listed industrial enterprises from 2009 to 2019. • The results suggest that green finance significantly improves industrial green production efficiency. • Our study makes recommendations on how to best link CSR, green finance, and industrial green transformation. [ABSTRACT FROM AUTHOR]

This research examines the effects of executive political connections on corporate performance by comparing firms with mergers and acquisitions (M&As) and firms without M&A activities in the energy sector using China Securities Regulatory Commission industry data from 2008 to 2018. We integrate two theoretical approaches, resource dependence and the agency view into one framework, and find that executives' political connections have a positive effect on corporate performance when there are no M&A activities, which is consistent with the resource dependence theory; however, well-connected executives harm firm performance through M&A activities. Our main results still hold after considering endogeneity issues, substituting relevant variables, comparing the effect of the global financial crisis, and controlling for market structure. Our study provides significant insight into the energy sector, which can help practitioners and policymakers who want to make advancements in firms' competitiveness through better implementation of policies related to M&A. [ABSTRACT FROM AUTHOR]

Based on panel data of 31 provincial capital cities in the country from January 21 to November 20, 2020, this research empirically analyzes the impacts of daily newly confirmed cases and daily new deaths from COVID-19 on PM10, PM2.5, SO2, CO, and NO2 emissions form green energy consumption by using the method of System Generalized Moments (SYS-GMM). We conclude that the COVID-19 pandemic has an inhibitory effect on all types of emissions, in that a greater number of confirmed cases and deaths brings about more stringent anti-epidemic policies, fewer emissions, and better air quality in China. Moreover, we use the methods of sample segmentation, cross-sectional regression, and pollutant emissions of the top three cities in terms of GDP to test their robustness. Overall, our evidence advances the debate over air quality after COVID-19, and that evidence from China provides beneficial experiences that correlate to its provincial data. [ABSTRACT FROM AUTHOR]

Owing to economics are usually linked with energy production, economic policy may have an instantaneous adjustment according to the current monetary, financial, cultural circumstances. This research thus investigates the dynamic co-movement as well as cointegration relationships between economic policy uncertainty (EPU) and disparate energy productions, i.e., Chinese coal, natural gas, crude oil, electricity as well as renewable energy, during the period from January 1995 to October 2019 in China. We compare the two EPU indices and make empirical and robust analysis to get more evidence for the time-varying co-movement between energy production and EPU. The empirical results show that there are stationary properties and cointegration relationships between energy production and EPU. By utilizing wavelet co-movement analysis in the time-frequency domain, our results show a significant positive co-movement among disparate energy productions and EPU at high frequencies, i.e., in the short term, but weaker co-movement at low frequencies, i.e., in the long term. Hence, the phase-difference series are mostly around the zero line, implying the variables behave to the dynamics of the co-movement with positive causality. Policy recommendations are offered in accordance with our finding. [ABSTRACT FROM AUTHOR]

Taking China provincial-level data during 2003–2017 as the basic space-time unit, this research applies the Moran index and spatial econometric model to analyze the spatial pattern change trend and spillover effects of regional innovation output. The results show that, first, provincial innovation outputs mainly concentrate in the coastal economic belt and Yangtze economic zone. Second, there is a correlation in space for provincial innovation output, and the growth rate of provincial innovation output has a positive spillover effect. The rate of conditional β-convergence is 3.926%, and the half-life cycle of convergence is 17.665 years. Third, environmental regulations have pushed the development of regional innovation to some extent. Fourth and finally, regional innovation input and its spillover effects impact the level of regional innovation output. Innovation output, environment regulation, and R&D internal expenditure are the main paths for innovation's spillover effect. [ABSTRACT FROM AUTHOR]

This study empirically investigates the effect of external financial market friction on restructuring activities, based on panel data of listed Chinese firms from 2004 to 2018. The results show that there is a positive correlation between financial market friction and the number of restructuring deals. We also find that high financial market friction increases preference for cash payments and the likelihood of mergers and acquisitions. These findings add to the restructuring literature by capturing heterogenous restructuring forms. They also deepen the understanding of the firm boundary theory, by suggesting that firms have incentives to increase their scopes when facing external market distress. [ABSTRACT FROM AUTHOR]

As a typical deviation from profit-maximizing, the revenue-maximizing behavior has explained the strategy of firms in many industries. This research first looks into the Chinese non-life insurance market and finds evidence of revenue-maximizing behavior of the non-life insurers. We construct a model based on game theory to reflect the revenue-maximizing behavior and calculate the Nash equilibrium of the game. The research finds that revenue-maximizing players will incur operation loss in the game; the insurers with less competitive strength will suffer more loss. The theoretical results are hence applied tests by case study on Chinese auto insurance industry. The panel cointegration test and the regression results reveal that a more liberalized regulatory regime will result in a lower price, while large insurers tend to take advantage of their market power to price at a higher level than smaller insurers, this finding corresponding to the result of our theoretical model. [ABSTRACT FROM AUTHOR]

To investigate the effects of regulation on environmental pollution under Chinese-style fiscal decentralization, this research analyzes annual data over the period 2003 to 2017 covering 30 provinces in China with the spatial economic model. The empirical results show significant spatial agglomeration effects on the emissions of wastewater, sulfur dioxide, and solid waste. Environmental regulation helps reduce discharge of wastewater and solid waste, but does not help reduce the emission of sulfur dioxide; because there is significantly positive externality in treating pollutants with high fluidity, cost is larger than revenue for local governments. The relationship between fiscal decentralization and pollutants shapes an inverted U-shaped curve. We finally offer some implications in accordance with our empirical finding, such as the intensity of environmental regulation should be suitable for economic development, different measures should be taken based on the fluidity of pollutants, and a new evaluation system should be established. [ABSTRACT FROM AUTHOR]

To investigate the effects of government environmental regulation and industrial structure changes on carbon dioxide emissions, this research analyzes annual data over the period 2003–2015 covering 30 provinces in China (except for Tibet) with the panel smooth transition regression (PSTR) model. The empirical results show obvious non-linear effects of environmental regulation and industrial structure on carbon dioxide emission. Taking the effects of both linearity and non-linearity into consideration, environmental regulation will reduce carbon emissions with the change of industrial structure rationalization (SR). When the level of industrial structure optimization (SH) is low, environmental regulation promotes carbon dioxide emissions. When the level of industrial structure optimization (SH) is high, environmental regulation plays a significant inhibitive role on carbon dioxide emissions. The Kuznets relationship between GDP per capita (PGDP) and carbon dioxide emissions is influenced by local industrial structure rationalization and industrial structure optimization. Therefore, environmental regulation policies suitable for local conditions should be made based on the transition of the local industrial structure. [ABSTRACT FROM AUTHOR]

Environmental pollution is an important factor affecting the sustainable development of a country or region. Therefore, it is of great theoretical and practical significance to deeply study and judge the decoupling relationship between economic growth and environmental pollution. On the basis of 31 provinces in China, the present paper decomposes the decoupling elastic coefficient into scale decoupling elasticity, technical decoupling elasticity, and structural decoupling elasticity by log mean divisia index and analyzes the decoupling relation between economic growth and environmental pollution from 2001 to 2015. We also evaluate the degree of the decoupling in time and space for various provinces. The results show economic growth has decoupled from industrial waste water emissions; industrial solid waste has gradually gained some improvement; the decoupling state between economic growth and industrial exhaust is unstable; and the increasing economic scale is the key driver for environmental pollution. However, the evidence also shows that technology plays a positive role in the decoupling. From analysis of the spatial pattern of decoupling, almost all developed areas in the eastern coastal region have achieved decoupling, while decoupling in the middle and western regions is unstable. Finally, the revision of The Law of the People's Republic of China on Energy Conservation has played a certain role on the decoupling of economic growth and environmental pollution. [ABSTRACT FROM AUTHOR]

Political incentive is one of the most efficient methods to promote local officials to push for both economic growth and environmental progress in the context of China. Since previous scholars have never investigated the relationships between political turnover and environmental governance at the municipal level, in this work, we proxy pollution by SO2, COD, SOOT, and NHx and examine whether environmental performance affects the political turnover of the municipal party secretary by exploiting a panel conditional logit with a fixed-effect model for the period 2002-2013. The results indicate that environmental performance does not significantly impact the turnover of municipal party secretaries, offering evidence that an increase of SO2 is associated with the likelihood of promotion under the panel multinomial logit approach. However, a higher GDP growth rate plays the determinant factor affecting the promotion of China’s municipal party secretaries. Specific policy recommendations are proposed in accordance with our empirical findings. [ABSTRACT FROM AUTHOR]

As is well known, Chinese central government has full authority to determine the provincial and local officials’ turnover. However, China has not in detail interpreted the standards of officials’ promotions so far. In this paper, the latest database of city-level leaders for the period between 2002 and 2013 is utilized to investigate the influences of economic performance on party secretaries’ odds of being promoted. The estimation results by a panel multinomial logit method indicate that municipal annual GDP per capita is significantly positively associated with leaders’ chances of promotion. Specifically, the average GDP growth rates during leaders’ tenures have much higher effects. Moreover, some important factors of leaders’ personal characteristics also affect the political turnover. For instance, party secretaries’ connection with China’s Communist Youth League, political experience, educational level and professional expertise all have positive impacts on their chances of obtaining a promotion. In contrast, leaders’ ages and tenures are found to be negatively related to their promotion possibilities. [ABSTRACT FROM AUTHOR]

We employ data of 6194 firm-year observations for 1058 listed companies in the period 2006-2013 to investigate the interaction between stock liquidity and enterprise innovation in China and confirm that an increase in stock liquidity raises the number of patents granted, R&D investment, and the innovation efficiency of state-owned enterprises, while it decreases innovation significantly in private firms. These findings are also supported by quasi-natural experiments under the split-share structure policy reform and the adjustment of the stamp duty rate using propensity score matching and difference-in-difference methods. We then identify two possible mechanisms through which liquidity increases innovation: the entry of long-term and strategic institutional investors and the gradual privatization of SOEs. Several policy implications are provided in accordance with our findings. [ABSTRACT FROM AUTHOR]

This study investigates the long-run co-movement between venture capital and technological innovation for 28 provinces (including autonomous regions) in China, using the panel cointegration and panel-based error correction model over the 2001-2012 period. Our results confirm that venture capital and innovation have long-run cointegrated relationships as well as bidirectional causality for the whole country. Analysis of sub-samples again discovers similar results in both the eastern and central regions, but not in the western region. The policy implication shows that China's development of innovations should be based on more venture capital input and that the government should establish a long-run innovation policy to accelerate the development of venture capital. We also offer several constructive suggestions for governments in the western provinces. [ABSTRACT FROM AUTHOR]

Theoretical studies suggest that there is a close association between fiscal decentralization and economic growth. However, whether this linkage holds in China or not is a matter of ongoing debate in recent empirical studies. In this paper, we investigate the impact of the 1994 tax sharing system on economic growth in China. Using a panel dataset for 29 provinces in China over the 1995-2014 period in a simultaneous equations system that controls for the simultaneity of fiscal decentralization, physical capital accumulation and economic growth, the influence of decentralization on economic growth is estimated. The estimation results indicate that there is an inverted-U shaped relationship between fiscal decentralization and economic growth. Because the optimal level of fiscal decentralization that maximizes economic growth is higher than the data for most provinces, further decentralization is in general helpful to China's economic growth. [ABSTRACT FROM AUTHOR]

This research robustly investigates and verifies the impact of science-technology intermediary (STI) on regional innovation for panel data covering 31 provinces in China from 2000 to 2019. Overall, we find that STI's effects on regional innovation are positive, no matter in the static or dynamic model, reflecting that more innovation-related entities may be motivated to plug into a STI-centered network due to increasingly positive externality, which in turn strengthens STI's innovation-enhancing effect over time. Giving consideration to both development and transaction costs in innovation activities, this study explores three mechanisms of the STI-innovation nexus. (1) STI reduces transaction cost, which then stimulates collaborations of innovation. (2) STI facilitates specialization in innovation-related resources' optimal redistribution, improving regional capacity to successfully convert existing elements into innovation outputs. (3) STI strengthens the capacity to absorb the knowledge spillover from neighboring provinces and foreign countries. All arguments herein are supported for the case of China. • We investigate the relationship between Science-Technology Intermediary and innovation. • The data span covers 31 provinces in China from 2001 to 2019. • Both STI's static and dynamic effects on regional innovation are positive. • Three channels, transaction cost, reallocation, and spillover, that mediate the STI-innovation relationship. [ABSTRACT FROM AUTHOR]

• We investigate the distributional effects of economic policy uncertainty on energy efficiency by employing the panel quantile regression method. • We focus on the continuous city dataset of China from 2003 to 2019. • The finding demonstrates the influences of economic policy uncertainty on energy efficiency differ remarkably at various quantiles in Chinese cities. This research investigates the distributional effects of economic policy uncertainty (EPU) on energy efficiency by employing the dynamic panel quantile regression method on annual data of 39 cities in China from 2003 to 2019. The estimation results present that EPU has a negative influence on energy efficiency in median and upper efficiency cities, while subsample analysis exhibits that greater EPU brings about an even lower energy efficiency performance. Moreover, the negative effects are stronger in central and western cities and weaker in eastern cities, indicating that cities with a greater economic foundation and higher technology development can more easily handle EPU's effects on energy efficiency, thus partly weakening the negative influence. Overall, we demonstrate the influences of EPU on energy efficiency differ remarkably at various quantiles of the distribution in Chinese cities, and our findings contribute to the existing literature in examining the different impacts of EPU on said efficiency. [ABSTRACT FROM AUTHOR]

China's carbon market has become increasingly active in recent years, and thus it is of great significance to study the characteristics of the carbon allowance price fluctuation for the healthy and steady development of this market. As leverage is common in asset prices in general financial markets, this paper adopts the leverage stochastic volatility (SV-L) model to characterize the price volatility of the five pilot carbon markets in China. We first make a Bayesian inference for the SV model, then construct a Monte Carlo calculation process based on Gibbs sampling for empirical analysis, and finally compare the SV-L model with the normal stochastic volatility (SV–N) model. The results show that the carbon price fluctuations of the five pilot markets are quite different. Among them, Shenzhen, Guangdong, Shanghai, and Beijing have a "positive leverage effect", and Hubei has an "anti-leverage effect". Through comparative analysis, we find that the SV-L model is superior to the SV-N model in terms of the degree of data fitting and simulation ability. Finally, we offer suggestions on the development of China's unified carbon market. • We explore the characteristics of carbon price fluctuation in different pilot markets in China. • The SV-L model indicates that the carbon price fluctuation of each pilot province or city shows great difference. • Five pilot carbon markets show different degree of leverage effect. • The SV-L model is superior to the SV-N model for characterizing the carbon price of pilot markets in China. [ABSTRACT FROM AUTHOR]

• This paper investigates the effect of globalization on innovation by Chinese firms. • Using a combined dataset of 596,809 Chinese manufacturing firms. • We find that overall provincial globalization is associated with better innovation performance for Chinese firms. • China government should continue to attract foreign investors to enhance innovation. This paper investigates the effect of globalization on innovation by using a combined dataset of 596809 Chinese manufacturing firms with 1,993,154 observations and provincial globalization indices from 1998 to 2009. The empirical findings suggest that overall provincial globalization is associated with better innovation performance for Chinese firms. More specifically, economic, social, and political globalization, present positive impacts on technological innovation. Interestingly, through subsample analysis the findings indicate that globalization expresses a distinct relationship with firms' innovation performance. In particular, economic globalization correlates to greater technological innovation in private-owned enterprise, a lower one in stated-owned enterprises, and an insignificant one in foreign-owned enterprises. Moreover, a subsample analysis for different industries exhibits similar results as in the full sample except for the resources-intensive industry in which economic globalization is associated with lower innovation. Our findings indicate that China should continue to enhance connections in the economic, social, and political dimensions with other countries. [ABSTRACT FROM AUTHOR]

Highlights • The non-linear relationship between venture capital investment and technological innovation in China. • The panel smooth transition regression (PSTR) model. • VC only presents a positive impact on innovation in China when investment is large enough over the threshold level. • Venture capitalists are more willing to support innovation only for those in the “seed” and “initial” stages in China. Abstract This study investigates the non-linear relationship between venture capital investment and technological innovation for 28 provinces in China, using the panel smooth transition regression (PSTR) model for the period 2001-2014. Our results confirm that the relationship within the empirical model is indeed non-linear, and venture capital (VC) only presents a positive impact on innovation in China when investment is large enough over the threshold level. However, VC may severely hurt the innovative abilities of invested enterprises when the scale of investment is relatively small, especially in “western” and “lower-investment” provinces after dividing the sample provinces into different groups. [ABSTRACT FROM AUTHOR]

Globally, nations are increasingly focusing on green innovation in their environmental protection efforts as part of sustainable development, and digital finance is playing a vital role in enhancing green innovation. Employing annual data from 220 prefecture-level cities between 2011 and 2019, we empirically analyze the connections among environmental performance, digital finance, and green innovation via the Karavias panel unit root test with structural breaks, the Gregory-Hansen structural break cointegration test and pooled mean group (PMG) estimation. The following four points are the key conclusions: (1) The results support cointegration links between these variables when structural breaks are considered. (2) The PMG estimation outcomes indicate that green innovation and digital finance may have a favorable long-term effect on environmental performance. (3) For better environmental performance and more green innovation, the level of digitalization of digital finance is crucial. (4) The potential of digital finance and green innovation to improve environmental performance has not been fully realized in the western region of China. • The relationship among environmental performance, green innovation, and digital finance is investigated. • The entropy method is used to evaluate the environmental performance. • Green innovation benefits environmental performance in the long run. • Digital finance improves environmental performance through providing financial support to green innovation. • There is cointegration relationship among the three variables after considering structural breaks. [ABSTRACT FROM AUTHOR]

• The study firstly compares dust emission ability of sand desert, gobi, and farmland. • Gobi has the greatest dust emission ability under most wind velocity conditions. • Wind velocity and dust size influence comparing result of dust emission ability. It is unclear which of the land types of sand desert, gravel desert (Gobi), and farmland acts as the major source of dust emission in northern China. Based on field observations, this study compared the dust emission ability (E) of the three land types and investigated the principal influencing factors, i.e., horizontal mass flux (Q) and dust emission efficiency (μ). Results showed that E was greatest for sand desert, followed by Gobi and then farmland at low friction velocities (u * < 0.23 m s−1). However, with the increase of u * , the exponential rate of increase of E was fastest for farmland, followed by Gobi and then sand desert. This is because the rates of increase of both Q and μ were fastest for farmland and slowest for sand desert. Consequently, as u * increased the E of both Gobi and farmland gradually exceeded that of sand desert. Gobi was found to have the greatest E under most u * conditions (0.23–0.90 m s−1) because of the overlapping effects of the comparatively strong Q and high μ. The E of farmland exceeded that of Gobi under extreme u * conditions (>0.90 m s−1) owing to its lower Q but faster rate of increase of Q and μ as u * increased. The findings of this study illustrate that the effect of wind velocity and dust size should be taken into account when comparing the E of different land types. [ABSTRACT FROM AUTHOR]

Background: Lithium has been a first-line choice for maintenance treatment of bipolar disorders to prevent relapse of mania and depression, but many patients do not have a response to lithium treatment., Methods: We selected subgroups from a sample of 1761 patients of Han Chinese descent with bipolar I disorder who were recruited by the Taiwan Bipolar Consortium. We assessed their response to lithium treatment using the Alda scale and performed a genomewide association study on samples from one subgroup of 294 patients with bipolar I disorder who were receiving lithium treatment. We then tested the single-nucleotide polymorphisms (SNPs) that showed the strongest association with a response to lithium for association in a replication sample of 100 patients and tested them further in a follow-up sample of 24 patients. We sequenced the exons, exon-intron boundaries, and part of the promoter of the gene encoding glutamate decarboxylase-like protein 1 (GADL1) in 94 patients who had a response to lithium and in 94 patients who did not have a response in the genomewide association sample., Results: Two SNPs in high linkage disequilibrium, rs17026688 and rs17026651, that are located in the introns of GADL1 showed the strongest associations in the genomewide association study (P=5.50×10(-37) and P=2.52×10(-37), respectively) and in the replication sample of 100 patients (P=9.19×10(-15) for each SNP). These two SNPs had a sensitivity of 93% for predicting a response to lithium and differentiated between patients with a good response and those with a poor response in the follow-up cohort. Resequencing of GADL1 revealed a novel variant, IVS8+48delG, which lies in intron 8 of the gene, is in complete linkage disequilibrium with rs17026688 and is predicted to affect splicing., Conclusions: Genetic variations in GADL1 are associated with the response to lithium maintenance treatment for bipolar I disorder in patients of Han Chinese descent. (Funded by Academia Sinica and others.).